bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevention of Emotional Problems in Spanish Schoolchildren: Effectiveness of the Super Skills Multimedia Program to Promote Social-Emotional Skills
Authors: Orgilés Mireia , Espada Jose P. , Morales Alexandra 
Published: September 2024

AbstractCompared to traditional psychosocial interventions, the transdiagnostic approach focuses on common processes or factors that contribute to the development and maintenance of emotional problems. In Spain, the Super Skills Program has proven its effectiveness, but issues with displacement or scheduling for families can hinder access to the intervention. This study aims to examine the program’s effectiveness in preventing children’s psychosocial problems through learning socio-emotional skills when self-administered via the Internet. Participants were 283 Spanish children between the ages of 8 and 12. The children and their parents completed anxiety and depression scales before and after receiving the intervention and 12 months later. The program consisted of 8 self-applied sessions, at a rate of two per week, which included emotional education, cognitive restructuring, self-regulation techniques, training in social skills, problem-solving, and video feedback with cognitive preparation. Significant differences in anxiety and depression symptoms were found after the intervention. A significant reduction in anxiety scores and a marginally significant decrease in depression scores was observed at the long-term follow-up. The “intention to treat” analysis revealed a tendency for children who improved to drop out of the program, completing the intervention children with more symptomathology. Learning socio-emotional skills through a self-applied intervention via the Internet effectively reduced emotional symptoms in school children and is a valuable resource to improve child well-being and prevent future psychological problems.
Reproductive strategy, management, and medicinal uses of field horsetail (Equisetum arvense)
Authors: Pratt Morgan K. , Westbrook Anna S. , DiTommaso Antonio 
Published: September 2024

Abstract
Field horsetail (Equisetum arvense L.) is a perennial weed native to many areas of the northern hemisphere. Like other horsetail species, field horsetail is a spore-bearing plant from an ancient clade. Unlike some other horsetails, field horsetail is a problematic agricultural weed. It is especially difficult to control in low-tillage cropping systems. Neither chemical nor mechanical tactics are likely to achieve full control in a single operation. However, these tactics may be successfully combined in an integrated weed management program. This review summarizes available information about the biology, ecology, and management of field horsetail. We also note its potential value as a source of pharmaceutical compounds.
Microplastic and Associated Black Particles From Road‐Tire Wear: Implications for Radiative Effects Across the Cryosphere and in the Atmosphere
Authors: Reynolds Richard L. , Molden Nick , Kokaly Raymond F. , Lowers Heather , Breit George N. , Goldstein Harland L. , Williams Elizabeth K. , Lawrence Corey R. , Derry Jeff 
Published: September 2024

AbstractThe environmental effects of airborne micro‐ and nano‐size plastic particles are poorly understood. Microscopy and chemical analyses of atmospherically deposited particles on snow surfaces at high elevation (2,865–3,690 m) in the Upper Colorado River basin (UCRB; Colorado Rocky Mountains) revealed the presence of black substances intimately associated with microplastic fibers, particles interpreted to have originated as tire matter. Identical and similar particles occur in shredded tires and road‐surface samples. The substance responsible for the black color of all tires is carbon black, a graphitic light‐absorbing tire additive produced by hydrocarbon combustion that homogeneously permeates the mixture of tire polymers and other additives. Such black tire matter may thus exert radiative effects closely similar to those of black carbon. The presence in snow of many organic compound types common to tires, measured by two‐dimensional gas chromatography, suggests that atmospherically deposited black road‐tire‐wear matter is among the light‐absorbing particulates that advance the onset and rate of snow melt in the UCRB. The mass of road‐tire‐wear particles shed from vehicles may be estimated by multiplying measured amounts of eroded tire‐per‐distance traveled by vehicular distances. Under a combination of measurements and assumptions about the amounts and radiative properties of atmospheric tire‐wear particles, the radiative effects of these particles might add about 10%–30% to those effects from black carbon, an estimate ripe for revision. On regional and global scales, the amounts and effects of emitted and deposited tire‐wear matter likely vary by factors of geographic source, transport pathway, and depositional setting.
Investigation of Coastal Winds and Turbulence Characteristics Using Doppler Lidar
Authors: Li Ninghui , Dyer‐Hawes Quinn , Romanic Djordje , Burlando Massimiliano 
Published: September 2024

AbstractSea ports play a major role in the transport of goods worldwide, and knowledge of wind characteristics in these areas is vital to maintaining safety. However, coastal wind flow can be highly complex and turbulent, necessitating additional analysis. A Doppler lidar providing continuous wind profiles is deployed in the Port of Genoa, Italy, to characterize the mean wind velocity and turbulence properties within the coastal surface layer (40–250 m above ground level). Weather conditions, reanalysis data, and transient wind profiles are combined to analyze wind field characteristics on a day which experienced a thunderstorm. We also utilize a method to identify and categorize sources of turbulence through analysis of lidar derived quantities such as wind shear, turbulent kinetic energy, and vertical skewness. Seasonal variations in the wind properties are investigated by selecting data from June (summer) and December (winter). Differences are found in dominant wind direction and the associated frequency of convective mixing, with onshore winds most common in summer and offshore winds in winter. The measured lidar velocity is also compared against Monin–Obukhov similarity theory predictions, showing satisfactory agreement at low heights but struggling to reproduce observations of the stable atmospheric conditions present during winter.
High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor
Authors: Ha Viet-Anh , Giustino Feliciano 
Published: September 2024

Abstract2D semiconductors offer a promising pathway to replace silicon in next-generation electronics. Among their many advantages, 2D materials possess atomically-sharp surfaces and enable scaling the channel thickness down to the monolayer limit. However, these materials exhibit comparatively lower charge carrier mobility and higher contact resistance than 3D semiconductors, making it challenging to realize high-performance devices at scale. In this work, we search for high-mobility 2D materials by combining a high-throughput screening strategy with state-of-the-art calculations based on the ab initio Boltzmann transport equation. Our analysis singles out a known transition metal dichalcogenide, monolayer WS2, as the most promising 2D semiconductor, with the potential to reach ultra-high room-temperature hole mobilities in excess of 1300 cm2/Vs should Ohmic contacts and low defect densities be achieved. Our work also highlights the importance of performing full-blown ab initio transport calculations to achieve predictive accuracy, including spin–orbital couplings, quasiparticle corrections, dipole and quadrupole long-range electron–phonon interactions, as well as scattering by point defects and extended defects.
Gene-environmental influence of space and microgravity on red blood cells with sickle cell disease
Authors: Igbineweka Norris E. , van Loon Jack J. W. A. 
Published: September 2024

AbstractA fundamental question in human biology and for hematological disease is how do complex gene-environment interactions lead to individual disease outcome? This is no less the case for sickle cell disease (SCD), a monogenic disorder of Mendelian inheritance, both clinical course, severity, and treatment response, is variable amongst affected individuals. New insight and discovery often lie between the intersection of seemingly disparate disciplines. Recently, opportunities for space medicine have flourished and have offered a new paradigm for study. Two recent Nature papers have shown that hemolysis and oxidative stress play key mechanistic roles in erythrocyte pathogenesis during spaceflight. This paper reviews existing genetic and environmental modifiers of the sickle cell disease phenotype. It reviews evidence for erythrocyte pathology in microgravity environments and demonstrates why this may be relevant for the unique gene-environment interaction of the SCD phenotype. It also introduces the hematology and scientific community to methodological tools for evaluation in space and microgravity research. The increasing understanding of space biology may yield insight into gene-environment influences and new treatment paradigms in SCD and other hematological disease phenotypes.
Long COVID demographic and secondary care referral characteristics in primary care: analysis of anonymised primary care data from a multiethnic, deprived urban area in the UK
Authors: Chapman Martin , Durbaba Stevo , Tydeman Florence , Friend Matt , Duly Laura , Moore Julie , Curcin Vasa , Wang Yanzhong , Jolley Caroline J. , Kaltsakas Georgios , Chalder Trudie , Hart Nicholas , Ashworth Mark 
Published: September 2024

AbstractOnce the nature and number of patients with Long COVID was more fully understood, UK secondary care developed services to investigate, treat and support these patients. We aimed to identify evidence for demographic health inequalities based on general practitioner (GP) Long COVID referrals to available secondary care services. Despite Long COVID demographics broadly reflecting the multiethnic and socially disadvantaged profile of the study population, we found that secondary care referral was mainly focussed on older age patients and those born in the UK with co-morbid anxiety; although co-morbid diabetes was associated with reduced referrals.
Utilising an in silico model to predict outcomes in senescence-driven acute liver injury
Authors: Ashmore-Harris Candice , Antonopoulou Evangelia , Aird Rhona E. , Man Tak Yung , Finney Simon M. , Speel Annelijn M. , Lu Wei-Yu , Forbes Stuart J. , Gadd Victoria L. , Waters Sarah L. 
Published: September 2024

AbstractCurrently liver transplantation is the only treatment option for liver disease, but organ availability cannot meet patient demand. Alternative regenerative therapies, including cell transplantation, aim to modulate the injured microenvironment from inflammation and scarring towards regeneration. The complexity of the liver injury response makes it challenging to identify suitable therapeutic targets when relying on experimental approaches alone. Therefore, we adopted a combined in vivo-in silico approach and developed an ordinary differential equation model of acute liver disease able to predict the host response to injury and potential interventions. The Mdm2fl/fl mouse model of senescence-driven liver injury was used to generate a quantitative dynamic characterisation of the key cellular players (macrophages, endothelial cells, myofibroblasts) and extra cellular matrix involved in liver injury. This was qualitatively captured by the mathematical model. The mathematical model was then used to predict injury outcomes in response to milder and more severe levels of senescence-induced liver injury and validated with experimental in vivo data. In silico experiments using the validated model were then performed to interrogate potential approaches to enhance regeneration. These predicted that increasing the rate of macrophage phenotypic switch or increasing the number of pro-regenerative macrophages in the system will accelerate the rate of senescent cell clearance and resolution. These results showcase the potential benefits of mechanistic mathematical modelling for capturing the dynamics of complex biological systems and identifying therapeutic interventions that may enhance our understanding of injury-repair mechanisms and reduce translational bottlenecks.
Clinical and functional outcomes at 7-year follow-up of children presenting putative antecedents of schizophrenia at age 9-12 years
Authors: Cullen Alexis E. , Roberts Ruth E. , Fisher Helen L. , Laurens Kristin R. 
Published: September 2024

AbstractIdentification of youth presenting early risk factors for psychosis may facilitate preventive intervention. Through school-based screening, we recruited 112 children aged 9–12 years who presented multiple putative antecedents of schizophrenia (ASz), a family history of schizophrenia (FHx), or neither of these risk factors (typically-developing; TD). Clinical and functional outcomes were assessed at age 17–21 years (N = 93). Compared to the TD group, the ASz group had higher total Prodromal Questionnaire (PQ) scores (β = 10.59, 95% CI = 3.76, 17.42) and total psychopathology scores (β = 6.13, 95% CI: 1.03, 11.23), were more likely to score above-threshold on the PQ positive symptoms scale (OR = 4.00, 95% CI = 1.08, 14.83), and had lower scores on the Social and Occupational Functioning Scale (β = –9.43, 95% CI = –15.08, –3.77) at follow-up. The FHx and TD groups did not differ on any outcome. Findings suggest that population screening for putative antecedents of schizophrenia may identify children who would benefit from preventative intervention.
Chromosome-level genome assembly and annotation of Clanis bilineata tsingtauica Mell (Lepidoptera: Sphingidae)
Authors: Yan Yulu , Zhao Ke , Yang Longwei , Liu Nan , Xu Yufei , Gai Junyi , Xing Guangnan 
Published: September 2024

AbstractThe soybean hawkmoth Clanis bilineata tsingtauica Mell (Lepidoptera, Sphingidae; CBT), as one of the main leaf-chewing pests of soybeans, has gained popularity as an edible insect in China recently due to its high nutritional value. However, high-quality genome of CBT remains unclear, which greatly limits further research. In the present study, we assembled a high-quality chromosome-level genome of CBT using PacBio HiFi reads and Hi-C technologies for the first time. The size of the assembled genome is 477.45 Mb with a contig N50 length of 17.43 Mb. After Hi-C scaffolding, the contigs were anchored to 29 chromosomes with a mapping rate of 99.61%. Benchmarking Universal Single-Copy Orthologues (BUSCO) completeness value is 99.49%. The genome contains 252.16 Mb of repeat elements and 14,214 protein-coding genes. In addition, chromosomal synteny analysis showed that the genome of CBT has a strong synteny with that of Manduca sexta. In conclusion, this high-quality genome provides an important resource for future studies of CBT and contributes to the development of integrated pest management strategies.
Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2
Authors: Moraes dos Santos Lucas , Gutembergue de Mendonça José , Jerônimo Gomes Lobo Yan , Henrique Franca de Lima Leonardo , Bruno Rocha Gerd , C. de Melo-Minardi Raquel 
Published: September 2024

AbstractMolecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based approaches have led to the understanding of specific structural changes observed in MD trajectories, including those induced by mutations. In this study, we model the trajectories resulting from MD simulations of the SARS-CoV-2 spike protein-ACE2, specifically the receptor-binding domain (RBD), as interresidue distance maps, and use deep convolutional neural networks to predict the functional impact of point mutations, related to the virus’s infectivity and immunogenicity. Our model was successful in predicting mutant types that increase the affinity of the S protein for human receptors and reduce its immunogenicity, both based on MD trajectories (precision = 0.718; recall = 0.800; $$\hbox {F}_1$$ = 0.757; MCC = 0.488; AUC = 0.800) and their centroids. In an additional analysis, we also obtained a strong positive Pearson’s correlation coefficient equal to 0.776, indicating a significant relationship between the average sigmoid probability for the MD trajectories and binding free energy (BFE) changes. Furthermore, we obtained a coefficient of determination of 0.602. Our 2D-RMSD analysis also corroborated predictions for more infectious and immune-evading mutants and revealed fluctuating regions within the receptor-binding motif (RBM), especially in the $$\beta _{1}^{\prime }/\beta _{2}^{\prime }-C$$ loop. This region presented a significant standard deviation for mutations that enable SARS-CoV-2 to evade the immune response, with RMSD values of 5Å in the simulation. This methodology offers an efficient alternative to identify potential strains of SARS-CoV-2, which may be potentially linked to more infectious and immune-evading mutations. Using clustering and deep learning techniques, our approach leverages information from the ensemble of MD trajectories to recognize a broad spectrum of multiple conformational patterns characteristic of mutant types. This represents a strategic advantage in identifying emerging variants, bypassing the need for long MD simulations. Furthermore, the present work tends to contribute substantially to the field of computational biology and virology, particularly to accelerate the design and optimization of new therapeutic agents and vaccines, offering a proactive stance against the constantly evolving threat of COVID-19 and potential future pandemics.
Application of operating scenarios and analysis of unstable flow characteristics at various angles of inlet guide vane
Authors: Son Yong-Jin , Yang Hyeon-Mo , Lee Kyoung-Yong , Yoon Joon Yong , Choi Young-Seok 
Published: September 2024

AbstractIn this study, we analyzed the performance characteristics of an axial flow pump with different angles of internally installed inlet guide vanes (IGVs). We predicted the pump’s performance based on changes in the IGV angle and analyzed the impact of these angle variations on pump operation in the low-flow region. Additionally, we used real operational data from two sewage treatment plants to propose efficient operational scenarios. For turbulence flow analysis, the Reynolds-averaged Navier–Stokes equations were discretized based on the finite volume method. The grid formation was evaluated using the grid convergence index to select the optimal grid. Then, the internal flow was analyzed in detail through transient-state analysis. Through fast Fourier transform analysis, we confirmed that adjusting the IGV angle during pump operation in the low-flow region in response to load changes results in more stable operation compared with the existing method (valve control). Overall, our findings verified that energy reduction and efficient operation can be achieved through IGV angle adjustment compared with valve control.
New Bacillus paralicheniformis strain with high proteolytic and keratinolytic activity
Authors: Aktayeva Saniya , Khassenov Bekbolat 
Published: September 2024

AbstractBacillus paralicheniformis T7, which exhibits high proteolytic and keratinolytic activities, was isolated from soil in Kazakhstan. Its secreted proteases were thermostable and alkaline, demonstrating maximum activity at 70 °C and pH 9.0. The proteases and keratinases of this strain were sensitive to Ni2+, Co2+, Mn2+, and Cd2+, with Cu2+, Co2+ and Cd2+ negatively affecting keratinolytic activity, and Fe3+ ions have a strong inhibitory effect on proteolytic and keratinolytic activity. Seven proteases were identified in the enzymatic extract of B. paralicheniformis T7: four from the serine peptidase family and three from the metallopeptidase family. The proteases hydrolyzed 1 mg of casein, hemoglobin, gelatin, ovalbumin, bovine serum albumin, or keratin within 15 s to 30 min. The high keratinolytic activity of this strain was confirmed through the degradation of chicken feathers, horns, hooves, wool, and cattle hide. Chicken feathers were hydrolyzed in 4 days, and the degrees of hydrolysis for cattle hide, wool, hoof, and horn after 7 days of cultivation were 97.2, 34.5, 29.6, and 3.6%, respectively. During submerged fermentation with feather medium in a laboratory bioreactor, the strain secreted enzymes with 249.20 ± 7.88 U/mL protease activity after 24 h. Thus, B. paralicheniformis T7 can be used to produce proteolytic and keratinolytic enzymes for application in processing proteinaceous raw materials and keratinous animal waste.
Effects of artificial intelligence implementation on efficiency in medical imaging—a systematic literature review and meta-analysis
Authors: Wenderott Katharina , Krups Jim , Zaruchas Fiona , Weigl Matthias 
Published: September 2024

AbstractIn healthcare, integration of artificial intelligence (AI) holds strong promise for facilitating clinicians’ work, especially in clinical imaging. We aimed to assess the impact of AI implementation for medical imaging on efficiency in real-world clinical workflows and conducted a systematic review searching six medical databases. Two reviewers double-screened all records. Eligible records were evaluated for methodological quality. The outcomes of interest were workflow adaptation due to AI implementation, changes in time for tasks, and clinician workload. After screening 13,756 records, we identified 48 original studies to be incuded in the review. Thirty-three studies measured time for tasks, with 67% reporting reductions. Yet, three separate meta-analyses of 12 studies did not show significant effects after AI implementation. We identified five different workflows adapting to AI use. Most commonly, AI served as a secondary reader for detection tasks. Alternatively, AI was used as the primary reader for identifying positive cases, resulting in reorganizing worklists or issuing alerts. Only three studies scrutinized workload calculations based on the time saved through AI use. This systematic review and meta-analysis represents an assessment of the efficiency improvements offered by AI applications in real-world clinical imaging, predominantly revealing enhancements across the studies. However, considerable heterogeneity in available studies renders robust inferences regarding overall effectiveness in imaging tasks. Further work is needed on standardized reporting, evaluation of system integration, and real-world data collection to better understand the technological advances of AI in real-world healthcare workflows. Systematic review registration: Prospero ID CRD42022303439, International Registered Report Identifier (IRRID): RR2-10.2196/40485.