Abstract: With an ever-growing recognition of Land Surface Temperature (LST) as a key Essential Climate Variable (ECV), it becomes utmost important to have such a variable at both the fine spatial and temporal scales of urban spaces and dynamics. Sentinel-3 provides coarse LST (1 km, daily) based on thermal imagery acquired by its Sea and Land Surface Temperature Radiometer (SLSTR) as well as fine Spectral Directional Reflectances (SDR, 300 m, every two days) synergically inferred from both SLSTR and the optical bands acquired through the Ocean and Land Colour Instrument (OLCI), which gives opportunity for using the latter as predictor in the downscaling of the former. Herein, two scale-invariance-based architectures were developed: a single-timestamp model, trained with the coarse data of the timestamp whose fine target it tries to infer; and a multi-timestamp one, trained with several timestamps and that can infer for any other. While for the case of the multi-timestamp architecture, Machine Learning (ML) models besides Linear Regression (LR) were trained, solely LR was considered for the single-timestamp architecture due to the smaller amount of data available, making it less suitable for hyperparameter tuning. The models were developed over four Danish Functional Urban Areas (FUAs) between 2020 and 2023 using SRD-derived indices, seasonal and geospatial predictors. From 112 Sentinel-3 scenes, 105 were used for training and 7 for validation against Landsat data. While Gradient Boosting (GB) achieved the best coarse-scale performance (test set Root Mean Square Error, RMSE, of 1.56 K), fine-scale predictions showed degraded performance, indicating scale-invariance breakdown. Tree-based models performed poorly due to extrapolation limitations, whereas Neural Net (NN) and LR proved more robust. After residual correction, single-timestamp LR achieved the best fine-scale performance (test set RMSE of 1.40 K), making it the most reliable and operationally recommended architecture.

Abstract: Thyroid cancer (TC) is the most common endocrine malignancy, with a steadily rising global incidence. Despite most cases having a favorable prognosis, a subset of patients develops aggressive, recurrent, or radioiodine-refractory disease, demonstrating the need for improved molecular biomarkers and targeted therapies. The Forkhead box P (FOXP) transcription factors (FOXP1–FOXP4) have appeared as important regulators of tumor biology, yet their roles in thyroid cancer remain incompletely defined. This review summarizes current bioinformatic, experimental, and clinical evidence regarding FOXP expression patterns, molecular mechanisms, and clinical relevance in TC. FOXP3 and FOXP4 mainly associate with aggressive clinicopathological features, including extrathyroidal invasion, lymph node metastasis, and distant metastases, and may serve as markers of poor prognosis. The most explored FOXP3 contributes to immune evasion and radioiodine resistance by suppressing sodium iodide symporter expression and regulating tumor-associated immune responses. FOXP4 promotes tumor progression by activating key oncogenic signaling pathways and regulating non-coding RNAs. In contrast, evidence indicates that FOXP2 primarily acts as a tumor suppressor in TC by inhibiting cell proliferation and promoting apoptosis, although it may show context-dependent functions. FOXP1, though less well studied, is also suggested to have tumor-suppressive effects in some studies, and demands additional investigation in TC. Collectively, FOXP factors constitute promising diagnostic, prognostic, and treatment targets, although additional confirmation in large clinical studies is required.

Abstract: This article aims to situate itself within religious anthropological scholarship through a comparative study of Indigenous religious transformation in Malaysia and Bangladesh. Methodologically, the research combines phenomenological interpretation with a decolonial perspective rooted in a relational ontology that sees human beings as embedded in networks of land, ancestry, and community. Drawing on ethnographic engagement, narrative accounts, and interpretive analysis, the study examines two Indigenous communities—the Orang Asli of Peninsular Malaysia, where conversion to Islam occurs, and the Santal of northern Bangladesh, where conversion to Christianity has been significant. The findings suggest that religious conversion in these contexts rarely results in a straightforward doctrinal change. Instead, it unfolds as a negotiated transformation of moral life, kinship relations, and social belonging within existing cultural worlds. Indigenous actors often reinterpret new religious teachings through their own cosmological frameworks, creating hybrid moral landscapes where elements of Indigenous relational knowledge coexist with new religious practices. To understand these dynamics, the article develops the Nas–Tadabbur–Ihsan model, connecting relational ontology (Nas), reflective epistemology (Tadabbur), and ethical practice (Ihsan). While these concepts originate from Islamic ethical vocabulary, the framework functions as a universal analytical tool, emphasizing shared human capacities for reflection, relationality, and ethical responsibility. Therefore, the study suggests that Indigenous conversion is best understood as an ongoing process of ethical negotiation and relational reconfiguration rather than a mere cultural rupture or assimilation.

Abstract: Background/Objectives: The assessment of clinical competencies in nursing education requires valid and reliable instruments, especially for essential procedures such as the placement of a cervical collar in the care of polytrauma patients. The objective of this study was to analyze the psychometric properties of a rubric designed to assess the placement of cervical collars in nursing students in a low-fidelity clinical simulation environment. Methods: A quasi-experimental, cross-sectional study was conducted with 186 undergraduate nursing students, organized into 62 groups, over three academic years (2021–2024). An 8-item rubric was applied, with a 4-level Likert scale (1–4). Interrater reliability was analyzed using Cohen’s Kappa index, internal consistency using Cronbach’s alpha, and the internal structure of the instrument using exploratory factor analysis, applying Varimax orthogonal rotation. Results: Inter-rater reliability showed values ranging from moderate to substantial, with greater agreement observed in items related to the selection of the collar and the position of the medical team, and moderate agreement in those related to technical maneuvers and immobilization. The rubric showed adequate overall internal consistency (α = 0.76), with good to very good consistency values in 6 of the 8 items. Exploratory factor analysis identified a two-dimensional structure with a dominant procedural factor (4 items) and a second factor associated with clinical judgment (4 items). Conclusions: The validated rubric has adequate levels of reliability and internal consistency for evaluating the placement of cervical collars by nursing students. Its application can promote more objective and structured evaluation processes in clinical simulation for nursing students, contributing to the development of essential skills in the care of polytrauma patients.

Abstract: Although the rapid development of digital technology has significantly transformed the financial sector in Southeast Asean countries, no comprehensive study has yet mapped the evolution of digital finance in the region. This bibliometric study aims to fill this gap by providing a systematic scientific overview of the field. Derived from the Web of Science database, 252 peer-reviewed articles were compiled and analyzed using Biblioshiny R-package and VOSViewer software. The results reveal a steady growth in digital finance research in ASEAN from 2013 to 2025. The majority of articles in the region were from Indonesia, Malaysia, Vietnam, and Thailand. Current research predominantly addresses the antecedents of technology adoption, user acceptance, and continuance behavioral intentions, often grounded in theoretical frameworks such as the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Future research should explore the broader implications of digital finance, particularly its role in enhancing financial inclusion and promoting financial well-being at both individual and national levels.

Abstract: This review examines spider nutritional physiology, which remains incompletely characterized despite spiders’ importance in ecosystems and experimental settings. In captivity (including research facilities, zoological institutions, and private collections), feeding practices are often generalized and may not address metabolic demands that vary across taxa. Consequently, links between nutrition and outcomes such as growth, reproduction, and condition in captive spiders remain insufficiently delineated. Recent work in arachnid physiology and lipid metabolism indicates that some husbandry practices warrant reevaluation. Arachidonic acid (ARA), an omega-6 fatty acid and precursor to eicosanoid signaling molecules, contributes to lipid-mediated pathways across animal taxa. In arthropods, eicosanoid pathways have documented roles in processes such as development and reproduction; corresponding mechanisms in spiders are less defined, leaving an important gap in arachnid nutrition research. This review synthesizes evidence on the metabolic roles, dietary sources, and physiological relevance of ARA in spider nutrition. Available findings link lipids such as ARA with reproduction, cuticular maintenance, and metabolic function; low availability has been associated with stress responses, impaired development, and reduced fecundity in some captive contexts (Ginjupalli et al., 2015; Kangpanich et al., 2016; Stanley & Kim, 2018). Integrating lipid analyses into captive management can support animal welfare, improve comparability across studies, and inform feeding practices for arachnids.

Abstract: A classical fluid splitter produces the same patterns of energy redistribution as a Stern-Gerlach quantum device, with rotationally invariant coefficients of correlation between molecular paths. Alternative settings obey a cosine squared rule, leading to Tsirelson-type Bell violations with outcome independence. This is a confirmation of the Correspondence Principle of quantum mechanics, where individual quanta express system-level properties according to Born’s Rule. Kochen-Specker contextuality and Bell Locality are not contradicted by this result, but their interpretation is in question. The formal definition of “Local Realism” is limited to intrinsic particle properties. In contrast, quantum-like correlations require the acknowledgement of ensemble effects on dynamically inseparable propagating entities, even when they appear to operate one at a time.

Abstract: This study aimed to analyse the effects of a parkour-based Adventure Education (AE) program on the intrinsic motivation of primary school students, and to examine the role of enjoyment, self-confidence, and resilience as associated and predictive variables, considering differences according to time (pre-test–post-test) and gender. The sample consisted of 492 fifth- and sixth-grade primary education students (249 boys and 243 girls) with a mean age of 10.67 years, enrolled in 12 Spanish schools. A quasi-experimental design with pre-test and post-test measures was used following the implementation of a seven-session program based on the Pedagogical Model of Adventure Education. Data were collected using instruments validated in the Spanish population: the Intrinsic Motivation subscale of the Perceived Locus of Causality Scale, the Physical Activity Enjoyment Scale to measure enjoyment, the Self-Confidence subscale of the Competitive State Anxiety Inventory, and the Connor–Davidson Resilience Scale to assess resilience. Statistical analysis was performed using SPSS 28.0 software, conducting descriptive analyses, correlations, and hierarchical multiple linear regressions to examine the predictive capacity of the variables, and a 2×2 repeated-measures ANOVA (time × gender). The results showed significant increases in intrinsic motivation, enjoyment, self-confidence, and resilience after the intervention. Enjoyment emerged as the main predictor of intrinsic motivation, followed by self-confidence and resilience. Furthermore, the ANOVA revealed the significant effect of time whereas there were no significant differences between boys and girls, indicating that the program was equally effective for both genders.

Abstract: High-temperature superconductivity remains an open problem in condensed matter physics. While conventional and many unconventional approaches attribute superconductivity primarily to pairing mechanisms, experimental observations—including pseudogap behavior, strange-metal transport, and nanoscale inhomogeneity— suggest that pairing alone may be insufficient. We introduce a coordination-based framework in which superconductivity arises from the global organization of internal degrees of freedom associated with local electronic configurations. These degrees of freedom, modeled as effective pseudospin variables, form a system-spanning coordination manifold that stabilizes dissipationless transport, with pairing emerging as a secondary manifestation. We show that internal coordination induces an instability of the incoherent transport state, leading to global phase coherence. At the effective level, this yields a scaling relation for the transition temperature, T_c∼gm²/a_ψ′, linking superconductivity to the strength of coordination. The framework accounts for the separation between pseudogap onset and superconducting transition, the anomalous transport properties of strange metals, and nanoscale electronic inhomogeneity, and predicts distinct coherence scales and nontrivial vortex-core structure. These results suggest that optimizing coordination of internal degrees of freedom may provide an alternative route to enhancing superconductivity.

Abstract: Maintaining the concentration of magnesium in potable water above minimum levels has been suggested to have public health benefits. A twelve-month trial of attempting this goal by partial replacement of limestone with dolomite in eight out of twenty-six post-treatment contactors at the Ras al Khair seawater desalination plant, the largest such plant in Saudi Arabia with a daily production of over 1,000,000 m³ of desalinated water. Over the course of the trial increases in Mg concentration in the range 1 to 2 ppm were achieved without necessitating increases in carbon dioxide utilization or any reduction in production volume. Alkalinity, calcium, and total dissolved solids remained within acceptable parameters. Calculated supersaturation values suggest strongly that it will not be possible to increase concentrations significantly further at the pH and temperature conditions of the study. Thus, while use of dolomite to this extent is a very low-cost strategy for magnesium supplementation, its scope of application without additional carbon dioxide consumption and capital investment is limited. The ratio of magnesium to chloride in SWRO product water was estimated in the course of the study and was found to be approximately half of the ratio in Standard Seawater, suggesting that under operational conditions (giving 1500 mg/L from first pass reverse osmosis) rejection of magnesium was significantly greater than rejection of sodium.

Abstract: Shiga toxin-producing Escherichia coli (STEC) remain a leading cause of severe foodborne illness in the European Union, including haemolytic uraemic syndrome and fatalities. EU food safety criteria for STEC, established by Commission Regulation (EC) No 2073/2005 as amended, require serogroup-based testing for six designations — and only in sprouts. Most high-risk food categories, including raw milk cheese and minced meat, lack any mandatory STEC-specific food safety criterion. This serogroup-centred approach persists despite the 2020 EFSA scientific opinion concluding that all STEC strains are pathogenic, that any stx subtype may be associated with severe illness, and that serogroup alone cannot predict clinical outcome. The recent adoption of Implementing Regulation (EU) 2025/179, mandating whole genome sequencing for any Escherichia coli associated with foodborne outbreaks — without serogroup restriction — further highlights the disconnect between reactive investigation tools and preventive criteria. With the new WGS mandate becoming applicable in August 2026, we argue that a parallel effort is urgently needed to update food safety criteria from serogroup-based testing towards virulence gene profiling, aligning prevention with the scientific evidence and the genomic paradigm already adopted for outbreak response.

Abstract: Antibiotic contamination of water, particularly tetracycline (TC), poses significant environmental risks and requires sustainable treatment solutions. This study reports a green and cost-effective synthesis of a ZnO/chitosan nanocomposite (ZnO/CS) for photocatalytic TC removal. ZnO nanoparticles were synthesized using lime juice as a natural stabilizing agent and subsequently incorporated into a chitosan matrix. The physicochemical properties of the composite were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), UV–Vis diffuse reflectance spectroscopy (UV–Vis DRS), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and Brunauer–Emmett–Teller (BET) surface area analysis. The results confirmed the formation of hexagonal wurtzite ZnO and strong interfacial interactions between ZnO and the –NH2/–OH groups of chitosan. A red shift reduced the band gap from 3.18 to 3.03 eV, while the specific surface area increased from 10.7 to 21.7 m² g⁻¹. Under LED irradiation, the ZnO/CS nanocomposite achieved 94% TC removal within 120 min, following pseudo-first-order kinetics based on the Langmuir–Hinshelwood model. These findings demonstrate the potential of the green-synthesized ZnO/CS nanocomposite for antibiotic removal from aqueous environments.

Abstract: Cardiorenal syndrome type 1 (CRS-1) is defined as acute kidney injury (AKI) caused by acute decompensated heart failure (ADHF). Heart failure with preserved ejection fraction (HFpEF) is an increasingly prevalent subtype of heart failure. A significant number of patients with HFpEF during episodes of acute decompensation (ADHFpEF) develop CRS-1. The most important pathophysiological mechanisms leading to the development of CRS-1 in these patients are hemodynamic disturbances (elevated central venous pressure, elevated intra-abdominal pressure and pulmonary hypertension) and inflammation. Loop diuretics alone or in combination with thiazide diuretics and mineralocorticosteroid receptor antagonists are the mainstay therapeutic option for treating congestion in patients with ADHFpEF and CRS-1. Introducing SGLT-2 inhibitors as soon as clinically possible can further enhance diuresis and have a positive impact on reducing cardiorenal adverse events. Development of CRS-1 is a well known independent predictor of a worse outcome in patients with heart failure, although this impact appears to be less associated in patients with HFpEF, as compared to patients with HF with reduced EF. Further studies are needed to achieve a better understanding of pathophysiological mechanisms, and to introduce new treatment protocols, which would have a positive impact on cardiac and renal outcomes in these patients.

Abstract:

Background Rhinoplasty was the most frequently performed surgical procedure. Involuntary thoughts may occur before rhinoplasty, which can negatively affect both the psychological state and the postoperative healing process. Objectives This study was conducted to evaluate the effects of education provided to patients undergoing rhinoplasty on their preoperative intrusive thoughts and postoperative recovery. Methods This study was designed as a single-center, pretest-posttest, randomized controlled trial conducted in a state hospital between January 2024 and December 2024. The sample size was determined using power analysis, and 41 and 41 people were included in the control and intervention groups, respectively. Data were collected using the Personal Information Form, Preoperative Intrusive Thoughts Inventory (PITI), and Postoperative Recovery Index (PoRI). The intervention group received preoperative and discharge education via PowerPoint presentation and brochures. Results A significant decrease was detected in the preoperative PITI scores in the experimental group (p < .05). Although no statistically significant difference was observed between the total PoRI mean scores of the intervention and control groups before discharge after surgery, the total PoRI mean score of the patients in the intervention group on the seventh day after surgery was found to be statistically significantly lower than that of the patients in the control group (p < .05). Conclusion In conclusion, the education provided to patients who underwent rhinoplasty via PowerPoint presentation and brochure before surgery and before discharge reduced preoperative intrusive thoughts and positively affected postoperative recovery.

Abstract: Bovine Viral Diarrhea (BVD) is an infectious disease caused by the Bovine Viral Diarrhea Virus (BVDV), a member of the genus Orthopestivirus. The disease remains endemic across Australian beef and dairy production systems, imposing a multi-million-dollar annual burden on animal health, welfare, and industry sustainability. BVDV can be transmitted both horizontally and vertically, with persistently infected (PI) animals serving as the primary source of infection. Rapid identification and subsequent culling of PI animals are fundamental requirements for any successful eradication program. Currently, Australia’s decentralised, non-compulsory approach places the responsibility of biosecurity on individual producers, resulting in a fragmented national landscape. This review proposes that the strategic deployment of rapid, field-deployable point-of-care (POC) diagnostics serves as the transformative catalyst needed for a coordinated national eradication pathway. POC approaches utilising technologies such as lateral flow assays, nucleic acid amplification tests, and biosensors enable real-time, crush-side diagnosis and high-throughput surveillance, proving effective for early detection and control of infectious diseases. When integrated with robust biosecurity measures and optimised vaccination strategies, these POC advancements offer a scientifically sound and commercially viable pathway toward the systematic eradication of BVDV in the Australian cattle industry.

Abstract: Precise segmentation of defects is a key component of industrial quality control. This paper presents a comprehensive overview of contemporary methods utilising convolutional neural networks that have demonstrated practical efficacy. Depending on the application, semantic, instance-based, panoptic and hybrid segmentation methods are used to reliably detect material defects. Finally, prospects for industrial use are discussed, including the optimisation of hybrid methods, real-time capability and integration into existing production processes to ensure efficient, robust and practical defect detection.

Abstract: The construction industry is a key energy consumer and greenhouse gas emitter, and its green low-carbon transformation is critical to achieving China's "dual carbon" strategy. This study focuses on carbon emissions from the construction industry in Hunan Province, central China, using data from 2005 to 2022. An improved STIRPAT extended model combined with ridge regression is applied to identify key driving factors, and a CNN-LSTM-Attention hybrid model is constructed for multi-scenario carbon peak prediction from 2023 to 2040. The results show that industrial scale, urbanization rate, and energy intensity are the top three influencing factors, with energy intensity being the only significant inhibitory factor. Carbon emissions will continue to rise without peak under the high-carbon scenario, peak in 2035 under the baseline scenario, and peak in 2030 under the low-carbon scenario. The low-carbon scenario is the optimal path to meet Hunan's 2030 carbon peak target for the construction industry. Targeted policy suggestions are proposed for regional low-carbon development.

Abstract: With the rapid development of software-defined radio (SDR) technology, a digital, software-reconfigurable, and flexible solution is provided for microwave radiometers, particularly suitable for atmospheric water vapor and oxygen detection with wideband, multi-channel requirements, significantly improving system efficiency. Meanwhile, digitization helps improve channel consistency and address nonlinearity issues, while the digital zero-balancing mechanism implemented through adaptive integration is more suitable for digital platforms. This paper proposes a digital Dicke-type radiometer system based on an SDR platform, using Xilinx RFSoC XCZU47DR as the core hardware to achieve single-chip integration of RF signal sampling, digital local oscillator generation, and signal processing. The system implements a 46-channel channelized receiver (23 channels each for K-band and V-band) on FPGA using a polyphase filter bank. The prototype filters achieve 70 dB stopband attenuation and 0.5 dB passband ripple, with each polyphase branch requiring only 25 coefficients, significantly reducing hardware resource consumption. An adaptive integration method is proposed, where an adaptive switch controller dynamically adjusts the hot source injection time ratio by calculating the power difference between adjacent integration periods, enabling the Dicke zero-balancing mechanism to operate entirely in the digital domain. Furthermore, a complete hardware transfer model is established for three signal branches (antenna, hot source, and matched load), and full-chain calibration of all 46 channels is performed using a liquid nitrogen cold source, with calibration reliability verified through blackbody measurements. Experimental results demonstrate that the system achieves better than 0.7 K brightness temperature consistency across channels, with sensitivity less than 0.15 K at 1-s integration time, confirming its excellent channel consistency and measurement stability.

Abstract: Wildlife plays a vital role in maintaining ecological balance and biodiversity, relying on habitats that provide shelter, food, and essential resources. This study investigated wildlife distribution and diversity across the REDD+ program area in Cambodia’s Prey Lang Wildlife Sanctuary, a lowland evergreen forest ecosystem, and assessed the effects of forest habitats and anthropogenic pressure on their distribution. We used square transects for sampling and ArcGIS to calculate forest cover and distance to the nearest village as a proxy for human impact. Overall, we recorded seven mammals and two birds, with the great hornbill most frequently detected, followed by pileated gibbon, wild pig, long-tailed macaque, green peafowl, northern red muntjac, and Indochinese silvered langur; gaur and sambar deer were least detected. Wildlife richness and abundance were higher in evergreen-dominated habitats than in mixed deciduous-evergreen forests. Certain K-selected species, including pileated gibbon, Indochinese silvered langur, and great hornbill, were highly specialized and preferred intact forests, whereas generalist species such as northern red muntjac, long-tailed macaque, and wild pig showed ecological flexibility in habitat use. These findings emphasize tailored conservation strategies: protecting intact evergreen forests via REDD+ supports specialized species, while adaptive management in mosaic landscapes benefits generalists, enhancing wildlife conservation and sustainable management of Prey Lang Wildlife Sanctuary.

Abstract: Real-time 2D imagery super-resolution (SR) in UAV remote sensing encounters significant speed and resource-consuming bottlenecks during large-scale processing. To overcome this, we propose Semantic Injection State Modeling for Super-Resolution (SIMSR), an ultra-lightweight architecture that integrates land-cover semantics into a linear state-space model. This integration mitigates state forgetting inherent in linear processing by linking hierarchical features to persistent semantic prototypes, enabling high-fidelity image enhancement. The model achieves a state-of-the-art PSNR of 32.9+ for 4x SR on RSSCN7 agricultural grassland imagery. Furthermore, the implementation of geographically-chunked (tile-based) parallel processing simultaneously eliminates computational redundancies, yielding a 10.85x inference speedup, a 54% memory reduction, and an 8.74x faster training time. This breakthrough facilitates practical real-time SR deployment on UAV platforms, demonstrating strong efficacy for ecological monitoring applications by providing the detailed imagery essential for accurate analysis.