Miracle-dz/UniFAR-FTUs huggingface dataset:
Faculty from Marginalized Groups in the Health and Social Service Professions: Challenging “Expected Academic” Identity and Roles

Academics have historically been members of socially dominant groups—white, cisgender, heterosexual men, from middle- to upper-classes, who identify as able-bodied and able-minded. Members of other groups are often disadvantaged. In two larger studies, semi-structured interviews were conducted with professionals from marginalized groups. Here we explore the narratives of 16 participants who explicitly discussed their experiences in faculty positions within the health and social service professions. The expected academic roles of teacher, researcher, and colleague/administrator did not neatly fit for participants, clashing with the expectations they faced by virtue of their marginalized identities. Within the health and social service professions, the norms and expectations of the academy required marginalized faculty to make sacrifices of their time and sense of self to meet job demands. The effects of these role conflicts are pervasive, affecting many areas of academic work and beyond.
Development and validation of HBV surveillance models using big data and machine learning

Abstract Background The construction of a robust healthcare information system is fundamental to enhancing countries’ capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China’s rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization’s (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China. Methods Relevant data records extracted from the Family Medicine Clinic of the University of Hong Kong-Shenzhen Hospital’s Hospital Information System were structuralized using state-of-the-art Natural Language Processing techniques. Several ML models have been used to develop HBV risk assessment models. The performance of the ML model was then interpreted using the Shapley value (SHAP) and validated using cohort data randomly divided at a ratio of 2:1 using a five-fold cross-validation framework. Results The patterns of physical complaints of patients with and without HBV infection were identified by processing 158,988 clinic attendance records. After removing cases without any clinical parameters from the derivation sample (n = 105,992), 27,392 cases were analysed using six modelling methods. A simplified model for HBV using patients’ physical complaints and parameters was developed with good discrimination (AUC = 0.78) and calibration (goodness of fit test p-value >0.05). Conclusions Suspected case detection models of HBV, showing potential for clinical deployment, have been developed to improve HBV surveillance in primary care setting in China. (Word count: 264)
Using OpenStreetMap to improve population grids in Europe

ABSTRACT OpenStreetMap (OSM) database has previously been used to support spatial disaggregation of population data by partly masking out non-residential impervious areas in the European Copernicus imperviousness layer (IL). However, the exact procedure of OSM data incorporation is unknown, and its contribution to the improvement of estimation accuracy has never been studied. In this article, we present a sensitivity study to find out which road categories should be used for masking of IL and how the linear features might be transformed to raster representation. Using Austria and Slovenia as a study area, 2006 commune population counts are disaggregated into 100 m grid cells using 12 versions of modified IL. Further tuning of estimates is performed using CORINE Land Cover (CLC) data in an iterative algorithm. Disaggregated grids are then validated against reference 1 km census-based data. The results show that overall error was reduced thanks to OSM incorporation in all tested scenarios, although the relative improvement varies between as well as within the two countries. The best result (5.3% reduction) was achieved using railways and three major road categories (motorway, trunk, and primary) with double exaggeration of width.
Marine Resource Intensification and the Reorganization of Lithic Technologies during the Middle-Late Holocene in Northwest Alaska

ABSTRACT This study uses lithic technological organization from two successive Middle–Late Holocene archaeological cultures in northwest Alaska to test hypotheses about marine resource intensification through time. Researchers argue that maritime adaptations in northwest Alaska progressed from supplementary seasonal exploitation towards a highly complex, year-round reliance on marine resources. Robust faunal assemblages and organic technologies necessary to demonstrate this developmental transformation are generally lacking in sites from this time period. Instead, our primary sources of data are site locations, features, and lithic technology. Theorists have shown that technological organization, including lithic components, is greatly influenced by subsistence strategy and residential mobility. In theory, an increased reliance on marine resources should result in increased technological complexity, greater use of local raw materials, and overall less concern with optimizing size and weight of tools. I test these hypotheses using Arctic Small Tool and Norton tradition lithic assemblages from the stratified, multi-component site of Iyatayet, located in northwest Alaska. The results indicate technological organization of the later culture differed in many important ways from the earlier group, supporting interpretations of reduced mobility and a greater reliance on resources from the sea through time.
Molecular and thermodynamic determinants of self-assembly and hetero-oligomerization in the enterobacterial thermo-osmo-regulatory protein H-NS

Abstract Environmentally regulated gene expression is critical for bacterial survival under stress conditions, including extremes in temperature, osmolarity and nutrient availability. Here, we dissect the thermo- and osmo-responsory behavior of the transcriptional repressor H-NS, an archetypal nucleoid-condensing sensory protein, ubiquitous in enterobacteria that infect the mammalian gut. Through experiments and thermodynamic modeling, we show that H-NS exhibits osmolarity, temperature and concentration dependent self-association, with a highly polydisperse native ensemble dominated by monomers, dimers, tetramers and octamers. The relative population of these oligomeric states is determined by an interplay between dimerization and higher-order oligomerization, which in turn drives a competition between weak homo- versus hetero-oligomerization of protein-protein and protein-DNA complexes. A phosphomimetic mutation, Y61E, fully eliminates higher-order self-assembly and preserves only dimerization while weakening DNA binding, highlighting that oligomerization is a prerequisite for strong DNA binding. We further demonstrate the presence of long-distance thermodynamic connectivity between dimerization and oligomerization sites on H-NS which influences the binding of the co-repressor Cnu, and switches the DNA binding mode of the hetero-oligomeric H-NS:Cnu complex. Our work thus uncovers important organizational principles in H-NS including a multi-layered thermodynamic control, and provides a molecular framework broadly applicable to other thermo-osmo sensory proteins that employ similar mechanisms to regulate gene expression.
Recent developments in the management of ascites in cirrhosis

Abstract In recent years, advances have been made for treating ascites in patients with cirrhosis. Recent studies have indicated that several treatments that have been used for a long time in the management of portal hypertension may have beneficial effects that were not previously identified. Long‐term albumin infusion may improve survival in patients with cirrhosis and ascites while beta‐blockers may reduce ascites occurrence. Transjugular intrahepatic porto‐systemic shunt (TIPS) placement may also improve survival in selected patients in addition to the control with ascites. Low‐flow ascites pump insertion can be another option for some patients with intractable ascites. In this review, we summarize the latest data related to the management of ascites occurring in cirrhosis. There are still unanswered questions, such as the optimal use of albumin as a long‐term therapy, the place of beta‐blockers, and the best timing for TIPS placement to improve the natural history of ascites, as well as the optimal stent diameter to reduce the risk of shunt‐related side‐effects. These issued should be addressed in future studies.
Genomics reveals heterogeneous Plasmodium falciparum transmission and population differentiation in Zambia and bordering countries

Genomic surveillance plays a critical role in monitoring malaria transmission and understanding how the parasite adapts in response to interventions. We conducted genomic surveillance of malaria by sequencing 241 Plasmodium falciparum genomes from regions with varying levels of malaria transmission across Zambia. We found genomic evidence of high levels of within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in the country. We identified country-level clustering of parasites from Zambia and neighboring countries, and distinct clustering of parasites from West Africa. Within Zambia, our identity by descent (IBD) relatedness analysis uncovered spatial clustering of closely related parasite pairs at the local level and rare cases of long-distance sharing. Genomic regions with large shared IBD segments and strong positive selection signatures identified genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Together, our findings enhance our understanding of P. falciparum transmission nationwide in Zambia and highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.
Genetic Insights into the Relationship Between Psychiatric Disorders and Irritable Bowel Syndrome: A Mendelian Randomization Analysis.

Background: Irritable Bowel Syndrome (IBS) is often accompanied by psychiatric conditions, yet the causal relationship remains uncertain. This study leverages Mendelian Randomization to explore the genetic basis of the association between IBS and various psychiatric disorders. Methods: We analyzed GWAS data to assess the causal effects of Major Depressive Disorder (MDD), Anxiety, and other psychiatric disorders on Irritable Bowel Syndrome (IBS). Stringent criteria were used to select genetic instrumental variables, and we applied multiple Mendelian Randomization (MR) methods, including a reverse MR analysis, to investigate the impacts comprehensively. Results: Our study found a significant causal relationship between IBS and MDD (IVW OR: 1.328, 95% CI: 1.122, 1.572, P=0.001) and a slight but significant link with Anxiety Disorders (IVW OR: 1.0611, 95% CI: 1.0184, 1.1056, P=0.0046). Bipolar Disorder, Schizophrenia, OCD, ADHD, Anorexia Nervosa, and Insomnia did not show significant causal connections with IBS. The reverse MR analysis demonstrated a positive correlation between IBS and MDD (IVW OR: 1.522) and a negative one with ADHD (IVW OR: 0.866), while findings for Schizophrenia and other disorders were not significant. Conclusion: The study confirms a unidirectional causal relationship between IBS and certain psychiatric disorders, highlighting the relevance of the gut-brain axis. These insights contribute to the understanding of IBS pathophysiology and underscore the need for considering mental health in IBS management.
Utility of unmanned aerial vehicles for mapping invasive plant species: a case study on yellow flag iris (Iris pseudacorus L.)

ABSTRACT This study investigates the utility of an off-the-shelf, consumer-grade unmanned aerial vehicle (UAV) for invasive species mapping in a lacustrine fringe environment. Specifically, this work sought to determine whether such a UAV would be capable of creating accurate maps of the extent of patches of an invasive plant, yellow flag iris (Iris pseudacorus L.), more efficiently than could be accomplished by a traditional field survey, which is often considered in the literature to provide the most accurate maps. The study was conducted at two lakes in the central interior of British Columbia. The UAV used in this study was a DJI Phantom 3 Professional that can acquire images using the built-in 12.4 MP digital camera. This UAV was selected because it is representative of the type of aerial platform that is easily accessible to invasive plant managers in terms of cost, ease of use, and lack of legal restrictions. Three methods of mapping the yellow flag iris were compared: (1) field survey, (2) manual interpretation of the raw UAV-acquired imagery and the orthoimage created from these data, and (3) pixel-based classification of the orthoimage created from the UAV imagery using a random forest classifier. The results revealed that, at both lakes considered, manual interpretation of the UAV-acquired imagery produced the most accurate maps of yellow flag iris infestation, with a false-positive and false-negative classification rate of less than 1%.
The Quantified Boolean Bayesian Network: Theory and Experiments with a Logical Graphical Model

This paper introduces the Quantified Boolean Bayesian Network (QBBN), which provides a unified view of logical and probabilistic reasoning. The QBBN is meant to address a central problem with the Large Language Model (LLM), which has become extremely popular in Information Retrieval, which is that the LLM hallucinates. A Bayesian Network, by construction, cannot hallucinate, because it can only return answers that it can explain. We show how a Bayesian Network over an unbounded number of boolean variables can be configured to represent the logical reasoning underlying human language. We do this by creating a key-value version of the First-Order Calculus, for which we can prove consistency and completeness. We show that the model is trivially trained over fully observed data, but that inference is non-trivial. Exact inference in a Bayesian Network is intractable (i.e. $\Omega(2^N)$ for $N$ variables). For inference, we investigate the use of Loopy Belief Propagation (LBP), which is not guaranteed to converge, but which has been shown to often converge in practice. Our experiments show that LBP indeed does converge very reliably, and our analysis shows that a round of LBP takes time $O(N2^n)$, where $N$ bounds the number of variables considered, and $n$ bounds the number of incoming connections to any factor, and further improvements may be possible. Our network is specifically designed to alternate between AND and OR gates in a Boolean Algebra, which connects more closely to logical reasoning, allowing a completeness proof for an expanded version of our network, and also allows inference to follow specific but adequate pathways, that turn out to be fast.
Hamiltonicity of Sparse Pseudorandom Graphs

We show that every $(n,d,\lambda)$-graph contains a Hamilton cycle for sufficiently large $n$, assuming that $d\geq \log^{10}n$ and $\lambda\leq cd$, where $c=\frac{1}{9000}$. This significantly improves a recent result of Glock, Correia and Sudakov, who obtain a similar result for $d$ that grows polynomially with $n$. The proof is based on the absorption technique combined with a new result regarding the second largest eigenvalue of the adjacency matrix of a subgraph induced by a random subset of vertices. We believe that the latter result is of an independent interest and will have further applications.
Dynamics near the origin of the long range scattering for the one-dimensional Schrodinger equation

We consider the cubic Schrodinger equation on the line, for which the scattering theory requires modifications due to long range effects. We revisit the construction of the modified wave operator, and recall the construction of its inverse, in order to describe the asymptotic behavior of these operators near the origin. At leading order, these operators, whose definition includes a nonlinear modification in the phase compared to the linear dynamics, correspond to the identity. We compute explicitly the first corrector in the asymptotic expansion, and justify this expansion by error estimates.
I-Love-$\langle c_s^2 \rangle$: Approximately universal relations for the average neutron star stiffness

The accurate observations of neutron stars have deepened our knowledge of both general relativity and the properties of nuclear physics at large densities. Relating observations to the microphysics that govern these stars can sometimes be aided by approximate universal relations. One such relation connects the ratio of the central pressure to the central energy density and the compactness of the star, and it has been found to be insensitive to realistic models for the equation of state to a $\sim 10\%$ level. In this paper, we clarify the meaning of the microscopic quantity appearing in this relation, which is reinterpreted as the average of the speed of sound squared in the interior of a star, $\langle c_s^2 \rangle\! $. The physical origin of the quasi-universality of the $\langle c_s^2 \rangle - C$ relation is then investigated. Making use of post-Minkowskian expansions, we find it to be linked to the Newtonian limit of the structure equations, as well as to the fact that the equations of state that describe NSs are relatively stiff. The same post-Minkowskian approach is also applied to the relations between $\langle c_s^2 \rangle\! $, the moment of inertia, and the tidal deformability of a neutron star, arriving at similar conclusions.
Robust inference for an interval-monitored step-stress experiment under proportional hazards

Accelerated life tests (ALTs) play a crucial role in reliability analyses, providing lifetime estimates of highly reliable products. Among ALTs, step-stress design increases the stress level at predefined times, while maintaining a constant stress level between successive changes. This approach accelerates the occurrence of failures, reducing experimental duration and cost. While many studies assume a specific form for the lifetime distribution, in certain applications instead a general form satisfying certain properties should be preferred. Proportional hazard model assumes that applied stresses act multiplicatively on the hazard rate, so the hazards function may be divided into two factors, with one representing the effect of the stress, and the other representing the baseline hazard. In this work we examine two particular forms of baseline hazards, namely, linear and quadratic. Moreover, certain experiments may face practical constraints making continuous monitoring of devices infeasible. Instead, devices under test are inspected at predetermined intervals, leading to interval-censoring data. On the other hand, recent works have shown an appealing trade-off between the efficiency and robustness of divergence-based estimators. This paper introduces the step-stress ALT model under proportional hazards and presents a robust family of minimum density power divergence estimators (MDPDEs) for estimating device reliability and related lifetime characteristics such as mean lifetime and distributional quantiles. The asymptotic distributions of these estimates are derived, providing approximate confidence intervals. Empirical evaluations through Monte Carlo simulations demonstrate their performance in terms of robustness and efficiency. Finally, an illustrative example is provided to demonstrate the usefulness of the model and associated methods developed.
Configuration models for random directed hypergraphs

Many complex systems show non-pairwise interactions, which can be captured by hypergraphs. In this work, we establish configuration models in which both the vertex and the hyperarc degrees are preserved for different classes of directed hypergraphs (containing self-loops, degenerate hyperarcs and/or multiple hyperarcs). We propose an edge-swapping method to uniformly sample from these configuration models and prove that this method indeed samples uniformly from the classes with self-loops and multiple hyperarcs, and that the method does not sample uniformly from classes without self-loops, or with self-loops and degenerate hyperarcs but without multiple hyperarcs. We present a partial result on the class with self-loops, but without degenerate hyperarcs or multiple hyperarcs.
A Unified Causal View of Instruction Tuning

Instruction tuning on a mixture of tasks has improved zero-shot capabilities in natural language processing (NLP). Nevertheless, existing methods often learn features that exhibit correlations between instruction-formatted samples and target labels, rather than causal relationships. Termed as ``spurious correlation'' in statistics, such a correlation may change drastically in a new task, making the effect from the learned features to be misleading. To this end, we develop a meta Structural Causal Model (meta-SCM) to integrate different NLP tasks under a single causal structure of the data. Specifically, the meta-SCM introduces multiple latent factors that represent properties of source context, only some of which causally influence the target labels for a specific task. The key idea is to learn task-required causal factors and only use those to make predictions for a given task. Theoretically, we prove the causal factor can be identified without mixing information from others. Guided by the identifiability, we propose a Structural Instruction Tuning (SIT) method to learn the task-required causal representations that can mimic the causal factors for each task. The utility of our approach is verified by improvements of zero-shot ability on a range of unseen datasets and tasks.
Arqueología en la Linea Noroeste de La Española. Paisaje, cerámicas e interacciones

The northern region of Hispaniola is one the most referenced areas in Caribbean archaeology and historiography. Nevertheless, its central presence in textbooks belies a lack of understanding in both disciplines of the complex history of the region. The research presented here reassesses the interactions that occurred among the multiform indigenous communities (Meillacoid and Chicoid) that inhabited the region during the pre-Columbian period. A focus on these interactions forms the basis of an approach that can differentiate this region from others on Hispaniola and the Western Caribbean. It also links this research to recent Pan-Caribbean approaches, such as those employed by the Caribbean Research Group at the University of Leiden. As a result this research attempts to go beyond the traditional diachronic studies used in indigenous archaeology and rather will take a synchronic perspective. This highlights such issues as inter-group communication, competency, transculturation and syncretism that emerge from the Caribbean pre-Columbian multicultural mosaic. All of this is derived from an in-depth study of the cultural landscape in northern Hispaniola and nuances in material culture expressions, especially ceramic formal and stylistic traditions.