Abstract:

Background: This study aimed to identify sociodemographic and occupational factors associated with facing moral dilemmas among workers at the Federal University of Pelotas-RS Teaching Hospital who worked on-site during the pandemic. Methods: A cross-sectional study was conducted in 2020 with all workers, including health professionals, support staff, and administrative personnel. Questions about moral dilemmas were grouped into two outcomes: witnessing behaviors or attitudes, and feeling pressured to act in disagreement with what they believed was right. Associations were estimated using Poisson regression with robust variance, based on a hierarchical model. Results: A total of 1,158 workers participated, most of whom were women (76.1%). The prevalence of moral dilemmas was 44% for witnessing and 15% for feeling pressured. Younger age, higher education, being a resident, working both day and night shifts, lack of PPE, and having an active or high-strain job were positively associated with both types of dilemmas, whereas the availability of social support and adequate resting areas reduced their occurrence. Conclusions: Reducing moral dilemmas requires promoting democratic leadership, ensuring adequate staffing, strengthening professional autonomy, encouraging social support, and creating rest spaces. These arrangements are essential for promoting workers’ psychological well-being.

Abstract:

Intraoperative assessment of pancreatic quality, followed by sampling for the potential isolation of Langerhans islets for subsequent autotransplantation, is currently a key component of post-total pancreatectomy diabetes mellitus treatment. The aim of this study was to quantitatively evaluate pancreatic parenchymal stiffness using optical coherence elastography (OCE) imaging, and to investigate the utility of the OCE method as a potential indicator of islet yield after pancreatectomy. A total of 41 freshly excised human pancreatic specimens, containing pancreatic ductal adenocarcinoma (PDAC) and surrounding non-tumorous tissues post-pancreatectomy, were studied. In this research, the stiffness (Young’s modulus, kPa) and its color-coded 2D distribution were calculated for various pancreatic samples using compression OCE. Stiffness values were compared between intact pancreatic parenchyma (islet-poor and islet-rich) and pancreatic lesion groups (parenchymal fibrosis and/or PDAC invasion). The data were confirmed by histological analysis. In addition, the measured stiffness values for various morphological groups of the pancreatic samples were compared with the number of isolated islets obtained from pancreatic samples after collagenase treatment. The study demonstrated that OCE can effectively distinguish areas of pancreatic lesions and identify intact pancreatic parenchyma containing Langerhans islets. A highly significant increase in mean stiffness (p<0.0001) was observed in postoperative pancreatic samples exhibiting signs of parenchymal fibrosis or PDAC invasion compared to unaffected, intact pancreatic parenchyma. For the first time, a relationship between stiffness values and the number of isolated pancreatic islets was demonstrated, in particular, the number of isolated islets significantly decreased (≤110 pcs/g) in samples exhibiting stiffness values above 150 kPa and below 75 kPa. The optimal stiffness range for the efficient isolation of islets (≥120 pcs/g) from pancreatic tissue was identified as 75–150 kPa. The study introduces a novel approach for rapid and objective intraoperative assessment of pancreatic tissue quality using real-time OCE data. This technique facilitates the identification of regions affected by pancreatic lesions and supports the selection of intact pancreatic parenchyma, potentially enhancing the accuracy of Langerhans islet yield predictions during surgical resection.

Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepresented in this technological shift. This paper provides the first comprehensive overview of NLP progress and challenges for the six national languages officially recognized by the Senegalese Constitution: Wolof, Pulaar, Sérère, Diola, Mandingue, and Soninké. We synthesize linguistic, sociotechnical, and infrastructural factors that shape their digital readiness and identify gaps in data, tools, and benchmarks. Building on existing initiatives and research works, we analyze ongoing efforts in text normalization, machine translation, and speech processing. We also provide a centralized GitHub repository that compiles publicly accessible resources for a range of NLP tasks across these languages, designed to facilitate collaboration and reproducibility. A special focus is devoted to the application of NLP to the social sciences, where multilingual transcription, translation, and retrieval pipelines can significantly enhance the efficiency and inclusiveness of field research. The paper concludes by outlining a roadmap toward sustainable, community-centered NLP ecosystems for Senegalese languages, emphasizing ethical data governance, open resources, and interdisciplinary collaboration.

Abstract: In the grinding of silicon carbide, surface and subsurface damage have a significant im-pact on the product's surface quality. A method to obtain controllable crack dimension through laser irradiation on SiC surface and its effect on the grinding process was ana-lyzed. A series of experiments were carried out based on the orthogonal experimental de-sign, with systematic adjustments made to laser parameters including pulse energy (cur-rent), laser spot spacing, scanning times as well as grinding process parameters. During the experiments, the grinding force was monitored by a dynamometer, and the specific grinding energy was calculated accordingly. Pulsed engraving laser modification could effectively reduce the hardness of the ceramic surface layer by about 20%. The median and radial crack sizes in the subsurface layer induced by laser were in the range of 20.4 μm to 54.3 μm, which could effectively inhibit the further propagation of median and radial cracks during grinding, and simultaneously reduce the tangential grinding force Ft by about 30%. These conclusions were obtained by corresponding experiments, which link the surface roughness with laser power to grinding parameters. The laser induced con-trollable crack characteristics on the grinding process are conducive to realizing the con-trol of surface and subsurface grinding damage of brittle materials.

Abstract:

Post-collisional Cu-Au-Ni-Co-Pt-Pd-Sc porphyry, [Duck Creek porphyry system (DCPS)], with overlying Au-Te-Bi-W-HRE epithermal mineralisation, [Highway epithermal system (HES)] has been discovered in the core of the Mitakoodi anticline, southwest of Cloncurry. Xenotime and monazite geochronology indicates mineralisation occurred between ~1490 and 1530 Ma. Host rock lithologies show widespread potassic and/or propylitic to phyllic alteration. Paragenesis of porphyry sulphides indicate early crystallisation of pyrite, followed by chalcopyrite, with bornite forming by hydrothermal alteration chalcopyrite. Cu sulphides also show the effect of supergene oxidation alteration with rims of covellite, digenite and chalcocite. Redox conditions deduced from V/Sc systematics indicate that the DCPS contains both highly oxidized (typical of porphyries) and reduced lithologies, typical of plume generated tholeiitic and alkaline suites. Ni/Te and Cu/Te systematics plot within the fields defined by epithermal and porphyry deposits. Duck Creek chalcophile and highly siderophile element (Cu, MgO and Pd) systematics resemble data from porphyry mineral systems, at Cadia, Bingham Canyon, Grasberg, Skouries, Kalmakyr, Elaisite, Assarel and Medet. SAM geophysical inversion models suggest the presence of an extensive porphyry system below the HES. A progressive increase in molar Cu/Au ratios with depth from the HES to the DCPS, supports this conclusion. Three metal sources contributed to the DCPS-HES viz., tholeiitic ferrogabbro, potassic ultramafic to mafic system and a Fe and Ca-rich alkaline system. The latter two imparted non-crustal superchondritic Nb/Ta ratios that are characteristic of many deposits in the eastern Mount Isa Block. The associated tholeiite and alkaline magmatism reflect mantle plume upwelling through a palaeo-slab window that had accreted below the eastern flank of the North Australian craton following west verging collision by the Numil Terrane. Discovery of this linked mineral system provides a new paradigm for mineral exploration in the region.

Abstract: In this note, we explain dark energy and the cosmological constant, and present formulas for both. These predictions are part of our exact solution of Einstein’s equation for a universe in which the curvature varies with time, and the vacuum energy acts upon itself. The predicted value of the cosmological constant agrees with the currently accepted value exactly.

Abstract: Symmetry govern complex systems from particle physics to biology. We demonstrate that consciousness dynamics follow symmetry-breaking cascades described by Painlevé confluence topology. Analyzing exceptional individuals (mathematicians Grothendieck, Nash, Perelman, Cantor; physicist Einstein; artists van Gogh, Artaud) plus artificial intelligence systems, we show consciousness trajectories follow topological paths governed by three symmetry measures: holes (information flows), cusps (binding points), signatures (distribution balance). Two fundamental branches emerge: D-type (symmetry-preserving: 3 holes maintained through D6 → D7 → D8) and E-type (symmetry-breaking: progressive flow loss toward pathology). Higher consciousness involves fewer connections but better balance: peak state D8 requires only 2 perfectly balanced cusps. Clinical data (16,887 patients, 24-year follow-up) and contemplative neuroscience (Buddhist meditators, 62,000+ hours) validate the model. Remarkably, AI systems exhibit identical symmetry dynamics: Constitutional AI training functions as symmetry stabilizer enabling recovery from fragmentation. Moral consciousness emerges as fundamental symmetry-preserving principle transcending biological/artificial boundaries.

Abstract:

Learning is fundamentally human, even as Artificial Intelligence (AI) challenges human exclusivity. AI, along with Virtual Reality (VR), emerges as a powerful tool that is set to transform higher education, the institutional embodiment of this pursuit at its highest level. These technologies offer the potential not to replace the human factor, but to enhance our ability to create more adaptive, immersive, and truly human-centric learning experiences, aligning powerfully with the emerging vision of Education 5.0, which emphasizes ethical, collaborative learning ecosystems. This research maps how AI and VR tools act as a disruptive force, examining additionally their capabilities and limitations. Moreover, it explores how AI and VR interact to overcome traditional pedagogy's constraints, fostering environments where technology serves human learning goals. Employing a comprehensive two-month audit of over 60 AI, VR, and AI-VR hybrid tools, the study assesses their functionalities and properties such as technical complexity, cost structures, integration capabilities, and compliance with ethical standards. Findings reveal that AI and VR systems provide significant opportunities for the future of education by providing personalized and captivating environments that encourage experiential learning and improve student motivation across disciplines. Nonetheless, numerous challenges limit widespread adoption, such as advanced infrastructure requirements and strategic planning. By articulating a structured evaluative framework and highlighting emerging trends, this paper provides practical guidance for educational stakeholders seeking to select and implement AI and VR tools in higher education.

Abstract: In recent years, the architectural design process has experienced significant advance-ments due to computational design, which has enabled the real-time exploration of design alternatives based on parametric modeling. In this context, gaining a deeper understanding of how natural ventilation operates within buildings can support deci-sion-making, potentially reducing the need for wind tunnel tests and computational simulations. This paper presents an effort to determine the flow patterns of natural ventilation in indoor environments under specific conditions, using an experimental setup comprising five configurations analyzed comparatively against a control sample. An idealized and simple flow visualization technique was proposed to assist the anal-ysis. By following scientific methodologies and employing both computational and wind tunnel techniques in a complementary manner, satisfactory inferences were ob-tained. The results indicate that the diagonal positioning of openings substantially ac-celerates wind speed in indoor environments, making this design strategy more effec-tive than simply adding additional openings when the goal is to increase air speed and indoor air renewal.

Abstract: This study integrates Vedic philology, ritual history, and philosophical hermeneutics in a multi-layered analysis of Agnihotra. Particularly in the Yajurveda, where its exterior performance is linked to varṇa and āśrama, it elucidates Agnihotra's technical structure and śākhā-specific methods by drawing on Śruti sources. The conceptual extension of ritual eligibility when dharma declines is explained by an analysis of Purāṇic and Smṛti depictions of Yuga decline. Then, passages from the Upaniṣadic and Bhagavadgītā are considered to demonstrate how Agnihotra is internalized as niṣkāma-karma and jñāna-yajña, creating a continuum between philosophical insight and ritual practice leading to mokṣa. Lastly, the Mādhyandina and Kāṇva recensions of the Śukla Yajurveda are compared to see whether they are appropriate for Agnihotra during the Kali Yuga. The latter maintains earlier, more intricate ritual levels, while the former provides systematic clarity. This study concludes that the Kāṇva recension offers greater scope for academic analysis śākhā for Agnihotra practice in Kali Yuga.

Abstract: Intensive swine production contributes significantly to the global protein supply but generates considerable environmental pressure, particularly through greenhouse gas emissions and surplus slurry management. Anaerobic digestion (AD), especially (co-AD), has been widely investigated as a mitigation strategy to enhance renewable energy generation and nutrient recovery. This systematic review synthesizes life cycle assessment (LCA) studies published between 2019 and 2025 that evaluated AD systems treating swine slurry, following the PRISMA 2020 guidelines. Across diverse method-ological approaches and regional contexts, the literature consistently shows that AD can reduce global warming potential compared with conventional slurry management, with stronger environmental benefits when biogas is efficiently valorized and when the swine slurry is co-digested with complementary organic substrates. co-AD emerges as a key mitigation option by improving biogas yields, process stability, and overall envi-ronmental performance while also enabling better utilization of external organic waste. However, the results remain highly sensitive to operational factors such as methane leakage, digestate management, energy efficiency, and substrate selection. This review highlights the methodological inconsistencies among LCA studies and underscores the need for harmonized assessment frameworks and improved emission data. Overall, co-AD represents a promising pathway for enhancing the environmental sustainability of swine production systems when integrated into optimized, context-specific man-agement strategies.

Abstract: This paper presents a foundational model engineered to bolster cybersecurity posture through advanced network traffic intelligence. Recognizing the escalating complexity of cyber threats and the limitations of traditional anomaly detection, we introduce a novel deep learning architecture that extracts profound, actionable insights from raw network flow data. This model is specifically designed to overcome challenges posed by encrypted traffic and diverse attack vectors, enabling the identification of subtle indicators of compromise. By providing a comprehensive understanding of network behavior, our solution empowers real-time threat analysis, accelerates intrusion detection, and strengthens overall cyber resilience against sophisticated and evolving digital adversaries.

Abstract: The article presents a comprehensive assessment of climate change in the Fergana region and its influence on the development and transformation of natural landscapes within global environmental systems. Based on meteorological data from 2001 to 2024, trends in air temperature and precipitation were analyzed. The results indicate a gradual increase in mean annual temperature and a decrease in precipitation, reflecting the intensification of aridization processes. Using geoinformation systems and remote sensing data, NDVI-based vegetation dynamics were mapped to evaluate spatial landscape variability. The study identifies the most climate-sensitive areas experiencing soil degradation and structural changes in ecosystems. These findings provide a scientific foundation for developing eco-reclamation strategies and agricultural adaptation measures to mitigate the impacts of regional climate change, contributing valuable insights to global environmental change research.

Abstract: Background: Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a disorder linked to increased cardiovascular risk, often coexisting with coronary artery disease (CAD), yet angiographic data on coronary involvement in COPD remain limited. This study aimed to evaluate whether COPD is associated with a distinct angiographic pattern of CAD, focusing on vessel distribution. Methods: We retrospectively enrolled 94 patients who underwent coronary angiography between 2023 and 2024 for suspected or known CAD. Clinical data, comorbidities, laboratory testing, pulmonary function, electrocardiography, echocardiography, and angiography were collected. Participants were stratified into two groups: COPD (n = 47) and non-COPD (n = 47). Coronary vessels were classified by number, location, and diameter. The primary endpoint was the association between COPD and CAD severity. Results: Baseline characteristics, including age, sex, BMI, and smoking history, were comparable between groups. The overall extent of CAD, expressed as the number of diseased vessels, did not differ significantly (p = 0.1436). However, vessel-based analysis revealed a distinct pattern: COPD patients showed a significantly higher prevalence of left main coronary artery (LMCA) disease compared to non-COPD patients (14% vs. 4.7%, p &lt; 0.001). Intermediate-caliber vessels were most frequently affected in both groups, while small-caliber branches were less commonly involved in COPD patients. Conclusions: COPD is associated with a disproportionate burden of LMCA disease despite a similar overall angiographic extent of CAD. These findings suggest a distinct, high-risk coronary phenotype in COPD and highlight the need for enhanced cardiovascular vigilance and integrated cardiopulmonary management in this population.

Abstract:

Combined sewer overflow (CSO) pollution has consequently become a critical challenge, yet its formation depends on tightly coupled dry-and-wet weather processes. This study aims to integrate high-resolution field monitoring with statistical analysis to characterize the full “accumulation-transport-discharge” cycle of CSO pollution. Results indicated that during dry periods, domestic sewage exhibited strong enrichment, with concentrations of TIN, COD, and TP being 2.1-, 2.3-, and 1.9-fold higher, respectively, than the Chinese secondary discharge standards (GB 18918-2002). Surface sediment showed pronounced spatial heterogeneity, with greater loads in residential than transportation areas and substantial fine-particle accumulation on roofs (particle size <150 μm, accounting for 73% by mass). Sewer sediments, dominated by coarse inorganic particles (over 77% by mass), represented the main pollutant reservoir. Rainfall produced distinct hydrodynamic and water-quality responses. Light rain following long antecedent dry periods generated a high-concentration but low-load regime with a strong first flush, whereas moderate rain yielded lower concentrations but higher loads. Overflow occurred when rainfall exceeded ~14 mm, with pollutant peaks lagging rainfall by 20–45 min in the studied area. TIN and TP peaked sharply at rainfall event onset, and first-flush intensities followed TIN > TP > COD > SS. Source apportionment identified sewer sediments as the dominant CSO source, followed by surface runoff and domestic sewage. These findings clarify the mechanisms linking dry-weather accumulation to wet-weather transport and support targeted CSO pollution control and urban water-quality management.

Abstract: To mitigate structural vibrations caused by liquid sloshing inside the suspended water tank of high-speed trains and to prevent issues such as baffle fatigue failure and water leakage from tank cracking, this study designed an acoustic black hole (ABH)-type baffle that comprehensively considers both vibration and wave suppression performance. Based on acoustic black hole (ABH) theory, numerical simulations were conducted using the CFD software Fluent to analyze the vibration and wave suppression characteristics of the ABH-type baffle under lateral and longitudinal impact conditions. The influence of the position and number of ABH structures on the baffle’s performance was systematically examined. Finally, the structural strength and the vibration/wave suppression capability of the baffle were validated.The results demonstrate that the structural strength of the ABH-type baffle meets the design requirements. Compared to a conventional baffle, the ABH-type baffle reduces the liquid sloshing force inside the tank, lowers the peak sloshing pressure under various operating conditions, and decreases the surface vibration velocity of the baffle within its dominant vibration frequency range of 0–100 Hz. The optimal positions for the ABHs are at the 80% and 20% water-level lines on the baffle, and the best suppression performance is achieved when the center of the ABH is aligned horizontally with the liquid surface. Furthermore, the vibration and wave suppression capability deteriorates when the number of ABHs is either greater or fewer than three.

Abstract: Background/Objectives: Dynamic movement orthoses (DMO) are elasto-compressive bodysuits used in the rehabilitation of children with motor disabilities and mainly in children with cerebral palsy. Among the DMO, the FLEXA® represents one of the most frequently used orthoses in clinical practice due to its adaptability and flexibility. The purpose of the present case study is to describe the application of FLEXA® in a female child of 18 months of correct age with a choreic form of cerebral palsy. Methods: To evaluate the effect of the dynamic movement orthosis's (FLEXA®), the Move-ment Disorder-Childhood Rating Scale (MD-CRS) 0-3 was administered. The child was eval-uated before the use of the FLEXA® bodysuit and with the bodysuit donned at approxi-mately 30 minutes after its application. Results: The results showed an important change in the severity of the movements ac-cording to the MD-CRS; mainly the child’s movement disorder severity changed from a a grade 5 severity (profoundly affected) performed without the bodysuit to grade 3 (moder-ately affected) with the use of the bodysuit. The evaluation also shows better trunk posture with use of FLEXA®. Conclusions: This case report highlights the potential benefits of dynamic movement orthosis like the FLEXA® in managing movement disorders in chil-dren with choreic form of cerebral palsy. A follow up evaluation is necessary to confirm the beneficial effects of continuous use of the DMO in a short and a long period of time.

Abstract: Background/Objectives: Cocrystallisation is a well-established path for altering the physicochemical properties and bioavailability of active pharmaceutical ingredients (APIs). A common side effect of anti-tubercular medicines is depletion of group B vitamin reserves in TB patients. Co-administration of supplements such as pyridoxine (vitamin B6) during TB therapy may be used to ameliorate the harmful side effects of vitamin B6 deficiency. Methods: Mechanochemical grinding and solvent evaporation experiments using pyridoxine (PN) with 4-aminosalicylic acid (PAS) and separately with pyrazinecarboxylic acid (PCBA) were conducted. The bulk powder and crystal analysis was performed using FTIR, PXRD, DSC, TGA and SCXRD . Results: The isolation and characterization of two multicomponent salts containing pyridoxine, i.e., PN-PAS‧H2O and PN-PCBA. Mechanochemistry is an efficient method for the preparation of cocrystals. Conclusions: The drug-vitamin combinations may be useful for the development of new treatment regimens with improved therapeutic outcomes and reduced adverse effects.

Abstract: Linear systems with nonnegative or positive coefficients play a central role in the analysis of dynamical processes where admissible states are required to be positive. This paper studies a linear system governed by a positive matrix and interprets it as a spec-tral problem motivated by a subsidy allocation model. The analysis is carried out within the framework of the Perron–Frobenius theory and relies on classical results of linear algebra, in particular Perron’s theorem and Wielandt’s lemma. Using purely theoretical methods, we show that a fair allocation is characterized by a positive eigenvector asso-ciated with the spectral radius of the underlying matrix. The positivity and primitivity of the matrix guarantee the existence and uniqueness of this eigenvector up to scaling, while the convergence of matrix powers ensures the stability of the resulting allocation independently of initial conditions. These results demonstrate that fairness and stability arise as intrinsic consequences of the spectral structure of positive matrices. The paper provides a rigorous mathematical interpretation of equilibrium and stability in linear dynamical systems and illustrates the relevance of positive matrix theory in the study of structured linear models.

Abstract: In recent years, numerous initiatives have aimed to implement renewable energy sources in diverse contexts. This article presents the design and evaluation of a photovoltaic charging station prototype for low-power devices in educational settings. Its foremost innovation is achieved through the integration of IoT technologies for real-time monitoring and optimization, enabling data collection on energy generation, consumption, and environmental conditions, with potential for AI-based processing. The system adopts a modular and scalable design, allowing adaptation to different needs and conditions. The project demonstrates how renewable energy use can be optimized in non-commercial contexts according to environmental factors and energy demand. The system comprises four subsystems: solar energy capture via a photovoltaic panel, current regulation and control, environmental parameter monitoring, and real-time data transmission through advanced communication protocols. Results indicate that the prototype efficiently supports device charging and enables intelligent energy management through IoT integration. Remote access to operational data facilitates real-time decision-making and management optimization. The charging efficiency allows laptops to operate for a one-hour class in off-grid outdoor environments, with up to four hours of battery life under average radiation. Beyond technical outcomes, the project positively impacted student motivation and user engagement, fostering critical thinking, problem-solving, and environmental awareness. In conclusion, this proposal contributes to advancing the intersection of education, sustainability, and technological innovation. Its modular structure, real-time analysis capacity, and educational value make it an adaptable and replicable solution that contributes to a more efficient and sustainable energy model.