Search Results (71,384)

Background/Objectives: The purpose of this study was to determine whether a periodized resistance training program would influence self-reported depression and anxiety scores in college-aged females. Methods: Eight participants participated in a six-week periodized resistance training program. The participants completed a 3–5 repetition maximum (3–5 RM) for the sumo deadlift (SDL), bench press (BP), barbell back squat (BBS), and standing shoulder press (SSP). These data were used to estimate the 1 repetition maximum (1RM), which in turn was used to develop the periodization program. Following baseline testing, participants participated in two full-body workouts per week for six weeks. Each individual was retested after they completed the 6-week program, performing 3–5 RM for the SDL, BP, BBS, and SSP. To determine symptoms of depression and anxiety, the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) were distributed before and after participating in the resistance training program. A repeated measures 2 × 2 Analysis of Variance (ANOVA) was used to determine the effect of resistance training had on the outcome measures. Results: There was a significant (p = 0.011) decrease in BDI scores after the 6 weeks of resistance training. There was no statistically significant difference in the BAI scores (p = 0.106). There was no correlation between any individual exercise and the outcome scores. Conclusions: The results of the current study indicate that a periodized resistance training program is effective at reducing self-reported measures of depression using the BDI in college-aged females. Full article

In this work, we report the properties of molybdenum disulfide (MoS₂) thin films deposited on the p-type silicon substrate using RF magnetron sputtering. The structural, vibrational and morphological properties of MoS₂ thin films were investigated using the Raman spectroscopy, X-ray diffraction technique (XRD), atomic force microscope (AFM) and scanning electron microscope (SEM). Raman spectroscopy result showed the appearance of broad E¹_2g and A_1g Raman peaks even without DC biasing the substrate and becomes sharp and distinct when the substrate is DC biased at 60 V. Post-deposition annealing in sulfur ambient resulted in sharp and distinct Raman E¹_2g and A_1g peaks confirming the formation of MoS₂ thin film and improved Mo-S bonding on the top surface. X-ray diffraction spectra of the samples validates the formation of MoS₂ thin film with the appearance of [002] XRD peak, when the substrates are biased. Improved morphological effects with the reduction in nano-sized defects, advent of continuous film and low surface rms roughness value of 0.872 nm, were observed on samples deposited with substrate biasing and post sulfur annealing. A back-gated thin film transistor was fabricated with Al as source-drain contacts and MoS₂ as the semiconducting channel. The fabricated transistor exhibited p-type transfer characteristics with threshold voltage of −3.8 V. As a result of annealing and ambient exposure, MoO₃ fragments on the top of thinned MoS₂ layer resulted in extraction of hole from MoS₂, resulting in the p-type behavior in the fabricated thin film transistor. The combination of XRD analysis, Raman measurements and EDS data of the film confirmed MoO₃ inclusions in the MoS₂ thin film. Full article

Background and Objectives: Diabetes mellitus is a prevalent chronic disease caused by inadequate insulin secretion or ineffective insulin response, leading to complications such as retinopathy, nephropathy, heart attacks, and strokes. Recently, “diabetes distress (DD)” has emerged as a concept, highlighting the significant emotional burden of managing diabetes, which can impact disease outcomes. Thus, this study evaluates the impact of virtual clinics on diabetes distress and glycemic measures in individuals with diabetes mellitus. Materials and Methods: A cross-sectional study was conducted between May and August 2024 at the Endocrine and Diabetes Center in Alahsa, Saudi Arabia, targeting persons aged 18 and older with diabetes who had engaged in-person clinics, virtual clinics, or both between 2019 and 2024. Data were collected through structured phone interviews, supplemented by laboratory results from clinical records. The survey included demographic details, diabetes information, and the Diabetes Distress Scale. Statistical analyses, including descriptive statistics, were performed to explore the relationships between diabetes distress, clinic visit type, and glycemic control, with Mann–Whitney and Chi-Squared tests used to compare variables between two groups. Results: Of the 108 participants, 55.6% were male, with a mean age of 38.5 years. Type 2 diabetes was reported in 51.9% of individuals, while 48.1% had type 1. High emotional burden (44.4%) and regimen-related distress (28.7%) were prevalent, particularly among individuals with suboptimal glycemic control. While virtual visits were not significantly correlated with lower distress levels, individuals with suboptimal glycemic control exhibited significantly higher diabetes distress across various domains, including emotional and regimen-related distress (p < 0.05). Laboratory analysis showed a median HbA1c of 8.2%, with poor control associated with greater distress. Conclusions: Diabetic individuals with suboptimal glycemic control report higher diabetes distress levels, underscoring the need for integrated psychological support in DM care. Although virtual clinic visits did not significantly reduce distress, they provide a feasible option for individual follow-up. Full article

Background/Objectives: In tennis, timing plays a crucial factor as it influences the technique and effectiveness of strokes and, therefore, matches results. However, traditional technical evaluation methods rely on subjective observations or video motion-tracking technology, mainly focusing on spatial components. This study evaluated the reliability of an acoustic detection system in analyzing key temporal elements of the game, such as the rally rhythm and timing of strokes. Methods: Based on a machine learning algorithm, the proposed acoustic detection system classifies the sound of the ball’s impact on the racket and the ground to measure the time between them and give immediate feedback to the player. We performed trials with expert and amateur players in controlled settings. Results: The ML algorithm showed a detection accuracy higher than 95%, while the average accuracy of the whole system that was applied on-court was 85%. Moreover, this system has proven effective in evaluating the technical skills of a group of players on the court and highlighting their areas for improvement, showing significant potential for practical applications in player training and performance analysis. Conclusions: Quantitatively assessing timing offers a new perspective for coaches and players to improve performance and technique, providing objective data to set training regimens and optimize game strategies. Full article

Urolithiasis represents one of the most common urologic diseases, and its incidence demonstrates, globally, an increasing trend. The application of preventive measures is an established strategy to reduce urolithiasis-related morbidity, and it is based mostly on the adaptation of lifestyle factors and pharmacotherapy. Furthermore, other research areas demonstrate promising results, such as the research on the microbiome. In the current review, we searched for the latest data on lifestyle–based prevention and microbiome alterations in urolithiasis patients. The majority of the proposed lifestyle measures are already included in the urological guidelines, while additional factors, such as vitamin D supplementation, seem to have a putative positive effect. From the microbiome studies, several microbial composition patterns and metabolic pathways demonstrated an inhibiting or promoting role in lithogenesis. Up to the present, stone prevention has not shown satisfying results, which suggests that lifestyle measures are not adequate. Moreover, microbiome studies are prone to bias, since microbes are strongly affected by numerous clinical factors, while the analysis procedures are not standardized yet. Analysis standardization and data pooling from extensive registration of clinical and microbiome data are essential steps in order to improve the existing prevention strategy with targeted microbiome manipulations. Full article

An improved method for identifying nighttime tweek signals in WHU VLF measurements was developed by redesigning the extraction process and validated through comparison with World-Wide Lightning Location Network (WWLLN) data. Using the enhanced method, 1,728,032 tweek signals were identified from four years (2018–2021) of VLF data, forming the most comprehensive tweek dataset for the mid–low latitude region in China. Statistical analysis reveals distinct nighttime variations in tweek occurrence rates, which increase from 18:00 LT to 20:00 LT, remain high until 04:00 LT, and gradually decrease towards sunrise. Seasonal differences in propagation distance are evident, ranging from ~2000 km in summer to ~4000 km in winter, corresponding to the seasonal shift of lightning activity. The cutoff frequency showed apparent daily and seasonal fluctuations, and the trends of daily variation are opposite between winter and summer. The annual variation in cutoff frequency presents a pattern different from previous cognition, with a minimum of 1.62 kHz in summer and a maximum of 1.68 kHz in winter, influenced by the magnetic cyclotron frequency at ionospheric reflection points. These findings improve the understanding of nighttime tweek characteristics and ionospheric dynamics in East Asia, offering valuable insights for ionospheric research and VLF communication systems. Full article

Background/Objectives: Localization deficit is often said to be a symptom of Auditory Processing Disorder (APD). However, no clinically viable assessment of localization ability has been developed to date. The current study presents pilot data for a new assessment of absolute auditory localization using headphones. Methods: Speech phrases encoded with non-individualized head-related transfer functions (HRTF) using real-time digital processing were presented to two cohorts of participants with normal hearing. Variations in the simulated environment (anechoic and reverberant) and signal to noise ratio (SNR) were made to assess each of these factors’ influences on localization performance. Experiment 1 assessed 30 young adults aged 21–33 years old and Experiment 2 assessed 28 young adults aged 21–29 years old. All participants had hearing thresholds better than 20 dB HL. Results: Participants performed the localization task with a moderate degree of accuracy (Experiment 1: Mean RMS error = 25.9°; Experiment 2: Mean RMS error 27.2°). Front–back errors (FBEs) were evident, contributing to an average RMS error that was notably elevated when compared to similar free-field tasks. There was no statistically significant influence from the simulated environment or SNR on performance. Conclusions: An exploration of test viability in the pediatric and APD-positive populations is warranted alongside further correction for FBEs; however, the potential for future clinical implementation of this measure of absolute auditory localization is encouraging. Full article

Background: The palmaris longus (PL) is a long, thin muscle in the forearm’s flexor compartment, known for its variations. The present study aimed to study the PL muscle in Omani medical students and its correlation with grip strength. Methods: A cross-sectional prospective study was conducted among 240 medical students (120 males, 120 females) at Sultan Qaboos University, comprising 480 upper limbs. Participants were between 18 and 25 years old and had no history of forearm surgery. We considered 480 upper limbs irrespective of left or right side, and our main aim was to compare the grip strength according to the presence or absence of PL. We assessed the presence of the PL muscle using Schaeffer’s Test and Pushpakumar’s test and measured the grip strength using the CAMRY digital hand dynamometer. The data were analyzed using descriptive statistics, Chi-square tests, and independent t-tests. Results: The PL was present in 92.50% of the subjects (irrespective of side), with a higher prevalence in the females. The PL was absent in 24 (10.00%) males and 12 (5.00%) females, respectively. Average grip strength was 21.4 ± 5.25 kg in females and 40.92 ± 7.79 kg in males without considering PL presence or absence. If PL was present, then the mean grip strength was 30.84 ± 11.71 kg, and if the PL was absent, then the mean grip strength was 35.05 ± 12.44 kg. However, the p-value did not show any significant differences (p = 0.057). Conclusions: The PL is highly prevalent, especially in females, and its absence does not significantly affect grip strength. Hence, PL may be used for successful reconstructive surgeries without affecting hand function. Full article

The UK retail landscape has undergone significant changes over the past decade, driven by factors such as the rise of online shopping, economic downturns, and, more recently, the COVID-19 pandemic. Accurately measuring pedestrian flows in retail areas with high spatial and temporal resolution is essential for selecting the most appropriate forecasting model for different retail locations. However, several studies have adopted a one-size-fits-all approach, overlooking important local characteristics that are only occasionally captured by the best global model. In this work, using data generated by the SmartStreetSensor project, a large network of sensors installed across UK cities that collect Wi-Fi probe requests generated by mobile devices, we examine the optimal forecasting method to predict pedestrian footfall in various retail areas across Great Britain. After assessing six representative time series forecasting models, our results show that the LSTM model outperforms traditional methods in most areas. However, pedestrian counts at certain locations with specific spatial characteristics are better forecasted by other algorithms. Full article

Managing foliar corn diseases like northern leaf blight (NLB) and gray leaf spot (GLS), which can occur rapidly and impact yield, requires proactive measures including early scouting and fungicides to mitigate these effects. Decision support tools, which use data from in-field monitors and predicted leaf wetness duration (LWD) intervals based on meteorological conditions, can help growers to anticipate and manage crop diseases effectively. Effective crop disease management programs integrate crop rotation, tillage practices, hybrid selection, and fungicides. However, growers often struggle with correctly timing fungicide applications, achieving only a 30–55% positive return on investment (ROI). This paper describes the development of a disease-warning and fungicide timing system, equally effective at predicting NLB and GLS with ~70% accuracy, that utilizes historical and forecast hourly weather data. This scalable recommendation system represents a valuable tool for proactive, practicable crop disease management, leveraging in-season weather data and advanced modeling techniques to guide fungicide applications, thereby improving profitability and reducing environmental impact. Extensive on-farm trials (>150) conducted between 2020 and 2023 have shown that the predicted fungicide timing out-yielded conventional grower timing by 5 bushels per acre (336 kg/ha) and the untreated check by 9 bushels per acre (605 kg/ha), providing a significantly improved ROI. Full article

The study performed in this article aimed to reproduce the penetrometric profile of the soil from the perforation parameters of deep foundation and ground improvement. This could allow for more easily interpretable information on the soil strength during execution as well as validate the design hypotheses. To achieve this goal, a series of Machine Learning algorithms have been used and compared with traditionally applied analytical formulas. Dynamic time warping is used to measure the likeness of the results with the expected shape. The results show that the algorithms are capable of better fitting the penetrometric profiles of the soil. Tree ensemble methods stand out with the best results. Full article

Cure models and receiver operating characteristic (ROC) curve estimation are two important issues in survival analysis and have received attention for many years. In the development of biostatistics, these two topics have been well discussed separately. However, a rare development in the estimation of the ROC curve has been made available based on survival data with the cure fraction. On the other hand, while a large body of estimation methods have been proposed, they rely on an implicit assumption that the variables are precisely measured. In applications, measurement errors are generally ubiquitous and ignoring measurement errors can cause unexpected bias for the estimator and lead to the wrong conclusion. In this paper, we study the estimation of the ROC curve and the area under curve (AUC) when variables or biomarkers are subject to measurement error. We propose a valid procedure to handle measurement error effects and estimate the parameters in the cure model, as well as the AUC. We also make an effort to establish the theoretical properties with rigorous justification. Full article

This study investigates the viability of incorporating bicycles into the Dhaka Metro system, a groundbreaking urban transit project for Bangladesh. As Dhaka’s inaugural metro rail network, the system signifies a substantial advancement in addressing urban congestion and enhancing transportation alternatives in one of the world’s most densely populated cities. The current design of the metro fails to accommodate bicycles, hindering efficient first- and last-mile connectivity. The investigation utilized data from 382 fully completed questionnaires, obtained through purposive sampling, about metro–cycle integration in Dhaka. The research employed RIDIT and TOPSIS analyses to rank the characteristics deemed most essential for bicycle–metro integration according to user opinions. Research indicates that secure bicycle parking, multi-modal ticketing, route comfort, and safety measures are the foremost objectives for commuters. The high emphasis on secure parking indicates the need for safe and accessible storage options that would make cycling a viable mode for reaching metro stations. A multi-modal ticketing system further enhances convenience, providing seamless transitions between transit modes. Journey comfort and the need to mitigate risks posed by motorized vehicles underscore the importance of safe and user-friendly commuting environments. While features like road and station design were ranked lower in priority, the study emphasizes that a well-integrated bicycle infrastructure is essential to ensure the metro system’s success. With these improvements, Dhaka’s metro system can meet the growing demands for sustainable and inclusive urban mobility, setting a precedent for future infrastructure projects in Bangladesh. Full article

Background/Objectives: Depressive disorders are diagnosed using categorical definitions provided by DSM-5 and ICD-11. However, categorization for diagnostic purposes fails to account for the inherently dimensional nature of depression. Artificial categorization may impede research and obstruct the achievement of optimal treatment outcomes. Methods: The current study utilized a Canadian historical dataset called the National Population Health Survey (NPHS) to explore a simple alternative approach that does not depend on categorization. The NPHS collected complete data from 5029 participants through biannual interviews conducted in 1994–2010. Data collection included the K6 Distress Scale as well as the Composite International Diagnostic Interview Short Form for Major Depression. Data from the National Population Health Survey (NPHS) were used to quantify vulnerability to depressive symptoms through longitudinal K6 Distress Scale assessments. Variability of symptoms across this dimension of apparent vulnerability was quantified using ordinal regression, adjusting for age and sex. Results: Predicted probabilities from these models were used in simulations to produce a visualization of the epidemiology and to explore clinical implications. Conclusions: Consideration of these two dimensional factors (estimated overall level of vulnerability to depression and variability over time) is already a component of clinical assessment and is also accessible to repeated measurement in settings adopting measurement-based care. More formal consideration of these elements may provide a complementary approach to categorical diagnostic assessment and an opportunity for greater personalization of care and improved clinical outcomes. Future studies should validate these findings in diverse clinical settings to ensure their applicability in real-world contexts. Full article

The dispersion measures (DMs) of the fast radio bursts (FRBs) are a valuable tool to probe the baryonic content of the intergalactic medium and the circumgalactic medium of the intervening galaxies along the sightlines. However, interpreting the DMs is complicated by the contribution of the hot gas in and around our Milky Way. This study examines the relationship between $D{M}_{\mathrm{MW}}$, derived from localized FRBs, and the Galaxy’s hot gas, using X-ray absorption and emission data from O vii and O viii. We find evidence for a positive correlation between $D{M}_{\mathrm{MW}}$ and O vii absorption, reflecting contributions from both the disk and halo components. This conclusion is supported by two lines of evidence: (1) no correlation between $D{M}_{\mathrm{MW}}$ and O vii/O viii emission, which primarily traces dense disk regions; and (2) the comparison with electron density models, where $D{M}_{\mathrm{MW}}$ aligns with models that incorporate both disk and halo components but significantly exceeds predictions from pure disk-only models, emphasizing the halo’s role. Furthermore, the lack of correlation with O viii absorption suggests that the primary temperature of the Galaxy’s hot gas is likely around $2\times {10}^6$ K or less, as traced by O vii absorption, while gas at higher temperatures (∼3–5 × ${10}^6$ K) is present but less abundant. Our findings provide insights into the Milky Way’s gas distribution and improve $D{M}_{\mathrm{MW}}$ estimates for future cosmological studies. Full article