Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Unsaturated Flow on Salt Distributions in Tidally Influenced Coastal Unconfined Aquifers

Unsaturated flow influences both the seawater extent under steady‐state conditions and the propagation of tides in coastal aquifers. However, its effects on salt distributions in tidally influenced coastal aquifers are little investigated. The present study used numerical simulations and data from laboratory experiments to analyze the effects of unsaturated flow on density‐dependent solute transport in coastal unconfined aquifers. The effects of the inland boundary condition (i.e., constant‐head or constant‐flux) were tested. Compared to a stable sea level, the results show that unsaturated flow has a more pronounced influence on salt distributions in coastal unconfined aquifers when tides are considered, regardless of the type of inland boundary condition. Neglect of unsaturated flow effects leads to expansion of the upper saline plume (USP), shrinkage of the saltwater wedge (seaward movement of saltwater wedge), and overestimation of water and salt exchange across the aquifer‐ocean interface. This is caused by a lower head in the nearshore area during high‐tide periods with the unsaturated zone effects removed. Thus, without the unsaturated zone, stronger head gradients within the nearshore aquifer occur at high tide, leading to stronger tidally driven seawater infiltration and hence a larger USP. Counterintuitively, ignoring unsaturated flow effects leads to greater average inland head over a tidal period, which shifts the saltwater wedge seaward. It is concluded that unsaturated zone effects should not be neglected for modeling tide‐affected seawater intrusion, especially if quantification of near‐shore conditions is important.
Gravel‐Sand Transition of the Yangtze River: Human Disturbances, Migration Processes, and Controlling Factors

Despite abundant studies on gravel‐sand transitions (GSTs), GST origin and migration in large alluvial channels characterized by significant variations in width, numerous tributary (or distributary) streams, and frequent human disturbances remain difficult to explain. Here, we take the Yangtze River as an example and use field observations and numerical modeling to make progress toward addressing GST origin and migration. The results show that the Yangtze River exhibits a non‐abrupt GST approximately 60 km long. Within the GST and the adjacent area, there are two dramatic decreases in shear stress; the upstream one induces the settlement of sand from suspension, explaining the emergence of the Yangtze River GST, whereas the downstream one induces general cessation of gravel movement. However, the deposited gravel was mostly overwhelmed by sand. We argue that these changes in shear stress in the Yangtze River depended primarily on the combined effects of width variability and distributary systems. Since 1970, the Jingjiang Meander Cut‐off, the Gezhouba Dam, and the Three Gorges Dam (TGD) have been completed in succession, repeatedly altering the flow‐sediment regime within the GST. However, the GST position remained unchanged until the TGD began operation in 2003. The stability of the GST was primarily ascribed to the sufficient upstream sand supply (grain size <0.5 mm), the resistant lithologies upstream of Zhicheng, and the Jingjiang Great Levees constraints.
Memory‐Efficient GPU Volume Path Tracing of AMR Data Using the Dual Mesh

A common way to render cell‐centric adaptive mesh refinement (AMR) data is to compute the dual mesh and visualize that with a standard unstructured element renderer. While the dual mesh provides a high‐quality interpolator, the memory requirements of the dual mesh data structure are significantly higher than those of the original grid, which prevents rendering very large data sets. We introduce a GPU‐friendly data structure and a clustering algorithm that allow for efficient AMR dual mesh rendering with a competitive memory footprint. Fundamentally, any off‐the‐shelf unstructured element renderer running on GPUs could be extended to support our data structure just by adding a gridlet element type in addition to the standard tetrahedra, pyramids, wedges, and hexahedra supported by default. We integrated the data structure into a volumetric path tracer to compare it to various state‐of‐the‐art unstructured element sampling methods. We show that our data structure easily competes with these methods in terms of rendering performance, but is much more memory‐efficient.
The unique microbial diversity, community composition and networks of Pacific Islander endocervical and vaginal microbiomes in the presence or absence of Chlamydia trachomatis infection using metagenomic shotgun sequencing

Background Pacific Islanders are a vulnerable population with a high prevalence of Chlamydia trachomatis (Ct) sexually transmitted infections (STIs) and remain underrepresented in research. Here, 258 vaginal and 92 paired endocervical samples from women of diverse ethnicities in Fiji were evaluated using metagenomics to characterize microbial relative abundance, composition and networks including associations with Neisseria gonorrhoeae, human papilloma virus (HPV), Mycoplasma genitalium, Candida and bacterial vaginosis (BV). Results Pacific Islander ethnicities and age <25 years were significantly associated with Ct infection. Using VALENCIA, a sub-community state type (subCST) classifier, 93 (36.04%) vaginal and 38 (41.30%) endocervical microbiomes did not match reference subCSTs. Four unique subCSTs were developed to better classify Pacific Islander microbiomes: IV-D0, dominated by Gardnerella vaginalis; IV-D1, high/moderate G. vaginalis relative abundance with Prevotella spp. ; IV-D2, high/moderate G. vaginalis with Lactobacillus iners; and IV-E, moderate Prevotella spp. Ct positive endocervical and paired vaginal microbiomes were significantly more likely to have differential species relative abundance (81.58%) than Ct negative pairs (35.84%; AOR: 7.93; 95% CI: 2.93-21.93; P<0.0001). A significantly higher alpha diversity was found for iTaukei ethnicity, all subCST-IV types, BV, and Ct for vaginal microbiomes. For endocervical microbiomes, higher diversity was significant for subCST-IV-A, subCST-IV-D1, and subCST-IV-E, and high-risk HPV types. Overall, there was a significantly higher diversity for the endocervix in paired microbiomes. Vaginal microbiomes showed significant divergence in community composition as above and for Candida. Endocervical composition varied significantly by subCST type and Ct status. Gut and BV-associated bacterial clusters were present in Ct positive and negative paired endocervical and vaginal microbiome networks but were smaller with fewer bacterial and no Lactobacillus spp. interactions in Ct-infected endocervical networks where G. vaginalis generated polymicrobial biofilms along with Ct likely influence pathogenicity. Conclusions Fijian endocervical and vaginal microbiomes represent divergent microbial abundance and compositions, especially for Pacific Islander ethnicities, with distinct subCSTs compared to other global populations. The higher microbial diversity of the endocervix with prevalent G. vaginalis, L. iners and Prevotella spp. suggest that these microbiomes/networks may predispose to and/or promote chlamydial and HPV pathogenesis. Prospective studies are needed to further define causal associations to develop successful interventions.
Cross-linking mass spectrometric analysis of the endogenous TREX complex from Saccharomyces cerevisiae

The conserved TREX complex has multiple functions in gene expression such as transcription elongation, 3’ end processing, mRNP assembly and nuclear mRNA export as well as the maintenance of genomic stability. In S. cerevisiae, TREX is composed of the pentameric THO complex, the DEAD-box RNA helicase Sub2, the nuclear mRNA export adaptor Yra1 and the SR-like proteins Gbp2 and Hrb1. Here, we present the structural analysis of the endogenous TREX complex of S. cerevisiae purified from its native environment. To this end, we used cross-linking mass spectrometry to gain structural information on regions of the complex that are not accessible to classical structural biology techniques. We also used negative-stain electron microscopy to investigate the organization of the cross-linked complex used for XL-MS by comparing our endogenous TREX complex with recently published structural models of recombinant THO-Sub2 complexes. According to our analysis, the endogenous yeast TREX complex preferentially assembles into a dimer. The overall structures of the recombinant yeast THO-Sub2 complexes strongly resemble the structural conformation of the monomers and the dimer interface of the endogenous TREX complex.
A CDC-42-regulated actin network is necessary for nuclear migration through constricted spaces in C. elegans

Successful nuclear migration through constricted spaces between cells or in the extracellular matrix relies on the ability of the nucleus to deform. Little is known of how this takes place in vivo. We study confined nuclear migration in Caenorhabditis elegans larval P-cells, which is mediated by the LINC complex to pull nuclei towards the minus ends of microtubules. Null mutations of LINC component unc-84 lead to a temperature-dependent phenotype, suggesting a parallel pathway for P-cell nuclear migration. A forward genetic screen for enhancers of unc-84 identified cgef-1 (CDC-42 Guanine Nucleotide Exchange Factor). Knockdown of CDC-42 in the absence of the LINC complex led to a P-cell nuclear migration defect. Expression of constitutively active CDC-42 rescued nuclear migration in cgef-1; unc-84 double mutants suggesting CDC-42 functions downstream of CGEF-1. The Arp2/3 complex and non-muscle myosin II (NMY-2) were also found to function parallel to the LINC pathway. In our model, CGEF-1 activates CDC-42, induces actin polymerization through the Arp2/3 complex to deform the nucleus during nuclear migration while NMY-2 helps push the nucleus through confined spaces.
Fractional Hitting Sets for Efficient and Lightweight Genomic Data Sketching

The exponential increase in publicly available sequencing data and genomic resources necessitates the development of highly efficient methods for data processing and analysis. Locality-sensitive hashing techniques have successfully transformed large datasets into smaller, more manageable sketches while maintaining comparability using metrics such as Jaccard and containment indices. However, fixed-size sketches encounter difficulties when applied to divergent datasets. Scalable sketching methods, such as Sourmash, provide valuable solutions but still lack resourceefficient, tailored indexing. Our objective is to create lighter sketches with comparable results while enhancing efficiency. We introduce the concept of Fractional Hitting Sets, a generalization of Universal Hitting Sets, which uniformly cover a specified fraction of the k-mer space. In theory and practice, we demonstrate the feasibility of achieving such coverage with simple but highly efficient schemes. By encoding the covered k-mers as super-k-mers, we provide a space-efficient exact representation that also enables optimized comparisons. Our novel tool, SuperSampler, implements this scheme, and experimental results with real bacterial collections closely match our theoretical findings. In comparison to Sourmash, SuperSampler achieves similar outcomes while utilizing an order of magnitude less space and memory and operating several times faster. This highlights the potential of our approach in addressing the challenges presented by the ever-expanding landscape of genomic data. SuperSampler is an open-source software and can be accessed at github.com/TimRouze/supersampler. The data required to reproduce the results presented in this manuscript is available at github.com/TimRouze/Expe_SPSP.
Rarefaction is currently the best approach to control for uneven sequencing effort in amplicon sequence analyses

Considering it is common to find as much as 100-fold variation in the number of 16S rRNA gene sequences found across samples in a study, researchers need to control for the effect of uneven sequencing effort. How to do this has become a contentious question. Some have argued that rarefying or rarefaction is “inadmissible” because it omits valid data. A number of alternative approaches have been developed to normalize and rescale the data that purport to be invariant to the number of observations. I generated community distributions based on 12 published datasets where I was able to assess the ability of multiple methods to control for uneven sequencing effort. Rarefaction was the only method that could control for variation in uneven sequencing effort when measuring commonly used alpha and beta diversity metrics. Next, I compared the false detection rate and power to detect true differences between simulated communities with a known effect size using various alpha and beta diversity metrics. Although all methods of controlling for uneven sequencing effort had an acceptable false detection rate when samples were randomly assigned to two treatment groups, rarefaction was consistently able to control for differences in sequencing effort when sequencing depth was confounded with treatment group. Finally, the statistical power to detect differences in alpha and beta diversity metrics was consistently the highest when using rarefaction. These simulations underscore the importance of using rarefaction to normalize the number of sequences across samples in amplicon sequencing analyses. Importance Sequencing 16S rRNA gene fragments has become a fundamental tool for understanding the diversity of microbial communities and the factors that affect their diversity. Due to technical challenges, it is common to observe wide variation in the number of sequences that are collected from different samples within the same study. However, the diversity metrics used by microbial ecologists are sensitive to differences in sequencing effort. Therefore, tools are needed to control for the uneven levels of sequencing. This simulation-based analysis shows that despite a longstanding controversy, rarefaction is the most robust approach to control for uneven sequencing effort. The controversy started because of confusion over the definition of rarefaction and violation of assumptions that are made by methods that have been borrowed from other fields. Microbial ecologists should use rarefaction.
Improved algorithm of structure strategy in ontology matching

Similarity propagation is essential step for structure strategy.However,the existing algorithm of similarity propagation does not take a reasonable quantitative analysis for propagated value.To solve this problem,a new algorithm of similarity propagation is proposed which based on information content of concept,information content of concept is acquired by the context of ontology structure,and propagated value is adjusted by the value of information content of concept to obtain a more accuracy propagated value.Theoretical analysis and the results of experiment is shown that the improved algorithm is efficient.
Few-shot 3D Point Cloud Semantic Segmentation with Prototype Alignment

Semantic Segmentation for 3D point clouds has made great progress in recent years. Most existing approaches for 3D point cloud segmentation are fully supervised, and they require a large number of well-annotated data for training. The training data is cost and quite difficult to obtain. Moreover, these fully supervised approaches cannot segment new classes well that are unseen in the training process. Thus, Few-shot segmentation has been developed to mitigate these limitations by learning to perform segment from a few labeled examples. In this paper, we propose a method to more adequately utilize information of query set and support set to promote performance of semantic segmentation for 3D point clouds. Specifically, we first extract support and query features and generate multiple prototypes to map the distribution of point clouds. Then we apply a transductive label propagation method to exploit the relations between labeled multi-prototypes and unlabeled points, and between pairs of unlabeled points. Finally, we utilize query points and predicted query masks to perform segmentation for support points. Our proposed method shows improvements for specific classes on S3DIS dataset compared to baselines in 2/3-way 1-shot point cloud semantic segmentation.
Building term hierarchies using graph-based clustering

Classical tasks of a librarian, such as screening and categorizing new documents based on their content, are increasingly replaced by search engines or through the use of cataloging software. A first overview of a corpus topical orientation can be achieved by combining graph-based search engines and clustering methods. Existing classical clustering methods, however, often require an a priori specification of the desired number of clusters to be output and do not consider term relationships in graphs, which is deficient from a practical point of view. Therefore, fully unsupervised graph-based clustering approaches at the term level offer new possibilities that mitigate these shortcomings. Within this work, a set of novel graph-based clustering algorithms have been developed. The hierarchical clustering algorithm (HCA) forms term hierarchies by iteratively isolating nodes of a given co-occurrence graph based on the evaluation of the edge weight between the nodes. Based on the co-occurrence graph inherent relationships of terms, a new graph is built agglomerative forming individual term clusters of related terms. The feasibility of the outlined methods for text analysis is shown.
A case study in designing trustworthy interactions: implications for socially assistive robotics

This work is a case study in applying recent, high-level ethical guidelines, specifically concerning transparency and anthropomorphisation, to Human-Robot Interaction (HRI) design practice for a real-world Socially Assistive Robot (SAR) application. We utilize an online study to investigate how the perception and efficacy of SARs might be influenced by this design practice, examining how robot utterances and display manipulations influence perceptions of the robot and the medical recommendations it gives. Our results suggest that applying transparency policies can improve the SAR's effectiveness without harming its perceived anthropomorphism. However, our objective measures suggest participant understanding of the robot's decision-making process remained low across conditions. Furthermore, verbal anthropomorphisation does not seem to affect the perception or efficacy of the robot.
The impact of TP53 activation and apoptosis in primary hereditary microcephaly

Autosomal recessive primary microcephaly (MCPH) is a constellation of disorders that share significant brain size reduction and mild to moderate intellectual disability, which may be accompanied by a large variety of more invalidating clinical signs. Extensive neural progenitor cells (NPC) proliferation and differentiation are essential to determine brain final size. Accordingly, the 30 MCPH loci mapped so far (MCPH1-MCPH30) encode for proteins involved in microtubule and spindle organization, centriole biogenesis, nuclear envelope, DNA replication and repair, underscoring that a wide variety of cellular processes is required for sustaining NPC expansion during development. Current models propose that altered balance between symmetric and asymmetric division, as well as premature differentiation, are the main mechanisms leading to MCPH. Although studies of cellular alterations in microcephaly models have constantly shown the co-existence of high DNA damage and apoptosis levels, these mechanisms are less considered as primary factors. In this review we highlight how the molecular and cellular events produced by mutation of the majority of MCPH genes may converge on apoptotic death of NPCs and neurons, via TP53 activation. We propose that these mechanisms should be more carefully considered in the alterations of the sophisticated equilibrium between proliferation, differentiation and death produced by MCPH gene mutations. In consideration of the potential druggability of cell apoptotic pathways, a better understanding of their role in MCPH may significantly facilitate the development of translational approaches.
What defines a great surgeon? A survey study confronting perspectives

Background The definition of a great surgeon is usually reported by surgeons themselves. The objective of the study was to define a multifaceted definition of a great surgeon, by confronting patients', healthcare workers', and surgeons' perspectives. Study design An online open-ended questionnaire was created to identify three qualities and three shortcomings defining a great surgeon. Age, gender, and profession of respondents were collected. Responses with a similar meaning were combined into word groups and labeled within four themes: human qualities, technical surgical skills (TSS), non-technical skills (NTS), and knowledge. Multivariate analyses were conducted between themes and respondent characteristics. Results Four thousand seven hundred and sixty qualities and 4,374 shortcomings were obtained from 1,620 respondents including 385 surgeons, 291 patients, 565 operating theater (OT) health professionals, and 379 non-OT health professionals. The main three qualities were dexterity (54% of respondents), meticulousness (18%), and empathy (18%). There was no significant difference between professional categories for TSS. Compared with surgeons, non-OT health professionals and patients put more emphasis on human qualities (29 vs. 39% and 42%, respectively, p < .001). OT health professionals referred more to NTS than surgeons (35 vs. 22%, p < 0.001). Knowledge was more important for surgeons (19%) than for all other professional categories (p < 0.001). Conclusions This survey illustrates the multifaceted definition of a great surgeon. Even if dexterity is a major quality, human qualities are of paramount importance. Knowledge seems to be underestimated by non-surgeons, although it essential to understand the disease and preparing the patient and OT team for the procedure.
Towards Measuring the Cognitive Loads of Different Dialog Acts through Dependency Distance

Although relevance theory has called attention to the analysis of cognitive aspects of pragmatic phenomena, few investigations have explored whether distinct dialog acts (DAs) require different degrees of cognitive loads, not to mention examining them with objective indices. The current paper then adopted a syntactic cognitive index – dependency distance – to analyze whether distinct categories of DAs differ in cognitive loads. Specifically, this paper adopted mean dependency distance (MDD), mean hierarchical distance (MHD), and normalized dependency distance (NDD) to examine the language data in the Switchboard Dialog Act Corpus (SwDA). The results showed that MDD, MHD and NDD are all effective in differentiating four genres of DAs – Information Request (IR), Agreement (Ag), Understanding (Un), and Answering (An), among which IR has the highest values of the three indicators, Un has the lowest, and Ag and An are somewhere in between. A follow-up ANOVA further corroborated that the forward DA (IR) significantly differed from the backward ones (Ag, Un, and An). With these results obtained, this paper may shed light on the relationship between DAs and cognitive resources, providing a new perspective for the research under the paradigm of pragmatics.