Tag: statistics

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-39514-3. Online ahead of print.

ABSTRACT

Ore particle size distribution is an important metric for evaluating blasting outcomes and affects the energy consumption of ore crushing equipment. Faced with dense accumulation of ore, nonuniform size distributions, dust occlusion, and target loss due to motion, using computer vision methods, we propose a blasting ore size detection method based on efficient dehazing network and multi-dimensional feature fusion, which is an improvement to YOLOv8. Firstly, we constructs an efficient defogging backbone network that combines feature attention and composite scalable backbone so that the model can efficiently extract the features of ore images and enhance the robustness of the model to dust interference in the ore crushing process. Secondly, we introduces a new feature fusion network that combines the convolution model and the Vmamba sequence model as well as cross-layer fusion of multi-scale features so that the model can effectively adapt to the dramatic scale change of blasting ore, capture fine ore and large-size ore, avoid ore omission, and improve the accuracy of particle size statistics. Finally, the multi-dimensional feature fusion ability of Dynamic Head was introduced to optimize the target detection head, and the feature fusion was further optimized so that the feature tensor obtained from the ore image was adapted to the detection and positioning task of ore, and the discrimination ability of the model for ore was improved. Experiments were conducted on a manually labeled jaw fracture ore dataset. Compared to the YOLOv8n algorithm, the average precision ([Formula: see text]) for detecting eight size categories of ore increased by 7%. On datasets containing interference such as smoke, dust, and wet conditions, the mean average precision at the IoU threshold of 0.5 (mAP50) improved by 7.6%. For fine ores below D5 (72 mm), the detection precision ([Formula: see text]) increased by 18.8%, while the recall rate ([Formula: see text]) rose by 13.8%. On the total one-class dataset, the recall rate ([Formula: see text]) and mAP50 reached 84% and 88.1%, respectively.

PMID:41764266 | DOI:10.1038/s41598-026-39514-3

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-025-32082-y. Online ahead of print.

ABSTRACT

Rapidly increasing municipal solid waste (MSW) generation, reaching 160,039 tonnes per day in India, and the environmental burdens of conventional disposal highlight the need for efficient waste-to-biofuel solutions. This study conducts a comparative Life Cycle Assessment (LCA) of seven MSW-to-biofuel pathways: open landfilling, landfill gas recovery, incineration, torrefaction, gasification, hydrothermal carbonization, and integrated gasification. Using a functional unit of 1 tonne of MSW, the assessment quantifies environmental impacts across five midpoint categories (GWP, SOD, FEP, LU, WC) following ISO 14040/44 guidelines. The methodology integrates experimental MSW characterization, national waste statistics, and ± 10% sensitivity analysis to address uncertainties in methane capture, energy recovery, and grid displacement. Results show substantial differences across pathways, with integrated gasification (MIG) emerging as the most sustainable option, achieving an avoided GWP of – 1095 kg CO₂ eq, water savings of – 1125.61 m³, and the lowest land-use requirement (- 32.39 m²·a). Material Flow Analysis further validates MIG’s superior mass-energy conversion when combined with recycling. The study’s novelty lies in its first holistic comparison of seven thermochemical and conventional MSW pathways tailored to India, integrating LCA and MFA evidence. the findings support prioritizing advanced thermochemical routes, particularly MIG, for climate-resilient, resource-efficient, and circular MSW management.

PMID:41764252 | DOI:10.1038/s41598-025-32082-y

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-40752-8. Online ahead of print.

ABSTRACT

The role of Nature ^**** in supporting human life, health, and well-being has been recognized and appreciated since ancient times, and has become a topic of scientific investigation with early studies dating back several decades. In recent years, this field has gained renewed attention and methodological refinement, driven by interdisciplinary frameworks and advances in environmental psychology, ecology, and health sciences, including new ecosystem-based approaches that highlight the deep human dependence on Nature for both mental and physical health. Among Nature-based Interventions that aim at exposing people to the natural environment, Green Prescriptions (GRx) represent a promising strategy to address human health challenges in ways that can also support environmental sustainability, in line with the Planetary Health framework. However, significant gaps remain in our understanding of the specific ecological factors that influence health outcomes during therapeutic activities in natural settings; in particular, it remains unclear how ecosystem structure and functions modulate health responses in individuals. This nine-month pilot study examined the therapeutic efficacy of GRx within a Mediterranean woodland ecosystem, to assess if and how variations in ecosystem structure influence health outcomes in individuals with complex chronic conditions. Using a novel aggregated index to characterize four distinct woodland patches, we identified a gradient in structural complexity where greater ecosystem functionality was consistently associated with greater alleviation of psychological and physical symptoms. Notably, health outcomes were independent of weather conditions and participants’ baseline connectedness to Nature, whereas temporal dynamics and the presence of peaks in the productivity of some species influenced both perceptions and physical responses. This underscores the intrinsic role of ecosystem properties and dynamic functions in modulating human health responses, while also suggesting the potential presence of a complex set of signals pervading complex ecosystems that is worth further exploration. The results demonstrated cumulative health benefits, including significant reductions in medication use over time, particularly among individuals with respiratory challenges and chronic pain. Furthermore, participants showed improved environmental awareness and behavior, embracing the interconnectedness principle, which is integral to effective environmental conservation. This study highlights the potential of well-functioning ecosystems to serve as co-effectors in healthcare interventions, advancing the goals of Planetary Health while reinforcing the importance of preserving ecological integrity. (**In this paper, “Nature” is written with a capital “N” to indicate the living biosphere and the abiotic matrices (soil, air, and water) in which life is embedded, including the ecological processes they sustain. This capitalization reflects the scientific perspective of Nature not merely as a passive backdrop, but as an active ecological system that interacts and influences human health. It also avoids confusion with “nature” as the intrinsic quality of a phenomenon**).

PMID:41764240 | DOI:10.1038/s41598-026-40752-8

Sci Data. 2026 Feb 28. doi: 10.1038/s41597-026-06926-9. Online ahead of print.

ABSTRACT

Observer bias and inconsistencies in traditional plant phenotyping methods limit the accuracy and reproducibility of fine-grained plant analysis. To address these limitations, TomatoMAP is introduced as a comprehensive dataset for Solanum lycopersicum. The dataset contains 68,080 RGB images: 3,616 high-resolution macrophotographs (3648 × 5472) with semantic annotations, and 64,464 moderate-resolution images (1080 × 1440) captured from 12 plant poses at four camera elevations. Each image is accompanied by manually annotated bounding boxes for seven regions of interest (leaves, panicle, flower clusters, fruit clusters, axillary shoot, shoot, and whole-plant area) and by labels spanning 50 BBCH classes representing phenologically growth stages. A general cascading structure is proposed. For real-time applicability, models emphasizing the accuracy-efficiency trade-off (MobileNetv3, YOLOv11, and Mask R-CNN) are prioritized and benchmarked against multiple state-of-the-art models. Performance is assessed using accuracy, mAP, inference FPS, and normalized confusion matrices. In a study involving five domain experts, AI models trained on TomatoMAP achieves comparable accuracy levels. Reliability of automated fine-grained phenotyping is supported by Cohen’s Kappa statistics and inter-rater agreement heatmaps.

PMID:41764239 | DOI:10.1038/s41597-026-06926-9

NPJ Prim Care Respir Med. 2026 Feb 28. doi: 10.1038/s41533-026-00496-4. Online ahead of print.

ABSTRACT

We aimed to assess an obstructive sleep apnoea (OSA) diagnostic approach performed solely in primary care centres (PCC) with the support of an autoscoring home sleep apnoea testing (aHSAT, ApneaLink^TM Air) device and compare the diagnoses with those undertaken by the manual analysis of home sleep apnoea testing (mHSAT), and polysomnography (PSG) if necessary, of a certified sleep specialist. This multicentre, cross-sectional study was undertaken between April 2016 and November 2020. We randomly selected patients aged 30-70 years with a high probability of OSA (≥ 3 points on the STOP-Bang questionnaire) who were visiting any of the four PCCs assigned for referral to the University Hospital Doctor Josep Trueta, Girona, Spain. 2599 patients were assessed for eligibility; 403 provided a high probability of OSA and 329 could be compared between PCC and hospital. 210 (63.8%) patients were male and the mean age was 56.5 (SD: 9.2) years. The global agreement between PCC and hospital diagnoses was 41.6% and severe OSA showed the highest level of agreement (96.2%). The Kappa index for severe OSA was 0.46 (95% CI: 0.37, 0.55) and the specificity was 0.99 (95% CI: 0.97, 1.00). The ApneaLink^TM Air device showed high specificity for severe OSA in a high-risk primary care population with a high pre-test probability of OSA. When aHSAT indicates severe OSA, hospital confirmation may be unnecessary, whereas negative or moderate findings may still require specialist assessment.

PMID:41764227 | DOI:10.1038/s41533-026-00496-4

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-40464-z. Online ahead of print.

ABSTRACT

To assess the host response to mono- and co-infection of tick-borne encephalitis (TBE) virus with Borrelia burgdorferi sensu lato and Anaplasma phagocytophilum bacteria, as well as the possibility of using the analysis of the level of endocannabinoids and eicosanoids in urine for effective diagnostics. Urine of patients with Lyme disease (LD) (in the form of erythema migrans (EM) or neuroborreliosis (NB)), TBE, diagnosed by ELISA-based detection of serum and CSF anti-TBEV IgM and IgG antibodies in all cases, human granulocytic anaplasmosis (HGA), co-infection of TBEV, LD, and healthy individuals (Control Group, CG) was analyzed. A GC/LC-MS/MS platform was used to identify changes in the phospholipid metabolite profile in urine. Lipid peroxidation product levels were estimated by measuring 4-hydroxy-2-nonenal (4-HNE by GC-MS/MS and F2-isoprostanes 8-isoPGF2α by LC-MS/MS). Endocannabinoids and eicosanoids levels were assessed using LC-MS/MS. Statistically significant differences in the concentration of 8-isoP (EM, NB, TBE vs. CG) were observed in patients’ urine before treatment. However, the analysis of endocannabinoids showed significant differences in oleylethanolamide (OEA) concentration (TBE vs CG). The study of pro-inflammatory eicosanoid levels showed a difference for: prostaglandin E2 (PGE2) (TBE vs CG), leukotriene D4 LTD4 (EM vs HGA), and 5-hydroxyeicosatetraenoic acid (5-HETE) (EM vs NB), assessed before treatment. The levels of anti-inflammatory eicosanoids showed a difference for prostaglandin D2 (PGD2) (EM vs CG) and 15-hydroxyeicosatetraenoic acid (15-HETE) (TBE vs CG). However, the results in the level of phospholipid metabolites from patients after therapy did not show statistically significant differences compared to the value before treatment and between groups. Tick-borne diseases are accompanied by changes in lipid metabolism, both ROS- and enzyme-dependent, which can be identified even in urine. Urinary lipid mediators show potential as supportive markers but require validation in larger patient cohorts.

PMID:41764219 | DOI:10.1038/s41598-026-40464-z

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-37724-3. Online ahead of print.

ABSTRACT

Brazil is the world’s leading coffee producer and increasingly adopts shaded agroforestry systems to enhance sustainability. However, the influence of topography on soil functionality within these systems remains insufficiently understood. This study evaluated soil physical and chemical properties across slope positions (Upper, Middle, and Lower Thirds) and depths (0-60 cm) in a shaded coffee agroforestry system using multivariate statistics and Bayesian network modeling. Results revealed that upper slope positions exhibited greater macroporosity (15-20%) and lower bulk density (1.10-1.15 g cm⁻³), whereas lower slope positions accumulated higher total organic carbon (2.5-3.0%) and microporosity (28-32%). Principal Component Analysis indicated that topography modulated soil porosity and carbon distribution, with total organic carbon (TOC) positively correlating with nutrient availability and negatively with acidity. Bayesian network analysis identified TOC as the most influential attribute, displaying the highest expected influence (1.25) and strength (1.15), along with elevated centrality in conserved environments. These results demonstrate that TOC functions as a central integrator linking soil structure, chemistry, and fertility across topographic gradients. Overall, shaded coffee agroforestry enhanced soil quality and functionality, particularly in upper slope areas, underscoring its potential for sustainable land management in tropical landscapes.

PMID:41764216 | DOI:10.1038/s41598-026-37724-3

Nat Commun. 2026 Feb 28. doi: 10.1038/s41467-026-69816-z. Online ahead of print.

ABSTRACT

Imaging genetics links genetic variations to brain structures and functions, but the computational challenges posed by high-dimensional imaging and genetic data are significant. In voxel-level genome-wide association studies, we introduce a Representation learning-based Voxel-level Genetic Analysis (RVGA) framework that reduces computational time and storage burden by over 200 times. RVGA enhances statistical power by denoising images and shares minimal datasets of summary statistics for associations across the whole genome of the entire image for secondary analyses. Additionally, it introduces a unified estimator for voxel heritability, genetic correlations between voxels, and cross-trait genetic correlations between voxels and non-imaging phenotypes. Applying RVGA to hippocampus shape and white matter microstructure in the UK Biobank (n = 53,454) reveals 39 and 275 novel loci, respectively. We identify heterogeneity in heritability within images and subregions that share genetic bases with 14 brain-related phenotypes, such as the genetic correlation between the hippocampus and educational attainment, and between the anterior corona radiata and schizophrenia. RVGA replicates known genetic associations and uncovers new discoveries.

PMID:41764180 | DOI:10.1038/s41467-026-69816-z

J Orthop Sports Phys Ther. 2026 Mar;56(3):158-175. doi: 10.2519/jospt.2026.13561.

ABSTRACT

OBJECTIVE: To compare the effects of supervised physical therapy to home exercise programs on functional outcomes in patients after distal radius fractures. DESIGN: Intervention systematic review with meta-analysis of randomized clinical trials (RCTs). LITERATURE SEARCH: We searched MEDLINE, EMBASE, Web of Science, Scopus, CENTRAL, Epistemonikos, Cumulative Index of Nursing and Allied Health Literature, SPORTDiscus, Physiotherapy Evidence Database, and LILACS databases from inception to April 2025. STUDY SELECTION CRITERIA: We included RCTs comparing supervised physical therapy with a home exercise program on functional outcomes in patients with distal radius fracture. DATA SYNTHESIS: We used a random-effects meta-analysis for clinically homogeneous RCTs. We assessed risk of bias using the Cochrane Risk of Bias 2.0 and applied the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to judge the certainty of evidence. RESULTS: Thirteen RCTs were included. At 6 weeks, there were significant differences for Patient-Rated Wrist Evaluation (mean difference [MD] = -11.64 points, P < .001) with moderate certainty of evidence, for grip strength relative to the unaffected side (MD = 12.85%, P = .03) with low certainty of evidence, and for wrist extension range of motion (MD = 8.99°, P = .03) with moderate certainty of evidence. All results were in favor of the supervised physical therapy group. There were significant differences in favor of supervised physical therapy for wrist function and extension range of motion in patients over 65 years (P < .05). A greater number and frequency of supervised physical therapy sessions were associated with greater pain relief and improved wrist range of motion (P < .05). CONCLUSION: Supervised physical therapy had statistically significant short-term benefits in wrist function, grip strength, and wrist extension range of motion. J Orthop Sports Phys Ther 2026;56(3):158-175. Epub 4 February 2026. doi:10.2519/jospt.2026.13561.

PMID:41764173 | DOI:10.2519/jospt.2026.13561

Transl Psychiatry. 2026 Feb 28. doi: 10.1038/s41398-026-03925-7. Online ahead of print.

ABSTRACT

Stimulants are the first-line pharmacological treatment for ADHD and generally effective, yet 35-61% of individuals discontinue treatment within a year. We investigated the contribution of common and rare genetic variants to early stimulant discontinuation using data from 18,362 individuals with ADHD (31% female) initiating stimulants in iPSYCH, a Danish population-based case-cohort linked to national registers. Discontinuation was defined as a ≥ 180-day gap between dispensations within one year of initiation. We examined genetic differences by age groups, estimated SNP-heritability (h²_SNP), conducted genome-wide association studies (GWAS), polygenic score (PGS) analyses, and assessed associations with protein truncating variants (PTV). Within one year, 7102 individuals (39%) had discontinued stimulants. Age-stratified analyses (cut-off: age 16) revealed low genetic correlation (r₉ = 0.23, 95% CI: -0.37, 0.83) between children and adolescents/adults. The h²_snp for discontinuation was 0.06 (95% CI: 0.02, 0.11) overall, 0.08 (95% CI: 0.02, 0.14) in children, and 0.14 (95% CI: 0.02, 0.27) in adolescents/adults. No genome-wide significant loci were identified overall or in adolescents/adults; however, one locus (SLC5A12, chromosome 11) reached genome-wide significance in children. Ten of 36 PGSs were associated with discontinuation, with higher psychiatric risk PGSs predicting increased discontinuation, while educational attainment and BMI PGSs showed divergent effects by age. Reduced burden of dopamine-related PTVs was nominally associated with discontinuation, particularly in adolescents/adults. These findings suggest modest contributions of both common and rare variants to stimulant discontinuation in ADHD and point to potential developmental differences in genetic architecture.

PMID:41764167 | DOI:10.1038/s41398-026-03925-7