text:
Chinese Taishan (in cinese ) è una nave da crociera, in servizio per la Bohai Cruise Co., Ltd.. Dal 2011 al 2013 prestò servizio per la compagnia genovese Costa Crociere.

Storia

A partire da Novembre 2011, la nave era stata noleggiata a Costa Crociere dalla controllata Ibero Cruceros per operare durante tutto il 2012 nella zona del Mar Rosso.

La nave non è mai stata acquistata definitivamente da Costa Crociere, e non era neanche stato reso noto quando Costa Voyager sarebbe tornata ad operare per Ibero Cruceros con il nome originario di Grand Voyager. Da maggio a novembre 2014 la nave doveva fare delle crociere nell'Adriatico e nello Ionio al posto della Costa Classica che le aveva realizzate nelle estati del 2012 e del 2013. Nel novembre 2013 Costa Crociere ha ufficializzato la vendita della Costa Voyager a una compagnia cinese lasciando i porti di scalo di Trieste ed Ancona senza i 30 attracchi previsti. Dal 2013 entra in servizio per la Bohai Cruise Co., Ltd. cambiando nome in Chinese Taishan.

Caratteristiche
La Costa Voyager era la più piccola nave della flotta Costa Crociere. Ha 418 cabine totali, di cui 28 suite, 16 panoramiche e 12 con balcone privato.
Ha inoltre, 3 ristoranti, 4 bar, 1 piscina, 2 vasche idromassaggio e un centro benessere con palestra, sale trattamenti, bagno turco e sauna.
Per quanto riguarda il divertimento, la Voyager mette a disposizione dei clienti: un teatro, un casinò, una discoteca, un internet point, una biblioteca, una sala carte, una galleria commerciale e lo Squok Club (Squok è la mascotte di Costa Crociere).

La nave ha 7 ponti, di cui sei sono destinati agli ospiti, dedicati agli dei greci:
 Neptune
 Dionysus
 Venus
 Selene
 Apollon
 Helios

Note

Altri progetti

Collegamenti esterni

Voyager


Portable, collapsible water bottle collapses to 1" thick to easily fit in your pocket or purse for travel. Wide mouth opening for easy filling with ice and drink. Flip-up drink spout seals securely when not in use. Dishwasher safe, BPA free, food-grade silicon and plastic. Watertight and fits in most car cupholders. 21 oz.


text:
Q: how to activate DJANGO.CORE.CONTEXT_PROCESSORS.REQUEST I read this

DJANGO.CORE.CONTEXT_PROCESSORS.REQUEST
If TEMPLATE_CONTEXT_PROCESSORS contains this processor, every
  RequestContext will contain a variable request, which is the current
  HttpRequest. Note that this processor is not enabled by default;
  you'll have to activate it.

from this page
But it seems there is no information how to activate this processor.
Here is my original question
Access request in django custom template tags
After i followed the answer
i still got errors
TemplateSyntaxError at / Caught an exception while rendering: 'request' Original Traceback (most recent call last):
File "C:\Python25\lib\site-packages\django\template\debug.py", line 71, in render_node result = node.render(context)
File "C:\Python25\lib\site-packages\django\template__init__.py", line 936, in render dict = func(*args)
 File "c:\...\myapp_extras.py", line 7, in login request = context['request']
File "C:\Python25\lib\site-packages\django\template\context.py", line 44, in getitem raise KeyError(key) KeyError: 'request'

the code causing problem is
request = context['request']   in
from django import template

register = template.Library()

@register.inclusion_tag('userinfo.html',takes_context = True)
def userinfo(context):
 request = context['request']
 address = request.session['address']
 return {'address':address}

A: I answered this here: How can I pass data to any template from any view in Django?
Also see the comments on my answer... you might want that bit of info too.

A: in settings.py
from django.conf import global_settings

TEMPLATE_CONTEXT_PROCESSORS = global_settings.TEMPLATE_CONTEXT_PROCESSORS + (
    'django.core.context_processors.request',
)

redpajama_set_name: RedPajamaStackExchange


text:
01380 732821 hello@buildingbridgessw.org.uk
Programme Benefits
Programme Journey
Programme FAQs
Referrals: Register for Someone Else
Self-Referral: Register for Yourself
Building Bridges Programme Privacy Notice
The Building Bridges programme treats the information we hold about our programme participants very seriously and we will comply with the requirements of the General Data Protection Regulation (GDPR) (EU) 2016/679.
The Building Bridges Programme is the local implementation across Swindon and Wiltshire of the national Building Better Opportunities (BBO) programme, which is jointly funded by The National Lottery Community Fund and the European Social Fund. The Managing Authority for the national BBO programme is the Department for Work and Pensions ESF Team.
The Building Bridges Programme is delivered by a partnership of 40 organisations, led by Community First, working collaboratively under a legal Partnership Agreement
The principles that we operate for all our participant data are:
We only capture and store the minimum amount of data we need to provide our service and meet the needs of our funders.
We will only share participant information with the National Lottery Community Fund, or other authorised bodies, in relation to the operation of the BBO Programme and it will only be shared in a secure manner.
We will not share any of our participant data to be included on any marketing or mailing lists
We are required to store participant data in both hard copy and electronic formats to meet the needs of our funders.
We have put in place a secure Management Information System in order to ensure that participant data can be shared and stored as securely as possible between our programme partners.
Each of our partner organisations has a data protection and security policy in place and the Building Bridges Partnership Agreement details how the partners will work together to ensure participant data is protected when they are working collaboratively to support them.
All participant information, both hard copy and electronic, will be stored securely and retained at least until 31 December 2034 to meet the requirements of our funders.
This information will be used to evaluate this project and to report to The National Lottery Community fund and European Social Fund for monitoring purposes. Participants may be contacted by these funders to discuss their involvement in the project.
We will dispose of all participant information, both hard copy and electronic, in a secure manner after 31st December 2034 or later if required by our funders.
If participants wish to view the information that the programme holds about them, they should formally apply in writing to the Building Bridges Programme Manager, Community First, Unit C2 Beacon Business Centre, Hopton Park, Devizes, Wiltshire, SN10 2EY.
If participants would like to find out more about our data protection and security for the programme, they should visit our website at www.buildingbridgessw.og.uk or contact our programme team on 01380 732821 or hello@buildingbridgessw.org.uk.
This Privacy Notice will be made publicly available though our programme website and participants will be made aware of its existence when joining the programme.
BBO Programme Data
The Managing Authority has confirmed that the legal basis that they will be using to collect, store and process all of the required participant data collected on the BBO Programme will be 'Public Task', meaning that the processing is necessary for performing a task that is in the public interest or an official function and has a clear basis in law.
As a result of the programme being delivered under the basis of 'Public Task', the Managing Authority and The National Lottery Community Fund have informed us that there is no requirement for participants to provide consent on the standard BBO Programme documents for their data to be collected, stored and processed.
The Department for Work and Pensions ESF Managing Authority is the Data Controller for all personal data required to help deliver the BBO Programme. Information about how and why the Data Controller uses the BBO Programme personal data can be found at www.gov.uk/dwp/personal-information-charter.
The The National Lottery Community Fund and all partners within the Building Bridges Programme will be Data Processors for this information.
Additional Building Bridges Programme Data
In addition to the data required to complete the standard BBO Programme documentation, the Building Bridges Programme also captures some additional participant data to help us operate our programme more effectively and meet the needs of our funders.
Our online referral process
Referral information from external organisations already supporting individual participants
Photographic consent forms
Participant's' economic status self-declaration form
Participant's needs analysis form
Participants' self-assessment of their wellbeing, using the Warwick Edinburgh Wellbeing Measure Score
Participants' self-assessment of their readiness for employment
Parental consent form for participants aged Under 16
This information is used by the Building Bridges Programme in order to improve our needs analysis and action planning with participants. Participants who join the programme on or after the 25th May 2018 will be asked to give their consent for this data to be captured and stored as part of the programme.
This information will only be shared with the The National Lottery Community Fund, or other authorised bodies, in relation to our operation of the BBO programme and any analysis will be undertaken in an anonymised fashion – e.g. calculating the average improvement in wellbeing self-assessment score for all our participants.
Community First, as the lead partner for the Building Bridges Programme will be the Data Controller for participant information captured in this way and our partner organisations will be Data Processors.
Non-Building Bridges Participant Data
A number of our partner organisations capture additional participant data as part of their standard processes to help them operate more effectively.
Where this is the case, that partner organisation will have a separate Privacy Notice in place that details how the information will be captured, stored and processed. The partner organisation will put in place separate consent arrangements to capture this data and they will act as the Data Controller for it.
Building Bridges Programme Referrals
All participant referrals to the Building Bridges programme should be made via the online referral process on our programme website.
If a participant makes a referral directly to one of our programme partner organisations, that partner will either ask the individual to complete the online referral process or complete it on their behalf.
The online referral process has been designed to capture the minimum necessary personal information to enable us to contact the potential participant, understand how the programme might help them and match them to the most appropriate partner organisation to help support them.
If the individual becomes a programme participant, this data is then transferred within the secure Management Information System to form part of the participant's file.
If a referral request does not result in the individual becoming a Building Bridges participant within six months for whatever reason, all data captured in the referral process will be securely destroyed. Although this period may appear slightly long, our experience to date is that obtaining proof of eligibility for some participants with complex circumstances can take up to four months and many other potential participants can take several months before they decide to engage fully with the programme. We do not want to exclude potential participants who fall into these categories unnecessarily.
If the potential participant subsequently wishes to re-engage with the Building Bridges Programme, they would be asked to complete a new online referral.
The online referral process makes potential participants aware of how the data they are providing will be managed.
Participant Rights to View Data
Participants have a right to view all of the data that the Building Bridges Programme holds on them and any requests should be made formally in writing to the Building Bridges Programme Manager, Community First, Unit C2 Beacon Business Centre, Hopton Park, Devizes, Wiltshire, SN10 2EY.
As all required participant data is being collected, stored and processed under the basis of 'Public Task', participants cannot claim the right to erasure ("right to be forgotten") or the right to portability of their data.
Participants do, however, have a right to object to their data being processed and any such requests would be considered by the Managing Authority. In the first instance, any such requests should be made formally in writing to the Building Bridges Programme Manager at the address above.
Retrospective Application of Privacy Notice
The current advice from the The National Lottery Community Fund is that the Department for Work and Pensions ESF Managing Authority will be adopting a going-forward position for the updated Privacy Notices arising from the General Data Protection Regulation.
As a result, this Privacy Notice will only be issued to participants that join the Building Bridges Programme from the 25th May 2018 onwards. We will not be issuing copies of this updated Privacy Notice to participants that have already joined or left your project before this date.
Programme Delivery Staff
The Building Bridges Programme maintains a circulation list of staff within our partner organisations that are involved in the delivery of the programme.
These circulation lists are necessary for us to maintain efficient operation of the programme and inform programme delivery staff of learning and governance updates from the national BBO Programme.
The staff circulation lists are amended as we are informed of staff changes and reviewed on a quarterly basis.
A full review of staff on the circulation lists was undertaken prior to the introduction of the General Data Protection Regulation and staff can elect to be removed from the lists at any time.
The Building Bridges programme is jointly funded by The National Lottery Community Fund and the European Social Fund. Find out more about our funding and the partners involved in supporting the Building Bridges programme in Wiltshire and Swindon.
The Building Bridges programme supports people across Swindon and Wiltshire who are facing significant challenges in being able to develop their skills, access education or move towards the world of work. The programme is a partnership of organisations who are experts at supporting people and giving them the skills and confidence they need to move forward. Taking part in the programme is voluntary and all of the advice and support is offered free of charge.
The programme is jointly funded by The National Lottery Community Fund and the European Social Fund.
Building Bridges Programme
C/O Community First
Unit C2 Beacon Business Centre
Hopton Park
SN10 2EY
Email: hello@buildingbridgessw.org.uk
© Building Bridges Programme, 2020 | Jointly funded by The National Lottery Community Fund and the European Social Fund. | Website design by Bold
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You heard all of the noise right before the election – "If Obama wins another term, our prices will have to go up" (among other things that will go up or down, like employee numbers, hours, unemployment rates, etc.). There have been a few brave souls that announced that, indeed, the prices for their products will increase – Kentucky Fried Chicken and Papa John's being two of the loudest thus far. But the real reason for this renewed interest of mine is that Five Guys just alerted the media that they would likely raise prices in the face of Obamacare. Now THAT is a national tragedy.
On many message boards, I see the same twisted economic logic at play that Obama and Obamacare apologists used throughout the elections. A vast majority out there are of two opinions on this increased price nonsense. First, they look at it as a vast conspiracy by those who just want to keep the people down. There's no need to raise prices – Obama's re-election is just giving the companies the perfect cover to do so, and only because they want to make more money.
Second, it is a knee-jerk reaction from those who have no idea how economics, and additionally, business, works. They don't have to raise prices. They can just take less profit, these sweet, naive people believe. Which is exactly how most businesses, especially small business owners, look at the situation.
Why should we let these excess taxes bother us? We should just take less money, and sell our product cheaper than what we would have sold it for had Obamacare not come into the picture. That idea sounds like a real winner. I think I'm going to teach a course on that sort of nonsense at a local grade school – but even those students would be able to tell that I'm full of it.
Which leads me to provide another couple of fallacies I've heard from the Obama Administration regarding prices and economics. The first is that the only way to grow the economy is by broadening the middle class. All economic growth, according to the President and his ilk, comes from that specific segment of the population.
What? The middle class works hard, earns their money, and then spends it on food, housing and cars. Occasionally, they'll make a big purchase – a large TV or a pretty nice vacation – but that's only once every few years. It's true the middle class keeps the economy chugging along – if they stop buying things the economy does slow down – but to say that they're the engine for economic growth is just plain false.
The upper class, the one-percenters, is the pony to bet on when it comes to making the economy soar. How many jobs has Bill Gates created? Hundreds of thousands? And all those workers buy things. They pay their taxes, property, income and sales. Chuck Lunchbox down the street? The only job he'll create is when he retires. Even then, that's no sure thing. His employer may not replace him.
The second fallacy is that on the date of Obama's first inauguration, unemployment was at 7.8 percent. On the date of Obama's second inauguration, the unemployment rate was at — wait for it — 7.8 percent.
The administration's spin on this hope but no change moment? Due to W's policies, unemployment was increasing in 2008. After four years of Obama, it's now just beginning to decrease. Again, not buying it.
The second 7.8 doesn't begin to account for those states that "forget" to report their figures or those people that have stopped receiving unemployment benefits and those that have dropped out of the workforce altogether. If we were truly interested in the true number, it would be a staggering one.
Finally, it is about time the current administration and its apologists stop discussing and blaming the issues on W. It's been four years. Most of us can clean up some substantial stuff in four years. Obama's administration has done very little to clean up anything – they've just made more messes.
Which leads us back to Obamacare. Prices will rise, the middle class will be squeezed and the economy will begin to further collapse. Brilliant. Who wants to type up my name on the next Nobel Prize for economics?
Chris Markham writes a regular column for fredericknewspost.com.


The shoe Maven, Tanya Walker was photographed by Miami advertising and lifestyle photographer Jeffery Salter in South Florida for More than Motion Magazine. photographed by Miami based Advertising, celebrity, people and commercial photographer Jeffery Salter. He was photographed by Miami Lifestyle and Fitness photographer, sports advertising and commercial photographer Jeffery Salter. Jeffrey is an award winning photographer who also does fitness and celebrity portraiture. He does location photography in Atlanta, Miami, Orlando, Tampa, New York City , Los Angeles and Dallas.


The LoveWorld Television Ministry has grown from airing our flagship programs on only one TV Station during the mid-nineties to broadcasting our programs in all the continents of the world, and currently, we are on 390 Television stations in over 180 nations worldwide; amongst these are stations with coast to coast coverage, e.g., USA Networks & ION; TV 4 ME, Australia; CNL, Ukraine and the AIT & NTA Network, Nigeria. This year, one of our major achievements is the Live Transmission of the Monthly Global Classroom/Service with the man of God – Rev. Chris Oyakhilome on terrestrial TV Stations in various nations, Network Services (with a coast to coast coverage) and on our Internet Television.


text:
Savills Names New North America CEO
Mitchell Rudin, the brokerage's president since the start of 2019, will succeed outgoing Chairman & CEO Mitchell Steir.
the Editors of Commercial Property Executive
Mitchell Rudin, Chairman & CEO, Savills North America. Image courtesy of Savills
Savills has selected President Mitchell Rudin to serve as chairman & CEO of Savills North America. The appointment will be effective June 30, when current CEO Mitchell Steir steps down after 37 years in the industry. During his tenure, Steir had spearheaded Savills' $260 million acquisition of Studley in 2014.
Rudin joined the firm in 2018 and became president at the start of 2019. Prior to his work at Savills, he served as CEO of Mack-Cali Realty Corp. for two years. Rudin also was CEO & president of U.S. commercial operations at Brookfield Office Properties, where he oversaw the rebranding of the firm's 80-property, 50 million-square-foot national portfolio.
Rudin also previously held various positions with CBRE, most recently serving as the company's CEO & president for its New York Tri-State Region. He holds a Juris Doctor from Boston College Law School and a Bachelor of Arts from Franklin & Marshall College.
In December, Savills hired Peter Hennessy as vice chairman in its New York City corporate office. Hennessy had previously served as president at Cushman & Wakefield.
Brookfield Office Properties
Mack-Cali Realty Corporation
Mitchell Rudin
Mitchell Steir
Scorecard: Energy-Saving Efforts Continue, Albeit at a Slower Pace
Westcore Buys 4.1 MSF Industrial Portfolio


Am I overthinking my appearance...?
Discussion in 'Business Models, Niches, Industries' started by Ryan G, Jun 12, 2018.
My business partner and I are in the process of starting a local technology services business, and I feel like we're getting too hung up on how we should dress.
We've both spent the last 13+ years in corporate America being forced to dress in mostly business and business casual attire. So, here we are now...looking to avoid that corporate feeling in our own business, but we still want to be taken seriously.
We aren't exactly in Silicon Valley, but at the same time we are a technology shop, so there shouldn't be an expectation for us to dress to the nines.
Should we simply test out casual vs business casual vs business and read impressions from our prospects and clients? Then make a decision...?
Should we decide what our brand represents and stick to that image? Basically, if a local business doesn't want to work with us because of our casual appearance, we'll just move on...?
As I'm typing, I feel like we're definitely overthinking this.
We're meeting with our first business prospect tomorrow. I'm not too worried about our attire for this first meeting since I have a personal connection with the company. However, I feel more concerned about the businesses in the future when we officially launch outside of our initial 3-4 trial use-case companies.
Maybe at your office you can be casual. But if meeting with clients for the first time, I'd tend to think one should err on the professional side.
You will never get yelled at for dressing the part, however you might for not.
jasoncuellar123 and Ryan G like this.
I argue in favor of professionalism, that's it. Whatever that means in the space. Be professional.
Thomas Baptiste, The_Saphir and Ryan G like this.
I think it is best to have a professional look when de4aling directly with customers, maybe even a logo'd shirt to show a sort of uniform.
Back in the day IT people could dress in shorts flip flops and a wife beater in a corporate office if they wanted to because so few people had the skills needed at the time they could get away with it but that's not the case 99% of the time now days.
From my experience there is still a "right" to be casual attitude with a lot of IT people but there are a lot of competing technology based service businesses out there so whatever you can do to make sure you set your self apart is good.
I definitely want to maintain a professional image, so we'll adapt over time to find the right look for our customers and brand.
Honestly, it's a personal preference and style is really overrated, but I usually go with a Polo style T-shirt with a good dress pants. The most important is shoes though. Shoes should be classy and well cleaned all the time. I've seen the difference it makes with sponsors when they took in my attire. It's all up to you, attire aside the value you offer is more important.


text:
Saint Andrew
Demitrie
Demitrie Weather
, Saint Andrew, DM Outlook Hourly 3 hr Past Avg
Time in Demitrie is Wed 20th Jan 10:35 pm |
Demitrie Current weather report
Canefield Airport Canefield Melville Hall Le Raizet Airport
Weather today in Demitrie, Dominica is going to be Patchy rain possible with a maximum temperature of 26°c and minimum temperature of 24°c. Expected precipitation falling is 4.10 mm.
Weather tomorrow in Demitrie, Dominica is going to be Patchy rain possible with a maximum temperature of 26°c and minimum temperature of 24°c. Expected precipitation falling is 0.90 mm.
15 km/h E
Weather in Demitrie, Dominica
Today's weather is turning out to be patchy rain possible. The visibility is going to be around 10 km i.e. 5 miles and an atmospheric pressure of 1014 mb . The daytime temperature is going to reach 26 °c and the temperature is going to dip to 24 °c at night. We expect around 4.1 mm of precipitation to fall and cloud covering 58% of the sky, the humidity will be around 78%.
Tomorrow weather is forecasted to be patchy rain possible. The visibility is going to be around 10 km i.e. 6 miles and an atmospheric pressure of 1014 mb. The daytime temperature is going to reach 26 °c and the temperature is going to dip to 24 °c at night. It will be mostly dry with little or no precipitation and cloud covering 40% of the sky, the humidity will be around 76%.
On Friday weather will be patchy rain possible with daytime temperature reaching 27 °c. Night time temperature are expected to be 24 °c.We expect around 1.3 mm of precipitation to fall. The visibility is going to be around 10 km i.e. 5 miles and an atmospheric pressure of 1015 mb. We expect around 1.3 mm of precipitation to fall and cloud covering 56% of the sky, the humidity will be around 78%.
Book flights and hotels for Demitrie
Please also visit Demitrie Historical Weather, Weather widget and Weather Charts pages. Historical or past weather forecast page provides historical weather forecast from 1st July, 2008 till now in 3 hourly interval. Text weather page will allow you to get a weather text summary for next 14 days and weather chart page displays weather pattern like temperature, wind speed, gust, pressure, etc. in graphical mode for next 14 days. We hope you like it.
Looking to buy past/historical weather for Demitrie, please visit Historical Weather Data section.


text:
\section{Introduction}
Personalization is all about creating a fulfilling experience for an end-user. To achieve this, the system requires knowledge of past user preferences and interactions to produce adequate recommendations. The interaction between the user and system facilitates designs that maintain customer relationships for an extended period.

The purpose of user engagement and personalization is customer advocacy. The end goal of customer advocacy is to work with existing and new customers to grow loyalty and retention. Because personalization has been proven effective for big businesses, it is important to consider it for local news in their geographical location. American local news has been drastically losing readers and business due to ineffective advertisement placements and an increase in digital readers. Now, local newspapers are trying to switch to subscription-based models that function on personalization and user engagement. Studies have shown the internet has become a major source of news due to its constant availability, and about nine in ten adults in the US read news online \citep{raza2021news}. However, an essential issue in the online media domain is the lack of definition of the criteria for newsworthiness (\citep{shoemaker2006news} as cited in \citep{raza2021news}). Therefore, creating a recommender system on a digital app is one-way local newspapers can increase their customer advocacy. The goal of the recommender system is to improve user experience and user engagement by prompting appropriate news articles to newsreaders.

Personalized news applications tend to prioritize news items based on topics in global user preferences across all news categories and geographical locations, as well as based on the popularity and recency of news items. However, the focus on long-term high-level preferences may, in fact, result in taking attention away from local stories that help provide the distinguishing added value for local newspapers.

For example, a local newsreader may not generally be a sports fan, and hence sports-related features may not play a major role in generating personalized content for that user. However, the user, like many other local readers, might have an intense interest in the local high school team. Similarly, local readers may be interested in reading about local crime, even though for most users, this may not be part of their global news preferences. In such situations, global user preferences cannot be used to generate recommendations to users interested in local news content. At the same time, purely localized models will not be able to represent the users' broader interests that are needed to generate recommendations on more general topics such as national politics, entertainment news, etc. Ideally, the recommender system must combine global preferences with localized models for specific content categories in order to provide useful recommendations at all levels and to help increase user engagement on content where there is intense local interest among readers.

In this research, we explore a session-based modeling approach to the personalized recommendation by focusing on different topic categories both at the local as well as global preference levels. We perform an offline empirical evaluation of different scenarios based on recorded past data rather than online experiments on a live system such as a news app. These experiments aim to inform the design of a hybrid recommendation framework that will allow local news outlets to provide added value and enhance user experience at the local level. Local news companies are shifting to digital subscription-based models because system effectiveness can translate to user satisfaction; personalized local news apps can then lead to reader advocacy and reader retention. We believe more focus on users' local interests would lead to a better recommender system to boost reader retention.

Thus the main Research Questions (RQ) of this work are as follows:

\noindent RQ1 - How do localized recommendation models perform in regards to system accuracy compared to standard models that focus on users' global preferences for news?

\noindent RQ2 - What is the effect of leveraging different local news categories on the overall quality of news recommendations?

We answer these research questions through a series of experiments based on a local news dataset from the city of Syracuse. We hypothesized that considering the context on the item side, which in this case is locality, would increase news recommender system accuracy for certain categories of local news. Our experiments will show that (a) considering a localized model is indeed helpful to improve the effectiveness of personalization along all of the considered evaluation metrics and (b) that the approach of focusing on subcategories will allow the system to identify those local news categories where localized recommendations are most useful.

There are three ways that user experience is commonly evaluated in recommender systems, according to \citep{konstan2012recommender}:
 (i) by carrying out user studies where the subjects are given certain questionnaires during different stages of recommendations,
(ii) by combining study on longitudinally logged data with the questionnaire-based user study (iii) by addressing other evaluation measures such as combining accuracy and beyond-accuracy measures in certain ways. We used the third approach to evaluate our work.

This paper is organized as follows: Section 2 reviews related works. In Section 3, we discuss our dataset, and baselines methods metrics we used for our empirical experiments. In Section 4, we present details of the experimental design and a discussion of our results. The paper ends with a conclusion and future works in Section 5.

\section{Related Work}

Throughout the past decade, well-known news agencies such as The New York Times, Washington Post, and BBC have created personalized news feeds for their subscribers based on their profile or the content information of the articles read by the users. Increasingly these online systems use personalization to cater to users' interests and drive user engagement\citep{spangher2015building, graff2015washington, raza2020survey}.
Research in news recommendation has explored a variety of methods such as Content-Based Filtering \citep{capelle2012semantics}, Collaborative Filtering \citep{das2007google}, Hybrid approaches \citep{das2007google}, Deep Learning \citep{qin2020research, de2018chameleon} and Graph-based models \citep{symeonidis2020session}.

These recommender systems have been trying to increase user engagement by filtering large article spaces and by assisting users in finding articles relevant to their interests through customization or personalization. \citep{jawaheer2014modeling}.

Recently, session-based recommendation algorithms in the news domain have been shown to be effective in recommending news items, in part because of the importance of factors such as recency and freshness in the news domain \citep{jannach2020research}. The goal is to consider the latest user session in session-based approaches and neglect or discount long-term user preferences \citep{jannach2020research}. In \citep{de2018chameleon}, the authors have proposed a deep learning meta-architecture named Chameleon on session-based news recommendations, which focuses solely on short-term users' preferences. The architecture includes a convolutional neural network for extracting textual features and a Long Short-Term Memory (LSTM) layer to model the sequence of clicked items in ongoing user sessions.

Some efforts have recently considered both long-term and short-term user preferences in the recommendation system \citep{liu2018stamp, villatel2018recurrent, sun2020go}. In \citep{symeonidis2020session}, authors applied random walks with restart strategy and different time windows on heterogeneous graph networks to capture both users' long-term and short-term preferences. They applied their approach onto different news datasets and showed the efficiency of their approach.

In addition to these systems, there has also been research conducted around applying context to recommender systems in order to generate better recommendations. Context factors may include the time a user reads an article, the general location of the user, or the specific order of articles read by a user. An example is music recommendation systems that use different contexts, situations, and musical preferences of users to create a more accurate recommendation algorithm \citep{kaminskas2012contextual}. In the domain of news recommendation, the Chinese news recommender system CROWN \citep{wang2015crown}, for example, uses contextual user data such as time and location to increase the accuracy of recommendations and enhance user engagement. This real-time news recommender system uses contextual information, such as time, day of the week, the user's device, and a combination of different algorithms to account for the changes to user preferences during the day.

While there have been many experiments with recommender systems in a broader news context, we found a research gap in using recommender systems for local news outlets in order to increase their reader retention rates.

We also wanted to explore using locality as an item-based context since previous research mostly focused on user-based context. However, locality in general does not necessarily lead to effective recommendation, even for local news sources. Readers of local news sources are interested in both local news as well content in broader non-local context. Furthermore, some local news categories  require specific models for recommendation due unique characteristics of these news categories and how users interact with them.

\section{Experimental Methodology}

Our approach involves considering local preferences in creating session-based news recommendation models that hopefully translate to increased user engagement. To conduct our empirical study, we collected and processed the data from a local news source. We designed our experiments based on the data to compare the localized models with standardized models and identify the effects of different news categories on overall recommendations.

\subsection{Dataset}

The data from this research is roughly ten years of subscriber and user-interactions data from Syracuse News \footnote{https://www.syracuse.com}, a local newspaper in Syracuse, New York. The dataset has different content, behavioral, contextual, and session information. We organized this data using two categories of tags, one based on the articles' main types and one based on the URL information. The main categories that we used were news, sports, and life \& culture. Based on the URL, the second category is more specific and sorts the article into one of the subcategories. We've selected 4 months of all available user sessions for our experiments: December 1st, 2018 to March 31st, 2019. We elected to only focus on 4 months of data to account for the fact that this is a session-based model that would not need to be trained long-term. In a pre-processing step, we set a tag based on locality. Using a semi-automatic system, we used keywords that would define an article as global (i.e., US Government, Celebrity news, Lottery...) or local (i.e., Restaurants, Local sports teams, Local crime, Weather reports, State news, etc...). For example, the article titled "US government quietly spends millions to guard confederate cemeteries." was tagged as non-local, with "US Government" being the keywords used.
In contrast, the article titled "On this date: Binghamton 'evacuated' in nation's largest civil defense drill in 1957" was tagged as local since Binghamton is a New York county. For our dataset, we used Syracuse's city, so local news would include any articles that discussed New York state, New York counties, or cities of New York, in addition to global articles. Figure ~\ref{fig: CH1} shows how a Syracuse news source includes local and national news stories. The news source contains the top news categories and the list of various specific subcategories that the stories fall under.

\begin{figure*}[h]
  \includegraphics[width=\linewidth,height=12cm]{syracuse_2.png}
  \caption{An example homepage of Syracuse news and two example news articles on it.}
  \label{fig: CH1}
\end{figure*}
While many articles were categorized based on their headline, we manually read through a select number of articles to assign a tag accurately. The data was organized into sessions with a length of 1 day and sorted by their timestamp. Sessions with only one interaction were excluded since they are not helpful in our session-based recommender systems study. The results and statistics of the pre-processed datasets are shown in figure~\ref{fig: CH2} and tables~\ref{tab:freq}-~\ref{tab:commands}. In the first table, we can see we have 2826 non-local articles and 8145 local articles.

\begin{table}
  \caption{Detailed statistics of the Syracuse dataset.}
  \label{tab:freq}
  \begin{tabular}{cc}
    \toprule
    Period&12/1/2018 - 3/30/2019\\
    \midrule
    \texttt{\#articles} & 10971\\
    \texttt{\#local articles} & 8145\\
    \texttt{\#non-local articles} & 2826\\
    \texttt{\#sessions} & 60934\\
  \bottomrule
\end{tabular}
\end{table}

\begin{table}
  \caption{Breakdown of the dataset based on the main categories (sports, news, and life \& culture.)}
  \label{tab:commands}
  \begin{tabular}{cccc}
    \toprule
    Locality & News & Sports & Life \& Culture\\
    \midrule
   Local Articles& 34.02\% & 30.35\% & 11.43\%\\
   Non-local Articles & 13.92\% & 3.4\% & 6.89\% \\
    \bottomrule
  \end{tabular}
\end{table}

\begin{figure*}[h]
  \includegraphics[width=\textwidth,height=5.5cm]{Sheet_2.jpeg}
  \caption{Distribution of the Syracuse dataset based on the sub categories (sports, news, and life \& culture)}
  \label{fig: CH2}
\end{figure*}

\subsection{Baseline Methods and Evaluation Metrics}
We applied the following baseline techniques for our experiments using the implementation from \citep{ludewig2018evaluation}: Association Rules (AR) \citep{agrawal1994fast,mobasher2001effective}, first-order Markov Chains (MC) \citep{norris1998markov}, Sequential Rules (SR) \citep{ludewig2018evaluation}, and Session-based KNN (SKNN) \citep{jannach2017recurrent}. We did not use the hybrid approach because the only content information we had from articles was the headline and URL. We had minimal contextual information surrounding the users, only looking at their location and time stamps. The deep learning approach needs a larger data set, so we neglect to report the results of that approach. We elected to use the so-mentioned simple baseline methods because they have mostly outperformed the more complicated approaches \citep{ludewig2018evaluation}.

\begin{itemize}
\item {\verb|Association Rules (AR)|}: AR was based on the methodology proposed by \citep{agrawal1994fast} and discussed in \citep{mobasher2001effective}, which was the first application of association rule mining in the domain of recommender systems. This utilizes clickstream data to formulate a model that effectively generates web news personalization. We used reference \citep{ludewig2018evaluation} adaptation of AR, which is a simplified version of association with the rules of size two. When an item appears after another item in a session, the rules are being created regardless of the occurrence gap. No minimum support or confidence thresholds were applied following our utilization of \citep{ludewig2018evaluation}.
\item {\verb|Markov Chains (MC)|}: In MC, the rules are extracted from a first-order Markov Chain, and the sequence in the data is being considered \citep{norris1998markov}. Each item's score in a given session is calculated by counting the frequency of users who viewed other items right after viewing that item. The MC describes the transition probability between two subsequent articles in a single session. It calculates how often a reader views a specific article after viewing another one.
\item {\verb|Sequential Rules (SR)|}: SR is similar to AR and MC. It considers the items' order, but unlike MC, with a minimum of one step distance between the two items. The rule is then getting a weight associated with the item-gap inverse (one over the number of steps between the two items). From the currently viewed item in one session, we set the maximum number of clicks to step back to 10. Another important hyper-parameter was the decay function, which measures the distance between two clicks set to a linear function \citep{ludewig2018evaluation}.
\item {\verb|Session-based KNN (SKNN)|}: SKNN compares the entire current session with the training data's past sessions to determine the recommended items. Rather than considering only the last event in the current session, as in ItemKNN, the SKNN method compares the entire current session with the training data's neighboring sessions. After trying several values for k, we decided to use k = 20 because it suited our experiment the best. For the session similarity measure, we used cosine similarity, which was used to find the k most similar past sessions for any given session \citep{jannach2017recurrent}.
\end{itemize}

There are two main evaluation methods: objective measures, such as accuracy and diversity, and subjective measures, such as reader satisfaction. This study focused on objective measures since we were using offline experiments and did not have access to the users. To measure quality factors such as accuracy, we have selected a set of metrics such as Hit Rate (HR), NDCG, and Mean Reciprocal Rank (MRR)\citep{parra2013recommender, ozgobek2014survey}.
\begin{itemize}
\item {\verb|HR@K|}: Among the top K items (articles in our experiments) HR finds the rate of times in which relevant items are retrieved \citep{parra2013recommender, wu2021personalized}.
\item {\verb|NDCG@K|}: is a standard ranking metric that uses the graded relevance to rank each item (which commonly, an article is viewed as either relevant or not relevant by the other ranking metrics) \citep{parra2013recommender, wu2021personalized}.
\item {\verb|MRR@K|}: is a ranking metric that takes the average of the reciprocal ranks of the top K results for a sample of recommendation lists. MRR considers the rank of the item \citep{parra2013recommender, wu2021personalized}.
\end{itemize}

\section{Experimental Results and Analysis}

In this section, we present our experiments to address the research questions (RQ1 and RQ2). As noted earlier, the primary goal of these experiments is to determine the degree to which models trained on certain local news categories outperform recommendation models based on general and global user preferences. In this context, we also want to identify scenarios in which broader models based on both local and non-local preferences are more appropriate to provide the most effective recommendations. Our ultimate goal from this study is to gain insights into the best way to design hybrid news recommenders (combining both localized and general models) for local news outlets.

\subsection{Experimental Design}

Using our local news dataset (presented in section 3.1), we experimented with different session-based recommendation methods (see section 3.2) in three different scenarios to explore the effectiveness of localized models in a news recommendation system.

In the first scenario, all articles (both local and non-local) were used in the training of the models as well as in the testing phase. In the second scenario, only local articles were used to learn localized models, and these models were also tested only on local news data.
In the third scenario, models were learned based on all data, but were only tested on test data comprising of local news articles. We used HR@K, NDCG@k, MRR@K for respective datasets to measure the system's performance in each scenario.

For training and testing splits, we used one single train-test split. The data was split in such a way that the sessions of all four months except those of the last ten days of the entire dataset were placed in the training set. We used the articles from the last ten days for testing. We report the results of applying this evaluation scheme using the Syracuse dataset. Sessions with only one interaction were excluded as we could not use them for the next-lick prediction.

In the initial experiment, we compared the performance of our baseline session-based recommender systems in the above three scenarios. It should be noted that our aim here is not to identify the best algorithm for making news recommendations. Instead our goal as to address RQ1, i.e., to determine how much more effective the recommendations would be when the algorithm focuses on local news. We compared the local and general models using several different algorithms to show that the results were not algorithm-specific.

To address RQ2, we designed an experiment to determine the impact of "hyper-local" models where models were trained and/or tested on specific news categories and subcategories both at the local and the global levels. With these experiments, we hope to find effective models to recommend different local article categories. We also wanted to distinguish local news categories where these localized models are beneficial and those categories where the broader and global preference models are more appropriate.

So, in the next set of experiments, we implemented nine different scenarios to find the effectiveness of training models on all vs. training on local articles in various news categories. We chose the categories of sports, life \& culture, and news since they have the largest amount of articles compared to other categories. We created three scenarios with each of these categories to test the model effectiveness when trained on all articles (local and non-local) compared to when it's trained on just local articles (in different categories). The first scenario trained on all articles and tested on local sports articles, the second trained on all articles and tested on all sports, and the third trained on local articles and tested on local sports articles. We ran these three scenarios following the same protocol as the first experiment, using performance metrics such as HR@K, MRR@K, and NDCG@K. We also replicated these experimental scenarios in all three categories mentioned above.

\subsection{Main Results and Discussion}

\begin{table*}
\small
  \caption{Results on the test set of Syracuse Local and All datasets.}
  \label{tab:local-all}
  \begin{tabular}{lcc|cccccc}
    \toprule
     Method&  Training Set & Testing Set & HR@10& HR@20& MRR@10& MRR@20&NDCG@10& NDCG@20\\
    \midrule
   SKNN& All & All  & 0.4368 & 0.5460& 0.1288&  0.1366& 0.2566& 0.2852\\
   &  Local& Local & \textbf{0.4940}& \textbf{0.5938}& \textbf{0.1446}& \textbf{0.1514}& \textbf{0.2926} &\textbf{0.3183} \\
      &  All & Local & 0.4584& 0.5653 & 0.1378 & 0.1452 & 0.273 & 0.3008 \\

    \midrule
   MARKOV& All & All  &0.3276 & 0.3918 & 0.16096 & 0.1655 & 0.2295 & 0.2463\\
   &  Local& Local & \textbf{0.361} & \textbf{0.4441} & \textbf{0.1845} & \textbf{0.1904} & \textbf{0.2547} & \textbf{0.2764}\\
      &  All & Local & 0.3396 & 0.4109 & 0.1700 & 0.175 & 0.2393 & 0.25796 \\
    \midrule
   AR& All & All  & 0.4304 & 0.5117 & 0.2069 & 0.2128 & 0.2997 & 0.3213\\
   &  Local& Local & \textbf{0.4631} & \textbf{0.5486} & \textbf{0.2198} & \textbf{0.2266} & \textbf{0.31930} & \textbf{0.3437} \\
      &  All & Local & 0.456 & 0.5391 & 0.2147 & 0.22 & 0.3184 & 0.3382 \\
    \midrule
    SR& All & All  & 0.3918 & 0.471 & 0.1732 & 0.17892 & 0.259 & 0.2798\\
   &  Local& Local & \textbf{0.4156} & \textbf{0.5011} & \textbf{0.2090} & \textbf{0.2151} & \textbf{0.2969} & \textbf{0.3193} \\
      &  All & Local & 0.4133 & 0.4916 &  0.1873 & 0.1929 & 0.2766 & 0.2972\\
    \bottomrule
  \end{tabular}
\end{table*}

The results of our first experiment are depicted in Table ~\ref{tab:local-all}. These result show that, in general, recommendation models that are trained on local news articles tend to be more accurate when recommending local articles than recommenders that were trained on both local and non-local articles.

Also, looking at the results across different recommendation algorithms, the session-based KNN model (SKNN) generally performed better than the other methods with respect to all three metrics. More importantly, the overall finding of the effectiveness of localized models is not affected by choice of the algorithm. For these reasons, in subsequent experiments, we only used SKNN to compare the performance of different models in the context of different scenarios.

With the second set of experiments (shown in Table~\ref{tab:maincategory}), we found that, when recommending local articles, training on local articles yielded better personalization than training with all articles. This effect was observed across all of the scenarios involving local news categories. These findings support the conjecture that users' local news preferences may differ from their general preferences on news topics. For example, users may not be interested in general news articles related to the life \& culture category. However, specific local art and culture events are often the subject of intense interest on the part of local readers. Such articles may be recommended using localized recommendation models but may be omitted from recommendation lists otherwise.

We also observe a difference in the degree of improvement in recommendation effectiveness across categories. For example, there is a greater advantage in using localized models for the Local News Category than there is for the other two categories.In fact, it may be possible that the more general models trained on all news articles perform better than localized models in the case of some news categories. This indicates that simply training based on local news is not enough. The overall system must be calibrated carefully to take advantage of those localized models where there is a significant difference in user preferences between local news items and general news items.

The localization effect mentioned above is even more evident when more granular categorization of local news articles is used. In order to find specific characteristics of users' local preferences, we decided to explore the main categories by breaking them down into subcategories. Referring to the 3.1 section, the article subcategories are based on URL information. For example, the URL of the article, which is titled "A closer look at Chevy's 2020 silverado hd pickup that will debut in February," is: "\url{https://www.syracuse.com/auto/2018/12/new_silverado_in_february_2019.html}". Based on this, the extracted subcategory is "/auto/" which is the first subdirectory of the URL. The main categories and subcategories are not mutually exclusive sets. For example, News and Life \& Culture are in two separate main categories but share the same /auto/ subcategory.

In each scenario, the main categories are broken down to probe how the top subcategories perform, which is shown in Table~\ref{tab:subcategory}). The performance using HitRate@20 shows significant variance across different subcategories depending on training sets (local vs. all). For example, in the subcategory of News/Politics, we can observe a higher performance when the model is trained on all articles. This is an example of the situation where localized models would be less effective than global models. In this case, the effect is likely due to the fact that among local readers, their news preferences related to politics center more around non-local and national issues.

\begin{table}
\small
  \caption{Results for different scenarios on various news categories using SKNN method.}
  \label{tab:maincategory}
  \begin{tabular}{cc|ccccc}
    \toprule
     Training Set & Testing Set &  HR@20&  MRR@20 &  NDCG@20\\
    \midrule
    All & All& 0.5460 & 0.1366 & 0.2852\\
   Local & Local&  \textbf{0.593} & \textbf{0.1514} & \textbf{0.3183}\\
 All & Local& 0.5653 & 0.1452 & 0.3008\\
    \midrule
    All & All Sports&  0.5410 & 0.1334 & 0.2862 \\
  Local & Local Sports& \textbf{0.5583} & \textbf{0.1397} & \textbf{0.2930} \\
All & Local Sports&  0.5329 & 0.1327 & 0.2839\\
    \midrule
   All & All Life\&Culture&  0.5797 &  0.1906 & 0.3478 \\
  Local& Local Life\&Culture& \textbf{0.6557} & 0.1885 & \textbf{ 0.3919}\\
All & Local Life\&Culture&  0.6393 & \textbf{0.2125} & 0.3865\\
    \midrule
   All & All News& 0.6460 & 0.1729 & 0.3553\\
  Local & Local News& \textbf{0.75} & \textbf{0.2015} & \textbf{0.4240}\\
All & Local News&  0.6979 & 0.1912 & 0.3909\\
    \bottomrule
  \end{tabular}
\end{table}

On the other hand, the results for the subcategory of Sport/Orange basketball (a local basketball team) shows the opposite effect, with significant increase in performance from the non-local models. It should be noted that additional experiments with larger datasets are needed to draw definitive conclusions. But, the results reasonably support the assertion that for some specific local news categories, it is important train localized recommendation models and incorporate then into a larger ensemble or hybrid system.
.
\begin{table*}
\small
  \caption{Results on various news subcategories.}
  \label{tab:subcategory}
  \begin{tabular}{cc|c|c|c}
    \toprule
    Training Set & Testing Set & News/Crime& News/Politics& News/news\\
 \midrule
    Local& Local &0.25&0.1 & 0.127\\

    Local & Local News & \textbf{0.46}&0.238&0.173\\

    All& All &0&0.189474&0.152\\

    All& All News &0&\textbf{0.340}&\textbf{0.214}\\
   \toprule
    &  & Sport/sports& Sport/Orange basketball&Sport/highschool sports\\
    \midrule
    Local&Local &0.095&0.596&0.32704\\
    Local&Local Sports &\textbf{0.1607}&\textbf{0.7622}&\textbf{0.3798}\\
     All&All &0.117&0&0\\
    All & All Sports &0.155&0&0\\
    \bottomrule
  \end{tabular}
\end{table*}

\section{Conclusion}

In this paper we proposed using localized models in session-based recommender system, particularly when recommending local news items where there is intense local interest and there is significant difference between users' global and local news preferences. These findings can inform the design of more effective local news recommender system that distinguish between certain categories of local and general news.

We conducted multiple offline experiments on a local news dataset that showed how localized models in specific news categories performed better compared to models based on general news preferences. We did a case study that shows there is a distinction between the way users interact with local news vs. global news, and for some categories there is a significant difference in users' global and local preferences.

Moving forward, we plan to conduct additional experiments with datasets from other local news sources, possibly combining these datasets to allow for experiments with more granular category structures while reducing the possibility of over-fitting. We also plan to explore the effect of model localization on beyond accuracy metrics such as diversity and novelty.

Furthermore, we plan to develop a general recommendation framework for local news that involves automatically identifying specific categories of news that benefit from localized models and to combine these localized models with other models based on general preferences into an integrated system.

In order to truly understand the impact of localized models on recommendation effectiveness, eventually we must perform a user study involving a live experimental system. We intend to explore the creation of such a system, possibly as an extension of an existing online local news site, to conduct such a user study.

The ultimate goal of this and future efforts in this direction are to find ways to more effectively derive user engagement for local news outlets which in turn helps these outlets generate more subscription and advertising revenue. Such effective recommender systems may be among the tools that can help reverse the current trend toward the extinction of locally sources news.

\bibliographystyle{ACM-Reference-Format}

redpajama_set_name: RedPajamaArXiv


If there is one thing that unites the punditocracy, it is their view that young people should have to participate in some kind of "national service." General Stanley McChrystal was the most recent one to float the idea in the Wall Street Journal and at the Aspen Institute, but Michael Gerson on the (kind of) right and E. J. Dionne on the pretending-to-be-center-left both jumped in to talk about what a good idea it was. In fact, when it comes to the punditocracy, none of the "cool" kids are particularly vocal at calling this idea what it is: a bad one.
National service is much more talked about than it is done. The idea is most popular among people who are a bit nostalgic for the good old days when the federal government used to hire teens and twenty-somethings to knock down a few trees. Typically, when a pundit calls for national service, he is almost certain to say at some point that he is not talking about the kind of national service that happened during the Vietnam War. Instead, he's talking about something more vegetarian, like we had during the New Deal.
Truth be told, most of the ideas that are discussed are usually even tamer than that. The Civilian Conservation Corps were extremely popular with Americans at the time, but clearing the woods probably wasn't so popular with Brer Rabbit and Brer Fox. Today, thanks to organizations like the Sierra Club, critters have a vote, and one that keeps the government from forming Civilian Conservation Corps 2.0. Fortunately, today we have plenty of inner-city schools where we can dispatch City Year tutors and Teach for America alums instead.
There are those who get excited about the prospect of volunteering and there are those who have a muted reaction which is neither instinctively for it nor against it. I will include myself in the latter category. While I appreciate the objectives of national service, I have also come to appreciate that typically any difference it makes is on the margins rather than fundamental. But that is also why I am so skeptical of any calls for making it mandatory or "expected."
A lot of people believe that it would make millennials turn off the Game of Thrones episodes and the Jon Stewart reruns so that they can get out and do something with their lives. But anyone who has spent much time around bureaucracies knows that they function much better in theory than in practice.
Usually the military is kept open as one possible avenue for national service. Nonetheless, if young people decided to spend their year in national service in the Army instead of building habitats for rare bullfrogs in the Okefenoke Swamp, they would soon find that they would either be assigned the menial tasks or otherwise spend the majority of their year in the service in training for a military occupational specialty which they would be unlikely to ever put to use.
It is likely that the same would be true of other programs which would be under pressure to process students through quickly. And many young people would have difficulty adapting. In spite of what John Kerry said, it isn't true that the kids who get the bad grades "get stuck in Iraq." The intellectual standards for being in the military today are high compared to the admittedly low standards of our education system. On the other hand, the military is typically less selective than urban rejuvenation programs which are usually so sought after by rich suburban kids.
One thing that many young people do not realize when they enter into their first challenge — whatever that might be — is that the world is often uncooperative and it frustrates ideals. Not that this isn't a good lesson to learn, but it isn't one to take on before you understand your capabilities and core competencies. And, coming out of high school and that room on the second floor of your parents' house, you don't know that — or at least you shouldn't.
That doesn't mean that your first step out of your parents' door should be in the direction of your college dormroom. You might even consider skipping college altogether. Instead, young people should do whatever it takes to test their limitations. A good way to start is by doing all of the things that you don't want to do: Maybe skydiving if you're afraid of heights or hiking if you hate the outdoors. You should try to hitchhike if strangers make you nervous or just get on the road and start driving if you've never been anywhere without your parents before. If you're parents ever made you go to a toy gun bash, it might be good for you to consider a stint in the Marine Corps. If you were a military brat, you might think about spending some time living amidst an Amish community.
The point is, when young people are young, they should take the path of greatest resistance. And they should be encouraged to do so. People calling for mandatory (or "expected") national service probably think that they are doing this, but shifting kids from the oversight of helicopter parents to the oversight of helicopter bureaucracies is probably not the best way to do this. This kind of service could be whatever we want it to be when we talk about it in theory. But, in practice, past experience suggests that it would just be another one or two years of public school with the stated purpose of "serving the national interest". Kids today don't need another year of school. In fact, they might not need all of the years that they have now, especially since many of our most promising students are the ones that drop out.


People of all ages enjoy the benefits of the Activator Method Chiropractic Technique. Dr. Gibson finds it very helpful in the treatment of infants and young children due to its quick and gentle approach for a population that sometimes has a difficult time staying in any one position too long! It is also her technique of choice for some elderly clients or those with osteoporosis or other conditions, which may be a contraindication for manual adjustments. The Activator is also very helpful in treating non-spinal complaints and is incorporated into Dr. Gibson's treatment of shoulder, elbow, wrist, hip, knee, ankle, and foot, and TMJ complaints.
Dr. Gibson is Advanced Proficiency Rated in this technique, which means that she has undergone courses at basic, intermediate and advanced levels and has fulfilled the required written and practical examinations. In order to maintain this rating, Activator Methods requires their rated doctors to continue with annual continuing education courses to ensure that all Activator doctors are held to the highest standards.


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Alumni Spotlight: Juan Jaen
by Kyah Dubay | Feb 3, 2018 | Alumni Spotlights
"I wonder if I could go to school here." That was Juan Jaen's thought as he walked past the University of Michigan's old chemistry building while visiting from his home city of Madrid (Spain). Anita, his girlfriend at the time, now his wife, replied, "Well, go inside...
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Lab X Technologies has announced it has issued a production license to Avid for use of its MADI (Multichannel Audio Digital Interface) IP for the company's MADIX™ Module.
The MADI interface allows professional audio, video, live and broadcast technology manufacturers to develop products with flexible I/O interfaces, with minimal modifications to host interface codes.
Using Fiber and Coaxial connections, MADI interfaces with up to 64 channels of digital audio in both directions. With a Field Programmable Gate Array (FPGA) core, the MADIX's electrical and mechanical interface is compatible with all Lab X MIX network I/O modules.
"Our VENUE customers demand high reliability and standards-based connectivity for their critical live applications," said David Gibbons, VP of live sound, Avid. "Lab X's FPGA-based solution is cost-effective, highly interoperable and allows us to implement the technology quickly. We've successfully partnered with Lab X several times, so we immediately turned to them to help us deliver this.


Today's POP RESCUE from a fate unknown, is the 1995 album Medusa from Eurythmics vocalist Annie Lennox.
I should admit here, that I'm not particularly a fan of Annie Lennox. I don't really know why – I just can't put my finger on it.
I remember this album selling by the bucket load when I worked in a record store during the 1990s, and I'm also a big fan of the album artwork. It's only my unreasonable discomfort with Lennox that stopped me from buying it 19 years ago.
Medusa was hugely commercially successful, but whether this was because of Annie Lennox or because it was an album made up entirely of cover versions, remains a mystery. Either way, it was highly successful for Lennox, and spawned four singles.
Starting with the first single, No More 'I Love Yous', this track was the big hit, and it is also a fantastic showcase for her vocals. Throw this alongside the vaudeville styled video (see below), and you can see how it grabbed attention in February 1995.
Next up is Take Me To The River, a cover that has been done by many other artists, and this version doesn't necessarily tread new water.
Second single, a cover of Procol Harum's A Whiter Shade Of Pale, suits Lennox's vocals pretty well, and it's sympathetic to the original. The inclusion of some delicate harp plucking is nice, but the track is not really a track that really goes anywhere (this, and the original version).
Don't Let It Bring You Down is a nice use of Lennox's higher vocals again, but it is otherwise fairly dull. Musically it doesn't really do anything until nearer the end when the piano and backing vocals join in.
Train In Vain opens with beats and double bass, and feels a lot more up-beat than what we've heard so far.
The up-beat tempo continues with I Can't Get Next To You, with Spanish guitar and string section. So far, this is my second favourite track after No More 'I Love Yous'.
Downtown Lights is the next track, and it's also the longest one on the album, weighing in at almost 7 boring minutes.
A cover of The Persuaders song Thin Line Between Love And Hate is up next, with a nice bass line, synth, harmonica, and scattered strings, set against a low vocal line. This is actually quite a nice chilled out track.
Some delicate guitar bring in the next track, Waiting In Vain – the third single from the album. Whilst it's an okay track, it rarely goes into new territory for this album.
Final track Something So Right was the fourth and final single, and it's essentially a sleepy end to this somewhat dreary album.
Where is Annie Lennox now?
Annie has continued to write and record music as part of Eurythmics and as a solo artist since the release of Medusa in 1995.
She is due to release her 7th solo album Nostalgia (a collection of 1930s and 1940s songs) in October 2014.
Posted in 1990s, Annie LennoxTagged 1995, A Whiter Shade Of Pale, Eurythmics, Medusa, No More I Love You's, Procol Harum, review, Something So Right, Waiting In VainBookmark the permalink.
I think 2/5 stars is too harsh! It should have been 3 or 4 just because "No More 'I Love Yous'" is on this album! Annie rules!


The appellants (B) appealed against their convictions for murder.
The wife (R) of the victim (V) had given evidence identifying B as the murderers, but there were inconsistencies in her evidence. B gave statements in which they admitted killing V, but they later alleged that they had been forced to sign the statements. The prosecution also relied on oral statements made by B in which they admitted involvement. The judge's directions included a comment that the cause of V's death had only been known after the post-mortem, yet B had known V had hanged when they made their statements before the post-mortem. Following the dismissal of their appeals against conviction by the Court of Appeal of Trinidad and Tobago, B sought to adduce psychiatric evidence before the Privy Council that they were of low intelligence, which could have affected their fitness to plead. The issues were (i) whether a direction in accordance with R. v Mushtaq (Ashfaq Ahmed)  UKHL 25,  1 W.L.R. 1513should have been given in relation to B's confessions; (ii) the effect of the direction on special knowledge as to the cause of death; (iii) the appropriate directions regarding B's alleged oral admission; (iv) whether R's evidence had called for a special caution; (v) whether B should be allowed to raise fitness to plead for the first time before the Privy Council; (vi) if there had been a material misdirection, whether to apply the proviso in the Supreme Court of Judicature Act 1962 (Trinidad and Tobago) s.44(1), namely that an appeal could be dismissed if the court considered that no substantial miscarriage of justice had occurred, notwithstanding that the point raised in the appeal could be decided in the appellant's favour.
(1) A Mushtaq direction had been required. All three conditions had been present: it had been open to the jury to conclude that B had made the statements and that the statements were true, and there was evidence on which they could have concluded that B had signed as a result of oppression. It was difficult to understand why, in R. v Wizzard (Barry)  UKPC 21, it had been considered that the fact that the appellant had made an unsworn statement from the dock denying that he had made the confession meant that a Mushtaq direction was not required. Simply because the appellant denied making the statement did not mean that the jury could not find that he had done so, Wizzard considered. However, the judge's direction had effectively removed the option that the jury could act on the statements if they found they had been signed as a result of improper police conduct, even if they believed the statements to be true; it therefore constituted a Mushtaq direction, Mushtaq considered (see paras 15-19 of judgment). (2) During B's interviews, the police had already been treating the case as a hanging because of R's evidence. The judge had plainly been wrong to imply that the sequence of admissions and post-mortem results indicated B's special knowledge. However, no miscarriage of justice had been caused because of the strength of other evidence (paras 21-22). (3) Whether a warning about relying on an oral statement was required depended heavily on the facts of each case. B's written statements and R's evidence formed the essential case, while the oral statements were of little importance. To single out the oral statements as deserving special care would have been potentially misleading (paras 26-27). (4) The need for a special caution about the approach to a witness's evidence derived from the possibility that she had a motive for giving an untruthful account. As B had not made an explicit case that R's evidence was tainted by improper motive, and R had never been given the opportunity to deal with that suggestion, it would be highly questionable whether the judge could properly have raised it. Accordingly, no specific caution had been required (paras 30-33). (5) It was not to be assumed that even highly persuasive evidence produced for the first time at the final appeal stage would be admitted, Brown v Trinidad and Tobago  UKPC 2applied. However, the psychiatrists were distinguished and their opinions that B might have been unfit to plead raised a substantial issue about the fairness of their trial and the safety of their convictions. Their further opinions that the reliability of B's confessions could have been affected by their intellectual impairment and that a defence of diminished responsibility could have been raised required that the appeals be remitted to the Court of Appeal (paras 48-49). (6) The only material misdirection had been on special knowledge, and the jury would have convicted regardless of whether that direction had been given. The essential prosecution case had rested on B's statements and R's evidence. On the evidence that had been available at trial, it was impossible to say that the relevant statements had been wrongly admitted or that the jury had been wrong to find that they provided clear evidence of B's guilt. Accordingly, the Court of Appeal had properly applied the proviso (para.58).
Although it was not to be assumed that even highly persuasive evidence produced for the first time at the final appeal stage would be admitted, evidence from distinguished psychiatrists indicated that the low intelligence of two men convicted of murder might have affected their fitness to plead. That raised a substantial issue about the fairness of their trial and the safety of their convictions; the psychiatrists' further opinions that the reliability of the men's confessions could have been affected by their intellectual impairment, and that a defence of diminished responsibility could have been raised, required that the appeals be remitted to the Court of Appeal of Trinidad and Tobago.


text:
SP6PBB – w latach 70. i 80. XX wieku jeden z najprężniejszych i najgłośniejszych klubów krótkofalarskich w Polsce. Klub powstał w roku 1968 z inicjatywy entuzjastów krótkofalarstwa Mariana Wrzoska SP6BYE (SK) i Tomasza Wizy SP5BCA (obecnie SP7BCA).

Z klubem współpracowało wielu kadetów, podoficerów i chorążych łączności.

W związku z systemem antenowym, którym klub dysponował, niekiedy przez kolegów nazywany był Radiem Legnica – z racji jego słyszalności na całym świecie.

Klub działał przy Centralnym Ośrodku Szkolenia Wojsk Łączności w Legnicy. SP6PBB mógł poszczycić się ponad 60 000 łączności potwierdzonych kartami QSL oraz potwierdzonymi prawie wszystkimi krajami zaliczanymi do DXCC.

Linki zewnętrzne
 Historia klubu SP5PSL (s. 9)

Przypisy

6

redpajama_set_name: RedPajamaWikipedia


Low estrogen (oestrogen) levels can cause numerous health issues. Though the estrogen (oestrogen) hormone is commonly associated with perimenopausal and menopause, low estrogen (oestrogen) levels can occur for other reasons.
Estrogen (oestrogen) replacement therapy, or ERT, provides relief from the many debilitating symptoms caused by low estrogen (oestrogen) levels. If you're interested in Estrogen (Oestrogen) Replacement Therapy, please call (732) 338-0577 or contact Forever Young Complete Healthcare online.
Low estrogen (oestrogen) levels affect everyone differently. You may experience all of these symptoms or just one. Similarly, low estrogen (oestrogen) levels can occur for any number of reasons. They can happen naturally due to age, illness, as a part of menopause or due to the surgical removal of ovaries (hysterectomy).
Estrogen (oestrogen) replacement therapy (ERT) is a form of hormone replacement therapy, which is commonly referred to as HRT. To determine if ERT is necessary, your doctor will perform a simple test to measure your body's hormone levels. This can include a blood test, urine test or saliva test.
Hormone Replacement Therapy typically uses synthetic hormones that are similar to those your body naturally produces. A safer, more natural alternative is bioidentical hormone replacement therapy, or BHRT. BHRT uses estrogen (oestrogen) that's biologically and chemically identical to what naturally occurs in your body.
Deciding on the right treatment depends on your needs and comfort level. The best course of action is to talk with a doctor about Estrogen (Oestrogen) Replacement methods.
Estrogen (Oestrogen) Replacement Therapy is a safe way to treat low levels of estrogen (oestrogen). Regardless, it's very important to let your doctor know if you're suffering from any conditions that may interfere with the treatment.
Depending on your type of therapy, your doctor may have other advice. To give an example, some Estrogen (Oestrogen) Replacement patches shouldn't be exposed to direct sunlight.
If you're struggling with menopause or dealing with low estrogen (oestrogen) symptoms like hot flashes (hot flushes), joint pain and depression, estrogen (oestrogen) hormone replacement therapy (ERT) may be the answer. Please call (732) 338-0577 or contact Forever Young Complete Healthcare online.
Estrogen Replacement Therapy Consultation Today!


text:
Rong Baisheng
Chinese architect and civil engineer
This is a Chinese name; the family name is Rong.
容柏生
(1930-08-27)27 August 1930
South China Institute of Technology
Architect, Civil Engineer
Shenzhen Shangri-La Hotel (1981)
Guangdong International Building (1985)
Rong Baisheng (Chinese: 容柏生; 27 August 1930 – 11 May 2019) was a Chinese architect and civil engineer. A pioneer in skyscraper design and construction in China, he was elected an inaugural member of the Chinese Academy of Engineering in 1995. His works include the Guangdong International Building, which was China's tallest building when completed in 1990, and the Shenzhen Shangri-La Hotel (1981).
Rong was born on 27 August 1930[1] in Guangzhou, Guangdong, Republic of China, with his ancestral home in Nanping, Zhuhai.[2] His father was in the military, and the family became refugees during the Second Sino-Japanese War. He was frequently on the run with his mother and siblings to evade Japanese occupation.[2]
After the surrender of Japan in 1945, Rong returned to Guangzhou and resumed his education.[2] In September 1949, he entered the Civil Engineering Department of Lingnan University (Guangzhou).[3] In 1952, when the Communist government reorganized China's higher education according to the Soviet model, Lingnan's engineering departments became part of the newly established South China Institute of Technology (now South China University of Technology), and Rong was a member of the first class that graduated from the university in July 1953.[2][3]
Upon graduation from university, Rong worked at the Guangdong Provincial Architectural Design and Research Institute from 1953 to 1958.[4] From January 1958 to January 1972, he taught for 14 years at the Guangdong Provincial Architecture and Engineering School. He returned to the Guangdong Provincial Architectural Design and Research Institute in 1972.[4] After working for decades at the state-owned company, he started his own firm, RBS Architectural Engineering Design Associates, in January 2003.[3][4]
Guangdong International Building, designed in 1985, completed in 1990
In the 1970s, Rong began researching the structural design of skyscrapers, and devised a complete system of methodology and computer programs.[1] With the commencement of the reform and opening era, Rong's career prospered in the 1980s. He designed the Shenzhen Asia Hotel (now Shangri-La Hotel) in 1981. The 33-story building was a landmark of Shenzhen at the time, and won a Science and Technology Progress Award from the Ministry of Construction of China.[2]
In 1985, Rong designed the 200-meter, 63-story Guangdong International Building using innovative designs and technologies.[2][5] When completed in 1990, it was the tallest building in China and the first 200-meter skyscraper in the country.[6] It won a National Design Gold Medal, the Zhan Tianyou Civil Engineering Award, and the State Science and Technology Progress Award (Second Class).[2][5] Recognized as a pioneer in skyscraper design and construction in China, Rong was elected an inaugural member of the Chinese Academy of Engineering in 1995.[2][3]
Rong died in Guangzhou, China on 11 May 2019, at the age of 88.[2][3]
^ a b "容柏生 基本信息". Chinese Academy of Engineering. Retrieved 2019-05-13.
^ a b c d e f g h i 苏海伦 (2019-05-12). "设计广东国际大厦"63层"的容柏生走了!系土生土长的广州院士". Sohu (in Chinese). Retrieved 2019-05-13.
^ a b c d e Yue, Huairang (2019-05-12). "中国工程院院士、中国工程设计大师容柏生逝世,享年90岁". The Paper. Retrieved 2019-05-13.
^ a b c "容柏生 主要经历". Chinese Academy of Engineering. Retrieved 2019-05-13.
^ a b "容柏生院士逝世". Guangming Daily. 2019-05-13. Retrieved 2019-05-13.
^ "Top Ten Skyscrapers in China". China Pictorial. Retrieved 2019-05-17.
RBS Architectural Engineering Design Associates
Academicians of the Chinese Academy of Engineering
Ai Xing
Ba Denian
Chen Saijuan
Chen Shilu
Cheng Taining
Dai Fudong
Du Qinghua
Fan Lichu
Fu Zhihuan
Gao Bolong
Gao Changqing
Gu Songfen
Guan De
He Jingtang
He Yousheng
Hou Fusheng
Hou Yunde
Huang Xuhua
Huang Xutao (Thomas Huang)
Jiang Shaoji
Jin Donghan
Jin Yilian
Li Guohao
Li Hengde
Li Jiangang
Li Lianda
Li Sanli
Li Xiaohong
Li Zaiping
Liang Weiyan
Lin Xiangdi
Liu Boli
Liu Dajun
Liu Jingnan
Liu Tonghua
Liu Yuanzhang
Lou Zhicen
Lu Xiaopeng
Min Enze
Ni Weidou
Ning Bin
Pan Jiazheng
Pan Yunhe
Peng Shilu
Peng Sixun
Qian Xuesen
Qian Zhengying
Ruan Xueyu
Sang Guowei
Shao Xianghua
Shen Zuyan
Shi Changxu
Shi Ping
Song Jian
Song Wencong
Sun Baoguo
Sun Jinliang
Sun Wei
Joseph Sung (Shen Zuyao)
Tong Zhipeng
Tu Jida
Wang Daheng
Wang Mengshu
Wang Xuan
Wang Yongzhi
Wang Yupu
Wang Zeshan
Wang Zhenyi
Weng Shilie
Wu Dechang
Wushour Silamu
Xu Delong
Xu Kuangdi
Yan Dongsheng
Yang Jinzong
Yu Songlie
Yuan Longping
Zhang Guangdou
Zhao Wenzhi
Zheng Zhemin
Zhong Denghua
Zhong Nanshan
Zhou Ji
Zhu Guangya
Retrieved from "https://en.wikipedia.org/w/index.php?title=Rong_Baisheng&oldid=904686015"
20th-century Chinese architects
21st-century Chinese architects
Chinese civil engineers
Engineers from Guangdong
Lingnan University (Guangzhou) alumni
Members of the Chinese Academy of Engineering
People from Guangzhou
South China University of Technology alumni


Although I wasn't the first hire at DMA Solutions (see Marci Allen), as one of the original employees to come on board, I've had the great pleasure over our company's fifteen-year history working alongside Dan'l and other team members to develop a successful marketing agency that serves one industry: the fresh produce industry.
As you can imagine, when the company first started, our main goal was to gain traction in the industry as a recognizable and viable marketing service company. We weren't sure how you, the industry, would respond to positioning ourselves as an "agency" so we dubbed ourselves "a marketing boutique." The reason we didn't call ourselves an agency was because at that point, marketing agencies didn't have a great reputation and we were unsure you would trust one to guide your business and brand to new heights. The great news, of course, is that you did.
So many things regarding DMA and the business have changed since 2004, including embracing that we are indeed a marketing agency as opposed to a boutique. In fact, when I started in 2007, Dan'l, Marci and I didn't even have job titles! We were "Managers of Quite A Lot" and we did it fast and furious as we aimed to not only thrive as marketers, but also encourage the use of marketing as a means to increase demand (and down the road, consumption) of fresh fruit and vegetables.
Now, fifteen years later, so many business aspects that helped us launch back then are purely anecdotal and make for great happy hour stories of "the old days at DMA." Thinking back over the years, there have been absolute business challenges that were hard to overcome, that seemed like impossible barriers at the time. We now see how those business challenges have shaped us into the company we are today, and we are able to find gratitude in the journey and the opportunity to learn and sharpen our skillset to become better servants of this industry. Truly, these lessons we learned will keep us around for the next fifteen years—and beyond.
Take a walk down memory lane with us as we reflect on the challenges that have shaped the DMA team into who we are today.
What we know now: You bet it's been risky, and we're not threatened by this reality any longer. We've remained dedicated to fresh even when other businesses and opportunities have come knocking—because what we are NOT passionate about is increasing demand for soft drinks or tobacco. No, we're in the business of increasing demand of fresh fruits and vegetables. Period.
Because we dedicate our time and talent exclusively to fresh, we have become subject matter experts on the services that we provide, and as a result, we are able to provide an extremely high level of service, achieving measurable results for the companies that engage with us.
What we know now: We realized that if we were going to wait to sell our services to people in search of marketing solutions in this niche space, we might be waiting a while. To scale our own growth, and ultimately, increase demand for fresh produce, we decided to start by sharing and giving away what we know. We are, after all, in the market of serving marketers on a budget, who often have little to no marketing support—and zero time to get it all done.
It has been rewarding to understand that our choice to "share first", beginning with the content and free resources that we share on our website and our blog, has been helpful to our fellow marketers in the fresh produce industry. Over the course of a year, we publish approximately 150 blog posts and 8 educational or "how-to" eBooks that include marketing-related material specifically tailored for fresh produce professionals. Although we are a for-profit company, we are first and foremost a helpful resource for people seeking sound and actionable marketing direction in this space.
What we know now: When Mother Nature is in charge, even the most well-laid marketing plans can easily end up in flux in the fresh produce space. From rapidly changing weather patterns and conditions to food recalls, we've been through it all, and we admit that these unforeseen events can be challenging for the professionals charged with navigating them. That's part of why we are so dedicated to developing a family-oriented business culture for the people who choose to dedicate their careers to the future of fresh—because truthfully, we've learned that this work ain't for the faint of heart, and it isn't for everyone.
What we know now: From a digital marketing perspective, people are becoming increasingly vocal about their complaints, compliments and questions (note: these are categories that we consistently track) on social media and through company websites. When they reach out to company or brand, they expect a timely response. As the marketers on the front line of this engagement opportunity with consumers, our work as marketers never sleeps. Successful team members at DMA appreciate the uniqueness of this industry and choose to "lean in" to its benefits versus focusing on the possibility of a tragedy. That said, we also understand that we must always be at the ready, just in case.
What we know now: We've never quite known of a produce company with a limitless budget, and we've learned how to serve companies with just about any budget in mind. Over the years, we've viewed this as a huge opportunity to start with a smaller spend and make a big impact. When this happens, history dictates that more money becomes available for the next project. This limitation has simply made our team stronger over the years, forcing us to be resourceful, thoughtful, smarter marketers.
What we know now: We are dedicated to finding and shaping the next generation of fresh produce industry talent. While "fresh" is certainly attractive to the upcoming generations, the reality of career here requires a unique perspective and one that is most often rare. Whether we are recruiting locally in our hometown of Dallas, TX, participating in industry-wide recruiting efforts or through the Almy family's foundation at Texas A&M University (see Aggies for Fresh), identifying the people who will continue our work and mission to increase demand of fresh fruits and vegetables to tomorrow's consumer is perhaps the most important work we will do in our career. At the end of the day, this is the legacy that we hope to build as an organization.
Along the way, we've slowly but surely adapted our business practices and mindsets to better serve the industry, our clients and our team. As we look ahead, we see more opportunity for growth as we continue to recruit talent and educate our own industry professionals as well as consumers about the game-changing benefits fresh fruits and vegetables can bring to people and communities. It is an absolute pleasure to serve you, fresh produce. We look forward to many more years to come!


NASA's Centennial Challenges prize program is seeking new ideas for prizes and new partner organizations. The question remains whether Congress provide allocate money for new challenges. Funding has been hit or miss (mostly miss) for the last decade.
Current information about Centennial Challenges is available at www.nasa.gov/challenges. The new Notice of Opportunity is available here.
Tethers Unlimited has received a $500,000 Phase II award from the NASA Institute of Advanced Concepts to continue work on Spiderfab, a system for 3D printing large structures in space. The Bothell, Washington-based company began work on Spiderfab under a $100,000 NIAC Phase I award last year.
"As NASA begins a new chapter in exploration, we're investing in these seed-corn advanced concepts of next-generation technologies that will truly transform how we investigate and learn about our universe," said Michael Gazarik, NASA associate administrator for space technology.
Spiderfab combines the techniques of fused deposition modeling (FDM) with methods derived from automated composite layup to enable rapid construction of very large, lightweight, high-strength, lattice-like structures with both compressive and tensile elements. SpiderFab would enable structures to be launched in extremely compact form as raw feedstock, which would be used to create structures optimized for the microgravity environment rather than the launch environment. The technology could also evolve to use orbital debris and extraterrestrial materials as feedstock.


If you hate shopping for individual dental insurance plans, you're not alone. After all, with all of the choices out there, it can seem like a never-ending task!
"Is this plan affordable all the way around?"
Some dental insurance for individuals looks great on the surface, but then you realize there are a ton of "hidden" charges - like sky-high deductibles, copays for everything under the sun, and a bunch of exclusions. Sure, the monthly premium payments might be low, but you're going to wind up paying a ton of money if you ever need to actually use your benefits!
When you're shopping around for individual dental insurance plans, be sure to look at more than just the monthly premium payment. You'll have to read all of the fine print to get a clear idea of what kind of expenses you'll actually be dealing with.
"Will everyone in my house be covered under this plan?"
If you have a spouse and kids, getting a family dental plan is a much better buy than trying to find an individual plan for everyone in your house. With a family dental plan, you'll wind up getting to take advantage of deals and savings that you never could have gotten under an individual plan.
But don't blindly assume that all individual dental insurance plans can expand to include everyone in your household. Some can, but others can't. You'll have to do your homework before you sign on the dotted line. Otherwise, you might end up being awfully surprised later!
"Does this dental individual policy come with vision insurance?"
If you're looking for the best buy, look for dental insurance for individuals that comes bundled together with vision coverage. After all, most health insurance policies don't include either one, so you're probably in the market for both of them anyways. By bundling a dental individual plan with vision coverage, you'll likely get to save money on both policies!
"Does this cover everything it needs to?"
All individual dental insurance plans are different. Some may offer affordable prices - but make up for it by offering cheap coverage. Before you sign up for a specific policy, you'll need to make sure that it covers all of your needs. For example, if you think you might need braces soon, make sure that your policy comes with orthodontic coverage.