bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Surgical Competences for Neck Dissection and Total Laryngectomy on Revascularized Cadaver Models: Onco-Neck-Score and Onco-Larynx-Score
Authors: Rullière Anne , Danion Jérôme , Dufour Xavier , Oriot Denis , Faure Jean-Pierre , Favier Valentin , Carsuzaa Florent 
Published: October 2024

Background In surgical simulation, evaluation tools are necessary to allow the overall and specific level of each gesture to be assessed for learners, to allow active feedback and follow-up. The aim of this study was to create and validate a scale for the assessment of competences for neck dissection (ND) and total laryngectomy (TL) in head and neck surgical oncology simulation specific for revascularized cadavers’ models. Methods Two independent scales were created for ND and TL based on a two-round Delphi method. The scales were used during ND and TL simulation sessions on SimLife® (Symedis, Poitiers, France) model. Surgical steps were scored by 2 independent observers. To assess its ease of use, a questionnaire was answered by senior surgeons (SS) at the end of the sessions. Results Fifteen items were included in the final version for ND scale and 20 for TL scale. The results of 14 lateral ND and 8 TL were included. The mean score was higher for SS (69 ± 6.4; 87.5 ± 8.5) than for residents (36.5 ± 11; 57.5 ± 13.2) for ND ( P = 0.0006) and TL ( P = 0.028) respectively. Six SS strongly agreed that this tool had a positive impact on resident training with stepwise feedback and accurately represented their competences. Conclusion We developed a pedagogic tool built to assess surgical competence for head and neck surgical oncology on revascularized cadaver models. This tool has a good construct validity thanks to the expert reviewing with Delphi method and appears to have fine acceptability by the SS.
Creative health in the urban Global South: barriers and facilitators in the cases of Cochabamba and Salvador
Authors: Shaughnessy C , Santiago D , Donoso PP , Perkins R , Lisboa T 
Published: October 2024

Aims: The Global South has some of the world’s largest cities, where rapid, ad hoc development of urban centres and ‘megacities’ has fuelled major socio-economic, environmental, and public health concerns. These urban environments can generate feelings of loneliness, with multiple barriers for access and participation in socio-cultural infrastructures. An inclusive future agenda for global creative health must, therefore, consider how urbanisation impacts social public health, what creative health approaches can do to alleviate this, and what the barriers are to access. This article explores barriers and facilitators to accessing socio-cultural urban infrastructures in two case-study cities: Salvador in Brazil and Cochabamba in Bolivia. Methods: Data were collected as part of a survey examining access to, and engagement in, arts and cultural activities undertaken between 25 January and 1 May 2023. This article focuses on two questions: What helps you to access artistic and cultural events in your city? and What barriers do you face in accessing artistic and cultural events in your city? 239 open responses from adults, in Portuguese and Spanish, were analysed using descriptive thematic analysis. Results: Findings highlight how emergent issues around existing economic inequality, safety, and accessibility can limit residents’ capacity to engage in creative health activities. While preliminary in scope, this raises wider public health implications for how creative health approaches may be leveraged within urban, Global South contexts. Conclusions: Findings highlight how greater dialogue is needed between the urban development, public health, and creative health sectors. Given the emerging evidence of the role of creative engagement to alleviate loneliness, integrating creative health approaches within urban public health may further strengthen connections with the most vulnerable communities, and help to build healthier cities. The article ends by outlining an approach that incorporates both local and city-wide creative encounters, highlighting how future interventions could be appropriately designed that gradually scale these types of interventions from tailored local offerings to larger, city-wide activities.
Effects of pre-operative patient expectations on the outcome after total shoulder arthroplasty: A systematic review
Authors: Claes Anke , Mesel Annelien De , Verborgt Olivier , Struyf Filip 
Published: October 2024

Aim To synthesize the evidence considering effects of pre-operative patient expectations on the post-operative outcomes in patients with total shoulder arthroplasty. Methods PubMed, Web of Science and Cochrane were searched for relevant studies. Studies before 2000 were excluded. Studies examining effects of pre-operative patient expectations on post-operative outcome in adults who had undergone total shoulder arthroplasty were included if at least one of the following treatment outcomes should have been measured: shoulder function, range of motion, shoulder pain, activities of daily living, muscle strength, patient satisfaction, or quality of life. After screening 875 studies four studies were included. Relevant data was extracted in a standardized way. Quality assessment was performed through QUIPS and EBRO methods. Both were performed by two independent reviewers. Results All 4 studies had a high risk of bias and level of evidence B. Moderate evidence was found regarding the absence of an association between greater pre-operative patient expectations and numerous outcome measures. All other associations yielded conflicting or preliminary evidence. Discussion Informing patients about what can be expected can be of great importance. Evidence lacking. To confirm or reject the findings of this systematic review, future research should focus on high-quality research with validated research protocols.
Arthroscopic Repair of Rotator Cuff Tears in Older Adults: A Retrospective Case-Series Study
Authors: Baytoon Danyal , Schmidt Viktor , Bazan Aleksander , Wadsten Mats , Sayed-Noor Arkan 
Published: October 2024

Introduction Rotator cuff tears (RCTs) are a common source of pain in the shoulder girdle. There is still debate about the optimal treatment for older adults with RCTs. In clinical practice, patients who do not respond well to non-surgical management may still be eligible for operative treatment. In this study, we assessed the outcome of arthroscopic repair of RCTs in patients ≥60 years old. Material and method A retrospective case series was conducted to include patients who underwent arthroscopic repair of RCTs from 1 January 2018 to 1 January 2021. The study included individuals aged ≥60 years who had radiologically confirmed RCTs (verified by MRI) and clinical findings including sleep-disturbing pain and reduced range of motion. Preoperative treatment included physiotherapy for at least 6 months and one subacromial corticosteroid injection. Results Fifty-three RCTs were treated during the study period. After exclusion because of incomplete documentation, 45 patients remained. The mean age was 66 years and 80% had isolated supraspinatus tears and 25% had variable degrees of fatty infiltration (Goutallier grade 1-3) on MRI examination with positive tangent sign. There were no surgical site infections and three symptomatic re-ruptures (6%). At follow-up, (71%) reported no remaining sleep-disturbing shoulder pain. Abduction improved from 62° to 122°. Flexion improved from 68° to 135°. This study found that people aged 60 years and older who underwent repair of RCTs showed statistically significant clinical improvement in shoulder flexion and abduction with less sleep-disturbing shoulder pain. These encouraging results may contribute to the existing literature, favoring the choice of surgical treatment for symptomatic RCTs in this age group with failed nonoperative treatment. Conclusion The arthroscopic repair of RCTs in patients 60 years and older yielded a substantial increase in shoulder flexion and abduction, significantly reducing sleep-disturbing shoulder pain. Postoperative complications were minimal.
The Importance of Accounting for the Dead in Migration
Authors: Bird Cate E. , Shangraw Austin 
Published: October 2024

Executive Summary This article highlights the importance of accounting for the dead in migration contexts, from international humanitarian law (IHL), international human rights law (IHRL), and forensic perspectives. Starting by reviewing obligations under IHL and IHRL for the processes of accounting, the article discusses forensic action and the role that accounting can play to protect the dead and clarify the fate and whereabouts of the missing for their families. Considering the complexity of missing and deceased migrant cases, this problem must be approached from several complementary angles, including States codifying international legal obligations related to accounting for the dead in domestic legal or policy frameworks; developing national mechanisms to collect, centralize, and report disaggregated information on migrant deaths; addressing migrant deaths from a public health perspective; pursuing identification efforts including participating in transnational coordination mechanisms; developing strong partnerships with civil society actors; and coupling accounting initiatives with policies that promote the search for missing migrants.
Excessive Use of Force and Migrant Death and Disappearance in Southern Arizona
Authors: Reineke Robin C. , Martinez Daniel E. 
Published: October 2024

Executive Summary In this article, we present a qualitative analysis of the events surrounding death or disappearance in autopsy and missing person reports from the Pima County Office of the Medical Examiner (PCOME) in Arizona to highlight how interactions between border enforcement personnel and migrants can be deadly. We reviewed PCOME records of undocumented border crosser deaths between 2000 and 2023 and observed three main types of deadly U.S. Border Patrol (USBP) practices: reckless motor vehicle pursuits, aggressive strategies used to detain individuals who are on foot, and the use of lethal force. Our findings reveal that these tactics, which we argue constitute forms of “excessive use of force,” represent significant yet overlooked factors contributing to migrant death and disappearance in southern Arizona. We make the following policy recommendations: 1. Immediate measures to prevent the loss of life (A). The Department of Homeland Security (DHS) should mandate a ban on border enforcement methods that provoke fear, panic, or confusion. (B). DHS should take measures to substantially reduce the use of high-speed motor vehicle pursuits by USBP and other immigration enforcement officials. (C). DHS should ensure that USBP officers are compliant with Department of Justice (DOJ) standards on use of deadly force, in particular the policy that “Deadly force may not be used solely to prevent the escape of a fleeing suspect.” 2. Investigate Border Fatalities Involving Border Enforcement Officers (A). We call on the Government Accountability Office (GAO) to conduct an official review of all medical examiner and coroner records along the U.S.-Mexico border for fatality cases in which border enforcement personnel were involved in any way in the circumstances surrounding death. (B). We encourage the formation of civilian review boards in border regions to review medical examiner and coroner records of migrant fatalities involving immigration officials as well as immigration officials’ apprehension strategies immediately preceding fatal encounters with migrants.
Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force
Authors: Cao Jian , Zhang Jianhua , Wang Chang , Li Kexiang , Zhang Jianjun , Wang Guihua , Ren Hongliang 
Published: October 2024

AbstractThe wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.
Sequence Flow: interactive web application for visualizing partial order alignments
Authors: Zdąbłasz Krzysztof , Lisiecka Anna , Dojer Norbert 
Published: October 2024

Abstract
Background
Multiple sequence alignment (MSA) has proven extremely useful in computational biology, especially in inferring evolutionary relationships via phylogenetic analysis and providing insight into protein structure and function. An alternative to the standard MSA model is partial order alignment (POA), in which aligned sequences are represented as paths in a graph rather than rows in a matrix. While the POA model has proven useful in several applications (e.g. sequencing reads assembly and pangenome structure exploration), we lack efficient visualization tools that could highlight its advantages.

Results
We propose Sequence Flow – a web application designed to address the above problem. Sequence Flow presents the POA as a Sankey diagram, a kind of graph visualisation typically used for graphs representing flowcharts. Sequence Flow enables interactive alignment exploration, including fragment selection, highlighting a selected group of sequences, modification of the position of graph nodes, structure simplification etc. After adjustment, the visualization can be saved as a high-quality graphic file. Thanks to the use of SanKEY.js – a JavaScript library for creating Sankey diagrams, designed specifically to visualize POAs, Sequence Flow provides satisfactory performance even with large alignments.

Conclusions
We provide Sankey diagram-based POA visualization tools for both end users (Sequence Flow) and bioinformatic software developers (SanKEY.js). Sequence Flow webservice is available at https://sequenceflow.mimuw.edu.pl/. The source code for SanKEY.js is available at https://github.com/Krzysiekzd/SanKEY.js and for Sequence Flow at https://github.com/Krzysiekzd/SequenceFlow.
Increased thyroid hormone sensitivity is correlated with visceral obesity in patients with type 2 diabetes
Authors: Yu Lu , Liu Yujia , Wang Yingxuan , Wang Gang , Xiao Xianchao , Wang Huan , Wang Hanyu , Sun Hui , Wang Guixia 
Published: October 2024

Abstract
Objective
The study aimed to assess whether thyroid hormone (TH) sensitivity is related to visceral fat area (VFA) and visceral obesity in euthyroid subjects with type 2 diabetes (T2D).

Methods
750 euthyroid patients with T2D were enrolled. A VFA of 80 cm2 or more was considered visceral obesity. Central TH sensitivity was conducted using thyrotrophic thyroxine resistance index (TT4RI), thyrotropin index (TSHI), and thyroid feedback quantile-based index (TFQI). Free triiodothyronine to free thyroxine (FT3/FT4) was utilized for assessing peripheral TH sensitivity.

Results
The subjects had a mean age of 51.5 ± 11.1 years, and 540 (72.0%) of them were men. In multivariable regression analyses, there was a positive correlation of FT3/FT4 tertile with visceral obesity, after full adjustment for confounding variables (P < 0.05). The middle and highest FT3/FT4 tertiles were correlated with a 134% [95% CI (1.24, 4.44)] and 98% [95% CI (1.04, 3.78)] higher prevalence of visceral obesity than the lowest tertile, respectively. Conversely, elevated TFQI levels were linked to a decreased prevalence of visceral obesity. Stratified analysis revealed that these associations were particularly pronounced in participants who are neither overweight nor obese and those aged less than 60 years (all P < 0.05).

Conclusions
Higher TH sensitivity is correlated with visceral obesity and elevated VFA in euthyroid patients with T2D, particularly among those younger than 60 years and individuals who are neither overweight nor obese.
Resource-optimized cnns for real-time rice disease detection with ARM cortex-M microprocessors
Authors: Nugroho Hermawan , Chew Jing Xan , Eswaran Sivaraman , Tay Fei Siang 
Published: October 2024

AbstractThis study explores the application of Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNNs), for detecting rice plant diseases using ARM Cortex-M microprocessors. Given the significant role of rice as a staple food, particularly in Malaysia where the rice self-sufficiency ratio dropped from 65.2% in 2021 to 62.6% in 2022, there is a pressing need for advanced disease detection methods to enhance agricultural productivity and sustainability. The research utilizes two extensive datasets for model training and validation: the first dataset includes 5932 images across four rice disease classes, and the second comprises 10,407 images across ten classes. These datasets facilitate comprehensive disease detection analysis, leveraging MobileNetV2 and FD-MobileNet models optimized for the ARM Cortex-M4 microprocessor. The performance of these models is rigorously evaluated in terms of accuracy and computational efficiency. MobileNetV2, for instance, demonstrates a high accuracy rate of 97.5%, significantly outperforming FD-MobileNet, especially in detecting complex disease patterns such as tungro with a 93% accuracy rate. Despite FD-MobileNet’s lower resource consumption, its accuracy is limited to 90% across varied testing conditions. Resource optimization strategies highlight that even slight adjustments, such as a 0.5% reduction in RAM usage and a 1.14% decrease in flash memory, can result in a notable 9% increase in validation accuracy. This underscores the critical balance between computational resource management and model performance, particularly in resource-constrained settings like those provided by microcontrollers. In summary, the deployment of CNNs on microcontrollers presents a viable solution for real-time, on-site plant disease detection, demonstrating potential improvements in detection accuracy and operational efficiency. This study advances the field of smart agriculture by integrating cutting-edge AI with practical agricultural needs, aiming to address the challenges of food security in vulnerable regions.
Automated segment-level coronary artery calcium scoring on non-contrast CT: a multi-task deep-learning approach
Authors: Föllmer Bernhard , Tsogias Sotirios , Biavati Federico , Schulze Kenrick , Bosserdt Maria , Hövermann Lars Gerrit , Stober Sebastian , Samek Wojciech , Kofoed Klaus F. , Maurovich-Horvat Pál , Donnelly Patrick , Benedek Theodora , Williams Michelle C. , Dewey Marc 
Published: October 2024

Abstract
Objectives
To develop and evaluate a multi-task deep-learning (DL) model for automated segment-level coronary artery calcium (CAC) scoring on non-contrast computed tomography (CT) for precise localization and quantification of calcifications in the coronary artery tree.

Methods
This study included 1514 patients (mean age, 60.0 ± 10.2 years; 56.0% female) with stable chest pain from 26 centers participating in the multicenter DISCHARGE trial (NCT02400229). The patients were randomly assigned to a training/validation set (1059) and a test set (455). We developed a multi-task neural network for performing the segmentation of calcifications on the segment level as the main task and the segmentation of coronary artery segment regions with weak annotations as an auxiliary task. Model performance was evaluated using (micro-average) sensitivity, specificity, F1-score, and weighted Cohen’s κ for segment-level agreement based on the Agatston score and performing interobserver variability analysis.

Results
In the test set of 455 patients with 1797 calcifications, the model assigned 73.2% (1316/1797) to the correct coronary artery segment. The model achieved a micro-average sensitivity of 0.732 (95% CI: 0.710–0.754), a micro-average specificity of 0.978 (95% CI: 0.976–0.980), and a micro-average F1-score of 0.717 (95% CI: 0.695–0.739). The segment-level agreement was good with a weighted Cohen’s κ of 0.808 (95% CI: 0.790–0.824), which was only slightly lower than the agreement between the first and second observer (0.809 (95% CI: 0.798–0.845)).

Conclusion
Automated segment-level CAC scoring using a multi-task neural network approach showed good agreement on the segment level, indicating that DL has the potential for automated coronary artery calcification classification.

Critical relevance statement
Multi-task deep learning can perform automated coronary calcium scoring on the segment level with good agreement and may contribute to the development of new and improved calcium scoring methods.

Key Points

Segment-level coronary artery calcium scoring is a tedious and error-prone task.

The proposed multi-task model achieved good agreement with a human observer on the segment level.

Deep learning can contribute to the automation of segment-level coronary artery calcium scoring.

Graphical Abstract