Specific Domain Research Articles

Doing politics in the other language. Sentiment and subjectivity in Swiss political debates

ABSTRACT Experimental research on decision making and moral dilemmas shows effects of using a second or foreign language on cognition: People tend to apply different rationalities and are less biased when thinking and solving tasks the L2. In this contribution, the manifestations of a foreign language effect are investigated in naturally occurring spoken language data in a specific domain (politics). While some scholars have hypothesised that a possible foreign language effect could be relevant for multilingual political institutions (such as the administration of the European Union), so far, no quantitative research has been done to test the hypothesis. To fill this gap, the conversational turns of 10 Swiss politicians who appear both in French – and German-speaking national TV are analysed. A total of 2100 turns in their respective L1 or L2 are submitted to sentiment and subjectivity analyses using Natural Language Processing tools. The analyses show that politicians tend to be less negative and less subjective in their respective L2. The data suggest that the use of L2s may indeed have an influence on the interactional quality of political debates.

Specific variants in ftsI reduce carbapenem susceptibility in Pseudomonas aeruginosa.

The ftsI locus of gram-negative bacteria encodes penicillin-binding protein 3 (PBP3), a common target of β-lactam antibiotics. Recent genomic surveillance of carbapenem-resistant Pseudomonas aeruginosa revealed that 17% of strains possessed nonsynonymous substitution in ftsI. However, the contribution of ftsI nonsynonymous substitution alone to the antimicrobial susceptibility of P. aeruginosa has not been formally evaluated. Therefore, we assessed the effect of ftsI nonsynonymous substitutions alone on β-lactam susceptibility in recombinant P. aeruginosa strains. The nonsynonymous substitutions C265G (Leu89Val), C1379T (Met460Thr), T1412G (Val471Gly), C1510T (Arg504Cys), C1579A (Pro527Thr), C1579T (Pro527Ser), C1599A (Phe533Leu), and G1609C (Val537Leu) were introduced into ftsI in an antimicrobial-susceptible strain via homologous recombination. Then, their β-lactam susceptibilities were investigated using the broth microdilution method and growth parameter analysis for the growth curves. The introduction of the N-terminal Leu89Val mutation did not alter β-lactam susceptibility. By contrast, the introduction of penicillin-binding (PB) domain mutations (Met460Thr, Val471Gly, Arg504Cys, Pro527Thr, Pro527Ser, Phe533Leu, or Val537Leu) reduced the susceptibility to meropenem and doripenem by two- to eightfold in MIC. Arg504Cys, the most common mutation encountered clinically, reduced susceptibility to cefepime by fourfold. Growth parameter analysis revealed that, conversely, these PB domain mutations generally increase the susceptibility to cefiderocol and piperacillin. The cocrystal structures of PBP3 with β-lactams suggest that the positions of PB domain mutations can affect the mobility of previously proposed key residues, namely, Tyr409, Arg489, Tyr503, Tyr532, Phe533, and the KSGT motif, via intramolecular interactions. These data demonstrated that seven specific variants in ftsI are genetic signals of bacterial adaptation to carbapenems.IMPORTANCEPrevious studies have reported the occurrence of ftsI mutations under various genetic backgrounds in Pseudomonas aeruginosa clinical isolates. However, the nature of ftsI mutations by themselves has not been thoroughly investigated under a common genetic background using recombinant strains. This study presents experimental data on the effect of ftsI point mutations alone on bacterial susceptibility to a wide range of antipseudomonal β-lactams. This study found that seven specific penicillin-binding domain mutations in FtsI/PBP3 reduced the efficacy of carbapenems but increased the efficacies of piperacillin and cefiderocol. This key finding will facilitate the development of therapeutic options for carbapenem-resistant P. aeruginosa-associated infections. Furthermore, this study contributes to the development of a reliable database collating resistance-associated point mutations, which would aid the interpretation of genomic data on P. aeruginosa clinical isolates.

Road Rage Against the Machine: Humans and LLMs Share a Blame Bias Against Driverless Cars

Human language reflects our social values, biases, and moral judgments. Large language models (LLMs) trained on extensive human texts may therefore learn or encode such information, allowing them to generate responses within moral and ethical domains. Investigating whether LLMs exhibit human-like (including potentially biased or skewed) moral judgments is therefore crucial. Recent moral psychology research suggests that humans tend to have stronger negative reactions toward, and attribute more blame to, intelligent autonomous machines than to fellow humans for identical harm. Here we examine whether LLMs (OpenAI’s GPT-3.5 and GPT-4) exhibit a similar bias against machines in the specific domain of driverless cars. We replicate experiments from two previous studies in the USA and China and find that GPT-4 (but not GPT-3.5), similar to human participants reported previously, consistently rates machine drivers as more blameworthy and causally responsible than human drivers for identical traffic harm (Study 1), while also rating machine versus human drivers’ identical actions as more harmful and morally wrong (preregistered Study 2). This asymmetry in moral judgments is replicated across both LLMs and human participants in a new crash scenario that is unlikely to have been included in the LLMs’ training sets (preregistered Study 3). We discuss whether the blame bias against machines might be morally justified, and also propose that its presence in humans and LLMs could be due to different mechanisms.

Pre-service teachers’ forms of reasoning in discussions of ethical cases

ABSTRACT This article contributes to the field of professional ethics in teacher education by presenting findings from a qualitative study of Norwegian first- and fourth-year pre-service teachers’ discussions of ethical cases. Analytical attention is on the forms of reasoning and concept use in these discussions. Theoretically, the article applies an Aristotelian perspective on forms of reasoning, contrasting phronesis (moral reasoning) with techne (pragmatic reasoning), and examines the reasoning forms in interaction with academic concepts and everyday concepts. Findings indicate that pre-service teachers at both levels use mostly everyday concepts in discussions of ethics and frame the cases as primarily pragmatic problems solvable by engaging techne. Phronesis is less engaged in the discussions. The article argues for the need to treat ethics as a specific knowledge domain in teaching. Implications discussed include how to teach ethics in initial teacher education and the role of academic concepts for teacher professional ethics.

Supervised Learning-Based Fault Classification in Industrial Rotating Equipment Using Multi-Sensor Data

The reliable operation of rotating machinery is critical in industrial production, necessitating advanced fault diagnosis and maintenance strategies to ensure operational availability. This study employs supervised machine learning algorithms to apply multi-label classification for fault detection in rotating machinery, utilizing a real dataset from multi-sensor systems installed on a suction fan in a typical manufacturing industry. The presented system focuses on multi-modal data analysis, such as vibration analysis, temperature monitoring, and ultrasound, for more effective fault diagnosis. The performance of general machine learning algorithms such as kNN, SVM, RF, and some boosting techniques was evaluated, and it was shown that the Random Forest achieved the best classification accuracy. Feature importance analysis has revealed how specific domain characteristics, such as vibration velocity and ultrasound levels, contribute significantly to performance and enabled the detection of multiple faults simultaneously. The results demonstrate the machine learning model’s ability to retrieve valuable information from multi-sensor data integration, improving predictive maintenance strategies. The presented study contributes a practical framework in intelligent fault diagnosis as it presents an example of a real-world implementation while enabling future improvements in industrial condition-based maintenance systems.

Existence of Weak Solutions for a Degenerate Goursat‐Type Linear Problem

ABSTRACTFor a generalization of the Gellerstedt operator with mixed‐type Dirichlet boundary conditions to a suitable Tricomi domain, we prove the existence and uniqueness of weak solutions of the linear problem and for a generalization of this problem. The classical method introduced by Didenko, which study the energy integral argument, will be used to prove estimates for a specific Tricomi domain.

Migration of an Open Source Application to Software Product Lines

Software reuse is a cornerstone of modern software engineering, enhancing development efficiency and system adaptability. Software Product Lines (SPL) offer a structured approach to creating software families by leveraging reusable assets within a specific domain. This paper presents a methodology for migrating an open-source project management application to an SPL using the Mobioos Forge platform. Additionally, we extend the application with a new microservice-based module aligned with Algeria's recent regulatory framework (Loi organique 18-15). Our results demonstrate improved reusability and flexibility, supported by feature modeling, variant generation, and a modular architecture. This work highlights the practical benefits of SPL in real-world applications.

Switched impulsive integro-delay dynamic system and its controllability

We investigate the controllability properties of implicit impulsive switched Volterra–Fredholm–Hammerstein integro-delay dynamic system on arbitrary time domain using time scale theory. This pioneering study explores novel controllability results for such complex systems, emphasising the crucial role of controllability in control design. We establish comprehensive controllability results, including controllability at impulsive points and interval endpoints, by leveraging time scale theory, operator algebra theory and Banach fixed-point theory. Theoretical and simulated examples are given on a specific time domain to demonstrate the practical applicability and consequences of our conclusion, showcasing their potential in real-world control systems. This research advances the understanding of controllability in complex dynamic systems, paving the way for further investigations and applications in diverse fields.

New variants and genotype-phenotype correlation in KIF5A mutation: the contribution of a large Italian cohort.

Variants in the Kinesin-family member 5A (KIF5A) gene are associated with a range of motor diseases, and a strong correlation between the protein domains (motor, stalk and tail) and the clinical phenotype has been proposed. However, several studies have reported exceptions contributing to a complex genotype-phenotype correlation in recent years. Further studies are needed to improve our knowledge about the prevalence of KIF5A variants and their genotype-phenotype correlation. 390 patients (220 hereditary spastic paraplegia, 80 Charcot-Marie-Tooth disease type 2 and 90 amyotrophic lateral sclerosis) have been selected for next-generation sequencing Clinical Exome. Five patients have been found to carry causative variants in the KIF5A gene. Of these, three are familiar cases, and two are sporadic. Segregation analysis was performed on the familiar probands. The five patients with pathogenic variants represent 4% of the studied population, and the clinical and genetic analysis of these five families allowed us to examine different scenarios.Some of these data support the hypothesis of a complex correlation between domains and disease. These data confirm the complex genotype-phenotype correlation, both in terms of clinical heterogeneity associated with a specific domain and variability within the members of the same family, but also suggest a strong genotype-phenotype correlation, both intrafamiliar and interfamiliar, produced by a few variants.

Ethics regulation and sociology in France

The French research ecosystem long resisted extending the ethics regulation processes established for biomedical science into the social sciences. This is now changing. This history of resistance is examined, together with the alternatives proposed. These include self-regulation by professional associations. Consideration is also given to the wider legal environment for French social sciences, particularly the laws on defamation and privacy, which also influence the opportunities for research and for the pursuit of grievances by participants. The introduction of ethics regulation, through IRB-style committees in universities and research organizations, reflects isomorphic pressures from the international research community, reinforced by the impact of the European Union’s General Data Protection Regulations (GDPR) on the application of national privacy law. Nevertheless, outside the specific domain of health-related research, ethics regulation still sits more lightly on French social science than in the anglosphere.

Exploring the 9- layered Model for Emotional Intelligence

Emotional intelligence has been a topic, which revolves around a lot of controversy. Many authors have their own viewpoint of explaining, their own definition of EI. However, it has been most researched area in the field of Humanities and Social Sciences. As it covers emotions, cognitive process, it is also included in the field of psychology. EI can be considered now-a-days, as an own subject matter, as is it not only confined to any specific domain, rather, it spread its roots even to every domain of human life, wherever, emotions play an important role. To understand the nature of an individual, it is quite essential that we must understand how that person manages and control his or her emotions in the given circumstances. This paper, is therefore, an attempt to understand the emotions, at every step of human intelligence. The study includes the pioneering work undertaken by various researchers, which can form the basis for corporate as well as academic excellence.

How Students Feel and How They Regulate Motivation Matter in a Writing Class

ABSTRACT Despite the proliferation of studies on the effects of emotions on academic performance, their impact in the specific domain of writing is underexplored. This study examined students’ writing performance in relation to positive and negative emotions, motivational beliefs of self-efficacy and task value, and regulation of emotion and motivation. Situated in an undergraduate writing course, longitudinal data were collected over the span of a semester. Participants were 44 undergraduate students who completed self-reported surveys after each of the five major writing assignments. Results revealed that the overall writing performance was predicted by between-individual differences in positive emotions and motivation regulation, as well as by within-individual differences in motivation regulation. Furthermore, an interaction effect was detected among negative emotions, self-efficacy and task value. These findings underscore the importance of the motivational and affective components in the writing process. Implications for improving writing performance are discussed.

SYNTACTIC RELATIONS IN NOUN-NOUN MODEL OF COMPOUND TERMS RELATED TO TRANSPORT SHPERE IN ENGLISH AND UZBEK LANGUAGES

Compound terms are important features of any specific domain. This is also true for transport sphere. The article illustrates the syntactic relations of transport terms between English and Uzbek languages. Particularly, these relations are analyzed in the model of noun-noun connection. Three ways of this connections in both languages are analyzed and highlighted with relevant examples. Keywords: Transport Sphere, Terminology, Terms, Syntactics, Noun-Noun Model, Word Formation.

Protecting Privacy in Software Logs: What Should Be Anonymized?

Software logs, generated during the runtime of software systems, are essential for various development and analysis activities, such as anomaly detection and failure diagnosis. However, the presence of sensitive information in these logs poses significant privacy concerns, particularly regarding Personally Identifiable Information (PII) and quasi-identifiers that could lead to re-identification risks. While general data privacy has been extensively studied, the specific domain of privacy in software logs remains underexplored, with inconsistent definitions of sensitivity and a lack of standardized guidelines for anonymization. To mitigate this gap, this study offers a comprehensive analysis of privacy in software logs from multiple perspectives. We start by performing an analysis of 25 publicly available log datasets to identify potentially sensitive attributes. Based on the result of this step, we focus on three perspectives: privacy regulations, research literature, and industry practices. We first analyze key data privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) , to understand the legal requirements concerning sensitive information in logs. Second, we conduct a systematic literature review to identify common privacy attributes and practices in log anonymization, revealing gaps in existing approaches. Finally, we survey 45 industry professionals to capture practical insights on log anonymization practices. Our findings shed light on various perspectives of log privacy and reveal industry challenges, such as technical and efficiency issues while highlighting the need for standardized guidelines. By combining insights from regulatory, academic, and industry perspectives, our study aims to provide a clearer framework for identifying and protecting sensitive information in software logs.

Leveraging a Systems Approach for Immigrant Integration: Fostering Agile, Resilient, and Sustainable Organizational Governance

Effectively managing immigrant workforces presents a significant contemporary challenge for organizations operating in a globalized world. Current management practices often fall short, failing to adequately address the complex interplay of social issues, cultural and linguistic distances, and the valuable human capital immigrants possess. This paper proposes a theoretically developed conceptual model for immigrant management, synthesized from a comprehensive review of systems theory, migration studies, and organizational governance literature. The model advances systems theory by operationalizing its core tenets—interdependence, feedback loops, and holistic perspective—into a practical governance framework for the specific domain of immigrant workforce integration, demonstrating the theory’s applicability to complex socio-organizational challenges. It outlines six interdependent subsystems—from needs assessment to end-of-work transitions. While conceptual, this paper lays a robust foundation for future empirical research by providing testable propositions regarding the efficacy of its subsystems and their impact on integration outcomes. It calls for empirical validation of the proposed relationships and the model’s overall effectiveness in diverse organizational contexts. By adopting this structured yet adaptable framework, organizations can move towards more agile governance practices in human resource management, allowing for iterative adjustments and fostering more resilient and sustainable immigrant integration. This approach directly contributes to addressing immigrant integration issues by offering a holistic, actionable framework that moves beyond piecemeal solutions, thereby enhancing organizational capability and promoting positive societal impact.

Socioeconomic and Racial/Ethnic Disparities in Sleep and Cognitive and Academic Functioning Across Childhood and Adolescence: A Meta-Analytic Review.

Youth from socioeconomically disadvantaged backgrounds and minoritized racial/ethnic groups face a greater risk for sleep disparities and poor cognitive/academic outcomes compared to their peers from higher socioeconomic status (SES) and majority racial/ethnic groups. This meta-analysis has two main objectives. First, it examined SES and racial/ethnic variables as moderators of the association between individual sleep parameters (i.e., objective duration, objective quality, subjective duration, subjective quality, schedule/chronobiology, and variability/consistency) and overall (i.e., combined assessment) cognitive/academic outcomes (e.g., memory, GPA). Second, it assessed sleep parameter and outcome domain as moderators of the association between sleep broadly (i.e., no distinction between various sleep parameters) and overall cognitive/academic outcomes to test whether the magnitude of the association varied across specific sleep parameters and outcome domain. Thirty-three studies comprising 410 effect sizes and 52 854 participants were included. The meta-analysis was conducted per best practices. For sleep and cognitive functioning, the overall weighted effect was r = .11, 95% CI [.08, .14], p<.001. Several significant differential associations between various sleep parameters and cognitive functioning emerged, showing some parameters were stronger predictors. Academic performance yielded similar results, with an overall weighted effect size of r = .14, 95% CI [.10, .17], p<.001. SES and race/ethnicity also modified relations between certain sleep parameters and cognitive/academic functioning. The findings provide evidence for SES and race/ethnicity-related disparities, highlighting areas requiring further investigation. The discussion addresses methodological limitations in studying SES and race/ethnicity in relation to sleep and offers future research directions.

The Development of Violence Research in Psychiatric Nursing: A Bibliometric Perspective.

There is a growing emphasis on violence-related research in psychiatric nursing, with an annual increase rate of 2.12% in publications and the highest number of publications occurring in 2024. This trend underscores the escalating importance of addressing violence in mental health settings. This study aims to demonstrate the quantitative and qualitative features of violence publications in the field of psychiatric nursing from a bibliometric perspective. Web of Science was used during the research. This study employed bibliometric analysis, a methodological approach for delineating the scope of information and assessing productivity within a specific domain. The data were searched with the keyword combination 'violence and psychiatric nursing', including studies published until December 2024, the study date, without a time limit. In this study, 464 violence research/reviews in the field of nursing were identified between 2001 and 2025, and the research was completed with 438 violence studies in line with the exclusion criteria. 1493 authors wrote 390 research and 48 review/systematic review articles, with an average of 22.14 citations for each publication. Most were published in 2024. There is an apparent increase in the involvement of psychiatric nurses in studies pertaining to violence. It is proposed that nursing professionals should undertake further research to investigate violence processes and develop ethically sound approaches to patients and healthy individuals, taking into account biopsychosocial factors. These findings collectively suggest that while progress is being made in understanding and addressing violence in psychiatric nursing, there remains a critical need for ongoing research, policy development and practical interventions to ensure the safety and well-being of both nurses and patients in mental health settings.

An Overview of Health Informatics and Health Science Librarians' Role

Abstract: Health informatics focused on specific domain knowledge whereas Librarianship structured on generic subject areas. The health Science Librarians should acquire, exchange, organize and share knowledge. The skills required are acquire and preserve knowledge resources for future use and requires to understanding of both biomedicine and information science. The health Informatics specialists requires to have the domain knowledge in addition to health science librarianship. This paper highlights the role of Health science Librarians in Health informatics.

Ferroelastic writing of crystal directions in oxide thin films.

Crystals often have complex structural domains, but a general method to remove or deterministically control such local heterogeneity is lacking. The resulting heterogeneity in crystal orientations obscures our understanding of material properties and can reduce the reliability and performance of related applications. Here, using shear stress from an atomic force microscope tip, we ferroelastically write local crystal orientations in oxide thin films. Applying this deterministic and reversible control to SrRuO3 and (La0.7Sr0.3)(Mn0.9Ru0.1)O3 films, we realize twin-free single crystals and design specific crystal-orientation domain textures at the nanoscale. Furthermore, through magnetoelastic coupling, we can mechanically manipulate the local magnetic anisotropy, and thereby write and erase functional nanoscale magnetic textures unattainable by conventional methods. Thus, pure mechanical force emerges as a means to control structural heterogeneity on demand and may make it possible to program electronic and spintronic functionalities.

Protocol of a collaborative evaluation systematized non-systematic reviews by “DESCreview”, a Design tool for Evaluating risk of bias/quality in Systematized and sCoping reviews

Background. Reproducible reviews that have a systematized approach, such as scoping, mapping, rapid, and other non-systematic reviews (henceforth, referred to as Scoping et al. reviews), have become a necessary step in a wide range of observational studies for public health research. Nevertheless, the quality of such Scoping et al. reviews is never questioned or evaluated. We propose a general-purpose tool for assessing the quality and risk of bias of Scoping et al. reviews, using a collaborative evaluation.MethodsThis Scoping et al. reviews tool (DESCreview, Design tool for Evaluating risk of bias/quality in Systematized and sCoping reviews) consists of a nine-domain assessment with four possible probabilities of quality. It includes the following domains in three parts: (A) Items applicable to all Scoping et al. reviews (Selection of papers; Classification; Extraction; Conflict of interest; Specific domain relevant to the question); (B) Items applicable to some Scoping et al. reviews (Preregistration and protocol difference, Risk of bias); and (C) Items only applicable for systematic reviews (Meta-analysis (if applicable), Strength of evidence). Each of the nine domains is rated from “Very high quality with low risk of bias” to “Very low quality with high risk of bias”. The overall confidence is assigned by combining all the nine domains into an overall strength rated: high, moderate, low, critically low. These four categories would be included in the review as the “calibration”. We also propose a collaborative evaluation, involving all potentially interested colleagues, using an online questionnaire. In the absence of a reference method, the validation study will be based on a comparison with AMSTAR-2, and feedback from user experience resulting in the production of a paper after one year of testing.DiscussionDESCreview allow simple general-purpose tool for assessing the quality and risk of bias of systematized review in occupational and public health. The originality also lies in the collaborative validation process.