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The QDIS-7: using one scale to measure the disease-specific quality-of-life impact of different medical conditions
MicroRNA-129-5p-mediated translational repression of microglial ROCK1 leads to enhanced phagocytosis
Examining doctors’ business analytics capabilities in using the electronic medical record system for decision-making effectiveness in intensive care units: Impact of the COVID-19 pandemic
Background Advancements in electronic medical record (EMR) systems raise the demand for doctors’ digital and analytical skills to process large-scale healthcare data for evidence-based decisions. The present challenge arises with the need to understand how doctors can develop business analytics capabilities using the EMR system for decision-making from an end user’s perspective. Aim Integrating the technology acceptance model and the business analytics model for healthcare, this study examines how individual doctors’ technology perceptions of using an EMR system influence their ability to develop business analytics capabilities for making effective healthcare decisions in intensive care units (ICUs). The research questions are: How do doctors’ perceptions of using an EMR system influence their ability to develop business analytics capabilities? and How do doctors’ business analytics capabilities affect the effectiveness of their healthcare decisions? This study focuses on the context of using the EMR system as a business analytics-enabled architecture rather than a general information system. Methods We surveyed a final sample of 130 ICU doctors from public tertiary hospitals in Malaysia, a developing country. This study uses PLS-SEM to analyze two phases, comparing doctors’ technology perception and business analytics capabilities before and during the pandemic. Results We found significant shifts in ICU doctors’ perceptions of using the EMR system (i.e., perceived ease of use and usefulness) influencing the development of their business analytics capabilities (i.e., data aggregation, data analysis, and data interpretation) for decision-making effectiveness. Data analysis was the only capability contributing to decision-making effectiveness during the pandemic. Significant differences in the relationships were observed before and during the COVID-19 pandemic. Conclusion We demonstrate that COVID-19 has accelerated favorable technology perceptions and the increasing dependency on developing business analytics capabilities to inform healthcare decisions. Our findings contribute to the critical importance, challenges, and opportunities of using the EMR system for more data-driven decision-making, especially in the post-COVID era.
On the nature of spin reorientation transition thermal hysteresis in NiO(111)/Fe(110) bilayers
Abstract We report on temperature-driven in-plane 90° magnetization switching in NiO(111)/Fe(110) bilayer epitaxially grown on a W(110) single crystal, investigated using magneto-optical Kerr effect and X-ray magnetic circular and linear dichroism measurements. As the temperature varies, an abrupt switching of the easy axis between the in-plane Fe[001] and Fe $$\left[ {1\overline{{{\text{1}}}} 0} \right]$$ crystallographic directions is observed. In the temperature range of approximately 210–285 K, a thermal hysteresis region appears, where two energy minima coexist at a given temperature. Our experimental findings are supported by phenomenological modeling. Simulations incorporating temperature-dependent anisotropy constants successfully reproduce the key features of the observed phenomenon, most notably the temperature-driven hysteresis of ferromagnetic magnetization switching. The spin reorientation transition in both exchange-coupled ferromagnetic and antiferromagnetic layers is driven by the interplay between magnetocrystalline and interfacial magnetic anisotropies in the ferromagnet, which stabilizes specific magnetization orientation at given temperature.
Linking basic principles of solution chemistry to kidney stone formation timelines
Abstract Kidney stone formation remains enigmatic, largely because of its multifactorial nature, and because assessment is by necessity based mostly on a posteriori analysis and/or on specific analyses (e.g., prescribed components found in urine) that focus on particular conditions. Here, we offer a different perspective to assess overall aspects of stone formation, delineating a method to calculate minimum times of stone formation as a function of stone type (calcium oxalate, calcium phosphate, and uric acid) and size (up to 10 mm), in the form of the pure mass of the stone, without consideration of actual formation or aggregation causes or processes. The calculations thus represent characteristic measures that delineate limits on times required to form specific stone volumes as a function of chemical content and mass. The times to form each stone type and specific size vary considerably, ranging from days to years. A key factor is the amount of the “building block” material in urine that actually contributes to stone formation, i.e., the % yield from solution to solid phase. In some cases, unrealistically high yields (e.g., 5–10%) are required to form a stone with a specified size, type, and time; this indicates that other factors – at least some of which can be deduced from the analysis – play key roles in stone formation. This information thus provides estimates that constrain assessments of stone formation mechanisms and interpretation of clinical findings.
Role of ventilator and ultrasound parameters in predicting extubation success
Closed circuit artificial ıntelligence model named morgaf for childhood onset systemic lupus erythematosus diagnosis
Molecular identification and diversity of gastrointestinal apicomplexan protozoa in pigs in the Republic of Korea
Reservoir characterization of Yolde Formation, Kolmani Field, Gongola Basin, Nigeria using pressure, temperature, PVT, and well log data
Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex
Evaluating locally available organic amendments to enhance soil health indicators for highbush blueberry production east of the Cascades in the U.S. Pacific Northwest
Analysis of chondroitin degradation by components of a Bacteroides caccae polysaccharide utilization locus
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
Accurately and rapidly detecting objects and their locations in drone-captured images from maritime search and rescue scenarios provides valuable information for rescue operations. The YOLO series, known for its balance between lightweight architecture and high accuracy, has become a popular method among researchers in this field. Recent advancements in the newly released YOLO11 model have demonstrated significant progress in general object detection tasks across everyday scenarios. However, its application to the specific task of drone-based maritime search and rescue still leaves substantial room for improvement. To address this gap, we propose targeted optimizations to enhance YOLO11’s performance in this domain. These include integrating a Space-to-Depth module into the Backbone, incorporating a content-aware upsampling algorithm in the Neck, and adding an extra detection head to better exploit shallow image features. These modifications significantly improve the model’s ability to detect small, overlapping, and rarely occurring objects, which are common challenges in maritime search and rescue tasks. Experimental evaluations conducted on the large-scale SeaDronesSee dataset demonstrate that the proposed optimized YOLO11 outperforms YOLOv8, YOLO11, and MambaYOLO across all scales. Moreover, under lightweight configurations, the model achieves substantial performance gains over YoloOW, a method renowned for its accuracy but depends on heavyweight configurations. In the lightweight complexity range, the proposed model achieves a relative accuracy improvement of 20.85% to 43.70% compared to these state-of-the-art methods. The code supporting this research is available at https://github.com/bgno1/sds_yolo11.
Multiple mush generations provide insight into the longevity of open-conduit basaltic volcanoes
Biometric and physiological responses of Virola Surinamensis to cadmium and biochar in amazonian soil
Unravelling root system architecture plasticity in response to abiotic stresses in maize
Assessment of ecofriendly carbon capture using Bacillus subtilis induced calcium carbonate precipitation with focus on applications mechanisms and cost efficiency
Abstract This work focuses on exploiting the naturally occurring microbial calcium carbonate precipitation catalyzed by microbial consortia within lakes and oceans biogeochemistry for carbon dioxide removal from atmosphere. In this work, Bacillus subtilis OQ119616 was used for carbon dioxide sequestration in equi-molar concentrations into Bacillus-induced calcium carbonate precipitation (BICCP). As this process requires alkaline media, urea degradation by urease and nitrogen fixation were traced. BICCP has been formed from calcium salts in the following order: chloride > nitrate > acetate > citrate. However, conversion efficiency percentage (CE%) of calcium salts to CaCO3 exhibited a different attitude of citrate > acetate > chloride > nitrate. Calcium citrate is excluded from consideration. Acetate, however, is the most efficient salt; it significantly exhibited the highest CE%, with the least cost and highest economic feasibility. The wide range in quantities, efficiency and feasibility indicates the importance of the salt anion in BICCP. In addition, BICCP exhibited applicability in healing concrete cracks, improving field capacity of sand soil and the subsequently improved seed germination of Vicia faba. BICCP was also accompanied by adsorption of heavy metals as partial purging of waste/sewage water for hygiene/reuse. Bacillus subtilis exhibited the ability to perform MICP, utilizing various calcium salts in the following order: chloride > acetate > nitrate > citrate. However, acetate is the most efficient salt of calcium to be converted to calcium carbonate precipitate by B. subtilis, as it exhibited the highest conversion efficiency percentage (g/g %), with the least cost and highest economic feasibility. Carbon dioxide removal (CDR) occurs at simultaneous equity to CaCO3 precipitation at mole/mole ratios. Economic feasibility (US$/m3) showed that BICCP may be applicable in CDR for cleansing carbon dioxide inside closed systems and for environmental safety. The bacterially induced CaCO3 proved successful applicability in improving the field capacity of sand soil and growth of V. faba, healing concrete cracks and sorption of heavy metals for depolluting sewage/wastewater for hygiene reuse. BICCP could repair concrete cracks of 1–2 mm wide in 7 days by 210 * 106 cells/mL. Adsorption of heavy metals (Pd, Zn, Cd and Cu) for partial removal of contaminants in/from waste/sewage water for hygiene reuse.