Efficient ventilation is a crucial aspect in ensuring the efficient and secure operation of mines. Central to this ventilation system are axial fans, whose maintenance directly impacts their operational efficiency, longevity, and safety. Despite the integral role these fans play, a comprehensive understanding of how ventilation design influences their maintenance remains to be fully explored in existing literature. This study, therefore, seeks to delve deeper into this issue. The paper aims to highlight the significant role ventilation design plays in the maintenance and overall performance of axial fans. We hypothesize that optimized ventilation design can not only reduce the frequency of maintenance interventions but also enhance the fan's lifespan and performance. The research will encompass in-depth examination of current ventilation designs and their respective maintenance challenges. It will identify the key parameters that influence fan efficiency, maintenance, and life span. The research will explore strategies for enhancing ventilation design to improve maintenance outcomes. By bridging this gap in knowledge, the study's findings can offer valuable insights for mining industries, informing the development of more effective maintenance strategies. This can lead to more efficient mining operations, reduced downtime, and enhanced safety protocols, which is most important in the mining sector.

The quest for high-speed computing with optimal power usage has spurred the rise of approximate computing, a methodology that sacrifices precision for improved power efficiency. This paper delves into the realm of approximate computing by exploring the power consumption aspects of both existing and novel architectures of approximate 4:2 compressors. Employing Intel Quartus Prime, the study seeks to elevate the performance metrics of multipliers. By scrutinizing the power consumption characteristics, the research aims to shed light on the efficacy of approximate computing in real-world scenarios. Through meticulous analysis, it intends to uncover the trade-offs between accuracy and energy consumption, elucidating the potential benefits and drawbacks of adopting approximate computing methodologies in practical applications. The investigation into 4:2 compressors serve as a microcosm for broader discussions surrounding approximate computing’s role in contemporary computing paradigms. It endeavors to provide insights into how approximate computing techniques can be harnessed to bolster the efficiency and performance of computational systems, particularly in scenarios where stringent power constraints coexist with the demand for high computational throughput.

The increasing computational demands of state-ofthe-art machine learning models have posed significant challenges for real-time applications, particularly in environments where hardware resources are limited. A novel adaptive inference-time compute framework is introduced, offering an efficient solution that dynamically adjusts computational resources based on the complexity of the input data. Through the use of dynamic scaling of model layers, attention heads, and precision levels, this approach optimizes computational efficiency without significantly compromising accuracy. Extensive experiments demonstrate the potential for substantial reductions in FLOPs, latency, and energy consumption, while maintaining high performance across various tasks. The results highlight the framework's ability to intelligently manage computational resources, ensuring scalability and practicality, especially in resource-constrained settings. This adaptive methodology represents a significant advancement in improving the balance between computational efficiency and model performance.

In many rural areas of arid and semi-arid regions, balancing agricultural and environmental water needs is a key challenge facing resource managers. This is complicated by the tendency for the water needs of cultivated crops to be better understood than those of aquatic ecosystems. In particular, the timing and magnitude of flow needed to sustain key ecological functions remain poorly quantified in many regions. This work aims to quantify hydrologic conditions that support persistence of key ecosystem species using a functional flows framework. We use the coho ( Oncorhynchus kisutch) and Chinook ( Oncorhynchus tshawytscha) salmon run in Scott Valley, a 2,109 km 2 undammed rural watershed in northern California, USA, as a case study. Taking advantage of a nearly two-decade ecological monitoring dataset and long-term stream gauge measurements, we used lasso regression to build predictive models of coho and Chinook salmon reproductive success based on hydrologic metrics. To control for cohort effects, we chose normalized ecological response metrics for coho and Chinook (number of outmigrating smolt per spawning adult or spawning adult female). For both species, we calculated optimal prediction models using a cross-validation bootstrapping approach to resample and test on unsampled observations. Lambda values, a key fitting parameter in the lasso models, were selected based on an average relative test error threshold of 1.0. Selected lambda values were used to calculate a final predictive model, or Hydrologic Benefit function, using the full dataset for each species. Hydrology could explain a greater degree of variance in relative coho reproduction than in Chinook. The hydrologic metrics that explain the greatest variance in coho reproduction values occur during the window of their parents’ spawning and, to a lesser extent, in the spring and fall of their year of rearing in freshwater. This supports an interpretation that spawning conditions may exert a significant influence on the mortality rates of the hatching juveniles. Robustness of the results indicate that this method for empirically deriving hydrologic metrics with the highest ecological benefit for a threatened species may be useful in other watersheds, where sufficient ecological data records are available, to evaluate trade-offs and support water management decisions in human-altered novel ecosystems.

The Complex Trial Protocol (CTP), a P300-based Concealed Information Test (CIT) is an innovative tool that can be used to identify individuals who possess crime-related information. We tested the CTP in a mock terrorism scenario with three different probes. Forty-one undergraduate participants were randomly assigned to one of three groups, Innocent Control (IC), Simply Guilty (SG), and Guilty Countermeasure (GCM). Individuals in the SG and GCM groups underwent a mock terrorism scenario and were exposed to three pictorial probes, the face of an accomplice, the crime scene, and the mock explosive device. Additionally, the GCM group performed a memory suppression countermeasure. Based on the AUCs generated, the CTP showed a good to very good predictive ability ranging from .63 to .94 depending on the probe presented. The aggregated scores led to an AUC of .79 for the SG participants and of .90 for the GCM, indicating that it may be advantageous to use multiple probes. Overall, hit rates ranged from 54-78% (bomb), 64-93% (crime scene), and 71-93% (male accomplice). Attempting to suppress information had the opposite effect of generating slightly higher P300 amplitudes than in SG individuals. Stimuli quality and ecological issues are discussed.

Lower socioeconomic status (SES) groups are at heightened risk of exposure to adversity, with early adverse experiences associated with less optimal neurocognitive development, which has downstream effects on education, work, and health indices. Maternal stress is similarly cited to negatively influence infant development. Given the myriad of stressful experiences more common in lower SES contexts, this review sought to understand whether maternal stress drives differences in infant neurocognition between SES groups. Four databases were systematically searched in line with PRISMA guidelines. Fourteen studies were eligible for inclusion, of which twelve reported infant neurocognitive development to be negatively associated with maternal stress, while ten reported positive associations with SES. Nine studies examined the relationship between stress and SES, with six supporting an interactive effect between maternal stress and SES, although the strength and direction of this relationships varied. Gaps in the current research regarding infant brain responses and research into lower income settings, were identified.

Adolescence spans from age 11 or 12 to 17 or 18, encompassing a duration of six years. The phase from 11/12 to 14/15 years old is often referred to as junior high school for individuals. This three-year period marks an acceleration phase of physical development, all bodily systems and structures rapidly develop and progressively mature. The stage from 14/15 to 17/18 years old is also referred to as early youth, coinciding with high school attendance. Following successive developmental stages, individuals in early youth have achieved physiological maturity and are nearly at the adult intellectual level, exhibiting more abundant characteristics in personality and other psychological attributes. However, the prevalence of subclinical psychiatric symptoms is higher in late childhood and adolescence compared to adulthood. Adolescence, marked by swift physical transformations, hormonal shifts, brain restructuring, and a transition in social roles, represents a high-risk period for mental and emotional disorders. This review systematically explores the sexual development, hormonal changes and physical development, neurodevelopment and effects of hormones in adolescences, describing the physiological characteristics underlying of susceptibility to mental and emotional disorders during adolescence.

Background: Despite well-documented relationships between climate and malaria transmission, there is a lack of information on how precipitation and temperature as climatic factors specifically impact malaria burden among different age groups in high-transmission areas in western Kenya. Current models often overlook the time-lagged effects of climate variables, such as precipitation and temperature, on age-group specific malaria burden. Methods: This study utilized monthly malaria positivity data from three health centers, along with climate data from western Kenya by applying Negative Binomial mixed effects models with both current and lagged climate variables. Interaction plots, analysis of deviance, and goodness-of-fit tests were used to assess the significance of some relationships or choose a model with a better fit. Results: The study revealed that lagged precipitation (Lag2) and temperature were significant predictors of malaria positivity, with older age groups showing higher susceptibility. Site-to-site and year-to-year variations were also identified as important sources of variation to be considered. Conclusions: The study highlights the importance of considering both age-specific vulnerability and climatic influences in malaria control strategies, suggesting the need for targeted interventions for malaria risk in age-specific groups following the period of precipitation.

The review paper by Bai et al. "Translating Earth system boundaries for cities and businesses" elucidates "the steps and choices involved in a scientifically rigorous translation of Earth System Boundaries (ESB) for businesses and cities".[1] It is hoped that such purportedly scientifically rigorous approaches will enable translation of global frameworks, such as planetary boundaries and carbon budgets to smaller scales for local decisions. Ten principles for translating ESBs to businesses and cities are proposed to establish a fully coherent and transparent procedure. Similar approaches have also been used by others in recent publications [2,3]

not-yet-known not-yet-known not-yet-known unknown In this article, we indicate that under suitable assumptions of a modulus of continuity we obtain either the global (in time) existence of small data Sobolev solutions or the blow-up result of local (in time) Sobolev solutions to semi-linear damped σ-evolution equations with a modulus of continuity term in the nonlinearity of derivative type. When the latter situation occurs, another novelty of this work is to report sharp estimates for the lifespan of solutions, which have never appeared in previous literature, by catching the upper bound and the lower bound simultaneously.

Background Long-acting Gonadotropin-releasing hormone analogs(GnRHa), including leuprolide, goserelin, histrelin, buserelin, triptorelin, have been widely used for a variety of diseases including prostate cancer, breast cancer, endometriosis, uterine leiomyomas, and central precocious puberty. However, their real-world safety profile differences have not been adequately compared. Objective: We aimed to investigate the adverse event (AE) profile differences of long-acting GnRHa reported by the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: All indications were searched long-acting GnRHa, as primary suspect drugs, from FAERS data (January 2004 to September 2023). We performed disproportionality analyses by reporting odds ratios (ROR) and conducted univariate and multivariate logistical regression analyses to determine the odds ratio (OR) of serious AEs associated with long-acting GnRHa under different exposure factors. Results: Reproductive system and breast disorders possessed the greatest proportion in AEs of the five long-acting GnRHa. Buserelin and histrelin demonstrated a higher percentage of AEs in the gastrointestinal and psychiatric disorders separately, which also exhibited a higher risk of important medical events in logistic regression analysis and the risk was lower in patients under 18 years old than those over 18 . Conclusions：Significant disparities exist between the adverse event profiles of long-acting GnRHa.The identification of high-risk factors and the enhancement of AEs monitoring are crucial during clinical application.

Researchers and academics are frequently challenged with processing vast amounts of literature, often requiring precise, targeted summaries that cater to specific informational needs. A novel approach has been developed to enhance the precision of automated academic summarization by leveraging prompt-based techniques that steer content focus in a more controlled manner. Through carefully designed prompts and fine-tuning processes, the method enables more relevant and concise summaries by directing the model's attention toward particular sections of a document, such as methodologies or key findings. The fine-tuned model not only improves content relevance but also adapts dynamically across diverse academic domains, demonstrating substantial advancements in generating high-quality, domain-specific summaries. Experimental results indicate that the model's capacity to produce coherent, focused summaries directly aligned with user prompts offers significant potential for streamlining literature reviews and other academic tasks that require processing extensive textual data. This research showcases the effectiveness of prompt-based content steering and fine-tuning in transforming the capabilities of LLMs, pushing the boundaries of automated academic summarization.

This research aims to present the studies on contract management (CM) from a holistic perspective by conducting bibliometric analysis. Data were collected from the Web of Science core database. A total of 125 articles were reached after applying the search criteria. The bibliometric data obtained was analyzed using VOSviewer software. Research from 23 countries or regions and 5 different disciplines has been published. The most studies were conducted in 2022, 2017, and 2018 and the field of Health Care Sciences Services. Health Services Research, Hospital Health Services Administration, and Hospitals Health Networks journals have a major academic impact. The USA and Newcastle University have made the most significant contributions in this area. There is no clear leadership among authors publishing in the field of CM. The first three keywords used most frequently in the works are contracting, contract management, and Cambodia. It is important for researchers to show more interest in the CM field and to collaborate internationally. More research on (1) the typologies and classifications of CM and (2) the effectiveness and performance of CM (especially in countries implementing CM) will contribute to our knowledge in this area and will also guide policy in this area.

The activity budget quantifies time and describes how animals spend their time among various activities such as foraging, self-maintenance, and reproduction. The study investigated how Lesser Adjutant Storks (Leptoptilos javanicus) adjust their behaviour in response to human disturbance in Janakinagar-Murtiya Important Bird and Biodiversity Area of Nepal. Using the Focal Animal Sampling method, we captured 600 minutes of video footage along road transects over two seasons (summer and winter 2023). The behavioural analysis revealed significant shifts: during summer, the storks spent 47.18% of their time on vigilance, while in winter, they devoted 26.2% of their time to feeding. This indicates that storks prioritize vigilance to mitigate risks from human interference. As human disturbance increases, species exhibits a stronger preference for vigilance over other activities. The data shows that vigilance takes precedence over feeding, highlighting an increased focus on vigilance in response to heightened disturbance (p < 0.05). This strategic shift underscores the importance of vigilance for the storks’ survival in their habitat. Our findings, including a significant behavioural shift (df = 3, χ² = 1174.95, p < 0.05), emphasize the need to understand how disturbance influences stork behaviour for effective conservation. By comprehending these patterns, conservation efforts can be tailored to mitigate the impact of human activities on stork populations.

In pollination networks, indirect plant-plant interactions mediated by their shared pollinators, can shape community dynamics and species fitness; yet, the influence of floral traits on species roles remains unclear, particularly in diverse ecosystems like the tropical Andes. We studied hummingbird-mediated interactions among 31 flowering plants in three high-elevation shrubby habitats located in southern Ecuador. During August and November 2022, and January 2023, we collected stigma samples and constructed weighted interaction networks linked by heterospecific pollen grains. Species roles were determined by defining if they were overall donors or receptors of pollen. We also explored the association between the abundance of flowers and different floral traits and species roles. Finally, we assessed the potential influence of floral roles on species fitness by calculating the ratio of conspecific-to-heterospecific pollen grains observed in each species. We found that the identity of donor and receptor species was highly dynamic across sites and time. Donor species were characterized by being highly abundant, and having long and wide corollas, while receptor species had low abundance, and short and narrow corollas. Donor species received less heterospecific pollen than conspecific pollen, indicating that the pollen sharing roles of species could have fitness consequences. Our findings highlight the importance of floral traits and abundance in shaping floral roles and their potential fitness consequences in hummingbird-mediated indirect interactions.

Understanding the spatial and temporal distributions of rare species is important for informed management. The black-necked crane Grus nigricollis, a rare bird in China and flagship species in alpine wetlands, is nationally protected. Using site and environmental data, we use Maximum Entropy (MEM) and Random Forest (RFM) models to predict suitable habitat for this bird. Environmental variables that most affect its distribution are distance from buildings and roads, and isothermality, with contribution rates of 15.1%, 15.05%, and 5.85%, respectively. Using the AUC (area under curve) coefficient as an index to evaluate model precision, the predictions of the RFM are most consistent with the known distribution of these cranes, predicting the highest match with known crane sites (AUC = 0.945). Suitable habitat for this crane occurs mainly in Nyingchi city riverine wetland, where the centre of distribution is located in a valley where the Yarlung Tsangpo and Niyang rivers converge. A comparison between MEM and RFM outputs reduces uncertainty in predictions of black-necked crane spatial distribution, and filters optimal results for the distribution area. These results enable more-informed protection of habitat for this sacred crane.

Marine plastispheres represent dynamic microhabitats where microorganisms colonise plastic debris and interact. Metaproteomics has provided novel insights into the metabolic processes within these communities, however the early metabolic interactions driving the plastisphere formation remain unclear. This study utilised metaproteomic and metagenomic approaches to explore early plastisphere formation on low-density polyethylene (LDPE) over three (D3) and seven (D7) days, focusing on microbial diversity, metabolic activity, and biofilm development. In total, 2,948 proteins were analysed, revealing dominant proteomes from Pseudomonas and Marinomonas, with near-complete metagenome-assembled genomes. Pseudomonas dominated at D3, while at D7, Marinomonas, along with Acinetobacter, Vibrio, and other genera became more prevalent. Pseudomonas and Marinomonas showed high expression of reactive oxygen species (ROS) suppression proteins, associated with oxidative stress regulation, while granule formation, and alternative carbon utilisation enzymes, also indicated nutrient limitations. Interestingly, 13 alkane and other xenobiotic degradation enzymes were expressed by five genera. The expression of toxins, several type VI secretion system (TVISS) proteins, and biofilm formation proteins by Pseudomonas indicated their competitive advantage against other taxa. Upregulated metabolic pathways, including those relating to substrate transport also suggested enhanced nutrient cross-feeding within the biofilm. These insights enhance our understanding of plastisphere ecology and its potential for biotechnological applications.

Manuscript type:- Case Report

Proximity-dependent biotinylation (PDB) is a powerful means of exploring the cellular environments in which proteins reside. Expressing a protein of interest (bait) fused to a biotin ligase and adding biotin induces the covalent biotinylation of proximal partners, which are recovered on streptavidin beads and identified by MS. However, a major technical limitation of PDB is peptide carryover into subsequent MS runs. This is mitigated via lengthy inter-sample washing, considerably lowering throughput. This study aims to optimize PDB sample acquisition using an EvoSep LC system coupled to a timsTOF mass spectrometer, which has higher throughput and sensitivity than our current system, with less carryover. Our efforts resulted in an ~15-fold increase in throughput using the 60 samples-per-day (SPD) gradient with better sensitivity, identifying nearly double the proteins found by our previously standardized workflow. Significance scoring also revealed more sensitive detection of high-confidence proximal interactions (~1.5-fold) for five well-characterized baits, validating the new experimental workflow. Importantly, carryover was extremely limited, even without inter-sample washing, and limited to easily filterable abundant proteins. Without washing, this method can process 60 samples per day, using 1/16th of the sample amount previously required.

Gallium nitride (GaN) high electron mobility transistors (HEMTs) have attracted considerable attention due to high electron mobility, wide bandgap, and other advantageous properties. However, the self-heating that occurs at high power densities has emerged as a significant challenge that restricts HEMTs’ potential in high-performance applications. This study introduces a novel approach for extracting channel temperature distributions and thermal resistance, which considers the bias-dependence of the heat source model and the electro-thermal coupling among multiple gate fingers. The thermal resistance extracted by the optimized thermal model in this study differs from the traditional thermal model by 14.8% under a power density of 8W/mm and a base temperature of 1 0 0 ◦ C . The precision of the model is validated through infrared (IR) thermography, showing only a 1.76% discrepancy in the peak surface temperature of the filtered model compared to the measurement. To evaluate the model’s applicability across various conditions, comparisons are conducted between the model’s predictions and measurements across a range of ambient temperatures and power dissipation, revealing maximum errors of 4.1% at 7 5 ◦ C and 2.7% at 1 0 0 ◦ C . Finally, the influence of thermal boundary resistance (TBR) on the total thermal resistance is explored to provide guidance for device modeling and thermal management.

Climate shapes ecological communities across space and time. It sets physiological limits for organisms, driving population dynamics, species distributions, community assembly and ultimately, biodiversity patterns. Among the various aspects of climate, an underexplored dimension is its frequency distribution—how common or rare climatic conditions are across space. To uncover the mechanisms driving community-level responses to climatic frequency, we addressed three key questions: Does climatic frequency influence the phylogenetic structure of ecological communities across geographical scales? Are rare climates less suitable for supporting the diversity of closely related species than common climates? Do species with relatively recent ancestors exhibit similar preferences for climatic frequencies? We analyzed global data on climate, geographical distributions, and phylogenetic relationships of extant terrestrial tetrapods – amphibians, birds, mammals, and squamate reptiles. Globally, we found that ecological communities are less phylogenetically clustered in rare climates. Our results reveal that communities in rare climates exhibit lower phylogenetic clustering, reflecting greater phylogenetic diversity. Additionally, species co-occurring in both exceedingly rare and highly common climates tend to depart from their climatic optima. Our findings suggest that climate frequency plays a more influential role in recent ecological dynamics and evolutionary adaptations than deep ancestral constraints in shaping these communities.

Neural networks have proven highly effective in signal processing and AI, particularly in handling complex, high-dimensional data with temporal dependencies. Additive recurrent On-Center Off-Surround (OCOS) networks are inspired by biological neural systems and are known for their ability to enhance contrast and selectively process information. In this work, we propose the use of Chebyshev polynomials as activation functions in additive recurrent OCOS networks to improve their performance in signal processing tasks. Chebyshev polynomials offer excellent approximation properties with minimal computational overhead, making them well-suited for dynamic systems. We demonstrate that integrating these polynomials as activation functions enhances the network’s ability to extract features, recognize patterns, and maintain stability in real-time signal analysis. Through empirical evaluations, we show that networks using Chebyshev polynomial activations outperform those using traditional activation functions in terms of stability, accuracy, and computational efficiency. The proposed framework is applied to various AI tasks, including real-time data analysis and adaptive filtering, highlighting its advantages in dynamic environments. Our results suggest that Chebyshev polynomials, when combined with additive recurrent OCOS networks, provide a robust and efficient approach to solving complex problems in AI and signal processing.

Title: An Endoscopic View Of A Rare Clinical FindingFakhruddin Almuzghi* (1), Mohamed Taraina (2), Mansur Bengharbya (2), Ismail Alghanodi (2), Abdulmottaleb Abushaala (2)(1) Internal Medicine Department, Hamad General Hospital, Hamad Medical Corporation, Qatar(2) Internal Medicine Department, Misrata Medical Center, Misrata, Libya*Corresponding author:Fakhruddin Almuzghi, MBChBInternal Medicine Department,Hamad General Hospital,Hamad Medical Corporation,QatarFAlmuzghi@hamad.qa

RENAL ARTERY THROMBOSIS: A CASE REPORT OF ACUTE ABDOMINAL PAIN AND RENAL ARTERY OCCLUSION