ethicalabs/Research-Intent-Collab huggingface dataset:
Natural Language Processing in Electronic Health Records (EHR): Automating Clinical Summarization and Patient Risk Stratification

Natural Language Processing (NLP) is revolutionizing the utilization of Electronic Health Records (EHR) by automating clinical summarization and patient risk stratification, thereby enhancing healthcare delivery. This chapter explores the integration of NLP technologies into EHR systems, highlighting their capacity to transform vast amounts of unstructured clinical data into actionable insights. Clinical summarization, a critical application of NLP, improves communication among healthcare providers and ensures continuity of care by generating concise, relevant summaries from comprehensive patient records. Through both extractive and abstractive summarization techniques, NLP facilitates efficient information retrieval, allowing clinicians to focus on key patient data.
A New Nonconvex Sparse Recovery Method for Compressive Sensing

As an extension of the widely used ℓr-minimization with 0 &lt; r ≤ 1, a new non-convex weighted ℓr − ℓ1 minimization method is proposed for compressive sensing. The theoretical recovery results based on restricted isometry property and q-ratio constrained minimal singular values are established. An algorithm that integrates the iteratively reweighted least squares algorithm and the difference of convex functions algorithm is given to approximately solve this non-convex problem. Numerical experiments are presented to illustrate our results.
Governance of food and nutrition security in Eswatini: an analysis of government policies and reports

Abstract                 Background                 Governance of food and nutrition security is vital in achieving sustainable development goals. Yet, the role of governance in shaping and preventing malnutrition risk is complex and poorly understood. This paper examined the governance of food and nutrition security in Eswatini.                                Methods                 Policy documents, annual reports, and minutes of board meetings from five government ministries were the documents that were used for this study. The data analysis focused on the strength of nutrition governance, actors involved in policymaking, nutrition-specific and sensitive-programs, and multisectoral coordination of programs.                                Results                 The findings show that Eswatini has medium strength, nutrition governance. The nutrition-specific programs included: micronutrient supplementation and deworming programs, breastfeeding campaigns, and treatment of acute malnutrition. The nutrition-sensitive initiatives included programs on school nutrition, sanitation and hygiene, agriculture production, and healthcare. However, multisectoral coordination was ineffective, as collaborative efforts are not structured, during implementation.                                Conclusion                 This study examined the governance of food and nutrition security in Eswatini using documents from government ministries. Diverse actors were involved in policy formation and implementation. The strength of nutrition governance was medium and multisectoral coordination was usually ad-hoc. The multiple actors involved in nutrition governance in Eswatini need to intentionally plan to improve multisectoral coordination to achieve higher impact.
The Contest Over Meaning: Hermeneutics as an Interpretive Methodology for Understanding Texts

This article focuses on the methodological and epistemological aspects of hermeneutics, a leading genre of interpretive research. Beginning with a brief overview of the limitations of methodological discussions of hermeneutics in current organizational research, the article first introduces readers to the historical context of hermeneutics and then discusses the major epistemological and methodological concepts and debates that inform contemporary hermeneutics. Next, methodological guidelines for employing hermeneutics in organizational research are proposed. Finally, some conclusions are offered.
Objective assessment of stress and surgical performance during simulated robot-assisted laparoscopic surgery

MIS techniques achieved in the last decades have improved the quality of interventions and patient recovery, although there are still doubts about how they affect surgeons' health. This study aims to analyze the relationship between surgeon physiological and subjective stress parameters during laparoscopic and robot-assisted laparoscopic surgery (RALS) and the quality of surgical performance by means of wearable technology.This study was conducted in a simulation environment with tasks involving hand-eye coordination and technical surgical skills. Sixteen surgeons from three different surgical disciplines participated in this study using both a conventional laparoscopic technique and the Versius® robotic platform for RALS. Two wearable sensors were used to analyze surgeons' physiological stress, as well as a subjective questionnaire for stress assessment during surgical practice (SURG-TLX).The results of the data analysis showed that stress experienced was reduced in RALS when compared to conventional laparoscopy, and with it the percentage of errors committed. Novice surgeons performed better in most parameters compared to experienced microsurgeons.Surgeons without previous experience in laparoscopic surgery showed an improvement in their stress and surgical performance when using robot-assisted surgery.
Efficient parallel algorithms for modern GPU-equipped high-performance computing systems

Um rechnerisch aufwendige Simulationen durchzuführen, werden Supercomputer benötigt. Moderne Hochleistungsrechner sind meist mit Grafikprozessoren (GPUs) ausgestattet. In dieser Dissertation analysierten und entwickelten wir numerische Methoden (ein semi-Lagrange discontinuous Galerkin Verfahren und einen rationalen Exponentialintegrator), die die Leistung solcher massiv-parallelen Systeme effizient nutzen.
Structural Group Sparse Representation for Image Compressive Sensing Recovery

10 pages, 4 figures, 1 table, published at IEEE Data Compression Conference (DCC) 2013
Verification of Arms Control and Disarmament Agreements

Abstract                This chapter discusses the nature and extent of verification measures in arms control and disarmament and considers thematic areas where verification is generally required, as well as weapon-specific issues within those areas. It provides verification measures in both bilateral and multilateral agreements, including but not limited to legally binding treaties. It also talks about transparency as a critical first step towards building confidence among parties and other stakeholders on implementing arms control and disarmament agreements. The chapter analyses how weapons, their parts and components, and weapons development, production, and storage facilities are sometimes inadvertently or deliberately omitted from declarations and annual progress reports by States. It considers satellite imagery or reconnaissance overflights, which are integral to verification of compliance.
Random Combinatorial structures:the convergent case

This paper studies the distribution of the component spectrum of combinatorial structures such as uniform random forests, in which the classical generating function for the numbers of (irreducible) elements of the different sizes converges at the radius of convergence; here, this property is expressed in terms of the expectations of {\it independent} random variables $Z_j$, $j\ge1$, whose joint distribution, conditional on the event that $\sum_{j=1}^n jZ_j = n$, gives the distribution of the component spectrum for a random structure of size $n$. For a large class of such structures, we show that the component spectrum is asymptotically composed of $Z_j$ components of size $j$, $j\ge1$, with the remaining part, of size $n-\sum_{j\ge1} Z_j$, being made up of a single, giant component.
Human Rights Treaty Bodies’ Monitoring of the Accountability in Peacekeeping Operations

This paper aims to answer a question: What is the legal basis of UN human rights treaty bodies for monitoring the UN’s accountability with regard to peacekeeping operations? For that purpose, demonstrations have been given regarding the institutional characteristics and practices of the reporting system under the International Covenant on Civil and Political Rights, whose treaty body is called the Human Rights Committee (HRC), in accordance with the current discussion about the accountability of international organizations. The accountability of international organizations has increasingly received attention from a variety of perspectives, including human rights protection, good governance, peacekeeping operations and immunity of international organizations. Pursuant to the broad scope of discussion on accountability, the present study deepens the analysis on legal issues regarding the UN’s accountability with regard to peacekeeping operations, with special focus on UN practices and the new developments in this field. In contrast to a general understanding, this paper highlights the roles of UN human rights treaty bodies as a mechanism for accountability over UN peacekeeping operations. It is revealed that HRC is able to monitor the human rights situation in a peacekeeping operation based on the legal relationship between the UN and member states and their duties that arise therein.
Nurse qualifications and perceptions of patient safety and quality of care in <scp>S</scp>outh <scp>A</scp>frica

AbstractA plethora of research links professional nurses' qualifications to patient outcomes. Also, research has shown that reports by nurses on the quality of care correspond with process or outcome measures of quality in a hospital. New to the debate is whether professional nurses' qualifications impact on their perceptions of patient safety and quality of care. This research aims to investigate professional nurses' perceptions of patient safety and quality of care in South Africa, and the relationship between these perceptions and professional nurses' qualifications. A cross‐sectional survey of 1117 professional nurses from medical and surgical units of 55 private and 7 public hospitals was conducted. Significant problems with regard to nurse‐perceived patient safety and quality of care were identified, while adverse incidents in patients and professional nurses were underreported. Qualifications had no correlation with perceptions of patient safety and quality of care, although perceptions may serve as a valid indicator of patient outcomes. Creating an organizational culture that is committed to patient safety and encourages the sharing of adverse incidents will contribute to patient safety and quality of care in hospitals.
Metagenomic analysis of Raphidiopsis raciborskii microbiome: beyond the individual

Raphidiopsis raciborskii is a toxic, invasive bacteria with a defined biogeographic pattern attributed to the generation of ecotypes subjected to local environmental filters and to phenotypic plasticity. The interactions taking place between the cyanobacterium and the other bacteria inhabiting the external polysaccharide-rich matrix surrounding the cells, or phycosphere, may be ecotype-specific and would have different influence on the carbon and nutrient cycling in the ecosystem. Here, we describe the bacterial community or microbiome (assessed by 16S rRNA metagenomics) associated to two R. raciborskii strains that have been described as different ecotypes: the saxitoxin-producer MVCC19 and the non-toxic LB2897. Our results showed that both ecotypes share 50% of their microbiomes and differ in their dominant taxa. The taxon having the highest abundance in the microbiome of MVCC19 was Neorhizobium (22.5% relative abundance), while the dominant taxon in LB2897 was the Planctomycetes SM1A02 (26.2% relative abundance). These groups exhibit different metabolic capabilities regarding nitrogen acquisition (symbiotic nitrogen-fixing in Neorhizobium vs. anammox in SM1A02), suggesting the existence of ecotype-specific microbiomes that play a relevant role in cyanobacterial niche-adaptation. In addition, as saxitoxin and analogues are nitrogen-rich (7 atoms per molecule), we hypothesise that saxitoxin-producing R. raciborskii benefits from external sources of nitrogen provided by the microbiome bacteria. Based on these findings, we propose that the mechanisms involved in the assembly of the cyanobacterial microbiome community are ecotype-dependent.
Randomness as Reference: Benchmark Metric for Optimization in Engineering

Benchmarking optimization algorithms is fundamental for the advancement of computational intelligence. However, widely adopted artificial test suites exhibit limited correspondence with the diversity and complexity of real-world engineering optimization tasks. This paper presents a new benchmark suite comprising 235 bounded, continuous, unconstrained optimization problems, the majority derived from engineering design and simulation scenarios, including computational fluid dynamics and finite element analysis models. In conjunction with this suite, a novel performance metric is introduced, which employs random sampling as a statistical reference, providing nonlinear normalization of objective values and enabling unbiased comparison of algorithmic efficiency across heterogeneous problems. Using this framework, 20 deterministic and stochastic optimization methods were systematically evaluated through hundreds of independent runs per problem, ensuring statistical robustness. The results indicate that only a few of the tested optimization methods consistently achieve excellent performance, while several commonly used metaheuristics exhibit severe efficiency loss on engineering-type problems, emphasizing the limitations of conventional benchmarks. Furthermore, the conducted tests are used for analyzing various features of the optimization methods, providing practical guidelines for their application. The proposed test suite and metric together offer a transparent, reproducible, and practically relevant platform for evaluating and comparing optimization methods, thereby narrowing the gap between the available benchmark tests and realistic engineering applications.
Metagenomic analysis of the gut microbiome of Nile tilapia (Oreochromis niloticus) from biofloc andpond aquaculture systems in Kerala, South India

Nile tilapia (Oreochromis niloticus) is one of the most commonly cultured fish species in global aquaculture, with production expected to increase further due to its strong culture performance and resistance to various environmental conditions. The gut microbiota significantly affects the host’s health and the gut of Nile tilapia harbour a diverse microbial community. An experimental study was conducted to analyse the bacterial composition and functional profile of the gut microbiota of Nile tilapia from two different aquaculture systems, Biofloc and Pond culture systems in Kerala, South India. Bacterial communities in the gut of tilapia collected from two systems were classified down to the genus level using 16S rRNA amplicon sequencing. The most prevalent bacterial phyla in the Pond group were Firmicutes, Proteobacteria and Fusobacteria, while Bacteroidetes, Firmicutes and Proteobacteria dominated the biofloc group. At the genus level, Streptococcus and Pseudomonas were the most abundant in the Pond group, whereas Prevotella and Blattobacterium were more prevalent in the Biofloc group. Higher microbial diversity was observed in the gut microbiome of Nile tilapia from the biofloc group. The functional profile of the gut microbiome of Nile tilapia exhibited alterations between the two aquaculture systems. The functional profile of the gut microbiome of Nile tilapia assessed by PiCrust2 revealed that the membrane transport-associated function was predominant in the Pond group and carbohydrate metabolism-associated function in the Biofloc group. The study illustrated how the host environment significantly impacts the composition, diversity and functional profile of the gut microbiome of Nile tilapia.   Keywords: Biofloc, Gut microbiota, Nile tilapia, Metagenomics
A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems

This paper presents a framework for estimating the remaining useful life (RUL) of mechanical systems. The framework consists of a multi-layer perceptron and an evolutionary algorithm for optimizing the data-related parameters. The framework makes use of a strided time window to estimate the RUL for mechanical components. Tuning the data-related parameters can become a very time consuming task. The framework presented here automatically reshapes the data such that the efficiency of the model is increased. Furthermore, the complexity of the model is kept low, e.g. neural networks with few hidden layers and few neurons at each layer. Having simple models has several advantages like short training times and the capacity of being in environments with limited computational resources such as embedded systems. The proposed method is evaluated on the publicly available C-MAPSS dataset, its accuracy is compared against other state-of-the art methods for the same dataset.
THE INFORMATION SYSTEM FOR THE IMPLEMENTATION OF THE HUMAN RESOURCES PROGRAM (HRIS) AT THE OFFSHORE CONSTRUCTION COMPANY PT. GUNANUSA UTAMA FABRICATORS

This research is about Human Resources Information Systems (HRIS) at PT. Gunanusa Utama Fabricators, offshore platform construction company. The research was conducted from January to March 2024, with the number of employees working at this company varying each month: 256 employees in January, 281 employees in February, and 331 employees in March. Descriptive methods with a qualitative approach were used to collect data through in-depth interviews, participant observation and documentation studies. The research results show that HRIS significantly increases the efficiency of HR administration by automating processes, enabling more informed decision making based on data, and optimizing employee skills management. However, the main challenges faced include resistance to change from employees and changes in organizational culture required to support the adoption of new technologies. Large and complex companies, with most employees being contract workers, add to the challenges in implementing HRIS. This research emphasizes the importance of effective change management in overcoming these barriers to maximize the benefits of HRIS in the context of the dynamic construction industry
3D-Printed Multi-Layer PCBs: Evaluating the Structural Integrity and Electromagnetic Compatibility of Additively Manufactured Circuits

New opportunities for fabricating multilayer printed circuit boards (PCBs) have appeared because of additive manufacturing, thanks to greater flexibility, shorter turnaround times and the ability to make prototypes on demand. The durability and compatibility with electromagnetic fields of 3D-printed multilayer PCBs are still not well understood and raise worries for high-standards applications. This research evaluates both the structural durability and electromagnetic interference properties of PCBs that have been 3D printed from special conductive and dielectric materials. A series of prototype PCBs were put together, printed, tested in tests for strength and electrical characteristics and tested for electromagnetic interference. Tests were completed using both finite elements and electromagnetics to support the experimental results. The research has found that 3D-printed PCBs have good strength and work properly, but they still need to improve in reliability and the effectiveness of shielding against electrical interference. It points out important factors that influence the quality of structural and EMC results and gives suggestions for finding the ideal print parameter and material combination. These results are important for developing highly reliable, manufacturable components for new electronic systems used in aerospace, IoT and wearable electronics.
A thematic analysis to examine the feasibility of EHR-based clinical decision support for implementing <i>Choosing Wisely</i>® guidelines

Abstract                                   Objective                   To identify important barriers and facilitators relating to the feasibility of implementing clinical practice guidelines (CPGs) as clinical decision support (CDS).                                                   Materials and Methods                   We conducted a qualitative, thematic analysis of interviews from seven interviews with dyads (one clinical expert and one systems analyst) who discussed the feasibility of implementing 10 Choosing Wisely® guidelines at their institutions. We conducted a content analysis to extract salient themes describing facilitators, challenges, and other feasibility considerations regarding implementing CPGs as CDS.                                                   Results                   We identified five themes: concern about data quality impacts implementation planning; the availability of data in a computable format is a primary factor for implementation feasibility; customized strategies are needed to mitigate uncertainty and ambiguity when translating CPGs to an electronic health record-based tool; misalignment of expected CDS with pre-existing clinical workflows impact implementation; and individual level factors of end-users must be considered when selecting and implementing CDS tools.                                                   Discussion                   The themes reveal several considerations for CPG as CDS implementations regarding data quality, knowledge representation, and sociotechnical issues. Guideline authors should be aware that using CDS to implement CPGs is becoming increasingly popular and should consider providing clear guidelines to aid implementation. The complex nature of CPG as CDS implementation necessitates a unified effort to overcome these challenges.                                                   Conclusion                   Our analysis highlights the importance of cooperation and co-development of standards, strategies, and infrastructure to address the difficulties of implementing CPGs as CDS. The complex interactions between the concepts revealed in the interviews necessitates the need that such work should not be conducted in silos. We also implore that implementers disseminate their experiences.
Active Inference or Control as Inference? A Unifying View

Active inference (AI) is a persuasive theoretical framework from computational neuroscience that seeks to describe action and perception as inference-based computation. However, this framework has yet to provide practical sensorimotor control algorithms that are competitive with alternative approaches. In this work, we frame active inference through the lens of control as inference (CaI), a body of work that presents trajectory optimization as inference. From the wider view of `probabilistic numerics', CaI offers principled, numerically robust optimal control solvers that provide uncertainty quantification, and can scale to nonlinear problems with approximate inference. We show that AI may be framed as partially-observed CaI when the cost function is defined specifically in the observation states.