Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimodal, Multiparty Modeling of Collaborative Problem Solving Performance

Modeling team phenomena from multiparty interactions inherently requires combining signals from multiple teammates, often by weighting strategies. Here, we explored the hypothesis that strategic weighting signals from individual teammates would outperform an equal weighting baseline. Accordingly, we explored role-, trait-, and behavior-based weighting of behavioral signals across team members. We analyzed data from 101 triads engaged in computer-mediated collaborative problem solving (CPS) in an educational physics game. We investigated the accuracy of machine-learned models trained on facial expressions, acoustic-prosodics, eye gaze, and task context information, computed one-minute prior to the end of a game level, at predicting success at solving that level. AUROCs for unimodal models that equally weighted features from the three teammates ranged from . 54 to . 67, whereas a combination of gaze, face, and task context features, achieved an AUROC of . 73. The various multiparty weighting strategies did not outperform an equal-weighting baseline. However, our best nonverbal model (AUROC = .73) outperformed a language-based model (AUROC = .67), and there were some advantages to combining the two (AUROC = .75). Finally, models aimed at prospectively predicting performance on a minute-by-minute basis from the start of the level achieved a lower, but still above-chance, AUROC of . 60. We discuss implications for multiparty modeling of team performance and other team constructs.
A structure-function substrate of memory for spatial configurations in medial and lateral temporal cortices

Prior research has shown that structures of the mesiotemporal lobe, particularly the hippocampal-parahippocampal complex, are engaged in different forms of spatial cognition. Here, we developed a new paradigm, the Conformational Shift Spatial task (CSST), which examines the ability to encode and retrieve spatial relations between three unrelated items. This task is short, uses symbolic cues, and incorporates two difficulty levels and can be administered inside and outside the scanner. A cohort of 48 healthy young adults underwent the CSST, together with a set of validated behavioral measures and multimodal magnetic resonance imaging (MRI). Interindividual differences in CSST performance correlated with scores on an established spatial memory paradigm, but neither with episodic memory nor pattern separation performance, highlighting the specificity of the new measure. Analyzing high resolution structural MRI data, individuals with better spatial memory showed thicker medial as well as lateral temporal cortices. Functional relevance of these findings was supported by task-based functional MRI analysis in the same participants and ad hoc meta-analysis. Exploratory resting-state functional MRI analyses centered on clusters of morphological effects revealed additional modulation of intrinsic network integration, particularly between lateral and medial temporal structures. Our work presents a novel spatial memory paradigm and supports an integrated structure-function substrate in the human temporal lobe. Task paradigms are programmed in python and made open access.
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels

Group equivariant convolutional networks (GCNNs) endow classical convolutional networks with additional symmetry priors, which can lead to a considerably improved performance. Recent advances in the theoretical description of GCNNs revealed that such models can generally be understood as performing convolutions with G-steerable kernels, that is, kernels that satisfy an equivariance constraint themselves. While the G-steerability constraint has been derived, it has to date only been solved for specific use cases - a general characterization of G-steerable kernel spaces is still missing. This work provides such a characterization for the practically relevant case of G being any compact group. Our investigation is motivated by a striking analogy between the constraints underlying steerable kernels on the one hand and spherical tensor operators from quantum mechanics on the other hand. By generalizing the famous Wigner-Eckart theorem for spherical tensor operators, we prove that steerable kernel spaces are fully understood and parameterized in terms of 1) generalized reduced matrix elements, 2) Clebsch-Gordan coefficients, and 3) harmonic basis functions on homogeneous spaces.
Tight Second-Order Certificates for Randomized Smoothing

Randomized smoothing is a popular way of providing robustness guarantees against adversarial attacks: randomly-smoothed functions have a universal Lipschitz-like bound, allowing for robustness certificates to be easily computed. In this work, we show that there also exists a universal curvature-like bound for Gaussian random smoothing: given the exact value and gradient of a smoothed function, we compute a lower bound on the distance of a point to its closest adversarial example, called the Second-order Smoothing (SoS) robustness certificate. In addition to proving the correctness of this novel certificate, we show that SoS certificates are realizable and therefore tight. Interestingly, we show that the maximum achievable benefits, in terms of certified robustness, from using the additional information of the gradient norm are relatively small: because our bounds are tight, this is a fundamental negative result. The gain of SoS certificates further diminishes if we consider the estimation error of the gradient norms, for which we have developed an estimator. We therefore additionally develop a variant of Gaussian smoothing, called Gaussian dipole smoothing, which provides similar bounds to randomized smoothing with gradient information, but with much-improved sample efficiency. This allows us to achieve (marginally) improved robustness certificates on high-dimensional datasets such as CIFAR-10 and ImageNet. Code is available at https://github.com/alevine0/smoothing_second_order.
PARTS OF SPEECH TAGGING: A REVIEW OF TECHNIQUES

Technology advances by the day and computers can be considered as valuable to almost every learned person. One of the most uses of computers nowadays is for internet surfing and social networking. Computers in this context are not restricted to desktop or laptop computers only. Internet surfing and social networking has made interactions between people and computers very easy, where people can communicate using their languages thus making processing of these languages a useful task for the computers to interpret. The correct processing of these languages on the computer relies on the correct identification of parts of speech (POS) in sentences which has been an active area of research for a long time. This paper presents a review parts of speech tagging, comparison of different tagging techniques, their characteristics, difficulties, limitation, and Multilingual Parts of Speech (POS) tagging approaches.
EfgA is a conserved formaldehyde sensor that halts bacterial translation in response to elevated formaldehyde

Normal cellular processes give rise to toxic metabolites that cells must mitigate. Formaldehyde is a universal stressor and potent metabolic toxin that is generated in organisms from bacteria to humans. Methylotrophic bacteria such as Methylorubrum extorquens face an acute challenge due to their production of formaldehyde as an obligate central intermediate of single-carbon metabolism. Mechanisms to sense and respond to formaldehyde were speculated to exist in methylotrophs for decades but had never been discovered. Here we identify a member of the DUF336 domain family, named efgA for enhanced formaldehyde growth, that plays an important role in endogenous formaldehyde stress response in M. extorquens PA1 and is found almost exclusively in methylotrophic taxa. Our experimental analyses reveal that EfgA is a formaldehyde sensor that inhibits translation in response to elevated levels of formaldehyde. Heterologous expression of EfgA in Escherichia coli increases formaldehyde resistance, indicating that its interaction partners are widespread and conserved and may include translational machinery. EfgA represents the first example of a formaldehyde stress response system that does not involve enzymatic detoxification. Thus, EfgA comprises a unique stress response mechanism in bacteria, whereby a single protein directly senses elevated levels of a toxic intracellular metabolite and modulates translational activity.
Analysis of Published Amphibian Neoplasia Case Reports

Abstract Neoplasia due to environmental contaminants has been previously reported in wild amphibians; however, minimal research has been done to investigate individual cases of amphibian neoplasia independent of environmental contamination or viral etiologies. This study reviewed published literature for neoplasia in amphibians in order to supplement the Exotic Species Cancer Research Alliance (ESCRA) database. Through searches of three scientific literature databases (PubMed, CAB Abstracts, and Web of Science Zoological Record), 50 cases of amphibian neoplasia were found in 36 articles published between 1954 and 2018. The most common species reported were African clawed frogs (Xenopus laevis; n = 8) and axolotls (Ambystoma mexicanum; n = 6). Of the 50 cases, 27 of the neoplasms were malignant and 23 benign, with the majority of the malignant cases being localized (n = 17). Chromatophoroma (n = 9), lymphoma/leukemia (n = 6), and papilloma (n = 5) were the most frequently reported neoplasms, and skin (n = 24) and the hemolymphatic system (n = 6) were the most common locations. No treatment was provided for the majority (69%) of these cases. When treatment was provided, surgical excision was most frequently chosen and was associated with a better prognosis (n = 12, P < 0.001). Males and amphibians with benign neoplasms were more likely to have a better prognosis (P = 0.049 in a literature data set spanning 1954–2018 and P = 0.019 for 1970–2018), and animals with malignant neoplasms were more likely to have a poor prognosis (P = 0.036 for a literature data set spanning 1970–2018). This analysis of neoplasia in amphibians enables us to evaluate published cases of amphibian neoplasia to extend the analytical power of resources such as the ESCRA database and provide insight into prognostic factors of neoplasia in amphibian species.
Mitochondrial profiling reveals dynamic, sex- and age-specific mitochondrial phenotypes in human immune cell subtypes

How mitochondria functionally differ between immune cell subtypes, between the sexes, and with aging has not been defined in humans. We deploy a high-throughput mitochondrial phenotyping platform to define cell-type specific mitochondrial features in human circulating immune cell subtypes. In women and men spanning four decades of life, we find that mitochondrial content, mitochondrial DNA copy number (mtDNAcn), and respiratory chain enzymatic activities vary by up to 3.5-fold between neutrophils, monocytes, B and T lymphocyte subtypes. Mitochondria exhibit specific age- and sex-related differences among individual cell subtypes, including an age-related increase in mtDNAcn. In an intensive repeated-measures study, we also identify remarkable weekly variation in mitochondrial content and respiratory chain function, which is partially correlated with changes in circulating biomarkers. Our results also define multivariate mitochondrial phenotypes − mitotypes − that distinguish lymphoid from myeloid cell types, naive-to-memory lymphocyte states, and moderately differ between women and men. Finally, a comparison of mitochondrial features in purified cell subtypes and in peripheral blood mononuclear cells (PBMCs) invites caution in using cell type mixtures to infer person-level mitochondrial function. Together, these findings identify dynamic cell-type specific variation in mitochondrial biology among circulating leukocytes and provide foundational knowledge to develop interpretable blood-based assays of mitochondrial health.
Full-length transcript sequencing of human and mouse identifies widespread isoform diversity and alternative splicing in the cerebral cortex

Alternative splicing is a post-transcriptional regulatory mechanism producing multiple distinct mRNA molecules from a single pre-mRNA. Alternative splicing has a prominent role in the central nervous system, impacting neurodevelopment and various neuronal functions as well as being increasingly implicated in brain disorders including autism, schizophrenia and Alzheimer’s disease. Standard short-read RNA-Seq approaches only sequence fragments of the mRNA molecule, making it difficult to accurately characterize the true nature of RNA isoform diversity. In this study, we used long-read isoform sequencing (Iso-Seq) to generate full-length cDNA sequences and map transcript diversity in the human and mouse cerebral cortex. We identify widespread RNA isoform diversity amongst expressed genes in the cortex, including many novel transcripts not present in existing genome annotations. Alternative splicing events were found to make a major contribution to RNA isoform diversity in the cortex, with intron retention being a relatively common event associated with nonsense-mediated decay and reduced transcript expression. Of note, we found evidence for transcription from novel (unannotated genes) and fusion events between neighbouring genes. Although global patterns of RNA isoform diversity were found to be generally similar between human and mouse cortex, we identified some notable exceptions. We also identified striking developmental changes in transcript diversity, with differential transcript usage between human adult and fetal cerebral cortex. Finally, we found evidence for extensive isoform diversity in genes associated with autism, schizophrenia and Alzheimer’s disease. Our data confirm the importance of alternative splicing in the cerebral cortex, dramatically increasing transcriptional diversity and representing an important mechanism underpinning gene regulation in the brain. We provide this transcript level data as a resource to the scientific community.
STUDYING NON-EQUILIBRIUM THERMODYNAMICS USING NON-EQUILIBRIUM MOLECULAR DYNAMICS SIMULATIONS

One of the greatest hindrances to the development of theories of non-equilibrium thermodynamics beyond the local equilibrium approximation is the difficulty of formulating definitive experimental tests of the basic concepts. For example, the existence and definition of quantities such as temperature and entropy in far-from-equilibrium systems are extremely difficult questions to directly address by experiment. Of course, this is partially due to the extraordinary success and great range of validity of non-equilibrium thermodynamics in the local-equilibrium approximation. It is usually necessary to create systems under extreme conditions such as shock waves, if we want to see deviations from the local equilibrium approximation, although nonNewtonian fluids also provide some opportunities. Even in these situations, gaining direct experimental access to measurable quantities that can be related to the theory is not simple. Alternatively, non-equilibrium molecular dynamics simulations are an ideal test environment for many concepts in non-equilibrium thermodynamics. Many quantities of interest can be directly computed in molecular dynamics simulations. In this paper, I would like to discuss several ways in which non-equilibrium molecular dynamics simulations can be used to extract detailed information that can contribute to a deeper understanding of non-equilibrium thermodynamics. I will also describe some of the pitfalls of this approach.
Toward Interactions through Information in a Multifractal Paradigm

In a multifractal paradigm of motion, Shannon’s information functionality of a minimization principle induces multifractal–type Newtonian behaviors. The analysis of these behaviors through motion geodesics shows the fact that the center of the Newtonian-type multifractal force is different from the center of the multifractal trajectory. The measure of this difference is given by the eccentricity, which depends on the initial conditions. In such a context, the eccentricities’ geometry becomes, through the Cayley–Klein metric principle, the Lobachevsky plane geometry. Then, harmonic mappings between the usual space and the Lobachevsky plane in a Poincaré metric can become operational, a situation in which the Ernst potential of general relativity acquires a classical nature. Moreover, the Newtonian-type multifractal dynamics, perceived and described in a multifractal paradigm of motion, becomes a local manifestation of the gravitational field of general relativity.
How Life Works—A Continuous Seebeck-Peltier Transition in Cell Membrane?

This paper develops a non-equilibrium thermodynamic approach to life, with particular regards to the membrane role. The Onsager phenomenological coefficients are introduced in order to point out the thermophysical properties of the cell systems. The fundamental role of the cell membrane electric potential is highlighted, in relation to ions and heat fluxes, pointing out the strictly relation between heat exchange and the membrane electric potential. A Seebeck-like and Peltier-like effects emerge in order to simplify the description of the heat and the ions fluxes. Life is described as a continuos transition between the Peltier-like effect to the Seebeck-like one, and viceversa.
Evaluation of the Global S-Entropy Production in Membrane Transport of Aqueous Solutions of Hydrochloric Acid and Ammonia

The results of experimental studies of volume osmotic fluxes (Jvkr) and fluxes of dissolved substances (Jkr) in a system containing a synthetic Nephrophan® membrane (Orwo VEB Filmfabrik, Wolfen, Germany) set in a horizontal plane are presented. The membrane separated water and aqueous HCl or ammonia solutions or aqueous ammonia and HCl solutions. It was found that for the homogeneity conditions of the solutions Jvk and Jk depend only on the concentration and composition of the solutions. For concentration polarization conditions (where concentration boundary layers are created on both sides), Jvkr and Jkr depend on both the concentration and composition of the solutions and the configuration of the membrane system. The obtained results of the Jvk and Jk flux studies were used to assess the global production of entropy for the conditions of homogeneity of solutions (ΦSk), while Jvkr and Jkr—to assess the global production of entropy for concentration polarization conditions (ΦSkr). In addition, the diffusion-convective effects and the convection effect in the global source of entropy were calculated. The concentration polarization coefficient ζir was related to modified concentration Rayleigh number, e.g., the parameter controlling the transition from non-convective (diffusive) to convective state. This number acts as a switch between two states of the concentration field: convective (with a higher entropy source value) and non-convective (with a lower entropy source value). The operation of this switch indicates the regulatory role of earthly gravity in relation to membrane transport.
Some explicit and unconditional results on gaps between zeroes of the Riemann zeta-function

We make explicit an argument of Heath-Brown concerning large and small gaps between nontrivial zeroes of the Riemann zeta-function, $\zeta(s)$. In particular, we provide the first unconditional results on gaps (large and small) which hold for a positive proportion of zeroes. To do this we prove explicit bounds on the second and fourth power moments of $S(t+h)-S(t)$, where $S(t)$ denotes the argument of $\zeta(s)$ on the critical line and $h \ll 1 / \log T$. We also use these moments to prove explicit results on the density of the nontrivial zeroes of $\zeta(s)$ of a given multiplicity.
The Influence of Organisational Culture and Work Ethic on Lecturer Performance: The Mediating Role of Competency

This research aimed to analyse and explain the direct and indirect influences of organisational culture and work ethic on lecturer competency and performance. The research sampled 72 respondents at the Universitas Islam Raden Rahmat. The sampling technique was saturated samples and the analytical method used path analysis with SPSS 21 software. The results show that the respondents’ responses to the organisational culture, work ethic and competency agreed with each other. The results of hypothesis testing prove that the organisational culture was applied properly. Work ethic could improve competency and indirectly improve lecturer performance. Competency becomes a top priority in completing job responsibilities. Competency has an intervening role for organisation culture and for work ethics for lecturer performance, both having very high significance values.
Possible Life Saver: A Review on Human Fall Detection Technology

Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed fall detection systems and devices has increased dramatically and some of them are already in the market. Fall detection devices/systems can be categorized based on their architectures as wearable devices, ambient systems, image processing-based systems, and hybrid systems, which employ a combination of two or more of these methodologies. In this review paper, a comparison is made among these major fall detection systems, devices, and algorithms in terms of their proposed approaches and measure of performance. Issues with the current systems such as lack of portability and reliability are presented as well. Development trends such as the use of smartphones, machine learning, and EEG are recognized. Challenges with privacy issues, limited real fall data, and ergonomic design deficiency are also discussed.
Deep Learning-Based Object Classification and Position Estimation Pipeline for Potential Use in Robotized Pick-and-Place Operations

Accurate object classification and position estimation is a crucial part of executing autonomous pick-and-place operations by a robot and can be realized using RGB-D sensors becoming increasingly available for use in industrial applications. In this paper, we present a novel unified framework for object detection and classification using a combination of point cloud processing and deep learning techniques. The proposed model uses two streams that recognize objects on RGB and depth data separately and combines the two in later stages to classify objects. Experimental evaluation of the proposed model including classification accuracy compared with previous works demonstrates its effectiveness and efficiency, making the model suitable for real-time applications. In particular, the experiments performed on the Washington RGB-D object dataset show that the proposed framework has 97.5% and 95% fewer parameters compared to the previous state-of-the-art multimodel neural networks Fus-CNN, CNN Features and VGG3D, respectively, with the cost of approximately 5% drop in classification accuracy. Moreover, the inference of the proposed framework takes 66.11%, 32.65%, and 28.77% less time on GPU and 86.91%, 51.12%, and 50.15% less time on CPU in comparison to VGG3D, Fus-CNN, and CNN Features. The potential applicability of the developed object classification and position estimation framework was then demonstrated on an experimental robot-manipulation setup realizing a simplified object pick-and-place scenario. In approximately 95% of test trials, the system was able to accurately position the robot over the detected objects of interest in an automatic mode, ensuring stable cyclic execution with no time delays.