Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA)

Motivation Doublets are usually considered an unwanted artifact of single-cell RNA-sequencing (scRNA-seq) and are only identified in datasets for the sake of removal. However, if cells have a juxtacrine attachment to one another in situ and maintain this association through an scRNA-seq processing pipeline that only partially dissociates the tissue, these doublets can provide meaningful biological information regarding the interactions and cell processes occurring in the analyzed tissue. This is especially true for cases such as the immune compartment of the tumor microenvironment, where the frequency and type of immune cell juxtacrine interactions can be a prognostic indicator. Results We developed Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA) as a pipeline for identifying and analyzing biological doublets in scRNA-seq data. CIcADA identifies putative doublets using multi-label cell type scores and characterizes interaction dynamics through a comparison against synthetic doublets of the same cell type composition. In performing CIcADA on several scRNA-seq tumor datasets, we found that the identified doublets were consistently upregulating expression of immune response genes. Contact Courtney.T. Schiebout.GR@Dartmouth.edu, Hildreth.R. Frost@Dartmouth.edu
Automated Detection of Skin Tone Diversity in Visual Marketing Communication

Companies invest heavily in diversity, equity, and inclusion efforts. Specifically, the representation of people in visual marketing communication is often considered a manifestation of diversity policies. We propose a standard framework built on machine learning to create novel measures quantifying skin tone dynamics. We first use the Swin Transformer to extract skin pixels from images. Next, the K-means algorithm is deployed to classify skin tone components from the extracted skin pixels, accounting for multiple people with distinct skin colors in an image. Using images posted by 34 fashion brands on Instagram and Twitter, we demonstrate a useful application of the tool. The results highlight that, in the past two years, the fashion industry has slightly increased its diversity, represented by the increased variety of skin tones of people included in social media posts. Our method allows for automated detection of objective measures of skin-tone diversity in visual marketing communications.
Why it Remains Challenging to Assess Artificial Intelligence

Artificial Intelligence (AI) assessment to mitigate risks arising from biased, unreliable, or regulatory non-compliant systems remains an open challenge for researchers, policymakers, and organizations across industries. Due to the scattered nature of research on AI across disciplines, there is a lack of overview on the challenges that need to be overcome to move AI assessment forward. In this study, we synthesize existing research on AI assessment applying a descriptive literature review. Our study reveals seven challenges along three main categories: ethical implications, regulatory gaps, and socio-technical limitations. This study contributes to a better understanding of the challenges in AI assessment so that AI researchers and practitioners can resolve these challenges to move AI assessment forward.
Perinuclear damage from nuclear envelope deterioration elicits stress responses that contribute to LMNA cardiomyopathy

Mutations in the LMNA gene encoding nuclear lamins A/C cause a diverse array of tissue-selective diseases, with the heart being the most commonly affected organ. Despite progress in understanding the molecular perturbations emanating from LMNA mutations, an integrative understanding of the pathogenesis leading to cardiac dysfunction remains elusive. Using a novel cell-type specific Lmna deletion mouse model capable of translatome profiling, we found that cardiomyocyte-specific Lmna deletion in adult mice led to rapid cardiomyopathy with pathological remodeling. Prior to the onset of cardiac dysfunction, lamin A/C-depleted cardiomyocytes displayed nuclear envelope deterioration, golgi dilation/fragmentation, and CREB3-mediated golgi stress activation. Translatome profiling identified upregulation of Med25, a transcriptional co-factor that can selectively dampen UPR axes. Autophagy is disrupted in the hearts of these mice, which can be recapitulated by disrupting the golgi or inducing nuclear damage by increased matrix stiffness. Systemic administration of pharmacological modulators of autophagy or ER stress significantly improved the cardiac function. These studies support a hypothesis wherein stress responses emanating from the perinuclear space contribute to the development of LMNA cardiomyopathy. Teaser Interplay of stress responses underlying the development of LMNA cardiomyopathy
Linear-algebraic approach to electronic excitation of atoms and molecules by electron impact

A linear-algebraic method, based on an integral equations formulation, is applied to the excitation of atoms and molecules by electron impact. Various schemes are devised for treating the one-electron terms that sometimes cause instabilities when directly incorporated into the solution matrix. These include introducing Lagrange undetermined multipliers and correlation terms. Good agreement between the method and other computational techniques is obtained for electron scattering for hydrogenic and Li-like atomic ions and for H/sub 2/ /sup +/ in two- to five-state close-coupling calculations.
ON A CLASS OF GENERALIZED MARSHALL–OLKIN BIVARIATE DISTRIBUTIONS AND SOME RELIABILITY CHARACTERISTICS

We consider here a general class of bivariate distributions from reliability point of view, and refer to it as generalized Marshall–Olkin bivariate distributions. This class includes as special cases the Marshall–Olkin bivariate exponential distribution and the class of bivariate distributions studied recently by Sarhan and Balakrishnan [25]. For this class, the reliability, survival, hazard, and mean residual life functions are all derived, and their monotonicity is discussed for the marginal as well as the conditional distributions. These functions are also studied for the series and parallel systems based on this bivariate distribution. Finally, the Clayton association measure for this bivariate model is derived in terms of the hazard gradient.
Histone variant H2B.Z acetylation is necessary for maintenance of Toxoplasma gondii biological fitness

Through regulation of DNA packaging, histone proteins are fundamental to a wide array of biological processes. A variety of post-translational modifications (PTMs), including acetylation, constitute a proposed histone code that is interpreted by “reader” proteins to modulate chromatin structure. Canonical histones can be replaced with variant versions that add an additional layer of regulatory complexity. The protozoan parasite Toxoplasma gondii is unique among eukaryotes in possessing a novel variant of H2B designated H2B.Z. The combination of PTMs and the use of histone variants is important for gene regulation in T. gondii, offering new targets for drug development. In this work, T. gondii parasites were generated in which the 5 N-terminal acetylatable lysines in H2B.Z were mutated to either alanine (c-Myc-A) or arginine (c-Myc-R). c-Myc-A mutant only displayed a mild effect in its ability to kill mice. c-Myc-R mutant presented an impaired ability to grow and an increase in differentiation to latent bradyzoites. This mutant line was also more sensitive to DNA damage, displayed no virulence in mice, and provided protective immunity against future infection. While nucleosome composition was unaltered, key genes were abnormally expressed during in vitro bradyzoite differentiation. Our results show that the N-terminal positive charge patch of H2B.Z is important for these procceses. Pull down assays with acetylated N-terminal H2B.Z peptide and unacetylated one retrieved common and differential interactors. Acetylated peptide pulled down proteins associated with chromosome maintenance/segregation and cell cycle, opening the question of a possible link between H2B.Z acetylation status and mitosis.
Requirements and Design Principles for Blockchain-enabled Matchmaking-Marketplaces in Additive Manufacturing

Blockchain-enabled marketplaces offer considerable potential for cross-company networks. The area of additive manufacturing appears particularly promising. However, the practical impact of business-to-business marketplaces in today’s organizations are still scarce, and academic literature contains limited design guidelines. Synthesizing knowledge from literature, practice, and qualitative expert interviews, our study explores 27 mandatory requirements, six optional requirements, and 12 design principles.
Neurexin 3 is required for the specific S-cone to S-cone bipolar cell synapse in the mammalian retina

Specific wiring is essential for sensory systems to precisely relay information to higher brain regions. The retina, an approachable part of the brain, is an ideal model for studying neural circuits due to its well-organized structure. In the retina, S-cone photoreceptors sense and relay short-wavelength (e.g., blue) light signals for encoding color information and other environmental cues. S-cones usually account for less than 10% of cones and are precisely connected to S-cone bipolar cells (SCBCs). This connection is ancient and highly conserved across species, indicating essential functions. How this wiring specificity is formed and maintained, however, is not understood. To unveil the molecular mechanisms underlying this highly specific connection, we sequenced the transcriptomes of thirteen-lined ground squirrel (TLGS) photoreceptors. We chose TLGS for their cone-rich retina and the absence of cones that co-express multiple opsin proteins, as compared to mice. We used a targeted SMART-seq approach to obtain high-resolution transcriptomes from S- and M-cone photoreceptors and identified a cell-adhesion molecule, Nrxn3, as a potential candidate mediating the S-cone to SCBC connection. Given the limitations of genetic manipulation in TLGS, we utilized mouse models to study the function of Nrxn3 in S-cones. In ‘true’ S-cones (S-opsin+/M-opsin-) that lack Nrxn3 expression, the number of connections with SCBCs was drastically reduced, indicating a critical role of Nrxn3 for this synapse. While neurexins are well known for their diverse roles in regulating various synapses, this study is the first to document its crucial role in mediating or maintaining a specific synapse in the central nervous system. In addition, the differentially expressed genes identified here provide a valuable resource for further investigating cone subtype-specific functions.
The research on model of mining association rules based on quantitative extended concept lattice

Concept lattice represents knowledge with the relationships between the intension and extension of concepts, and the relationships between the generalization and specialization of concepts, thus it is properly applied to the description of mining association rules in databases. The quantitative extended concept lattice (QECL) evolves from concept lattice by introducing an equivalent relationship to its intension and quantity to its extension, which further enriches the relationships between its intentions. Based on QECL, we can mine association rules, comparing with well-known Apriori. Mining association rules on QECL does not need to scan databases for many times, has higher quality of time complexity and shows association rules on the Hasse diagram of QECL more visual and concise. Moreover, it can be used to mine association rules interactively according to the user subjective interest.
OSM: An Open Set Matting Framework with OOD Detection and Few-Shot Learning

Natural image matting is the task of precisely estimating alpha mattes to separate foreground objects from background images. Existing matting methods only focus on classical closed-set problems where object categories and data distributions are similar between training and test sets. However, in the open world setup, there exists a situation where testing samples are drawn from a different distribution than the training data. To handle this situation, we present the first open set matting (OSM) framework that contains two networks: (1) an out-of-distribution (OOD) detection network to identify OOD to-be-matted objects; and (2) an incremental few-shot learning matting module to enlarge the existing knowledge base of to-be-matted objects. Our OOD detection network leverages metric-based prototype learning to be aware of unseen objects and increase inter-class separability, utilizing intra-batch connections to enhance intra-class compactness. Compared to other OOD detection methods, our network achieves state-of-the-art performance on SIMD dataset. Further, our incremental few-shot learning matting module improves the performance on unseen to-be-matted objects by gradually incorporating novel classes into the existing knowledge base without catastrophic forgetting and over-fitting.
Hyperpolarization-Activated Cation Channels Shape the Spiking Frequency Preference of Human Cortical Layer 5 Pyramidal Neurons

Abstract Discerning the contribution of specific ionic currents to complex neuronal dynamics is a difficult, but important, task. This challenge is exacerbated in the human setting, although the widely characterized uniqueness of the human brain compared with preclinical models necessitates the direct study of human neurons. Neuronal spiking frequency preference is of particular interest given its role in rhythm generation and signal transmission in cortical circuits. Here, we combine the frequency-dependent gain (FDG), a measure of spiking frequency preference, and novel in silico analyses to dissect the contributions of individual ionic currents to the suprathreshold features of human layer 5 (L5) neurons captured by the FDG. We confirm that a contemporary model of such a neuron, primarily constrained to capture subthreshold activity driven by the hyperpolarization-activated cyclic nucleotide gated (h-) current, replicates key features of the in vitro FDG both with and without h-current activity. With the model confirmed as a viable approximation of the biophysical features of interest, we applied new analysis techniques to quantify the activity of each modeled ionic current in the moments before spiking, revealing unique dynamics of the h-current. These findings motivated patch-clamp recordings in analogous rodent neurons to characterize their FDG, which confirmed that a biophysically detailed model of these neurons captures key interspecies differences in the FDG. These differences are correlated with distinct contributions of the h-current to neuronal activity. Together, this interdisciplinary and multispecies study provides new insights directly relating the dynamics of the h-current to suprathreshold spiking frequency preference in human L5 neurons.
Physiological reprogramming in vivo mediated by Sox4 pioneer factor activity

Tissue damage elicits cell fate switching through a process called metaplasia, but how the starting cell fate is silenced and the new cell fate is activated has not been investigated in animals. In cell culture, pioneer transcription factors mediate “reprogramming” by opening new chromatin sites for expression that can attract transcription factors from the starting cell’s enhancers. Here we report that Sox4 is sufficient to initiate hepatobiliary metaplasia in the adult liver. In lineage-traced cells, we assessed the timing of Sox4-mediated opening of enhancer chromatin versus enhancer decommissioning. Initially, Sox4 directly binds to and closes hepatocyte regulatory sequences via a motif it overlaps with Hnf4a, a hepatocyte master regulator. Subsequently, Sox4 exerts pioneer factor activity to open biliary regulatory sequences. The results delineate a hierarchy by which gene networks become reprogrammed under physiological conditions, providing deeper insight into the basis for cell fate transitions in animals.
Generalized plasticity and the modelling of soil behaviour

The paper outlines the theory of generalized plasticity in which yield and plastic potential surfaces need not be explicitly defined, and shows how a very effective general model describing the behaviour of sands and of clays under monotonic or transient loading can be developed. The model is currently one of the simplest and yet one of the most effective ones for describing the full range of behaviour. The hierarchical structure of the model limits the number of parameters which have to be experimentally determined for a given material to those strictly necessary for the problem at hand. A discussion of currently used models is included.
Design and analysis of simple robust controllers

The contribution is focused on the design and tuning of simple continuous-time SISO regulators of PID-like structures. All desirable controllers are obtained in the parameter form of general solutions of linear equations in the ring of proper and Hurwitz-stable rational functions. The final controller is then chosen for given specifications, e.g. robustness, asymptotic tracking and disturbance rejection.
Spontaneous emission spectrum of a V-type three-level atom in a Fabry–Perot cavity containing left-handed materials

The spontaneous emission of a V-type Zeeman atom in a Fabry–Perot cavity containing left-handed materials (LHMs) is investigated. Because of the strong indirect quantum interference induced by the refocusing and phase compensation of LHMs, the population evolution and the emission spectrum are much different from that in isotropic environments at different initial conditions. For the degenerate cases, by preparing different initial states, the population decays much faster or slower than that in free vacuum, while the spontaneous emission spectra are narrowed or broadened, respectively. For large detuning cases, the population exchange between two upper levels could be weakened, and the Fano minimum appears in the emission spectrum. In addition, the influence of the dipole orientation on the spectrum is discussed.
The anomalous wake accompanying bubbles rising in a thin gap: a mechanically forced Marangoni flow

A novel wake structure, observed as penny-shaped air bubbles rise at moderate Reynolds number through a thin layer of water bound between parallel glass plates inclined at a shallow angle relative to the horizontal, is reported. The structure of the wake is revealed through tracking particles suspended in the water. The wake completely encircles the rising bubble, and is characterized by a reverse surface flow or ‘edge jet’ which transports fluid in a thin boundary layer along the bubble surface from the tail to the nose at speeds which are typically an order of magnitude larger than the bubble rise speed. A consistent physical explanation for the wake structure is proposed. The wake is revealed to be a manifestation of the three-dimensionality of the flow in the suspending fluid. The bubble surface advances through a rolling motion, thus generating regions of surface divergence and convergence at, respectively, the leading and trailing edges of the bubble. A nose-to-tail gradient in surfactant concentration is thus established, and the associated surface tension gradient drives the edge jet. The dependence of the wake structure on the suspending fluid is examined experimentally. Surfactants play an anomalous role in the reported flow, serving to promote rather than suppress surface motions. The wake structure is an example of a mechanically forced Marangoni flow, and so represents a mechanical analogue of that accompanying thermocapillary drop motion in microgravity. A theoretical model is developed which reproduces the salient features of the flow, and on the basis of which an estimate is made of the mechanically induced surface tension gradient along the bubble surface.
The 2021 German Federal Election on Social Media: Analysing Electoral Risks Created by Twitter and Facebook

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the ‘systemic electoral risks’ created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research.
Numerical methods for large-scale nonlinear optimization

Recent developments in numerical methods for solving large differentiable nonlinear optimization problems are reviewed. State-of-the-art algorithms for solving unconstrained, bound-constrained, linearly constrained and non-linearly constrained problems are discussed. As well as important conceptual advances and theoretical aspects, emphasis is also placed on more practical issues, such as software availability.
Anticipating Energy-driven Crises in Process Industry by AI-based Scenario Planning

Power outages and fluctuations represent serious crisis situations in energy-intensive process industry like glass and paper production, where substances such as oil, gas, wood fibers or chemicals are processed. Power disruptions can interrupt chemical reactions and produce tons of waste as well as damage of machine parts. But, despite of the obvious criticality, handling of outages in manufacturing focuses on commissioning of expensive proprietary power plants to protect against power outages and implicit gut feeling in anticipating potential disruptions. With AISOP, we introduce a model for AI-based scenario planning for predicting crisis situations. AISOP uses conceptual, well-defined scenario patterns to capture entities of crisis situations. Data streams are mapped onto these patterns for determining historic crisis scenarios and predicting future crisis scenarios by using inductive knowledge and machine learning. The model was exemplified within a proof of concept for energy-driven disruption prediction. We were able to evaluate the proposed approach by means of a set of data streams on weather and outages in Germany in terms of performance in predicting potential outages for manufacturers of paper industry with promising results
An estimate of the Kelvin impulse of a transient cavity

The Lagally theorem is used to obtain an expression for the Bjerknes force acting on a bubble in terms of the singularities of the fluid velocity potential, defined within the bubble by analytic continuation. This expression is applied to transient cavity collapse in the neighbourhood of boundaries, allowing analytical estimates to be made of the Kelvin impulse of the cavity. The known result for collapse near a horizontal rigid boundary is recovered, and the Kelvin impulse of a cavity collapsing in the neighbourhood of a submerged and partially submerged sphere is estimated. A numerical method is developed to deal with more general body shapes and in particular, bodies of revolution. Noting that the direction of the impulse at the end of the collapse phase generally indicates the direction of the liquid jet that may form, the behaviour of transient cavities in these geometries is predicted. In these examples the concept of a zone of attraction is introduced. This is a region around the body, within which the Kelvin impulse at the time of collapse, and consequent jet formation, is expected to be directed towards the body. Outside this zone the converse is true.