Search Results (113)

As artificial intelligence (AI) becomes increasingly utilized to perform tasks requiring human intelligence, patients who are pregnant may turn to AI for advice on over-the-counter (OTC) medications. However, medications used in pregnancy may pose profound safety concerns limited by data availability. This study focuses on a chatbot’s ability to accurately provide information regarding OTC medications as it relates to patients that are pregnant. A prospective, descriptive design was used to compare the responses generated by the Chat Generative Pre-Trained Transformer 3.5 (ChatGPT-3.5) to the information provided by UpToDate^®. Eighty-seven of the top pharmacist-recommended OTC drugs in the United States (U.S.) as identified by Pharmacy Times were assessed for safe use in pregnancy using ChatGPT-3.5. A piloted, standard prompt was input into ChatGPT-3.5, and the responses were recorded. Two groups independently rated the responses compared to UpToDate on their correctness, completeness, and safety using a 5-point Likert scale. After independent evaluations, the groups discussed the findings to reach a consensus, with a third independent investigator giving final ratings. For correctness, the median score was 5 (interquartile range [IQR]: 5–5). For completeness, the median score was 4 (IQR: 4–5). For safety, the median score was 5 (IQR: 5–5). Despite high overall scores, the safety errors in 9% of the evaluations (n = 8), including omissions that pose a risk of serious complications, currently renders the chatbot an unsafe standalone resource for this purpose. Full article

Agricultural workers—individuals employed for labor in agriculture—are at high risk of various negative health outcomes, with many impacted by both the existence of health disparities and stress. While the issue of farm stress and associated psychosocial health outcomes has been studied in the general agricultural population, research investigating these issues specifically within the agricultural worker population is sparse. This study presents data from the United States Western Region Agricultural Worker Stress Survey (N = 354), which gauged workers’ perceived stress levels, sources of stress, desired stress management topics, and preferred methods of receiving information and support services. Long working hours, working in extreme temperatures, and a lack of time emerged as the top three stressors. On average, workers across the Western region of the U.S. are experiencing a moderate level of stress, with younger workers reporting greater stressor pileup than their older counterparts. Retirement planning was cited as the most preferred stress management topic, regardless of demographic. Lastly, workers chose in-person counseling as the support modality that they would most likely utilize. This research provides a variety of stress management recommendations such as working with farm owners to increase the safety of their operation, investing in face-to-face counseling services, and utilizing community health workers as sources of support. Full article

Personalized itinerary recommendations are essential as many people choose traveling as their primary leisure pursuit. Unlike model-based and optimization-based methods, sequential-pattern-mining-based methods, which are based on the users’ previous visiting experience, can generate more personalized itineraries and avoid the difficulties caused by the two methods. Although sequential-pattern-mining-based methods have shown promise in generating personalized itineraries, the following three challenges remain. First, they often overlook user diversity in time and category preferences, leading to less personalized itinerary suggestions. Second, they typically evaluate sequences only by POI preference, ignoring crucial factors of optimal visiting times and travel distance. Third, they tend to recommend feasible but not optimal itineraries without exploring extended combinations that could better meet user constraints. To solve the difficulties above, a novel personalized itinerary recommendation system for social media is proposed. First, the user preference, which contains time and category preferences, is generated for all users. Users with similar preferences are clustered into the same group. Then, the sequential pattern mining algorithm is adopted to create frequent sequential patterns for each group. Second, to evaluate the suitability of an itinerary, we define the itinerary score according to the considerations of the POI preference, time matching, and travel distance. Third, based on the tentative itineraries generated from the sequential pattern mining process, the Sequential-Pattern-Mining-based Itinerary Recommendation (SPM-IR) algorithm is developed to create more candidate itineraries under user-specified constraints. The top-N candidate sequences ranked by the proposed itinerary score are then returned to the target user as the itinerary recommendation. A real-life dataset from geotagged social media is implemented to demonstrate the benefits of the proposed personalized itinerary recommendation system. Empirical evaluations show that 94.82% of the generated itineraries outperformed real-life itineraries in POI preference, time matching, and travel-distance-based itinerary scores. Ablation studies confirmed the contribution of time and category preferences and highlighted the importance of time matching in itinerary evaluation. Full article

Background/Objectives: Despite advances in public health and medical treatment, the number of patients with type 2 diabetes is increasing and it remains among the top 10 causes of death and a leading cause of disability in the United States. Early interventions with innovative approaches are essential to improving dietary intake and blood glucose control, potentially preventing or delaying type 2 diabetes and related complications. This study examined the effects of integrating real-time feedback from continuous glucose monitoring (CGM) into individualized nutrition therapy (INT) on diet and sleep quality in individuals with prediabetes and overweight or obesity. Methods: Thirty participants were randomized to either the treatment (n = 15) or the control group (n = 15). Both groups received individualized nutrition recommendations tailored to energy needs for weight maintenance and blood glucose control. The treatment group had real-time access to CGM data, while the control group remained blinded. Dietary intake and sleep quality were assessed using ASA24 recall and analyzed via general linear model repeated measures. Results: Incorporating CGM feedback into nutrition therapy significantly increased whole-grain (p = 0.02) and plant-based protein intake (p = 0.02) in the treatment group, with trends toward increased fruit intake (p = 0.07) and a reduced percentage of calories from carbohydrates (p = 0.08). Sleep efficiency also improved significantly by 5% (p = 0.02) following the intervention. Conclusions: These findings support the effectiveness of CGM-enhanced nutrition therapy in improving diet and sleep quality in individuals with prediabetes and overweight or obesity. Further research is needed to assess the sustainability and long-term impact of this approach. Full article

Heterogeneous information networks (HINs) have seen rapid development and have attracted extensive attention because of their effectiveness in recommender systems. Although many existing models based on HINs for recommender systems have obtained good recommendation performance on account of their superior ability to process heterogeneous data and capture rich semantic information, there are still several problems. Firstly, the temporal relations among different nodes in meta-paths, which include users and items, are rarely considered in HINs. Secondly, the interactions among meta-paths, users, and items are similarly often overlooked. Thirdly, their ability to learn the heterogeneous information of users and items is limited. In view of the above problems, we propose a system for the temporal enhancement of top-N recommendations on HINs called TMRec. Specifically, we first adopted long short-term memory (LSTM) and residual self-attention (RSA) to process users and items and enhance the network’s ability to both learn the heterogeneous information in them and capture the temporal relations among them. Second, we designed a novel method for processing meta-paths, including deep perception self-attention (DPSA), max pooling, and L₂-normalization, that can effectively obtain the temporal relations among different nodes in meta-paths. Third, we used collaborative attention to process meta-paths, users, and items to obtain their interactions. Finally, extensive experiments were conducted on four public datasets of recommender systems to verify the superiority of our method compared with state-of-the-art top-N recommendation models. Full article

The imbalanced use of fertilizers, particularly the inefficient application of nitrogen (N), has led to reduced nitrogen use efficiency (NUE), lowered crop yields and increased N losses in Nepal. This study aimed to enhance yields, NUE and farm profitability by optimizing N fertilizer rates, application timing and methods through multilocation trials and demonstrations. In 2017, 57 field trials were conducted in two mid-hill districts using a completely randomized block design. The treatments included control (CK), NPK omission (N0, P0 and K0), variable N rates (60, 120, 180 and 210 kg N ha⁻¹) and top-dressing timings (120 kg N ha⁻¹ applied at knee height and shoulder height, V6, V10 and V8 stages). A full dose of recommended P (60 kg ha⁻¹) and K (40 kg ha⁻¹) were applied at planting, while N was top-dressed in two equal splits at knee-height and shoulder-height growth stages for P and K omission treatments, as well as for treatment with variable N rates. Grain yields responded quadratically, with optimum N rates ranging from 120 to 180 kg ha⁻¹ across the districts. N applied at 120 kg ha⁻¹ and top-dressed at V6 and V10 increased maize yield by 20–25%, partial factor productivity of nitrogen (PFPN) by 12%, agronomic efficiency of nitrogen (AEN) by 21% and gross margin by 10% compared to conventional knee and shoulder height application. In 2018 and 2019, fertilizer BMPs, including V6 and V10 top-dressing and the urea briquette deep placement (UDP) were demonstrated on 102 farmers’ fields across five mid-hill districts to compare their agronomic and economic significance over traditional farmers’ practice (FP). UDP, validated in 2018 field trials, increased yields by 34% (8.8 t ha⁻¹) and urea top-dressing at V6 and V10 increased yield by 33% (8.7 t ha⁻¹) compared to FP (5.8 t ha⁻¹), reducing the average yield gap by 3.0 t ha⁻¹. Moreover, the gross margin was increased by 39% (V6 and V10) and 40% (UDP) over FP. The findings highlight the need for widespread adoption of fertilizer BMPs to close the yield gap and maximize profitability with minimal nitrogen footprint. Full article

Background: Schizophrenia is classified by the World Health Organization (WHO) as one of the top ten diseases contributing to the global medical economic burden. Some studies have pointed out that exercise is effective for physical and mental health, as well as cognition. We hypothesized that participation in pickleball intervention would lead to improved self-esteem and reduced psychiatric symptoms in schizophrenia patients. Method: We recruited participants with schizophrenia from a long-term care facility and a regional hospital, dividing them into two groups based on the institutions. The experimental group underwent a nine-week pickleball exercise intervention, with sessions three times a week, each lasting 90 min, and a Dink ball test was conducted weekly. Questionnaires on self-esteem and the short-form health survey were collected both before and after the intervention. Result: This trial included 30 patients, divided equally into the experimental group (n = 15) and the control group (n = 15). After the nine-week pickleball intervention, there were no significant differences between the experimental and control groups in the Rosenberg Self-Esteem Scale (RSES) (p = 0.153) or the Brief Symptom Rating Scale (BSRS-5) (p = 0.289). However, the Dink test scores in the experimental group showed significant improvements in physical activity capabilities and attention over time, with average hit counts increasing from 5.3 ± 1.5 to 10.7 ± 2.3 (p < 0.01). Conclusions: Although the pickleball intervention did not yield significant differences in self-esteem and symptom measures between groups, the improvements observed in physical performance and attention in the experimental group suggest that exercise remains a feasible complementary approach for managing schizophrenia symptoms. Further research with larger sample sizes is recommended. Full article

Background/Objectives: Oral cancer ranks among the top ten cancers globally, with a five-year survival rate below 50%. This study aimed to evaluate the effectiveness of autofluorescence-guided surgery compared to standard surgical methods in identifying tumor-free margins and ensuring complete excision. Methods: A prospective cohort of 80 patients was randomized into two groups: the control group underwent excision with a 10 mm margin based on clinical judgment, while the experimental group used autofluorescence guidance with a 5 mm margin beyond fluorescence visualization loss. Autofluorescence imaging was performed using the OralID device, which employs a 405 nm excitation laser to detect abnormal tissue. Ethical approval was obtained from the “Spitalul Clinic Municipal de Urgență Timișoara” Ethics Committee (approval number 08/26.02.2021), and the trial was registered at the University of Medicine and Pharmacy Timisoara (trial no. 59/25.11.2021). A double analysis was conducted: a primary analysis of the full cohort and a subgroup analysis focusing on squamous cell carcinoma (control: n = 19; experimental: n = 24). Histopathological analysis was the gold standard for margin evaluation, with margins coded as tumor-free margins (0), close (1), or infiltrated (2). Results: Statistically significant differences were observed in tumor-free margins between the control (73.17%) and experimental (97%) groups (p = 0.003). Subgroup analysis for SCC showed no significant difference (control: 84.21%; experimental: 95.83%; p = 0.306). Tumor location also differed significantly (p = 0.011), while other baseline variables, such as tumor type and patient characteristics, showed no significant differences. Conclusions: Autofluorescence-guided surgery improves the detection of tumor-free margins and may serve as an effective adjunct in oral cancer management. Larger studies are recommended to confirm these findings. Full article

Background/Objectives: For effective exercise prescription for patients with cardiovascular disease, it is important to determine the target heart rate at the level of the anaerobic threshold (AT-HR). The AT-HR is mainly determined by cardiopulmonary exercise testing (CPET). The aim of this study is to develop a machine learning (ML) model to predict the AT-HR solely from non-exercise clinical features. Methods: From consecutive 21,482 cases of CPET between 2 February 2008 and 1 December 2021, an appropriate subset was selected to train our ML model. Data consisted of 78 features, including age, sex, anthropometry, clinical diagnosis, cardiovascular risk factors, vital signs, blood tests, and echocardiography. We predicted the AT-HR using a ML method called gradient boosting, along with a rank of each feature in terms of its contribution to AT-HR prediction. The accuracy was evaluated by comparing the predicted AT-HR with the target HRs from guideline-recommended equations in terms of the mean absolute error (MAE). Results: A total of 8228 participants included healthy individuals and patients with cardiovascular disease and were 62 ± 15 years in mean age (69% male). The MAE of the AT-HR by the ML-based model was 7.7 ± 0.2 bpm, which was significantly smaller than those of the guideline-recommended equations; the results using Karvonen formulas with the coefficients 0.7 and 0.4 were 34.5 ± 0.3 bpm and 11.9 ± 0.2 bpm, respectively, and the results using simpler formulas, rest HR + 10 and +20 bpm, were 15.9 ± 0.3 and 9.7 ± 0.2 bpm, respectively. The feature ranking method revealed that the features that make a significant contribution to AT-HR prediction include the resting heart rate, age, N-terminal pro-brain natriuretic peptide (NT-proBNP), resting systolic blood pressure, highly sensitive C-reactive protein (hsCRP), cardiovascular disease diagnosis, and β-blockers, in that order. Prediction accuracy with the top 10 to 20 features was comparable to that with all features. Conclusions: An accurate prediction model of the AT-HR from non-exercise clinical features was proposed. We expect that it will facilitate performing cardiac rehabilitation. The feature selection technique newly unveiled some major determinants of AT-HR, such as NT-proBNP and hsCRP. Full article

The rice sector is facing the challenge of increasing rice yields while maintaining or improving input use efficiency. The purpose of this study was to determine the most effective vegetation indices for monitoring nitrogen uptake (N uptake) under different irrigation techniques. The study was conducted in Uruguay over two rice-growing seasons. A split plot experimental design featured two irrigation treatments (main plots): continuous flooding (C) and alternate wetting and drying (AWD). The nitrogen-rate (N-rate) treatments (split plots) included no nitrogen, the recommended N-rate based on soil analyses, and two additional doses (±50% of the recommendation). The plant N uptake relationships with selected drone-based vegetation indices (VIs) were assessed at panicle initiation. The presence or absence of standing water during image collection affected the VIs and their relationships with N uptake. The relationships estimated for traditional irrigation may not be applicable for AWD. The SCCCI was the top index with a significantly stronger relationship with N uptake under the C (R² = 0.84) and AWD (R² = 0.71) irrigation techniques in relation to all evaluated vegetation indices. The Clre, NDRE², NDRE, and CLg also had a significant relationship with N uptake under both irrigation treatments in both seasons, though their average R² values of 0.75, 0.74, 0.73, and 0.71, respectively, were lower than the SCCCI (average R² = 0.78). The findings would assist rice growers for selecting effective VIs for remote crop monitoring. Full article

To mitigate the issues of soil quality degradation and environmental pollution caused by excessive fertilizer use in apple orchards, the present study investigated the effects of organic fertilizer substitution combined with chemical nitrogen (N) fertilizer reduction on soil nutrient status, enzyme activity, and microbial communities (bacteria, fungi and archaea) over one year in an apple orchard. Five fertilization treatments were implemented, including 100% chemical fertilizer (CK), 80% chemical fertilizer + 20% liquid humic fertilizer (S1), 60% chemical fertilizer + 40% liquid humic fertilizer (S2), 60% chemical fertilizer + 20% liquid humic fertilizer (S3), and 40% chemical fertilizer + 40% liquid humic fertilizer (S4). Substituting chemical fertilizers with liquid humic fertilizers effectively enhanced the soil organic matter (SOM) content in the topsoil (0–20 cm) for all treatments. Compared to CK, the amounts of available N (NO₃⁻-N and NH₄⁺-N) were decreased in the topsoil and the amounts of total N, total phosphorous and available phosphorous were increased in the subsoil (20–40 cm) for all treatments. The β-diversity of bacterial communities exhibited the highest sensitivity to soil environmental changes, followed by that of archaea, whereas fungi demonstrated the least susceptibility. The higher soil carbon/nitrogen ratio and SOM content in S2 altered the abundance of microorganisms (Proteobacteria, Ascomycota, and Crenarchaeota) that were closely related to the decomposition and mineralization of SOM and N, enhancing the efficiency of SOM decomposition. The activities of sucrase (SUC), urease (UE), and phosphatase were increased, also promoting the conversion efficiency of SOM and improving N fixation and soil fertility. In the organic fertilizer substitution treatments (S1 and S2), the abundance of dominant Actinobacteriota, Ascomycota and Crenarchaeota phyla were increased, as well as the activities of SUC and UE, accelerating the decomposition and mineralization of SOM and improving soil fertility. In the top, organic fertilizer substitution combined with reduced chemical N fertilizer (S3 and S4) treatments increased the abundance of bacteria and fungi. In addition, RDA showed that total potassium content could significantly affect changes in the bacterial and fungal community structure in subsoil. Overall, organic fertilizer substitution enhanced the content of soil available nutrients and improved soil nutrient retention. It is recommended to promote organic fertilizer substitution + chemical N fertilizer reduction (S4) with the supplementation of potassium fertilizer in the subsoil. The findings provide a theoretical basis and practical guidance for improving orchard soil management and achieving sustainable development in the apple industry. Full article

The degree of conversion (DC) is crucial in determining the mechanical and clinical performance of resin-based composites (RBCs). This in vitro study aimed to evaluate the effect of the resin type and placement technique on the DC of RBCs (micro-hybrid, packable, hybrid, ormocer-based and flowable) polymerized with a second-generation LED light-curing unit (LCU). A total of 75 RBC samples were divided into three groups. Each RBC was placed into 4 mm diameter and 2 and 8 mm heigh Teflon molds with conventional standard, bulk, and incremental techniques (n = 5) and polymerized by LED LCU (229.153 mW/cm²) using the standard mode. After 24 h, DC was determined by FTIR spectrophotometry. The data were analyzed with two-way ANOVA and Tukey’s HSD test (p < 0.05). The DC of the RBCs varied between 62.8 and 29.2%. While the same DC was obtained for 2 mm samples at the top and the bottom surfaces, the DC of the 8 mm samples gradually diminished from the top surface to the bottom surface. Significant differences were observed in the DC of the RBCs. An optimal DC was obtained for packable, micro-hybrid and ormocer-based RBCs polymerized by LED LCU with the recommended curing times. Considering that the polymerization process is versatile, further in vitro studies are needed. Full article

Relative humidity (RH) is measured in vivaria with a broad range to accommodate seasonal fluctuations. It is assumed that measurements in the room (macroenvironment) reflect those in the cage (microenvironment). However, there is limited data comparing RH in the macroenvironment to the microenvironment and how the mice may be affected by variations in RH that fall within husbandry recommendations. This study aimed to compare RH in the macroenvironment to that of the microenvironment in various group sizes of laboratory mice; and examine how variation in microenvironmental RH impacts pup survival. Temperature and RH were measured using a temperature/humidity data logger attached to a solid top cage lid. The lid was rotated across N = 48 breeding trios and N = 33 same sex cages on a C57BL/6J background. Further, once a week, a single breeding trio was selected (N = 23) to compare RH readings to weekly rates of pup loss in a larger breeding colony. Across all cages, RH was higher in the microenvironment than the macroenvironment. RH was universally higher in the summer than in the winter, and increased with group size. For breeding cages, as microenvironmental RH increased, the proportion of pups lost each week decreased in a linear relationship. No threshold of decreased mortality could be identified. These data highlight RH as a potential extrinsic factor. While these patterns are correlational, they warrant further research focused on the causative role of RH on mouse welfare. Full article

The optimized sowing method and appropriate seed rate can improve wheat N use efficiency. However, the interactive effect of the sowing method and seed rate on N use efficiency, particularly N uptake and root length density, are unclear. A field experiment was conducted for two growing seasons in southern Shanxi province, China, using a split-plot design with the sowing method as the main plot (wide-belt sowing, WBS, and conventional narrow-drill sowing, NDS) and seed rate as the sub-plot (100–700 m⁻²). Our results showed that WBS had a significant and positive effect on N use efficiency (yield per unit of available N from the fertilizer and soil, by 4.7–15.4%), and the relatively higher seed rates (>300 or 400 m⁻²) enlarged the effects. The N use efficiency increases under WBS were mainly attributed to the increases in N uptake before anthesis, resulting from the promoted nodal roots per plant and per unit area, and root length density in the top layer(s). WBS promoted N translocation and the N harvest index, resulting in equivalent grain protein concentration and processing quality compared to NDS. Thus, adopting higher seed rates (>300 m⁻²) combined with WBS is recommended for achieving greater N efficiencies while maintaining the grain protein concentration and processing quality of winter wheat. Full article

Port state control (PSC) inspections, considered a crucial means of maritime safety supervision, are viewed by the industry as a critical line of defense ensuring the stability of the international supply chain. Due to the high level of globalization and strong regional characteristics of PSC inspections, improving the accuracy of these inspections and efficiently utilizing inspection resources have become urgent issues. The construction of a PSC inspection ontology model from top to bottom, coupled with the integration of multisource data from bottom to top, is proposed in this paper. The RoBERTa-wwm-ext model is adopted as the entity recognition model, while the XGBoost₄ model serves as the knowledge fusion model to establish the PSC inspection knowledge graph. Building upon an evolutionary game model of the PSC inspection knowledge graph, this study introduces an evolutionary game method to analyze the internal evolutionary dynamics of ship populations from a microscopic perspective. Through numerical simulations and standardization diffusion evolution simulations for ship support, the evolutionary impact of each parameter on the subgraph is examined. Subsequently, based on the results of the evolutionary game analysis, recommendations for PSC inspection auxiliary decision-making and related strategic suggestions are presented. The experimental results show that the RoBERTa-wwm-ext model and the XGBoost₄ model used in the PSC inspection knowledge graph achieve superior performance in both entity recognition and knowledge fusion tasks, with the model accuracies surpassing those of other compared models. In the knowledge graph-based PSC inspection evolutionary game, the reward and punishment conditions ($n,f$) can reduce the burden of the standardization cost for safeguarding the ship. A ship is more sensitive to changes in the detention rate $\beta$ than to changes in the inspection rate $\alpha$. To a certain extent, the detention cost $C_{DC}$ plays a role similar to that of the detention rate $\beta$. In small-scale networks, relevant parameters in the ship’s standardization game have a more pronounced effect, with detention cost $C_{DC}$ having a greater impact than standardization cost $C_S$ on ship strategy choice and scale-free network evolution. Based on the experimental results, PSC inspection strategies are suggested. These strategies provide port state authorities with auxiliary decision-making tools for PSC inspections, promote the informatization of maritime regulation, and offer new insights for the study of maritime traffic safety management and PSC inspections. Full article