ethicalabs/Research-Intent-Collab huggingface dataset:
TECHNOLOGY FOR IMPLEMENTING THE LEAN SIX SIGMA QUALITY MANAGEMENT MODEL IN HIGHER EDUCATION INSTITUTIONS. PART 1: IDENTIFICATION AND MEASUREMENT OF THE EDUCATIONAL PROCESS CRITICAL TO QUALITY CHARACTERISTICS

Обґрунтовано актуальність впровадження методології управління якістю Lean Six Sigma (LSS) у закладах вищої освіти (ВНЗ) України для підвищення ефективності освітніх і наукових бізнес-процесів відповідно до рекомендацій міжнародних стандартів. Метою статті є аналіз особливостей технології впровадження методології LSS у ВНЗ з метою вдосконалення навчально-наукових бізнес-процесів та прикладного застосування технології LSS в освітньому середовищі України. Практичне значення статті полягає в підвищенні якості освітнього процесу у ВНЗ шляхом використання засобів циклу безперервного вдосконалення DMAIC та LSS з метою підвищення ефективності реалізації ключового процесу «Розробка навчально-методичного забезпечення ( НМЗ) для навчального процесу».
A systematic review of natural language processing applications in Trauma &amp; Orthopaedics

AimsPrevalence of artificial intelligence (AI) algorithms within the Trauma &amp; Orthopaedics (T&amp;O) literature has greatly increased over the last ten years. One increasingly explored aspect of AI is the automated interpretation of free-text data often prevalent in electronic medical records (known as natural language processing (NLP)). We set out to review the current evidence for applications of NLP methodology in T&amp;O, including assessment of study design and reporting.MethodsMEDLINE, Allied and Complementary Medicine (AMED), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) were screened for studies pertaining to NLP in T&amp;O from database inception to 31 December 2023. An additional grey literature search was performed. NLP quality assessment followed the criteria outlined by Farrow et al in 2021 with two independent reviewers (classification as absent, incomplete, or complete). Reporting was performed according to the Synthesis-Without Meta-Analysis (SWiM) guidelines. The review protocol was registered on the Prospective Register of Systematic Reviews (PROSPERO; registration no. CRD42022291714).ResultsThe final review included 31 articles (published between 2012 and 2021). The most common subspeciality areas included trauma, arthroplasty, and spine; 13% (4/31) related to online reviews/social media, 42% (13/31) to clinical notes/operation notes, 42% (13/31) to radiology reports, and 3% (1/31) to systematic review. According to the reporting criteria, 16% (5/31) were considered good quality, 74% (23/31) average quality, and 6% (2/31) poor quality. The most commonly absent reporting criteria were evaluation of missing data (26/31), sample size calculation (31/31), and external validation of the study results (29/31 papers). Code and data availability were also poorly documented in most studies.ConclusionApplication of NLP is becoming increasingly common in T&amp;O; however, published article quality is mixed, with few high-quality studies. There are key consistent deficiencies in published work relating to NLP which ultimately influence the potential for clinical application. Open science is an important part of research transparency that should be encouraged in NLP algorithm development and reporting.Cite this article: Bone Jt Open 2025;6(3):264–274.
High–Performance Music Information Retrieval System for Song Genre Classification

With the large amounts of multimedia data produced, recorded and made available every day, there is a clear need for well-performing automatic indexing and search methods. This paper describes a music genre classification system, which was a winning solution in the Music Information Retrieval ISMIS 2011 contest. The system consisted of a powerful ensemble classifier using the Error Correcting Output Coding coupled with an original, multi-resolution clustering and iterative relabelling scheme. The two approaches used together outperformed other competing solutions by a large margin, reaching the final accuracy close to 88%.
Language Alignment via Nash-learning and Adaptive feedback

Recent research has shown the potential of Nash Learning via Human Feedback for large language model alignment by incorporating the notion of a preference model in a minimax game setup. We take this idea further by casting the alignment as a mirror descent algorithm against the adaptive feedback of an improved opponent, thereby removing the need for learning a preference model or the existence of an annotated dataset altogether. The resulting algorithm, which we refer to as Language Alignment via Nash-learning and Adaptive feedback (LANA), is capable of self-alignment without the need for a human-annotated preference dataset. We support this statement with various experiments and mathematical discussion.
Legislative Framework for the Protection of Minors’ Rights  in Criminal Proceedings

The study aims to investigate the role of legislative consolidation of the rights and legitimate interests of minors in criminal proceedings. The relevance of the study is due to the priority policy of the state to protect the rights and legitimate interests of the family, motherhood and childhood, as well as the active preventive work of au-thorized bodies. Constitutional, as well as sectoral guarantees of minors in criminal proceedings are consid-ered, and the authors’ different points of view on this issue are analyzed. The article analyzes and compares the concept of “minor” in the sectoral legislation of the Russian Federation. Apart from the above, a study of the norms of international law regulating the protection of the rights and legitimate interests of minors and the pos-sibility of their introduction into domestic legislation is performed. A number of factors that allow to refer a per-son to the category of “minor”, and, consequently, the possibility to benefit from the enshrined rights and guar-antees, have been revealed.
Latency Evaluation of an IoT Bluetooth 5 Opportunistic Edge Computing System

There are more and more IoT devices that need to be interconnected with each other to perform compute-intensive tasks due to their limitations in terms of storage, computing power and energy consumption. However, IoT devices encounter the problem of the lack of wireless connectivity in places where they are deployed or where they are traveling through. A solution to this problem consists in the use of opportunistic systems, which provide connectivity and processing resources efficiently by reducing remote communications to the cloud. Opportunistic networks are considered useful both in IoT scenarios where the cloud becomes saturated (e.g., due to an excessive amount of concurrent communications or to Denial-of-Service (DoS) attacks), as well as in those areas where wireless communications coverage is not available, such as it frequently occurs in rural areas or during natural disasters, wars or when other factors cause network outages. This paper presents the design of a novel opportunistic Edge Computing system based on the use of Bluetooth 5 and Single Board Computers (SBCs). To illustrate the performance and feasibility of the proposed system, latency tests are presented. For such latency tests, an experimental testbed was built by communicating two separate IoT networks (each network consisted of an IoT node and an opportunistic Edge Computing gateway). The tests calculated the time of message propagation from one end node to another. The obtained results show that the developed system obtains latencies between 850 and 1200ms, depending on the scenario, which make the solution viable for many application scenarios with low latency requirements.
(451) Human Rights and Sexual Health to Reproductive Health, A Research Project on Massive Open One line Courses (MOOCs)

Abstract                                   Introduction                   Faced with alarming and persistent reproductive health indicators, the raise in refusal of oral contraception by young people and the decline in access to abortion in some developed countries, United states more precisely, UNESCO Chair is creating a mini MOOC in the MOOC Rights, sexual health in Educations, "What sexual health and human rights bring to reproductive health?                                                   Objective                   To raise awareness and advance knowledge, empower citizens and their practice in the area of human rights in relation to reproductive health. This includes a variety of aspirations: the protection of young people from sexual violence, infertility; the fight against gender inequality, incest, sexual mutilation, sexual exploitation, unsafe abortion.                                                   Methods                   This mini MOOC is composed of 6 mini modules with different formats: • What are the contributions of sexual health to reproductive health? • What are the contributions of human rights to reproductive health? • The desire for a child • Contraception, historical abortion and current issues • Reduction of unwanted pregnancies? • The role of man in reproductive health, a challenge for achieving the 2030 SDGs This mini-MOOC is blended-learning approach, at opening sessions of the MOOC, learners register on a social network (WhatsApp, Fb….) and create private groups to discuss and exchange regularly different materials (testimonies, useful links, files…). This learning technique, which mixes a top down and a horizontal approach, aims at creating a community of learners, a strong group entity that can positively impact public opinion to thrive change.                                                   Results                   Past MOOCs results 2021, 93% of learners were satisfied and would recommend UNESCOs’ MOOC. We have had more than 40,000 learners in total in only two years (2019-2021). More than one thousand members of our community on Facebook dedicated to the MOOC and more than one thousand participants of contests/polls and quizess on social media.                                                   Conclusions                   What we want to do with ISSM is create an intercultural MOOC available in English and/or more your local languages (Spanish?), that promotes reproductive health and human rights and reflects both our values and vision. A process of co-creation taking into account intercultural diversity as well as the United Nations human rights framework and the Sustainable Development Goals (SDGs)                                                   Disclosure                   No
CIGR Handbook of Agricultural Engineering, Volume I Land and Water Engineering, Chapter 5 Irrigation and Drainage, Part 5.6 Land Drainage

First paragraph: Land drainage deals with the control of waterlogging and soil salinization in agricultural lands. In flatlands, a first problem emerges if soil infiltration rates are low and rainfall or irrigationwater stands on the ground surface, generally in small depressions or at the edges of the irrigation basin. This problem can be solved by leveling and smoothing the land and providing it with a uniform slope for excess water to flow through furrows or shallow ditches toward the surface drainage outlet. Surface water is discharged into a collector drain through pipes to prevent the erosion of the open ditch bank. Waterlogging of the root zone due to the presence of perchedwater tables also occurs if the percolation rate is lower than the amount of water infiltrated, because of poor internal drainage of the soil. In flatlands, percolation can be improved by means of subsoiling to break hardpans and other types of less pervious layers of the topsoil. Thus, the soil structure, porosity, and hydraulic conductivity are enhanced and thus so is water percolation. In areas with insufficient natural drainage, subsurface drainage systems are required to maintain the groundwater table below the root zone, thus keeping it free from waterlogging and salinization. These systems consist of parallel, horizontal, generally perforated plastic pipes, although deep open field drains also are used as a first step of drainage development. Groundwater flows toward the lateral drains and through them to the outlet, where it is discharged into the collector drain by means of a rigid unperforated pipe. The drainage water, removed from the field through the surface and subsurface drainage systems, is conveyed through a network of main drains to the outlet, where it is discharged into a water body by gravity flow, by pumping, or through tidal gates. Land drainage has contributed to agricultural development in rainfed areas of the temperate regions, in irrigated lands of the arid and semiarid regions, and in the humid tropics. In the temperate humid regions, land drainage promotes good aeration of the root zone and provides moisture appropriate in the topsoil to ensure workability. Therefore, in these regions, drainage has been an efficient means to increase crop production and to decrease farming costs. In irrigated lands, drainage is indispensable to prevent the permanent hazard of waterlogging and salinization: Of 260 million ha of irrigated lands, approximately 60 million ha currently suffer from the effects of salinization [1] and FAO estimates that salt buildup has severely damaged about 30 million ha. In the humid tropics, particularly in lowland areas where, traditionally, only paddy is grown, land drainage is required to increase rice production and to diversify agriculture by growing dry-foot crops.
The African Court on Human and Peoples’ Rights and Its Protection of the Right to a Fair Trial

Abstract Article 3(1) of the Protocol to the African Charter on Human and Peoples’ Rights on the Establishment of an African Court on Human and Peoples’ Rights provides that: “[t]he jurisdiction of the Court shall extend to all cases and disputes submitted to it concerning the interpretation and application of the [African] Charter, this Protocol and any other relevant Human Rights instrument ratified by the States concerned.” Since its establishment, the African Court on Human and Peoples’ Rights has handed down judgments dealing, inter alia, with the right to a fair trial under Article 7 of the African Charter on Human and Peoples’ Rights. This article discusses these judgments to highlight how the Court has interpreted or applied Article 7 of the African Charter. The author will analyse the jurisprudence of the Court on the right to a fair trial and in particular discuss the following themes that have emerged from this jurisprudence: the Court’s interpretation of the components of the right to a fair trial; the right to be heard and the right to defend oneself; the right to legal assistance, including legal aid; manifest errors in the trial; the right to be tried within a reasonable time; and the role of a prosecutor in contributing to the fairness of the trial. The author also discusses how the African Court has invoked other treaties to interpret the relevant provisions of the African Charter and how the African Court has interpreted other treaties apart from the African Charter.
Universal quantum computation and quantum error correction with ultracold atomic mixtures

Abstract                Quantum information platforms made great progress in the control of many-body entanglement and the implementation of quantum error correction, but it remains a challenge to realize both in the same setup. Here, we propose a mixture of two ultracold atomic species as a platform for universal quantum computation with long-range entangling gates, while providing a natural candidate for quantum error-correction. In this proposed setup, one atomic species realizes localized collective spins of tunable length, which form the fundamental unit of information. The second atomic species yields phononic excitations, which are used to entangle collective spins. Finally, we discuss a finite-dimensional version of the Gottesman–Kitaev–Preskill code to protect quantum information encoded in the collective spins, opening up the possibility to universal fault-tolerant quantum computation in ultracold atom systems.
Input-Based Ensemble-Learning Method for Dynamic Memory Configuration of Serverless Computing Functions

10 pages, 2 tables, 28 figures, accepted conference paper - UCC'24
Saddlepoint approximation for Student's t-statistic with no moment conditions

A saddlepoint approximation of the Student's t-statistic was derived by Daniels and Young [Biometrika 78 (1991) 169-179] under the very stringent exponential moment condition that requires that the underlying density function go down at least as fast as a Normal density in the tails. This is a severe restriction on the approximation's applicability. In this paper we show that this strong exponential moment restriction can be completely dispensed with, that is, saddlepoint approximation of the Student's t-statistic remains valid without any moment condition. This confirms the folklore that the Student's t-statistic is robust against outliers. The saddlepoint approximation not only provides a very accurate approximation for the Student's t-statistic, but it also can be applied much more widely in statistical inference. As a result, saddlepoint approximations should always be used whenever possible. Some numerical work will be given to illustrate these points.
Implementasi Human Resource Information System (HRIS) dalam Meningkatkan Efisiensi Administrasi SDM PT Bio Farma Jawa Barat

Digital transformation in human resource management has become a strategic necessity in the era of the 5.0 industrial revolution. One widely adopted innovation is the Human Resource Information System (HRIS), which aims to improve the efficiency of HR administration. Most research focuses on the private sector and has not examined HRIS implementation in state-owned pharmaceutical companies. This indicates the need for in-depth study in the context of state-owned enterprises, particularly PT Bio Farma (Persero) in West Java. The main issue that must be examined is the contribution of HRIS to time efficiency, data accuracy, and job satisfaction of administrative staff. The purpose of this study is to analyze the impact of HRIS implementation on HR administration efficiency. The research method used is a descriptive quantitative approach with a purposive sample of 40 respondents. Data collection techniques were carried out through questionnaires and interviews. Data analysis used simple regression tests and descriptive analysis. The results show that HRIS can improve time efficiency, data accuracy, and job satisfaction. The implications of this research provide practical contributions to companies in strengthening digital HR systems, as well as theoretical contributions to the development of HR information system models.
Order Conditions for Sampling the Invariant Measure of Ergodic Stochastic Differential Equations on Manifolds

AbstractWe derive a new methodology for the construction of high-order integrators for sampling the invariant measure of ergodic stochastic differential equations with dynamics constrained on a manifold. We obtain the order conditions for sampling the invariant measure for a class of Runge–Kutta methods applied to the constrained overdamped Langevin equation. The analysis is valid for arbitrarily high order and relies on an extension of the exotic aromatic Butcher-series formalism. To illustrate the methodology, a method of order two is introduced, and numerical experiments on the sphere, the torus and the special linear group confirm the theoretical findings.
Artificial Intelligence in Neurology: A Research Study on Machine Learning Applications in Brain Imaging, Diagnosis, and Prognosis

Background: Neurological diseases present a heavy healthcare burden, and traditional diagnosis techniques are limited by accuracy and speed. Artificial intelligence, and especially machine learning, provides novel solutions for the improvement of brain imaging interpretation and prognosis forecasting.  Objective: To assess the effectiveness of machine learning models as a neurological imaging diagnostic and prognostic tool with special attention to statistical reliability, interpretability, and accuracy.  Methods: Brain imaging datasets were preprocessed, segmented, and enhanced using MRI, fMRI, CT, and PET.   CNNs, RNNs, SVMs, and ensemble solutions in the accepted practices were trained and checked.   Performance was measured by accuracy, F1-scores, measures of interpretability, and statistical significance testing.  Results: With testing accuracy of 89.5%, validation accuracy of 90.2%, and training accuracy of 95.6%, CNNs excelled among the models.  Other methods were beaten by F1-scores of 0.91.  With heatmaps in stroke datasets overlapping up to 91.5%, visualization aided interpretability.  With statistical analysis (p &lt; 0.001), a +12.4% boost over baselines was seen. Clinical utility at the individual case level was demonstrated, with 90.7% agreement with radiologists and 92.1% accuracy in stroke predictions.  Conclusion: The CNN-based approaches to machine learning, i.e., provide helpful, comprehensible, and practical solutions to neurological imaging.   The models enhance the accuracy of the diagnosis, early disease identification, and prognostic decision-making.   The application of artificial intelligence to clinical neurology is a breakthrough solution to the problems of bias, data heterogeneity, compliance, and the enhancement of patient care.
AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations

12 pages, 1 table, to be submitted
Diversity of perspectives in biodiversity conservation: A case study of port land use in Antwerp and Rotterdam

Conflicts of interest often undermine conservation initiatives against biodiversity decline. Effective decision-making requires a deeper understanding of the positions, criteria, concerns, and perspectives of stakeholders. However, managing so many perspectives can be difficult, and if not done well, conflicts arise which make it difficult to achieve conservation goals. The purpose of this study is to demonstrate that identifying areas of consensus is a good starting point to generate more effective debates and address complex issues. To do this, we investigate the diversity of perspectives regarding biodiversity conservation schemes among stakeholders in the studied ports of Antwerp and Rotterdam. Using Q-methodology, a semi-quantitative technique that enables us to systematically study the subjective views of stakeholders involved in a topic, we identified and organized a range of shared perspectives into three groups, known as factors. A total of 20 participants sorted 45 statements according to their perceptions and objectives, from -4 'most disagreeable' to 4 'most agreeable'. Then, respondents explained their rankings in a post-sorting interview. Next, the data was analyzed quantitatively and qualitatively. The quantitative analysis was conducted in two parts: (i) Dividing respondents into groups based on similar perspectives and (ii) coupling distinguishing statements with one of the factors characteristic of that viewpoint. Finally, in a qualitative analysis, we used the distinguishing statements and insights from interviews to create narratives and titles for the three factors: (1) Ports are key for our economic wealth, hence port development should continue, (2) Nature first, and (3) Multi-actor governance. Our findings confirm consensuses in three areas: policy, land use, and mitigation tactics. Interestingly, all narratives unanimously agreed on the importance of regulating port development and land use changes via legislation and environmental impact assessments. However, they debated the rigidity of legislation and whether offsetting port expansion (and associated land and resource use claims) should take place locally or internationally. We also found that decision-making mostly followed a human-centered perspective, where economic values were more relevant than intrinsic ones. These insights can serve as a baseline for stakeholders to form coalitions around areas of consensus to depolarize debates and avoid decision-making gridlocks.