Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional selectivity for naturalistic social interaction perception in the 1 human superior temporal sulcus 2 3

10 Recognizing others’ social interactions is a crucial human ability. Using simple stimuli, previous studies have shown 11 that social interactions are processed in the superior temporal sulcus (STS) and the medial prefrontal cortex (mPFC). 12 However, it remains unknown to what extent social interaction selectivity is observed for real world stimuli where 13 social interactions covary with other perceptual and social information, such as faces, voices, and theory of mind. By 14 using a naturalistic fMRI movie paradigm and advanced machine learning methods, we found that broad social15 affective features predict neural responses in social brain regions, including the STS and mPFC. However, only the 16 STS showed robust and unique selectivity specifically to social interactions, independent from other covarying 17 features. This selectivity generalized across two separate fMRI datasets. These findings suggest that naturalistic social 18 interaction perception recruits dedicated neural circuity in the STS and is a critical dimension of human social 19 understanding. 20 Introduction 21 Humans learn a great deal about the social world by observing others’ social interactions, defined here as action or 22 communication between two or more people that are directed at and contingent upon each other. This social 23 observation helps us form impressions of interacting people (e.g., whether they are prosocial or antisocial), their social 24 relationships, and relative social status (Quadflieg and Koldewyn, 2017). Our ability to extract social information 25 about interacting people appears to emerge in infancy. For example, infants show preference for a person or character 26 who helps others achieve their goals over someone who hinders (Hamlin, 2015; Hamlin et al., 2007; Hamlin and 27 Wynn, 2011). These findings underscore the importance of observing others’ social interactions for making social 28 judgements. 29 Previous studies have reported that the posterior superior temporal sulcus (pSTS) (Isik et al., 2017; Walbrin 30 et al., 2018; Walbrin and Koldewyn, 2019) and the cortical midline structure (the medial prefrontal cortex (mPFC) 31 and the precuneus) are involved in recognizing others’ social interactions (Iacoboni et al., 2004; Petrini et al., 2014). 32 Importantly, social interactions appear to be processed selectively, in a manner that is functionally distinct from other 33 related social functions, including detecting faces, animacy, other agents’ goals and theory of mind. Most prior studies, 34
Phosphorylation-dependent mitotic SUMOylation drives nuclear envelope–chromatin interactions

In eukaryotes, chromatin binding to the inner nuclear membrane (INM) and nuclear pore complexes (NPCs) contributes to spatial organization of the genome and epigenetic programs important for gene expression. In mitosis, chromatin-nuclear envelope (NE) interactions are lost and then formed again as sister chromosomes segregate to post-mitotic nuclei. Investigating these processes in S. cerevisiae, we identified temporally and spatially controlled phosphorylation-dependent SUMOylation events that positively regulate post-metaphase chromatin association with the NE. Our work establishes a phosphorylation-mediated targeting mechanism of the SUMO ligase Siz2 to the INM during anaphase, where Siz2 binds to and SUMOylates the VAP protein Scs2. The recruitment of Siz2 through Scs2 is further responsible for a wave of SUMOylation along the INM that supports the assembly and anchorage of subtelomeric chromatin at the INM and localization of an active gene (INO1) to NPCs during the later stages of mitosis and into G1-phase.
Genetic analysis of coronary artery disease using tree-based automated machine learning informed by biology-based feature selection

Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-based Pipeline Optimization Tool (TPOT), have been developed to take some of the guesswork out of ML thus making this technology available to users from more diverse backgrounds. The goals of this study were to assess applicability of TPOT to genomics and to identify combinations of single nucleotide polymorphisms (SNPs) associated with coronary artery disease (CAD), with a focus on genes with high likelihood of being good CAD drug targets. We leveraged public functional genomic resources to group SNPs into biologically meaningful sets to be selected by TPOT. We applied this strategy to data from the UK Biobank, detecting a strikingly recurrent signal stemming from a group of 28 SNPs. Importance analysis of these uncovered functional relevance of the top SNPs to genes whose association with CAD is supported in the literature and other resources. Furthermore, we employed game-theory based metrics to study SNP contributions to individual level TPOT predictions and discover distinct clusters of well-predicted CAD cases. The latter indicates a promising approach towards precision medicine.
Increased ACTL6A Occupancy Within mSWI/SNF Chromatin Remodelers Drives Human Squamous Cell Carcinoma

Mammalian SWI/SNF (BAF) chromatin remodelers play dosage-sensitive roles in many human malignancies and neurologic disorders. The gene encoding the BAF subunit, ACTL6A, is amplified at an early stage in the development of squamous cell carcinomas (SCCs), but its oncogenic role remains unclear. Here we demonstrate that ACTL6A overexpression leads to its stoichiometric assembly into BAF complexes and drives its interaction and engagement with specific regulatory regions in the genome. In normal epithelial cells, ACTL6A was sub-stoichiometric to other BAF subunits. However, increased ACTL6A levels by ectopic expression or in SCC cells led to near-saturation of ACTL6A within BAF complexes. Increased ACTL6A occupancy enhanced polycomb opposition over the genome activating SCC genes and also enhanced the recruitment of transcription factor TEAD with its co-activator YAP, promoting their chromatin binding and enhancer accessibility. Both of these mechanisms appeared to be critical and function as a molecular AND gate for SCC initiation and maintenance, thereby explaining the specificity of the role of ACTL6A amplification in SCCs. Highlights ACTL6A occupancy within BAF complexes is sub-stoichiometric in normal epithelial cells. SCC cells upregulate ACTL6A thus increasing ACTL6A assembly with BAF complexes. Genome-wide chromatin profiling identifies ACTL6A-dependent regulatory regions. Increasing ACTL6A incorporation enhances TEAD-YAP binding to BAF complexes. ACTL6A overexpression counteracts polycomb-mediated repression at SCC signature genes.
The plant circadian clock gene LHY influences Medicago truncatula nodulation

Legumes house nitrogen-fixing endosymbiotic rhizobia in specialized polyploid cells within root nodules, which are factories of metabolic activity. We discovered that the circadian clock-associated transcriptional factor LATE ELONGATED HYPOCOTYL (LHY) affects nodulation in Medicago truncatula. By carrying out expression analysis of transcripts over time in nodules we found that the clock enables coordinated control of metabolic and regulatory processes linked to nitrogen fixation. Rhythmic transcripts in root nodules include a subset of Nodule-specific Cysteine Rich peptides (NCRs) that have the LHY-bound conserved Evening Element in their promoters. Until now, studies have suggested that NCRs act to regulate bacteroid differentiation and keep the rhizobial population in check. However, these conclusions came from the study of a few members of this very large gene family that has complex diversified spatio-temporal expression. We suggest that rhythmic expression of NCRs may be important for temporal coordination of bacterial activity with the rhythms of the plant host, in order to ensure optimal symbiosis. Highlights The circadian clock-associated transcriptional factor LATE ELONGATED HYPOCOTYL (LHY) impacts on successful Medicago truncatula-rhizobial symbiosis The plant clock coordinates rhythmic patterns of metabolic and regulatory activity in nodules and drives rhythmic expression of a subset of Nodule-specific Cysteine Rich (NCR) genes. Rhythmic expression of NCRs may be important for temporal coordination of bacterial activity with plant host rhythms to ensure optimal symbiosis.
Diverse arsenic-containing lipids in the surface ocean

Arsenic is present at nanomolar levels throughout the surface ocean, and microbes assimilate this toxic element due to its similarity to inorganic phosphorus. Although the concentration and characterization of dissolved arsenic has been a focus of ocean studies, the size of the particulate arsenic pool and its partitioning into organic molecules within the microbial community is not known. We measured the particulate pool of arsenic in five surface samples from the open ocean and determined the contribution of arsenic-containing lipids to this pool. Here we show that the accumulation of arsenic into lipids is a widespread phenomenon in the surface ocean. Particulate arsenic concentrations were 15 to 42 pmol L−1 with 7–20% of the particulate arsenic pool in the form of arsenolipids. We characterized these arsenolipids and found that arsenosugar phospholipids dominated the arsenolipid pools in our samples with a minor component of arsenohydrocarbons and other unidentified lipids. A significant portion of the arsenosugar phospholipids (up to 35%) were present as previously undescribed mixed acyl ether lipids, suggesting a bacterial source. Scientific significance statement Marine microbes experience constant exposure to the toxic element arsenic. However, there are no baseline measurements of how much arsenic accumulates in microbial communities nor do we know the full spectrum of arsenic containing biomolecules produced in marine systems. In culture-based studies there is strong evidence that phytoplankton synthesize arsenic-containing lipids, but these lipids have not been observed in natural communities of marine microbes. Here we make measurements of bulk particulate arsenic at five sites in the surface open ocean and show that a significant portion of this particulate arsenic is present as complex arsenic-containing lipids. We characterize this arsenolipid pool chemically and quantitatively to show a variety of chemically distinct and quantitatively significant lipids that expand our understanding of marine arsenic biogeochemistry. Data availability statement Mass spectrometry data and its associated metadata will be available on Dryad with publication. Scripts for data processing and figure generation found on github at https://github.com/kheal/particulate_As_data_analysis.
The automation of continuous reactions in supercritical CO2: the acid-catalysed etherification of short chain alcohols

We describe a new, automated apparatus for continuous catalytic reactions in supercritical carbon dioxide, scCO2. The reactor incorporates on-line sampling, enabling us to quantify gaseous products such as light alkenes, which would normally be lost in the decompression stage of more conventional supercritical reactors. The on-line sampling is coupled to a gas chromatograph running an isothermal program, which provides automated analysis of the reaction products. We illustrate the operation of the reactor by studying the acid-catalysed etherification of linear alcohols, C1 to C5, both individually and in pairs, over a range of temperatures and pressures equating to a total of 180 different experiments.
The Impact of Mobile Ordering Service on Offline Store Diversity and Product Diversity

Offline retail stores have adopted mobile ordering technology to enhance their customer experience. A mobile ordering channel allows customers to find a nearby store and choose a product by lowering the search costs. However, the impact of mobile ordering services on the diversity of customer experiences has not been examined. In this study, the effects of mobile ordering technology on store and product diversity are measured. We analyzed the transaction data of 170,635 users over 16 weeks of store visits. The effect of mobile ordering technology on store and product diversity was estimated using the difference-in-differences method. We find that mobile ordering services can positively affect store and product diversity. The results are consistent after analyzing the data resampled with propensity score matching. This study provides the managerial implication that mobile ordering technology is valuable for offline retail stores that aim to extend their customers’ shopping and product experiences. ,
Factors Impacting the Influence of Analytic Capabilities on Organizational Performance in Higher Education

In response to changing fiscal needs and opportunities, higher education institutions have adopted new ways to use financial information for improved decision making. Drawing upon resource based theory we examine the connection between university level data analytic capabilities and organizational performance. We posit this relationship to exist through a serially mediated path of data-driven culture and data quality. The study provides empirical evidence that establishing a data-driven culture contributes to data quality which together result in increased organizational performance. The serial mediation pathway creates a positive effect between data analytic capabilities on organizational performance. This is critical information relative to both resource based theories and practical implications for higher education relative to beginning the investment cycle at the organizational culture level related to use of data.
The Virtual Tutor: Tasks for conversational agents in Online Collaborative Learning Environments

Online collaborative learning environments are becoming increasingly popular in higher education. Etutors need to supervise, guide students and look out for conflicts within the online environment to ensure a successful learning experience. Web-based platforms allow for interactive elements such as conversational agents to disencumber the e-tutor. Repeatable tasks, which do not require a human response, can be automatized by these systems. The aim of this study is to identify and synthesize the tasks an e-tutor has and to investigate the automatisation potential with conversational agents. Using a design science research approach a literature review is conducted, identifying 13 tasks. Subsequently, a matrix is established, contrasting the tasks with requirements for the use of conversational agents. Furthermore, a virtual tutor framework is developed, clarifying the agent type selection, the technical structure and components for a prototype development in an online collaborative learning environment.
Older Adults' Use of Online Neighborhood Social Networks: Perceptions, Challenges and Effects

Online social networks (OSNs) have demonstrated potential for enabling older adults to remain socially connected and for counteracting social isolation and loneliness. With older adults preferring to age in place, their local community and neighborhood gain in importance. Online neighborhood social networks (ONSNs) are a novel type of OSN aimed at connecting local communities by facilitating social interaction, information sharing and peer support among neighbors. With a focus on trust and privacy, local relevance and integration with local organizations and institutions, they might be particularly well suited for the needs of older adults. We investigate the relationship between older adults and ONSNs by analyzing usage data, an online survey and interviews with users of an ONSN active in two urban neighborhoods in Germany. Our findings show that the case ONSN was successful in facilitating communication between neighbors and in promoting participation in community life for older adults.
Regulatory and Security Standard Compliance Throughout the Software Development Lifecycle

Our systematic literature review aims to survey research on regulatory and security standard requirements as addressed throughout the Software Development Lifecycle. Also, to characterize current research concerns and identify speciﬁc remaining challenges to address regulatory and security standard requirements throughout the SDLC. To this end, we conducted a systematic literature review (SLR) of conference proceedings and academic journals motivated by ﬁve areas of concern: The initial search produced 100 papers, and our review process narrowed this total to 20 articles to address our three research questions. Our ﬁndings suggest that academic software engineering research directly connecting regulatory and security standard requirements to later stages of the SDLC is rare despite the importance of compliance for ensuring societally acceptable engineering.
When to Signal? The Contextual Conditions for Career-Motivated User Contributions in Online Collaboration Communities

This paper examines the contextual conditions for users’ career concern as a motivational driver of contributions in online collaboration communities. On the data of user-level activities from a computer programming-related online Q&A community (Stack Overflow), merged with job-market data for software-developer, we find robust evidence of a positive association between individual users’ career concern and their contributions. More important, we find that this positive relationship is further strengthened through the contextual conditions: the number of vacancies in the job market, the expected salaries from these jobs, and the transparency in the flow of career-related information within the community. We contribute to the literature on motivation in online collaboration communities. Our study thus offers insight into how career concern can be effectively utilized to motivate contributors in these communities. Our findings also foreshadow a possible paradigm change by characterizing online collaboration communities as institutions of career concern and skill signaling.
Moderating Effects of Time-Related Factors in Predicting the Helpfulness of Online Reviews: a Deep Learning Approach

Given the importance of online reviews, as shown by extensive research, we address the problem of predicting the helpfulness of online product reviews by developing a comprehensive research model guided by the theoretical foundations of signaling and social influence theories. We use review order and time interval to incorporate the moderating effects of the time-related variable on the reviewer’s valuation of products and the related details they provide. Applying deep learning techniques in text processing and model building on a dataset of 239297 reviews, the empirical findings represent a strong support of the proposed approach and show its superior performance in predicting review helpfulness compared to current approaches. This research contributes to theory by analyzing online reviews from the points of two well-known information processing theories and contributes to practice by developing a model to sort the newly posted reviews.
Machine Learning-Based Android Malware Detection Using Manifest Permissions

The Android operating system is currently the most prevalent mobile device operating system holding roughly 54 percent of the total global market share. Due to Android’s substantial presence, it has gained the attention of those with malicious intent, namely, malware authors. As such, there exists a need for validating and improving current malware detection techniques. Automated detection methods such as anti-virus programs are critical in protecting the wide variety of Android-powered mobile devices on the market. This research investigates effectiveness of four different machine learning algorithms in conjunction with features selected from Android manifest file permissions to classify applications as malicious or benign. Case study results, on a test set consisting of 5,243 samples, produce accuracy, recall, and precision rates above 80%. Of the considered algorithms (Random Forest, Support Vector Machine, Gaussian Naïve Bayes, and K-Means), Random Forest performed the best with 82.5% precision and 81.5% accuracy.
Emancipation Research in Information Systems: Integrating Agency, Dialogue, Inclusion, and Rationality Research

Emancipation is a key concept in critical theories. Prior work suggests that emancipation is a complex and multi-faceted concept. Many conceptualizations of emancipation exist, and emancipation is defined in different ways. Existing empirical studies mainly focus on one or few components of emancipation. To have an integrated understanding of emancipation, we review the literature on emancipation in information systems (IS), with a view toward developing a typology of components of emancipation in the IS field. The typology of emancipation components consists of four components: freedom to act, freedom to express, freedom to belong and freedom to think. These components relate to the concepts of agency, dialogue, inclusion, and rationality, respectively.
Quest for Control: Managing Software Development in Networked Operating Environments

Instead of developing software purely within the confines of one company, software companies increasingly procure many of the functionalities of their software from external entities and actors via system integrations and utilizing resources provided by external application programming interfaces (APIs). In addition to the benefits that can be reaped via integrations and working in cooperation with other companies, this type of networked software development leads to a reduction of control for the individual companies. As a result, companies need to resort to specific strategies and practices that reduce the risks emerging from lack of control. By utilizing data collected from Finnish software companies, we map the factors that cause reduction of control, study why companies give away control, and identify the challenges surfacing from it. To tackle these issues, we identify two strategies that software companies can take to counter the reduction of control.
Urea‐induced conformational changes of chitosan molecules and the shift of break point of Mark–Houwink equation by increasing urea concentration

Chitosan solutions of the same 83% degree of deacetylation (DD) but different weight average molecular weights (Mws) (78–914 kDa) in 0.01M HCl containing different concentrations of urea (0–6M) were prepared. Intrinsic viscosity ([η]) and weight average molecular weight (Mw) of chitosan were measured with a capillary viscometer and light scattering, respectively. Mark–Houwink exponent a was used as the parameter of conformational index. The Mark–Houwink exponent a increased with increasing concentrations of urea. When solutions contained 0, 2, 3, 4, and 6M urea, the value of a increased from 0.715 to 0.839, 0.894, 1.000, and 1.060, respectively. This indicates the occurrence of urea-induced conformational transitions of chitosans. The break point shifted from 223 kDa in solutions containing no urea to 280 kDa in 2M urea solutions, to 362 kDa in 4M urea solutions and further to 481 kDa in 6M urea solutions. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 75: 452–457, 2000