text:
package com.amazonaws.services.pinpoint.model;

import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;

/**
 * Endpoint update request
 */
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class EndpointRequest implements Serializable, Cloneable, StructuredPojo {

    /** The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or RegistrationId). */
    private String address;
    /**
     * Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection criteria
     * when you create a segment.
     */
    private java.util.Map<String, java.util.List<String>> attributes;
    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     */
    private String channelType;
    /** The endpoint demographic attributes. */
    private EndpointDemographic demographic;
    /** The last time the endpoint was updated. Provided in ISO 8601 format. */
    private String effectiveDate;
    /**
     * The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will be set
     * to ACTIVE if the address is updated.
     */
    private String endpointStatus;
    /** The endpoint location attributes. */
    private EndpointLocation location;
    /** Custom metrics that your app reports to Amazon Pinpoint. */
    private java.util.Map<String, Double> metrics;
    /**
     * Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     * ALL – User receives all messages. NONE – User receives no messages.
     */
    private String optOut;
    /** The unique ID for the most recent request to update the endpoint. */
    private String requestId;
    /** Custom user-specific attributes that your app reports to Amazon Pinpoint. */
    private EndpointUser user;

    /**
     * The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or RegistrationId).
     *
     * @param address
     *        The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or
     *        RegistrationId).
     */

    public void setAddress(String address) {
        this.address = address;
    }

    /**
     * The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or RegistrationId).
     *
     * @return The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or
     *         RegistrationId).
     */

    public String getAddress() {
        return this.address;
    }

    /**
     * The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or RegistrationId).
     *
     * @param address
     *        The address or token of the endpoint as provided by your push provider (e.g. DeviceToken or
     *        RegistrationId).
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withAddress(String address) {
        setAddress(address);
        return this;
    }

    /**
     * Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection criteria
     * when you create a segment.
     *
     * @return Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection
     *         criteria when you create a segment.
     */

    public java.util.Map<String, java.util.List<String>> getAttributes() {
        return attributes;
    }

    /**
     * Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection criteria
     * when you create a segment.
     *
     * @param attributes
     *        Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection
     *        criteria when you create a segment.
     */

    public void setAttributes(java.util.Map<String, java.util.List<String>> attributes) {
        this.attributes = attributes;
    }

    /**
     * Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection criteria
     * when you create a segment.
     *
     * @param attributes
     *        Custom attributes that your app reports to Amazon Pinpoint. You can use these attributes as selection
     *        criteria when you create a segment.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withAttributes(java.util.Map<String, java.util.List<String>> attributes) {
        setAttributes(attributes);
        return this;
    }

    public EndpointRequest addAttributesEntry(String key, java.util.List<String> value) {
        if (null == this.attributes) {
            this.attributes = new java.util.HashMap<String, java.util.List<String>>();
        }
        if (this.attributes.containsKey(key))
            throw new IllegalArgumentException("Duplicated keys (" + key.toString() + ") are provided.");
        this.attributes.put(key, value);
        return this;
    }

    /**
     * Removes all the entries added into Attributes.
     *
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest clearAttributesEntries() {
        this.attributes = null;
        return this;
    }

    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     *
     * @param channelType
     *        The channel type.
     *
     *        Valid values: APNS, GCM
     * @see ChannelType
     */

    public void setChannelType(String channelType) {
        this.channelType = channelType;
    }

    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     *
     * @return The channel type.
     *
     *         Valid values: APNS, GCM
     * @see ChannelType
     */

    public String getChannelType() {
        return this.channelType;
    }

    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     *
     * @param channelType
     *        The channel type.
     *
     *        Valid values: APNS, GCM
     * @return Returns a reference to this object so that method calls can be chained together.
     * @see ChannelType
     */

    public EndpointRequest withChannelType(String channelType) {
        setChannelType(channelType);
        return this;
    }

    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     *
     * @param channelType
     *        The channel type.
     *
     *        Valid values: APNS, GCM
     * @see ChannelType
     */

    public void setChannelType(ChannelType channelType) {
        this.channelType = channelType.toString();
    }

    /**
     * The channel type.
     *
     * Valid values: APNS, GCM
     *
     * @param channelType
     *        The channel type.
     *
     *        Valid values: APNS, GCM
     * @return Returns a reference to this object so that method calls can be chained together.
     * @see ChannelType
     */

    public EndpointRequest withChannelType(ChannelType channelType) {
        setChannelType(channelType);
        return this;
    }

    /**
     * The endpoint demographic attributes.
     *
     * @param demographic
     *        The endpoint demographic attributes.
     */

    public void setDemographic(EndpointDemographic demographic) {
        this.demographic = demographic;
    }

    /**
     * The endpoint demographic attributes.
     *
     * @return The endpoint demographic attributes.
     */

    public EndpointDemographic getDemographic() {
        return this.demographic;
    }

    /**
     * The endpoint demographic attributes.
     *
     * @param demographic
     *        The endpoint demographic attributes.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withDemographic(EndpointDemographic demographic) {
        setDemographic(demographic);
        return this;
    }

    /**
     * The last time the endpoint was updated. Provided in ISO 8601 format.
     *
     * @param effectiveDate
     *        The last time the endpoint was updated. Provided in ISO 8601 format.
     */

    public void setEffectiveDate(String effectiveDate) {
        this.effectiveDate = effectiveDate;
    }

    /**
     * The last time the endpoint was updated. Provided in ISO 8601 format.
     *
     * @return The last time the endpoint was updated. Provided in ISO 8601 format.
     */

    public String getEffectiveDate() {
        return this.effectiveDate;
    }

    /**
     * The last time the endpoint was updated. Provided in ISO 8601 format.
     *
     * @param effectiveDate
     *        The last time the endpoint was updated. Provided in ISO 8601 format.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withEffectiveDate(String effectiveDate) {
        setEffectiveDate(effectiveDate);
        return this;
    }

    /**
     * The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will be set
     * to ACTIVE if the address is updated.
     *
     * @param endpointStatus
     *        The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will
     *        be set to ACTIVE if the address is updated.
     */

    public void setEndpointStatus(String endpointStatus) {
        this.endpointStatus = endpointStatus;
    }

    /**
     * The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will be set
     * to ACTIVE if the address is updated.
     *
     * @return The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will
     *         be set to ACTIVE if the address is updated.
     */

    public String getEndpointStatus() {
        return this.endpointStatus;
    }

    /**
     * The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will be set
     * to ACTIVE if the address is updated.
     *
     * @param endpointStatus
     *        The endpoint status. Can be either ACTIVE or INACTIVE. Will be set to INACTIVE if a delivery fails. Will
     *        be set to ACTIVE if the address is updated.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withEndpointStatus(String endpointStatus) {
        setEndpointStatus(endpointStatus);
        return this;
    }

    /**
     * The endpoint location attributes.
     *
     * @param location
     *        The endpoint location attributes.
     */

    public void setLocation(EndpointLocation location) {
        this.location = location;
    }

    /**
     * The endpoint location attributes.
     *
     * @return The endpoint location attributes.
     */

    public EndpointLocation getLocation() {
        return this.location;
    }

    /**
     * The endpoint location attributes.
     *
     * @param location
     *        The endpoint location attributes.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withLocation(EndpointLocation location) {
        setLocation(location);
        return this;
    }

    /**
     * Custom metrics that your app reports to Amazon Pinpoint.
     *
     * @return Custom metrics that your app reports to Amazon Pinpoint.
     */

    public java.util.Map<String, Double> getMetrics() {
        return metrics;
    }

    /**
     * Custom metrics that your app reports to Amazon Pinpoint.
     *
     * @param metrics
     *        Custom metrics that your app reports to Amazon Pinpoint.
     */

    public void setMetrics(java.util.Map<String, Double> metrics) {
        this.metrics = metrics;
    }

    /**
     * Custom metrics that your app reports to Amazon Pinpoint.
     *
     * @param metrics
     *        Custom metrics that your app reports to Amazon Pinpoint.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withMetrics(java.util.Map<String, Double> metrics) {
        setMetrics(metrics);
        return this;
    }

    public EndpointRequest addMetricsEntry(String key, Double value) {
        if (null == this.metrics) {
            this.metrics = new java.util.HashMap<String, Double>();
        }
        if (this.metrics.containsKey(key))
            throw new IllegalArgumentException("Duplicated keys (" + key.toString() + ") are provided.");
        this.metrics.put(key, value);
        return this;
    }

    /**
     * Removes all the entries added into Metrics.
     *
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest clearMetricsEntries() {
        this.metrics = null;
        return this;
    }

    /**
     * Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     * ALL – User receives all messages. NONE – User receives no messages.
     *
     * @param optOut
     *        Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     *        ALL – User receives all messages. NONE – User receives no messages.
     */

    public void setOptOut(String optOut) {
        this.optOut = optOut;
    }

    /**
     * Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     * ALL – User receives all messages. NONE – User receives no messages.
     *
     * @return Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     *         ALL – User receives all messages. NONE – User receives no messages.
     */

    public String getOptOut() {
        return this.optOut;
    }

    /**
     * Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     * ALL – User receives all messages. NONE – User receives no messages.
     *
     * @param optOut
     *        Indicates whether a user has opted out of receiving messages with one of the following values:
     *
     *        ALL – User receives all messages. NONE – User receives no messages.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withOptOut(String optOut) {
        setOptOut(optOut);
        return this;
    }

    /**
     * The unique ID for the most recent request to update the endpoint.
     *
     * @param requestId
     *        The unique ID for the most recent request to update the endpoint.
     */

    public void setRequestId(String requestId) {
        this.requestId = requestId;
    }

    /**
     * The unique ID for the most recent request to update the endpoint.
     *
     * @return The unique ID for the most recent request to update the endpoint.
     */

    public String getRequestId() {
        return this.requestId;
    }

    /**
     * The unique ID for the most recent request to update the endpoint.
     *
     * @param requestId
     *        The unique ID for the most recent request to update the endpoint.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withRequestId(String requestId) {
        setRequestId(requestId);
        return this;
    }

    /**
     * Custom user-specific attributes that your app reports to Amazon Pinpoint.
     *
     * @param user
     *        Custom user-specific attributes that your app reports to Amazon Pinpoint.
     */

    public void setUser(EndpointUser user) {
        this.user = user;
    }

    /**
     * Custom user-specific attributes that your app reports to Amazon Pinpoint.
     *
     * @return Custom user-specific attributes that your app reports to Amazon Pinpoint.
     */

    public EndpointUser getUser() {
        return this.user;
    }

    /**
     * Custom user-specific attributes that your app reports to Amazon Pinpoint.
     *
     * @param user
     *        Custom user-specific attributes that your app reports to Amazon Pinpoint.
     * @return Returns a reference to this object so that method calls can be chained together.
     */

    public EndpointRequest withUser(EndpointUser user) {
        setUser(user);
        return this;
    }

    /**
     * Returns a string representation of this object; useful for testing and debugging.
     *
     * @return A string representation of this object.
     *
     * @see java.lang.Object#toString()
     */
    @Override
    public String toString() {
        StringBuilder sb = new StringBuilder();
        sb.append("{");
        if (getAddress() != null)
            sb.append("Address: ").append(getAddress()).append(",");
        if (getAttributes() != null)
            sb.append("Attributes: ").append(getAttributes()).append(",");
        if (getChannelType() != null)
            sb.append("ChannelType: ").append(getChannelType()).append(",");
        if (getDemographic() != null)
            sb.append("Demographic: ").append(getDemographic()).append(",");
        if (getEffectiveDate() != null)
            sb.append("EffectiveDate: ").append(getEffectiveDate()).append(",");
        if (getEndpointStatus() != null)
            sb.append("EndpointStatus: ").append(getEndpointStatus()).append(",");
        if (getLocation() != null)
            sb.append("Location: ").append(getLocation()).append(",");
        if (getMetrics() != null)
            sb.append("Metrics: ").append(getMetrics()).append(",");
        if (getOptOut() != null)
            sb.append("OptOut: ").append(getOptOut()).append(",");
        if (getRequestId() != null)
            sb.append("RequestId: ").append(getRequestId()).append(",");
        if (getUser() != null)
            sb.append("User: ").append(getUser());
        sb.append("}");
        return sb.toString();
    }

    @Override
    public boolean equals(Object obj) {
        if (this == obj)
            return true;
        if (obj == null)
            return false;

        if (obj instanceof EndpointRequest == false)
            return false;
        EndpointRequest other = (EndpointRequest) obj;
        if (other.getAddress() == null ^ this.getAddress() == null)
            return false;
        if (other.getAddress() != null && other.getAddress().equals(this.getAddress()) == false)
            return false;
        if (other.getAttributes() == null ^ this.getAttributes() == null)
            return false;
        if (other.getAttributes() != null && other.getAttributes().equals(this.getAttributes()) == false)
            return false;
        if (other.getChannelType() == null ^ this.getChannelType() == null)
            return false;
        if (other.getChannelType() != null && other.getChannelType().equals(this.getChannelType()) == false)
            return false;
        if (other.getDemographic() == null ^ this.getDemographic() == null)
            return false;
        if (other.getDemographic() != null && other.getDemographic().equals(this.getDemographic()) == false)
            return false;
        if (other.getEffectiveDate() == null ^ this.getEffectiveDate() == null)
            return false;
        if (other.getEffectiveDate() != null && other.getEffectiveDate().equals(this.getEffectiveDate()) == false)
            return false;
        if (other.getEndpointStatus() == null ^ this.getEndpointStatus() == null)
            return false;
        if (other.getEndpointStatus() != null && other.getEndpointStatus().equals(this.getEndpointStatus()) == false)
            return false;
        if (other.getLocation() == null ^ this.getLocation() == null)
            return false;
        if (other.getLocation() != null && other.getLocation().equals(this.getLocation()) == false)
            return false;
        if (other.getMetrics() == null ^ this.getMetrics() == null)
            return false;
        if (other.getMetrics() != null && other.getMetrics().equals(this.getMetrics()) == false)
            return false;
        if (other.getOptOut() == null ^ this.getOptOut() == null)
            return false;
        if (other.getOptOut() != null && other.getOptOut().equals(this.getOptOut()) == false)
            return false;
        if (other.getRequestId() == null ^ this.getRequestId() == null)
            return false;
        if (other.getRequestId() != null && other.getRequestId().equals(this.getRequestId()) == false)
            return false;
        if (other.getUser() == null ^ this.getUser() == null)
            return false;
        if (other.getUser() != null && other.getUser().equals(this.getUser()) == false)
            return false;
        return true;
    }

    @Override
    public int hashCode() {
        final int prime = 31;
        int hashCode = 1;

        hashCode = prime * hashCode + ((getAddress() == null) ? 0 : getAddress().hashCode());
        hashCode = prime * hashCode + ((getAttributes() == null) ? 0 : getAttributes().hashCode());
        hashCode = prime * hashCode + ((getChannelType() == null) ? 0 : getChannelType().hashCode());
        hashCode = prime * hashCode + ((getDemographic() == null) ? 0 : getDemographic().hashCode());
        hashCode = prime * hashCode + ((getEffectiveDate() == null) ? 0 : getEffectiveDate().hashCode());
        hashCode = prime * hashCode + ((getEndpointStatus() == null) ? 0 : getEndpointStatus().hashCode());
        hashCode = prime * hashCode + ((getLocation() == null) ? 0 : getLocation().hashCode());
        hashCode = prime * hashCode + ((getMetrics() == null) ? 0 : getMetrics().hashCode());
        hashCode = prime * hashCode + ((getOptOut() == null) ? 0 : getOptOut().hashCode());
        hashCode = prime * hashCode + ((getRequestId() == null) ? 0 : getRequestId().hashCode());
        hashCode = prime * hashCode + ((getUser() == null) ? 0 : getUser().hashCode());
        return hashCode;
    }

    @Override
    public EndpointRequest clone() {
        try {
            return (EndpointRequest) super.clone();
        } catch (CloneNotSupportedException e) {
            throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e);
        }
    }

    @com.amazonaws.annotation.SdkInternalApi
    @Override
    public void marshall(ProtocolMarshaller protocolMarshaller) {
        com.amazonaws.services.pinpoint.model.transform.EndpointRequestMarshaller.getInstance().marshall(this, protocolMarshaller);
    }
}


text:
Tag Archives: President Trump
January 17, 2021 UncategorizedAmazon, censorship, Donald Trump, Facebook, Freedom of Speech, Freedom of the Press, Google, Patrick Henry, President Trump, Twitterwaynetdowdy
Photo by Mathias P.R. Reding on Pexels.com
Politically Incorrect I may be, but I have a right in America to be however I choose, regardless of what public opinion may dictate as proper or improper, offensive to a particular group or party, providing I do not physically harm someone; or what supports their agenda and makes me a dedicated supporter, worthy of praise.
To be clear, at one time in my life, I may have wanted to burn down the White House, but not anymore. I prefer to live in peace and to treat others the way I want to be treated, no matter who they are or what their occupation is in life. We are all in this together.
I do not support and was saddened to see what happened at the White House on January 6, 2021; nor the events that led to the attack, which, in my opinion, may be legally attributed to outgoing President Donald Trump, based upon what he said to the crowd gathered near the White House before the attack began. (I will not go into all of that because only a caveman wouldn't know what I am referring to and cavemen can't read anyway.)
As someone who has been censored, I am censor-sensitive and feel a lot like Patrick Henry, whom I have written about in previous blogs, but I am not willing to die to defend your right (or President Trump's) right to say anything. That is just asking a little bit much: I will speak out, though, and fight to prevent our words from being silenced by censors.
On one level, nothing going on in the political arena matters to me, but I do feel obligated to express my opinion and view of what I see happening.
What I don't feel is right is all the politically driven censorship by Facebook and Twitter, which I am sure was influenced by the recent Congressional actions against Facebook, Amazon, Google, and other technology companies dominating the market.
More recently, Facebook removed ads for guns and weapons because of more political interference. Click Here
The new controlling party doesn't like guns, so how strange that Facebook suddenly makes a decision to stop advertising the sale of items frowned upon by the Democrats in particular.
At what point does the First Amendment of the United States Constitution protect Freedom of Speech? With today's political environment, it doesn't in most circumstances, as can be shown by Facebook and Twitter shutting down President Trump's accounts.
Though private companies and not really protected under the provisions of the First Amendment, I see the situation as the beginning of the disappearance of another of the Writings on the Wall. To understand that statement, read Animal Farm by George Orwell (buy from this link and I earn a commission).
Most people in modern society fall within the Sheep category written about in Animal Farm, who supported and could not accept that the controlling party (Pigs) were removing the Writings on the Wall; illustrative of the disappearance of what was voted on during the revolution (animals taking over the farm and running off the farmers who killed and used animals and their parts). Also reflective of what would be the Constitution or controlling documents agreed upon by the Animals/People.
On Facebook, I posted a link to an article written on April 2, 2005, Patrick Henry's take on American values and wrote the following:
Would Patrick Henry have defended President Trump's right to say all of the controversial statements and claims? As a writer and one who has written many words that some found offensive and decided to not follow my blog because I supported issues different from their beliefs, I think of who will be the one to decide what you may read?
The power of the media was shown when its false allegations of the Spanish attacking one of the American ships started the Spanish-American war (see below for link to History).
If Freedom of Speech does not matter, go to China and Russia where the governments exhibit total control and have a history of making people disappear who speak out against the establishments.
Is the news media responsible for what happened at the White House, because the news outlets provided the platform for the inciteful speeches made by President Trump? No.
Some politicians are wanting to hold Facebook, Twitter, and other private companies responsible for hateful content that leads to violence, so what it the difference? There isn't.
Starting with control over the private sector is only the start for the erosion of America's Freedom of Speech protections.
Next in line of attack will be the news media outlets or reporters who report on issues that result in violence or political upheaval.
Real Fake News helped start the Spanish American War in 1898 by falsely reporting the Spanish attacked the USS Maine in Cuba. A lie that fed the mass frenzy to attack the Spanish and to defend the Nation!
More Fake News led to the attack on the Capitol when the Commander in Chief encouraged his followers to take a stand, promising to be there with them when they did. He lied.
Oh, Sheep, where does it end?
(For more evidence of the political pressure involved in censorship that threatens the information technology of today, read Capitol Hill Attack Could End Section 230 As We Know It by Daniel Howley·Technology Editor, Wednesday, January 13, 2021.
The problem arises when a particular group of people (controlling party) will determine the information available for people to read or not read, much as what goes on in communist countries.)
Protests Gone Viral by Wayne T. Dowdy
May 31, 2020 Current Affairs, UncategorizedAssociate Press, Atlanta Riots, conspiracy, LA Riots, Michelle Alexander, President Trump, Protests, Riots, terrorism, The Marshal Project, The New Jim Crow, Wall Street Journal, Wayne T. Dowdywaynetdowdy
Photo by Vital1na on Pexels.com
Racism lives and continues to thrive in America and around the world. Police brutality in Minneapolis, Minnesota that resulted in the death of an African-American man named, George Floyd, on May 25, 2020, sparked riots across the United States and caused disruptions around the world.
US cities assess protest damage, await another day of unrest by By TIM SULLIVAN and MATT SEDENSKY
Reading or watching news isn't my favorite past time and it took all of the chaos going on in my hometown of Atlanta, Georgia to draw my attention to what is going on in many American cities.
In researching for this blog, I read what one source stated that I know most people will not see the seriousness of one word used in the following statement "terrorist":
"Officials moved to restore order. Governors called in the National Guard, mayors extended curfews for a third night in some cities and President Trump said he would designate Antifa as a terrorist organization."
The Wall Street Journal, Officials Look to Restore Order After Riots
Though I am not an attorney and do not intend this to be legal advice by any standard, I am of the opinion that under American law, terrorism and domestic terrorism carry strict penalties, and when coupled with conspiracy laws, the use of that one word, when tied into legal terminology few can comprehend, many people who are protesting and are in the group of those tied to the violent offenses, may be charged accomplices.
If you don't believe me about the severe criminal penalties for terrorist-related crimes, read what the law states in 18 U.S. Code CHAPTER 113B—TERRORISM
Two of my former blogs also relate to conspiracy laws and how easy men and women may end up spending the rest of their lives in prison. The men I wrote about got lucky when former President Obama commuted their life sentences: https://straightfromthepen.com/2016/01/05/freedom-for-a-friend/ and https://straightfromthepen.com/2016/08/09/freedom-for-another-friend/
My hope is that the protests do result in needed changes to eliminate racism and police brutality in America and abroad. The reality is that the stereotyping will continue for decades more to follow, because there will always be those who refuse to move away from the past and see each person as they are, rather than by some external element beyond control.
The sad part for me is in knowing that innocent people always get caught in the crosshairs of anger and hate and suffer dire consequences for what others have done. In this case, that will include the innocent protesters who get labeled as terrorists and go to prison for the rest of their lives for only doing what they felt they must do to take a stand against injustice.
April 23, 2018 Current Affairs, Politics, reentry, Returning Citizen Success StoriesAdams County; BOP, Brandon Sample, CCA, CoreCivic, halfway houses; Attorney General, Jeff Sessions, Politics, President Trump, proclamation, Sally Q. Yates, Shon Hopwood, storms, Tara Simmons.waynetdowdy
Storms ravage the United States: tornados, thunder storms, snow and ice storms, in April, along with the political and technological storms that drive the progression or digression of the nation. Storms fuel change: Cruise Missiles that bombed Syrian chemical weapon sites, were launched with the intent to create change, to deter a tyrant from using chemical weapons on Syrian citizens. Advancement in technology drove the Cruise Missiles.
A political storm drove the decision to attack another country. Maybe a different political storm, driven by humanitarian concerns, will form to attack policies that fuel mass incarceration in America.
CHANGES: During the early seventies, I loved listening to "Changes" by Black Sabbath (album title: "4"), and "I'd Love to Change the World" by Ten Years After. Throughout the decades of my life, I've witnessed numerous changes. Things once viewed as fantasy become reality. For instance, in the sixties cartoon, The Jetsons, phones used to communicate became cellphones of today, with technology that permitted users to see the person on the other end of the line, like Skype.
STORMS: Natural storm patterns changed, as have the nature of storms that fueled technological changes; advancements in medicine and technology used in the treatment of illnesses that extended life expectancy, created other storms: World population explosion, food shortages, soaring health care cost and big business profit increases that often thrive on the misery of others. Private Prison companies fall within the latter category.
One of the largest private prison companies is CoreCivic, formerly Correctional Corporation of America (CCA). Investors filed a lawsuit against the corporation because CCA had fraudulently claimed to provide a high level of quality services that assured satisfied customers, boasting about its contracts with the United States Department of Justice.
Former BOP Director Harley G. Lappin is named in the securities fraud lawsuit. Him and J. Michael Quinlan left the BOP under unfavorable circumstances to work for CCA. (Read "The Truth About Incarceration, Part II" for more on the issue.)
SALLY Q. YATES: And then came the "Yates Memorandum." Ms. Yates is the former Assistant United States Attorney, who planned to phase out private prison contracts because of inferior services and numerous quality and safety issues. One CCA prison of concern, was Adams County Correctional Center, where a riot erupted over poor conditions that resulted in the death of a prison guard and several injuries to staff and inmates, and over one million dollars in damages.
The Investors filed suit and claimed to have lost $1.2 million when their "159,000" shares of CCA/CoreCivic stock dropped because of conduct covered in the lawsuit; however, since then, President Trump and Attorney General, Jefferson Beauregard Sessions III, revived the stock value.
As I've previously written, CCA and GEO Group's stock value SOARED within a week after the last Presidential Election. When AG Sessions rescinded the Yates Memorandum and agreed to maintain private prison contracts, including the one with Adams County Correctional Center, it was back to business as usual.
I wonder if that decision put money and CoreCivic stock into the pockets and portfolios of AG Sessions and President Trump?
PERSONAL STORMS: The calm storms of my life continue as I fight for freedom and refuse to give up until that day comes, or when my time expires in this thing called life. Whatever the case may be, I will not give up. If life exists after bodily functions expire, I'll fight from the other side in my pursuit of justice.
I have not won the lottery, at least, not yet. On April 5th I received a March 29, 2018, denial of my Administrative Remedy Request (BP-10) in reference to my halfway house placement date. The author essentially stated that the Warden properly responded, and then noted that the halfway house budget led to placement terms being reduced to 120-days or less.
In my BP-11, I pointed out that the Regional Director failed to address my abuse of discretion claims against the Warden, Residential Reentry Manager, and BOP Director. I also shown that 300-days in a halfway house, at $72.00 per day, would cost $21,600, but if I failed to receive enough time in a halfway house to successfully reintegrate into society and became a recidivist, it would cost much more.
If I fail on supervised release and get the full 5-years revoked, with the cost of my incarceration soaring above $100,000 per year due to a medication I take for a lung condition, that'd cost over $500,000. If I committed another federal crime, that'd be real expensive; however, I did stress that that is not on my agenda. My plan involves becoming a positive success story upon release.
The day after the BP-10 Response was dated, President Trump issued a Presidential Proclamation.
PRESIDENTIAL PROCLAMATION OF SECOND CHANCES: On March 30, 2018, President Trump stated, in part, "I am committed to advancing reform efforts to prevent crime, improve reentry, and reduce recidivism. I expressed this commitment in my 2018 State of the Union Address and reinforced it by signing an Executive Order to reinvigorate the 'Federal Interagency Council on Crime Prevention and Improving Reentry.' In the spirit of these efforts, I call on Federal, State, and local prison systems to implement evidence-based programs that will provide prisoners with the skills and preparation they need to succeed in society. This includes programs focused on mentorship and treatment for drug addiction and mental health issues, in addition to job training.
"This month, we celebrate those who have exited the prison system and successfully reentered society. We encourage expanded opportunities for those who have worked to overcome bad decisions earlier in life and emphasize our belief in second chances for all who are willing to work hard to turn their lives around.
"NOW, THEREFORE, I, DONALD J. TRUMP, President of the United States of America, by virtue of the authority vested in me by the Constitution and the laws of the United States, do hereby proclaim April 2018 as Second Chance Month. I call on all Americans to commemorate this month with events and activities that raise public awareness about preventing crime and providing those who have completed their sentences with an opportunity for an honest second chance.
IN WITNESS WHEREOF, I have hereunto set my hand this thirtieth day of March, in the year of our Lord, two thousand eighteen, and of the Independence of the United States of America, the two hundred and forty-second.
"President Donald J. Trump Proclaims April 2018 as Second Chance Month," http://www.whitehouse.gov, March 30, 2018.
AFTER PRISON SUCCESS STORIES: Brandon Sample, Shon Hopwood, and Tara Simmons are three of many ex-offenders who became success stories after their release from prison. All three entered a field many people said could not be done: Brandon Sample became a practicing attorney; Shon Hopwood an attorney and then a Professor of Law at Georgetown Law University, and Tara Simmons took her fight to the Washington State Supreme Court to become an attorney.
Justice Mary Yu wrote in her opinion that "[S]immons began 'meaningful treatment' while in prison and 'changed her life to a degree that can only be deemed remarkable, both in terms of the efforts she had put forth and the positive results she has achieved.'"
Justice Yu also gave props to Shon Hopwood, who represented Simmons. "'Both Hopwood and Simmons are living examples of a person's ability to change if he or she has the will and opportunity to do so.'"
Prison Law & Prison Education News Services, 04/13/18, (email: news@prisonlawblog.com), quoting from Seatletimes.com and Prison Legal News.
The Washington Supreme Court ruled that the Washington State Bar Association should allow her to take the bar exam, another victory for Mr. Hopwood and Real Justice in America.
I know of numerous others who were released and become success stories in their own right, especially my peers who are members of Twelve Step programs, as well as several former UNICOR employees who got out and became successful in the world of work.
UNICOR: In 1936, Congress created the Federal Prison Industries, Inc., trade name UNICOR (for UNIque CORporation), to teach inmates marketable job skills. UNICOR is supposed to be a Work Program for Inmates, not a conglomerate to increase earnings that allows executive staff to give themselves bonuses: Some current practices border on exploitation of prisoners.
(A 04/10/18, USA TODAY article, "Federal Prison Bonuses Stir Outrage," included bonuses for an array of federal prison officials, including wardens who shave dollars from prison budgets at the expense of prisoners.)
Statistically, UNICOR does reduce recidivism, so it is a good program within the BOP that allows inmate employees to earn enough to buy essentials for survival in prison. But in recent years, inmate pay has dwindled to allow the organization to increase its profit margins. I made more money per day in the early '90s ($10.80) than I do today ($10.51). So much for the show of gratitude by my employers for my dedicated years of service, huh?
Sometimes I feel like the old work horse in George Orwell's, Animal Farm, who the Pigs hauled off to the glue factory after having served his purpose. (Well, maybe not that bad. They are keeping me around to mentor others and to pass on my accumulated knowledge before leaving.)
PROGRAMS: The BOP does have some beneficial programs taught by inmates and staff alike. Recidawareness is one such program, founded by a federal prisoner, Frank C., who devotes himself toward helping others through a curriculum that combines spiritual and practical principles. The program helps participants focus on interpersonal aspects of their lives and the improvement of decision-making skills to assist them in changing behavior to avoid becoming a recidivist.
The Psychology department also offers programs that, if practiced, assists participants at living their lives in a different manner by teaching them to make better decisions (e.g. Cognitive Thinking, Anger Management, Health & Wellness, Job Application & Resume Writing, Non-Residential Drug Treatment Program, Residential Drug Abuse Treatment Program). However, even though Narcotics Anonymous and Alcoholics Anonymous are suggested programs for graduates of the drug programs, and are listed in the Psychology Services Program Statement, to my knowledge, most institutions do not focus on making AA/NA meetings available to inmates.
CO-OCCURRING (DUAL ) DIAGNOSIS: In "No Sympathy" that you can read on this blogspot, I reference a 12/02/02, USA TODAY article, "Study: Treat Addicts Mental Illness." Studies show that treating substance abuse and underlying mental disorders help people to not "reoffend," and thus decrease recidivism rates.
BOP policy remains the same (ONE (1) institution offers treatment for those with dual disorders.)
FOCAL POINTS: The current focus in prison reform appears to be on reentry initiatives. Focusing on recidivism makes sense, since we fuel the system we claim to hate, when we get out and return to make the system grow bigger and stronger.
Now if Congress or the President will implement laws or policies to make prison administrators accountable for failure to comply with Congressional directives, things will change. Until then, corrupt politicians and prison officials will continue to accept bribes from private prison executives and continue to feed mass incarceration in America.
Visit http://www.straightfromthepen.com and https://www.smashwords.com/profile/view/WayneMrDowdy for other writings from Wayne T. Dowdy. In April 2018, Murder Slim Press published his short story, "Guns, Drugs & Thugs" in THE SAVAGE KICK Magazine.

redpajama_set_name: RedPajamaCommonCrawl


The Bruno Out-Rider allows no power scooter or power chair to come between you and your truck. After all, this rugged, reliable lift makes the transition of your mobility device in and out of your truck bed as easy as the push of a button. Boasting vehicle-specific bases and device-specific docking, the Out-Rider installs in your truck's bed and automatically lifts, lowers and rotates your mobility device, making vehicle transfers quick and efficient.


Advocates for the application of technology in U. S. schools would like teachers to move beyond the use of computers for simple tasks such as drill and practice to new applications like the use of multimedia, and as a research and problem solving tool. This emphasis on integration has not yielded adequate achievement results because many teachers do not frequently utilize technology for instruction. This is because teachers' ability to integrate computer technology effectively depends on their own knowledge about technology and the access they have to technology. The lack of knowledge has resulted in computer use most often in computer classes and not in core academic subjects such as math and science. This study analyzed teacher access to technology and its impact on technology integration in mathematics instruction in urban public secondary classrooms. The findings from this research highlighted the need for continued dialogue on this topic by refocusing attention on technology integration in urban public mathematics classrooms.
The study used a causal-comparative research design. In this design the researcher determines the cause or the reason for existing differences in groups or individuals. In a causal-comparative research the participants are already in groups prior to the study and therefore they are not subject to manipulation.
Kruskal-Wallis one-way analysis of variance was used to compare the two sample means for differences and the Mann-Whitney U-test was used to determine statistical significance using an alpha level of 0.05. Spearman rho correlation was used to determine the magnitude and direction of any relationship.
Data for urban public secondary mathematics teachers was retrieved from National Center for Educational Statistics, Schools and Staffing Survey (SASS) questionnaires. Variables that represented teacher experience, professional development and availability of computer technology were extracted from the SASS datasets.
Teacher experience had no effect on technology integration in urban public secondary classrooms. There was no difference between novice, experienced and veteran teachers and technology integration in mathematics instruction. The results for professional development indicated that teachers who participated in professional development showed significantly different (p≥ 4.77) use of computer technology for instruction and instructional activity (p≥ 5.91) in mathematics. The number of computers in a classroom significantly influenced (p≥ 37.28) technology integration in mathematics instruction in urban public secondary classrooms. Teachers who have more computers in their classroom integrated technology more frequently in mathematics instruction.
keywords: technology integration, instruction, public schools, education, mathematics instruction.
P. Harvey-Buschel (2010) TECHNOLOGY INTEGRATION: A QUANTITATIVE EXAMINATION OF FACTORS THAT IMPACT TECHNOLOGY INTEGRATION IN URBAN PUBLIC SECONDARY MATHEMATICS CLASSROOMS, INTED2010 Proceedings, pp. 1927-1937.


text:
Steven Wright known as Steven
Faculty of Creative Industries
Senior Lecturer In Fashion Design
steven.wright@southwales.ac.uk
CAD406
Cardiff - Atrium
B. Des (Fashion Design)
MA Hons (Art History and Curatorship)
Steven has been an educator working in Higher Education in Australia and the UK since 2004 working across Fashion and visual art programs. As Course Leader his main focus in the design and delivery of future focused program of study that gives students the skills, attributes and industry exposure to allow them to flourish.
Steven has run his own label "Corr Blimey" since 2001, along with working in the fashion exhibitions, modelling and event management sector. His work is informed by engagement is design process, sustainability and Human Centered Design. Steven has been asked to speak around the world and has presented through various media outlets including ITV, BBC and the ABC.
2016 – Present: Course Leader (Fashion Design) University of South Wales
2001- Present: Designer, Corr Blimey
2013- 2016: Course coordinator Bachelor of Design (Fashion Design) Canberra Institute of Technology
2013 – 2016: Festival Producer, FASHFEST
2014 – 2016: Fashion Director, HAUS Models
2004 – 2013: Senior Lecturer in Fashion Canberra Institute of Technology
2005-2007: Fashion Editor, LIP Magazine
2002-2007: Costume Designer, Various
2016 (August-November) "Sketching Process", Tom Skeehan, Contributing Designer
2015 (13 November) "Furnished", School of Art, Australian National University, Invited guest lecture
2015 (15 October) "Design and Collaboration", School of Art, Australian National University, Invited guest lecture 2015 (15 July) "Japanese Fashion and Contemporary Art", School of Critical Enquiry, Australian National University, Canberra. Invited guest lecture
2015 (1 July) "Iris", Canberra International Film Festival, Invited Key Note Speaker
2015 (15 April) "Multiples and Productions", School of Art, Australian National University, External Assessor
2015 (20 March) "WHO IS…", Collaborative Project with Designcraft and Walter Knoll, Project Manager
2014 (5 November) "Dior and I: The connection between Pressure and Innovation", Canberra International Film Festival, Invited Key Note Speaker
2013 (8 November) "Solving Problems Through Sustainability", TFIA Industry Magazine, Fabric Contributing author
2013-ongoing "The Fashion Studies Book", (Routledge, London and New York, in press), Contributing author 2013 (9 June) "How to teach Sustainable Design", Design Industry of Australia , 5X5 talk series, Canberra, Invited Key note Speaker
2013 (26 April) "Diana Vreeland – Fashion industry Q+A", National Gallery of Australia, Fashion and Film, Invited Key note Speaker
2012 (31 October): "The connection between fashion and contemporary art", School of Critical Enquiry, Australian National University, Canberra. Invited guest lecture.
2012 (18 July): "Commune" Sustainability Conference, School of Fashion and Textiles, Royal Melbourne Institute of Technology University, Melbourne. Workshop leader and key note speaker. Conferences
2012 (9 August): "Designing Australian Fashion Futures", Australian Fashion Research Network Forum, National Library of Australia, Canberra. Editorial Assistant and Master of Ceremonies.
2011 (19-26 June): "Creative Sustainability", German government sustainable design conference. German Federal Government-sponsored Australian representative.
2017:Cardiff Fashion Week. Producer
2015: Design Canberra: Design Hub. Producer.
2014: National Portrait Gallery: Winter Festival – Fire and Ice. Fashion Coordinator.
2012: Fashionably Early: Designing Australian Fashion Futures. Gallery of Australian Design, Canberra. Producer.
2010: National Botanic Gardens 40th Birthday Garden Party, National Botanic Gardens, Canberra. Fashion Parade Project Manager.
2009: Constructing Identity Exhibition and Event, National Portrait Gallery, Canberra. Collaborative curator and Project Manager.
2008: VIVID National Photography Festival, National Archives of Australia, Canberra. Collaborative curator and event manager.
2006: Forecast, Experimental Fashion and Dance event, National Gallery of Australia, Canberra. Production Manager.
2015 – 2016: QIC – Canberra Centre, Style Consultant
2014: Design Institute of Australia (ACT) Fashion Consultant
2009-2016: Steven Wright Consultancy (Fashion SME consultancy)
@Dress_Wright


Old books and their former owners...now there's a story you could write!
So...here's an idea for a book YOU could write.
Come to the Book Sale in April, find a bunch of old books that are signed by a previous owner/reader, search online for information on that person and share all in your new book. It's kind of a spin on genealogy and readership.
Pictured below is Our Girls, the 1890 edition owned by Nellie C Roach. Gotta wonder the power these stories and poems might had on that little girl.


This year in July we are planning, with 6 other members of the Association Ubuntu from France, to go and spend some 3 weeks or so in Bwira, in order to visit our partners and their families, the women from Abihuje (= together, in Kinyarwanda). The first action we're doing is that Ronny and I will be running 10 miles on the 27th April 2014 in the heart of Edinburgh! Are you prepared to be with us on this (but from the comfort of your seat…..)? Because the Association Ubuntu is a charity recognised in France but not in the UK, I can't use fund-raising websites such as "Just Giving" but would still welcome donations… or just a message of encouragement! Please use the form below to send us your messages.
we also simply look forward to meeting the people from Bwira, because the Association Ubuntu puts an emphasis on relationships and collaboration. We don't want to be impersonal, unknown people far away, seemingly with power and money, we want to break prejudices, learn from each other and develop ideas and projects together.
Comments, questions or encouragement message!


text:
October 6, 2021 @ 4:57pm » Zach Koons
Chris Paul Addresses The Situation With Deandre Ayton
News broke earlier this week that the Phoenix Suns and former No. 1 overall pick Deandre Ayton have reached somewhat of an impasse in contract negotiations, casting doubt on the big man's long-term future with the franchise. ESPN's Adrian Wojnarowski revealed in a report Tuesday that the disconnect comes from the Suns' reluctance to offer […]
July 31, 2021 @ 6:12pm » Chris Rosvoglou
NBA Insider Has Telling Comment On Chris Paul's Basketball Future
Chris Paul could opt out of his $44.2 million option for the 2021-22 season, but that doesn't mean he won't return to the Phoenix Suns. According to Bleacher Report's Jake Fischer, the Suns are expected to sign Paul to a three-year contract worth roughly $90 million. The exact terms of this contract aren't available since […]
July 27, 2021 @ 7:25pm » Zach Koons
Look: Chris Paul Sends Message To Suns Fans
The Phoenix Suns made a miraculous run to the NBA Finals this past season in their first trip to the playoffs in over a decade. Praise has rightfully been given to head coach Monty Williams and rising young talents Devin Booker and Deandre Ayton, but a lot of the credit for the remarkable year goes […]
July 21, 2021 @ 2:53pm » Dan Lyons
NBA World Reacts To Big Lakers Offseason Rumors
The Los Angeles Lakers know that their championship window with LeBron James and Anthony Davis will shut sooner than later. The team had a pretty glaring need for better point guard play this past season, and will reportedly have their eyes on some huge prizes at that position this summer. Obviously the biggest name who […]
July 21, 2021 @ 2:01pm » Matt Audilet
Magic Johnson Has 1 Star Player In Mind For The Lakers
The Los Angeles Lakers were served a first-round exit at the hands of the Phoenix Suns earlier this postseason. And with both LeBron James and Anthony Davis battling injury issues, the 2020 NBA champions certainly weren't looking capable of making a title-defending run. This loss for LA marked the start of an incredible run for […]
July 21, 2021 @ 1:09pm » Tzvi Machlin
Los Angeles Lakers Reportedly Interested In Signing Veteran Point Guard
After suffering an early playoff elimination, the Los Angeles Lakers may be retooling in the offseason. And Chris Paul could be someone the Lakers try to recruit. According to Marc J. Spears of The Undefeated, the Lakers are interested in signing "an elite veteran point guard" this offseason. Chris Paul, who has a player option […]
July 21, 2021 @ 11:43am » Chris Rosvoglou
Chris Paul Sends Clear Message About His Basketball Future
Chris Paul came so close to capturing his first NBA title. Unfortunately for the veteran point guard, the Phoenix Suns were unable to take care of business after claiming an early 2-0 lead over the Milwaukee Bucks. Following the heartbreaking loss on Tuesday night, Paul spoke to reporters about this missed opportunity. Unsurprisingly, this loss […]
July 20, 2021 @ 10:37pm » Matt Audilet
Stat Shows Just How Bad Bucks Were In 2nd Quarter vs. Suns Tonight
With the energy of tonight's electric crowd at Fiserv Forum behind them, the Bucks got off to a red-hot start in tonight's Game 6 matchup. After the first quarter of play, Milwaukee led the Suns 29-16. That margin would quickly dwindle though. Scoring just 13 points in the second frame, the Bucks surrendered their double-digit […]
July 20, 2021 @ 9:40pm » Andrew McCarty
Everyone Is Saying The Same Thing About Suns PG Chris Paul
On Tuesday night, the Milwaukee Bucks and Phoenix Suns stepped on the court for Game 6 of the NBA Finals. The Suns opened up the series with two wins at home and looked well on their way to winning the series. However, the Bucks bounced back in a big way, winning both home games and […]
July 20, 2021 @ 9:07pm » Alek Arend
Look: Atmosphere Outside Milwaukee Bucks Arena Is Going Viral
This year's NBA Finals hasn't just been a competition between the Bucks and Suns; it's a battle of the fans. The debate might be over, though. We are giving the edge to Milwaukee's fan base. The Bucks last won a basketball championship in 1971. It's been a long stretch of mediocrity ever since. But Giannis […]
July 18, 2021 @ 3:36pm » Matt Hladik
Chris Paul Called Out For 'Dirty' Play In Game 5 Loss
Giannis Antetokounmpo's iconic alley-oop dunk at the end of Game 5 overshadowed what many thought was a dirty play by Chris Paul. Paul is an all-time great and an eventual Hall of Famer, but he also has a well-earned reputation of pushing the envelope with his physicality and gamesmanship. A number of analysts and fans […]
NBA World Reacts To A Wild Bucks-Suns Game 5 Finish
The Phoenix Suns looked like they might run away with Game 5 of the NBA Finals in the first quarter. The Milwaukee Bucks dominated the second and third quarters. We ended up with an absolutely classic finish, with Giannis Antetokounmpo, Jrue Holiday and company picking up the first road win of the series to go […]
Watch: LeBron James Shares Why He's Rooting For The Suns
Space Jam star and occasional basketball player LeBron James is at tonight's NBA Finals Game 5 between the Phoenix Suns and Milwaukee Bucks. There was no real mystery which team he's rooting for, but he made it clear tonight with an interview from courtside. Chris Paul is one of LeBron's closest friends in basketball. While LeBron […]
July 17, 2021 @ 11:17pm » Alek Arend
NBA World Reacts To Chris Paul's Game 5 Finals Performance
Game 5 of the NBA Finals was supposed to be Chris Paul's signature moment. Perhaps the high stakes got the better of him. So far, he's failed to show up when the Phoenix Suns needed him most Saturday night. Paul's play, good or bad, has had a drastic impact on the Suns' performance in the […]
Bucks Announce 1 Coach Will Miss Tonight's NBA Finals Game
The Milwaukee Bucks announced on Saturday they will be without Thanasis Antetokounmpo for Game 5 of the NBA Finals. He's not the only member of the organization that'll be absent for this evening's game. Bucks assistant coach Josh Oppenheimer will not be present on the bench for Game 5 of the NBA Finals, per ESPN's […]
Report: Giannis' Brother Thanasis Antetokounmpo Enters Health Protocol
Just hours before tonight's crucial Game 5 of the NBA Finals, the Milwaukee Bucks are down a notable, if not essential player. Thanasis Antetokounmpo, a reserve and brother of former MVP Giannis Antetokounmpo, has entered the league's health and safety protocols. So far, it is unclear whether he has tested positive for COVID-19, or if […]
TV Ratings Announced For Game 4 Of The NBA Finals
When the Milwaukee Bucks and Phoenix Suns emerged victorious from their respective conferences, there was cause for concern. Why? Well, both are considered small-market teams, so the expectation was the TV ratings for the NBA Finals would be disappointing. Such an expectation was wrong to begin with. The NBA Finals Game 4 ratings were revealed […]
LeBron James Responds To Chris Paul Trade Question
Los Angeles Lakers star LeBron James made an appearance on Jimmy Kimmel Live this week to promote Space Jam: A New Legacy and discuss a few NBA-related topics. James showed his support for Phoenix Suns guard Chris Paul at one point during his interview with guest host Arsenio Hall. He even commented on the trade from 2011 […]
NBA World Reacts To Officiating Crew For Game 3
Chris Paul and the Phoenix Suns hold a 2-0 series advantage heading into Milwaukee tonight. But, there could be a roadblock on their way to extending that lead. The officials for Game 3 have been released — and there's one name on the list that Suns fans won't be too happy to see. Scott Foster […]
July 9, 2021 @ 11:43am » Tzvi Machlin
Dwyane Wade Has Message For Chris Paul After Game 2 vs. Bucks
Chris Paul's second NBA Finals game was his second NBA Finals win as his Phoenix Suns topped the Milwaukee Bucks in a 118-108 victory. Among the many to offer Paul congratulations after the win was NBA legend Dwyane Wade. As Paul walked off the court after the win, he was greeted by a masked-up D-Wade. […]
July 7, 2021 @ 2:52pm » Chris Rosvoglou
NBA World Reacts To LeBron's Message For Chris Paul
LeBron James didn't shy away from showing his support for Chris Paul during Game 1 of the NBA Finals. After the Phoenix Suns' statement win over the Milwaukee Bucks on Tuesday night, James tweeted the following message to Paul: "one down, three to go." James has always been close friends with Paul, but some NBA […]
July 7, 2021 @ 11:17am » Matt Hladik
LeBron James Shares Message For Chris Paul After Game 1
LeBron James and Chris Paul are contemporaries and close friends, and James, a four-time NBA champion, is rooting for Paul to get his first ring. Last night, the Phoenix Suns beat the Milwaukee Bucks 118-105 in Game 1 of the NBA Finals. Paul, the Suns' floor general, was brilliant, scoring 32 points on 12-of-19 shooting […]
July 6, 2021 @ 5:53pm » Zach Koons
ESPN Computer's Prediction For Game 1 Of NBA Finals
After over six months of non-stop basketball, the 2021 NBA Finals are finally here. Game 1 between the Milwaukee Bucks and the Phoenix Suns will tip-off late on Tuesday night. Both teams have proven to be among the league's elite this season, but have taken drastically different paths into the NBA Finals. The hobbled Bucks […]
July 5, 2021 @ 7:38pm » Alek Arend
Devin Booker Has Honest Take On Suns' Path To NBA Finals
Injury luck has been on the Phoenix Suns' side all postseason long. Opposing team's fans have used this as a way to negate the Suns' success, as a result, and Devin Booker is sick of it. There's no denying Phoenix's trip to the NBA Finals involved a bit of luck (well, probably a lot of […]


There isn't a speck of doubt that a flower blossom isn't one of the loveliest creations on earth. Our Iota Nickel Pendant raises the stakes on this claim by taking the beauty of the bud and maintaining it for all eternity. That's because we've fashioned ours from brass that we've treated to an oxidized silver finish. The one-light pendant will never fade like the last roses of summer!


text:
BioM: Bauer, Estelle (1926)
Contact: Stan Schwarze
Surnames: BAUER LAMER
----Source: WEEKLY CLARION (Dorchester, Clark Co, WI) 12/03/1926
Bauer, Estelle (NOV 1926)
(Taylor County Leader)
The wedding of Miss Estelle Bauer, daughter of Mr. and Mrs. Frank Bauer, to Joseph Lamer Jr., son f Mr. and Mrs. Joseph Lamer of Tomahawk, took place Wednesday morning at 8 o'clock in Holy Rosary Church, the rev. Fr. Rueter reading the service.
The bride's gown was of rosewood twilleen with which she wore a silver metallic hat. The bridal bouquet was a shower of carnations and roses.
The bridesmaid, Miss Amelia Bauer, sister of the bride, wore a gown of tan twilleen with hat of gold metallic. She also carried a bouquet of carnations and roses. Louis Bauer, uncle of the bride, was the best man. During the service the church choir of which the bride has been a member of many years, sang the nuptial mass.
The ceremony at the church was followed by a dinner at the home of the bride's parents to the relatives and a few intimate friends only.
During the afternoon Mr. and Mrs. Lamer left for Wis. Rapids where they will spend a few days with relatives. They will make their home in Tomahawk.
The bride is one of the popular young ladies of this city and is widely known, having clerked at the Kostner store the past five and a half years.
Mr. Lamer, although somewhat of a stranger here, is highly spoken of and is the manager of the fox farm near Tomahawk where he has a new home awaiting his bride.
With their many friends we join in extending hearty congratulations.
Among the out of town guests at the wedding were: Mr. and Mrs. Joseph Lamer, parents of the bridegroom, and their son Herman, of Tomahawk; Mr. and Mrs. George Berard of Wis. Rapids, Mrs. Berard is a sister of the bride; Mr. and Mrs. Dailey of Abbotsford, and Mr. and Mrs. Richard Bahr of Marshfield, sisters and brother-in-law of the bridegroom.


text:
Q: ConfigurationManager.AppSettings in Roslyn returns an empty string I'm fully aware this question has been asked multiple time on here, but I have scoured the internet and have yet to find a solution.
I run the following .csx file with scriptcs (just to test and make sure the ConfigurationManager works):
#load "C:\Tickets\LoadConfig.csx"

using System;
using System.Configuration;
Console.WriteLine(AppDomain.CurrentDomain.SetupInformation.ConfigurationFile);
Console.WriteLine(ConfigurationManager.AppSettings.AllKeys);

Here is the LoadConfig.csx, I found it on here SO post and multiple people said they had good results.
#r "System.Configuration"

using System;
using System.IO;
using System.Linq;

var paths = new[] { Path.Combine(Environment.CurrentDirectory, "web.config"), Path.Combine(Environment.CurrentDirectory, "app.config") };
var configPath = paths.FirstOrDefault(p => File.Exists(p));

if (configPath != null)
{
    AppDomain.CurrentDomain.SetData("APP_CONFIG_FILE", configPath);

    var t = typeof(System.Configuration.ConfigurationManager);
    var f = t.GetField("s_initState", System.Reflection.BindingFlags.Static | System.Reflection.BindingFlags.NonPublic);
    f.SetValue(null, 0);

    Console.Write(configPath); // Here to make sure it found the app.config file properly
}

Here's the app.config too:
<?xml version="1.0" encoding="utf-8" ?>

<configuration>
    <appSettings>
        <add key="testKey" value="testValue" />
    </appSettings>
</configuration>

However, when I run the first code block it tells me that the current configuration file is app.config and that the AllKeys property is System.String[]. I've made sure that all the files are in the same folder and that the app.config is written correctly too. I'm just stuck right now and not sure if there are any other solutions or if I'm completely overlooking something. If anyone has any suggestions they'd be much appreciated, thanks.

A: This is because you are printing ConfigurationManager.AppSettings.AllKeys directly, which is not a string so it just prints the object type.
You need to iterate around the keys with something like
var keys = ConfigurationManager.AppSettings.AllKeys;
foreach (var key in keys)
{
    Console.WriteLine(key);
}
Console.ReadLine();

or
ConfigurationManager.AppSettings.AllKeys.ToList().ForEach(k => Console.WriteLine(k));

Output:

testKey

redpajama_set_name: RedPajamaStackExchange


ABSTRACT - Among various gravitational models, Huff's probabilistic model of retail gravitation is probably the most widely used model. Its ability as an explanatory tool, however, is handicapped by the fact that it includes all potential shopping areas in its competitive system. This paper proposes a new model based on the concept of choice set. Results from a large scale study in a Canadian city indicate that the proposed model substantially outperforms Huff's model, and can be used for both predictive and explanatory purposes.
Chow Hou Wee and Michael R. Pearce (1985) ,"Patronage Behavior Toward Shopping Areas: a Proposed Model Based on Huff's Model of Retail Gravitation", in NA - Advances in Consumer Research Volume 12, eds. Elizabeth C. Hirschman and Moris B. Holbrook, Provo, UT : Association for Consumer Research, Pages: 592-597.
Among various gravitational models, Huff's probabilistic model of retail gravitation is probably the most widely used model. Its ability as an explanatory tool, however, is handicapped by the fact that it includes all potential shopping areas in its competitive system. This paper proposes a new model based on the concept of choice set. Results from a large scale study in a Canadian city indicate that the proposed model substantially outperforms Huff's model, and can be used for both predictive and explanatory purposes.
Since the emergence of shopping centers in the 1950's and 1960's, retail sales have been shifting increasingly toward such centers. Estimates indicate that shopping centers will account for 50, of all retail sales by 1990 (Dickinson 1981, p.57). In a recent study (Prestwick 1980), 47% of the sampled shoppers in a major shopping mall reported that they were there because of the mall itself. Thus, almost half of the shoppers did not make their shopping locational choice because of the attraction of specific stores or products and services, but instead were attracted by some aspects of the mall and its complex of units. Related to the development of shopping centers is the conscious attempts by many downtown retail areas to get organized as "business entities" to react to the increasingly threats posed by shopping centers (Spalding 1981; Petto 1983).
The evolution of planned and organized shopping areas such as shopping centers and revitalized downtown areas has several implications. To the consumer, the evolution represents another level of patronage decision in the form of increased choices between different shopping areas. To the marketer, it means an increasing need to attract the consumer to the shopping area, and not just to a particular store. The importance of promoting the whole shopping area thus takes on more significance than promoting a particular store. Related to this, therefore, is the need to understand the main factors that affect the choice of shopping areas by consumers, and how they can be attracted.
l = a parameter which is to be estimated empirically to reflect the effect of travel time or distance on various kinds of shopping trips.
In essence, the model states that the probability of any shopper choosing a particular retail center is equal to the ratio of the utility of that center to the sum of utilities of all potential competing centers in the system (Huff 1964, p.37)0 Specifically, the utility or attractiveness of a center is directly related to the size of the center and inversely related to the distance separating consumers from the center.
Huff's model is probably the most parsimonious specification of modern theory-based approaches to the study of consumer spatial behavior. Earlier gravity models (Reilly 1929; Converse 1949) were specified at an aggregate level and were deterministic in nature. In contrast, Huff specified a multiplicative utility function with two variables, selling space and travel time. These two variables clearly act as proxies for the principal constructs of Central Place Theory (Christaller 1933; Losch 1954 - the importance of a center and economic distance. Thus 9 the theoretical justification of Huff's model can be found in Central Place Theory (Huff 1981).
Another major strength of the model is its inclusion of the effects of competition on the behavior of the shopper. This, by itself, adds much credibility to the model. By constructing probability contours, Huff's model also explicitly allows for the occurrence of irregularities of trading areas (Huff 1964).
Huff's model also survived much empirical testing since its formulation (Huff 1962; Lakshmanan and Hansen 1965; Bucklin 1967a,b; Brunner and Mason 1968; Pacione 1974; Thomas 1976; Stanley and Sewall 1976; Lieber 1977; Turner and Cole 1980; Nevin and Houston 1980; Gautschi 1981). It is also interesting to note that in spite of the problems surrounding the calibration of the model, the A value in Huff's model has been empirically verified in many studies (Carrothers 1956; Huff 1962; Forbes 1968; Bucklin 1971a,b; Haines et al. 1972; Young 1975; Stanley and Sewall 1976). In general, they tend to support an empirical value of about 2.0 for normal household shopping despite various calibration methods used (Wee and Pearce 1984).
Huff's model is not without weaknesses. First, the model assumes that consumers with comparable socioeconomic characteristics will depict similar retail center patronage and that there are no internal differences of significance within the area of analysis.
Second, it is interesting to note that Huff's competitive system includes all potential retail centers in that system (Huff 1964, p.37). In other words, the basic see of shopping area choice alternatives is assumed to be spatially accessible to all consumers without taking into account possible other factors that might affect the choice of shopping areas. Thus, the use of the basic set in the model is similar to what urban geographers labelled as "store opportunity set" in store choice behavior (Marble and Bowlby 1968) and what marketers labelled as "awareness set" in brand choice behavior (Campbell 1973; Narayana and Markin 1975; Hawkins et al 1980). Subsequent studies have continued to apply Huff's model in the same way (Stanley and Sewall 1976; Nevin and Houston 1980). While this approach may be appealing when there are only a few recognizable shopping centers within a city, the situation becomes less defensible when there are many shopping centers with varying degrees of consumer patronization. Thus, should a shopping area which a consumer patronizes once a year or even once in two years be included with another which he patronizes once every month? What criteria should be used for inclusion or exclusion of shopping centers in the competitive system? Clearly, if all shopping areas are included, the model may bear little relationship to actual consumer patronage patterns. This is because consumers may patronize different subsets of shopping areas within the basic set or they may patronize shopping areas that have not been included in the set. Using a priori assumption that the same set of area choice alternatives apply to all consumers may be necessary if one is interested to use the model in relation to predicting patronage behavior or estimating the size of trading area for a new center. The same assumption becomes highly questionable when one is also interested to explain patronage behavior among an existing set of shopping areas.
"In addition to the potential bias resulting from omitted variables, bias may stem from an improperly specified choice set ... "
This problem is further compounded by socioeconomic factors. Mobile shoppers, for example, may visit many centers within the city, or take advantage of car-oriented out-of-town centers if available, whereas other shoppers who are spatially relatively confined will be more dependent on local shopping facilities. In essence, Huff's model is still applied from a retailer's point of view.
l = an exponent value.
The purpose of this study is to empirically test whether the proposed model will outperform Huff's model.
A city in southwestern Ontario was used as the research site. The size of the city (population of 284,000) plus its traditional role as a test city for many market research studies makes it ideal for the nature of this study. Besides, in terms of membership, the city has the largest Downtown Business Improvement Area in Canada.
In total, 15 shopping areas have been included for this study. The criteria for inclusion were that the area should have at least 100,000 square feet of retail selling space and that it must have some form of management promoting it as a business entity. It was not necessary that the area be a planned center. The choice of 100,000 square feet as the cut-off for size was consistent with the findings of Turner and Cole (1980) who concluded that gravity models are more suitable for large and medium shopping areas.
Basic data on each of the shopping areas, including their retail selling space, were obtained from several secondary sources. The 1980 Canadian Directory of Shopping Centers provided the basic data for each of the shopping areas in this study, except for two areas. These data were verified and updated with the respective management of each shopping area and planning officials of the city.
It is important to emphasize that the city stretches only 9.3 miles from east to west and 7.2 miles from north to south. Most of the shopping areas in the study have competitors within a two-mile range, and the majority of them are located within a 3.5 mile range of downtown. Even the two farthest shopping areas are within 4.5 miles of the core of downtown.
Applebaum (1966) in his study of supermarket trade areas showed that the drawing power of a store could extend beyond 2 miles. Brunner and Mason (1968) found that the most significant and consistent driving time dimension in delineating shopping center trading areas was at the 15-minute driving points, as 75% of each center's shoppers resided within this range. Interesting, though, was the fact that 25% of the shoppers were willing to drive more than 15 minutes to the center. In fact, their study showed that where suburban centers were concerned, a higher percentage of shoppers (almost 30%) drove more than 15 minutes to the center.
Considering the results of the two studies, and taking into account the relatively small size of the city, the very accessible transportation system, and that this study was concerned with shopping areas as opposed to individual stores, all 15 shopping areas could be considered as potential competitors to one another.
The proposed model was tested against Huff's model with regard to the shopper's behavior toward the downtown area for non-grocery shopping. The dependent variable was operationalized as the number of actual trips (and dollars) that was made in downtown as a proportion of the total trips (and dollars) to all shopping areas in the consumer's choice set over a two-week diary period.
Square footage of selling space was often used as a surrogate measure for attraction of the shopping area (Huff 1962, 1963, 1964, 1981; Bucklin 1971a, b) and had applied in many studies, including Stanley and Sewall (1976) and Nevin and Houston (1980), and was applied in this study as well.
For the disincentive variable (Dij), distance was used instead of travelling time as it was felt that the former was a more objective measure. Specifically, crow-flight (straightline) distance was adopted after close study of the map of the research site which showed that there were no major obstacles within the city. The distance was measured from the consumers place of work if the majority of trips originated from and ended at the place of work. Otherwise, it was measured from the consumer's home. Thus this method of measurement took into account, in aggregate, trips' origin and end.
Finally, the X value was fixed at 2.0. In doing so, the authors had chosen not to consider the calibration issue, in light of the fact that there are many different methods of calibration and that the issue is still fraught with problems (Wee and Pearce 1984). There is considerable empirical support for using a X value of 2.0 for ordinary household goods shopping when the distance between competing shopping areas is not very great, and when shopping trips involve travelling to community or regional shopping areas (Reilly 1929; Carrothers 1956; Huff 1962; Forbes 1968; Bucklin 1971a, b; Young 1975; Stanley and Sewall 1976). Other researchers have also used the value of 2.0 in their studies (Huff and Lutz 1979; Nevin and Houston 1980). Thus, this study has opted to apply a model that has more operational and practical relevance to the manager, rather than engage in an academic pursuit that may have little value to Practitioners .
The data for this research were obtained as part of a large scale survey designed to obtain various information that helped to provide a better understanding of consumer spatial shopping behavior.
The survey required the respondent to complete an eight-page questionnaire and keep a two-week diary that recorded information on shopping trips and expenditure. Dillman's (1978) "Total Design Method" was closely followed in designing and implementing the survey. Initial contact letters, personally addressed to the female heads of households whenever possible, were mailed to 2070 residences in the city. A telephone call followed a few days after the letter. Of the 1269 principal shoppers reached by telephone, 823 agreed to participate in the study. A total of 679 returns, representing 82.5% of those who agreed to participate, were received. Of these, 482 respondents completed both the questionnaires and diaries and they formed the usable data-base sample. The return rate was equivalent to 58.6% of those who agreed to participate or 38.0% of those reached by telephone. Considering the level of difficulty of the survey instruments, the return rates were considered very satisfying.
Owing to the use of two research instruments in this research, non-response bias was determined in two ways. For those people who refused to participate in the study, three demographic questions on age group, educational level and years living in the city were asked over the telephone. The results of the difference of means test of the non-participants against the data-base sample showed that there were no significant differences with regard to the length of residence in the city and the education level. The only significant difference was that of age. Considering the nature of this study, the results were not surprising as older people tend to have more difficulties with their seeing and writing capabilities and thus tend to shun away from participating (Dillman 1978, p.53). In fact, the refusal rate was 42.1% for those people over 55 years of age.
As this study involved completion of both the questionnaire and diary, non-response bias was further assessed between those respondents who completed only the questionnaire and the data-base sample. Comparison between these two groups were made along 7 criteria -- age, education, Siegel's (NORC) job prestige scale, income, years living in the city, years living at the present address, and the number of shopping areas visited over the last three months. The only significant difference, using the difference of means test, between these two groups, at the conventional 5% level of significance, was that of educational level. Again, this result was not unexpected. It was possible that those participants with lower level of education had more difficulty in responding to both the questionnaire and diary.
Taking into account that there were no significant differences within each of the two sets of comparisons that were discussed above, it was concluded that non-response bias was definitely not a problem in this study.
Since all the variables were measured at least on interval scales, multiple regression was selected as the appropriate analytical technique.
Two common criteria were used for the selection of the better model. These were the value of R-square achieved by the least squares fit and the value of the residual mean square. In addition, a third statistic which has gained popularity in recent years, the Mallows' Cp statistic (Mallows 1973; Draper and Smith 1981, pp.229-302) was also used. Basically, the Mallows' Cp statistic involves comparing the actual Cp value with the expected Cp value. The criterion for deciding the better model is the Cp value that is closer to the E(Cp) value as it would indicate an unbiased model in which the equation fits the actual data better.
The results are shown in Table 1. With regard to the. trip data, Huff's model attained an adjusted R-square of 0.178, a residual mean square of 0.0719 and a very high Cp statistic of 56.57. In contrast, the proposed model had a vastly improved adjusted R-square of 0.253, a lower residual mean square of 0.0654, and a much lower Cp statistic of 8.00 which was closer to the E(Cp) value of 2.00. The proposed model thus outperformed Huff's model on all three criteria. The superiority of the proposed model was also clearly reflected when the two regression equations were compared. The proposed model had a higher beta value of 0.504 compared to 0.424 for Huff's model.
Similar patterns of results were shown for the expenditure data on downtown. Huff's model showed an adjusted R-square of 0.138, a residual mean square of 0.1021 and a Cp value of 41.18. The proposed model recorded an increase of about 0.06 for the adjusted R-square to o.197, a lower residual mean square of 0.0952, and a much lower Cp value of 6.07. The beta coefficient of the proposed model was also much higher.
Examinations of the residual plots show that while both Huff's and the proposed models were slightly skewed positively, they did not affect the robustness of the regression analysis (Snedecor and Cochran 1967; Bohrnstedt and Carter 1971; Pedhazur 1982, p.34-36).
Double cross-validation of the best fit regression model (Lord and Novick 1968, p.285; Mosier 1951) was carried out to determine the stability of the proposed model and to ascertain whether the shrinkage in R-square was serious. The regression equations derived from the split samples are shown in Table 2. The results show that the Beta values, significance levels and R-squares are very similar for the trip data, attesting to the stability of the proposed model. While some shrinkage is noted for the regression on the expenditure data in terms of double cross-validation, the model still performs very well in terms of cross-validation.
" ... given the potential practical value of the model, it is rather surprising that little research effort has gone into attempts to refine the original formulation in the practical context of retail planning within the city. Perhaps this represents a worthwhile direction for further research effort."
This study, besides responding to the above comment, serves to provide empirical evidence supporting the use of the concept of choice set in predicting and explaining consumer shopping behavior.
In order to better understand the problem of identifying potential competing shopping centers in Huff's model, the number and type of shopping areas visited by the principal shoppers during the entire study period were tabulated. Table 3 shows that consumers did not patronize all the potential competing shopping areas. Judging by the range and variance of the number of shopping areas visited, and the frequency in which each shopping area was included in the consumer's choice set, it was apparent that the set of shopping areas visited (choice set) varied from consumer to consumer. In general, the number of shopping areas within the consumer's choice set appeared to be around 6.0, as indicated by the mean of 6.55, mode of 6.0, and median of 6.36.
Many factors such as individual socio-demographic and psychographic differences, and the consumer's mobility and accessibility to shopping areas, could all have affected how and where the consumer shopped. While this research did not attempt to identify which of these factors did have an impact on the selection of shopping areas, the choice set intuitively acted as a surrogate measure that took into account such differences among individuals and other factors that could have affected their shopping behavior.
It was also interesting to note that the larger the mass of the shopping area, the more likely would it be included in the consumer's choice set (Spearman correlation coefficient of 0.7131, significance = 0.001; Kendall correlation coefficient of 0.5550, significance = 0.002). In addition, there was also a highly significant association between the frequency in which a shopping area was included in the consumer's choice set and the frequency in which the area was identified as a most-shopped area (Spearman correlation coefficient of 0.7464, significance = 0.001; Kendall correlation coefficient of 0.6381, significance = 0.001).
While using the proposed model may require more research, especially in terms of collecting data directly from the consumers, the process is not as complicated and difficult as it may seem. The research instruments can be simplified to that of a questionnaire alone. In fact, based on this study, using the proposed model even had a distinct advantage over using Huff's model as far as the distance measurement was concerned. Fewer distance measurements were needed for the proposed model as the respondent did not patronize all potential shopping areas. The average was six shopping areas in the choice set while there were 15 shopping areas in Huff's model.
Using the proposed model has two other advantages. First, it allows the user of the model to clearly identify which are the actual competing centers from the consumer's point of view. The user of the model will also be able to isolate the more "serious" competing centers in that such centers would be included more often in the consumer's choice set.
Second, the inability to identify actual competing centers has very much restricted the use of Huff's model to predictive purposes only. In contrast, the proposed models as operationalized in this study, not only can be used as a predictive tool, but also for explaining consumer patronage behavior toward existing shopping areas. The stability of the proposed model in terms of predictive and explanatory purposes was clearly established when the model was tested by double cross-validation.
In view that the future trend is toward building more shopping centers and that traditional shopping belts or areas are increasingly getting organized as integrated business entities, the problem of identification of potential competing shopping areas will become very difficult if Huff's model were to be applied without any modifications. Huff's model will also become more tedious to use when the number of shopping areas increases, for example, imagine the number of distance measurements needed if there are 20 potential competing centers. In contrast, the proposed model uses the choice set concept and is likely to be unaffected by the increasingly number of shopping areas.
Finally, it is important to point out that the model, as tested, has been deliberately confined in a parsimonious way in order to compare it against Buff's model. Further refinements to the proposed model can still be made. Possible variables that could be added to the proposed model may include the effects of specific stores and products (or services) on the choice of shopping areas, and more elaborate constructs such as image of the shopping area.
Applebaum, W. (1966), "Methods of Determining Store Trade Areas, Market Penetration, and Potential Sales," Journal of Marketing Research, Vol. 3 (May), 127-141.
Bohrnstedt, G.W. and T.M. Carter (1971), "Robustness in Regression Analysis," in H.L. Costner (ed), Sociological Methodology, San Francisco: Jossey-Bass.
Brunner, J.A. and J.L. Mason (1968), "The Influence of Driving Time Upon Shopping Center Performance," Journal of Marketing, Vol. 32 (April), 57-61.
Bucklin, L.P. (1967b), Shopping Patterns in an Urban Area, Berkeley, California: Institute of Business and Economic Research, University of California.
Bucklin, L.P. (1971a), "Retail Gravity Models and Consumer Choice: A Theoretical and Empirical Critique," Economic Geography, Vol. 47 (October)s 489-497.
Bucklin, L.P. (1971b), "Trade Area Boundaries: Some Issues in Theory and Methodology," Journal of Marketing Research, Vol. 8 (February). 30-37.
Campbell, B. (1973), "The Existence of Evoked Set and Determinants of its Magnitude in Brand Choice Behavior," in J. Howard and L. Ostlund (eds), Buyer Behavior: Theoretical and EmPirical Foundations, Alfred A. Knopf Inc., 243-244.
Carrothers, G.A.P. (1956), "A Historical Review of Gravity and Potential Models of Human Interaction," Journal of the American Institutes of Planners, Vol. 22, No. 2.
Christaller, W. (1933), Central Places in Southern Germans, translated by C.W.Baskin, Englewood, New Jersey: Prentice Hall, 1966.
Converse, P.D. (1949), "New Laws of Retail Gravitation," Journal of Marketing, Vol. 14 (January), 379-384.
Dickinson, R.A. (1981), Retail Management, Austin, Texas: Austin Press.
Draper, N.R. and H. Smity (1981), ApPlied Regression Analysis, 2nd Edition, New York: Wiley.
Forbes, J.D. (1968), "Consumer Patronage Behavior," in R.L. King (ed)s Marketing and the New Science of Planning, Chicago: American Marketing Association, 381-385.
Gautschi, D.A. (1981), "Specification of Patronage Models for Retail Center Choice," Journal of Marketing Research, Vol. 18 (May), 162-174.
Goldman, A. (1976), "Do Lower-Income Consumers have a More Restrictive Shopping Scope?" Journal of Marketing, Vol. 40 (January), 46-54.
Haines, G.H., L.S. Simon and M. Alexis (1972), 'Maximum Likelihood Estimation of Central City Food Trading Areas," Journal of Marketing Research, Vol. 9 (May), 154-159.
Hawkins, D.I., K.A. Coney and R.J. Best (1980), Consumer Behavior: Implications for Marketing Strategy, Dallas, Texas: Business Publications.
Huff, D.L. (1962), Determination of Intra-urban Retail Trade Areas, Los Angeles: University of California, Real Estate Research Program.
Huff, D.L. (1963), "A Probabilistic Analysis of Shopping Center Trade Areas," Land Economics, Vol. 39 (February), 81-90.
Huff, D.L. (1964), "Defining and Estimating a Trade Area," Journal of Marketing, Vol. 28 (July), 34-38.
Huff, D.L. (1981), "Retail Location Theory," in R.W. Stampfl and E.C. Hirschman (eds), TheorY in Retailing: Traditional and Nontraditional Sources, Chicago: American Marketing Association. 108-121.
Huff, D.L. and J.M. Lutz (1979), "Ireland's Urban System," Economic Geography, Vol 55 (No. 3), 196-212.
Lakshmanan,T.R. and W.G. Hansen (1965), "A Retail Market Potential Model," Journal of the American Institute of Planners, Vol. 31, 134-144.
Lieber, S.R. (1977), "Attitudes and Revealed Behavior: A Case Study," Professional Geographer, Vol. 29, 53-58.
Lord, F.M. and M.R. Novick (1968), Statistical Theories of Mental Test Scores, Reading, Mass: Addison-Wesley.
Losch, A. (1954), The Economics of Location, translated by W.H. Woglom and F. Stolper, New Haven: Yale University Press.
Mallows, C.L. (1973), "Some Comments on Cp," Technometrics, Vol. 15, 661-675.
Mosier, C.I. (1951), "Problems and Designs of Cross-Validation," Educational and Psychological Measurement, Vol. 11. 5-11.
Narayana, C.L. and R.J. Markin (1975), "Consumer Behavior and Product Performance: An Alternative Conceptualization," Journal of Marketing, Vol. 39 (October), 1-6.
Pacione, M. (1974), "Measures of the Attraction Factor: A Possible Alternative," Area, Vol. 6, 279-282.
Pedhazur, E.J. (1982), Multiple Regression in Behavioral Research: Explanation and Prediction, 2nd Edition, New York: Holt, Rinehart and Winston.
Petto, A.C. (1983), "Promotional Strategies and Atmospheric Changes for Revitalizing A Major Downtown Mall," Spring Conference (April 16), presentation to the American Collegiate Retailing Association.
Prestwick, L. (1980), "The Competitive Position of a Small Local Shopping Center," presentation to American Collegiate Retail Association, (April 12), quoted in E. G. May (1983), Product Positioning and Segmentation Strategy Adaptable to Retail Stores?
Reilly, W.J. (1929), Methods for the study of Retail Relationships, Austin, Texas: Bureau of Business Research Studies in Marketing, No. 4.
Shepherd, I.D.H. and C.J. Thomas (1980), "Urban Consumer Behavior," in J.A. Dawson (ed), Retail Geography, New York: Wiles. 18-94.
Snedecor, G.W. and W.G. Cochran (1967), Statistical Method- 6th Edition, Ames: Iowa State University Press.
Spalding, L.A. (1931), "Shopping Center Futures: Some Proof there is Life after Death - Downtown," Stores (October), 59-63.
Stanley, T.J and M.A. Sewall (1976), "Image Inputs to a Probabilistic Model: Predicting Retail Potential," Journal of Marketing, Vol. 40 (July), 48-53.
Thomas, C.J. (1976), "Sociospatial Differentiation and the Use of Services," in D.T. Herbert and R.J. Johnston (eds), Social Areas in Cities, London: Wiley.
Turner, R. and H.S.D. Cole (1980), "An Investigation into the Estimation and Reliability of Urban Shopping Models," Urban Studies, Vol. 17 (June), 139-157.
Wee, C.H. and M.R. Pearce (1984), "Retail Gravitational Models: A Review with Implications for Further Research," in Jay D. Lindquist (ed), DeveloPments in Marketing Science, Kalamazoo, Michigan: Academy of Marketing Science, Vol. VII. 300-305.
Young, W.J. (1975), "Distance Decay Values and Shopping Center Size," Professional Geographer, Vol. 27. 304-309.


text:
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
    package="com.derskeal.cryptoratia"
    android:versionCode="1"
    android:versionName="1.0" >

    <uses-sdk
        android:minSdkVersion="21"
        android:targetSdkVersion="25" />

    <uses-permission android:name="android.permission.INTERNET" />
    <uses-permission android:name="android.permission.ACCESS_NETWORK_STATE" />

    <meta-data
        android:name="android.support.VERSION"
        android:value="25.3.1" />

    <application
        android:allowBackup="true"
        android:icon="@drawable/icon"
        android:label="@string/app_name"
        android:roundIcon="@drawable/icon"
        android:supportsRtl="true"
        android:theme="@style/AppTheme" >
        <activity android:name="com.derskeal.cryptoratia.MainActivity" >
            <intent-filter>
                <action android:name="android.intent.action.MAIN" />

                <category android:name="android.intent.category.LAUNCHER" />
            </intent-filter>
        </activity>
        <activity
            android:name="com.derskeal.cryptoratia.btc"
            android:parentActivityName="com.derskeal.cryptoratia.MainActivity"
            android:windowSoftInputMode="stateHidden|adjustPan" >
        </activity>
        <activity
            android:name="com.derskeal.cryptoratia.eth"
            android:parentActivityName="com.derskeal.cryptoratia.MainActivity"
            android:windowSoftInputMode="stateHidden|adjustPan" >
        </activity>

        <provider
            android:name="com.android.tools.fd.runtime.InstantRunContentProvider"
            android:authorities="com.derskeal.cryptoratia.com.android.tools.fd.runtime.InstantRunContentProvider"
            android:multiprocess="true" />
    </application>

</manifest>

redpajama_set_name: RedPajamaGithub