Enterococcus faecium can cause severe infections and is often resistant to the first-line antibiotic ampicillin. Consequently, clinicians usually prescribe broad-spectrum antibiotics, promoting the selection of multidrug-resistant bacteria. We investigated whether machine learning models can detect ampicillin susceptibility directly from MALDI-TOF/MS to enable earlier optimised treatment in ampicillin-susceptible E. faecium infections. Two datasets of clinical E. faecium MALDI-TOF spectra and their resistance phenotype were analysed: our own Technical University of Munich (TUM) dataset and the publicly available MS-UMG dataset. We evaluated logistic regression (LR) and Light gradient boosting machine (GBM) models and explored transferability including a target-domain-adapted external validation. Discriminatory MALDI-TOF peaks were investigated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). LightGBM slightly outperformed LR in identifying ampicillin-susceptible isolates in both datasets (area under the precision-recall curve 0.907 ± 0.016 vs. 0.902 ± 0.030 for TUM; 0.902 ± 0.029 vs. 0.899 ± 0.054 for MS-UMG). Target-domain-adapted training demonstrated good transferability of LightGBM models (area under the precision-recall curve of 0.869 ± 0.013 when trained on TUM plus 30% MS-UMG, tested on the remaining 70% MS-UMG). SHapley Additive exPlanations (SHAP) analysis consistently identified a MALDI-TOF spectral peak at m/z ≈ 5091 as the most discriminative, which LC-MS/MS analysis mapped to bacteriocin T8. LightGBM and LR models can identify ampicillin-susceptible E. faecium isolates from MALDI-TOF spectra and generalise well to unseen datasets. Bacteriocin T8 serves as a key discriminatory feature associated with ampicillin resistance. While clinical implementation currently still requires confirmatory testing, the addition of larger datasets will support the development of more robust machine learning models.

The ubiquity of generative artificial intelligence (AI) in higher education presents both opportunities and significant pedagogical challenges. In graphic communication design, students increasingly rely on AI to conduct research, prepare presentations, generate design concepts, and produce videos—tasks traditionally requiring competence in computer-aided design (CAD) software. While these tools can enhance productivity, some students use them in ways that bypass learning, submitting AI-generated work without understanding underlying design principles or technical vocabulary. This study reports a qualitative case study conducted at Tamale Technical University in Northern Ghana, where 38 third-year graphic design students completed two presentation-based assessments requiring oral defense of their work. The study addressed three questions: (1) To what extent do students use generative AI in ways that hinder learning? (2) What patterns of terminology deficit, inconsistency, and anxiety emerge during oral defense? (3) How do students perceive the effectiveness of presentation-based assessment? Findings indicate that 81.6% of students used AI extensively, 89.5% could not define basic terminology from their own submissions, and 71.1% showed inconsistencies between submitted work and oral explanation. Despite initial anxiety, 71.1% reported that presentation-based assessment improved their learning. The study offers context-specific recommendations for design educators, including structuring interactive presentations, formulating probing questions, and clearly distinguishing between permitted and unethical AI use. It suggests that oral defense can reveal learning gaps, while treating claims about detecting unethical AI use cautiously and acknowledging alternative explanations such as language anxiety and prior instruction.

The article discusses the pedagogical aspects of integrating mathematical methods of signal analysis into the training of technical university students in the context of modern energy-efficient technologies and Internet of Things (IoT) systems. The relevance of the study is due to the growing demands on engineers to be able to work with large amounts of real data, perform analytical processing, and make informed engineering decisions in the field of computer-integrated heating control systems for “smart homes.” Particular attention is paid to the problem of insufficient practical orientation of teaching mathematical disciplines in technical education and the gap between theoretical knowledge and real engineering tasks. The purpose of the article is to justify and experimentally verify a step-by-step methodology for teaching student’s mathematical methods of analyzing heating parameters based on real IoT data using Fourier and wavelet transforms. The work applies competency-based, interdisciplinary, and practice-oriented approaches to teaching. The proposed methodology involves a sequential transition from the analysis of time temperature signals to spectral and time-frequency analysis, with the subsequent use of the results obtained to optimize the operation of heating systems. The article defines a list of key mathematical methods necessary for analyzing heating parameters in IoT systems and establishes their connection with specific laboratory work. A complete cycle of classes based on real or near-real data from a “smart home” is described. Considerable attention is paid to the physical and engineering interpretation of the spectral characteristics of temperature signals, which contributes to the formation of systematic engineering thinking in students. The pedagogical effectiveness of the methodology is confirmed by the results of an experimental study using quantitative indicators: levels of professional competence, results of educational testing, and assessment of practical skills. The data obtained indicate a statistically significant increase in the level of student training, an improvement in the quality of mastery of mathematical methods, and the ability to apply them to solve real engineering problems in the field of energy-efficient IoT systems.

Orientation: South African higher education institutions, including technical and vocational education and training (TVET) colleges, face persistent challenges in retaining skilled employees, with turnover intentions undermining work engagement, well-being and institutional performance. Research purpose: This study examined the factors influencing administrative staff retention at a public TVET college in Mpumalanga, South Africa. Motivation for the study: Research on employee retention in TVET colleges has largely overlooked administrative staff. Addressing this gap provides insights into an often-neglected workforce critical to institutional stability. Research design, approach and method: A quantitative, descriptive design was employed, using a stratified sample of 119 administrative employees at Nkangala TVET College. Data were collected through a structured, closed-ended questionnaire. Reliability was confirmed with Cronbach’s alpha, and Pearson’s correlations tested variable relationships. Main findings: Rewards and recognition, job security and career development significantly predict employee retention, while job satisfaction and performance appraisal were statistically insignificant. Practical/managerial implications: To retain administrative staff, TVET colleges should prioritise rewards and recognition as the strongest driver, alongside career development and job security, rather than relying on job satisfaction or performance appraisal. Contribution/value added: The study advances the understanding of administrative employee retention in South African TVET colleges and informs the development of evidence-based strategies to strengthen workforce stability in the sector.

At the current stage of the development of higher education, increasing importance is given to the development of entrepreneurial skills and innovations. At the same time, there are no established and widely applied methods for evaluating universities in terms of the entrepreneurship developed in them. Due to the identification of this problem, this article examines the policies and efforts of the European Union countries in relation to the promotion of entrepreneurship in education as a tool for achieving sustainable economic growth, striving for innovation and increasing the competencies of human resources. Various tools for improving entrepreneurial skills, improving the quality of education and thus increasing the competitiveness of EU member states are analysed. A hierarchical system and model for evaluating European Entrepreneurial Universities is proposed, which would support their effective functioning and adaptation to the conditions of a circular economy. Criteria for assessing entrepreneurial capacity are proposed, and three technical universities from Bulgaria are studied. The proposed model is verified by evaluating three leading Bulgarian universities. The results of the verification are presented.

The research aimed to create a hybrid model for assessing the carbon footprint of pilots’ education at a flight school, taking into account the level of implementation of green infrastructure by the educational institution, while excluding indirect emissions from the model. The study implemented an approach that combines fuzzy set theory with expert evaluation methods, utilizing membership functions and convolution mechanisms to incorporate subjective expert assessments into formalized numerical measures. The research was focused on two research questions: Does the proposed hybrid model allow for a practical assessment of a pilot’s carbon footprint during his training? Does the hybrid model provide the ability to automatically determine the level of carbon footprint of an aviation educational institution and generate substantiated recommendations for the strategic management of sustainable development of the educational process? The resulting model enables a quantitative assessment of individual CO2 emissions during pilot training and provides collective insights into the overall carbon footprint, accounting for the green infrastructure’s level of implementation. The hybrid model was tested and validated using real data from the Technical University of Košice (Slovakia) within the “PILOT” study program (2022–2025). The experimental calculations are based on the Viper SD4, a homogeneous aircraft type. The model is designed to account for multiple aircraft types through weighted aggregation, a feature that can be used in future institutional implementations. These recommendations are practical for managers and specialists at aviation educational institutions, environmental analysts, curriculum developers, and policymakers focused on sustainable development. At the current stage, the model primarily captures direct training-related and institution-level operational emissions, while indirect emissions were included only to a limited extent because of insufficiently available and non-systematically recorded data. Therefore, the proposed framework should be interpreted as an operational decision-support model rather than a full greenhouse gas inventory covering all indirect emission sources.

Developing an Integrity Policy for a Technical University: The Case of TU Delft.

This study examined the effect of forensic accounting techniques on fraud detection in universities in Ibadan, Oyo State, Nigeria. The study was motivated by persistent financial irregularities, including misappropriation of funds, falsified documents, and inaccurate financial reporting, despite the existence of conventional auditing systems. The aim was to determine the influence of data mining tools, document examination techniques, and ratio and trend analysis on fraud detection. A descriptive survey research design was adopted. The population comprised 398 accountants and audit staff drawn from three universities: University of Ibadan, Ajimobi Technical University, and Dominican University. Using Taro Yamane’s formula at a 0.05 margin of error, a sample size of 200 was determined through stratified purposive sampling. Data were collected using a structured questionnaire validated by experts and pilot-tested. Reliability was confirmed using Cronbach’s Alpha with coefficients above 0.70. Data were analyzed using descriptive statistics and simple linear regression in SPSS (Version 25) at a 0.05 significance level. The findings revealed that data mining tools had a significant positive effect on reducing financial irregularities (R = .368, R² = .136, F(1,193) = 30.299, p < .001, β = .368). However, document examination techniques (R² = .004, p = .382) and ratio and trend analysis (R² = .004, p = .381) did not show significant effects. The study concluded that technology-driven forensic tools were more effective in fraud detection than traditional analytical approaches within the sampled universities. It was recommended that universities prioritize investment in data mining technologies, strengthen staff capacity in forensic accounting, and develop integrated forensic frameworks to enhance fraud detection and financial transparency.

The study looked into the impacts of computer tutorial teaching techniques and three-dimensional (3D) computer animation on the interest of students in Delta State, Nigeria's technical colleges in Motor Vehicle Mechanics Work (MVMW). A quasi-experimental research design was adopted, guided by two hypotheses and two research questions. The population comprised of 157 final-year (Vocational III) technical college students offering MVMW, all of whom were purposively selected and grouped into two intact classes (A and B). Data were gathered with the Motor Vehicle Mechanics Work Interest Inventory Test (MVMWIIT), which three experts from Nigerian universities in the field of Technical Education verified. The instrument's dependability was determined utilizing the Cronbach alpha method, yielding a coefficient of 0.70. Results showed a notable variation in students’ interest mean scores between those instruced utilizing computer tutorials and those instructed using 3D computer animation, indicating the effectiveness of the teaching methods. Nevertheless, there exists no discernible disparity between the interest levels among male and female students that received the two instructional techniques. Based on these findings, the study suggestrs the integration of 3D computer animation and computer tutorial methods into the MVMW curriculum to enhance students’ interest in technical colleges across Delta State and Nigeria.

The paper describes the life of the famous Russian scientist in the field of thermal engineering, higher school teacher, Doctor of Technical Sciences, Professor Vladimir Iosifovich Evenko (1916 - 2008). During the Great Patriotic War, he participated in the labor front. From 1952 to 1998, he worked at Bryansk Institute of Transport Engineering - Bryansk State Technical University as an associate professor, professor, and head of the Department of Thermal Engineering (1963 - 1969, 1984 - 1987), Internal Combustion Engines (1973 - 1983). He is the founder of a scientific school in the field of thermal engineering.

Background: Aneurysmal bone cyst (ABC) is a benign but locally aggressive bone lesion. USP6 gene rearrangements have been proposed as a key diagnostic marker, detectable via fluorescence in situ hybridization (FISH). However, its clinical utility and correlation with recurrence remains unclear. This study evaluates USP6 FISH as a diagnostic tool and investigates whether USP6 positivity is associated with an increased recurrence risk. Materials & methods: This retrospective study analyzed 87 patients with primary ABC at Klinikum rechts der Isar, Technical University of Munich (1991–2021). Histopathological and radiological criteria were used for diagnosis, with USP6 FISH testing performed on available specimens. Statistical analyses, including Kaplan–Meier recurrence estimates and Cox regression were conducted to assess the association between USP6 status and recurrence. Conclusion: USP6 FISH is a highly specific but moderately sensitive tool for diagnosing primary ABC. While a positive USP6 result supports the diagnosis, clinical and histopathological correlation remains essential. Importantly, USP6 positivity showed no significant correlation with recurrence, suggesting that surgical factors play a larger role. These findings confirm the diagnostic relevance of USP6 FISH but indicate that recurrence risk should be assessed independently of molecular status.

The development of digital technologies in the economic and social spheres has transformed the requirements for higher education graduates and increased demand for interdisciplinary digital competencies. At the same time, local solutions implemented by individual universities do not always ensure alignment between educational content and the practical needs of professional environments, which highlights the importance of interuniversity coordination mechanisms. This article examines interuniversity mechanisms for the formation of digital competencies based on a STEM-oriented educational ecosystem in digital medicine, implemented within the joint «ITMedicine» program of Abylkas Saginov Karaganda Technical University and Karaganda Medical University. The objective of the study is to identify institutional mechanisms of interuniversity interaction and to determine their role in aligning educational programs with professional requirements. The research is grounded in the ecosystem approach and an institutional-analytical interpretation of data obtained from an expert survey of employers (n = 35) and university instructors (n = 70); respondents were allowed to select multiple answer options. A SWOT analysis was applied to systematize factors influencing the sustainability of the interuniversity model. The findings demonstrate that the sustainability of digital competency formation depends not only on curricular updates but also on institutionally embedded coordination mechanisms, including alignment of curricula and competency matrices, distribution of responsibilities between universities, and integration of employers into practice-oriented training formats. The conclusions may be used in designing interuniversity programs and developing network-based coordination mechanisms in higher education systems, including the adaptation of similar models in the Russian context.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease with a significant impact on a patient's daily life, negatively affecting numerous psychological and physical aspects. Thus, patients with HS may be at elevated risk of developing addictive disorders. We therefore aimed to evaluate the prevalence of the most common addictions and psychiatric comorbidities among patients with HS. This questionnaire-based pilot study was conducted between January and October 2021 at the Department of Dermatology and Allergology, School of Medicine and Health, Technical University of Munich, Germany. Demographics, disease severity, quality of life, presence of depression and anxiety, addictions including smoking habits, alcohol consumption, consumption of illicit drugs and prescription drugs, cannabis consumption, gambling, internet and food addiction were recorded. A total of 120 patients (48.3% female, 51.7% male; mean age 39.3 ± 13.2years) with HS were included. Most patients suffered from mild HS. Screening results for at least one addiction were positive in 71.7% of the participants, while smoking was most prevalent (60.0%), followed by pathological alcohol consumption (18.3%), food addiction (18.3%) and cannabis addiction (15.0%). Moreover, positive screening rates were 13.3% for addiction to illicit drugs or prescription medication, 12.5% for internet addiction and 5% for gambling. Using multivariate logistic regression, the correlation of patients' characteristics with addictive disorders was determined. Younger patients were more susceptible to internet, cannabis and food addiction. Food addiction was more prevalent in patients with an increased BMI. Addiction to illicit drugs or prescription medication was associated with anxiety. Strikingly, numerous addictions were recorded in patients with HS, even in those with mild disease severity. Thus, addictions in patients with HS should be addressed in time by physicians to provide early patient-centred health care.

Background Self-regulation of learning is a key consideration in the process of acquiring workplace competences. One key assumption of self-regulated learning in the literature is that the learner themself is undertaking a process of learning. However, in adult and vocational educational settings it is common that tasks may be either individual or cooperative. Theoretically, self-regulatory demands are different when applied to different learning forms, such as an individual task vs a cooperative learning task; but to date there is a dearth of empirical studies in this regard. Method Part of the CADCoM2024 + study on measuring CAD and FEM competences at EQF 6, the present study was conducted with 175 students from four mechanical engineering technical colleges in Germany. Through quantitative analysis we compared progression in CAD and FEM competency development in two learning approaches: individual self-regulated learning vs cooperative self-regulated learning. Results Strict invariance was partially present in both cross-sectional and longitudinal analyses. The differences in mean values suggest that there was strong learning progression in both individual self-regulated learning and cooperative self-regulated learning treatment groups. Interestingly, progression in FEM competency was better through cooperative self-regulated learning; however, progression in CAD competency was better through individual self-regulated learning. This latter finding was surprising given that students had demonstrated that they could work well together cooperatively, as shown in the FEM learning tasks. Conclusion This original interdisciplinary study suggests that skills for both individual and cooperative self-regulated learning are important for optimally acquiring workplace competences. Indeed, an important finding from this original study was that both individual and cooperative self-regulated learning are recommended as learning strategies: students made strong progress in competency development in both learning forms. Whether individual self-regulated learning or cooperative self-regulated learning is chosen as a pedagogical strategy for fostering workplace competences may depend on a variety of factors (such as interest, previous experience, social environment, and nature of the task). Further studies, including studies with larger sample sizes, are required to unpick this complexity and to confirm which factors might influence the pedagogical choice between individual and cooperative self-regulated learning strategies for competency development.

This case study examines the role of higher education institutions as regional economic anchors in the Kenyan coastal region. Focusing on Pwani University (PU) and the Technical University of Mombasa (TUM), the research analyzes how their transition to fully chartered universities in 2013 has catalyzed urban transformation, human capital development, and infrastructure development. Utilizing a qualitative comparative case study design and documentary analysis including the Auditor-General’s reports and County Integrated Development Plans, the study identifies a significant "multiplier effect" despite institutional financial challenges. Findings suggest that these universities stabilize local economies against seasonal fluctuations in tourism and provide the research infrastructure necessary for Kenya’s Blue Economy. Despite extensive research on Kenyan universities, limited research has been done to examine universities as economic anchors in the coastal region. The paper concludes by recommending the establishment of similar university anchors across all coastal counties to mitigate regional inequality. Keywords: Regional Development, Higher Education, Anchor Institutions, Blue Economy, Case Study.

Abstract Unsuitable physical environments are increasingly recognised not just as a nuisance, but also as a significant determinant in the pathophysiology of sleep disorders and chronic illness. According to the literature, even little environmental changes can have a significant impact on sleep homeostasis: persistent exposure to background noise above 30 decibels causes autonomic arousal associated to cardiovascular disease, but even low-level artificial light (5–10 lux) suppresses melatonin and disrupts metabolic homeostasis. When paired with thermal stress outside the ideal 18–21 $$^\circ $$ ∘ C, window or ventilation deficiencies enabling carbon dioxide to increase over 1,000 ppm, these environmental stressors affect sleep architecture and impede long-term cognitive recovery. This paper introduces an innovative approach to automatically regulating environmental conditions to ensure proper sleep. This approach leverages an integrated framework of model predictive control, fuzzy logic, and reinforcement learning. To validate this deterministic approach, the study utilises a high-fidelity digital twin of student accommodations at the Mărăşti Student Campus of the Technical University of Cluj-Napoca. Experimental results demonstrate that the proposed Meta-Controller significantly enhances physiological outcomes, yielding a notable 10.06% improvement in objective sleep quality metrics and a 5.41% reduction in health risk indicators associated with sleep deprivation. By achieving an optimised sleep score in 99.24% of cases, the study underscores the efficacy of merging heuristic logic with predictive and adaptive control paradigms. This work provides a pioneering contribution to the field of cyber-physical systems, laying a robust foundation for future advancements in environmental modelling and the development of intelligent, health-centric living spaces through advanced system dynamics.

The purpose of this article is to identify and analyse the characteristics of the development of the material and technical resources of technical universities in the process of their creation and development in the 1930s. The research was conducted within the context of industrialisation and higher education reforms in the USSR, with a focus on identifying common trends and specific features characteristic of railway-profile universities in Siberia. Two railway transport educational institutions were selected as the subject of the study: Tomsk Electromechanical Institute of Railway Transport Engineers (TEIRTE) and Novosibirsk Institute of Military Transport Engineers (NIMTE), which were under the jurisdiction of the People’s Commissariat for Railways. For the purpose of comparative analysis, several other educational institutions in the USSR under the jurisdiction of various departments were also considered. The research was based on the following methods: domain-specific/chronological, historical/descriptive, legal/technical, analogy-based, and generalisation. The research focused on the key areas of economic and administrative activity of the aforementioned educational institutions from the moment of their foundation in 1932 until the early 1940s. Given the quantitative growth of institutions after the reform of higher technical education, the primary problem was the formation of their material and technical facilities. The problems associated with the period of organisation were quite tangible throughout the first decade: there was a shortage of premises, classrooms, laboratories, and necessary equipment. The institutes also faced the problem of a shortage of dormitories and their poor domestic arrangements. Funding for technical universities was provided by the departments to which they were transferred. At the same time, all educational institutions faced a shortage of allocated funds. The analysis draws on the materials from the general-circulation newspapers published by TEIRTE and NIMTE, entitled «Quality Orientation» and «Transport Servicemen», periodicals, the works by scholars exploring the history of universities and their economic activities, as well as the documents from the State Archive of the Tomsk Region, Tomsk Regional Centre for Documentation of Contemporary History, and Central State Archive of Historical-Political Documents of St. Petersburg.

This paper substantiates the pedagogical potential of the Adaptive Digital Learning Route Method in teaching the course “Information Technologies in Technical Systems” at technical universities. The study addresses the problem of heterogeneity in students’ academic preparedness, digital competence, and readiness for independent engineering-oriented learning. The proposed method is based on personalization, level differentiation, continuous diagnostics, route flexibility, and digital pedagogical support. The research applies theoretical analysis, pedagogical modeling, structural design, and methodological generalization to develop the conceptual and procedural foundations of the method. The method includes five interrelated stages: diagnostic-orientation, profiling, route design, corrective-developmental support, and reflective-evaluative assessment. Its implementation is expected to improve students’ motivation, increase the quality of mastering theoretical and practical content, strengthen independent learning skills, and enhance professional readiness in the field of information technologies in technical systems. The study contributes to the theory and methodology of professional education by proposing a route-based adaptive model specifically designed for engineering disciplines.

The article contains a summary prepared by the direction of the organizing committee of the traditional International Scientific and Practical Conference of the Tajik Technical University named after Academician M.S. Osimi” Science is the basis of innovative development", regarding the commentary of the conference title. Much attention is paid to the role of science in the development of modern society, especially in the development of its economic activities. The article presents assumptions about the transformation of science into an independent and effective branch of the economy in modern society. It highlights the need for widespread use of scientific achievements to achieve Tajikistan's strategic goals. Keywords: culture, economy, science, productive forces, methods of production, automation, artificial intelligence.

<p><strong>Context and relevance.</strong> The practice of inclusive higher education in the context of digitalization needs up-to-date data on the higher mental functions of students with disabilities. The theoretical basis for the research was the cultural and historical theory of the development of higher mental functions and modern studies on its characteristics in hearing disorders. <strong>Objective.</strong> To identify the interrelationships of verbal and non-verbal mental actions among students with hearing impairments and differences in their indicators at the beginning and end of a semester. <strong>Hypotheses.</strong> There are significant differences in the interrelationships of verbal and non-verbal mental actions among students with hearing impairments with different types of auditory perception. There are significant differences in the indicators of verbal and non-verbal thinking of students with hearing impairments and with disabilities of other nosology at the beginning and at the end of the semester. <strong>Methods and materials.</strong> The study involved 57 undergraduate technical university students with disabilities (M = 18.8; SD = 4.2; 23% of women). To study verbal and non-verbal thinking, a test was used, composed of 6 subtests from ASTUR and supplemented with 3 subtests from WAIS by D. Wechsler and R. Amthauer’s Test. <strong>Results.</strong> Significant differences in correlations of indicators of verbal and non-verbal thinking of students with visual-auditory and auditory-visual types of information perception have been revealed. Indicators of verbal and non-verbal thinking of students with hearing disabilities are significantly lower at the end of the semester, unlike students with disabilities of other nosologies. <strong>Conclusions.</strong> The possibilities of applying research results to design educational content and pedagogical techniques for teaching technical subjects to students with hearing impairments are shown. Recommendations are formulated for the inclusion in the curriculum of educational practices of techniques aimed at mastering students with hearing disabilities their cognitive functions, as well as psychological relief techniques.</p>