Search Results (283,954)

This cross-sectional study explores the connections between resilience, work engagement, proactive strategies and personal resources among Italian kindergarten and primary school teachers. It specifically seeks to determine if and how personal resources can foster teachers’ work engagement, resilience, and proactive strategies at work. The study was conducted using a sample of 183 full-time, in-service kindergarten and primary teachers at public schools in Italy. Data were collected through self-report questionnaires, including the Brief Resilience Scale, the Ultra-Short Measure for Work Engagement, the Proactive Strategy scale, the Self-Compassion Scale, the Life Orientation Test-Revised, the Experienced compassion at work scale. Data were analyzed using a path analysis model. Results indicated that teachers’ self-compassion was positively associated with the use of proactive strategies and perceived received compassion was strongly related to work engagement. Moreover, higher levels of self-compassion were linked to greater work engagement. Teachers’ optimism and self-compassion were both positively associated with resilience, whereas self-criticism showed a significant negative association. Our research supports the need for educational policymakers and school leaders to focus on personal resources and work-related well-being. Full article

Understanding the chronic thermal acclimation capacity of chum salmon (Oncorhynchus keta) is essential for predicting species resilience and developing mitigation strategies under ocean warming. We investigated the upper limit of chronic thermal acclimation and its underlying molecular mechanisms in chum salmon smolts exposed to four constant temperatures (10, 14, 18, and 22 °C) for 6 weeks. Transcriptional responses of genes related to cellular stress protection, endocrine feedback regulation, antioxidant defense, metabolic regulation (AMPKα and mTOR), and protein degradation were quantified in the liver, skeletal muscle, and brain. Chronic exposure to elevated temperature elicited tissue-specific molecular responses, with the most pronounced effects observed at 22 °C. At this temperature, all tissues showed marked induction of heat shock proteins and ubiquitin, accompanied by suppression of antioxidant defenses, glucocorticoid receptor signaling, and AMPKα–mTOR-mediated metabolic regulation, particularly in the liver and muscle. These responses were consistent with previously reported impairments in growth performance, lipid reserves, and hematological indices from the same growth trial. In contrast, smolts maintained at 18 °C exhibited molecular signatures indicative of effective physiological compensation without severe cellular stress. Collectively, these results indicate that chum salmon smolts can acclimate to chronic warming up to 18 °C, whereas exposure to 22 °C exceeds their acclimation capacity and induces a tertiary stress response. Full article

Background: Ketamine and magnesium sulfate are commonly used perioperatively to prevent shivering, a frequent and clinically relevant complication of spinal and general anesthesia. Although their hypothermic effects are well documented, the neurotransmitter mechanisms underlying these effects remain insufficiently understood. This study examines whether serotonergic, adrenergic (α₂), and GABAergic (GABA_A) systems contribute to hypothermia induced by ketamine and a ketamine–magnesium sulfate combination. Methods: Body temperature was measured in Wistar rats after administration of ketamine (10 mg/kg) or the ketamine (5 mg/kg)–magnesium sulfate (5 mg/kg) combination. To assess neurotransmitter involvement, animals received yohimbine (α₂ antagonist), methysergide (non-selective 5-HT antagonist), or bicuculline (GABA_A antagonist) prior to ketamine or the drug combination. Data were analyzed using two-way repeated measures ANOVA followed by Tukey’s post hoc test. Results: Yohimbine at 0.5 and 1 mg/kg significantly potentiated ketamine-induced hypothermia, while only 3 mg/kg enhanced the effect of the ketamine–magnesium sulfate combination. Methysergide had a bidirectional influence: 1 mg/kg methysergide deepened ketamine-induced hypothermia, whereas 0.5 mg/kg methysergide attenuated the hypothermic effect of the ketamine–magnesium sulfate combination. Bicuculline (1–2 mg/kg) did not alter the hypothermic responses to ketamine or the combination. Conclusions: These findings indicate that ketamine- and ketamine–magnesium sulfate-induced hypothermia is primarily modulated by serotonergic and adrenergic mechanisms, whereas GABA_A receptor-dependent pathways do not appear to play a major role under the experimental conditions used. These results provide new mechanistic insights into NMDA antagonist–related thermoregulation and may help inform anesthetic strategies for shivering prevention and maintenance of perioperative thermal stability. Full article

One thermodynamic parameter that is crucial to heat transport within the fluidized bed inside the rotary kiln, during clinker production, is the specific heat capacity. The particular parameter is often considered constant in the open literature, while, in reality, it strongly depends on the fluidized bed’s temperature and composition, considering that the temperature inside the kiln ranges from approx. 800 K up to 2000 K. For the current study, a mixing rule reported in the literature was applied in order to calculate the C_p of the fluidized bed, utilizing temperature and composition profiles available in the literature. An in-house code was developed for the comparison of the literature-reported C_ps and those resulting from the mixing rule. It was discovered that the C_p of the fluidized bed had a proportional increase with the increase in the temperature along the length of the kiln. The deviation between the two values (calculated and literature) is relatively small in some cases, whereas, in others, it is quite significant, ranging from 1.56% to 52.49%, thus making the adoption of the temperature-dependence of C_p necessary. Establishing a more accurate relation for the specific heat capacity leads to a better energy balance inside the kiln, which, along with other improvements, can lead to a decrease in the energy consumed and a significant reduction in greenhouse gas emissions. Full article

Background/Objectives: While most patients resume sports within one year after total knee arthroplasty (TKA), data on whether patients achieve their desired level of sports activity remain limited. This study aimed to evaluate the relationship between desired sports activity levels and postoperative outcomes after TKA and to identify factors associated with achieving the desired activity level. Methods: This retrospective cohort study included 280 patients (63.9% female; mean age, 65.7 years) who underwent primary TKA with a mean follow-up of 28.2 months. The University of California and Los Angeles (UCLA) activity score was used pre- and postoperatively to assess the desired and the achieved activity level. Results: The mean UCLA activity score improved significantly after surgery (from 4.6 to 5.6; p < 0.001). However, the mean preoperative desired UCLA score was significantly higher than the mean postoperative achieved UCLA score (7.1 vs. 5.6; p < 0.001). Overall, 34.6% of patients reached their desired activity level. These patients demonstrated a significantly lower preoperative desired UCLA score (6.1 vs. 7.6; p < 0.001) and a higher postoperative achieved UCLA score (6.7 vs. 5.0; p < 0.001) compared with patients who did not. Male sex, higher preoperative UCLA scores, and lower preoperative desired UCLA scores were identified as independent predictors of achieving the desired activity level. Conclusions: The present study demonstrated that despite excellent Knee Society function and WOMAC scores only 1/3 of patients reach their sport-related desired activity level. Surgeons must ensure that they communicate realistic expectations to patients prior to surgery, in order to avoid dissatisfaction that may arise from unmet expectations. Full article

User-generated content (UGC) plays a central role in social commerce. However, existing knowledge remains theoretically fragmented across constructs, perspectives, and empirical contexts. To address this gap, this study conducts a systematic review of 60 peer-reviewed studies published between 2014 and 2024, following PRISMA 2020 guidelines. It develops an integrative conceptual perspective structured around five key dimensions: trust, authenticity, perceived risk, engagement, and loyalty. The findings demonstrate that UGC influences consumer decision-making primarily through mediating psychological and social mechanisms, including trust, satisfaction, perceived value, social presence, and community identification. At the same time, perceived risk remains insufficiently theorized, and comprehensive multi-dimensional models remain scarce in the literature. The study advances social commerce theory by consolidating fragmented evidence into a coherent conceptual framework. It also explicitly foregrounds the central explanatory role of mediating mechanisms in UGC effects. From a practical perspective, the findings highlight the strategic importance of fostering authentic and trustworthy UGC. This supports sustainable consumer–brand relationships and long-term value creation within digital platform ecosystems. The review has limitations related to database coverage and language restrictions, which may have led to the omission of relevant studies. Full article

Photovoltaic (PV) cells play an important role in the development of green energy. However, in practical photovoltaic systems, shunting-related defects and hotspot phenomena may originate not only from manufacturing imperfections, but also from mechanical stress and environmental factors during transportation, installation, and long-term field operation. Such hotspots not only reduce the power-generation efficiency and service life of PV cells but may also pose safety risks to grid-connected photovoltaic power stations. To address this problem, a squared even-order derivative (SEOD) method based on surface temperature analysis is introduced to enable the quantitative detection of thermal defects in PV cells. In this study, typical faults in PV cells, including low-resistance defects and silicon-based deep scratches, are analyzed. A simulation model is established to correlate typical faults with their equivalent volumetric heat sources, followed by experimental validation for low-resistance defects. Based on this framework, the SEOD algorithm is developed and applied to achieve high-precision localization and quantitative characterization of thermal defects in both simulation models and experimental samples. Full article

Background/Objectives: Telomere dysfunction and the shelterin complex are implicated in cancer, yet the specific functions and interactions of telomerase and shelterin genes in hepatocellular carcinoma (HCC) tumorigenesis remain poorly understood. This study aims to investigate the clinico-biological functions and collaborative contributions of telomerase and shelterin components in hepatocarcinogenesis. Methods: We analyzed tumor and matched non-tumor tissues from 274 HCC patients who underwent hepatectomy. Telomere-related parameters, including TERT (telomerase reverse transcriptase) expression and telomere length measured by qRT-PCR, telomerase activity assessed by the Telomerase Repeated Amplification Protocol assay, and six shelterin components analyzed by RNA sequencing, were correlated with clinicopathological features. siRNA-mediated knockdown of TPP1 (POT1–TIN2 organizing protein) was performed to evaluate its regulatory effect on TERT expression. Findings were externally validated. Results: TERT and TPP1 were upregulated in tumors with increased telomerase activity and shortened telomere length. Among the shelterin components, TPP1 showed the strongest correlation with TERT, and its expression increased with tumor multiplicity and advancing stage. TPP1 expression also correlated with proliferation-associated genes, consistent with Gene Set Enrichment Analysis suggesting TPP1 involvement in proliferative activity. TPP1 knockdown suppressed TERT protein expression and inhibited HCC cell proliferation, with the strongest anti-proliferative effect observed after dual TERT–TPP1 knockdown. Clinically, high TPP1 expression was associated with significantly earlier HCC recurrence, and co-high expression of TPP1–TERT was linked to significantly worse survival after hepatectomy. Conclusions: The TERT–TPP1 axis enhances proliferative activity and is associated with aggressive features and poor outcomes in HCC. TPP1 represents a potential therapeutic target and prognostic biomarker for HCC. Full article

Morbid obesity is a complex, multifactorial disorder characterized by metabolic and inflammatory dysregulation. The aim of this study was to observe changes in obese patients adhering to a personalized nutrition plan based on multi-omic data. This study included 14 adult patients with a body mass index (BMI) > 40 kg/m² who were consecutively recruited from those presenting to our outpatient clinic and who met the inclusion criteria. Clinical, biochemical, hormonal, and glycomic parameters were assessed, along with whole-genome sequencing (WGS) that included a focused analysis of obesity-associated genes and an extended analysis encompassing genes related to cardiometabolic disorders, hereditary cancer risk, and nutrigenetic profiles. Patients were stratified into nutrigenetic clusters using a patented unsupervised machine learning platform (German Patent Office, No. DE 20 2025 101 197 U1), which was employed to generate personalized nutrigenetic dietary recommendations for patients with morbid obesity to follow over a six-month period. At baseline, participants exhibited elevated glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), triglycerides, and C-reactive protein (CRP) levels, consistent with insulin resistance and chronic low-grade inflammation. The majority of participants harbored risk alleles within the fat mass and obesity-associated gene (FTO) and the interleukin-6 gene (IL-6), together with multiple additional significant variants identified across more than 40 genes implicated in metabolic regulation and nutritional status. Using an AI-driven clustering model, these genetic polymorphisms delineated a uniform cluster of patients with morbid obesity. The mean GlycanAge index (56 ± 12.45 years) substantially exceeded chronological age (32 ± 9.62 years), indicating accelerated biological aging. Following a six-month personalized nutrigenetic dietary intervention, significant reductions were observed in both BMI (from 52.09 ± 7.41 to 34.6 ± 9.06 kg/m², p < 0.01) and GlycanAge index (from 56 ± 12.45 to 48 ± 14.83 years, p < 0.01). Morbid obesity is characterized by a pro-inflammatory and metabolically adverse molecular signature reflected in accelerated glycomic aging. Personalized nutrigenetic dietary interventions, derived from AI-driven analysis of whole-genome sequencing (WGS) data, effectively reduced both BMI and biological age markers, supporting integrative multi-omics and machine learning approaches as promising tools in precision-based obesity management. Full article

Unmanned Aircraft Systems (UASs) offer a promising future for aviation operations, even though it suffers larger cyber-related challenges. As such, cyber-resilience becomes a core property for drones’ operations. This paper presents a systematic meta-review of the scientific literature on Unmanned Aircraft Systems cyber-resilience, starting from 28 literature reviews and surveys in the field. This study examines three areas: the typologies of cyber threats being investigated, the cyber-resilience aspects and functions, and how proposed mitigation strategies align with and support these resilience functions. Overall, 69 cyber threats were identified, where Global Positioning System (GPS) spoofing and jamming were the most frequent ones, underscoring the vulnerability of GPS-based navigation systems in UAS. In terms of cyber-resilience functions, the largest focus remains on the identification, protection, and detection of cyber threats, while limited attention emerges to incident handling and post-event recovery. This is confirmed by the higher frequency of preventive, rather than recovery-oriented, mitigation strategies. Overall, the findings point towards a still limited cyber-resilience implementation for Unmanned Aircraft Systems, witnessing the need for more systemic efforts to guarantee truly resilient UAS operations. Full article

Nahj al-Balāghah is widely recognized as a foundational and authoritative scripture in Shia Islam. One notable aspect of Nahj al-Balāghah is the deliberate selection and structured arrangement of Ḥadiths. According to the book’s introduction, al-Raḍī explains that he chose the Ḥadiths based on literary considerations. An analysis comparing the selected Ḥadiths with their full versions suggests their inclusion was determined not only by eloquence and rhetorical value but also by conceptual significance. Through textual and descriptive analytical methods, this study examines the author’s motives, especially his political and religious aims, in incorporating materials related to ʿĀisha. A comparison of the relevant ḥadīths in Nahj al-Balāghah and other historical sources indicates that Sayyid Raḍī omitted—or at least refrained from including—certain statements attributed to ʿAlī regarding the Prophet Muḥammad’s youngest wife. The omitted parts concern ʿĀisha’s inconsiderate behavior, grudges, sins, following Satan, and ignoring the Prophet’s prediction. Considering sectarian conflicts between Shiites and Sunnis in the 3rd and 4th centuries AH, some arising from criticisms of ʿĀisha’s conduct and sometimes escalating into violence, al-Raḍī, the supreme judge appointed by the ʿAbbāsid Caliphate, was compelled to omit and censor ʿAli’s harsh remarks about ʿĀisha to prevent further sectarian tensions. Full article

Cardiac pacing has undergone a significant transformation in the last decade. Leadless pacing (LP), once only a conceptual idea stemming from the early interest in eliminating lead-related complications of transvenous pacemakers, has now become a reality in clinical practice. Since the introduction of the first human single-chamber asynchronous leadless ventricular pacing in 2012, atrioventricular-synchronized single- or dual-chamber leadless pacing systems have been approved for clinical use since 2020. Leadless cardiac resynchronization therapy (CRT) has shown optimistic results in case series and awaits its full utility in real-world clinical practice. With the successful feasibility study of leadless conduction system pacing, we are eagerly awaiting long-term safety and efficacy data on a large scale. Another important frontier is the development of self-rechargeable LP, which may be an ideal pacemaker for the future and may reduce the burden of multiple device replacements as batteries near the end-of-service. Totally extravascular percutaneous leadless pericardial micro-pacemaker system implantation is under development. In this state-of-the-art review, we examine the evolution of cardiac pacing, emphasizing the development and utility of LP to meet maximum physiological pacing needs, optimize atrioventricular synchrony and cardiac resynchronization, and broaden its indications. Full article

The Collatz map is investigated from a nonlinear-dynamics perspective with emphasis on the structure of its iterative orbits. By embedding integers within Sharkovsky’s ordering, odd initial values are shown to be sufficient for a complete characterization of dynamics. A “direction-phase” decomposition is introduced to separate iterative orbits into upward and downward phases, yielding a family of recursive functions parameterized by the number of upward phases. This formulation reveals a logarithmic scaling relation between the total iteration count and the initial value, confirming finite-time convergence to the period-three orbit. The Collatz dynamics is further shown to be dynamically equivalent to a binary shift map, whose ergodicity implies inevitable evolution toward attractors, thereby reinforcing convergence. Numerical analysis indicates that attraction basins follow a power-law distribution and display pronounced self-similarity. Moreover, odd integers grouped by upward-phase counts are found to follow Gamma statistics. Beyond its research implications, the framework provides a concise pedagogical case study illustrating how nonlinear dynamics, symbolic dynamics, and statistical characterization can be integrated to analyze a classical discrete problem. Full article

Understanding how environmental conditions shape the functional composition of ecological communities is a central goal in community ecology. In this study, we apply this framework to the reptile and amphibian assemblages within Greece’s Mount Chelmos protected area. Based on comprehensive field surveys (2018–2021) across 168 sampling stations, we compiled species trait databases and quantified functional diversity using a corrected Rao’s Q index. We modeled the response of functional diversity to climate, land cover, topography (altitude, slope, aspect), geographic location, and taxonomic diversity, using Generalized Additive Models (GAMs). Additionally, we examined traitspace structure via PCA and evaluated environmental drivers of trait composition with multivariate GAMs. For reptiles, functional diversity was significantly affected by altitude, climate, and aspect, with higher values predicted in water-associated marginal zones surrounding the mountain massif. Traitspace analysis revealed clear ecological structuring along axes related to locomotion, body size, reproductive mode, foraging strategy, and substrate use, shaped by distinct combinations of environmental filters. In amphibians, environmental effects on functional diversity were not statistically significant; however, traitspace showed discernible responses to land cover, climate, and aspect, suggesting weaker—though detectable—filtering processes. Collectively, our findings indicate that Mount Chelmos functions as a system that modulates diversity, with environmental filters operating at fine-to-medium spatial scales to shape the functional composition and diversity of its herpetofauna. Full article

Roadside public transport stops represent localized air pollution hotspots where short-term exposure may differ substantially from levels reported by urban background monitoring. This study investigates the application of low-cost air quality sensors for long-term characterization of particulate matter and gaseous pollutants in a traffic-dominated urban microenvironment. The novelty of this work lies in the combined use of collocated low-cost sensors, energy-independent solar-powered deployment, height-resolved placement representative of different breathing zones, and integrated statistical and predictive analysis to resolve exposure-relevant pollutant dynamics at a single transport stop. Hourly concentrations of particulate matter (PM) PM₁, PM₂.₅, PM₁₀, nitrogen dioxide (NO₂), and ozone (O₃) were measured over one year at a roadside transport stop adjacent to a four-lane urban road carrying approximately 30,000 vehicles per day. Measurements were obtained using two collocated low-cost sensor units based on optical particle sensing for particulate matter and electrochemical sensing for gases, together with concurrent meteorological observations. Strong agreement between the two particulate matter sensors supported the use of averaged concentrations. Mean PM₂.₅ concentrations were substantially higher in winter (32.4 µg/m³) than in summer (10.4 µg/m³), indicating pronounced seasonal variability. PM₁ and PM₂.₅ exhibited closely aligned temporal patterns, while PM₁₀ showed greater variability. NO₂ displayed sharp diurnal peaks associated with traffic activity, whereas O₃ exhibited opposing seasonal and diurnal behavior and was negatively correlated with both PM₂.₅ (r = −0.32) and NO₂ (r = −0.29). One-hour-ahead predictive models incorporating meteorological and temporal variables achieved coefficients of determination up to 0.84. The results demonstrate that energy-independent low-cost sensor systems can robustly capture temporal patterns, pollutant interactions, and short-term predictability in localized roadside environments relevant to exposure assessment. Full article