Search Results (14,913)

Background: Lower urinary tract symptoms (LUTSs) are among the most common urological complaints in older men, frequently arising from benign prostatic hyperplasia (BPH) or prostate cancer (PCa). While both conditions share overlapping symptomatology, the way each condition progresses and is managed differs considerably. In sub-Saharan Africa, data on the relative burden of BPH and PCa among men presenting with LUTSs are scarce. This study aimed to determine the prevalence of histologically confirmed BPH and PCa among men presenting with LUTSs at a major tertiary referral center in Tanzania and to explore the association between specific urinary symptoms and histopathological diagnoses. Methods: A retrospective cross-sectional study was conducted at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania, reviewing medical records of adult male patients aged ≥50 years who presented with LUTSs and underwent prostatic biopsy between January and December 2023. A total of 133 patients were included through simple random sampling from an eligible population of 260. Data on demographics, comorbidities, International Prostate Symptom Score (IPSS), serum prostate-specific antigen (PSA), prostate volume, and histopathological biopsy outcomes were extracted using a purpose-built digital form. This study was conducted in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Most patients (39.8%) were aged 70 to 79 years. Hypertension was the most frequent comorbidity among those with chronic disease (31.65%), followed by diabetes mellitus (12.03%). The mean serum PSA was 465.1 ng/mL (SD = 1610.1), and the mean prostate volume was 80.6 cm³ (SD = 75.6). Histopathologically, 57.9% of biopsies were benign and 40.6% were malignant. The most commonly reported IPSS symptoms were urinary frequency (78.2%), weak stream (78.2%), and incomplete emptying (64.7%). Most patients (59.4%) had severe IPSSs. Statistically significant associations were observed between biopsy outcomes and incomplete emptying (p = 0.011), frequency (p = 0.014), weak stream (p = 0.022), nocturia (p = 0.001), urge incontinence (p = 0.004), and post-void dribbling (p < 0.001). IPSS severity was significantly associated with biopsy diagnosis (p < 0.001), with 63% of malignant cases presenting with moderate symptom scores. Conclusions: BPH was the predominant histopathological diagnosis among men presenting with LUTSs at this tertiary center, while prostate cancer accounted for a substantial minority of cases. Certain individual LUTSs, particularly nocturia, urge incontinence, and post-void dribbling, demonstrated significant associations with malignant histopathology. These findings underscore the necessity for systematic histopathological evaluation in all men presenting with LUTSs in resource-limited settings, irrespective of symptom severity. Full article

The exploration of deep-sea microorganisms is transitioning from ex situ laboratory analysis to in situ real-time monitoring. While in situ technologies offer unprecedented access to microbial activities in their natural extreme habitats, they face a critical, yet often overlooked, bottleneck: the absence of a robust metrological framework. This lack of standardized calibration, traceability, and reference materials results in data that are often irreproducible, device-specific, and incomparable across studies, severely undermining scientific discovery and resource assessment. This review provides a systematic analysis of the current landscape of deep-sea microbial detection technologies, categorizing them by their operational principles and critically evaluating their performance, limitations, and metrological readiness. By synthesizing the technological challenges with the principles of metrology, we identify the fundamental gap between advanced sensing capabilities and the lack of in situ measurement standards. To bridge this gap, we propose an innovative “laboratory simulation–in situ detection–remote calibration” trinity calibration system. This framework establishes a complete metrological traceability chain tailored for extreme deep-sea conditions, aiming to transform isolated sensor data into globally comparable, scientifically robust, and industrially actionable information, thereby paving the way for precision deep-sea biology and governance. Full article

Digital village construction (DVC) is an important tool for promoting rural revitalization and increasing farmers’ income. This paper selects panel data at the county level and employs the difference-in-differences (DID) method, combined with mediation effect models, heterogeneity tests, and multi-dimensional robustness tests, to systematically explore the impact of DVC on farmers’ income and its internal transmission path. According to the research, the DVC has a positive impact on farmers’ income at the 1% significance level, a conclusion that remains valid after robustness tests such as PSM-DID and substitution of the explained variable. Industrial restructuring, agricultural mechanization, and enterprise agglomeration are positively significant at the 5%, 1%, and 1% levels, respectively, indicating that these three are the core intermediary mechanisms for increasing farmers’ income, promoting farmers’ income growth by releasing structural dividends, efficiency dividends, and agglomeration dividends, respectively. The income-increasing effect of DVC exhibits significant heterogeneity, being positively significant at the 5% and 1% levels in areas with a deep digital divide and non-grain-producing areas, but not significant in areas with a shallow digital divide and major grain-producing areas. Therefore, policy recommendations are to optimize resource allocation, broaden income-increasing pathways, and implement differentiated policies. Full article

The evaluation of biodiversity is an essential tool for conservation, management of natural resources, and assessment of ecosystem functioning. Choosing an appropriate and understandable diversity metric is critical to ultimately make better decisions and apply more sustainable resource management. However, biodiversity metrics are numerous, and care must be taken when using them. So, should one consider all these metrics to obtain the right information? If not, how should one choose? This paper aims to demonstrate the importance of understanding and selecting the appropriate diversity metrics to reach accurate conclusions. We simulated theoretical plant communities for which calculations of different biodiversity metrics were carried out to understand why and how to use them. We explored Richness, Evenness and Disparity components of biodiversity using both scales of diversity partitioning (i.e., alpha and beta diversity). In doing so, a decision tree is proposed to select diversity metrics according to user objectives. We also suggest an add-in term if alpha metrics are calculated with subsamples to better reflect biodiversity. Finally, we recommend that when dealing with ecosystem functioning or conservation concerns, species-dependent metrics should be used, as they reflect Disparity. However, there is a critical need to increase knowledge and data availability on species traits or phylogeny to be able to better analyze Disparity. Full article

The increasing demand for environmentally sustainable and efficient laundry detergents has prompted the exploration of innovative biotechnological solutions. This study aims to integrate solid fermentation and by-product valorization for high-quality proteases suitable for laundry detergents. Of 486 strains isolated from fruit by-products, 9 were selected for their proteolytic activity, but only 3 showed proteolytic activity in the presence of detergent components. Strain M17, identified as Yarrowia lipolytica (Yl), proved to be the most effective in producing proteolytic extracts with activity similar to that found in commercial detergents. The produced proteases were incorporated into laundry detergent formulations, and their enzyme activity was compared with that of commercial laundry detergents. The results showed that the proteolytic extracts have enzyme activity similar to that of commercial laundry detergents. Culture media were developed to enhance protease production using fruit by-products. The highest activity (43.71 U (g dm)⁻¹) was achieved at C/N = 20.04, while the best productivity (1.37 U (g dm·h)⁻¹) at pH 7.0 and 30 °C was observed. The results demonstrate that culture media based on fruits and vegetable by-products enhance protease yield and activity. This approach not only reduces waste but also adds value to natural resources through an environmentally friendly process. This study underscores the potential of combining solid-state fermentation with by-products. Using Yl in combination with fruit and vegetable by-products is a practical, eco-friendly method for producing high-quality proteases for laundry detergents. This green enzyme innovation offers significant promise for advancing the detergent proteolytic enzymes and promoting sustainable practices in by-product management. Full article

Robust vehicle detection in real-world traffic surveillance remains challenging due to degraded imagery caused by motion blur, adverse weather, and low illumination, which significantly increases detector sensitivity to hyperparameter configurations. This study proposes a “Frugal AI” distributed multi-GPU framework that optimizes hyperparameters via a stochastic simplex-based search coupled with five-fold cross-validation. Utilizing three low-cost NVIDIA GTX 1050 Ti GPUs, the framework performs parallel candidate exploration with an asynchronous model-level exchange mechanism to escape local optima without the overhead of gradient synchronization. Seven CNN backbones—VGG16, VGG19, GoogLeNet, MobileNetV2, ResNet18, ResNet50, and ResNet101—were evaluated within YOLOv2 and Faster R-CNN detectors. To address memory constraints (4 GB VRAM), YOLOv2 was selected for extensive benchmarking. Performance was measured using a harmonic precision–recall-based cost metric to strictly penalize imbalanced outcomes. Experimental results demonstrate that under identical wall-clock time budgets, the proposed framework achieves an average 1.38% reduction in aggregated cost across all models, with the highly sensitive VGG19 backbone showing a 4.00% improvement. Benchmarking against Bayesian optimization, genetic algorithms, and random search confirms that our method achieves superior optimization quality with statistical significance ($p < 0.05$). Under a rigorous IoU = 0.75 threshold, the optimized models consistently yielded F1-scores 0.8444 $\pm$ 0.0346. Ablation studies further validate that the collaborative model exchange is essential for accelerating convergence in rugged loss landscapes. This research offers a practical, scalable, and cost-efficient solution for deploying robust AI surveillance in resource-constrained smart city infrastructure. Full article

With the transformation of resource-based cities and the restructuring of industrial sectors, the sustainable conservation of coal mining heritage has become a global focus. In China, coal mining heritage faces challenges such as degradation and inadequate management, highlighting the urgent need for more context-sensitive and systematic conservation approaches. This study develops an integrated, landscape-oriented analytical framework for stakeholder identification to address these challenges and to better understand stakeholder differentiation in coal mining heritage conservation. The research objectives are as follows: (1) to bring together a three-dimensional framework based on material-technical, socio-cultural, and experiential dimensions; (2) to analyse the roles and interactions of stakeholders; and (3) to explore how technical knowledge, socio-cultural memory, and daily experiences influence the protection and reuse of coal mining heritage sites. The study integrates the theoretical frameworks of landscape character assessment, historic urban landscape, and experiential landscape, using data from field observations and interviews analysed via ATLAS.ti. The findings show that the proposed framework offers a more systematic understanding of the dynamic relationships between stakeholders and heritage landscapes, thereby providing practical guidance for local governments and relevant institutions in developing inclusive and context-sensitive conservation strategies. Full article

In situ resource utilization (ISRU) and in situ fabrication and repair (ISFR) are critical research and technological paradigms for future space exploration. They aim to reduce reliance on Earth-supplied materials by utilizing resources available on celestial bodies, while enabling on-site fabrication and repair through the use and processing of local resources. ISRU and ISFR are strongly interconnected, with the shared objective of enabling more sustainable and autonomous long-duration missions to the Moon, Mars, and beyond. This work presents a comprehensive and critical review of scientific and patent literature published primarily between 2010 and 2025, complemented by selected earlier seminal contributions for context. The analysis provides an integrated perspective on major technological developments, key challenges, and emerging research directions in low-gravity and microgravity environments. Full article

Background: Evidence shows that simulation-based education for nurses and midwives contributes to strengthening patient safety and quality of care in healthcare settings. Nevertheless, it is implemented to a limited degree in Sub-Saharan African (SSA) higher education institutions, including Tanzania. This demands that Tanzania shift from a traditional model of teaching to incorporate simulation-based education to produce a skilled workforce. Objective: To explore perceptions and experiences of nurse educators (lecturers) and midwives on simulation-based education in Tanzania. Methods: The study employed a generic qualitative descriptive study design with purposive sampling. The data were collected through individual semi-structured interview guides with nurse educators and midwives (nine nurse educators and 11 midwife graduates) from two selected universities in the School of Nursing and their respective teaching hospitals. Qualitative inductive content analysis was used to analyze the data. Results: The data analysis revealed three themes and nine sub-themes: 1. Knowledge and skills in simulation-based education. 2. Challenges in the implementation of simulation-based education. 3. Ensuring patients’ safety. Conclusions: Students were indeed experienced, but not trained in how to use simulation-based education, and nurse educators had inadequate skills. A high number of students with inadequate infrastructure and resources is the major challenge experienced by participants. Simulation-based education is at an early stage of adoption in Tanzania and will require ongoing development, support and resources to fulfilll its potential in promoting patient safety. Full article

Remote-sensing inversion of water-quality parameters is a critical interdisciplinary field, integrating remote-sensing technology, environmental science, and water resources management, providing key technical support for precise water resources monitoring and ecological governance. To address the lack of comprehensive systematic reviews in this field, this study conducted a bibliometric-based narrative review, selecting 2812 valid English studies published during 1980–2026 from the Web of Science Core Collection (WOSCC) and performing in-depth knowledge mapping analysis via CiteSpace software. The results showed that global research in this field has gone through three stages: initial exploration (1980–2000), slow growth (2001–2015), and rapid explosion (2016–2026). China ranks first in publication volume worldwide, with a collaborative research pattern dominated by core institutions, including the Chinese Academy of Sciences, Wuhan University, and the National Aeronautics and Space Administration (NASA). The core research hotspots focus on multi-source data fusion, AI-driven inversion-model optimization, and the research shift from coastal to inland water bodies. Current research faces three key challenges: poor adaptability of multi-source data-fusion technologies to water-quality monitoring, inadequate integration of geospatial and thematic factors in inversion models, and an insufficient systematic approach of inland-water-body research. Accordingly, future research should focus on advancing remote-sensing data-fusion methods, further optimizing water-quality inversion models, and strengthening inland-water-body studies. This study clarifies the field’s development context and research characteristics, providing valuable references for subsequent academic exploration and practical applications in water resources management. Full article

Forensic age estimation is a fundamental component of biological profiling for unidentified skeletal remains, particularly in mass casualty incidents where specimens are frequently fragmented or incomplete. This review evaluates the diagnostic utility of craniofacial suture closure—specifically across four facial regions—as a non-invasive methodology for age determination in adults. By analyzing the predictable fusion patterns of ectocranial and endocranial sutures, forensic practitioners can derive approximate age ranges when postcranial indicators are absent or unreliable. Despite its utility, the reliability of suture-based estimation remains a subject of academic debate. The rate of closure is influenced by a complex interplay of environmental and biological factors, including nutritional status, hormonal influences, and mechanical loading. Historically, the method has faced criticism due to significant inter-individual variability and limited sample sizes in cadaveric studies. To improve precision and novel detail, this review explores the integration of emerging technologies such as artificial intelligence (AI) and machine learning (ML). These tools can process extensive cranial datasets to identify subtle morphological patterns that may elude human observation. While craniofacial suture analysis remains an essential resource in the forensic toolkit, its accuracy is contingent upon accounting for multi-factorial biological factors. The authors emphasize the necessity for further external validation across diverse global populations to ensure the generalizability and refinement of the technique in forensic medicine and osteology. Full article

Shale gas exploration in the Shixi block, Guizhou, faces significant challenges due to complex geological structures and normal pressure. To reduce exploration risk, we propose an integrated “Four-in-One” evaluation workflow that combines geological sweet spots, engineering feasibility, preservation conditions, and paleogeomorphology. The workflow features a ‘cap-constraint’ velocity model to reduce structural uncertainty and a tiered multi-scale discontinuity detection strategy for low-SNR seismic data. Application of this workflow in the Shixi block delineated two Class I favorable zones (42.61 km²) with estimated resources of 8.33 billion cubic meters. Drilling results from 56 horizontal wells validate the accuracy of our prediction model, confirming that preservation condition is the primary controlling factor for gas accumulation in this normally pressured setting. This study provides a practical reference for shale gas assessment in structurally complex, normally pressured regions. Full article

This study aims to explore the effects of micro-polluted river water on nitrogen and microbial communities of paddy field soil under different irrigation modes. The experiment was conducted in a water-saving park in Nanjing. By establishing three water quality conditions—clean water, micro-polluted river water, and alternating irrigation—and two moisture conditions—flood irrigation and controlled irrigation—this study investigates the effects of different irrigation patterns on soil nitrogen and microbial communities. The results indicate that, under flood irrigation, the input of micro-polluted river water can effectively alleviate NH₄⁺-N loss during the heading stages of rice growth by 49.3%. Moisture conditions are the primary factor influencing microbial community structure. Although the input of micro-polluted river water reduces community stability, rotation irrigation can increase microbial abundance and enhance network complexity, thereby enhancing the system’s resilience. Redundancy analysis shows that soil moisture, pH, and ion content are the key environmental factors driving microbial distribution. The clean and polluted water rotation irrigation model performs best in maintaining soil nitrogen and microbial health. Rotation irrigation promotes the enrichment of key functional groups, such as Actinobacteria, effectively increasing rice yield. This study provides a theoretical basis for promoting sustainable agricultural production through water resource management. Full article

NAC (NAM, ATAF1/2 and CUC2) transcription factors constitute one of the largest plant-specific transcription factor families and play pivotal roles in plant growth, development, and responses to environmental stresses. Systematic characterization of NAC genes is essential for understanding regulatory networks underlying key agronomic and adaptive traits. As a conservation-priority woody species with distinctive biological and horticultural value, Sinojackia xylocarpa Hu lacks comprehensive knowledge of its NAC repertoire, and elucidating its NAC family will facilitate functional studies related to development and environmental adaptation. Based on whole-genome data of S. xylocarpa, we conducted a systematic survey and characterization of the NAC transcription factor family. In total, 115 SxyNAC genes encoding the conserved NAC domain were identified, and their loci were unevenly distributed across 12 chromosomes. Analyses of gene-duplication modes and collinearity indicated that whole-genome/segmental duplication events were the major driving force for the expansion of this family. Phylogenetic relationships, gene structures, and conserved motifs classified the SxyNAC members into 15 subfamilies, revealing a highly conserved N-terminal NAC domain and a markedly diversified C-terminal regulatory region with pronounced member- and lineage-specific differences. Promoter cis-element prediction showed extensive enrichment of light-responsive, phytohormone-responsive, and stress-related elements, suggesting that SxyNAC genes may participate in coordinated regulation of multiple environmental cues and endogenous hormone pathways. Transcriptome data from six fruit developmental stages, together with qRT-PCR validation of ten representative genes, demonstrated diverse temporal and tissue-specific expression patterns during fruit development and close associations with fruit growth regulation. Overall, our findings establish a framework for exploring the evolutionary trajectories and functional diversification of NAC genes in S. xylocarpa, and they offer a valuable resource for NAC-family research and conservation-focused functional genomics in other rare or threatened plant species. Full article

Universities play a critical role in knowledge creation and technological innovation, serving as key drivers of regional development. However, existing research has paid limited attention to the mechanisms through which university innovation inputs translate into firm-level performance, particularly in the context of science and technology corridors in emerging economies. This study investigates how university innovation resources affect enterprise performance in the G60 Science and Technology Corridor within China’s Yangtze River Delta, one of the country’s most dynamic innovation regions. Using a panel dataset of 55 universities across nine cities from 2008 to 2017, we employ spatial analysis and fixed-effects panel regression models to examine the relationship between university innovation inputs and firm performance and further explore the mediating roles of local human capital and firm R&D investment. The results show that university innovation inputs significantly enhance enterprise performance, although excessive human resource inputs exhibit a negative effect on both short-term and long-term outcomes. Local human capital and firm R&D investment serve as key mediating mechanisms, with input and output resources influencing enterprise performance through distinct pathways. Heterogeneity analysis reveals that non-state-owned enterprises and small- and medium-sized enterprises derive greater long-term benefits from university resources. These findings contribute to the literature by clarifying the conceptual distinction between university innovation inputs and outputs, and by demonstrating the micro-level mechanisms—R&D investment and human capital—through which university-generated knowledge affects firm performance. The results also provide empirical evidence from an emerging economic context, extending the applicability of knowledge spillover and absorptive capacity theories. Policy implications include optimizing university human resource allocation, strengthening university–enterprise collaboration, and providing targeted support for non-state-owned enterprises and SMEs. Future research may extend the analysis to include institutional factors and university heterogeneity. Full article