Browse Articles

A person-centered approach to cognitive performance analysis in primary school children: Comparisons through self-organizing maps

The objective of this study was to identify distinct student profiles based on physical, psychological, and social characteristics, and examine their impact on cognitive performance. A total of 194 children participated in this cross-sectional design study (mean age = 10.61 years, SD = 0.45; 48.96% girls). The study included participants from diverse racial backgrounds. Using Self-Organizing Maps, an unsupervised neural network clustering technique, six distinct profiles were identified. These profiles revealed significant effects in daily physical activity, self-reported physical, social, and psychological factors, and physical performance. Profiles characterized by higher physical activity levels and positive social and psychological factors were associated with better cognitive performance, in contrast to profiles with lower levels in these domains. These findings suggest that students’ cognitive outcomes may be linked to their physical, psychological, and social characteristics, which interact to shape cognitive functioning. The recognition of the diversity of student profiles in specific educational settings may facilitate the design of more targeted programs that address individual needs and strengths, thereby enhancing their development in these domains within similar educational contexts.

Ratiometric fluorescence nanoprobe based on nitrogen-doped carbon dots for Cu2+ and Fe3+ detection

RELMβ sets the threshold for microbiome-dependent oral tolerance

Optimal two-stage group sequential designs based on Mann-Whitney-Wilcoxon test

The Mann-Whitney-Wilcoxon test, often referred to as the Mann-Whitney U test or Wilcoxon rank-sum test, is a non-parametric statistical test used to compare two independent groups when the dependent variable is ordinal or continuous but not normally distributed. It’s particularly useful for small sample sizes or when the assumptions of parametric tests, such as the t-test, are violated, including cases where the data is skewed. This study focuses on the Mann-Whitney-Wilcoxon test for ordinal data, which frequently arises in biomedical research when the proportional odds assumption does not hold. Currently, there are no optimal two-stage randomized clinical trial designs utilizing the Mann-Whitney-Wilcoxon test. To address this research gap, our study proposes optimal two-stage designs based on the Mann-Whitney-Wilcoxon test. We demonstrate the application of these designs through illustrative examples and evaluate their operating characteristics.

High fidelity zero shot speaker adaptation in text to speech synthesis with denoising diffusion GAN

Peroxisomal core structures segregate diverse metabolic pathways

Abstract Peroxisomes are single membrane-bounded oxidative organelles with various metabolic functions including β-oxidation of fatty acids. Peroxisomes of many species confine certain metabolic enzymes into sub-compartments sometimes visible as electron dense cores. Why these structures form is largely unknown. Here, we report that in the smut fungus Ustilago maydis detergent resistant core structures are enriched for different enzymes excluding several key enzymes of the β-oxidation pathway. This confinement contributes to generation of peroxisome subpopulations that differ in their enzyme content. We identify short amino acid motifs necessary and sufficient for protein self-assembly into aggregates in vitro. The motifs trigger enrichment in cores in vivo and are active in mammalian cells. Perturbation of core assembly via variation of such motifs affects peroxisome function in U. maydis strains challenged with fatty acids. Thus, protein core structures serve to compartmentalize the lumen of peroxisomes thereby preventing interference of biochemical reactions. Metabolic compartmentalization of peroxisomes via assembly of specific proteins may occur in other organisms as well.

Retraction: Inhibition of tumor vasculogenic mimicry and prolongation of host survival in highly aggressive gallbladder cancers by Norcantharidin via blocking the ephrin type a receptor 2/focal adhesion kinase/paxillin signaling pathway

Cause-specific mortality after spousal bereavement in a Danish register-based cohort

Abstract Spousal bereavement is associated with increased all-cause mortality, but less is known for cause-specific mortality. We estimated the average effect of bereavement on cause-specific mortality. Furthermore, we developed and evaluated the performance of prediction models estimating individualized mortality risks. This matched cohort study leveraged nationwide registry data on 223,500 married Danish individuals aged ≥ 65 years. Individuals were followed from bereavement date until death, emigration, or 3-year end of follow-up. G-estimation was used to estimate the average effect of bereavement on cause-specific mortality. Risk prediction models were developed and internally validated using logistic regression and Extreme Gradient Boosting utilizing information on sociodemographic factors and healthcare expenditures prior to bereavement. Among males, bereavement was associated with increased 3-year mortality from cardiovascular disease (CVD) (Risk Difference: 8 deaths/1000 individuals [95% confidence intervals (CI) 3;13]), digestive diseases (3 [95% CI 1;5]), psychiatric diseases/suicide (3 [95% CI 1;5]), and respiratory diseases (4 [95% CI 1;8]) and decreased 3-year mortality for dying from dementia/Parkinson’s disease (-4 [95% CI -6;-2]). Among females, bereavement was only associated with increased 3-year mortality from CVD (5 [95% CI 3;7 ]) and from psychiatric diseases/suicide (1 [95% CI 1;2]). The prediction models developed using sociodemographic information and healthcare expenditures showed limited accuracy in identifying cause-specific mortality risk. On average, spousal bereavement slightly elevated the risk for most causes of death for males and less so for females. Despite incorporating comprehensive healthcare and sociodemographic data, accurately predicting individual cause-specific mortality remains challenging.

Heat flows solubilize apatite to boost phosphate availability for prebiotic chemistry

Abstract Phosphorus is an essential building block of life, likely since its beginning. Despite this importance for prebiotic chemistry, phosphorus was scarce in Earth’s rock record and mainly bound in poorly soluble minerals, with the calcium-phosphate mineral apatite as key example. While specific chemical boundary conditions have been considered to address this so-called phosphate problem, a fundamental process that solubilizes and enriches phosphate from geological sources remains elusive. Here, we show that ubiquitous heat flows through rock cracks can liberate phosphate from apatite by the selective removal of calcium. Phosphate’s strong thermophoresis not only achieves its 100-fold up-concentration in aqueous solution, but boosts its solubility by two orders of magnitude. We show that the heat-flow-solubilized phosphate can feed the synthesis of trimetaphosphate, increasing the conversion 260-fold compared to thermal equilibrium. Heat flows thus enhance solubility to unlock apatites as phosphate source for prebiotic chemistry, providing a key to early life’s phosphate problem.

Effect of infill ratios in SLA 3D printing on mechanical properties of castable wax patterns for molded shells in investment casting

Investment casting has become an integral part of the modern industry’s manufacturing process with high precision. However, this technology still faces several challenges that need to be addressed for process improvement, especially the complex and flexible part. This research demonstrates the possibility of applying additive manufacturing techniques (3-dimensional printing (3DP)) and castable wax in investment casting. The main objective is to investigate the effect of infill ratios on the mechanical properties of 3D printed patterns and evaluate the ability to create mold shells using the printed patterns for casting stainless steel SUS 304. The results indicate that the infill density considerably influences the printed samples’ mechanical properties, mold-creating ability, weight, and building time. The mechanical properties of the printed samples, including Young’s modulus, tensile strength, and work of extension increase from 13.08 MPa, 393.33 MPa, and 4.25 MJ/m3 to 21.72 MPa, 671.48 MPa, and 9.62 MJ/m3, respectively. Moreover, the infill ratios of printed patterns, less than 25%, can be employed to fabricate the IC mold with exceptional quality. The printed patterns’ average surface roughness (SR) is 2.49 μm, while the average SR of the casted parts is 7.33 μm. The results strongly strengthen the idea of applying the 3DP technique and castable wax substance in investment casting (IC).

Lightweight DCGAN and MobileNet based model for detecting X-ray welding defects under unbalanced samples

Histamine-modulated wettability switching in G-protein-coupled receptor inspired nanochannel for potential drug screening and biosensing

Using the TSA-LSTM two-stage model to predict cancer incidence and mortality

Cancer, the second-leading cause of mortality, kills 16% of people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack of exercise have been linked to cancer incidence and mortality. However, it is hard. Cancer and lifestyle correlation analysis and cancer incidence and mortality prediction in the next several years are used to guide people’s healthy lives and target medical financial resources. Two key research areas of this paper are Data preprocessing and sample expansion design Using experimental analysis and comparison, this study chooses the best cubic spline interpolation technology on the original data from 32 entry points to 420 entry points and converts annual data into monthly data to solve the problem of insufficient correlation analysis and prediction. Factor analysis is possible because data sources indicate changing factors. TSA-LSTM Two-stage attention design a popular tool with advanced visualization functions, Tableau, simplifies this paper’s study. Tableau’s testing findings indicate it cannot analyze and predict this paper’s time series data. LSTM is utilized by the TSA-LSTM optimization model. By commencing with input feature attention, this model attention technique guarantees that the model encoder converges to a subset of input sequence features during the prediction of output sequence features. As a result, the model’s natural learning trend and prediction quality are enhanced. The second step, time performance attention, maintains We can choose network features and improve forecasts based on real-time performance. Validating the data source with factor correlation analysis and trend prediction using the TSA-LSTM model Most cancers have overlapping risk factors, and excessive drinking, lack of exercise, and obesity can cause breast, colorectal, and colon cancer. A poor lifestyle directly promotes lung, laryngeal, and oral cancers, according to visual tests. Cancer incidence is expected to climb 18–21% between 2020 and 2025, according to 2021. Long-term projection accuracy is 98.96 percent, and smoking and obesity may be the main cancer causes.

The impact of health and technology shifts on antibiotic use among the elderly in Thailand

S1PR1-biased activation drives the resolution of endothelial dysfunction-associated inflammatory diseases by maintaining endothelial integrity

Marbled murrelet habitat suitability in redwood timberlands of Northern Coastal California utilizing LiDAR-derived individual tree metrics

The marbled murrelet ( Brachyramphus marmoratus ) is a threatened seabird found from Southern California to Alaska that forages at sea but nests in near coastal forests. Marbled murrelet nesting habitat is generally comprised of old-growth or mature forests with large trees having platforms suitable for nesting. Here, we estimate a habitat suitability model (HSM) that relates evidence of nesting to characteristics of putative trees derived from high resolution light imaging detection and ranging (LiDAR) data. Our study area in Northern California contained stands of old-growth forests on state, federal, and private lands but was predominated by private second-growth redwood and Douglas-fir timberlands. We estimated a two-sample HSM using Maxent software and implemented objective and repeatable covariate selection, model evaluation, and classification methods. Our HSM predicts relative likelihood of occupancy using predicted Habitat Suitability Index (HSI) values that we then classify into five habitat classes based on a novel use of the predicted to expected (P/E) ratio curve. From HSI predictions, we identified patches of murrelet habitat and estimated concave polygons surrounding individual trees within and proximately close to each patch. These methods provide repeatable boundaries for identification of patches and important individual trees based on HSI. Patches with greater relative probability of occupancy were characterized by high densities of 60-meter and taller trees, a large sum of heights for 50-meter and taller trees, and high values of standard deviation of 50-meter and taller trees. During hold-out model evaluations, our HSM showed extremely high fidelity for known patches with indirect evidence of nesting based on occupancy.

Blockchain driven medical image encryption employing chaotic tent map in cloud computing

Negative global-scale association between genetic diversity and speciation rates in mammals

Proton or photon? Comparison of survival and toxicity of two radiotherapy modalities among pediatric brain cancer patients: A systematic review and meta-analysis

Background With the introduction of new therapy modalities and the resulting increase in survival rates, childhood brain cancers have become a focal point of research in pediatric oncology. In current protocols, besides surgical resection and chemotherapy, radiotherapy is required to ensure optimal survival. Our aim was to determine which of the two major irradiation options, proton (PT) or photon (XRT), was the least harmful yet effective for children with brain tumors. Methods The protocol was registered on PROSPERO in advance (CRD42022374443). A systematic search was performed in four databases (MEDLINE via (PubMed), Embase, Cochrane Library, and Scopus) on 23 April 2024. Odd ratios (OR) and mean differences (MD) with 95% confidence intervals (CI) were calculated using a random-effects model. Survival and six major types of side effects were assessed based on data in the articles and reported using the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Heterogeneity was assessed using Higgins and Thompson’s I2 statistics. Results Altogether, 5848 articles were screened, of which 33 were eligible for data extraction. The 5-year overall survival results showed statistically no significant difference between the two radiotherapy modalities (OR = 0.80, 95% CI: 0.51–1.23, p = 0.22, I2 = 0%). In terms of toxicity rates, an advantage was found for PT, particularly in terms of chronic endocrine side effects (hypothyroidism OR: 0.22, 95% CI: 0.10–0428, p = 0.002, I2 = 68%), neurocognitive decline (global IQ level MD: 13.06, 95% CI: 4.97–21.15, p = 0.009, I2 = 68%). As for hematological, acute side effects, neurological changes and ophthalmologic disorders PT can be beneficial for survivors in terms of reducing them. Conclusions In comparison with XRT, PT can reduce most side effects, without significantly decreasing the survival rate. There is considerable clinical relevance in the findings, even not all of them are statistically significant, which may facilitate the development of protocols regarding the usage of radiotherapy methods, and may encourage the establishment of more proton centers, where more studies can be done.

Development of a battery free, solar powered, and energy aware fixed wing unmanned aerial vehicle

Abstract Unmanned Aerial Vehicles (UAVs) hold immense potential across various fields, including precision agriculture, rescue missions, delivery services, weather monitoring, and many more. Despite this promise, the limited flight duration of the current UAVs stands as a significant obstacle to their broadscale deployment. Attempting to extend flight time by solar panel charging during midflight is not viable due to battery limitations and the eventual need for replacement. This paper details our investigation of a battery-free fixed-wing UAV, built from cost-effective off-the-shelf components, that takes off, remains airborne, and lands safely using only solar energy. In particular, we perform a comprehensive analysis and design space exploration in the contemporary solar harvesting context and provide a detailed accounting of the prototype’s mechanical and electrical capabilities. We also derive the Greedy Energy-Aware Control (GEAC) and Predictive Energy-Aware Control (PEAC) solar control algorithm that overcomes power system brownouts and total-loss-of-thrust events, enabling the prototype to perform maneuvers without a battery. Next, we evaluate the developed prototype in a bench-top setting using artificial light to demonstrate the feasibility of batteryless flight, followed by testing in an outdoor setting using natural light. Finally, we analyze the potential for scaling up the evaluation of batteryless UAVs across multiple locations and report our findings.