text:
"A couple of fastballs tonight that just caught too much of the plate," Swanson said after the start. "Moving forward, I just have to minimize the amount of plate that I'm catching with them, whether that's throwing a little bit more inside, a little bit more outside, top of the zone, bottom of the zone. Adjustments I need to make moving forward, and that's what I'm going to do."
Servais praised Swanson for making adjustments and staying aggressive in the strike zone when opposing offenses have hit him well. However, he's lacked consistency and teams have taken advantage.
"Give him an opportunity to kind of regroup," Servais said. "He got hit around a little bit. Certainly saw it (Thursday) night. Kind of got cornered into some fastball counts and everybody knows that's his pitch, and they got on it. He'll make a concerted effort to work on the off-speed pitches down there.
"I will say, I saw some improvement with his slider. I saw some decent changeups. But, just the consistency of it throughout an entire outing, you've got to have it at this level."
The Mariners are considering several options to fill Swanson's rotation spot but no definitive decisions were made Friday.
Seattle ace Marco Gonzales was projected to start Friday night, LeBlanc is scheduled for Saturday, and Yusei Kikuchi for Sunday's finale against Minnesota. Mike Leake is projected to pitch the opener against the Rangers on the road Monday before Swanson's turn comes up again.
"Still up for discussion a little bit who takes that turn or where we go there," Servais said. "We'll look internally of course and see who may be able to handle that one."
Mariners top prospect Justus Sheffield was scheduled to pitch Friday night with the Rainiers, and likely wouldn't be called up to start on three days rest unless he makes an abbreviated appearance.
Rainiers left-hander Tommy Milone (4-2, 3.83) pitched Thursday night, and would likely be available should Seattle decide to promote from Triple-A. He has allowed just five earned runs across his past four starts, and has logged more starts (eight) and innings (49 1/3) than any other Rainiers pitcher this season. However, he would have to be added to the 40-man roster.
Seattle could also opt for a bullpen day -- the team is staffed with 10 relievers currently.
"We could," Servais said. "Or bring somebody up and not expect them to go six, seven innings, but get the game going and go from there. You could do a lot of different things, but we haven't made a decision."
The outcome of Friday night's game could also impact the decision as the Mariners will have to make another roster move Saturday to reactivate LeBlanc ahead of his start.
BULLPEN BOOST
Seattle's bullpen has seen just as much, if not more, turnover than its starting rotation during this homestand.
Right-hander Parkel Markel was promoted from Tacoma on Sunday, and has since made his MLB debut, and Dan Altavilla was called up and optioned back to Double-A Arkansas in the span of one day. Right-hander Austin Adams was called up from Tacoma to replace him Monday.
Right-handed relievers Matt Festa and Ryan Garton were recalled from Tacoma in moves corresponding with Swanson's on Friday, while left-hander Zac Rosscup was designated for assignment.
"Those guys have gone multiple innings," Servais said of Garton and Festa, which plays well into the structure of Seattle's bullpen.
Servais said the decision to DFA Rosscup had a lot to do with that setup, and needing relievers who can remain in games across more than one frame.
"Zac really is a left-on-left guy," Servais said. "That's what he's good at. He's got the left-handed breaking ball. We're not really built that way. We need guys that can go out and pitch for one-plus, two innings."
Earlier Friday, the Mariners claimed right-hander Andrew Moore off waivers from the Giants, and designated right-hander Nick Rumbelow for assignment. Moore will report to Arkansas.
"We're going to see a lot of players continue to join our roster as this thing moves forward," Servais said. "There will be some turnover in our roster. We knew that when the season started."
Lauren Smith: 360-754-5473, @smithlm12
Seattle Mariners manager Scott Servais pulls starting pitcher Erik Swanson from the game in the fourth inning against the Minnesota Twins of a baseball game, Thursday, May 16, 2019, in Seattle. At center is catcher Omar Narvaez. The Twins won 11-6. Stephen Brashear AP
Lauren Smith covers the Seattle Mariners for The News Tribune. She previously covered high school sports at TNT and The Olympian, beginning in 2015. She is a graduate of the University of Washington and Emerald Ridge High School.
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◄ Search Results Showing Item 3 of 134 Preferred library: Creston Public Library?
Dillard, J. D., (film director.). Latimore, Jacob, 1996- (actor.). Gabriel, Seychelle, 1991- (actor.). Hill, Dul©♭, (actor.). Reid, Storm, 2003- (actor.). Universal Pictures Home Entertainment (Firm), (publisher.). WWE Studios. (Added Author). BH Tilt (Firm) (Added Author). Jacob Latimore, Seychelle Gabriel, Dule Hill, Storm Reid, Sasheer Zamata, Brandon Johnson, Cameron Esposito. (Cast).
Physical Description: 1 videodisc (90 min.) sound, color ; 4 3/4 in.
Participant or Performer Note: Jacob Latimore, Seychelle Gabriel, Dule Hill, Storm Reid, Sasheer Zamata, Brandon Johnson, Cameron Esposito.
Summary, etc.: Left to care for his little sister after their parents' passing, a young street magician turns to illegal activities to keep a roof over their heads. He is forced to use his magic and a brilliant mind to save his sister when he gets in too deep and she is kidnapped.
MPAA rating: R; for language throughout, drug content and some violence.
DVD, region 1, NTSC, wide screen (2.40:1); Dolby digital 5.1, Dolby digital 2.0; described video.


Strongest brazing materials for titanium?
What are the strongest brazing materials for titanium?
The main materials I would like to use would be copper or silver, in which case I would like to ask which would form a stronger bond with titanium. Otherwise what are the strongest bond forming materials for brazing nickel titanium wire to titanium?
To give at least some context to this. Titanium is generally considered 'exotic' for welding purposes as it is quite sensitive to both temperature change and contamination by atmospheric gasses, even at temperatures significantly below its melting point.
Like aluminium, titanium is quite reactive but protects itself from corrosion by formation of a stable oxide surface and any welding, brazing or soldering process will inevitably involve removing this layer.
Titanium can be TIG welded to itself without too much difficulty but this definitely comes under the category of 'advanced' welding in terms of both operator skill and equipment needed. In particular it needs good shielding on both sides of the weld. Indeed in some cases it may be preferable to weld it under an entirely inert atmosphere. The weldability also depends on the alloy with high alloy multi-phase alloys being more difficult.
Titanium can be brazed with the right filler and flux. Because of its reactivity vacuum brazing is an attractive option.
You might get away with using a low temperature silver solder with a fairly active flux but in general high strength brazed joints will need to be done under vacuum or an inert atmosphere.
Bear in mind though that titanium will burn in air if it gets hot enough.
Depending on your application you might want to to consider mechanical methods such as rivets or screws or look at adhesive joints.
On one hand brazing can be a good way to attach wires to much larger metal parts because there is much less chance of melting the wire and it can form a neat and convenient joint. However it is less suitable for highly stressed applications for a couple of reasons.
The brazing filler usually has a significantly lower strength than the base metal. This may not matter in certain types of joints (eg bicycle frames) where the joint is designed so that the contact area is much larger than the section of the members being joined but joining wire to a flat surface is not so good.
Brazed joints are strongest when there is a relatively small and consistent gap between the surfaces being joined. This is hard to achieve with wire.
Wire derives much of its strength from the drawing process (ie work hardening) so heating to brazing temperatures may well significantly reduce its strength.
Certainly brazing load bearing wires is not something that is seen very often. It is much more common to see some sort of mechanical (eg pressed, crimped or spliced) terminator....think bike brake cables and guitar strings. I'm not saying that it won't work but it doesn't sound like the best way to proceed to me.
One possibility would be to put an eye or ferrule on the end of the wire and TIG weld an attachment point to the joint, this is actually not that far off how biological tendon-bone attachments work.
In terms of steel vs titanium, you will certainly find steel a lot easier to work with, especially in the proof of concept stage of development where it is likely that you will be making a lot of changes to the prototypes. There is also a certain amount of middle ground between mild steel and titanium in the shape of high strength steels like chrome-moly alloys. It is certainly safe to say that there are a lot of difficulties associated in manufacturing in titanium.
Not the answer you're looking for? Browse other questions tagged welding or ask your own question.
What materials or techniques can I use to reduce this electrical effect when building spotwelding tables?
Schaeffler, De Long, and WRC welding diagrams - which steels can be used?


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text:
Student's Published Works 
LWL | Rhea Chadha
Nov 09, 2022 Posted by: HSA Tutoring
Newest Student Article
Inspiring Indian Women Authors: Creating a Supportive Environment
Rhea Chadha
Published: 09 November 2022 | Download
Student's Published Works
This exploratory research aims to get a high-level understanding of the factors that encourage or discourage the writing efforts of Indian women authors. A list of such factors was first obtained through qualitative secondary research, and both quantitative and qualitative feedback was obtained on these factors by designing a questionnaire that was administered to an illustrative set of Indian women authors. The study was designed to determine the average percentage scores for encouraging and discouraging factors for each respondent, and also whether a majority or minority of respondents experienced each particular factor. The results indicate that a majority of the survey respondents faced an overall unsupportive environment in their creative writing efforts.
Keywords: Learning India, women authors, encouraging/discouraging factors, supportive/unsupportive environment
India has a rich literary tradition. The Mahabharata, The Ramayana, The Gita, numerous Vedas and Upanishads are amongst the most famous texts, but there are countless more. Writing is seeing a boom even in current times. According to an article in the Financial Express by Dar (2022, pp. 5), the report titled 'Value proposition of Indian publishing', pegged the Indian publishing industry at ₹500 billion in 2019 and projected it would reach ₹800 billion by 2024. On those lines, it is worth mentioning that according to an article in The Hindu by Salam (2022), Geetanjali Shree has recently become the first Indian author to win the prestigious International Booker Prize for the translation of her Hindi novel, Ret Samadhi.
However, the representation of women authors in Indian publishing remains low. In an article in the Times of India (TNN, 2019), it is mentioned that the HT-Nielsen bestsellers list for India comprises mostly male authors whereas the NY Times' list comprises mostly women authors. This difference could be due to several factors such as lack of interest, lack of creativity, or perhaps structural biases in the system which discourage Indian women authors. Erica Jong had said, "There is still the feeling that women's writing is a lesser class of writing…that what women know about is a less category of knowledge". As the author of this study, when I co-authored the book 'Life as a Teacher' on learning from all experiences, I did not experience such biases but did encounter a couple of challenges which motivated me to dig deeper into this topic.
The purpose of this research study is to determine factors which either discourage or encourage women authors, and to survey a few women authors to analyse the kind of environment - whether supportive or unsupportive - that they experience.
The hypothesis is that the environment being experienced by these authors is 'Unsupportive'. If yes, then that would most likely explain the low representation of women in Indian writing.
The study consisted of three steps:
Step 1: Determining factors that encourage or discourage women writers (Secondary Research)
Discussions with a few women authors and a review of articles appearing in papers, journals etc. was conducted to create a high-level list of factors that influence the writing propensities of women authors. These were then classified into two groups: factors that encourage and factors that discourage writing by Indian women authors. The classification resulted in a list of five factors that encourage Indian women writers and seven factors that discourage them.
Group I: List of factors that encourage Indian women authors
The list - and explanations - of factors that provide encouragement includes:
Strong background/family support: Encouragement is provided by the family and domestic engagements are shared.
Availability of mentors/sponsors: People who guide throughout the publishing process and support the author.
Opportunities/programs to encourage development of talent: These comprise workshops at literature festivals, opportunities at schools or colleges and/or government-offered programs to express writing.
Awards/recognition for creative writing efforts: Recognition for being a first-time author or awards by educational bodies.
Technological Advances that are simplifying the publishing process and removing intermediaries: E-publishing options with wider reach and revenue potential.
These factors, taken together, create a 'Supportive' environment.
Group II: List of factors that discourage Indian women authors
The list of factors that result in discouragement includes:
Gender bias against women writers: This could be in the form of women not being encouraged to write or being discouraged from pursuing writing.
Lack of role models: Having very few Indian women authors to look up to.
Overall low female representation in various fields: For example, while the proportion of female managers in Asia has increased from 20% to 25%, little progress has been made beyond this since 2016 (Financial Express, 2022). This, by itself, could explain the lower proportion of women writers in the overall population of writers.
Unfavourable publishing ecosystems: Budding women writers may lack knowledge of publishing ecosystems or could experience lack of support. This could perhaps be due to focus on limited genres.
Low importance of literature as a profession: The focus may be more on academics, and reading/writing may be considered a pastime rather than a full-time vocation.
The perception that writing is substandard or unremunerative: Allegedly, Margaret Atwood worried that her failure to have a nervous collapse was a sign of a substandard writer (Anantharaman, 2022). Since writing need not always provide a stable and secure income, it may discourage writing efforts.
Language barriers to writing: Writing in regional languages in a country as diverse as India is unappreciated and regional authors don't tend to reach the mainstream or masses. Very few have the conviction of Geetanjali Shree to say that their creative writing is exclusively in Hindi (Jha, 2022).
These factors, taken together, create an 'Unsupportive' environment.
Step 2: Scoring each factor (Primary Research)
The output of Step 1 was used to develop a survey questionnaire to which detailed responses were sought either over a call or via email from 30 Indian women authors. Responses were received from 15 women authors. For each respondent, the factors were scored in the following manner:
The factor was scored as '1' if it resonated with the respondent's personal experience.
It was scored as '0.5' if it partially resonated with the respondent's experience.
It was scored '0' if the factor did not resonate with the respondent's experience.
Step 3: Analysis Design to determine whether women authors experience a 'Supportive' or 'Unsupportive' environment
Step 3.1 Analysis for each respondent across factors
The responses from each respondent were then consolidated in a worksheet. For each respondent, Average (percentage) Scores were calculated:
The list of 5 encouraging factors (Group I) [Average Percentage Supportive Score], and
The list of 7 discouraging factors (Group II) [Average Percentage Unsupportive Score].
Step 3.2 Definition and Implication of 'Net Score'
The 'Net Score' was then calculated as the difference between the Average Percentage Supportive Score (APSS) and the Average Percentage Unsupportive Score (APUS).
Net Score = APSS - APUS
The implications of the Net Score are as follows:
A positive Net Score will imply that the respondent, on average, experienced a 'Supportive' environment.
A zero Net Score will imply that the respondent experienced a Net Neutral environment.
A negative Net Score will imply that the respondent experienced an 'Unsupportive' environment.
Moreover, if the Net Score (positive or negative) has a magnitude of 25% or higher, then the degree of impact of the Net Score would be considered 'High', else it would be considered 'Low'.
Step 3.3 Analysis for each factor across the entire group of respondents
The percentage of respondents who experienced each factor was determined ('Total Respondent Percentage' or TRP). if:
TRP > 66%, the factor was experienced by a 'Majority' of the respondents
TRP between 33% and 66%, the factor was experienced by a 'Moderate' number of the respondents
TRP < 33%, the factor was experienced by a 'Minority' of the respondents
The results were then analysed.
The results are as described below:
Analysis of Net Score
A majority of the respondents (73%) had a 'Net Score' that was negative, implying that a majority of Indian women authors experienced an overall 'Unsupportive' environment in their writing efforts. The analysis also indicates that 33% of the respondents experienced a 'High' level of discouragement, and an additional 40% experienced a 'Low' level of discouragement. The remaining 27% of respondents experienced 'High' and 'Low' levels of encouragement in equal measure i.e., 13.5% experienced 'High' levels of encouragement and 13.5% experienced 'Low' levels of encouragement.
Group of Factors that Encourage
The analysis indicates that within the group of factors that encouraged Indian women authors, the two factors that were experienced by a 'Majority' of the respondents are:
'Strong background/family support'. One of the respondents mentioned, "Family was always there", and a similar sentiment was shared by 80% of the respondents.
'Technological Advances'
The factors experienced by a 'Moderate' number of respondents include 'Availability of mentors/sponsors', 'Awards/recognition for creative writing efforts' and 'Opportunities/programs to encourage development of talent'. A respondent commented that they had "no clear idea of who to approach, where to go, what to do and when".
Group of Factors that Discourage
The results indicate that within the group of factors that discouraged Indian women authors, the following factors were experienced by a 'Majority' of the respondents:
'Overall low female representation in various fields'. A key sentiment from the respondents was "organisations should go by merit, and not by other considerations".
'Writing perceived as unremunerative'
'Language barriers to writing'
'Low importance of literature as a profession'. One respondent exclaimed "Books are seen as pastimes and efforts to write are frowned upon".
'Lack of role models'
The factor 'Unfavourable publishing ecosystems' was experienced by a 'Moderate' number of respondents.
However, only a 'Minority' of the respondents considered the factor 'Gender bias against women writers' was relevant in their context.
This is an exploratory study and hence the survey was conducted with a focused set of participants. The initial results do seem to indicate that Indian women authors experience an 'Unsupportive' environment. The study should be expanded to a wider base of participants to validate the findings.
Also, the sample of authors consisted of upper middle-class women living in a metropolis. It is not completely representative of the universe of Indian women authors, but is illustrative. Future studies can choose a more diverse set of participants.
The list of factors that encourage and discourage Indian women authors was based on a review of articles in general purpose magazines and newspapers because the literature review did not lead to any scholarly articles which had such a list of relevant factors. When asked, the responding women authors validated these factors and mentioned they couldn't think of any additional ones to add to the list. Moreover, the strength of the factors within each group was considered to be equal and then a simple average score for each group was determined. A research study can be undertaken to determine the comprehensiveness of these factors and their relative strengths.
The study is illustrative of the challenges that Indian women authors experience. All the women authors who responded to the survey mentioned that this topic resonates with them. They mentioned that they would like to see the final research report and would be interested in supporting efforts to promote Indian women authors.
The study emphasizes the need to create an enabling ecosystem for women authors to actualize their writing potential. Steps like instituting rewards are very simple to implement, yet can have a tremendous impact in terms of encouraging emerging talent. This talent should be encouraged from a young age and school programs should be instituted to enable more girl students in their creative writing journeys. To paraphrase Ayn Rand, the question for Indian women authors shouldn't be who is going to let them write, it should be who is going to stop them.
Also, as the overall representation of women in various fields goes up, their contribution to writing efforts in those fields should commensurately increase. Hence, the overall efforts for women empowerment need to be strengthened.
Anantharaman, Latha (2022) Making Everything Illuminated. India Today, May 10-16
Dar, Vaishali (2022) Words & Figures. The Financial Express, May 29
FE Bureau (2022) Higher female representation in management results in positive impact. The Financial Express, March 7
Jha, Aditya Mani (2022) The Past Comes First. India Today, June 7-13
Khan, Faizal (2022) 'It's important kids find some mirror in literature'. The Financial Express
Salam, Ziya Us (2022) Geetanjali Shree's 'Tomb of Sand' first Hindi novel to win International Booker Prize. The Hindu, May 27, https://www.thehindu.com/books/books-authors/geetanjali-shree-wins-international-booker-prize-for-first-hindi-novel-tomb-of-sand/article65465146.ece
Times News Network (2019) Women writers and gender disparity in the publishing world. www.timesofindia.com, https://timesofindia.indiatimes.com/life-style/books/features/women-writers-and-gender-disparity-in-the-publishing-world/articleshow/69201735.cms
I would like to acknowledge all the accomplished Indian women authors who participated in the study not only for providing responses to the survey questions, but also for the detailed discussion and qualitative inputs they provided for enhancing the quality of this paper.
LWL | Brain Implant Maintain Memories
Sep 05, 2022 Posted by: HSA Tutoring
Can a Brain Implant Maintain an Alzheimer's Patient's Memories?
Santiago Lobos Melazzo
Published: 05 September 2022 | Download
Alzheimer's Disease is a neurological degenerative disease that starts in the limbic system and proceeds to decay the rest of the brain. There's no pinpointed cause for the disease but autopsies discovered a correlated malfunction of Tau and Beta-Amyloid proteins in the neurons. The disease has no cure but is constantly being studied with the minimum intent of slowing it down. The brain has various devices that deal with translating some of the senses into electrical impulses to artificially inform the brain of each particular sense. Technology has also advanced to store large amounts of information in the smallest of devices. Combining the current neuro implants with the technology of memory banks, a device can in theory be made so that it sends information to the cortex of the brain so that patients recognize the things they witness at a basic level. Implants would recognize objects and people and activate files with data to inform the patient of what they're presented.
Keywords: Alzheimer's, memory, neurological, degenerative, technology
Alzheimer's Disease is a degenerative disease that affects the brain. The proteins Tau and Beta-Amyloid lose control of the neurons and start making them decay. The first area where this disease strikes is the limbic system and the first sign that announces its arrival is the memory loss and functions related to memory failure. The concept being questioned is if an implant can help relieve the symptoms caused by Alzheimer's. A memory chip or drive that can alternate the functions the limbic system performs in the brain, to keep the patients conscious and the relatives alleviate for a little longer until the disease evolves to the next phases.
The Disease
The degeneration has unknown causes, but autopsies have provided a common denominator between diseased Alzheimer's patients. The brains of these people had the proteins Tau and Beta-Amyloid in uncanny situations (Jockers, 2021; U.S. Department of Health and Human Services, 2017). The Tau proteins are macromolecules mainly found in the microtubules of the neurons. When people develop the Alzheimer's disease, the tau proteins unravel from the structure of the microtubules and the unstructured parts of the microtubules start spreading up and pailing in different areas of the neuron (Drummond et al., 2020; Ellison, J. M., 2021; Polan, S., 2020). The Beta-Amyloid comes from the breakdown of a larger protein called Amyloid Prosecutor Protein (APP). The APP is at the neuron's membranes and it is naturally sliced by two enzymes, Beta and Gamma Secretase (ALZFORUM, n.d.). Beta Secretase cleavages the APP through the outer membrane, and the Gamma Secretase cleavages it through the inner membrane. The remaining part of the APP that was cut between the two enzymes is called Beta-Amyloid. It is left with 38 to 40 long amino acids peptide. It floats in between the neurons to be decomposed by the brain's nutrients. In Alzheimer's patients, there is an inexplicable mutation in the Gamma Secretase enzyme which modifies the cut length of the Beta-Amyloid. Instead of being 38 to 40, it becomes 42 amino acids long peptide, thereby being unable to be absorbed by the outer cell environment (Haugabook, S. & Sambamurti, K., 2007). Eventually, these 42 long Beta Amyloids start to opulate outside the neurons and start forming plaques, called Amyloid Plaques. These two protein malfunctions, with unknown causes and no discovered correlation, are the more prominent characteristics of a brain with Alzheimer's disease. When both errors develop, neurons start dying one by one, mainly located in the limbic system, starting with the hippocampus and the entorhinal cortex. The decay of these areas causes the first symptoms to be memory loss, and the further the decaying disease expands the more neural functions patients start to lose (Fidel Romano et al., 2007). The inevitable outcome of suffering the disease is death. There are some treatments to try and slow down the progress but no cure, yet (Long, J. M., & Holtzman, D. M., 2019).
Technology nowadays is being implemented in various ways into the brain. There are not only brain implants but also robots that can perform neurosurgery, in development. Currently, there are brain implants aiding sight and hearing, with more technology under development. The Sight implant was developed in order to allow the blind to see.
Figure 1: Second Sight Orion 1
It uses an external camera where one version has the camera installed in sunglasses. It is connected to a transmitter located in the head in direct contact with the implant in the brain. The device passes the information from what the camera sees into electrical pulses that the implant translates and sends through the cortex. Through this aid, the blind has reported their newly acquired ability to see, although reports also express the need for constant maintenance of the device (Second Sight Orion 1, n.d.). There are also hearing aids that work in a similar way (Devlin, H., 2019); an external device to capture the sound waves and an internal device that translates them into pulses and sends them to the respective part of the brain.
Figure 2: Coclear Implant
Besides these two implants that assist the senses to be felt, there is a new technology developed with the aim to implement synchronization with other technologies, no longer limiting the brain's activity to human functions but to robotic ones as well. Ideas for implants that will have the ability to operate external technologies like phones and/or computers already seem concrete and possible (Kennedy, R., 2021). Though, with all of these brain devices and the complexity of the brain itself, robots are being made in order to operate through the complexities and reduce the risk that could be man-made. The science working with these robots designates it as Precision Automated Neurosurgery, and it is also a work in progress (Qureshi, Y. A. & Mohammadi, B., 2018).
The question is if an implant could possibly maintain the memories of Alzheimer's patients to alleviate the first phase of the disease. Combining the current and future technologies, it might be possible. It is all theoretical but here is how one could possibly see it function: the idea would be to have a memory chip or a transmitter connected to external digital memory, in which the brain can look for information when trying to remember. This would be done by storing information in forms that vision and hearing implants can activate upon detecting similar information. Since the implants can translate information from what they see and hear, information would be stored that could be triggered by what one sees or hears. For example, once someone sees his/her daughter, the visual implant would activate the memory file about the daughter and this file would indicate to the patient that the one he/she sees is his/her daughter. A similar process would be followed with sounds.
The technology has already been tested. We can send information through the brain and make it understand things based on electrical pulses. Additionally, we have devices that can store information in different files. A combination of these can make patients aware of their surroundings.
The device would call upon stored information by visual and sonar activation. However, as technology advances, it could be upgraded into something more. Once it's advanced enough, the implant could allow the download of every lived experience into an upgraded memory bank and provide the patients with an artificial eidetic memory. Although this level of technology would be ideal, first, the principle of the initial device should be successful in its functions; something that won't be easy to accomplish as the complexity of both the brain and the disease can bring numerous conflicts. The brain itself is complex, but the disease apports its own level of unpredictability due to the absence of information. It is unknown how the disease would affect the artificial electrical impulses or how the beta-amyloid plaques might prevent its proper function. However, if nothing unprecedented occurs, the device could work and bring forth tranquillity to the patient's families, allowing the sick to live their lives at their basics until the next phase of the disease takes over the rest of the brain.
The degenerative Alzheimer's Disease, as mysterious as it is, can in theory be appeased by brain implants. The combination of current and future neuro devices allows for the innovation of a single complex device implanted in the brain that could indulge information about the things a patient witnesses, essentially giving the person a sense of recognition as the limbic system decays.
Jockers. (2021). Alzheimer's disease: Symptoms, causes and natural support strategies. DrJockers.com.
https://drjockers.com/alzheimers-disease/
U.S. Department of Health and Human Services. (2017). What happens to the brain in Alzheimer's disease? National Institute on Aging.
https://www.nia.nih.gov/health/what-happens-brain-alzheimers-disease
Drummond, E., Pires, G., MacMurray, C., Askenazi, M., Nayak, S., Bourdon, M., Safar, J., Ueberheide, B., & Wisniewski, T. (2020). Phosphorylated Tau Interactome in the human Alzheimer's disease brain. OUP Academic. Available at: https://academic.oup.com/brain/article/143/9/2803/5893817
Ellison, J. M. (2021). Tau protein and Alzheimer's disease: What's the connection? Tau Protein and Alzheimer's Disease: What's the Connection? | BrightFocus Foundation. https://www.brightfocus.org/alzheimers/article/tau-protein-and-alzheimers-disease-whats-connection
Polan, S. (2020). The study reveals how renegade protein interrupts Brain Cell function in Alzheimer's disease. NYU Langone News. https://nyulangone.org/news/study-reveals-how-renegade-protein-interrupts-brain-cell-function-alzheimers-disease
Haugabook, S., & Sambamurti, K. (2007). Gamma secretase. Gamma Secretase - an overview | ScienceDirect Topics. https://www.sciencedirect.com/topics/neuroscience/gamma-secretase
Fidel Romano, M., Daniela Nissen, M., Maria Del Huerto Paredes, N., & Alberto Parquet, C. (2007). Enfermedad de Alzheimer - UNNE. https://med.unne.edu.ar/revistas/revista175/3_175.pdf
Long, J. M., & Holtzman, D. M. (2019). Alzheimer's disease: An update on pathobiology and treatment strategies. Cell. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778042/
Second Sight Orion 1. (n.d.). Retrieved from https://www.infotecnovision.com/wp-content/uploads/2017/09/Ori%C3%B3n-I-300x300.jpg.
Medgadget. (2016). Retrieved from https://www.medgadget.com/2016/10/second-sights-orion-brain-implant-bypasses-visual-system-let-blind-see.html
Devlin, H. (2019). Scientists create mind-controlled hearing aid. The Guardian. https://www.theguardian.com/society/2019/may/15/scientists-create-mind-controlled-hearing-aid
Cochlear Implant. (n.d.). Retrieved from https://www.mayoclinic.org/-/media/kcms/gbs/patient-consumer/images/2013/08/26/11/03/an01963_ds00172_im03853_ans7_cochlearimplant09thu_jpg.jpg
Kennedy, R. (2021). What is Neuralink? how does the technology work and what can a person do with it? Republic World. https://www.republicworld.com/technology-news/other-tech-news/what-is-neuralink-how-does-the-technology-work-and-what-can-a-person-do-with-it.html
Qureshi, Y. A., & Mohammadi, B. (2018). Robotic oesophagogastric cancer surgery. Annals of the Royal College of Surgeons of England. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5956573/
LWL | Psychology, Machine Learning, and AI
Application of Psychology in Artificial Intelligence and Machine Learning
Siddarth Gupta
Classical and operant conditioning is the basis of learning in psychology and is imperative to the learning habits of humans. One of the objectives of Artificial Intelligence (AI) is to mimic human learning for the creation of a fully functioning artificial human mind and brain. This research paper aims to induce conditioning into Machine Learning (ML) algorithms to design machine intelligence with commonsense and high learning capabilities. We see how stimulus-response and rewards & punishment play an imperious role in reinforcement learning and deep learning - a subpart of machine learning. Although reinforcement learning is similar to operant conditioning, there are still a lot of complexities of the human mind which pose a hindrance to the invention of General Artificial intelligence which has been featured in science fiction stories for over a century. We discover how building algorithms using logic and theoretical knowledge can be influential in the answer to integrating common sense into the environment of machine learning. When we are using reinforcement learning, it explores and exploits the data in the environment and learns by mistake and error. When we apply classical conditioning, the machine can use a loop into three subparts: the first one associates events that occur simultaneously, the second part collects the evidence that a made association is important, and the third recognizes the important association. The ability to recognize prior associations allows for the formation of both evidence for and against the existence of a given relationship, as well as the creation of more complicated associations by recognizing occurrences of strongly associated event pairs as events in and of themselves.
Keywords: Psychology, AI, Machine Learning
I begin the paper with a preface to conditioning and its types like classical conditioning and instrumental conditioning. Further on I explore the idea of machine learning and various types of machine learning which can be incorporated with conditioning such as reinforcement learning. The paper aims to explore the idea of reward, punishment, and stimulus in Artificial Intelligence for the development of common sense and human-like minds and learning habits. The hypothesis that is proposed in the research paper relates to the fact that humans learn from stimulus-to-stimulus association. And in the second part how reinforcement learning is similar to operant conditioning. I have come up with essentially two hypotheses which outline the project in the paper
Hypothesis A
Classical conditioning can be used as a model of its environment to incorporate common sense partially or completely in a machine learning algorithm.
Hypothesis B
Operant conditioning can be used as a model of its principle to replicate the reward and punishment phenomenon in reinforcement learning
Beginning with the psychology aspect, conditioning is a behavioural process whereby certain feedback becomes more frequent/predictable in a given surrounding as a result of reinforcements (Elmer, 2020). Reinforcements typically are a stimulus or reward for the preferred response. It mainly has two types: Classical and Operant conditioning. Classical conditioning is a type of learning that happens unconsciously. When you learn through classical conditioning, an automatic conditioned response is paired with a specific stimulus (Elmer, 2020). (This creates a behaviour, a very famous example is Pavlov's dog experiment in which he explores the concept of dog salivation when seeing food to create a conditioned stimulus in which the dog salivates when he hears a bell or some sound that makes him expect a stimulus like food (Elmer, 2020). Operant conditioning is a method of learning that employs rewards and punishments for behaviour (Cherry, 2020). Through operant conditioning, an association is made between a behaviour and a consequence (whether negative or positive) for that behaviour. For illustration, when lab rats press a switch when a green light is on, they admit a food bullet as a price. When they press the switch when a red light is on, they admit a mild electric shock. As a result, they learn to press the switch when the green light is on and avoid the red light (Cherry, 2020).
In the technological aspect, Artificial Intelligence (AI) is the creation of the stimulation of human-level intelligence in a machine to mimic human beings in real-time (Education, 2022). Machine learning (ML) is referred to as the process by which a machine learns and reacts to its environment and surroundings depending on the data it has been provided and the data it has collected (Education, 2022a). There are various types of machine learning for example supervised learning, unsupervised learning, and reinforcement learning (Education, 2022a). In the paper, reinforcement learning is used as the basis of the research considering that it is a model of the reward and punishment mechanism. In reinforcement learning, an agent (the machine/algorithm) explores and exploits its environment through trial and error to receive the desired results (Education, 2022a). Reinforcement learning is mainly used in autonomous driving, healthcare, and various other fields (Education, 2022a).
Classical conditioning application in Artificial intelligence
Classical conditioning can be considered the model of its surroundings and the stimulus, then common sense knowledge can be designed as a model of classical conditioning to be later incorporated into reinforcement learning from stimulus to stimulus (Anirudh, 2019). By building algorithms of associations, we can essentially build a model of the environment and common sense (Anirudh, 2019). The agent - which is the machine - can be conditioned to react to the reward (being the common-sense knowledge) by forming an interdependence between unconditioned stimulus and conditioned stimuli. We see the feedback loop in which the significant associations are made through three steps of the hierarchy: the first phase connects events that happen at the same time, the second portion gathers evidence that a created connection is significant, and the third party acknowledges the significant connection. The capacity to detect past connections allows for the construction of both evidence for and against the presence of a particular link, as well as the creation of more sophisticated associations by treating the occurrences of highly related event pairs as separate events (Anirudh, 2019). This also creates a hierarchical model of data.
Instrumental learning in Reinforcement learning
Knowing that reinforcement learning is used in situations where there is a reward and punishment, instrumental conditioning is the most ideal learning style present in the field of psychology which can be integrated with machine learning (Poddiachyi, 2020). By principle on the surface, both the phenomena, in theory, follow the same ideology of trial and error, as we see the agent learns through exploration of the environment what to avoid and what to exploit in a given situation. The Law of Effect highlights two key aspects of animal learning that are replicated in RL algorithms (Poddiachyi, 2020). To begin, an algorithm must be selectional, which means it must test many actions and choose one based on the results. Second, the algorithms must be associative, which means that they must link specific situations (states) to actions discovered during the selection phase.
The system is implemented as four modules that reflect the system's key processing phases. These modules are pre-processing, recognition, association, and significance. The pre-processing module converts object movement data into predefined events from which patterns are learned. Existing event patterns are recognized by the recognition module, which creates tokens that reflect those patterns. To create new candidate patterns, the association module associates the pattern tokens depending on their time. Finally, the significance module gathers fresh pattern evidence and evaluates whether a pattern is considered to exist based on classical conditioning. The system is built around a feedback loop that connects the pattern recognition, association, and significance modules. The modules and the data that is exchanged between them are depicted in Figure 1.
The system gradually takes time-frames that include bounding boxes for each object of interest in the observed scene as input. The first module examines these boxes and makes a record of the items' spatial connections. The module then identifies certain differences in spatial connections between each frame and utilises these differences as the fundamental event instances that the recognition system uses to recognize patterns of those events.
Figure 1: Model System
Materials and Research Methodology
This chapter explores the methodology of research. Papers related to the hypothesis was researched on the internet, particularly over Google Scholar. I have formed results and conclusions through them and attempted to build algorithms by creating hypotheses to be integrated into the machine and deep learning processes to build better reinforcement learning.
As result, it is discovered that hypothesis A doesn't fail due to the fact that the presumptions that the positive correlation of exactness between the classical conditioning model and how well the model performed in certain situations failed but some results were in line with the expectations. The model of the three systems did not necessarily fail as the model worked out of the classical conditioning model of fidelity to learn through association. While the data do include some evidence in favour of the hypothesis, it is not clear enough to proclaim the hypothesis as standing or to declare the hypothesis to be disproved. This opens room for further research and speculation through various algorithms, systems, and models. It is also discovered that the model can be used to teach machine learning about common sense knowledge partially. Furthermore, we discover that hypothesis B is more successful than hypothesis A as the reinforcement learning model is based on rewards and punishments. Reinforcement learning has improved further from the law of effort which is the principle based on instrumental learning (Poddiachyi, 2020). We see that the model has been very successful in terms of instrumental learning but also has some aspects which do not concern the operant conditioning model. The exploration phase for an RL algorithm is the selection process, and there are numerous ways to do it. For instance, consider the greedy policy, which stipulates that an agent selects a random action with a chance of and then chooses greedily (the action that provides the greatest immediate reward) with a probability of 1 (Anirudh, 2019). We're attempting to answer The Exploration-Exploitation Dilemma, which states, to put it simply, when one should stop exploring and start exploiting, by steadily reducing during training. Another intriguing aspect is motivation. It is what impacts the intensity and direction of behaviour in instrumental conditioning (Anirudh, 2019). The food was left outside the box in Thorndike's experiment. When the cat escapes from the box, it gets the food, which reinforces the activities it took to get out. Of course, it has nothing to do with reality, but the reward signal is essentially motivation, and the goal is to make the agent's experience gratifying.
Reinforcement learning is the study of how artificial systems may handle challenges involving instrumental conditioning (Anirudh, 2019). Perhaps less clear is the link between reinforcement learning and classical conditioning. Learning to act in a way that maximizes rewards and minimizes punishments, on the other hand, necessitates the capacity to foresee future rewards and punishments (Anirudh, 2019). As a result, most reinforcement-learning systems include this capability. One method for predicting future reinforcements based on temporal differences accounts well for behavioural (e.g., Sutton & Barto, 1990) and neural (e.g., McClure, Berns, & Montague, 2003; O'Doherty, Dayan, Friston, Critchley, & Dolan, 2003; O'Doherty et al., 2004; Schultz, 1998, 2002; Schultz, Dayan, & Montague, 1997; Schultz & Dickinson, 2000; Suri, 2002) findings on classical conditioning.
As hypothesis A is not a complete failure but partial success, the model can be improved and the results can have a large variety of applications, especially in the field of self-driving cars and where stimuli - stimuli response can be a determining factor and help with the development of AI and creating a general AI or even super-powered one eventually.
Hypothesis B can be used incorporated where reinforcement learning is used and directly be used to create an ecosystem for the machine learning program to learn quickly
Yechiam, E., Busemeyer, J. R., Stout, J. C., Bechara, A. (2005). Using cognitive models to map relations between neuropsychological disorders and human decision-making deficits. Psychological Science, 16(12), 973–978.
Alonso, Eduardo & Schmajuk, Nestor A. (September 2012). "Special Issue on Computational Models of Classical Conditioning Guest Editors' Introduction". Learning and Behaviour, 40(3), pages 231–240.
MAIA, T. I. A. G. O. (2009). Reinforcement learning, conditioning, and the brain: Successes and challenges. https://link.springer.com/. Retrieved June 10, 2022, from https://link.springer.com/content/pdf/10.3758%2FCABN.9.4.343.pdf
Cherry, K. (2020, June 4). What is operant conditioning and how does it work? Verywell Mind. Retrieved June 10, 2022, from https://www.verywellmind.com/operant-conditioning-a2-2794863
Elmer, J. (2020, January 8). Classical conditioning: How it works and how it can be applied. Healthline. Retrieved June 10, 2022, from https://www.healthline.com/health/classical-conditioning
Furze, T. A. (2013, July). The Application of Classical Conditioning to the Machine Learning of a Commonsense Knowledge of Visual Events. core.ac.UK. Retrieved June 10, 2022, from https://core.ac.uk/download/pdf/53141335.pdf
Manchev, N. (2021, October). Reinforcement learning introduction: Foundations and use-cases. Reinforcement Learning Introduction: Foundations and Use-Cases. Retrieved June 10, 2022, from https://blog.dominodatalab.com/introduction-to-reinforcement-learning-foundations
Poddiachyi, A. (2020, May 3). Reinforcement learning, brain, and psychology: Classical and instrumental conditioning. Medium. Retrieved June 10, 2022, from https://towardsdatascience.com/reinforcement-learning-brain-and-psychology-part-2-classical-and-instrumental-conditioning-217a4f0a989
The Unlikely Techie. (2020, July 26). Conditioning algorithms: Reinforcement learning - an introduction. The Unlikely Techie. Retrieved June 10, 2022, from https://www.unlikelytechie.com/post/conditioning-algorithms-reinforcement-learning-an-introduction
VK, Anirudh. (2019, July 11). The brains behind AI: How pavlov's Dogs & Weight Loss Tips influenced reinforcement learning. Analytics India Magazine. Retrieved June 10, 2022, from https://analyticsindiamag.com/the-brains-behind-ai-how-pavlovs-dogs-weight-loss-tips-influenced-reinforcement-learning/
Vélez, J. I. (1970, January 1). Machine Learning Based Psychology: Advocating for a data-driven approach. International Journal of Psychological Research. Retrieved June 10, 2022, from https://www.redalyc.org/journal/2990/299067861001/html/
Scott, J. zu. (2019, September 16). Combining AI's power with self-centered human nature could be dangerous. Chatham House – International Affairs Think Tank. Retrieved June 11, 2022, from https://www.chathamhouse.org/2019/03/combining-ais-power-self-centered-human-nature-could-be-dangerous
Frankenfield, J. (2022, March 16). How artificial intelligence works. Investopedia. Retrieved June 11, 2022, from https://www.investopedia.com/terms/a/artificial-intelligence-ai.asp#:~:text=Artificial%20intelligence%20(AI)%20refers%20to,as%20learning%20and%20problem%2Dsolving.
in, B. (2021). Artificial Intelligence. BuiltIn. Retrieved June 11, 2022, from https://builtin.com/artificial-intelligence
Bajaj, P. (2022, June 3). Reinforcement learning. GeeksforGeeks. Retrieved June 11, 2022, from https://www.geeksforgeeks.org/what-is-reinforcement-learning/
Osiński, B. (2022, February 15). What is reinforcement learning? The Complete Guide. deepsense.ai. Retrieved June 11, 2022, from https://deepsense.ai/what-is-reinforcement-learning-the-complete-guide/
B, W. (1913). Apa PsycNet. American Psychological Association. Retrieved June 12, 2022, from https://psycnet.apa.org/record/1926-03227-001
Education, I. C. (2022, July 7). Artificial Intelligence (AI). What-Is-Artificial-Intelligence. https://www.ibm.com/cloud/learn/what-is-artificial-intelligence
Education, I. C. (2022a, July 6). Machine Learning. What Is Machine Learning? https://www.ibm.com/cloud/learn/machine-learning

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: SSRS Execution Service ParameterValue variable index failing SSRS Execution Service ParameterValue variable index failing
I'm trying to use the SSRS Execution Service ParameterValue array without  defining the number of indices. Microsoft's example is this:
http://technet.microsoft.com/en-us/library/reportexecution2005.reportexecutionservice.render.aspx
        ' Prepare report parameter.
        Dim parameters(2) As ParameterValue
    parameters(0) = New ParameterValue()
    parameters(0).Name = "EmpID"
    parameters(0).Value = "288"
    parameters(1) = New ParameterValue()
    parameters(1).Name = "ReportMonth"
    parameters(1).Value = "6" ' June
    parameters(2) = New ParameterValue()
    parameters(2).Name = "ReportYear"
    parameters(2).Value = "2004"

But I want to add a variable number of objects. I want to do something like this:
            ' Prepare report parameter.
            Dim parameters() As ParameterValue
        parameters(0) = New ParameterValue()
        parameters(0).Name = "EmpID"
        parameters(0).Value = "288"
        parameters(1) = New ParameterValue()
        parameters(1).Name = "ReportMonth"
        parameters(1).Value = "6" ' June
        parameters(2) = New ParameterValue()
        parameters(2).Name = "ReportYear"
        parameters(2).Value = "2004"

        For x As Integer = 0 To MyList.Count - 1
            ' Start
            Dim n As Integer = x + 3 ' Start adding values after the last entry
            parametersRdl(n) = New ParameterValue()
            parametersRdl(n).Name = "NameFromMyList"
            parametersRdl(n).Value = MyList(x)
        Next

Obviously I can't define the number of indices in the array, because I don't know who long MyList is. When I remove the number of indices I get this error:
"NullReferenceException was unhandled by user code. Object reference is not set to an instance of an object."  Does anyone have experience with the SSRS ParameterValue object? OR am I doing something wrong with my array building? Hopefully I get an answer that works with ParameterValue.
Any help is appreciated, thanks!

A: You're getting a null reference because your array has not been instantiated. You have to set the size of the array.
If you have access to the MyList object when declaring the array, you can do the following to create an array the size of the list plus three.
' Gives size of three + list count
Dim parameters(MyList.Count + 2) As ParameterValue

If you only have access to the list at a later stage you can use the Resize function
Array.Resize(parameters, parameters.Length + MyList.Count)

A: This function creates a parameter list of SsrsExecutionService.ParameterValue values.  It then adds parameter Names and Values of type ParameterValue() to the list.  At the very    end it does a List.ToArray to put the ParameterValue list into the ParameterValue array that SSRS accepts.
The purpose of this is to avoid creating a ParameterValue array and having to define the size of the index in the array.
You will later pass this parameter array to reporting serives execution service: rs.SetExecutionParameters(parameters, "en-us")
This is also an example of how to send MDX parameters to SSRS.
    Public Function ToMDXParamArray(startDate As String, endDate As String, employeeNames As String, gender As String, ethnicity As String) As SsrsExecutionService.ParameterValue()

        ' The function was passed a comma delited text string of employee names. They need to be split up and added to the parameter array indivudually.
        ' If this were a SQL query the whole string could be passed to a single parameter.
        Dim employeeList() As String = employeeNames.Split(",")

        ' Create a parameter list to hold SsrsExecutionService.ParameterValue values
        Dim paramList As New List(Of SsrsExecutionService.ParameterValue)
        ' Define a single ParameterValue. In SSRS this has Name, Value, and Label fields.
        Dim p As New SsrsExecutionService.ParameterValue()

        ' Create a new ParameterValue
        p = New SsrsExecutionService.ParameterValue()
        ' Assigne a name and value
        p.Name = "StartDate"
        p.Value = "[EmploymentDates].[YearMonthDate].[Month].&[" + startDate + "]"
        ' Add that ParameterValue to the parameter list
        paramList.Add(p)

        p = New SsrsExecutionService.ParameterValue()
        p.Name = "EndDate"
        p.Value = "[EmploymentDates].[YearMonthDate].[Month].&[" + endDate + "]"
        paramList.Add(p)

        p = New SsrsExecutionService.ParameterValue()
        p.Name = "Gender"
        p.Value = "[" + gender + "]"
        paramList.Add(p)

        p = New SsrsExecutionService.ParameterValue()
        p.Name = "Ethnicity"
        p.Value = ethnicity
        paramList.Add(p)

        ' Now add that list of employee names. For Analysis Services/MDX the names have to be added individually. For SQL you pass the entire string to a single parameter.
        ' This loop of an unknown number of employees in employeeList is exactly why you don't want to create a parametersRdl(50) As SsrsExecutionService.ParameterValue with a defined index size.
        For x As Integer = 0 To employeeList.Count - 1
            p = New SsrsExecutionService.ParameterValue()
            p.Name = "ProvidersProviderLocation"
            p.Value = "[Employees].[Employee Store].[Employees].&[" + employeeList(x) + "]"
            paramList.Add(p)
        Next

        ' Create the Execution Service Parameter Value object
        Dim parametersRdl() As SsrsExecutionService.ParameterValue
        ' Assigne the parameter list to the SSRS ParameterValue array
        parametersRdl = paramList.ToArray()

        ' Return the ParameterValue
        Return parametersRdl
    End Function

Once again I had to beat my head against a wall before figuring this out, I hope this helps others.

redpajama_set_name: RedPajamaStackExchange


text:
Get George Boole from Amazon.com
George Boole Biography
This Biography consists of approximately 2 pages of information about the life of George Boole.
Encyclopedia of World Biography on George Boole
The English mathematician George Boole (1815-1864) invented mathematical, or symbolic, logic and uncovered the algebraic structure of deductive logic, thereby reducing it to a branch of mathematics.
George Boole was born on Nov. 2, 1815, in Lincoln. He attended a primary school of the National Society and then a school for commercial subjects. This was the last of his formal schooling but not the end of his education, for he inherited a talent for self-study from his father, a shoemaker by trade but a philosopher by inclination. At the age of 16 young Boole became an assistant teacher in an elementary school. Four years later he opened his own school.
Meanwhile he had discovered mathematics. Disgusted with the poor quality of the texts that his students had to use, Boole began to study the works of the great mathematicians. Without guidance he mastered these books and was producing original mathematics by...
More summaries and resources for teaching or studying George Boole.
George Boole from Gale. ©2005-2006 Thomson Gale, a part of the Thomson Corporation. All rights reserved.


text:
The Most Profitable Film Categories in 2014
The films generating the greatest return on investments in 2014 were from the categories of Horror, Faith-Based and Young Adult. The Young Adult category was of no surprise, as it always generates large audiences in the most sought after demographics. The real news was the dramatic increase in Horror and Faith-Based market profitability.
Both categories thrive on ultra low budget films and have enough higher budget films to skew the profit margins for the industry as a whole. For years, Hollywood banked on the common laws of averages that drove one film out of every eight to make enough money to cover all eight films and then some. But today, with the number of other entertainment venues reducing the audience, Hollywood looked to the big blockbusters to cover the costs of all other portfolio films.
Independents typically don't have the luxury of producing a hit rate of 8:1 to cover the expenses of all its films. To compensate most production companies reduced the budget on each production to force profitability. However, packaging films for distribution is still wise when films such as "God's Not Dead" becomes a domestic breakout hit with $61MM at the box office and $26MM in video sales to date – Not bad for a $2MM budget.
The Horror genre also has skewed elements in its numbers. With 900 Horror films made in 2014, only 30 received proper distribution. Of those 30, three films (Annabelle, Ouija, Deliver Us From Evil) generated two thirds of the $255MM box office revenue for the Horror category (A hit rate of 10:1). However, far more Horror films will contribute to the bottom line in video and television sales, which is on the rise.
The Faith-Based market had more breakout hits (Heaven is for Real, God's Not Dead, Son of God, When the Game Stands Tall) in 2014 than the Horror market. The genre saw 470 films made, 23 get proper distribution and had four hits (a 6:1 hit rate). The four films generated $212MM of the $277MM box office receipts, which equates to 76% of the genre's revenue.
From an investor's standpoint, Faith-Based films are the best opportunity for investment when the films are packaged. It's been proven year after year that Horror and Faith-Based films are still risky investments when they are not packaged. Yet, that's exactly how most are produced, driving up the risk factor for the investors.
Both the Faith-Based market and Horror market took a dive in 2015 with only a couple hopefuls to be released in the fall. Most analysts are suggesting the drop is due to shifts in the marketplace. The Horror genre is getting more studio financing for direct to television releases and the Faith-Based market released more poorly constructed films thinking their audience would watch anything with the "right" content.
It's still my passion to package 6-8 great stories using high production values for the general market with great moral and wholesome themes. I firmly believe that is still the best way to drive the greatest revenue and the largest audience for any genre. But, we'll see what the future holds.
← The Audience is Smarter
What if, Jenner… →


text:
Q: Get accountexpires from computerobject in AD by using VBscript I'm trying to get the date from an attribute called 'accountExpires' of a computer object in Active Directory. If the object haven't been set it just says 'never' and if you look it just have a many numbers. I made this and it working for the attribute 'lastlogon', but not for 'accountExpires'. Maybe someone can help me out.
I'm using VBscript because our company is using this in our loginscript.
On Error Resume Next

Dim ADSysInfo, objComputer, lobjDate, laccountExpiresDate, WSHShell
Set WSHShell = CreateObject("WScript.Shell")

Set ADSysInfo = CreateObject("ADSystemInfo")
Set objComputer = GetObject("LDAP://" & ADSysInfo.ComputerName)
msgbox objComputer
Set lobjDate = objComputer.get("lastLogon")         '   <----- Working ----->
'   Set lobjDate = objComputer.get("accountExpires")    ' <----- Not Working ----->
msgbox err.number
if IsNull(lobjDate) then
    msgbox "No Date"
else
    laccountExpiresDate = Integer8Date(lobjDate, getLocaltimeZoneBias)
    msgbox laccountExpiresDate
end if

Function Integer8Date(objDate, lngBias)
' Function to convert Integer8 (64-bit) value to a date, adjusted for
' local time zone bias.
  Dim lngAdjust, lngDate, lngHigh, lngLow
  lngAdjust = lngBias
  lngHigh = objDate.HighPart
  lngLow = objdate.LowPart
' Account for bug in IADslargeInteger property methods.
  If lngLow < 0 Then
    lngHigh = lngHigh + 1
  End If
  If (lngHigh = 0) And (lngLow = 0) Then
    lngAdjust = 0
  End If
  lngDate = #1/1/1601# + (((lngHigh * (2 ^ 32)) + lngLow) / 600000000 - lngAdjust) / 1440
  Integer8Date = CDate(lngDate)
End Function

' Obtain local time zone bias from machine registry.
Function getLocaltimeZoneBias
  Dim lngBiasKey, lngBias

  lngBiasKey = WSHShell.RegRead("HKLM\System\CurrentControlSet\Control\TimeZoneInformation\ActiveTimeBias")
  If UCase(TypeName(lngBiasKey)) = "LONG" Then
    lngBias = lngBiasKey
  ElseIf UCase(TypeName(lngBiasKey)) = "VARIANT()" Then
    lngBias = 0
    For k = 0 To UBound(lngBiasKey)
      lngBias = lngBias + (lngBiasKey(k) * 256^k)
    Next
  End If
  getLocaltimeZoneBias = lngBias
End Function 'getLocaltimeZoneBias


If unaccounted for in your estate plans, estate taxes can significantly reduce your assets before your beneficiaries receive them. It is imperative to talk with a lawyer who understands how estate tax laws — and any changes to them — impact your estate plans. At my law firm, W. Frank Ward, PC, I can ensure that the security you have provided for your loved ones is safeguarded from unnecessary taxation. As a Marietta estate tax planning attorney, I have offered individualized estate planning services to Georgia residents for 19 years.
Estate tax laws are constantly changing; when those changes occur, it is vital to speak with a lawyer. Recent changes to estate tax laws have made future rates, exemptions and other tax conditions easier to predict, which provides a great opportunity to secure plans for your family and loved ones.
If you own a business, it is especially important to ensure that you know the true value of the business to determine if an estate tax plan should be incorporated with your estate planning. Do not risk receiving improper valuation or overlooking assets; every individual and family is unique, and I will work closely with you to establish confidence and comfort with your legal decisions.
To receive help with your estate planning and to understand how estate taxes will impact your beneficiaries, call me at 678-905-8753, toll free at 866-970-7268 or send me an email to schedule a no-obligation consultation. For your convenience, I can accommodate your schedule, including night and weekend availability, and if necessary, I can travel to meet with you.


text:
The 2014 Asian Men's Junior Handball Championship is the 14th edition of the Asian Men's Junior Handball Championship held from 2–14 August 2014 at Tabriz, I. R. Iran under the aegis of Asian Handball Federation. It also acts as the qualification tournament for the 2015 Men's Junior World Handball Championship. Qatar wins the title by beating South Korea in the final match.

Draw

Group A

Group B

Placement matches

9th–10th-place match

7th–8th-place match

5th–6th-place match

Knockout stage

Knockout stage table

Semifinal matches

Bronze-medal match

Final match

Final standings

References

Handball
Asian Men's Junior
Asian Handball Championships
Asian Men's Junior Handball Championship
Asian Men's Junior Handball Championship

redpajama_set_name: RedPajamaWikipedia


If you order 2, 4, 6 or 8+ 5 gallons online, a rising discount rate is shown on the shopping cart! Colors can be mixed.
New from Performix! In connection with European regulations it is not permitted to offer Toluene containing products to private users. To enable Classic International to freely offer the Performix 5 gallon cans to anybody, on our request Performix replaced the Toluene proportion by Xylene, which has the same properties. Therefore these 5 gallon cans (UVX-type) can now be ordered online by anyone. Additionally, the new Performix 5 gallon cans are also UV resistant.


text:
Tetradium subsp. var.
⇕ warning.png"" cannot be used as a page name in this wiki. to warning.png"" cannot be used as a page name in this wiki.
✓ deciduous
Rutaceae > Tetradium var. ,
If this plant info box on watering; zones; height; etc. is mostly empty you can click on the edit tab and fill in the blanks!
Tetradium is a genus of nine species of trees in the family Rutaceae, occurring in temperate to tropical east Asia. In older books, the genus was often included in the related genus Euodia (orthographic error, "Evodia"), but that genus is now restricted to tropical species (1). In cultivation in English-speaking countries, they are known as Euodia, Evodia, or Bee bee tree.
They are attractive trees with deciduous glossy pinnate leaves. Tetradium daniellii (syn. T. hupehensis) develops a smooth gray bark that resembles that of a beech tree and grows to a height of 20 metres. The leaves resemble the foliage of an ash tree and are a glossy dark green in summer. In fall there is little color change and leaves tend to drop green to yellow-green. The tree is covered in late July and August with masses of large flat white to gray cluster of small white flowers, particularly valued when few other tree-size plants are flowering. It attracts large numbers of bees and is sought after by beekeepers as a source of late summer honey. The flowers produce clusters of seed that is present from late August through November. The seeds start as bright red capsules that when fully ripe open to expose shiny black buckshot seed as Autumn progresses. The small, red-to-black berries are popular with many birds.
Nine species including:
Tetradium austrosinense - Korean Euodia
Tetradium calcicola
Tetradium daniellii - Korean Euodia
Tetradium fraxinifolium (Hook.) T. G. Hartley
Tetradium glabrifolium (Champ. ex Benth.) T. G. Hartley
Tetradium ruticarpum
Tetradium trichotomum
w:Tetradium. Some of the material on this page may be from Wikipedia, under the Creative Commons license.
Tetradium QR Code (Size 50, 100, 200, 500)
Retrieved from "http://www.gardenology.org/w/index.php?title=Tetradium&oldid=127082"


CROATIA: After nearly 20 years of running one of the most successful festivals in South East Europe, the EXIT team has announced the launch of a new festival in Croatia, dubbed Sea Star. The event is set to make its debut in Umag's Stella Maris resort from May 26 – 27.
The first names revealed for the debut edition are headliners The Prodigy, plus local favourites Dubioza Kolektiv and Croatian hosts Urban&4. The seaside site will present national and international artists across six different stages. Along with the two official festival days, festivalgoers can also expect a huge warm-up party on May 25 as well as an after party on May 27.
The EXIT team has also announced that it will connect all four of its festivals under the same umbrella in 2017, with the the EXIT Summer of Love. A special holiday offer is now available under the tagline 'One ticket = four festivals", where each ticket bought for EXIT Festival in Serbia comes bundled with complimentary tickets to the other three EXIT-run festivals in Croatia, Montenegro and Romania.


text:
Incentives for solar heating panels
"The coalition government gave details of its subsidies for solar heating panels this morning, as part of a series of environmental announcements aimed at boosting the government's green credentials."
The awaited Renewable Heat Incentive (RHI) aimed at increasing the amount of heat that homes and business can generate from low-carbon sources such as solar heating panels and evacuated tubes. Only a tiny proportion of the UK's housing stocks have renewable heat technology.
Up to 25,000 installations will now support from July, to help people cover the installation price of greener heating systems and will ensure there is a fair spread of such technologies across all regions of the UK.
Chris Huhne, Secretary of State, said "The incentive is the first of its kind in the world. It will help the UK shift away from fossil fuels, reducing carbon emissions and encouraging innovation, jobs and growth in green technologies. Renewable heat is a largely untapped resource and an important new green industry of the future".
solar heating panels and other technologies
Other eligible technologies include biomass boilers air source and ground source heat pumps with boilers that generate electricity at the same time as heating included too.
This technology can be challenging to use as a domestic application. Biomass boilers need more attention and refuelling than standard fossil fuel boilers.
Ground source heat pumps need to be installed underground and cover a wide area, which makes them impractical in urban areas and hard to retrofit, so installing solar panels and solar tubes are the most practical of these technologies in an urban and domestic setting.
The subsidy will be paid for from government coffers, and from July, up to 25,000 installations will be supported by RHI Payments, to help people cover the purchase price of green heating systems if they are willing to agree to give feedback on how the equipment performs.
A full system of RHI payments will be available to households from October 2012, as will anyone else who has had available MCS equipment installed since July 2009.
Stuart Lovatt from Power My Home adds, "This is fantastic news for homeowners who can now feel confident in solar technologies with the government's endorsement and support.
The demand for solar technologies has increased tenfold over the last two years, and now with the Renewable Heat Incentive scheme, demand will be high, so being an early adopter is recommended."
The principal focus of this early phase will be on people living off the gas grid, where fossil fuels like heating oil are both more expensive and have higher carbon contents.
Incentives for solar heating panels was last modified: November 1st, 2018 by Stuart Lovatt
Incentives for solar heating panels are confirmed
Solar heating panels and the Renewable Heat Incentive scheme
Solar panels » Incentives for solar heating panels
"PV-powered people."
Stuart Lovatt 2011-03-10
Founder of Power My Home.


IAR Embedded Workbench™ Professional now also includes tools for graphical system design, testing facilities, and automatic documentation.
IAR Embedded Workbench is one of the most advanced C and Embedded C++ development tools in the market. Now IAR Systems introduces the professional edition of the IAR Embedded Workbench, which is not only an advanced compiler and debugger kit but also a drawing tool ─ for designing, testing and documenting the C/EC++ development.
· The graphical design tool represents any complex system with UML-based state charts, suitable for real-time systems with many concurrent and interrelated processes or execution threads.
· Advanced testing and simulation facilities help to detect errors at an early stage of the software development process.
· The documentation tool saves developers valuable time and energy by generating well-structured system documentation automatically, either in RTF or HTML format.
The IAR Embedded Workbench Professional is a powerful and easy-to-use tool that meets the increasing demand for documentation at the engineering level without implementing large and complex modelling tools for the entire organization. Any engineer will be able to create an overview of his design, simulate and test its functionally, and most important, create the system documentation automatically.
"The final quality and market approval of any embedded application depends largely on the decisions made in the early design and validation phases of a development project. We are convinced that by offering tools that support and relieve embedded developers in this work, we can help infuse higher quality in many embedded application projects and thereby render our customers great market success" says Mats Ullström, Product Manager, IAR Systems.
IAR Embedded Workbench Professional will first be available for MSP430 and AVR; other targets will follow later in 2002.


text:
"""Support for the Tuya climate devices."""
from datetime import timedelta
import logging

from homeassistant.components.climate import (
    DOMAIN as SENSOR_DOMAIN,
    ENTITY_ID_FORMAT,
    ClimateEntity,
)
from homeassistant.components.climate.const import (
    FAN_HIGH,
    FAN_LOW,
    FAN_MEDIUM,
    HVAC_MODE_AUTO,
    HVAC_MODE_COOL,
    HVAC_MODE_FAN_ONLY,
    HVAC_MODE_HEAT,
    HVAC_MODE_OFF,
    SUPPORT_FAN_MODE,
    SUPPORT_TARGET_TEMPERATURE,
)
from homeassistant.const import (
    ATTR_TEMPERATURE,
    CONF_PLATFORM,
    CONF_UNIT_OF_MEASUREMENT,
    ENTITY_MATCH_NONE,
    PRECISION_TENTHS,
    PRECISION_WHOLE,
    TEMP_CELSIUS,
    TEMP_FAHRENHEIT,
)
from homeassistant.core import callback, valid_entity_id
from homeassistant.helpers.dispatcher import async_dispatcher_connect

from . import TuyaDevice
from .const import (
    CONF_CURR_TEMP_DIVIDER,
    CONF_EXT_TEMP_SENSOR,
    CONF_MAX_TEMP,
    CONF_MIN_TEMP,
    CONF_TEMP_DIVIDER,
    DOMAIN,
    SIGNAL_CONFIG_ENTITY,
    TUYA_DATA,
    TUYA_DISCOVERY_NEW,
)

DEVICE_TYPE = "climate"

SCAN_INTERVAL = timedelta(seconds=15)

HA_STATE_TO_TUYA = {
    HVAC_MODE_AUTO: "auto",
    HVAC_MODE_COOL: "cold",
    HVAC_MODE_FAN_ONLY: "wind",
    HVAC_MODE_HEAT: "hot",
}

TUYA_STATE_TO_HA = {value: key for key, value in HA_STATE_TO_TUYA.items()}

FAN_MODES = {FAN_LOW, FAN_MEDIUM, FAN_HIGH}

_LOGGER = logging.getLogger(__name__)

async def async_setup_entry(hass, config_entry, async_add_entities):
    """Set up tuya sensors dynamically through tuya discovery."""

    platform = config_entry.data[CONF_PLATFORM]

    async def async_discover_sensor(dev_ids):
        """Discover and add a discovered tuya sensor."""
        if not dev_ids:
            return
        entities = await hass.async_add_executor_job(
            _setup_entities,
            hass,
            dev_ids,
            platform,
        )
        async_add_entities(entities)

    async_dispatcher_connect(
        hass, TUYA_DISCOVERY_NEW.format(SENSOR_DOMAIN), async_discover_sensor
    )

    devices_ids = hass.data[DOMAIN]["pending"].pop(SENSOR_DOMAIN)
    await async_discover_sensor(devices_ids)

def _setup_entities(hass, dev_ids, platform):
    """Set up Tuya Climate device."""
    tuya = hass.data[DOMAIN][TUYA_DATA]
    entities = []
    for dev_id in dev_ids:
        device = tuya.get_device_by_id(dev_id)
        if device is None:
            continue
        entities.append(TuyaClimateEntity(device, platform))
    return entities

class TuyaClimateEntity(TuyaDevice, ClimateEntity):
    """Tuya climate devices,include air conditioner,heater."""

    def __init__(self, tuya, platform):
        """Init climate device."""
        super().__init__(tuya, platform)
        self.entity_id = ENTITY_ID_FORMAT.format(tuya.object_id())
        self.operations = [HVAC_MODE_OFF]
        self._has_operation = False
        self._def_hvac_mode = HVAC_MODE_AUTO
        self._min_temp = None
        self._max_temp = None
        self._temp_entity = None
        self._temp_entity_error = False

    @callback
    def _process_config(self):
        """Set device config parameter."""
        config = self._get_device_config()
        if not config:
            return
        unit = config.get(CONF_UNIT_OF_MEASUREMENT)
        if unit:
            self._tuya.set_unit("FAHRENHEIT" if unit == TEMP_FAHRENHEIT else "CELSIUS")
        self._tuya.temp_divider = config.get(CONF_TEMP_DIVIDER, 0)
        self._tuya.curr_temp_divider = config.get(CONF_CURR_TEMP_DIVIDER, 0)
        min_temp = config.get(CONF_MIN_TEMP, 0)
        max_temp = config.get(CONF_MAX_TEMP, 0)
        if min_temp >= max_temp:
            self._min_temp = self._max_temp = None
        else:
            self._min_temp = min_temp
            self._max_temp = max_temp
        self._temp_entity = config.get(CONF_EXT_TEMP_SENSOR)

    async def async_added_to_hass(self):
        """Create operation list when add to hass."""
        await super().async_added_to_hass()
        self._process_config()
        self.async_on_remove(
            async_dispatcher_connect(
                self.hass, SIGNAL_CONFIG_ENTITY, self._process_config
            )
        )

        modes = self._tuya.operation_list()
        if modes is None:
            if self._def_hvac_mode not in self.operations:
                self.operations.append(self._def_hvac_mode)
            return

        for mode in modes:
            if mode not in TUYA_STATE_TO_HA:
                continue
            ha_mode = TUYA_STATE_TO_HA[mode]
            if ha_mode not in self.operations:
                self.operations.append(ha_mode)
            self._has_operation = True

    @property
    def precision(self):
        """Return the precision of the system."""
        if self._tuya.has_decimal():
            return PRECISION_TENTHS
        return PRECISION_WHOLE

    @property
    def temperature_unit(self):
        """Return the unit of measurement used by the platform."""
        unit = self._tuya.temperature_unit()
        if unit == "FAHRENHEIT":
            return TEMP_FAHRENHEIT
        return TEMP_CELSIUS

    @property
    def hvac_mode(self):
        """Return current operation ie. heat, cool, idle."""
        if not self._tuya.state():
            return HVAC_MODE_OFF

        if not self._has_operation:
            return self._def_hvac_mode

        mode = self._tuya.current_operation()
        if mode is None:
            return None
        return TUYA_STATE_TO_HA.get(mode)

    @property
    def hvac_modes(self):
        """Return the list of available operation modes."""
        return self.operations

    @property
    def current_temperature(self):
        """Return the current temperature."""
        curr_temp = self._tuya.current_temperature()
        if curr_temp is None:
            return self._get_ext_temperature()
        return curr_temp

    @property
    def target_temperature(self):
        """Return the temperature we try to reach."""
        return self._tuya.target_temperature()

    @property
    def target_temperature_step(self):
        """Return the supported step of target temperature."""
        return self._tuya.target_temperature_step()

    @property
    def fan_mode(self):
        """Return the fan setting."""
        return self._tuya.current_fan_mode()

    @property
    def fan_modes(self):
        """Return the list of available fan modes."""
        return self._tuya.fan_list()

    def set_temperature(self, **kwargs):
        """Set new target temperature."""
        if ATTR_TEMPERATURE in kwargs:
            self._tuya.set_temperature(kwargs[ATTR_TEMPERATURE])

    def set_fan_mode(self, fan_mode):
        """Set new target fan mode."""
        self._tuya.set_fan_mode(fan_mode)

    def set_hvac_mode(self, hvac_mode):
        """Set new target operation mode."""
        if hvac_mode == HVAC_MODE_OFF:
            self._tuya.turn_off()
            return

        if not self._tuya.state():
            self._tuya.turn_on()

        if self._has_operation:
            self._tuya.set_operation_mode(HA_STATE_TO_TUYA.get(hvac_mode))

    @property
    def supported_features(self):
        """Return the list of supported features."""
        supports = 0
        if self._tuya.support_target_temperature():
            supports = supports | SUPPORT_TARGET_TEMPERATURE
        if self._tuya.support_wind_speed():
            supports = supports | SUPPORT_FAN_MODE
        return supports

    @property
    def min_temp(self):
        """Return the minimum temperature."""
        min_temp = (
            self._min_temp if self._min_temp is not None else self._tuya.min_temp()
        )
        if min_temp is not None:
            return min_temp
        return super().min_temp

    @property
    def max_temp(self):
        """Return the maximum temperature."""
        max_temp = (
            self._max_temp if self._max_temp is not None else self._tuya.max_temp()
        )
        if max_temp is not None:
            return max_temp
        return super().max_temp

    def _set_and_log_temp_error(self, error_msg):
        if not self._temp_entity_error:
            _LOGGER.warning(
                "Error on Tuya external temperature sensor %s: %s",
                self._temp_entity,
                error_msg,
            )
            self._temp_entity_error = True

    def _get_ext_temperature(self):
        """Get external temperature entity current state."""
        if not self._temp_entity or self._temp_entity == ENTITY_MATCH_NONE:
            return None

        entity_name = self._temp_entity
        if not valid_entity_id(entity_name):
            self._set_and_log_temp_error("entity name is invalid")
            return None

        state_obj = self.hass.states.get(entity_name)
        if state_obj:
            temperature = state_obj.state
            try:
                float(temperature)
            except (TypeError, ValueError):
                self._set_and_log_temp_error(
                    "entity state is not available or is not a number"
                )
                return None

            self._temp_entity_error = False
            return temperature

        self._set_and_log_temp_error("entity not found")
        return None

redpajama_set_name: RedPajamaGithub


text:
Simu Liu Is A Big Fanboy Of Priyanka Chopra Jonas And These Bollywood Stars
Mavenir Brings Dynamic Network Slicing Innovation Through TM Forum Catalyst Ecosoft eHealth Program
Kayrros Names Mark Taylor Vice President, Energy Transition
GradRight and Prodigy Finance come together to support Rohit's dream of international higher education
Uttiya Roy
DKODING Studio
Simu Liu is swimming in fame, but the Korean actor has something else up his sleeve. He amazed interviewers with his thoughts on Bollywood films.
Simu Liu burst into the scene with the Asian-Canadian sitcom 'Kims Convenience'. But now, he's making significant strides into Hollywood with his marquee role as Shang-Chi in the MCU. He's on the path to success and doesn't seem to be stopping any time soon, but there might be more in store for him yet. The actor also has a secret that he keeps close to his chest. He's a big fan of Bollywood.
Highlights —
Simu Liu and cinema
As Shang Chi
Bollywood calling!
Careerific!
Before Simu Liu got the chance to work for 'Kim's Convenience', he was an accountant. The actor started his career as an accountant just out of business school, but he didn't fit in and was there just for eight months. He says, "It's not what I wanted, but it was a move to appease the parents. That, to me at the time, was what it meant to be a fully functional adult. Things like "following your passion" and "finding your creative outlets" didn't mean anything to me because I didn't have that area of my brain. So I thought I did the right thing".
Video Credits: Dream Angel
As an Asian immigrant, he had made his career decisions based on who he was. He needed to support his family, and his dreams and aspirations didn't come into play at all. He started acting on a whim, applying to and getting into the large sets of Guillermo del Toro's 'Pacific Rim'. But, he worked hard to get any of the roles he could get, finally settling in with an agent after he got some bit roles.
Related: Why Simu Liu Hated Watching Squid Game
His first significant role was in 'Blood and Water', a little-known show from Canadian television. He said, "It was a show about a Chinese-Canadian family in Vancouver, and it was spoken both in Mandarin and in English. Because they had that requirement for casting, I was the only guy who could do it, and they had to cast me".
Simu Liu was cast as Shang Chi after a tweet. In 2018, he tweeted about playing the role, and it became an excellent space for Asian-American representation within Marvel film. He said, "I was a dress-up Spider-Man for kids' birthday parties for a while. It was early on in my acting career, and I wanted to get my reps in. I wanted to take every possible opportunity to perform, and these superhero parties paid pretty decently. So I started doing that, and, of course, after I got physically assaulted by enough kids, eventually, I kind of lost the joy to put on the suit. I thought that was maybe the last time I was going ever to play a superhero, but thankfully, that wasn't the case".
Simu Liu as Shang Chi
He loved superhero films, and he worked to make them into his reality. He shined in part as an expert honing martial arts performance and making sure that he achieves his goals. It also showed off his spark of brilliance as an actor and set him down on a path for success.
Related: A Single Tweet Altered The Fate Of Simu Liu Making Him The First Asian Superhero Of MCU
Talking about the famous bus fight scene, he also said, "We used every square inch of that bus. I don't want to spoil too much, but inside, outside, on top. We got creative with it, and it is one of my favourite sequences in the movie. And we've got some pretty incredible action sequences".
Bollywood calling?
Video Credits: CNN-News18
Simu Liu's favourite Bollywood stars are Shah Rukh Khan, Irrfan Khan, Aishwarya Rai Bachchan, and Priyanka Chopra Jonas. Simu Liu's knowledge of Bollywood surprised his interviewer from "Times of India". Even though he limited himself to people who have broad exposure to the western world, he promised the newspaper that he would be watching more Indian films in the days ahead. He would continue to gain more knowledge of the film industry.
Simu Liu's favourite Bollywood stars indicate that he is open to all kinds of movies and shows off his fanboy-ness for Bollywood films.
Tags priyanka chopra jonas shah rukh khan Shang-Chi Simu Liu
Uttiya Roy, an author-at-large, terrifying presence and overall nerd. I write cultural critiques and go into why media is doing what it is. I love OTT and live on the internet. Netflix, Prime, Hotstar and comics are my lifeblood. For me media is a mirror to the real world and writing is the best way to interpret it.
Johnny Depp Is Holding On To The Role Of Jack Sparrow With His Life
Agatha All Alone: Kathryn Hahn To Get Her Standalone Disney+ Show
Spider-Man Has Entered The Oscar Race With A Push From Marvel
Does Edward Norton Finally Have A Window To Come Back Into The MCU As Hulk?
Here's All The Proof That Simu Liu Is A Bigger Fanboy Of Bollywood Than Of Marvel
Why Simu Liu Hated Watching Squid Game
A Single Tweet Altered The Fate Of Simu Liu Making Him The First Asian Superhero Of MCU
How Childhood Trauma Shaped The MCU
Simu Liu's Shang-Chi Creates A Perfect Base For Avengers 5
Shang-Chi: How The Yakuza And Triads Can Change The Game


text:
Ecolab Media Coverage CBS Evening News Super Bowl fans could be tackled by the flu
Ecolab Media Coverage | CBS Evening News: Super Bowl fans could be tackled by the flu
Football fans attending the Big Game in Minneapolis may have an increased risk of contracting the flu. CBS News met with public health experts in the area, including Ecolab's Dr. John Hanlin, vice president of Food Safety and Public Health, to learn about best practices to protect against the flu. Dr. Hanlin provided tips for flu prevention and discussed Ecolab's work with hotels in the Twin Cities to help keep guests healthy.
The full story can be viewed on cbsnews.com.