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Reproductive outcomes in women with prior cesarean scar pregnancies over six years
How ‘animal methods bias’ is affecting research careers
Integrating multidimensional data analytics for precision diagnosis of chronic low back pain
Abstract Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chronic (cLBP). Whilst multi-factorial, the relative importance of contributors to cLBP remains unclear. We leveraged a comprehensive multi-dimensional data-set and machine learning-based variable importance selection to identify the most effective modalities for differentiating whether a person has cLBP. The dataset included questionnaire data, clinical and functional assessments, and spino-pelvic magnetic resonance imaging (MRI), encompassing a total of 144 parameters from 1,161 adults with (n = 512) and without cLBP (n = 649). Boruta and random forest were utilised for variable importance selection and cLBP classification respectively. A multimodal model including questionnaire, clinical, and MRI data was the most effective in differentiating people with and without cLBP. From this, the most robust variables (n = 9) were psychosocial factors, neck and hip mobility, as well as lower lumbar disc herniation and degeneration. This finding persisted in an unseen holdout dataset. Beyond demonstrating the importance of a multi-dimensional approach to cLBP, our findings will guide the development of targeted diagnostics and personalized treatment strategies for cLBP patients.
Trump team ‘survey’ sent to overseas researchers prompts foreign-interference fears
Research on the performance of MXMCCC materials for gas leakage sealing
Abstract To address the issues of poor strength and low efficiency in traditional clay-cement composite gas-sealing materials (CCC), a method was proposed to prepare a new type of sealing material by utilizing multi-walled carbon nanotubes (MWCNTs) along with xanthan gum (XG) and magnesium oxide (MgO) to modify CCC. Through controlled experiments of water extraction rate testing, the optimal water-to-solid ratio for the multi-component system material has been determined to be 0.6. Mechanical performance testing reveals that when 1.5% xanthan gum, 5% magnesium oxide, and 1.39% multi-walled carbon nanotubes are added, the compressive strength of the multi-walled carbon nanotube-xanthan gum-magnesium oxide-clay-cement composite (MXM-CCC) reaches 18.60 MPa, with a flexural strength of 3.89 MPa. Pore integration analysis reveals that MXM-CCC has a porosity of 17.29%, with pore sizes ranging from 2.00 nm to 50 nm accounting for 71.46% of the total. The proportion of larger pores has decreased, resulting in a more optimal distribution of pore sizes. The formation mechanism and sealing mechanism of MXM-CCC were explored using characterization techniques such as XRD, FTIR, SEM, and thermogravimetric analysis. The hydroxyl and carboxyl groups in konjac gum undergo chelation with Ca²⁺ in CCC, forming a chelate structure. This causes the hydration products of the clay and cement to adhere together, improving the pore structure and mechanical properties of MXM-CCC. The addition of multi-walled carbon nanotubes accelerates the hydration reaction, increasing the content of substances such as C-(A)-S-H gel, ettringite, and Mg(OH)2 in the MXM-CCC. These chemicals act as a framework, providing support within the pores and inhibiting the shrinkage of MXM-CCC, and improving the adhesion between various hydration products. Additionally, multi-walled carbon nanotubes perform a nano-filling role, filling the pores and improving the density of the multi-component material, thereby enhancing its mechanical properties.
Efficient template free polymerization of continuously porous hybrid conducting polymers for highly stable flexible micro pseudocapacitors
Author Correction: CT based 3D radiomic and clinical airway examination model for evaluating mask ventilation in oral and maxillofacial surgery patients
Characteristics of atmospheric dustfall fluxes and particle size in an open pit coal mining area and surrounding areas
Mitigation of salinity stress via improving growth, chlorophyll contents and antioxidants defense in sunflower with Bacillus pumilis and biochar
Music genre classification with parallel convolutional neural networks and capuchin search algorithm
Wiener index application in intuitionistic fuzzy rough graphs for transport network flow
Abstract The applicability of different topological indices is indispensable in fields such as chemistry, electronics, economics, business studies, medicine, and the social sciences. The most popular index in graph theory is the wiener index $$\left(\mathcal{W}\mathcal{I}\right)$$ , which is based on the geodesic distance between two vertices. It is assumed that the weight of the geodesic between vertex x and vertex y in intuitionistic fuzzy rough graphs (IFRG) is zero in the absence of a directed path. With regard to intuitionistic fuzzy rough graphs, the objective of this work is to investigate in detail the wiener index $$\left(\mathcal{W}\mathcal{I}\right)$$ and the average wiener index ( $$\mathcal{A}\mathcal{W}\mathcal{I})$$ . Also, the connectivity index $$\left(\mathcal{C}\mathcal{I}\right)$$ is one of the most significant indices, providing several examples and results. For intuitionistic fuzzy rough graphs, alternative distance and degree-based topological indices have also been developed. The research on intuitionistic fuzzy rough graphs that has been suggested is appropriate for representing imprecise data and uncertainty in practical situations. Additionally, examined is the connection between the wiener and connectivity indices. Finally, we proposed the use of wiener indices in transport network flow.
Author Correction: Potato starch quality in relation to the treatments and long-term storage of tubers
Neural architecture search using attention enhanced precise path evaluation and efficient forward evolution
Prediction and classification technology of rockburst hazard in deep buried and high in-situ stress tunnel
Predicting habitat suitability of Illicium griffithii under climate change scenarios using an ensemble modeling approach
Optimizing generative AI by backpropagating language model feedback
Lab-in-a-Fiber detection and capture of cells
Abstract A lab-in-a-fiber component was fabricated using an optical fiber and a fiber capillary. It was used in a test suspension of fluorescently labeled and unlabeled cells and enabled detection of the labeled cells. Subsequently the labeled cells were selectively collected via suction into the capillary. A novel sampling technique reduced photobleaching of the labeled cells, extending the measurement time. The collected cells remained viable for downstream analysis. This platform’s low fabrication cost, simplicity, compatibility with standard laboratory equipment, and capacity for fully automated cell capture highlights its potential for future applications in minimally invasive sample collection and point-of-care diagnostics. We demonstrate this LiF device to showcase the capability of optical fiber technology in creating low-cost, low-complexity cancer diagnostic devices. Furthermore, the LiF device holds promise for in vivo diagnostics, facilitating cell isolation and analysis.
Plant landscape characteristics of mountain traditional villages under cultural ecology: a case study of Pilin village
Abstract With the rapid increase in urbanization, the landscape appearance of traditional village plants under the intensification of human activities is transforming. The lack of knowledge about the characteristics and values of traditional village plant landscapes has led to the “urban parkification” of rural plant landscapes, which makes the style and cultural characteristics of the village gradually fade, there is a need to sort out the characteristics of traditional village plant landscapes to conserve them. From the perspective of cultural ecology, this paper analyzed the characteristics of the plant landscape and its influencing factors in the “production-living-ecological” spaces of traditional mountain villages, selecting Pilin Village in Gaopo Miao Township, Guiyang as a case study. The results showed that Pilin Village has a stepped landscape pattern of “forest-field-village-field-river”, the spatial distribution of the plant landscape was summarized as “natural forest land-surrounding village forest-terraces-garden-farmland”, and the planting structure reflected a different layout in the vertical direction. The plant landscape in the “production-living-ecological” spaces was rich, with obvious differences in the spaces’ characteristics, but they also intersected, showing a “mutual adaptation” relationship with the environment and social humanities. The formation and development of the plant landscape characteristics and style of Pilin Village are the concentrated reflections of multiple factors in the cultural ecosystem, which is a dynamic process of continuous integration and adaptation with the environment from a macroscopic pattern to microscopic construction, reflecting the wisdom of Chinese ethnic minorities’ living environment construction. Based on the analysis of the plant landscape characteristics of Pilin Village and its influencing factors, the need for plant landscape conservation and construction in traditional mountain villages under the background of rural revitalization was determined, and the study provides some reference for contemporary village plant landscape planning, biodiversity conservation, and rural habitat construction.