Miracle-dz/UniFAR-FTUs huggingface dataset:
‘It Depends’: A qualitative study on how adolescent students explain bystander intervention and non-intervention in bullying situations

The aim of the current study was to examine how junior high school students interpret, motivate, and explain various bystander behaviors in bullying situations. The participants were 17 junior high school students recruited from four schools in Sweden. Semi-structured interviews were conducted and analysed with grounded theory methods. The analysis generated a conceptual model of bystander interpreting–considering process in school bullying. A core category named ‘it depends’ was developed to explain how the participants in the study motivated their own and their peers’ actions as bystanders in various bullying situations. Whether they intervened or not depended on how they interpreted the situation in terms of: (a) seriousness of the situation, including trivialization; (b) social relationships with the involved; (c) locus of responsibility, including displacement of responsibility, and victim blame; (d) social status; (e) perception of risk; and (f) defender self-efficacy. The implications of these results for bullying prevention and intervention efforts are discussed.
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

We introduce a method to train Quantized Neural Networks (QNNs) -- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time. At traintime the quantized weights and activations are used for computing the parameter gradients. During the forward pass, QNNs drastically reduce memory size and accesses, and replace most arithmetic operations with bit-wise operations. As a result, power consumption is expected to be drastically reduced. We trained QNNs over the MNIST, CIFAR-10, SVHN and ImageNet datasets. The resulting QNNs achieve prediction accuracy comparable to their 32-bit counterparts. For example, our quantized version of AlexNet with 1-bit weights and 2-bit activations achieves 51% top-1 accuracy. Moreover, we quantize the parameter gradients to 6-bits as well which enables gradients computation using only bit-wise operation. Quantized recurrent neural networks were tested over the Penn Treebank dataset, and achieved comparable accuracy as their 32-bit counterparts using only 4-bits. Last but not least, we programmed a binary matrix multiplication GPU kernel with which it is possible to run our MNIST QNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy. The QNN code is available online.
Direct‐Push Electrical Conductivity Logging for High‐Resolution Hydrostratigraphic Characterization

Fine‐scale hydrostratigraphic features often play a critical role in controlling ground water flow and contaminant transport. Unfortunately, many conventional drilling‐ and geophysics‐based approaches are rarely capable of describing these features at the level of detail needed for contaminant predictions and remediation designs. Previous work has shown that direct‐push electrical conductivity (EC) logging can provide information about site hydrostratigraphy at a scale of relevance for contaminant transport investigations in many unconsolidated settings. In this study, we evaluate the resolution and quality of that information at a well‐studied research site that is underlain by highly stratified alluvial sediments. Geologic and hydrologic data, conventional geophysical logs, and particle‐size analyses are used to demonstrate the capability of direct‐push EC logging for the delineation of fine‐scale hydrostratigraphic features in saturated unconsolidated formations. When variations in pore‐fluid chemistry are small, the electrical conductivity of saturated media is primarily a function of clay content, and hydrostratigraphic features can be described at a level of detail (<2.5 cm in thickness) that has not previously been possible in the absence of continuous cores. Series of direct‐push EC logs can be used to map the lateral continuity of layers with non‐negligible clay content and to develop important new insights into flow and transport at a site. However, in sand and gravel intervals with negligible clay, EC logging provides little information about hydrostratigraphic features. As with all electrical logging methods, some site‐specific information about the relative importance of fluid and sediment contributions to electrical conductivity is needed. Ongoing research is directed at developing direct‐push methods that allow EC logging, water sampling, and hydraulic testing to be done concurrently.
Anti-social Punishment Can Prevent the Co-evolution of Punishment and Cooperation

Keywords: Evolutionary game theory Prisoner's dilemma Public goods game Structured populations Spite a b s t r a c t The evolution of cooperation is one of the great puzzles in evolutionary biology. Punishment has been suggested as one solution to this problem. Here punishment is generally defined as incurring a cost to inflict harm on a wrong-doer. In the presence of punishers, cooperators can gain higher payoffs than non-cooperators. Therefore cooperation may evolve as long as punishment is prevalent in the population. Theoretical models have revealed that spatial structure can favor the co-evolution of punishment and cooperation, by allowing individuals to only play and compete with those in their immediate neighborhood. However, those models have usually assumed that punishment is always targeted at non-cooperators. In light of recent empirical evidence of punishment targeted at cooperators, we relax this assumption and study the effect of so-called 'anti-social punishment'. We find that evolution can favor antisocial punishment, and that when antisocial punishment is possible costly punishment no longer promotes cooperation. As there is no reason to assume that cooperators cannot be the target of punishment during evolution, our results demonstrate serious restrictions on the ability of costly punishment to allow the evolution of cooperation in spatially structured populations. Our results also help to make sense of the empirical observation that defectors will sometimes pay to punish cooperators. Explaining the evolution of cooperation is an issue of central importance in evolutionary biology as well as the social sciences. Why does the competitive process of natural selection often lead to altruistic cooperation, in which individuals pay a cost to give a benefit to others? To answer this question, numerous mechanisms for the evolution of cooperation have been proposed In direct reciprocity, my actions towards you depend on what you have done to me in the past. Axelrod (1984) found that the tit-for-tat (TFT) strategy was a winning strategy in his computer tournament. A TFT player cooperates in the first round of the repeated interaction. After the first round, a TFT player takes whatever action his opponent took in the previous round. For example, an ALLD player, who always defects in a repeated interaction, receives cooperation from a TFT player in the first round. However, the ALLD player is 'punished' by TFT with mutual defection in subsequent rounds. Therefore, cheating does not pay if the repeated interaction lasts long enough, and the TFT strategy …
The effects of reader-generated and previously existing text marking on comprehension in readers of different skill levels

Previous research examining effects of previously existing and reader generated text marking has failed to demonstrate whether or not it is beneficial or detrimental to the reader. Furthermore, whether or not text marking has differential effects on readers of different skill has not been determined. The studies reported here attempted to clarify the questions that remain about the effects of text marking on comprehension, in readers of different skill levels, through analysis of marking in student textbooks as well as through the use of experimental methods. Study 1 demonstrated that low-skill readers claim to highlight on more occasions when studying, but do not claim to mark more of the text. However, textbook analyses failed to support this finding. Additionally, lowskill readers claim to prefer a previously marked textbook to a greater degree than high-skill readers. Study 2 found that low-skill readers claim to, and use text-marking strategies more often and mark more of the text than high-skill readers. Study 2 also confirmed that low-skill readers report higher preference for studying previously marked texts and a tendency to study only material marked by a previous reader. Finally, Study 2 demonstrated that low-skill readers are less capable of identifying the most relevant material in textbooks and that this inability is related to poorer course performance. The finding that low-skill readers report greater reliance on previously marked material, use text-marking strategies more often, and are less capable of identifying the most relevant material suggests that many low-skill readers study irrelevant material in textbooks. Study 3 examined the effects of irrelevant text marking on comprehension and found that low-skill readers are differentially affected by the presence of irrelevant marking, such that the study of text containing irrelevant marking leads to poorer comprehension. Practical implications of these findings and suggestions for future research are discussed.
The Evolution of Social and Economic Networks

We examine the dynamic formation and stochastic evolution of networks connecting individuals whose payoffs from an economic or social activity depends on the network structure in place. Over time, individuals form and sever links connecting themselves to other individuals based on the improvement the resulting network offers them relative to the current network. Such a process creates a sequence of networks that we call an 'improving path'. The changes made along an improving path make the individuals, who added or deleted the relevant link(s) at each date, better off. Such sequences of networks can cycle, and we study conditions on underlying allocation rules that characterize cycles. Building on an understanding of improving paths, we consider a stochastic evolutionary process where in addition to intended changes in the network there is a small probability of unintended changes or errors. Predictions can be made regarding the relative likelihood that the stochastic evolutionary process will lead to any given network at some time. The evolutionary process selects from among the statically stable networks and cycles. We show that in some cases, the evolutionary process selects inefficient networks even though eAEcient ones are statically stable. We apply these results to the matching literature to show that there are contexts in which the evolutionarily stable networks coincide with the core stable networks, and thus achieve eAEciency.
Aberrant Hedgehog Ligands Induce Progressive Pancreatic Fibrosis by Paracrine Activation of Myofibroblasts and Ductular Cells in Transgenic Zebrafish

Hedgehog (Hh) signaling is frequently up-regulated in fibrogenic pancreatic diseases including chronic pancreatitis and pancreatic cancer. Although recent series suggest exclusive paracrine activation of stromal cells by Hh ligands from epithelial components, debates still exist on how Hh signaling works in pathologic conditions. To explore how Hh signaling affects the pancreas, we investigated transgenic phenotypes in zebrafish that over-express either Indian Hh or Sonic Hh along with green fluorescence protein (GFP) to enable real-time observation, or GFP alone as control, at the ptf1a domain. Transgenic embryos and zebrafish were serially followed for transgenic phenotypes, and investigated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR), in situ hybridization, and immunohistochemistry. Over-expression of Ihh or Shh reveals virtually identical phenotypes. Hh induces morphologic changes in a developing pancreas without derangement in acinar differentiation. In older zebrafish, Hh induces progressive pancreatic fibrosis intermingled with proliferating ductular structures, which is accompanied by the destruction of the acinar structures. Both myofibroblasts and ductular are activated and proliferated by paracrine Hh signaling, showing restricted expression of Hh downstream components including Patched1 (Ptc1), Smoothened (Smo), and Gli1/2 in those Hh-responsive cells. Hh ligands induce matrix metalloproteinases (MMPs), especially MMP9 in all Hh-responsive cells, and transform growth factor-ß1 (TGFß1) only in ductular cells. Aberrant Hh over-expression, however, does not induce pancreatic tumors. On treatment with inhibitors, embryonic phenotypes are reversed by either cyclopamine or Hedgehog Primary Inhibitor-4 (HPI-4). Pancreatic fibrosis is only prevented by HPI-4. Our study provides strong evidence of Hh signaling which induces pancreatic fibrosis through paracrine activation of Hh-responsive cells in vivo. Induction of MMPs and TGFß1 by Hh signaling expands on the current understanding of how Hh signaling affects fibrosis and tumorigenesis. These transgenic models will be a valuable platform in exploring the mechanism of fibrogenic pancreatic diseases which are induced by Hh signaling activation.
Comparison of Modern Stroke Thrombectomy Approaches Using an In Vitro Cerebrovascular Occlusion Model

BACKGROUND AND PURPOSE: A new in vitro cerebrovascular occlusion model of the intracranial circulation was developed recently for testing thrombectomy devices. Using this model, we compared recanalization success associated with different modern endovascular thrombectomy approaches. MATERIALS AND METHODS: Model experiments were performed in 4 thrombectomy test groups: 1) primary or direct Stentriever thrombectomy with a conventional guide catheter (control group), 2) primary Stentriever thrombectomy with a balloon-guide catheter, 3) combined Stentriever–continuous aspiration approach, and 4) direct aspiration alone. Successful recanalization was defined as a TICI score of 2b or 3. RESULTS: Seventy-one thrombectomy experiments were conducted. Similar rates of TICI 2b–3 scores were achieved with balloon-guide and conventional guide catheters (P = .34). The combined Stentriever plus aspiration approach and the primary aspiration thrombectomy resulted in significantly higher rates of TICI 2b or 3 than the conventional guide-catheter approach in the control group (P = .008 and P = .0001, respectively). The primary Stentriever thrombectomy with the conventional guide catheter showed the highest rate of embolization to new territories (53%). CONCLUSIONS: Data from our in vitro model experiments show that the Stentriever thrombectomy under continuous aspiration and primary aspiration thrombectomy approaches led to the highest degree of recanalization.
The Impact of Skewness and Fat Tails on the Asset Allocation Decision

The authors modeled the non-normal returns of multiple asset classes by using a multivariate truncated Lévy flight distribution and incorporating non-normal returns into the mean-conditional value at risk (M-CVaR) optimization framework. In a series of controlled optimizations, they found that both skewness and kurtosis affect the M-CVaR optimization and lead to substantially different allocations than do the traditional mean–variance optimizations. They also found that the M-CVaR optimization would have been beneficial during the 2008 financial crisis. Although practitioners are well aware that asset returns are not normally distributed and that investor preferences often go beyond mean and variance, the implications for portfolio choice are not well known. In a series of controlled traditional mean–variance optimizations (MVOs) and mean-conditional value at risk (M-CVaR) optimizations, we gained insights into the ramifications of skewness and kurtosis for optimal asset allocations. In our first four scenarios, prior to running the optimizations, we used the multivariate TLF distribution model to simulate a large number of returns with appropriate variance, skewness, and kurtosis, which, in turn, enabled us to more accurately measure the downside risk of a portfolio by using the CVaR. In our first example, in which returns are symmetrically distributed and have uniform tails, the MVO and the M-CVaR lead to the same results. When there are varying levels of skewness and kurtosis in the opportunity set of assets, the MVO and the M-CVaR lead to significantly different asset allocations. In particular, the combination of a negative skewness and a fat tail has the greatest impact on the optimal asset allocation weights. Intuitively, the M-CVaR prefers assets with higher positive skewness, lower kurtosis, and lower variance. Over the last 20 years, global high yield, U.S. REITs, U.S. TIPS, and value stocks have had significant negative skewness, whereas non-U.S. government bonds have had positive skewness. The kurtosis for global high yield, U.S. REITs, and U.S. TIPS is higher than it is for other asset classes. In a 14-asset-class bootstrapping analysis, the M-CVaR, relative to the MVO, leads to significantly higher allocations to non-U.S. government bonds and U.S. nominal bonds and lower allocations to global high yield, U.S. REITs, and commodities. An out-of-sample test showed that the M-CVaR outperformed the MVO in the financial crisis of 2008, with excess gains ranging from 0.84 percentage point to 1.44 percentage points across the efficient frontier. This outperformance suggests that higher-moment information embedded in historical returns had some predictive power in the crisis. Although we are just beginning to understand the impact of higher moments on asset allocation policy and further study is needed, these optimizations drive home a critical implication of modern portfolio theory: What matters is the overall impact on the portfolio’s characteristics.
Consumption Strikes Back ? : Measuring Long-Run Risk 1

We characterize and measure a long-run risk-return tradeoff for the valuation of cash flows exposed to fluctuations in macroeconomic growth. This tradeoff features risk prices of cash flows that are realized far into the future but are reflected in asset values. We apply this analysis to claims on aggregate cash flows, as well as to cash flows from value and growth portfolios. Based on vector autoregressions, we characterize the dynamic response of cash flows to macroeconomic shocks and document that there are important differences in the long-run responses. We isolate those features of a recursive utility model and the consumption dynamics needed for the long-run valuation differences among these portfolios to be sizable. Finally, we show how the resulting measurements vary when we alter the statistical specifications of cash flows and consumption growth.
Interplay of demographic variables, birth experience, and initial reactions in the prediction of symptoms of posttraumatic stress one year after giving birth

Background There has been increasing research on posttraumatic stress disorder (PTSD) following childbirth in the last two decades. The literature on predictors of who develops posttraumatic stress symptoms (PSS) suggests that both vulnerability and birth factors have an influence, but many studies measure predictors and outcomes simultaneously. Objective In this context, we aimed to examine indirect and direct effects of predictors of PSS, which were measured longitudinally. Method We assessed women within the first days (n=353), 6 weeks, and 12 months (n=183) after having given birth to a healthy infant. The first assessment included questions on demographics, pregnancy, and birth experience. The second and third assessments contained screenings for postpartum depression, PTSD, and general mental health problems, as well as assessing social support and physical well-being. We analysed our data using structural equation modelling techniques (n=277). Results Our final model showed good fit and was consistent with a diathesis-stress model of PSS. Women who had used antidepressant medication in the 10 years before childbirth had higher PSS at 6 weeks, independent of birth experiences. Subjective birth experience was the early predictor with the highest total effect on later PSS. Interestingly, a probable migration background also had a small but significant effect on PSS via more episiotomies. The null results for social support may have been caused by a ceiling effect. Conclusions Given that we measured predictors at different time points, our results lend important support to the etiological model, namely, that there is a vulnerability pathway and a stress pathway leading to PSS. PSS and other psychological measures stayed very stable between 6 weeks and 1 year postpartum, indicating that it is possible to identify women developing problems early. Highlights of the article Our results are consistent with a diathesis-stress model: vulnerability (antidepressant use in the previous 10 years) influenced posttraumatic stress symptoms at 6 weeks and 1 year, independently of stress (birth-related variables). The strongest predictor of posttraumatic stress symptoms 1 year postpartum was posttraumatic stress symptoms 6 weeks postpartum. This means that women who develop problems could be identified during routinely offered postpartum care. Women with a probable migration background experienced more PSS 1 year after the birth, which was an indirect effect through more episiotomies and more PSS after 6 weeks.
Positive priming and intentional binding: Eye-blink rate predicts reward information effects on the sense of agency

Human society is strongly rooted in people's experiences of agency; that is, the pervasive feeling that one engages in voluntary behavior and causes one's own actions and resulting outcomes. Rewards and positive affect play an important role in the control of voluntary action. However, the role of positive reward signals in the sense of agency is poorly understood. This study examined effects of reward-related information on the sense of agency by employing the intentional binding paradigm. This paradigm measures the extent to which actions and their effects subjectively shift together across time, reflecting a crucial component of people's sense of agency. Results showed that intentional binding is stronger when participants are primed with reward-related information via brief exposure to positive pictures. Interestingly, this positive priming effect was moderated by baseline eye-blink rates (an indirect marker of striatal dopaminergic functioning); reward-related information increased intentional binding mainly for participants displaying higher baseline eye-blink rates. These findings suggest a possible role for striatal dopamine activity in the process by which reward-related information shapes the way people see themselves as agents.