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ICACA UNDERSTANDING GHANA- SPECIAL COMMUNITY EVENTS AND CELEBRATIONS

Pastor P.j Tibayan 2 Thessalonians 2:1-12

The goal of this paper is to understand the drivers, configurations, and scenarios of two similar eruptive events, which occurred in the same solar active region 9973 on 2002 June 1 and 2. The June 2 event was previously studied by Sui, Holman, and Dennis (2006, 2008), who concluded that it was challenging for popular flare models. Using multi-spectral data, we analyze a combination of the two events. Each of the events exhibited an evolving cusp-like feature. We have revealed that these apparent ``cusps'' were most likely mimicked by twisted magnetic flux ropes, but unlikely to be related to the inverted Y-like magnetic configuration in the standard flare model. The ropes originated inside a funnel-like magnetic domain whose base was bounded by an EUV ring structure, and the top was associated with a coronal null point. The ropes appear to be the major drivers for the events, but their rise was not triggered by reconnection in the coronal null point. We propose a scenario and a three-dimensional scheme for these events in which the filament eruptions and flares were caused by interaction of the ropes.

The goal of this paper is to understand the drivers, configurations, and scenarios of two similar eruptive events, which occurred in the same solar active region 9973 on 2002 June 1 and 2. The June 2 event was previously studied by Sui, Holman, and Dennis (2006, 2008), who concluded that it was challenging for popular flare models. Using multi-spectral data, we analyze a combination of the two events. Each of the events exhibited an evolving cusp-like feature. We have revealed that these apparent ``cusps'' were most likely mimicked by twisted magnetic flux ropes, but unlikely to be related to the inverted Y-like magnetic configuration in the standard flare model. The ropes originated inside a funnel-like magnetic domain whose base was bounded by an EUV ring structure, and the top was associated with a coronal null point. The ropes appear to be the major drivers for the events, but their rise was not triggered by reconnection in the coronal null point. We propose a scenario and a three-dimensional scheme for these events in which the filament eruptions and flares were caused by interaction of the ropes.

We present a three-dimensional (3D) study of common envelope events (CEEs) to provide a foundation for future one-dimensional (1D) methods to model the self-regulated phase of a CEE. The considered CEEs with a low-mass red giant end with one of three different outcomes -- merger, slow spiral-in, or prompt formation of a binary. To understand which physical processes determine different outcomes, and to evaluate how well 1D simulations model the self-regulated phase of a CEE, we introduce tools that map our 3D models to 1D profiles. We discuss the differences in the angular momentum and energy redistribution in 1D and 3D codes. We identified four types of ejection processes: the pre-plunge-in ejection, the outflow during the plunge-in, the outflow driven by recombination, and the ejection triggered by a contraction of the circumbinary envelope. Significant mass is lost in all cases, including the mergers. Therefore a self-regulated spiral-in can start only with a strongly reduced envelope mass. We derive the condition to start a recombination outflow, which can proceed either as a runaway or a stationary outflow. We show that the way the energy of the inspiraling companion is added to the envelope in 1D studies intensifies the envelope's entropy increase, alters the start of the recombination outflow, and leads to different outcomes in 1D and 3D studies. The steady recombination outflow may dispel most of the envelope in all slow spiral-in cases, making the existence of a long-term self-regulated phase debatable, at least for low-mass giant donors.

Perma.cc archive of https://www.cdc.gov/vaccinesafety/ensuringsafety/sideeffects/index.html created on 2022-03-30 21:14:54.890074+00:00.

ICACA UNDERSTANDING AFRICA- AFRICAN VIP LIVE EVENTS

ICACA UNDERSTANDING GHANA- SPECIAL COMMUNITY EVENTS

Past studies have shown that when under extreme duress, people tend to cooperate rather than act selfishly (Auf der Heide, 2004; Drury, 2018). ). What appears to occur then is ‘contagious’ cooperation, in which people spontaneously self-organize in contexts where there is uncertainty and insufficient time for an organized (communicated) response. However, once the threat passes, spontaneous cooperation seems to fade. The current study aims to understand the processes underpinning spontaneous cooperation. To do this, we simulated a building evacuation in which participants were confronted with an obstacle blocking their escape.

Past studies have shown that when under extreme duress, people tend to cooperate rather than act selfishly (Auf der Heide, 2004; Drury, 2018). ). What appears to occur then is ‘contagious’ cooperation, in which people spontaneously self-organize in contexts where there is uncertainty and insufficient time for an organized (communicated) response. However, once the threat passes, spontaneous cooperation seems to fade. The current study aims to understand the processes underpinning spontaneous cooperation. To do this, we simulated a building evacuation in which participants were confronted with an obstacle blocking their escape.

Note this registration has been withdrawn: External events can be important stimuli for significant policy changes. This paper develops an integrated framework based on the Advocacy Coalition Framework, Multiple Streams model and Punctuated Equilibrium Theory to explore the effect of external events on China’s abolition of the Labor Reeducation System (LRS). Our analysis shows that external events contributed to abolition by breaking through decision makers’ “attention bottleneck,” tipping the balance of power and opening an opportunity window. The limited within-coalition learning was a sort of tactical response to external shocks, while the intercoalition learning can be understood as the result of interference from higher authorities. We also conclude that destabilizing events reduce the degree of consensus necessary for major policy change and enhance China’s authoritarian decision-making style. The role of external events largely depends on their relevance to the ideology and political interest of the Communist Party of China (CPC).

Note this registration has been withdrawn: External events can be important stimuli for significant policy changes. This paper develops an integrated framework based on the Advocacy Coalition Framework, Multiple Streams model and Punctuated Equilibrium Theory to explore the effect of external events on China’s abolition of the Labor Reeducation System (LRS). Our analysis shows that external events contributed to abolition by breaking through decision makers’ “attention bottleneck,” tipping the balance of power and opening an opportunity window. The limited within-coalition learning was a sort of tactical response to external shocks, while the intercoalition learning can be understood as the result of interference from higher authorities. We also conclude that destabilizing events reduce the degree of consensus necessary for major policy change and enhance China’s authoritarian decision-making style. The role of external events largely depends on their relevance to the ideology and political interest of the Communist Party of China (CPC).

110 p. : 24 cm

For someone having faced a significant stressor such as a serious accident, some form of assault or a chronic health issue, the high levels of resulting anxiety can lead to chronic forms of psychological dysfunction often labeled as posttraumatic stress (Rothschild, 2000). However, accepting and overcoming the psychological effects of significant adversity can require a person to surpass their previous level of functioning (Linley & Joseph, 2004). Currently, most of the research on adversarial growth is correlational and has focused on the relation between adversarial growth and variables which are not changeable. Benight and Bandura’s (2004) popular theoretical model of posttraumatic adaptation instead focuses on variables over which the individual can exert some control. Specifically, they suggest that beliefs of coping self-efficacy (i.e., perceptions of capability for handling stress) and resources such as social support (i.e., aid that is offered from one’s family and close friends) can be especially useful for recovery after adversity. In addition, based on prior research we believe that perceived benefit (i.e., the ability to find benefits in adversarial circumstances) is also a fundamental variable to consider in trying to influence adversarial growth (Linley & Joseph, 2005). As such, the purpose of the following study is to understand the degree to which self-efficacy, social support, and perceived benefit each predict adversarial growth among students who have been exposed to a significant adversarial event. More clearly, the purpose of this study is to investigate the relation between three main predictor variables (i.e., self-efficacy, social support, and perceived benefit) and two outcome variables (i.e., adversarial growth and severity of any trauma-like symptoms), all assessed via self-report questionnaires. We are measuring two outcome variables to examine how our predictor variables are related to both the positive and negative effects of significant adversity. We will also be measuring centrality to identity and trait anxiety so they can be used as moderator variables, as well as extraversion and optimism so they can be controlled for. We hypothesize that self-efficacy, social support and perceived benefit will all predict higher adversarial growth, especially among individuals who report low trait anxiety and high event centrality. We also hypothesize that self-efficacy, social support, and perceived benefit will all predict lower levels of post-traumatic stress symptoms, especially among individuals who report low trait anxiety and low event centrality. Additionally, on an exploratory basis, we are particularly interested in understanding which predictor(s) has the strongest relation with adversarial growth, and whether there are any interactions among predictors.

The event mixing method is analyzed for the study of the event-by-event $K/\pi$ ratio distribution. It is shown that there exists some correlation between the kaon and pion multiplicities in the mixed events. The $K/\pi$ ratio distributions in the mixed events for different sets of real events are shown. The dependence of the distributions on the mean $K/\pi$ ratio, mean and variance of multiplicity distribution in the real events is investigated systematically. The effect of imperfect particle identification on the $K/\pi$ ratio distribution in the mixed event is also considered.

The event mixing method is analyzed for the study of the event-by-event $K/\pi$ ratio distribution. It is shown that there exists some correlation between the kaon and pion multiplicities in the mixed events. The $K/\pi$ ratio distributions in the mixed events for different sets of real events are shown. The dependence of the distributions on the mean $K/\pi$ ratio, mean and variance of multiplicity distribution in the real events is investigated systematically. The effect of imperfect particle identification on the $K/\pi$ ratio distribution in the mixed event is also considered.

In dense Erd\H{o}s-R\'enyi random graphs, we are interested in the events where large numbers of a given subgraphs occur. The mean behaviour of subgraph counts is known, and only recently were the related large deviations results discovered. Consequently, it is natural to ask, what is the probability of an Erd\H{o}s-R\'enyi graph containing an excessively large number of a given subgraph? Using the large deviation principle, we study an importance sampling scheme as a method to numerically compute the small probabilities of large triangle counts occurring within Erd\H{o}s-R\'enyi graphs. The exponential tilt used in the importance sampling scheme comes from a generalized class of exponential random graphs. Asymptotic optimality, a measure of the efficiency of the importance sampling scheme, is achieved by the special choice of exponential random graph that is indistinguishable from the Erd\H{o}s-R\'enyi graph conditioned to have many triangles. We show how this choice can be made for the conditioned Erd\H{o}s-R\'enyi graphs both in the replica symmetric phase and also in parts of the replica breaking phase. Equally interestingly, we also show that the exponential tilt suggested directly by the large deviation principle does not always yield an optimal scheme.

In dense Erd\H{o}s-R\'enyi random graphs, we are interested in the events where large numbers of a given subgraphs occur. The mean behaviour of subgraph counts is known, and only recently were the related large deviations results discovered. Consequently, it is natural to ask, what is the probability of an Erd\H{o}s-R\'enyi graph containing an excessively large number of a given subgraph? Using the large deviation principle, we study an importance sampling scheme as a method to numerically compute the small probabilities of large triangle counts occurring within Erd\H{o}s-R\'enyi graphs. The exponential tilt used in the importance sampling scheme comes from a generalized class of exponential random graphs. Asymptotic optimality, a measure of the efficiency of the importance sampling scheme, is achieved by the special choice of exponential random graph that is indistinguishable from the Erd\H{o}s-R\'enyi graph conditioned to have many triangles. We show how this choice can be made for the conditioned Erd\H{o}s-R\'enyi graphs both in the replica symmetric phase and also in parts of the replica breaking phase. Equally interestingly, we also show that the exponential tilt suggested directly by the large deviation principle does not always yield an optimal scheme.

This article is from Frontiers in Oncology , volume 3 . Abstract The two most common primary bone malignancies, osteosarcoma (OS), and Ewing sarcoma (ES), are both aggressive, highly metastatic cancers that most often strike teens, though both can be found in younger children and adults. Despite distinct origins and pathogenesis, both diseases share several mechanisms of progression and metastasis, including neovascularization, invasion, anoikis resistance, chemoresistance, and evasion of the immune response. Some of these processes are well-studies in more common carcinoma models, and the observation from adult diseases may be readily applied to pediatric bone sarcomas. Neovascularization, which includes angiogenesis and vasculogenesis, is a clear example of a process that is likely to be similar between carcinomas and sarcomas, since the responding cells are the same in each case. Chemoresistance mechanisms also may be similar between other cancers and the bone sarcomas. Since OS and ES are mesenchymal in origin, the process of epithelial-to-mesenchymal transition is largely absent in bone sarcomas, necessitating different approaches to study progression and metastasis in these diseases. One process that is less well-studied in bone sarcomas is dormancy, which allows micrometastatic disease to remain viable but not growing in distant sites – typically the lungs – for months or years before renewing growth to become overt metastatic disease. By understanding the basic biology of these processes, novel therapeutic strategies may be developed that could improve survival in children with OS or ES.

Summary: We aim to collect additional data to complement an earlier study by testing the robustness of one of the core insights that emerged. The original study was an experiment about expertise search strategies at networking events. Like in the earlier study, participants are tasked to search for information that one other person in the room possesses (i.e., their search target) while concurrently being potentially the search target for another participant. The current study aims to investigate the robustness of the insight gained from the above study, namely that those who let others approach them gain more referrals than those who initiate interactions themselves. Detailed characteristics of study: The experiment is set up as an information search game in a setting that emulates a typical networking event. Specifically, participants are tasked to search for a specific other participant (their “search target”) based on short clues (“fun facts”) they are given about this participant at the start of the experiment. To measure how participants navigate the room during this task, we use sociometric badges: small electronic devices participants can wear on their body and which track participant movement during the experiment. Participants (n ≤ 72, as limited by the number of available sociometric badges) will be university students who sign up for the event, which is marketed as a research study about networking. Registration: Upon arrival on the day of the event, students will be given an ID number, a preassigned random number between 0 and 100. This ID number will be clearly displayed on a yellow vest participants will wear for the duration of the experiment. Participants will also be given a sociometric badge that also carries their ID number. A sociometric badge is an electronic device that a participant wear on a lanyard, and which records their movement around the room with the purpose of establishing which other participants they are interacting with at which time. The sociometric badges achieve this by measuring the signal strength (based on ultra-wideband technology) to the badges used by all other participants at shorter than one second intervals. The badges measure the absolute and relative location of participants. The badges do not record conversations. Entry survey: After registration and a short introduction by the research team, participants will be instructed to complete a short entry survey on their mobile phone or other portable device. This entry survey is designed to collect the following information. • Basic personal background information, including gender and programme of study. We will not record any sensitive personal information or person-identifying information. • Some questions designed to measure key personality and cognition variables (e.g., Big Five, altruistic networking, self-monitoring, self-efficacy) that will serve as control variables in our analysis, as well as to compare the sample to our original study, but will not be used to test our hypothesis. • Which other participants they already personally know. Information on prior relationships between participants is necessary for us to assign as a search target in the network experiment someone they do not already know. • Two fun facts about themselves. The two fun facts will form the basis of the search task assigned to the participants. Examples of “fun facts” include: “I eat bread with peanut butter every day for breakfast” and “I am an opera singer in my free time”. Participants are instructed to convey something they believe is highly specific to themselves but not directly visible or traceable to their physical appearance (e.g., gender) or cultural background. The students will be reminded that the fun fact must be something that close friends, but not acquaintances or strangers, will likely know about them. The search task: The two fun facts will form the basis of the search task assigned to all participants: participants will be provided with two fun facts written by another participant and the simple task consists of finding that participant during the event. During the experiment, all participants will be simultaneously searching for someone while potentially being the search target for somebody else. It is at the discretion of participants to provide referrals to other participants during the task. The planned duration for the event is one hour. Assigning search targets will take place directly after all participants have completed the entry survey. Specifically, the survey tool will randomly assign up to five search targets to each participant from the subset of other participants whom they have indicated that do not already know (ensuring all targets are different, avoiding friends of friends, avoiding symmetric pairs, and avoiding any search target to be assigned to more than three participants in any round). The search target’s fun fact will be communicated via the tool used for the entry survey alongside basic instructions for their search: • Only talk in pairs. If a person you want to talk to is already talking to someone else, you will either need to wait until they become available or go and talk to another person. • Track your conversations on the survey tool. After each conversation, please use the tool indicating: 1. The ID number of the person you spoke to 2. If you enquired about the fun facts assigned to you 3. If so, is this person your search target (i.e., wrote the fun facts assigned to you), 4. If not, did this person refer you to someone else? And if so, to whom? • Start each conversation with an icebreaker question. Before enquiring about the “fun facts” assigned to you, you must first both ask your icebreaker question. You find these at the top of the survey page where you are tracking each conversation. • When you indicate you have found the person you were looking for, you will be automatically assigned a new pair of fun facts, so you can start looking for a second person, and then a third, etc. (if time permits). Participants will be instructed to remain seated until we verify that everyone has read the instructions. Then, the floor will open, and participants can start walking around the room. Experimental treatment: We will randomly assign 30% of participants to a treatment condition and the remainder to the control condition. Those in the treatment condition will receive the additional instruction that they have been selected for a “special role” in the game. Specifically, these participants are instructed to always wait for other people to approach them instead of taking the initiative in starting conversations, and to only enquire about their assigned fun facts once they have given the other person the chance to ask about theirs. The only exception is when they believe they have identified their search target, in which case they can approach them. These special instructions are included on the closing page with the assigned search targets and general instructions. Participants are instructed to keep their special role a secret to all other participants. The treatment is designed to create variation in the extent to which individuals initiate conversations, which will allow us to observe if initiation reduces the number of referrals individuals receive during the interactions in the experiment. This is in line with the following hypothesis: Hypothesis: Initiating conversations leads to fewer referrals than letting others approach. Incentive: The incentive for participation will be the chance to win a prize (EarPods). Participants are made aware that the quicker they reach their first search target (in terms of the number of people they speak to), the higher their chance of winning. Those in the treatment condition are additionally made aware that, due to their special treatment, their chance of winning is determined differently: the fewer times they wrongly approach who they believed was the target, the higher their chance of winning. Exit survey: After the event, participants will be asked to complete a short survey about their experiences during the game. This will include questions about the emotions felt during game and the perceived difficulty. We will also ask specific questions to test if the experimental manipulation was effective, such as about the perceived balance between initiating conversations and letting others approach. Hypothesis testing and effect sizes: We will test our above hypothesis by using a two-tailed t-test, where we compare the referral rate (received referral = 1, didn’t receive = 0) between all the interactions in each group. We do so using interaction level data (number of interactions producing a referral, over the total number of interactions capable of producing a referral, within treatment group). Referral rates for both groups (control and treatment) will range between 0 and 1. We calculate detectable effect sizes as follows. In the original study (69 participants, 45 minutes), there were a total of 571 interactions, i.e. 8.27 interactions per person. Scaled up to 72 participants during 60 minutes, this would mean a total of 849 conversations (note that the exact number is unpredictable). However, we must exclude certain types of interactions which could not possibly lead to a referral: those where the participant found their target, and those where the participant did not ask their question. This removes 36.4% of interactions, leaving 363 which may be used for our analysis of referral rates. Scaled up to 72 participants (as limited by the number of sociometric badges we have) and planned duration of the experiment (60 minutes), we expect a total of 505 interactions. Assuming that treated and control participants do not differ in the duration of interactions, this means an estimated 168 interactions for members of the treatment group, and 337 for members of the control group. Interactions between two treated participants should occur rarely or never). With this sample size, we can detect, at a significance level of p< 0.05 and statistical power of 0.8, a minimum effect size of Cohen’s d = 0.27. Since the effect size in the main study was 0.56 (strong effect), we expect to be able to find the same effect in the current study. Further information Research question: When searching for information during networking events, do those who let others approach them gain more referrals than those who initiate interactions themselves? Dependent variables: • Proportion of interactions that produce a referral (excluding interactions that cannot possibly produce a referral). Independent variable: • Initiation of interaction (ego vs. alter) • Treatment vs control Exclusion criteria: We will exclude interactions in which: (a) the participant did not ask about the fun fact, (b) the conversation resulted in finding the search target, or (c) initiation direction was unclear or not logged. Missing data: Missing survey data (e.g., incomplete intake surveys) will be excluded from analyses involving those variables. Missing badge data will be logged, and those participants may be excluded from interaction-level analyses if essential location/interaction data is missing. Data sharing plan: De-identified interaction-level and survey data will be uploaded to OSF after data collection, pending ethical approval and participant consent.

Summary: We aim to collect additional data to complement an earlier study by testing the robustness of one of the core insights that emerged. The original study was an experiment about expertise search strategies at networking events. Like in the earlier study, participants are tasked to search for information that one other person in the room possesses (i.e., their search target) while concurrently being potentially the search target for another participant. The current study aims to investigate the robustness of the insight gained from the above study, namely that those who let others approach them gain more referrals than those who initiate interactions themselves. Detailed characteristics of study: The experiment is set up as an information search game in a setting that emulates a typical networking event. Specifically, participants are tasked to search for a specific other participant (their “search target”) based on short clues (“fun facts”) they are given about this participant at the start of the experiment. To measure how participants navigate the room during this task, we use sociometric badges: small electronic devices participants can wear on their body and which track participant movement during the experiment. Participants (n ≤ 72, as limited by the number of available sociometric badges) will be university students who sign up for the event, which is marketed as a research study about networking. Registration: Upon arrival on the day of the event, students will be given an ID number, a preassigned random number between 0 and 100. This ID number will be clearly displayed on a yellow vest participants will wear for the duration of the experiment. Participants will also be given a sociometric badge that also carries their ID number. A sociometric badge is an electronic device that a participant wear on a lanyard, and which records their movement around the room with the purpose of establishing which other participants they are interacting with at which time. The sociometric badges achieve this by measuring the signal strength (based on ultra-wideband technology) to the badges used by all other participants at shorter than one second intervals. The badges measure the absolute and relative location of participants. The badges do not record conversations. Entry survey: After registration and a short introduction by the research team, participants will be instructed to complete a short entry survey on their mobile phone or other portable device. This entry survey is designed to collect the following information. • Basic personal background information, including gender and programme of study. We will not record any sensitive personal information or person-identifying information. • Some questions designed to measure key personality and cognition variables (e.g., Big Five, altruistic networking, self-monitoring, self-efficacy) that will serve as control variables in our analysis, as well as to compare the sample to our original study, but will not be used to test our hypothesis. • Which other participants they already personally know. Information on prior relationships between participants is necessary for us to assign as a search target in the network experiment someone they do not already know. • Two fun facts about themselves. The two fun facts will form the basis of the search task assigned to the participants. Examples of “fun facts” include: “I eat bread with peanut butter every day for breakfast” and “I am an opera singer in my free time”. Participants are instructed to convey something they believe is highly specific to themselves but not directly visible or traceable to their physical appearance (e.g., gender) or cultural background. The students will be reminded that the fun fact must be something that close friends, but not acquaintances or strangers, will likely know about them. The search task: The two fun facts will form the basis of the search task assigned to all participants: participants will be provided with two fun facts written by another participant and the simple task consists of finding that participant during the event. During the experiment, all participants will be simultaneously searching for someone while potentially being the search target for somebody else. It is at the discretion of participants to provide referrals to other participants during the task. The planned duration for the event is one hour. Assigning search targets will take place directly after all participants have completed the entry survey. Specifically, the survey tool will randomly assign up to five search targets to each participant from the subset of other participants whom they have indicated that do not already know (ensuring all targets are different, avoiding friends of friends, avoiding symmetric pairs, and avoiding any search target to be assigned to more than three participants in any round). The search target’s fun fact will be communicated via the tool used for the entry survey alongside basic instructions for their search: • Only talk in pairs. If a person you want to talk to is already talking to someone else, you will either need to wait until they become available or go and talk to another person. • Track your conversations on the survey tool. After each conversation, please use the tool indicating: 1. The ID number of the person you spoke to 2. If you enquired about the fun facts assigned to you 3. If so, is this person your search target (i.e., wrote the fun facts assigned to you), 4. If not, did this person refer you to someone else? And if so, to whom? • Start each conversation with an icebreaker question. Before enquiring about the “fun facts” assigned to you, you must first both ask your icebreaker question. You find these at the top of the survey page where you are tracking each conversation. • When you indicate you have found the person you were looking for, you will be automatically assigned a new pair of fun facts, so you can start looking for a second person, and then a third, etc. (if time permits). Participants will be instructed to remain seated until we verify that everyone has read the instructions. Then, the floor will open, and participants can start walking around the room. Experimental treatment: We will randomly assign 30% of participants to a treatment condition and the remainder to the control condition. Those in the treatment condition will receive the additional instruction that they have been selected for a “special role” in the game. Specifically, these participants are instructed to always wait for other people to approach them instead of taking the initiative in starting conversations, and to only enquire about their assigned fun facts once they have given the other person the chance to ask about theirs. The only exception is when they believe they have identified their search target, in which case they can approach them. These special instructions are included on the closing page with the assigned search targets and general instructions. Participants are instructed to keep their special role a secret to all other participants. The treatment is designed to create variation in the extent to which individuals initiate conversations, which will allow us to observe if initiation reduces the number of referrals individuals receive during the interactions in the experiment. This is in line with the following hypothesis: Hypothesis: Initiating conversations leads to fewer referrals than letting others approach. Incentive: The incentive for participation will be the chance to win a prize (EarPods). Participants are made aware that the quicker they reach their first search target (in terms of the number of people they speak to), the higher their chance of winning. Those in the treatment condition are additionally made aware that, due to their special treatment, their chance of winning is determined differently: the fewer times they wrongly approach who they believed was the target, the higher their chance of winning. Exit survey: After the event, participants will be asked to complete a short survey about their experiences during the game. This will include questions about the emotions felt during game and the perceived difficulty. We will also ask specific questions to test if the experimental manipulation was effective, such as about the perceived balance between initiating conversations and letting others approach. Hypothesis testing and effect sizes: We will test our above hypothesis by using a two-tailed t-test, where we compare the referral rate (received referral = 1, didn’t receive = 0) between all the interactions in each group. We do so using interaction level data (number of interactions producing a referral, over the total number of interactions capable of producing a referral, within treatment group). Referral rates for both groups (control and treatment) will range between 0 and 1. We calculate detectable effect sizes as follows. In the original study (69 participants, 45 minutes), there were a total of 571 interactions, i.e. 8.27 interactions per person. Scaled up to 72 participants during 60 minutes, this would mean a total of 849 conversations (note that the exact number is unpredictable). However, we must exclude certain types of interactions which could not possibly lead to a referral: those where the participant found their target, and those where the participant did not ask their question. This removes 36.4% of interactions, leaving 363 which may be used for our analysis of referral rates. Scaled up to 72 participants (as limited by the number of sociometric badges we have) and planned duration of the experiment (60 minutes), we expect a total of 505 interactions. Assuming that treated and control participants do not differ in the duration of interactions, this means an estimated 168 interactions for members of the treatment group, and 337 for members of the control group. Interactions between two treated participants should occur rarely or never). With this sample size, we can detect, at a significance level of p< 0.05 and statistical power of 0.8, a minimum effect size of Cohen’s d = 0.27. Since the effect size in the main study was 0.56 (strong effect), we expect to be able to find the same effect in the current study. Further information Research question: When searching for information during networking events, do those who let others approach them gain more referrals than those who initiate interactions themselves? Dependent variables: • Proportion of interactions that produce a referral (excluding interactions that cannot possibly produce a referral). Independent variable: • Initiation of interaction (ego vs. alter) • Treatment vs control Exclusion criteria: We will exclude interactions in which: (a) the participant did not ask about the fun fact, (b) the conversation resulted in finding the search target, or (c) initiation direction was unclear or not logged. Missing data: Missing survey data (e.g., incomplete intake surveys) will be excluded from analyses involving those variables. Missing badge data will be logged, and those participants may be excluded from interaction-level analyses if essential location/interaction data is missing. Data sharing plan: De-identified interaction-level and survey data will be uploaded to OSF after data collection, pending ethical approval and participant consent.

Perma.cc archive of https://www.cdc.gov/vaccinesafety/ensuringsafety/sideeffects/index.html created on 2022-03-22 07:45:46.041630+00:00.

UPDATE (18 Jul 2021) - This is an update of the previous registration. The following three points have been updated: 1) The Chinese Sense of Adversity Scale (CMSAS) now has a corresponding descriptive paragraph in the Measures section (this was accidentally omitted in the previous registration); 2) This new registration indicates the correct ranges of the scales for all questionnaires being completed by the participants (i.e., the ranges are identical to the original scales created by the authors, whereas in the previous registration it was mistakenly indicated that all of the scale ranges were changed to a 1-5 scale); 3) Finally, in the previous registration, in the Data Collection Procedures section it was indicated that there would be three self-report questions at the end of the study asking whether participants were paying attention during the study and answering questions accurately, however now it is also indicated how these questions will be used to exclude participants. NOTE: The new registration only contains changes to reflect these three errors, the actual online study being completed by participants has not been changed in any way, and the data collected so far has never been investigated in any way whatsoever. For someone having faced a significant stressor such as a serious accident, some form of assault or a chronic health issue, the high levels of resulting anxiety can lead to chronic forms of psychological dysfunction often labeled as posttraumatic stress (Rothschild, 2000). However, accepting and overcoming the psychological effects of significant adversity can require a person to surpass their previous level of functioning (Linley & Joseph, 2004). Currently, most of the research on adversarial growth is correlational and has focused on the relation between adversarial growth and variables which are not changeable. Benight and Bandura’s (2004) popular theoretical model of posttraumatic adaptation instead focuses on variables over which the individual can exert some control. Specifically, they suggest that beliefs of coping self-efficacy (i.e., perceptions of capability for handling stress) and resources such as social support (i.e., aid that is offered from one’s family and close friends) can be especially useful for recovery after adversity. In addition, based on prior research we believe that perceived benefit (i.e., the ability to find benefits in adversarial circumstances) is also a fundamental variable to consider in trying to influence adversarial growth (Linley & Joseph, 2005). As such, the purpose of the following study is to understand the degree to which self-efficacy, social support, and perceived benefit each predict adversarial growth among students who have been exposed to a significant adversarial event. More clearly, the purpose of this study is to investigate the relation between three main predictor variables (i.e., self-efficacy, social support, and perceived benefit) and two outcome variables (i.e., adversarial growth and severity of any trauma-like symptoms), all assessed via self-report questionnaires. We are measuring two outcome variables to examine how our predictor variables are related to both the positive and negative effects of significant adversity. We will also be measuring centrality to identity and trait anxiety so they can be used as moderator variables, as well as extraversion and optimism so they can be controlled for. We hypothesize that self-efficacy, social support and perceived benefit will all predict higher adversarial growth, especially among individuals who report low trait anxiety and high event centrality. We also hypothesize that self-efficacy, social support, and perceived benefit will all predict lower levels of post-traumatic stress symptoms, especially among individuals who report low trait anxiety and low event centrality. Additionally, on an exploratory basis, we are particularly interested in understanding which predictor(s) has the strongest relation with adversarial growth, and whether there are any interactions among predictors.

UPDATE (18 Jul 2021) - This is an update of the previous registration. The following three points have been updated: 1) The Chinese Sense of Adversity Scale (CMSAS) now has a corresponding descriptive paragraph in the Measures section (this was accidentally omitted in the previous registration); 2) This new registration indicates the correct ranges of the scales for all questionnaires being completed by the participants (i.e., the ranges are identical to the original scales created by the authors, whereas in the previous registration it was mistakenly indicated that all of the scale ranges were changed to a 1-5 scale); 3) Finally, in the previous registration, in the Data Collection Procedures section it was indicated that there would be three self-report questions at the end of the study asking whether participants were paying attention during the study and answering questions accurately, however now it is also indicated how these questions will be used to exclude participants. NOTE: The new registration only contains changes to reflect these three errors, the actual online study being completed by participants has not been changed in any way, and the data collected so far has never been investigated in any way whatsoever. For someone having faced a significant stressor such as a serious accident, some form of assault or a chronic health issue, the high levels of resulting anxiety can lead to chronic forms of psychological dysfunction often labeled as posttraumatic stress (Rothschild, 2000). However, accepting and overcoming the psychological effects of significant adversity can require a person to surpass their previous level of functioning (Linley & Joseph, 2004). Currently, most of the research on adversarial growth is correlational and has focused on the relation between adversarial growth and variables which are not changeable. Benight and Bandura’s (2004) popular theoretical model of posttraumatic adaptation instead focuses on variables over which the individual can exert some control. Specifically, they suggest that beliefs of coping self-efficacy (i.e., perceptions of capability for handling stress) and resources such as social support (i.e., aid that is offered from one’s family and close friends) can be especially useful for recovery after adversity. In addition, based on prior research we believe that perceived benefit (i.e., the ability to find benefits in adversarial circumstances) is also a fundamental variable to consider in trying to influence adversarial growth (Linley & Joseph, 2005). As such, the purpose of the following study is to understand the degree to which self-efficacy, social support, and perceived benefit each predict adversarial growth among students who have been exposed to a significant adversarial event. More clearly, the purpose of this study is to investigate the relation between three main predictor variables (i.e., self-efficacy, social support, and perceived benefit) and two outcome variables (i.e., adversarial growth and severity of any trauma-like symptoms), all assessed via self-report questionnaires. We are measuring two outcome variables to examine how our predictor variables are related to both the positive and negative effects of significant adversity. We will also be measuring centrality to identity and trait anxiety so they can be used as moderator variables, as well as extraversion and optimism so they can be controlled for. We hypothesize that self-efficacy, social support and perceived benefit will all predict higher adversarial growth, especially among individuals who report low trait anxiety and high event centrality. We also hypothesize that self-efficacy, social support, and perceived benefit will all predict lower levels of post-traumatic stress symptoms, especially among individuals who report low trait anxiety and low event centrality. Additionally, on an exploratory basis, we are particularly interested in understanding which predictor(s) has the strongest relation with adversarial growth, and whether there are any interactions among predictors.

UPDATE (18 Jul 2021) - This is an update of the previous registration. The following three points have been updated: 1) The Chinese Sense of Adversity Scale (CMSAS) now has a corresponding descriptive paragraph in the Measures section (this was accidentally omitted in the previous registration); 2) This new registration indicates the correct ranges of the scales for all questionnaires being completed by the participants (i.e., the ranges are identical to the original scales created by the authors, whereas in the previous registration it was mistakenly indicated that all of the scale ranges were changed to a 1-5 scale); 3) Finally, in the previous registration, in the Data Collection Procedures section it was indicated that there would be three self-report questions at the end of the study asking whether participants were paying attention during the study and answering questions accurately, however now it is also indicated how these questions will be used to exclude participants. NOTE: The new registration only contains changes to reflect these three errors, the actual online study being completed by participants has not been changed in any way, and the data collected so far has never been investigated in any way whatsoever. For someone having faced a significant stressor such as a serious accident, some form of assault or a chronic health issue, the high levels of resulting anxiety can lead to chronic forms of psychological dysfunction often labeled as posttraumatic stress (Rothschild, 2000). However, accepting and overcoming the psychological effects of significant adversity can require a person to surpass their previous level of functioning (Linley & Joseph, 2004). Currently, most of the research on adversarial growth is correlational and has focused on the relation between adversarial growth and variables which are not changeable. Benight and Bandura’s (2004) popular theoretical model of posttraumatic adaptation instead focuses on variables over which the individual can exert some control. Specifically, they suggest that beliefs of coping self-efficacy (i.e., perceptions of capability for handling stress) and resources such as social support (i.e., aid that is offered from one’s family and close friends) can be especially useful for recovery after adversity. In addition, based on prior research we believe that perceived benefit (i.e., the ability to find benefits in adversarial circumstances) is also a fundamental variable to consider in trying to influence adversarial growth (Linley & Joseph, 2005). As such, the purpose of the following study is to understand the degree to which self-efficacy, social support, and perceived benefit each predict adversarial growth among students who have been exposed to a significant adversarial event. More clearly, the purpose of this study is to investigate the relation between three main predictor variables (i.e., self-efficacy, social support, and perceived benefit) and two outcome variables (i.e., adversarial growth and severity of any trauma-like symptoms), all assessed via self-report questionnaires. We are measuring two outcome variables to examine how our predictor variables are related to both the positive and negative effects of significant adversity. We will also be measuring centrality to identity and trait anxiety so they can be used as moderator variables, as well as extraversion and optimism so they can be controlled for. We hypothesize that self-efficacy, social support and perceived benefit will all predict higher adversarial growth, especially among individuals who report low trait anxiety and high event centrality. We also hypothesize that self-efficacy, social support, and perceived benefit will all predict lower levels of post-traumatic stress symptoms, especially among individuals who report low trait anxiety and low event centrality. Additionally, on an exploratory basis, we are particularly interested in understanding which predictor(s) has the strongest relation with adversarial growth, and whether there are any interactions among predictors.

Since the terrorist attacks on September 11, 2001, the threat of a biological or chemical terrorist attack on our society has transformed from a distant unease to a major, looming concern. National, state and local organizations are trying to prepare themselves for a threat that is of terrifying consequences and yet ambiguous in how or if it will even present. This effort aimed to understand the cognitive demands faced by first responders to biological and chemical terrorist events. Data collection involved employing Cognitive Task Analysis (CTA) interviews with officials at the local and federal level, attending a conference outlining major research advances in this area, and collecting observations at regional bioterrorism exercises. This report describes the findings using the Advanced Team Decision Making model (Zsambok, Klein, Kyne and Klinger, 1992) as a framework for understanding the challenges teams face in rapidly building and developing their situational understanding in response to these events. The findings from this study are important leverage points for understanding current gaps in response preparedness and areas for future research and development.

Since the terrorist attacks on September 11, 2001, the threat of a biological or chemical terrorist attack on our society has transformed from a distant unease to a major, looming concern. National, state and local organizations are trying to prepare themselves for a threat that is of terrifying consequences and yet ambiguous in how or if it will even present. This effort aimed to understand the cognitive demands faced by first responders to biological and chemical terrorist events. Data collection involved employing Cognitive Task Analysis (CTA) interviews with officials at the local and federal level, attending a conference outlining major research advances in this area, and collecting observations at regional bioterrorism exercises. This report describes the findings using the Advanced Team Decision Making model (Zsambok, Klein, Kyne and Klinger, 1992) as a framework for understanding the challenges teams face in rapidly building and developing their situational understanding in response to these events. The findings from this study are important leverage points for understanding current gaps in response preparedness and areas for future research and development.

Since the terrorist attacks on September 11, 2001, the threat of a biological or chemical terrorist attack on our society has transformed from a distant unease to a major, looming concern. National, state and local organizations are trying to prepare themselves for a threat that is of terrifying consequences and yet ambiguous in how or if it will even present. This effort aimed to understand the cognitive demands faced by first responders to biological and chemical terrorist events. Data collection involved employing Cognitive Task Analysis (CTA) interviews with officials at the local and federal level, attending a conference outlining major research advances in this area, and collecting observations at regional bioterrorism exercises. This report describes the findings using the Advanced Team Decision Making model (Zsambok, Klein, Kyne and Klinger, 1992) as a framework for understanding the challenges teams face in rapidly building and developing their situational understanding in response to these events. The findings from this study are important leverage points for understanding current gaps in response preparedness and areas for future research and development.

Since the terrorist attacks on September 11, 2001, the threat of a biological or chemical terrorist attack on our society has transformed from a distant unease to a major, looming concern. National, state and local organizations are trying to prepare themselves for a threat that is of terrifying consequences and yet ambiguous in how or if it will even present. This effort aimed to understand the cognitive demands faced by first responders to biological and chemical terrorist events. Data collection involved employing Cognitive Task Analysis (CTA) interviews with officials at the local and federal level, attending a conference outlining major research advances in this area, and collecting observations at regional bioterrorism exercises. This report describes the findings using the Advanced Team Decision Making model (Zsambok, Klein, Kyne and Klinger, 1992) as a framework for understanding the challenges teams face in rapidly building and developing their situational understanding in response to these events. The findings from this study are important leverage points for understanding current gaps in response preparedness and areas for future research and development.

Removable media, such as universal serial bus (USB) flash drives, present unique problems to the enterprise since insiders can use such media to remove proprietary information from company systems. Insiders may do this for legitimate reasons, such as to work on material at home, or they may do so for malicious reasons, such as to steal intellectual property. Organizations must establish and implement effective methods and processes to prevent unauthorized use of removable media while still allowing users with a genuine business need to access and remove such media. In addition, organizations should establish sound methods to track critical electronic assets so that they may better protect them. This report focuses on the theft of intellectual property using removable media, in particular, USB devices. We present methods to control removable media devices in a Microsoft Windows environment using Group Policy within an Active Directory environment. We also explore OpenDLP, an open source tool for identifying where sensitive data resides on organizational systems.

Removable media, such as universal serial bus (USB) flash drives, present unique problems to the enterprise since insiders can use such media to remove proprietary information from company systems. Insiders may do this for legitimate reasons, such as to work on material at home, or they may do so for malicious reasons, such as to steal intellectual property. Organizations must establish and implement effective methods and processes to prevent unauthorized use of removable media while still allowing users with a genuine business need to access and remove such media. In addition, organizations should establish sound methods to track critical electronic assets so that they may better protect them. This report focuses on the theft of intellectual property using removable media, in particular, USB devices. We present methods to control removable media devices in a Microsoft Windows environment using Group Policy within an Active Directory environment. We also explore OpenDLP, an open source tool for identifying where sensitive data resides on organizational systems.

The detection and identification of extreme weather events in large-scale climate simulations is an important problem for risk management, informing governmental policy decisions and advancing our basic understanding of the climate system. Recent work has shown that fully supervised convolutional neural networks (CNNs) can yield acceptable accuracy for classifying well-known types of extreme weather events when large amounts of labeled data are available. However, many different types of spatially localized climate patterns are of interest including hurricanes, extra-tropical cyclones, weather fronts, and blocking events among others. Existing labeled data for these patterns can be incomplete in various ways, such as covering only certain years or geographic areas and having false negatives. This type of climate data therefore poses a number of interesting machine learning challenges. We present a multichannel spatiotemporal CNN architecture for semi-supervised bounding box prediction and exploratory data analysis. We demonstrate that our approach is able to leverage temporal information and unlabeled data to improve the localization of extreme weather events. Further, we explore the representations learned by our model in order to better understand this important data. We present a dataset, ExtremeWeather, to encourage machine learning research in this area and to help facilitate further work in understanding and mitigating the effects of climate change. The dataset is available at extremeweatherdataset.github.io and the code is available at https://github.com/eracah/hur-detect. ## Citation Racah, Evan, et al. "ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events." Advances in Neural Information Processing Systems. 2017. ## Pictures https://extremeweatherdataset.github.io/variables.jpg

The detection and identification of extreme weather events in large-scale climate simulations is an important problem for risk management, informing governmental policy decisions and advancing our basic understanding of the climate system. Recent work has shown that fully supervised convolutional neural networks (CNNs) can yield acceptable accuracy for classifying well-known types of extreme weather events when large amounts of labeled data are available. However, many different types of spatially localized climate patterns are of interest including hurricanes, extra-tropical cyclones, weather fronts, and blocking events among others. Existing labeled data for these patterns can be incomplete in various ways, such as covering only certain years or geographic areas and having false negatives. This type of climate data therefore poses a number of interesting machine learning challenges. We present a multichannel spatiotemporal CNN architecture for semi-supervised bounding box prediction and exploratory data analysis. We demonstrate that our approach is able to leverage temporal information and unlabeled data to improve the localization of extreme weather events. Further, we explore the representations learned by our model in order to better understand this important data. We present a dataset, ExtremeWeather, to encourage machine learning research in this area and to help facilitate further work in understanding and mitigating the effects of climate change. The dataset is available at extremeweatherdataset.github.io and the code is available at https://github.com/eracah/hur-detect. ## Citation Racah, Evan, et al. "ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events." Advances in Neural Information Processing Systems. 2017. ## Pictures https://extremeweatherdataset.github.io/variables.jpg

Common envelope events are important interactions between two binary stars that lead to the formation of close binary systems. We present here a systematic three-dimensional study in which we model common envelope events with low-mass giant donors. The results allow us to revise the energy formalism that is usually used to determine common envelope event outcomes. We show that the energy budget for this type of system should include the recombination energy, and that it also must take into account that a significant fraction of the released orbital energy is taken away by the ejecta. We provide three ways in which our results can be used by binary population synthesis studies: a relation that links the observed post-common envelope binary with the initial binary parameters, a fitting formula for the $\alpha_{\rm ce}\lambda$ parameter of the standard energy formalism, and a revised energy formalism that takes into account both the recombination energy and the energy that is taken away by the ejecta.

Last year, school leaders were faced with unprecedented challenges as they grappled with school closures, the shift to online and hybrid models of instruction, and supporting their communities with an increased awareness of the need for social justice reform. The COVID-19 pandemic and killings of Ahmaud Arbery, Breonna Taylor, George Floyd, and others shined the light on inequities that have existed in our public education system for far too long. In response to these challenges, NSBA issued its guide entitled, "Reimagining School Board Leadership: Actions for Equity." This resource was a collaboration between NSBA's Dismantling Institutional Racism in Education (DIRE) initiative and Center for Safe Schools and focused on acknowledging and understanding current events and the historical issues of systemic racism in America. This resource established a call for school boards to rise to the current challenges our school systems are facing to transform public education, with a focus on equitable access to world-class education for every student. This "Questions for Boards to Ask Supplemental Guide" provides additional resources on how school boards can engage in conversations to drive this work forward. [This report was made with contributions from Aetna, BoardDocs, Crayola, and Hennes Communications. It is a publication by NSBA's DIRE (Dismantling Institutional Racism in Education) Initiative and the Center for Safe Schools. For "Reimagining School Board Leadership: Actions for Equity," see ED626157.]

"Scripts" are ways of describing the knowledge a person must have in order to understand the appropriate response in a given situation. In this document, literature on the ways in which children acquire scripts for social behavior through interaction with others is reviewed, and some departures from script theory are discussed. It is noted that most theories of human development acknowledge that interaction with adults is critical for a child's social, emotional, and cognitive growth. Examples of studies that use notions from script theory and a Vygotskian perspective to explain children's understanding of social events are provided. The final section of the paper describes a progress report on a project investigating the contributions made to children's event scripts by parents and by teachers in an early childhood center attended by the children. The project began as an effort to study the idea that parents and early childhood staff play complementary roles in children's lives. The methodology took account of both psychological and social processes. It was concluded that the event of becoming part of a group might be a good context for studying the contribution of staff and parents to children's understanding of the early childhood center. Contains 29 references. (LB)

"Scripts" are ways of describing the knowledge a person must have in order to understand the appropriate response in a given situation. In this document, literature on the ways in which children acquire scripts for social behavior through interaction with others is reviewed, and some departures from script theory are discussed. It is noted that most theories of human development acknowledge that interaction with adults is critical for a child's social, emotional, and cognitive growth. Examples of studies that use notions from script theory and a Vygotskian perspective to explain children's understanding of social events are provided. The final section of the paper describes a progress report on a project investigating the contributions made to children's event scripts by parents and by teachers in an early childhood center attended by the children. The project began as an effort to study the idea that parents and early childhood staff play complementary roles in children's lives. The methodology took account of both psychological and social processes. It was concluded that the event of becoming part of a group might be a good context for studying the contribution of staff and parents to children's understanding of the early childhood center. Contains 29 references. (LB)