ethicalabs/Research-Intent-Collab huggingface dataset:
Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals. [             Journal of Gerontological Nursing, 43             (7), 53–62.]
The Lacunae in the Rome Statute for the Exercise of Universal Jurisdiction by the International Criminal Court

The issue of “universal jurisdiction” reveals a legal chasm in the applicability of the Rome Statute and have plagued the International Criminal Court with criticisms for not having the right to exercise such jurisdiction over international crimes. Universal jurisdiction can be simply defined as “the exercise of jurisdiction regardless of any other acknowledged jurisdictional relationship to a State party to the Statute”. This question of universal jurisdiction becomes especially important when currently, the Court is recently struggling to exercise jurisdiction over the crimes committed in the Philippines, in the context of their government’s "War on Drugs" campaign, due to the withdrawal of the country as a State Party to the Statute on March 17, 2019. This article provides an insight into such lacunae of the Statute in terms of adequately preparing the ICC for exercising its jurisdiction in such situations or cases.
The Role of Organizational Culture as a Mediator Between the Influence of Motivation, Leadership, and Supply Chain Management on Employee Green Behavior

This research is motivated by the important role of companies in the context of globalization, where dependence between countries is increasing. The company is a vital element in meeting the needs of the global community. The main objective of this study is to analyze how organizational culture mediates the relationship between motivation, leadership, and supply chain management to employees' green behavior. The population of this study was employees of PT. X which has a total of 592 employees, the sampling technique used is simple random sampling so that a sample of 86 employees from PT. X. The research method used is quantitative research by applying Partial Least Squares (PLS) as a data analysis tool. The results showed that motivation and leadership had a significant and positive influence on employees' green behavior. Motivation also has a significant positive influence on employees' green behavior through mediating organizational culture. In addition, organizational culture also has a significant effect on the green behavior of employees at PT. X. in Indonesia. The results of this study have important implications in the context of human resource management that cares for the environment. These results can assist companies in developing strategies to improve employees' green behavior and achieve sustainability goals.
Diffusion Models For Multi-Modal Generative Modeling

Published as a conference paper at ICLR 2024
Effectiveness of Marine Protected Areas in the Philippines for Biodiversity Conservation

Abstract:                                             Quantifying the extent to which existing reserves meet conservation objectives and identifying gaps in coverage are vital to developing systematic protected‐area networks. Despite widespread recognition of the Philippines as a global priority for marine conservation, limited work has been undertaken to evaluate the conservation effectiveness of existing marine protected areas (MPAs). Targets for MPA coverage in the Philippines have been specified in the 1998 Fisheries Code legislation, which calls for 15% of coastal municipal waters (within 15 km of the coastline) to be protected within no‐take MPAs, and the Philippine Marine Sanctuary Strategy (2004), which aims to protect 10% of coral reef area in no‐take MPAs by 2020. We used a newly compiled database of nearly 1000 MPAs to measure progress toward these targets. We evaluated conservation effectiveness of MPAs in two ways. First, we determined the degree to which marine bioregions and conservation priority areas are represented within existing MPAs. Second, we assessed the size and spacing patterns of reserves in terms of best‐practice recommendations. We found that the current extent and distribution of MPAs does not adequately represent biodiversity. At present just 0.5% of municipal waters and 2.7–3.4% of coral reef area in the Philippines are protected in no‐take MPAs. Moreover, 85% of no‐take area is in just two sites; 90% of MPAs are &lt;1 km                       2                       . Nevertheless, distances between existing MPAs should ensure larval connectivity between them, providing opportunities to develop regional‐scale MPA networks. Despite the considerable success of community‐based approaches to MPA implementation in the Philippines, this strategy will not be sufficient to meet conservation targets, even under a best‐case scenario for future MPA establishment. We recommend that implementation of community‐based MPAs be supplemented by designation of additional large no‐take areas specifically located to address conservation targets.
Test Paper 4

Multi-model test.
Target RNA modification for epigenetic drug repositioning in neuroblastoma: computational omics proximity between repurposing drug and disease

RNA modifications modulate most steps of gene expression. However, little is known about its role in neuroblastoma (NBL) and the inhibitors targeting it. We analyzed the RNA-seq (n=122) and CNV data (n=78) from NBL patients in Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The NBL sub-clusters (cluster1/2) were identified via consensus clustering for expression of RNA modification regulators (RNA-MRs). Cox regression, principle component analysis and chi-square analysis were used to compare differences of survival, transcriptome, and clinicopathology between clusters. Cluster1 showed significantly poor prognosis, of which RNA-MRs' expression and CNV alteration were closely related to pathologic stage. RNA-MRs and functional related prognostic genes were obtained using spearman correlation analysis, and queried in CMap and L1000 FWD database to obtain 88 inhibitors. The effects of 5 inhibitors on RNA-MRs were confirmed in SH-SY5Y cells. The RNA-MRs exhibited two complementary regulation functions: one conducted by TET2 and related to translation and glycolysis; another conducted by ALYREF, NSUN2 and ADARB1 and related to cell cycle and DNA repair. The perturbed proteomic profile of HDAC inhibitors was different from that of others, thus drug combination overcame drug resistance and was potential for NBL therapy with RNA-MRs as therapeutic targets.
How reliable are annotations via crowdsourcing

The creation of golden standard datasets is a costly business. Optimally more than one judgment per document is obtained to ensure a high quality on annotations. In this context, we explore how much annotations from experts differ from each other, how different sets of annotations influence the ranking of systems and if these annotations can be obtained with a crowdsourcing approach. This study is applied to annotations of images with multiple concepts. A subset of the images employed in the latest ImageCLEF Photo Annotation competition was manually annotated by expert annotators and non-experts with Mechanical Turk. The inter-annotator agreement is computed at an image-based and concept-based level using majority vote, accuracy and kappa statistics. Further, the Kendall τ and Kolmogorov-Smirnov correlation test is used to compare the ranking of systems regarding different ground-truths and different evaluation measures in a benchmark scenario. Results show that while the agreement between experts and non-experts varies depending on the measure used, its influence on the ranked lists of the systems is rather small. To sum up, the majority vote applied to generate one annotation set out of several opinions, is able to filter noisy judgments of non-experts to some extent. The resulting annotation set is of comparable quality to the annotations of experts.
The Effect of Helicobacter pylori Eradication on Human Microbiota: Metagenome Analysis of the Human Gut Microbiome

A total of 152 stool samples from 76 patients with symptoms of gastrointestinal diseases have been analyzed using metagenomic shotgun sequencing technology to assess the effect of Helicobacter pylori eradication therapy on Bifidobacterium, Lactobacillus, Escherichia, and Clostridium genera. The relative abundance of bacteria representing these genera in the intestinal microflora of patients before and after antibiotic therapy has been evaluated. It has been shown that the therapy did not have any critical effect in the majority of cases on the number of Lactobacillus, Escherichia and Clostridium genera in the microbial community. Their abundance varied within 0.5% in 76.5%, 51.3%, and 55.2% of patients, respectively. The Bifidobacterium genus has been found to be more susceptible to antibiotics (their number decreased significantly in 60.5% of cases). However, 9.2% of patients have shown the opposite effect. Thus, the obtained data demonstrate that Helicobacter pylori eradication therapy does not have uniform effects on the key members of human intestinal microbiota. This fact should be taken into account when predicting the risks of side effects of antibiotics.
Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters for Glycosaminoglycans via Ab Initio Molecular Dynamics Simulations

Abstract                                    Glycosaminoglycans (GAGs) are negatively charged polysaccharides found on cell surfaces, where they regulate transport pathways of foreign molecules toward the cell. The structural and functional diversity of GAGs is largely attributed to varied sulfa-tion patterns along the polymer chains, which makes understanding their molecular recognition mechanisms crucial. Molecular dynamics (MD) simulations, with their un-matched microscopic perspective, have the potential to be a reference tool for exploring the patterns responsible for biologically relevant interactions. However, the capability of molecular dynamics models (                   i.e.                   , force fields) used in biosimulations to accurately capture sulfation-specific interactions is not well established. In this work, we evalu-ate the performance of molecular dynamics force fields for sulfated GAGs by studying ion pairing of Ca                   2+                   to sulfated moieties — N-methylsulfamate and methylsulfate — that resemble N- and O-sulfation found in GAGs, respectively. We tested nonpolariz-able (CHARMM36 and GLYCAM06), explicitly polarizable (Drude and AMOEBA), and implicitly polarizable through charge scaling (prosECCo75 and GLYCAM-ECC75) force fields. The Ca–sulfamate/sulfate interaction free energy profiles obtained with the tested force fields were compared against reference ab initio molecular dynamics (AIMD) simulations. AIMD reveals that the preferential Ca                   2+                   binding mode to sul-fated GAG groups is solvent-shared pairing, and only the charge-scaled models agree satisfactorily with the AIMD data. All other force fields exhibit poorer performance, sometimes even qualitatively. Surprisingly, even explicitly polarizable force fields dis-play a notable shortfall in their performance, attributed to difficulties in their optimiza-tion and possible inherent limitations in depicting high-charge-density ion interactions accurately. Finally, the underperforming force fields lead to unrealistic aggregation of sulfated saccharides, qualitatively distorting our understanding of the soft glycocalyx environment. Our results highlight the importance of accurately treating electronic polarization in MD simulations of sulfated GAGs and caution against over-reliance on currently available models without thorough validation and optimization.
Relation Between Imaging Microfeatures of Artificial Intelligence-assisted Diagnosis System and Prognosis of Lung Adenocarcinomas Presented as Ground-glass Nodules

Objective To investigate the relation between the imaging microfeatures of AI-assisted diagnosis system and the prognosis of lung adenocarcinomas presented as ground-glass nodules (GGN). Methods We retrospectively analyzed CT data of 162 patients with lung adenocarcinomas presented as GGN. According to different imaging characteristics, the patients were divided into pure ground glass nodules (PGGN) group and mixed ground glass nodules (MGGN) group. The AI-assisted diagnosis system was used to extract their imaging microfeatures, and their relation with the prognosis of the patients was analyzed. Results The five-year OS and RFS were 89.7% and 88.5% in PGGN group, and 81.0% and 79.0% in MGGN group (χ2=6.289/7.255, P < 0.05). Multivariate Cox regression showed that imaging microfeatures such as microvascular cluster (P < 0.001), standard nodule volume (P=0.013) and nodule length (P < 0.001) were independent risk factors for OS, meanwhile, imaging microfeatures such as microvascular cluster (P < 0.001), standard nodule volume (P=0.017), nodule length (P=0.005), nodule central density (P=0.038) and lymph node metastasis (P < 0.001) were independent risk factors for RFS. Conclusion The AI-assisted diagnosis system can effectively predict the prognosis of lung adenocarcinomas presented as GGN, and it also has a certain reference value for the clinical precision diagnosis and treatment of GGN and the prevention and treatment of early lung cancer.
ProteinShake: Building datasets and benchmarks for deep learning on protein structures

We present ProteinShake, a Python software package that simplifies dataset creation and model evaluation for deep learning on protein structures. Users can create custom datasets or load an extensive set of pre-processed datasets from biological data repositories such as the Protein Data Bank (PDB) and AlphaFoldDB. Each dataset is associated with prediction tasks and evaluation functions covering a broad array of biological challenges. A benchmark on these tasks shows that pre-training almost always improves performance, the optimal data modality (graphs, voxel grids, or point clouds) is task-dependent, and models struggle to generalize to new structures. ProteinShake makes protein structure data easily accessible and comparison among models straightforward, providing challenging benchmark settings with real-world implications. ProteinShake is available at https://proteinshake.ai.
Structure and electrochemistry of lithiated transition metal (Mn, Fe, Ni) nitrides as materials for negative electrode of lithium ion battery

Structure et électrochimie des nitrures de métaux de transition (Mn, Fe, Ni) lithiés comme matériaux d'électrode négative de batterie lithium ion                 Dans le but de trouver une alternative performante de matériau actif d’électrode négative pour accumulateur Li-ion à haute puissance, nous avons étudié la famille des nitrures de métaux de transition lithiés dans ce travail. La synthèse, la structure, les propriétés électrochimies des 3 nitrures, Li7MnN4, Li3FeN2 et Li2.0Ni0.67N font l’objet de ce travail de thèse.Les paramètres clés de la synthèse de Li7MnN4 (LMN), notamment ceux qui influencent la morphologie du composé sont identifiés et un protocole de synthèse optimisé est proposé. Ce protocole nous permet d’avoir un Li7MnN4 qui donne les meilleures performances électrochimiques de la littérature pour un composé d’insertion comme négative de batterie Li-ion, différente du graphite. Les performances de LMN excèdent fortement celle du matériau de référence Li4Ti5O12. Une cellule complète avec LMN sous sa forme délithiée avec LiNi1/3Mn1/3Co1/3O2 (NMC) à la positive a été construite. La faisabilité de cette cellule complète a été mis en évidence et le point crucial de l’équilibrage des capacités des deux électrodes a été étudié. Afin de préparer la forme délithiée de LMN, plusieurs oxydants et un protocole de delithiation chimique ont été proposés. Une étude structurale pour les modes vibrationnels de LMN a été effectué en combinant données expérimentales et calculs de DFT. De façon similaire, les paramètres clés de la synthèse de Li3FeN2 (LFN) ont été étudiés. Une instabilité thermique a été mise en évidence. Le LFN optimisé présente une bonne tenue en cyclage, ce qui montre la possibilité de l’utiliser comme matériau d’électrode négative. Le broyage mécanique impacte la structure de LFN sans amélioration des performances. La stabilité de Fe4+ avec l’électrolyte est discutée. Les paramètres cinétiques de Li2.0Ni0.67N (LNN) ont été étudiés par spectroscopie d’impédance complexe. Une simulation avec un circuit équivalent permet d’interpréter les résultats. La SEI de LNN s’avère très stable en cours de cyclage. La résistance de transfert de charge décroît avec le taux de lithium dans le LNN tandis que le coefficient de diffusion du lithium reste stable quelques soit le taux de lithium. L’énergie d’activation est donnée pour ce matériau.
Data Science, Learning by Latent Structures, and Knowledge Discovery

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
A Comparative Analysis of Implementing the Right to Water and Sanitation in South Africa and Türkiye in the Scope of Sen’s Capability Approach

South Africa and Türkiye are two emerging markets that have witnessed significant migration from rural to urban areas over the past 50 years. A similar challenge in both countries is the growing demand for water, which increasingly exceeds supply, primarily due to climate change and expanding urban populations. While South Africa is regarded as a pioneer in the judicial interpretation of socio-economic rights, there is work to be done as far as advancing the implementation of the right to water. Meanwhile, Türkiye has a draft water law presently undergoing deliberations that draws lessons from South Africa and Brazil. However, further efforts are needed to establish a clear legislative framework that protects the right to water. This article aims to provide a comparative analysis of the law and policy in South Africa and Türkiye, while exploring their connection to the capability approach developed by Amartya Sen. The article will first look at South Africa’s specific position, then explore Türkiye’s framework. Finally, it will present a cross-country comparison of their approaches and offer recommendations for advancing the right to water in both nations. The main findings of the article suggest that, given the challenges of climate change and increasing urban populations, South Africa must learn from Türkiye in advancing the realisation of the right to water. This approach also contributes to expanding people’s freedoms in line with the principles of the capability approach.
Figure 4 from Blood-Based Genomic Alteration Signature for Predicting Progression-Free Survival in &lt;i&gt;De Novo&lt;/i&gt; Metastatic Hormone-Sensitive Prostate Cancer: A Real-World Study

&lt;p&gt;Internal validation of the b.TRPC model and comparison with ctDNA%. &lt;b&gt;A&lt;/b&gt; and &lt;b&gt;B,&lt;/b&gt; ROC curves comparing the predictive performance of b.TRPC and ctDNA% for 0.5-, 1-, and 2-year CRPC-free survival. &lt;b&gt;C&lt;/b&gt; and &lt;b&gt;D,&lt;/b&gt; Calibration plots showing the agreement between predicted and observed survival probabilities for b.TRPC and ctDNA%. &lt;b&gt;E,&lt;/b&gt; C-index values demonstrating the superior prognostic accuracy of b.TRPC compared with ctDNA%. &lt;b&gt;F–H,&lt;/b&gt; DCA illustrating the net clinical benefit of b.TRPC across different time points. FPR, false positive rate; TPR, true positive rate.&lt;/p&gt;
A Parametric and Feasibility Study for Data Sampling of the Dynamic Mode Decomposition--Range, Resolution, and Universal Convergence States

Scientific research and engineering practice often require the modeling and decomposition of nonlinear systems. The Dynamic Mode Decomposition (DMD) is a novel Koopman-based technique that effectively dissects high-dimensional nonlinear systems into periodically distinct constituents on reduced-order subspaces. As a novel mathematical hatchling, the DMD bears vast potentials yet an equal degree of unknown. This serial effort investigates the nuances of DMD sampling with an engineering-oriented emphasis. This Part I aimed at elucidating how sampling range and resolution affect the convergence of DMD modes. We employed the most classical nonlinear system in fluid mechanics as the test subject--the turbulent free-shear flow over a prism--for optimal pertinency. We numerically simulated the flow by the dynamic-stress Large-Eddies Simulation with Near-Wall Resolution. With the large-quantity, high-fidelity data, we parametrized and identified four global convergence states: Initialization, Transition, Stabilization, and Divergence with increasing sampling range. Results showed that the Stabilization is the optimal state for modal convergence, in which DMD output becomes independent of the sampling range. The Initialization state also yields sufficient accuracy for most system reconstruction tasks. Moreover, defying popular beliefs, over-sampling causes algorithmic instability: as the temporal dimension, n, approaches and transcends the spatial dimension, m (i.e., m < n), the output diverges and becomes meaningless. Additionally, the convergence of the sampling resolution depends on the mode-specific dynamics, such that the resolution of 15 frames per cycle for target activities is suggested for most engineering implementations. Finally, a bi-parametric study revealed that the convergence of the sampling range and resolution are mutually independent.