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443 papers
Manual prescriptions and vaccination clinics were associated with higher vaccine prescription conversion, with particularly pronounced effects on non-NIP vaccines.
Calibration of microparameters in numerical simulations is a critical factor affecting model accuracy. To determine the relationship between macro‐ and microparameters in composite rock masses and the influence of soft rock layer proportions on mechanical properties, this study employed PFC2D software to construct numerical models of composite rock masses with varying soft‐to‐hard layer thickness ratios. A systematic analysis was conducted to investigate the influence of microparameters on macro‐mechanical properties. For composite rock bodies with varying soft rock layer thicknesses, as the soft rock proportion increases, the failure mode gradually shifts from shear failure dominated by hard rock to foliated failure dominated by soft rock. Cracks propagate along bedding planes and are constrained by hard rock layers. When the soft rock layer thickness increases from 10% to 90%, the total number of cracks increases by approximately twofold, while the proportion of shear cracks decreases from 75% to 40%. The crack counting rate exhibits exponential growth with stress and synchronizes with stress amplitude, peaking at 180–200 times/s − 1 . Laboratory test results align with numerical simulations, demonstrating that the PFC model accurately predicts composite rock mass strength (error ≤3.7%) and elastic modulus (error ≤4.6%). This study provides theoretical support for correlating macro‐ and micro‐mechanical properties in composite rock masses of varying hardness, offering significant reference value for stability assessment and reinforcement design in underground engineering.
In cancer patients at risk of cardiotoxicity, the precision of 2D echocardiographic AI analysis exceeds that of experts, matching that of 3D LVEF assessment.
This study aims to assess the level of income diversification among Yobe State small-scale farmers. Primary data was collected through a face-to-face survey-based approach through a multistage sampling technique, where 384 small-scale farmers were interviewed. The data were analyzed using statistical package for social science software (SPSS) version 26 for the descriptive analysis of the frequency distribution table, regression analysis and the Simpson Index of Diversification (SID) to test the study's aims and objectives. The results revealed that the respondents engaged in both On-farm and Non-farm livelihood diversification strategies. The overall SID of Non-farm diversification indicated that the respondents had a medium diversification index of 0.55, this primarily driven by participation in wage employment outside agriculture and self-employment. The on-farm diversification index was 0.30, indicating lower diversification than the Non-farm. This lower index is determined mainly by both food crops and cash crops. The study further revealed that small-scale farmers income diversification is influenced by the predictor factors of the farming operation system, average annual income in naira, age, farmland ownership, marital status, farm size, educational level, household size, and farming experience. The study concluded that the lower diversification index of On-farm could be due to the unpredictable risks associated with farming, making it less viable and turning farmers to off-farm activities as a means of coping strategies. And the Non-farm has a medium diversification index. This shows how important Non-farm is in stabilizing small-scale farmers' income and livelihood and signifies the potential risk facing the agricultural productivity in the study area.
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Both the groups resulted in acceptable, efficient and safe outcomes with no much difference in the brain activity levels, according to the findings of the present study.
The Bone Ring Technique (BRT) is a newer viable option for restoring complex defects around dental implants with three-dimensional bone augmentation with significant height and width augmentation of buccal bone.
ChemAutoAgent is presented, a multi-agent system that converts text-based instrument manuals into tested and reusable laboratory instrument drivers through a staged, evidence-traceable pipeline and demonstrates the feasibility of reusing published drivers in a multi-device workflow.
Telecommunications base-station towers support services that are indispensable to crisis communication, emergency response, public administration and economic continuity. Their dispersed location, height and lattice geometry make conventional close-access inspection hazardous, time-consuming and difficult to document consistently. This study evaluates the usefulness and limitations of uncrewed aircraft systems for inspecting steel lattice towers that form part of telecommunications critical infrastructure. A retrospective field study was conducted using records from inspections performed in 2022–2023 at 50 towers in three Polish provinces. More than 150 sorties were completed with a DJI Matrice 30T platform using optical zoom, thermal imaging, a laser rangefinder and georeferenced mission telemetry. Manual, column and spiral flight patterns were compared, while image sets were processed with photogrammetric software to support three-dimensional reconstruction and spatial localisation of defects. The observations show that uncrewed inspection is particularly effective for documenting coating damage, local corrosion, fastener deterioration, connection anomalies, snow or ice accretion and equipment requiring thermographic follow-up. Column flights generated the most detailed evidence but also the greatest processing burden; spiral flights were faster and better suited to screening and three-dimensional modelling. The study also identified important constraints: wind, battery endurance, vegetation, airspace restrictions, electromagnetic and navigation disturbances, and the need to protect sensitive infrastructure data. Uncrewed aircraft should therefore be treated as a risk-based screening and documentation tool integrated with engineering judgement and targeted close-contact or non-destructive testing, rather than as an unconditional replacement for statutory structural inspection.
A high initial investment in acquiring environmentally friendly products can discourage institutions from adopting them. This study explored the extent to which eco-friendly products contribute to supply chain resilience and operational performance at the Nigerian Maritime University. The study employed a quantitative survey method administering a sample of 303copies questionnaire to the staff of the organization using a stratified sampling technique. The hypotheses were tested and analyzed using a regression method with the aid of Minitab software. The regression analysis indicates eco-friendly products significantly relates to operational efficiency in Nigerian Maritime University, South-South Nigeria. The model regression indicates (R² = 99.20, B = 1.039, β = 0.0162, p = 0.000); indicating that the model is a good fit. The coefficient 1.0399 is highly significant (p < 0.001). This indicates a positive and strong effect, explaining that for every one-unit increase in eco-friendly products, the operational efficiency increases by approximately 1.039 units. The NOVA result confirms F = 4117.07, p < 0.001. The study concludes that the adoption of eco-friendly products plays a significant and positive role in enhancing organizational sustainability performance or resilience. Organizations should embed eco-friendly product selection into their procurement guidelines to promote sustainable operations. Management should invest in environmentally friendly technologies and capacity building initiatives to support the transition to sustainable practices.
USG provides improved detection of osteophytes and offers additional information on soft-tissue and early structural changes in knee OA and serves as a valuable, accessible adjunct to conventional radiography for comprehensive evaluation and early diagnosis of knee OA.
3D geological models provide digital representations of subsurface architecture and are increasingly applied in both academic research and industry. Their construction can follow implicit or explicit approaches, depending on data availability and final modelling applications. While 3D models based on subsurface data are traditionally employed in several fields of study, models derived from outcrop data are increasingly being developed. In this study, newly acquired geological mapping data from the Pasubio Massif (Southern Alps, northern Italy), covering an area of ~36 km² within the geographic extent of the CARG sheet 081 “Rovereto”, were used to develop and test an iterative explicit workflow for 3D geological modelling using Move software. The workflow is based on the construction of a structured grid of geological cross-sections, followed by the interpolation of stratigraphic horizons and fault surfaces through Ordinary Kriging. Field observations indicate that the lithostratigraphic units cropping out in the study area form a gently NW-dipping monoclinal structure, exhibit overall constant thicknesses and are affected by the Schio-Vicenza fault system. Model validation first involved a qualitative comparison between mapped geological boundaries and faults with those obtained from the intersection of the modelled surfaces with the topography (DEM), followed by thickness maps evaluation as an internal consistency check. Where inconsistencies emerged, cross-sections were refined and the model was iteratively updated until geological geometries and thickness trends became consistent with field-mapped evidence. A final quantitative assessment was then performed by analysing thickness deviations from mean unit thicknesses and by measuring the spatial overlap between mapped and model-interpolated geological boundaries and fault traces. Comparison between the preliminary and validated models, supported by thickness deviation statistics, indicates that most residual discrepancies are constrained within ±10–20% of expected thickness values. The results highlight the critical role of iterative validation in ensuring geologically robust 3D models, emphasising common sources of uncertainty in explicit geomodelling workflows. This study provides a methodological framework for producing reliable 3D geological models in data-poor regions, complementing the recently published ISPRA guidelines for the organisation and standardisation of model datasets and supporting future applications in academic research and regional or national geological surveys.
The findings can help clinicians better understand the planning of space opening for PMLIs before clear aligner therapy commences and provide baseline information for future research.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.
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