ethicalabs/Research-Intent-Collab huggingface dataset:
Low confidence levels with the robotic platform among senior surgical residents: simulation training is needed

Acquisition of robotic surgical skills by surgical residents is usually hindered by time pressure and financial imperatives. Robotic simulation training offers an attractive solution because it allows residents to learn in a safe, controlled, and standardized environment. We aimed to determine the confidence levels of senior surgical residents with the robotic platform, and how those levels were affected by simulation training. Twenty senior residents participated in a simulation course using perfused porcine tissue blocks to perform the following robotic procedures: Nissen fundoplication, Heller myotomy, sleeve gastrectomy, colectomy, and lobectomy. Procedural steps evaluated included port placements, docking process, suturing, using energy devices, and using staplers. Mean baseline confidence levels were low for all the surgical steps analyzed, and all these values significantly increased after the 3-day robotic training in the simulation center. A standardized formal robotic simulation program with realistic hands-on training should be incorporated in the general surgery residency curriculum.
Debatable Issues on Land Rights Protection of Indigenous Small-numbered Peoples of the North, Siberia and the Far East of the Russian Federation

Abstract                   The article presents the authors’ ideas concerning the legal nature of land rights of indigenous small-numbered peoples in Russia. It should be noted that land rights of indigenous small-numbered peoples are part of their special constitutional legal personality, an essential element of their legal status. On the basis of international acts on the rights of indigenous peoples, the opportunity to give indigenous small-numbered peoples of Russia their traditional land to use on the grounds of ownership is assessed as non-promising. The article scrutinises the system of land rights of indigenous small-numbered peoples that is established in Russia. The authors point to the imperfection of the legislation in this area, which may lead to violation of the rights of indigenous small-numbered peoples. It should be noted that one of the most important state guarantees is the right of indigenous small-numbered peoples to free and indefinite use of lands.
Deep Learning Explainability with Local Interpretable Model-Agnostic Explanations for Monkeypox Prediction

The accurate categorization of medical images is critical in facilitating clinical treatment and care. In recent studies, deep learning (DL) models have demonstrated tremendous possibility in image-based diagnosis, specifically in the areas of pneumonia detection, tumor cell identification, and COVID-19 diagnosis. It is challenging to identify Mpox (formerly known as monkeypox) on human skin due to the unavailability of a publicly available dataset of Mpox. In order to address this issue, authors have collected a dataset called “Monkeypox2022” and is made accessible to the public. The research community can find it on GitHub at this link: https://github.com/Angmo21720/data-set . The dataset was compiled using photographs sourced from various open-source and internet platforms, without any restrictions on their usage, including commercial purposes. In addition, the authors have made enhancements to the VGG16 model and conducted two experiments, Experiment 1 and Experiment 2, to evaluate its performance. Based on our research, it was discovered that the AUC score achieved by the model in Experiments 1 and 2 were 0.972 and 0.748, respectively, in identifying monkeypox patients. Local interpretable model-agnostic explanations (LIMEs) are utilized for analyzing the results of the model employed and uncovering the specific features on which various predictions were made by the model. This allows for a more comprehensive understanding of the factors that contribute to identifying a monkeypox infection.
Genetic discrimination in private insurance: global perspectives

In an era of personalized medicine rife with population databases and international consortia, genetic discrimination is once again moving to the forefront of the genetics policy debate. In North America and Europe, many countries have taken a political stance on the use of predictive genetic information by insurers. Asia is also becoming more conscious of the challenge raised by genetic discrimination. In this paper, we present data on the different policy options adopted to resolve the genetic and insurance dilemma in 47 different countries located in four world regions. Approaches varied according to legal traditions, the role insurance plays in each state, and the interplay between private and public health care systems. We conclude that a truly informed international debate on genetic discrimination in insurance should properly account for the limits of genetic predictive information and the social value of health and life insurance as perceived by the public.
The Public Interest Requirement in the Secondary Use of Health Data in Scientific Research: The Examples of Estonia and Finland

The General Data Protection Regulation (GDPR) foresees a flexible data processing regime for conducting scientific research with health data. This regime also enables extensive limitations on data subjects' rights to privacy and self-determination. Concern has been expressed that the notion of 'scientific research' may encompass conducting also profit-oriented commercial research that might not justify such limitations to data subjects' rights. Some authors have suggested a restriction on benefiting from the flexible scientific research regime: public interest should be set as a prerequisite for any scientific research employing health data without the data subject's consent. While the GDPR does not explicitly require that scientific research be in the public interest, it allows Member States to choose their policies. In light of this, the article examines the examples of Estonia and Finland to analyse whether national law should require the processing of health data in scientific research in the absence of the data subject's consent to be in the public interest. The article demonstrates on the basis of the two countries’ examples that it is possible to set a public interest standard without explicitly requiring the existence of a public interest via national legislation. Considering the future, the article also shows that, under the proposed European Health Data Space regulation, Member States may retain the public interest standard through the ethics-review requirement in their national law.
Hospital nurse shift length, patient‐centered care, and the perceived quality and patient safety

SummaryBackgroundThere is no clear evidence that can guide decision makers regarding the appropriate shift length in the hospitals in Malaysia. Further, there is no study that explored the value of patient‐centered care of nurses working longer shifts and its impact on the care outcomes.ObjectiveThe study aims to investigate the effect of the hospital nurse shift length and patient‐centered care on the perceived quality and safety of nurses in the medical‐surgical and multidisciplinary wards in Malaysia.MethodsA cross‐sectional survey has been conducted on 12 hospitals in Malaysia. Data have been collected via a questionnaire. A stratified sampling has been used. The Hayes macro regression analyses have been used to examine the mediating effects of patient‐centered care between the effect of working long shifts on the perceived quality and patient safety.ResultsThere is a significant mediation effect of patient‐centered care between the effect of shift length on the perceived quality (F = 42.90,P ˂ 0.001) and patient safety (F = 25.12,P ˂ 0.001).ConclusionPatient‐centered care mitigates the effect of the shift length on the care outcomes. The study provides an input for the policymakers that patient‐centered care and restructuring duty hours are important to provide high‐quality patient care.
ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models

This paper introduces ConceptMath, a bilingual (English and Chinese), fine-grained benchmark that evaluates concept-wise mathematical reasoning of Large Language Models (LLMs). Unlike traditional benchmarks that evaluate general mathematical reasoning with an average accuracy, ConceptMath systematically organizes math problems under a hierarchy of math concepts, so that mathematical reasoning can be evaluated at different granularity with concept-wise accuracies. Based on our ConcepthMath, we evaluate a broad range of LLMs, and we observe existing LLMs, though achieving high average accuracies on traditional benchmarks, exhibit significant performance variations across different math concepts and may even fail catastrophically on the most basic ones. Besides, we also introduce an efficient fine-tuning strategy to enhance the weaknesses of existing LLMs. Finally, we hope ConceptMath could guide the developers to understand the fine-grained mathematical abilities of their models and facilitate the growth of foundation models.
Gene Ontology: Pitfalls, Biases, Remedies

The Gene Ontology (GO) is a formidable resource but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices.
Fault-tree analysis considering latency of basic events

Severe accidents can occur even in advanced systems such as airplanes and nuclear power plants. In the accident analysis, most of the attention focuses on the active failure which initiates the occurrence of system failure, but the latent condition which allows the active failure to cause system failure must be considered. This paper proposes a simple method to deal with latent conditions in FTA (fault tree analysis) based on the detectability of basic events. In FTA analysis, the system failure occurs if all basic events in a minimal cut set occur, but all the event sequences leading to the occurrence of a minimal cut set do not always occur without their detection. Using the detectability index of a basic event, it is evaluated whether the critical state of a basic event is latent where its occurrence can cause the system failure. Based on the number/probability of critical states that can be detected by the detectability of a basic event, a new measure of its importance in contributing to the reduction of system failure is proposed. A simple illustrative example shows these properties.
A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data

Microbes are essentially yet convolutedly linked with human lives on the earth. They critically interfere in different physiological processes and thus influence overall health status. Studying microbial species is used to be constrained to those that can be cultured in the lab. But it excluded a huge portion of the microbiome that could not survive on lab conditions. In the past few years, the culture-independent metagenomic sequencing enabled us to explore the complex microbial community coexisting within and on us. Metagenomics has equipped us with new avenues of investigating the microbiome, from studying a single species to a complex community in a dynamic ecosystem. Thus, identifying the involved microbes and their genomes becomes one of the core tasks in metagenomic sequencing. Metagenome-assembled genomes are groups of contigs with similar sequence characteristics from de novo assembly and could represent the microbial genomes from metagenomic sequencing. In this paper, we reviewed a spectrum of tools for producing and annotating metagenome-assembled genomes from metagenomic sequencing data and discussed their technical and biological perspectives.
Predictions of water/oil interfacial tension at elevated temperatures and pressures: A molecular dynamics simulation study with biomolecular force fields

Abstract   The interfacial properties of water/oil mixtures is a topic of significant interest for the oil and gas and chemical industry, as they are required for performing process calculations. However, the reported data at high temperatures and pressures are scarce. The present study focuses on simulating the interfacial tension (IFT) of mixtures of water with i) toluene (water/toluene), ii) n-dodecane (water/n-dodecane) and iii) a 50:50 % wt toluene:n-dodecane mixture (water/toluene/n-dodecane), at 1.83 MPa and temperatures ranging from 383.15 to 443.15 K. Molecular Dynamics (MD) simulations with atomistic molecular models, developed primarily for biomolecular systems were employed. In the simulations performed, the effects of the water model and the scaling of interatomic interactions by introducing a binary interaction parameter,      k   i  j      , were assessed for the accurate reproduction of experimental data. The combination of the TIP4P/2005, SPC/E and TIP3P water models with the GAFF and Lipid14 force fields for toluene and n-dodecane respectively, coupled with appropriate binary interaction parameters,      k   i  j      , for the interaction of carbon with oxygen atoms were found to yield accurate results in the case of binary mixtures. For the water/toluene/n-dodecane mixture, all force field combinations tested resulted in overestimated IFT values for the whole range of state points examined. Our simulations show that these widely used force fields, originating from the world of biomolecular simulations, are suitable candidates in the study of binary water/oil mixtures. Nevertheless, the introduction of the      k   i  j       scaling parameter is not sufficient to allow the accurate reproduction of experimental IFT data for ternary water/oil/oil mixtures.
Exercise medicine and physical activity promotion: core curricula for US medical schools, residencies and sports medicine fellowships: developed by the American Medical Society for Sports Medicine and endorsed by the Canadian Academy of Sport and Exercise Medicine

Regular physical activity provides a variety of health benefits and is proven to treat and prevent several non-communicable diseases. Specifically, physical activity enhances muscular and osseous strength, improves cardiorespiratory fitness, and reduces the risk of hypertension, coronary heart disease, stroke, type 2 diabetes, mental health disorders, cognitive decline and several cancers. Despite these well-known benefits, physical activity promotion in clinical practice is underused due to insufficient training during medical education. Medical trainees in the USA receive relatively few hours of instruction in sports and exercise medicine (SEM). One reason for this shortage of instruction is a lack of curricular resources at each level of medical education. To address this need, the American Medical Society for Sports Medicine (AMSSM) assembled a group of SEM experts to develop curricular guidance for exercise medicine and physical activity promotion at the medical school, residency and sports medicine fellowship levels of training. After an evidence review of existing curricular examples, we performed a modified Delphi process to create curricula for medical students, residents and sports medicine fellows. Three training level-specific curricula emerged, each containing Domains, General Learning Areas, and Specific Learning Areas; options for additional training and suggestions for assessment and evaluation were also provided. Review and comment on the initial curricula were conducted by three groups: a second set of experts in exercise medicine and physical activity promotion, sports medicine fellowship directors representing a variety of fellowship settings and the AMSSM Board of Directors. The final curricula for each training level were prepared based on input from the review groups. We believe enhanced medical education will enable clinicians to better integrate exercise medicine and physical activity promotion in their clinical practice and result in healthier, more physically active patients.
The Concept of Exhumed Analogue for Characterization of High-Energy Geothermal Reservoir: an Example from Les Saintes Island (Guadeloupe Archipelago, Lesser Antilles) and Consequences for Exploration

The recognition of a fossil equivalent of the active geothermal system of the Basse-Terre Island in Guadeloupe archipelago (Lesser Antilles arc) in Terre-de-Haut Island (Les Saintes archipelago) allow us to better constrain the structure, the mineralogy and the petrological characters of the deep parts of an active geothermal reservoir. First, we demonstrate the occurrence, in Terre-de-Haut Island, of an exhumed analogue of the deeper parts Bouillante geothermal field. In this exhumed paleo-geothermal reservoir we characterize the nature and the P-T evolutions of the hydrothermal mineral associations in relation with fluids transfers. Moreover, high-temperature hydrothermal activity is coeval with the development of ductile tectonic structures, particularly schistose corridors, and is dated at 2.59 ± 0.12 Ma on white micas, involving maximum activity of 600 ky. These data provide a conceptual model, including brittle-ductile transition located at a depth between 2.5 and 4 km. In this way, brittle and ductile tectonic structures are efficient drains to connected vertical and lateral fluids and heat transfers. This may provide new guides for exploration of geothermal resources in volcanic arcs.
Statistical inference for discrete-time samples from affine stochastic delay differential equations

Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated as well. In particular, the optimal prediction-based estimating function and the asymptotic properties of the estimators are derived. The maximum pseudo-likelihood estimator is a particular case, and an expression is found for the efficiency loss when using the maximum pseudo-likelihood estimator, rather than the computationally more involved optimal prediction-based estimator. The distribution of the pseudo-likelihood estimator is investigated in a simulation study. Two examples of affine stochastic delay equation are considered in detail.
Erratum: Quantum computing in the presence of spontaneous emission by a combined dynamical decoupling and quantum-error-correction strategy [Phys. Rev. A<b>68</b>, 022322 (2003)]

Unfortunately, a mistake in the mathematical descriptionof the action of spontaneous emission SE replaced with: “Thaterrors in thequantum trajectories picture led us to the construction of awrong quantum-error-correcting code for correction of a“known-position SE error” in Ref. 1 . Fortunately, a correctcode can easily be constructed similarly to the originallypresented code, and the results of the paper remain largelyintact, requiring small modiﬁcations as a consequence of thenew encoding only , as we now describe.
EcoLife: Carbon-Aware Serverless Function Scheduling for Sustainable Computing

This work introduces ECOLIFE, the first carbon-aware serverless function scheduler to co-optimize carbon footprint and performance. ECOLIFE builds on the key insight of intelligently exploiting multi-generation hardware to achieve high performance and lower carbon footprint. ECOLIFE designs multiple novel extensions to Particle Swarm Optimization (PSO) in the context of serverless execution environment to achieve high performance while effectively reducing the carbon footprint.
Show Me: Unifying Instructional Image and Video Generation with Diffusion Models

Generating visual instructions in a given context is essential for developing interactive world simulators. While prior works address this problem through either text-guided image manipulation or video prediction, these tasks are typically treated in isolation. This separation reveals a fundamental issue: image manipulation methods overlook how actions unfold over time, while video prediction models often ignore the intended outcomes. To this end, we propose ShowMe, a unified framework that enables both tasks by selectively activating the spatial and temporal components of video diffusion models. In addition, we introduce structure and motion consistency rewards to improve structural fidelity and temporal coherence. Notably, this unification brings dual benefits: the spatial knowledge gained through video pretraining enhances contextual consistency and realism in non-rigid image edits, while the instruction-guided manipulation stage equips the model with stronger goal-oriented reasoning for video prediction. Experiments on diverse benchmarks demonstrate that our method outperforms expert models in both instructional image and video generation, highlighting the strength of video diffusion models as a unified action-object state transformer.
Key steps of a successful biological control against the sugarcane stemborer by inundative release of Trichogramma spp. : S1012TU08 Integrated Pest Management

For over ten years, a biological control strategy by inundative release of Trichogramma chilonis (Hymenoptera: Trichogrammatidae) against Chilo sacchariphagus (Lepidoptera: Crambidae) has been studied (French collaboration between INRA, CIRAD and FDGDON Reunion Island). Many key steps were elaborated the last years regarding the pest and beneficial insects. Strategies of biological control, mass production, and field releases were also investigated. Important results were obtained such as: (i) population dynamic of Chilo sacchariphagus and damage, (ii) efficacy of the egg parasitoid Trichogramma chilonis, (iii) strategies of insect release (period, dose, frequency, adapted packaging, and delayed emergence), (iv) optimization of mass production, (v) cold storage, (vi) field release methods and checking of field efficacy. An IPM strategy associating inundative release of an egg parasitoid, T. chilonis and conservation of a predatory ant, Pheidole megacephala, has been proposed. According to field experiments in Reunion Island, this reduced up to 50% of damage with financial gains ranging from 800 to 1800 dollars per ha. Successful long-term storage of T. chilonis and its good efficacy in field after cold storage make possible a large-scale application of IPM strategies in sugarcane production.
Surgical education based on combination of robotic-arm assisted total knee arthroplasty design and 3D-printing simulation

As compulsory content for orthopedic graduate students, total knee arthroplasty (TKA) is characterized by requirements of surgical accuracy and so is difficult to train since there is limited opportunity for young surgical trainees especially design of surgical operation and long term training to get experience. Traditional teaching of TKA for graduates is embarrassed by these barriers. Recent years, new techniques such as robotic-arm assisted surgery and 3D-printing technology have been extensively used in clinical training. For example the hybrid model with combined surgical design in virtue of robotic system and vivid simulation produced by 3D-printing for training. This paper reviewed is current situation in this field and evaluated the feasibility in clinical application