Miracle-dz/UniFAR-FTUs huggingface dataset:
Transactional Desire: Exploring Male Student Sex Workers in China

ABSTRACT This paper presents a descriptive study of Chinese male student sex workers through a grounded theory analysis of 25 semi-structured one-to-one online interviews. We found that the internet and introductions by peers were the two primary channels for Chinese male students to enter the sex industry. Most students were motivated to be involved in commercial sex by a mixture of consumption and sexual desires. Student sex workers motivated mainly by sexual desire often selected clients and considered commercial sex as “transactional hookups. ” Student sex workers used strategies, including concealing, separating sex and love, simulating boyfriend experiences, and terminating romantic relationships, to deal with the stigmas they encountered. Sexual health and sexually transmitted disease prevention-oriented sexuality education in China had positive impacts on male student sex workers, but we also found the need for more comprehensive sexuality education. As emerging adults, college students are in a life stage distinct from adolescents and adults. We believe student sex work, as well as emerging adult sex work in general, needs to be differentiated from voluntary adult sex work in both scholarly research and public discussions of the legal status of sex work, especially in cases where students are not informed about the risks of engaging in commercial sex.
Surveillance of communicable diseases using social media: A systematic review

Background Communicable diseases pose a severe threat to public health and economic growth. The traditional methods that are used for public health surveillance, however, involve many drawbacks, such as being labor intensive to operate and resulting in a lag between data collection and reporting. To effectively address the limitations of these traditional methods and to mitigate the adverse effects of these diseases, a proactive and real-time public health surveillance system is needed. Previous studies have indicated the usefulness of performing text mining on social media. Objective To conduct a systematic review of the literature that used textual content published to social media for the purpose of the surveillance and prediction of communicable diseases. Methodology Broad search queries were formulated and performed in four databases. Both journal articles and conference materials were included. The quality of the studies, operationalized as reliability and validity, was assessed. This qualitative systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results Twenty-three publications were included in this systematic review. All studies reported positive results for using textual social media content to surveille communicable diseases. Most studies used Twitter as a source for these data. Influenza was studied most frequently, while other communicable diseases received far less attention. Journal articles had a higher quality (reliability and validity) than conference papers. However, studies often failed to provide important information about procedures and implementation. Conclusion Text mining of health-related content published on social media can serve as a novel and powerful tool for the automated, real-time, and remote monitoring of public health and for the surveillance and prediction of communicable diseases in particular. This tool can address limitations related to traditional surveillance methods, and it has the potential to supplement traditional methods for public health surveillance.
Repeatable runout disturbance compensation with a new data collection method for hard disk drive

In this paper, a new method to determine repeatable runout (RRO) disturbance data is proposed. The obtained RRO disturbance data is further used to compensate for the RRO disturbance. The error transfer function (or sensitivity function) can be obtained without any additional instrument, and moreover the estimated RRO disturbance obtained from the proposed method will not be affected by the variation of the actuator model. Furthermore, the proposed method is much easier to be implemented than the fast Fourier transform and inverse fast Fourier transform (FFT/IFFT) method as much less computation is needed. Experimental results show that the servo tracking performance can be significantly improved by using the estimated disturbance to compensate the actual RRO disturbances. Comparative study between the proposed RRO compensation method and the iterative learning control (ILC)-based compensation method has also been performed in this paper.
Risk for Prison-to-Community Tuberculosis Transmission, Thailand, 2017–2020

To determine contributions of previously incarcerated persons to tuberculosis (TB) transmission in the community, we performed a healthcare facility–based cohort study of TB patients in Thailand during 2017–2020. We used whole-genome sequencing of Mycobacterium tuberculosis isolates from patients to identify genotypic clusters and assess the association between previous incarceration and TB transmission in the community. We identified 4 large genotype clusters (>10 TB patients/cluster); 28% (14/50) of the patients in those clusters were formerly incarcerated. Formerly incarcerated TB patients were more likely than nonincarcerated patients to be included in large clusters. TB patients within the large genotype clusters were geographically dispersed throughout Chiang Rai Province. Community TB transmission in the community was associated with the presence of formerly incarcerated individuals in Thailand. To reduce the risk for prison-to-community transmission, we recommend TB screening at the time of entry and exit from prisons and follow-up screening in the community.
Determination of Nonlinear Functional Response Functions in Rainfall-Runoff Processes

The operation of some hydrologie systems can be represented by a functional series expansion involving higher order nonlinear generalizations of the convolution integral, which underlies the unit hydrograph concept. A method was developed to determine the linear and nonlinear response functions of such systems on the basis of concurrent records of the input and output. This procedure was successfully tested in a special laboratory catchment and in a natural watershed to establish rainfall-runoff relations.
Textstar: a Fast and Lightweight Graph-Based Algorithm for Extractive Summarization and Keyphrase Extraction

We introduce Textstar, a graph-based summarization and keyphrase extraction system that builds a document graph using only lemmatization and POS tagging. The document graph aggregates connections between lemma and sentence identifier nodes. Consecutive lemmas in each sentence, as well as consecutive sentences themselves, are connected in rings to form a ring of rings representing the document. We iteratively apply a centrality algorithm of our choice to the document graph and trim the lowest ranked nodes at each step. After the desired number of remaining sentences and lemmas is reached, we extract the sentences as the summary, and the remaining lemmas are aggregated into keyphrases using their context. Our algorithm is efficient enough to one-shot process large document graphs without any training, and empirical evaluation on several benchmarks indicates that our performance is higher than most other graph based algorithms.
Contrastive Visual and Language Learning for Visual Relationship Detection

Visual Relationship Detection aims to understand real-world objects’ interactions by grounding visual concepts to compositional visual relation triples, written in the form of (subject, predicate, object). Previous works have explored the use of contrastive learning to implicitly predict the predicates from the relevant image regions. However, these models often directly leverage in-distribution spatial and language co-occurrences biases during training, preventing the models from generalizing to out-of-distribution compositions. In this work, we examine whether contrastive vision and language models pre-trained on large-scale external image and text dataset can assist the detection of compositional visual relationships. To this end, we propose a semi-supervised contrastive fine-tuning approach for the visual relationship detection task. The results show that fine-tuned models that were pre-trained on larger datasets do not yield better performance when performing visual relationship detection, and larger models can yield lower performance when compared with their smaller counterparts.
MPI-based Remote OpenMP Offloading: A More Efficient and Easy-to-use Implementation

MPI+X is the most popular hybrid programming model for distributed computation on modern heterogeneous HPC systems. Nonetheless, for simplicity, HPC developers ideally would like to implement multi-node distributed parallel computing through a single coherent programming model. As de facto standard for parallel programming, OpenMP has been one of the most influential programming models in parallel computing. Recent work has proven that the OpenMP target offloading model could be used to program distributed accelerator-based HPC systems with marginal changes to the application. However, the UCX-based version of remote OpenMP offloading still has many limitations in terms of performance overhead and ease of use of the plugin. In this work, we have implemented a new MPI-based remote OpenMP offloading plugin. By comparing it with the UCX-based version, the new MPI-based plugin has been significantly improved in terms of performance, scalability, and ease of use. Evaluation of our work is conducted using one proxy-app, XSBench and an industrial-level seismic modeling code, Minimod. Results show that, compared to the optimized UCX-based version, our optimizations can reduce offloading latency by up to 70%, and raise application parallel efficiency by 68% when running with 16 GPUs on data-bound applications. In particular, the introduction of the concept of locality-aware offloading gives developers of HPC programs greater possibilities to take full advantage of modern hierarchical heterogeneous computing devices.
Boundary bound states in integrable quantum eld theory

The purpose of this talk is to sketchsome recent progresswhich has been made in calcu- lating non-perturbatively the reflection factors for the sinh-Gordon model restricted to a half-line by integrable boundary conditions. The essential idea is to calculate the energy spectrum of boundary breathers in two independent ways; rstly by using the boundary bootstrap and secondly by quan- tizing the classical solutions corresponding to boundary breathers. Comparing these two calculations provides a way to determine the dependence of the reflection factors on the parameters introduced into the Lagrangian by the boundary conditions. The basic idea is illustrated using a massive free scalar eld with a linear boundary condition conning it to a half-line.
On the relationship between dissipation and the rate of spontaneous entropy production from linear irreversible thermodynamics

When systems are far from equilibrium, the temperature, the entropy and the thermodynamic entropy production are not defined and the Gibbs entropy does not provide useful information about the physical properties of a system. Furthermore, far from equilibrium, or if the dissipative field changes in time, the spontaneous entropy production of linear irreversible thermodynamics becomes irrelevant. In 2000 we introduced a definition for the dissipation function and showed that for systems of arbitrary size, arbitrarily near or far from equilibrium, the time integral of the ensemble average of this quantity can never decrease. In the low-field limit, its ensemble average becomes equal to the spontaneous entropy production of linear irreversible thermodynamics. We discuss how these quantities are related and why one should use dissipation rather than entropy or entropy production for non-equilibrium systems.
Ventral premotor cortex influences spinal cord activation during force generation

Force generation is a crucial element of dexterity and a highly relevant skill of the human motor system. How cerebral and spinal components interact and how spinal activation is influenced by cerebral primary motor and premotor areas is poorly understood. Here we conducted combined cortico-spinal functional MRI during a simple visually guided isometric force generation task in a group of 20 healthy young subjects. Activation was localized in the ipsilateral cervical spinal cord and contralateral primary motor and premotor areas. The main finding is that spinal activation was influenced by ventral premotor cortex activation. Spinal activation was furthermore significantly correlated with primary motor cortex activation while increasing target forces led to an increase in the amount of activation. These data indicate that human premotor areas such as the ventral premotor cortex might be functionally connected to the lower cervical spinal cord contributing to distal upper limb functions, a finding which extends our understanding about human motor function beyond the animal literature.
Mechanisms of nuclear pore complex disassembly by the mitotic Polo-like kinase 1 (PLK-1) in C. elegans embryos

The nuclear envelope, which protects and organizes the interphase genome, is dismantled during mitosis. In the C. elegans zygote, nuclear envelope breakdown (NEBD) of the parental pronuclei is spatially and temporally regulated during mitosis to promote the unification of the parental genomes. During NEBD, Nuclear Pore Complex (NPC) disassembly is critical for rupturing the nuclear permeability barrier and removing the NPCs from the membranes near the centrosomes and between the juxtaposed pronuclei. By combining live imaging, biochemistry, and phosphoproteomics, we characterized NPC disassembly and unveiled the exact role of the mitotic kinase PLK-1 in this process. We show that PLK-1 disassembles the NPC by targeting multiple NPC sub-complexes, including the cytoplasmic filaments, the central channel, and the inner ring. Notably, PLK-1 is recruited to and phosphorylates intrinsically disordered regions of several multivalent linker nucleoporins, a mechanism that appears to be an evolutionarily conserved driver of NPC disassembly during mitosis. (149/150 words) One-Sentence Summary PLK-1 targets intrinsically disordered regions of multiple multivalent nucleoporins to dismantle the nuclear pore complexes in the C. elegans zygote.
Arf6 Regulates Endocytosis and Angiogenesis by Promoting Filamentous Actin Assembly

Clathrin-mediated endocytosis (CME) is a process vital to angiogenesis as well as general vascular homeostasis. In pathologies where supraphysiological growth factor signaling underlies disease etiology, such as in diabetic retinopathy and solid tumors, strategies to limit chronic growth factor signaling by way of CME have been shown to have tremendous clinical value. ADP ribosylation factor 6 (Arf6) is a small GTPase that promotes the assembly of actin necessary for CME. In its absence, growth factor signaling is greatly diminished, which has been shown to ameliorate pathological signaling input in diseased vasculature. However, it is less clear if there are bystander effects related to loss of Arf6 on angiogenic behaviors. Our goal was to provide a analysis of Arf6’s function in angiogenic endothelium, focusing on its role in lumenogenesis as well as its relation to actin and CME. We found that Arf6 localized to both filamentous actin and sites of CME in 2-dimensional culture. Loss of Arf6 distorted both apicobasal polarity and reduced the total cellular filamentous actin content, and this may be the primary driver underlying gross dysmorphogenesis during angiogenic sprouting in its absence. Our findings highlight that endothelial Arf6 is a potent mediator of both actin regulation and CME.
Phenotypic plasticity and genetic differentiation drive troglomorphic character development in European cave loach

Using a cross-fostering experiment, we provide evidence for the contribution of both genetic differentiation and phenotypic plasticity to troglomorphic character development in the recently discovered cave form of Barbatula barbatula, an evolutionarily young lineage and first cavefish described in Europe, the northernmost record. We established reproducing populations of cave- and surface-dwelling loaches to produce cave, surface, and hybrid offspring and reared the F1 fish in a common garden setting in total darkness (DD) to simulate cave conditions as well as under the natural photoperiod (DL). We observed significant differences in the occurrence and extent of typical troglomorphic target characters among the offspring groups. Regardless of rearing conditions, cave fish exhibited smaller eyes, lighter body coloration, longer barbels, and larger olfactory epithelium than seen in surface fish. Hybrids in both rearing conditions generally showed an intermediate level of these traits. Surface and hybrid DD fish differed from the DL groups, resembling the cave fish phenotype in several traits, including eye size and body pigmentation. In contrast, cave and hybrid DL fish groups resembled surface fish phenotypes. Results confirmed that troglomorphic traits arise from heritable genetic differentiation of cave from surface forms and that phenotypic plasticity contributes to the process of adaptation to novel light conditions.
DR-BERT: A Protein Language Model to Annotate Disordered Regions

Despite their lack of a rigid structure, intrinsically disordered regions in proteins play important roles in cellular functions, including mediating protein-protein interactions. Therefore, it is important to computationally annotate disordered regions of proteins with high accuracy. Most popular tools use evolutionary or biophysical features to make predictions of disordered regions. In this study, we present DR-BERT, a compact protein language model that is first pretrained on a large number of unannotated proteins before being trained to predict disordered regions. Although it does not use any explicit evolutionary or biophysical information, DR-BERT shows a statistically significant improvement when compared to several existing methods on a gold standard dataset. We show that this performance is due to the information learned during pretraining and DR-BERT’s ability to use contextual information. A web application for using DR-BERT is available at https://huggingface.co/spaces/nambiar4/DR-BERT and the code to run the model can be found at https://github.com/maslov-group/DR-BERT.
Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources

Functional enrichment is the process of identifying implicated functional terms from a given input list of genes or proteins. In this article, we present Flame (v2.0), a web tool which offers a combinatorial approach through merging and visualizing results from widely-used functional enrichment applications while also allowing various flexible input options. In this version, Flame utilizes the aGOtool, g:Profiler, WebGestalt and Enrichr pipelines and presents their outputs separately or in combination following a visual analytics approach. For intuitive representations and easier interpretation, it uses interactive plots such as parameterizable networks, heatmaps, barcharts and scatter plots. Users can also: (i) handle multiple protein/gene lists and analyze union and intersection sets simultaneously through interactive UpSet plots, (ii) automatically extract genes and proteins from free text through text-mining and Named Entity Recognition (NER) techniques, (iii) upload single nucleotide polymorphisms (SNPs) and extract their relative genes or (iv) analyze multiple lists of differentially-expressed proteins/genes after selecting them interactively from a parameterizable volcano plot. Compared to the previous version of 197 supported organisms, Flame (v2.0) currently allows enrichment for 14,436 organisms.
The impact of chemical fixation on the microanatomy of mouse brain tissue

Chemical fixation using paraformaldehyde (PFA) is a standard step for preserving cells and tissues for subsequent microscopic analyses such as immunofluorescence or electron microscopy. However, chemical fixation may introduce physical alterations in the spatial arrangement of cellular proteins, organelles and membranes. With the increasing use of super-resolution microscopy to visualize cellular structures with nanometric precision, assessing potential artifacts - and knowing how to avoid them - takes on special urgency. We addressed this issue by taking advantage of live-cell super-resolution microscopy that makes it possible to directly observe the acute effects of PFA on organotypic brain slices, allowing us to compare tissue integrity in a ‘before-and-after’ experiment. We applied super-resolution shadow imaging to assess the structure of the extracellular space (ECS) and regular super-resolution microscopy of fluorescently labeled neurons and astrocytes to quantify key neuroanatomical parameters. While the ECS volume fraction and micro-anatomical organization of astrocytes remained largely unaffected by the PFA treatment, we detected subtle changes in dendritic spine morphology and observed substantial damage to cell membranes. Our experiments show that PFA application via immersion does not cause a noticeable shrinkage of the ECS in brain slices, unlike the situation in transcardially perfused animals where the ECS typically becomes nearly depleted. In addition to the super-resolved characterization of fixation artefacts in identified cellular and tissue compartments, our study outlines an experimental strategy to evaluate the quality and pitfalls of various fixation protocols for the molecular and morphological preservation of cells and tissues.
choros: correction of sequence-based biases for accurate quantification of ribosome profiling data

Ribosome profiling quantifies translation genome-wide by sequencing ribosome-protected fragments, or footprints. Its single-codon resolution allows identification of translation regulation, such as ribosome stalls or pauses, on individual genes. However, enzyme preferences during library preparation lead to pervasive sequence artifacts that obscure translation dynamics. Widespread over- and under-representation of ribosome footprints can dominate local footprint densities and skew estimates of elongation rates by up to five fold. To address these biases and uncover true patterns of translation, we present choros, a computational method that models ribosome footprint distributions to provide bias-corrected footprint counts. choros uses negative binomial regression to accurately estimate two sets of parameters: (i) biological contributions from codon-specific translation elongation rates; and (ii) technical contributions from nuclease digestion and ligation efficiencies. We use these parameter estimates to generate bias correction factors that eliminate sequence artifacts. Applying choros to multiple ribosome profiling datasets, we are able to accurately quantify and attenuate ligation biases to provide more faithful measurements of ribosome distribution. We show that a pattern interpreted as pervasive ribosome pausing near the beginning of coding regions is likely to arise from technical biases. Incorporating choros into standard analysis pipelines will improve biological discovery from measurements of translation.