nils-herrmann/clean_scirepeval huggingface dataset:
A molecular and cellular theory of depression.

Recent studies have begun to characterize the actions of stress and antidepressant treatments beyond the neurotransmitter and receptor level. This work has demonstrated that long-term antidepressant treatments result in the sustained activation of the cyclic adenosine 3',5'-monophosphate system in specific brain regions, including the increased function and expression of the transcription factor cyclic adenosine monophosphate response element-binding protein. The activated cyclic adenosine 3',5'-monophosphate system leads to the regulation of specific target genes, including the increased expression of brain-derived neurotrophic factor in certain populations of neurons in the hippocampus and cerebral cortex. The importance of these changes is highlighted by the discovery that stress can decrease the expression of brain-derived neurotrophic factor and lead to atrophy of these same populations of stress-vulnerable hippocampal neurons. The possibility that the decreased size and impaired function of these neurons may be involved in depression is supported by recent clinical imaging studies, which demonstrate a decreased volume of certain brain structures. These findings constitute the framework for an updated molecular and cellular hypothesis of depression, which posits that stress-induced vulnerability and the therapeutic action of antidepressant treatments occur via intracellular mechanisms that decrease or increase, respectively, neurotrophic factors necessary for the survival and function of particular neurons. This hypothesis also explains how stress and other types of neuronal insult can lead to depression in vulnerable individuals and it outlines novel targets for the rational design of fundamentally new therapeutic agents.
Cellphone identification using noise estimates from recorded audio

Rapid developments in technologies related to cell phones have resulted in their much broader usage than mere talking devices used for making and receiving phone calls. User-generated audio recordings from cell phones can be very helpful in a number of forensic applications. This paper proposes a novel system for cellphone identification from speech samples recorded using the cellphone. The proposed system uses features based on estimates of noise associated with recordings and classifies them using sequential minimal optimization (SMO) based Support vector machine (SVM). The performance of the proposed system is tested on a custom database of twenty-six cell phones of five different manufacturers. The proposed system shows promising results with average classification accuracy around 90% for classifying cell phones belonging to five different manufacturers. The average classification accuracy reduces when all the cell phones belong to the same manufacturer.
Peer support services for individuals with serious mental illnesses: assessing the evidence.

This review assessed the level of evidence and effectiveness of peer support services delivered by individuals in recovery to those with serious mental illnesses or co-occurring mental and substance use disorders.



Authors searched PubMed, PsycINFO, Applied Social Sciences Index and Abstracts, Sociological Abstracts, Social Services Abstracts, Published International Literature on Traumatic Stress, the Educational Resources Information Center, and the Cumulative Index to Nursing and Allied Health Literature for outcome studies of peer support services from 1995 through 2012. They found 20 studies across three service types: peers added to traditional services, peers in existing clinical roles, and peers delivering structured curricula. Authors judged the methodological quality of the studies using three levels of evidence (high, moderate, and low). They also described the evidence of service effectiveness.



The level of evidence for each type of peer support service was moderate. Many studies had methodological shortcomings, and outcome measures varied. The effectiveness varied by service type. Across the range of methodological rigor, a majority of studies of two service types--peers added and peers delivering curricula--showed some improvement favoring peers. Compared with professional staff, peers were better able to reduce inpatient use and improve a range of recovery outcomes, although one study found a negative impact. Effectiveness of peers in existing clinical roles was mixed.



Peer support services have demonstrated many notable outcomes. However, studies that better differentiate the contributions of the peer role and are conducted with greater specificity, consistency, and rigor would strengthen the evidence.
Healthy food subsidies and unhealthy food taxation: A systematic review of the evidence.

The Global Burden of Disease Study and related studies report unhealthy diet is the leading risk for death and disability globally. Given the evidence associating diet and non-communicable diseases (NCDs), international and national health bodies including the World Health Organization and United Nations have called for population health interventions to improve diet as a means to target NCDs. One of the proposed interventions is to ensure healthy foods/beverages are more accessible to purchasers and unhealthy ones less accessible via fiscal policy, namely taxation and subsidies. The objective of this systematic review was to evaluate the evidence base to assess the effect of healthy food/beverage subsidies and unhealthy food/beverage taxation. A comprehensive review was conducted by searching PubMed, Medline, and Google Scholar for peer-reviewed publications and seventy-eight studies were identified for inclusion in this review. This review was performed in keeping with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. Although moderate in quality, there was consistent evidence that taxation and subsidy intervention influenced dietary behaviors. The quality, level and strength of evidence along with identified gaps in research support the need for further policies and ongoing evaluation of population-wide food/beverage subsidies and taxation. To maximize success and effect, this review suggests that food taxes and subsidies should be a minimum of 10 to 15% and preferably used in tandem. Implementation of population-wide polices for taxation and subsides with ongoing evaluation of intended and unintended effects are supported by this review.
MARBLE: Mobile Augmented Reality Using a Distributed BLE Beacon Infrastructure

This paper describes MARBLE, which is a mobile augmented reality system that uses a cluster of off-the-shelf, low power, storage and bandwidth constrained Bluetooth Low Energy (BLE) beacons as an infrastructure. MARBLE efficiently stores and broadcasts minimal visual information of 3D objects and help localize a mobile viewer, who receives, renders, and experiences those 3D virtual objects while walking in the environment, wearing an augmented reality headset or viewing it through a smartphone. Compared to other common indoor AR systems, MARBLE consumes less computation resource, stores and broadcasts 3D objects and shapes data over a very long period, does not require a pre-defined texture pattern to be placed in the scene for camera pose estimation, and is less sensitive to camera capture quality. We conduct a user study to demonstrate that MARBLE is capable of capturing freehand gestures, and when replayed back, a user sees a virtual avatar performing the gestures in the 3D environment in real-time.
Statistical and Machine Learning approach in forex prediction based on empirical data

This study proposed a new insight in comparing common methods used in predicting based on data series i.e statistical method and machine learning. The corresponding techniques are use in predicting Forex (Foreign Exchange) rates. The Statistical method used in this paper is Adaptive Spline Threshold Autoregression (ASTAR), while for machine learning, Support Vector Machine (SVM) and hybrid form of Genetic Algorithm-Neural Network (GA-NN) are chosen. The comparison among the three methods accurate rate is measured in root mean squared error (RMSE). It is found that ASTAR and GA-NN method has advantages depend on the period time intervals.
A threat in the air. How stereotypes shape intellectual identity and performance.

A general theory of domain identification is used to describe achievement barriers still faced by women in advanced quantitative areas and by African Americans in school. The theory assumes that sustained school success requires identification with school and its subdomains; that societal pressures on these groups (e.g., economic disadvantage, gender roles) can frustrate this identification; and that in school domains where these groups are negatively stereotyped, those who have become domain identified face the further barrier of stereotype threat, the threat that others' judgments or their own actions will negatively stereotype them in the domain. Research shows that this threat dramatically depresses the standardized test performance of women and African Americans who are in the academic vanguard of their groups (offering a new interpretation of group differences in standardized test performance), that it causes disidentification with school, and that practices that reduce this threat can reduce these negative effects.
3D printing of microwave passive components by different additive manufacturing technologies

This paper presents an overview of the possibility offered by 3D plastic printers for a quick, simple and affordable manufacturing of working filters and other passive devices such as antennas. This paper thus goes through numerous examples of passive devices made with the Fused Deposition Modeling (FDM) and material jetting (Polyjet©) technologies and will highlight how they can now be considered as a solid companion to RF designers during an optimization process up to Ku and higher bands.
Behavior-driven visualization recommendation

We present a novel approach to visualization recommendation that monitors user behavior for implicit signals of user intent to provide more effective recommendation. This is in contrast to previous approaches which are either insensitive to user intent or require explicit, user specified task information. Our approach, called Behavior-Driven Visualization Recommendation (BDVR), consists of two distinct phases: (1) pattern detection, and (2) visualization recommendation. In the first phase, user behavior is analyzed dynamically to find semantically meaningful interaction patterns using a library of pattern definitions developed through observations of real-world visual analytic activity. In the second phase, our BDVR algorithm uses the detected patterns to infer a user's intended visual task. It then automatically suggests alternative visualizations that support the inferred visual task more directly than the user's current visualization. We present the details of BDVR and describe its implementation within our lab's prototype visual analysis system. We also present study results that demonstrate that our approach shortens task completion time and reduces error rates when compared to behavior-agnostic recommendation.
Error Log Processing for Accurate Failure Prediction

Error logs are a fruitful source of information both for diagnosis as well as for proactive fault handling – however elaborate data preparation is necessary to filter out valuable pieces of information. In addition to the usage of well-known techniques, we propose three algorithms: (a) assignment of error IDs to error messages based on Levenshtein’s edit distance, (b) a clustering approach to group similar error sequences, and (c) a statistical noise filtering algorithm. By experiments using data of a commercial telecommunication system we show that data preparation is an important step to achieve accurate error-based online failure prediction.
On the Reception and Detection of Pseudo-profound Bullshit

Although bullshit is common in everyday life and has attracted attention from philosophers, its reception (critical or ingenuous) has not, to our knowledge, been subject to empirical investigation. Here we focus on pseudo-profound bullshit, which consists of seemingly impressive assertions that are presented as true and meaningful but are actually vacuous. We presented participants with bullshit statements consisting of buzzwords randomly organized into statements with syntactic structure but no discernible meaning (e.g., “Wholeness quiets infinite phenomena”). Across multiple studies, the propensity to judge bullshit statements as profound was associated with a variety of conceptually relevant variables (e.g., intuitive cognitive style, supernatural belief). Parallel associations were less evident among profundity judgments for more conventionally profound (e.g., “A wet person does not fear the rain”) or mundane (e.g., “Newborn babies require constant attention”) statements. These results support the idea that some people are more receptive to this type of bullshit and that detecting it is not merely a matter of indiscriminate skepticism but rather a discernment of deceptive vagueness in otherwise impressive sounding claims. Our results also suggest that a bias toward accepting statements as true may be an important component of pseudo-profound bullshit receptivity.
Collaborative process planning and manufacturing in product lifecycle management

Companies are moving towards quickly providing better customer-centric products and services improve market share and market size with continuously growing revenue. As such, the effective collaboration among customers, developers, suppliers, and manufacturers throughout the entire product lifecycle is becoming much more important for the most advanced competitiveness. To address this need, a framework for product lifecycle collaboration is proposed in this study. The details of these collaboration models throughout the entire product lifecycle are depicted. As one of the key elements in product lifecycle collaboration, technology to support collaborative product manufacturing is proposed, developed and implemented in this study. It is hoped that the developed technology for collaborative product manufacturing will lay a frontier basis for further research and development in product lifecycle management.
Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks.

The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many noncoding variants statistically associated with human disease, nearly all such variants have unknown mechanisms. Here, we address this challenge using an approach based on a recent machine learning advance-deep convolutional neural networks (CNNs). We introduce the open source package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change in accessibility between variant alleles were far greater for Genome-wide association study (GWAS) SNPs that are likely to be causal relative to nearby SNPs in linkage disequilibrium with them. With Basset, a researcher can perform a single sequencing assay in their cell type of interest and simultaneously learn that cell's chromatin accessibility code and annotate every mutation in the genome with its influence on present accessibility and latent potential for accessibility. Thus, Basset offers a powerful computational approach to annotate and interpret the noncoding genome.
High altitude UAV navigation using IMU, GPS and camera

This paper deals with the integration of measurements provided by inertial sensors (gyroscopes and accelerometers), GPS (Global Positioning System) and a video system in order to estimate position and attitude of an high altitude UAV (Unmanned Aerial Vehicle). In such a case, the vision algorithms present ambiguities due to the plane degeneracy. This ambiguity can be avoided fusing the video information with inertial sensors measurements. On the other hand, inertial sensors are widely used for aircraft navigation because they represent a low cost and compact solution, but their measurements suffer of several errors which cause a rapid divergence of position and attitude estimates. To avoid divergence, inertial sensors are usually coupled with other systems as for example GPS. A camera presents several advantages with respect to GPS as for example great accuracy and higher data rate. Moreover, it can be used in urban area or, more in general, where no useful GPS signal is present. On the contrary, it has lower data rate than inertial sensors and its measurements have latencies which can prejudice the performances and the effectiveness of the flight control system. The integration of inertial sensors with a camera allows exploiting the better features of both the systems, providing better performances in position and attitude estimation. The data fusion is performed via a multirate Unscented Kalman Filter (UKF) because of the nonlinear dynamic system equation. Experimental results show the effectiveness of the proposed method.
AtDELFI: automatically designing legible, full instructions for games

This paper introduces a fully automatic method for generating video game tutorials. The AtDELFI system (Automatically DEsigning Legible, Full Instructions for games) was created to investigate procedural generation of instructions that teach players how to play video games. We present a representation of game rules and mechanics using a graph system as well as a tutorial generation method that uses said graph representation. We demonstrate the concept by testing it on games within the General Video Game Artificial Intelligence (GVG-AI) framework; the paper discusses tutorials generated for eight different games. Our findings suggest that a graph representation scheme works well for simple arcade style games such as Space Invaders and Pacman, but it appears that tutorials for more complex games might require higher-level understanding of the game than just single mechanics.
A "Never-Loose" Strategy to Play the Game of Tic-Tac-Toe

In much of the literature available to solve the tic-tac-toe board game, the common approaches, such as, co evolution, neural networks, evolutionary programming and genetic algorithm are used. In the present work we present a deterministic approach for playing tic-tac-toe game, in which 9 objective functions are defined to decide player's best move. For choosing the best from the solutions generated, by combination of mutating zero as 1, certain axioms are defined. The beauty of this method lies in the fact that if the player decides a move with this method, he never loses the match whenever the player begins the game. We suspect that functions can be defined on the similar grounds for other existing board games and some of this work is in progress and will be reported elsewhere. Some implications on these lines have been made as recommendations in this paper.
Friend or foe: The effect of implicit trustworthiness judgments in social decision-making

The human face appears to play a key role in signaling social intentions and usually people form reliable and strong impressions on the basis of someone's facial appearance. Therefore, facial signals could have a substantial influence on how people evaluate and behave towards another person in a social interaction, such as an interactive risky decision-making game. Indeed, there is a growing body of evidence that demonstrates that social behavior plays a crucial role in human decision-making. Although previous research has demonstrated that explicit social information about one's partner can influence decision-making behavior, such as knowledge about the partner's moral status, much less is known about how implicit facial social cues affect strategic decision-making. One particular social cue that may be especially important in assessing how to interact with a partner is facial trustworthiness, a rapid, implicit assessment of the likelihood that the partner will reciprocate a generous gesture. In this experiment, we tested the hypothesis that implicit processing of trustworthiness is related to the degree to which participants cooperate with previously unknown partners. Participants played a Trust Game with 79 hypothetical partners who were previously rated on subjective trustworthiness. In each game, participants made a decision about how much to trust their partner, as measured by how much money they invested with that partner, with no guarantee of return. As predicted, people invested more money in partners who were subjectively rated as more trustworthy, despite no objective relationship between these factors. Moreover, the relationship between the amount of money offered seemed to be stronger for trustworthy faces as compared to untrustworthy faces. Overall, these data indicate that the perceived trustworthiness is a strong and important social cue that influences decision-making.
Power, leadership and transformation: the doctor's potential for influence.

Power and leadership are concepts that are linked. Both are studied too infrequently in medical and health care settings, given the responsibilities and opportunities doctors and other health care personnel have to exert leadership and power appropriately to foster patient-centred and health care organisational goals.



This paper reviews Raven's concept of power, clarifies the bases of power that are available to doctors in different roles and provides illustrations of the application of the bases of power in medical practice. The relationship between power and leadership is explored, with an emphasis on how power and leadership are linked through the personal characteristics and competencies of the leader.


Transformational leadership illustrates the incorporation and elaboration of power strategies into a principles-driven, relationship-oriented and empirically grounded form of leadership. Illustrations of the appropriate and inappropriate use of power and leadership in health care settings are provided.



The study of power, the study of leadership and their linkage should be incorporated to a greater degree into medical education at all levels. Strategies to achieve this end are suggested.