bluuebunny/crossref_metadata_2025 huggingface dataset:
The discovery of three-dimensional Van Hove singularity
Authors: Wu Wenbin , Shi Zeping , Ozerov Mykhaylo , Du Yuhan , Wang Yuxiang , Ni Xiao-Sheng , Meng Xianghao , Jiang Xiangyu , Wang Guangyi , Hao Congming , Wang Xinyi , Zhang Pengcheng , Pan Chunhui , Pan Haifeng , Sun Zhenrong , Yang Run , Xu Yang , Hou Yusheng , Yan Zhongbo , Zhang Cheng , Lu Hai-Zhou , Chu Junhao , Yuan Xiang
Published: March 2024

Arising from the extreme/saddle point in electronic bands, Van Hove singularity (VHS) manifests divergent density of states (DOS) and induces various new states of matter such as unconventional superconductivity. VHS is believed to exist in one and two dimensions, but rarely found in three dimension (3D). Here, we report the discovery of 3D VHS in a topological magnet EuCd2As2 by magneto-infrared spectroscopy. External magnetic fields effectively control the exchange interaction in EuCd2As2, and shift 3D Weyl bands continuously, leading to the modification of Fermi velocity and energy dispersion. Above the critical field, the 3D VHS forms and is evidenced by the abrupt emergence of inter-band transitions, which can be quantitatively described by the minimal model of Weyl semimetals. Three additional optical transitions are further predicted theoretically and verified in magneto-near-infrared spectra. Our results pave the way to exploring VHS in 3D systems and uncovering the coordination between electronic correlation and the topological phase.
Revealing Fermi surface evolution and Berry curvature in an ideal type-II Weyl semimetal
Authors: Jiang Qianni , Palmstrom Johanna C. , Singleton John , Chikara Shalinee , Graf David , Wang Chong , Shi Yue , Malinowski Paul , Wang Aaron , Lin Zhong , Shen Lingnan , Xu Xiaodong , Xiao Di , Chu Jiun-Haw
Published: March 2024

In type-II Weyl semimetals (WSMs), the tilting of the Weyl cones leads to the coexistence of electron and hole pockets that touch at the Weyl nodes. These electrons and holes experience the Berry curvature generated by the Weyl nodes, leading to an anomalous Hall effect that is highly sensitive to the Fermi level position. Here we have identified field-induced ferromagnetic MnBi2-xSbxTe4 as an ideal type-II WSM with a single pair of Weyl nodes. By employing a combination of quantum oscillations and high-field Hall measurements, we have resolved the evolution of Fermi-surface sections as the Fermi level is tuned across the charge neutrality point, precisely matching the band structure of an ideal type-II WSM. Furthermore, the anomalous Hall conductivity exhibits a heartbeat-like behavior as the Fermi level is tuned across the Weyl nodes, a feature of type-II WSMs that was long predicted by theory. Our work uncovers a large free carrier contribution to the anomalous Hall effect resulting from the unique interplay between the Fermi surface and diverging Berry curvature in magnetic type-II WSMs.
Mixed tin-lead perovskites with balanced crystallization and oxidation barrier for all-perovskite tandem solar cells
Authors: Zhou Jin , Fu Shiqiang , Zhou Shun , Huang Lishuai , Wang Cheng , Guan Hongling , Pu Dexin , Cui Hongsen , Wang Chen , Wang Ti , Meng Weiwei , Fang Guojia , Ke Weijun
Published: March 2024

Mixed tin-lead perovskite solar cells have driven a lot of passion for research because of their vital role in all-perovskite tandem solar cells, which hold the potential for achieving higher efficiencies compared to single-junction counterparts. However, the pronounced disparity in crystallization processes between tin-based perovskites and lead-based perovskites, coupled with the easy Sn2+ oxidation, has long been a dominant factor contributing to high defect densities. In this study, we propose a multidimensional strategy to achieve efficient tin-lead perovskite solar cells by employing a functional N-(carboxypheny)guanidine hydrochloride molecule. The tailored N-(carboxypheny)guanidine hydrochloride molecule plays a pivotal role in manipulating the crystallization and grain growth of tin-lead perovskites, while also serving as a preservative to effectively inhibit Sn2+ oxidation, owing to the strong binding between N-(carboxypheny)guanidine hydrochloride and tin (II) iodide and the elevated energy barriers for oxidation. Consequently, single-junction tin-lead cells exhibit a stabilized power conversion efficiency of 23.11% and can maintain 97.45% of their initial value even after 3500 h of shelf storage in an inert atmosphere without encapsulation. We further integrate tin-lead perovskites into two-terminal monolithic all-perovskite tandem cells, delivering a certified efficiency of 27.35%.
Regulation of meiotic telomere dynamics through membrane fluidity promoted by AdipoR2-ELOVL2
Authors: Zhang Jingjing , Ruiz Mario , Bergh Per-Olof , Henricsson Marcus , Stojanović Nena , Devkota Ranjan , Henn Marius , Bohlooly-Y Mohammad , Hernández-Hernández Abrahan , Alsheimer Manfred , Borén Jan , Pilon Marc , Shibuya Hiroki
Published: March 2024

The cellular membrane in male meiotic germ cells contains a unique class of phospholipids and sphingolipids that is required for male reproduction. Here, we show that a conserved membrane fluidity sensor, AdipoR2, regulates the meiosis-specific lipidome in mouse testes by promoting the synthesis of sphingolipids containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs). AdipoR2 upregulates the expression of a fatty acid elongase, ELOVL2, both transcriptionally and post-transcriptionally, to synthesize VLC-PUFA. The depletion of VLC-PUFAs and subsequent accumulation of palmitic acid in AdipoR2 knockout testes stiffens the cellular membrane and causes the invagination of the nuclear envelope. This condition impairs the nuclear peripheral distribution of meiotic telomeres, leading to errors in homologous synapsis and recombination. Further, the stiffened membrane impairs the formation of intercellular bridges and the germ cell syncytium, which disrupts the orderly arrangement of cell types within the seminiferous tubules. According to our findings we propose a framework in which the highly-fluid membrane microenvironment shaped by AdipoR2-ELOVL2 underpins meiosis-specific chromosome dynamics in testes.
Supra-biological performance of immobilized enzymes enabled by chaperone-like specific non-covalent interactions
Authors: Sánchez-Morán Héctor , Kaar Joel L. , Schwartz Daniel K.
Published: March 2024

Designing complex synthetic materials for enzyme immobilization could unlock the utility of biocatalysis in extreme environments. Inspired by biology, we investigate the use of random copolymer brushes as dynamic immobilization supports that enable supra-biological catalytic performance of immobilized enzymes. This is demonstrated by immobilizing Bacillus subtilis Lipase A on brushes doped with aromatic moieties, which can interact with the lipase through multiple non-covalent interactions. Incorporation of aromatic groups leads to a 50 °C increase in the optimal temperature of lipase, as well as a 50-fold enhancement in enzyme activity. Single-molecule FRET studies reveal that these supports act as biomimetic chaperones by promoting enzyme refolding and stabilizing the enzyme’s folded and catalytically active state. This effect is diminished when aromatic residues are mutated out, suggesting the importance of π-stacking and π-cation interactions for stabilization. Our results underscore how unexplored enzyme-support interactions may enable uncharted opportunities for using enzymes in industrial biotransformations.
Atomically precise engineering of spin–orbit polarons in a kagome magnetic Weyl semimetal
Authors: Chen Hui , Xing Yuqing , Tan Hengxin , Huang Li , Zheng Qi , Huang Zihao , Han Xianghe , Hu Bin , Ye Yuhan , Li Yan , Xiao Yao , Lei Hechang , Qiu Xianggang , Liu Enke , Yang Haitao , Wang Ziqiang , Yan Binghai , Gao Hong-Jun
Published: March 2024

Atomically precise defect engineering is essential to manipulate the properties of emerging topological quantum materials for practical quantum applications. However, this remains challenging due to the obstacles in modifying the typically complex crystal lattice with atomic precision. Here, we report the atomically precise engineering of the vacancy-localized spin–orbit polarons in a kagome magnetic Weyl semimetal Co3Sn2S2, using scanning tunneling microscope. We achieve the step-by-step repair of the selected vacancies, leading to the formation of artificial sulfur vacancies with elaborate geometry. We find that that the bound states localized around these vacancies undergo a symmetry dependent energy shift towards Fermi level with increasing vacancy size. As the vacancy size increases, the localized magnetic moments of spin–orbit polarons become tunable and eventually become itinerantly negative due to spin–orbit coupling in the kagome flat band. These findings provide a platform for engineering atomic quantum states in topological quantum materials at the atomic scale.
Efficient finite strain elasticity solver for phase-field simulations
Authors: Shchyglo Oleg , Ali Muhammad Adil , Salama Hesham
Published: March 2024

We present an effective mechanical equilibrium solution algorithm suitable for finite strain consideration within the phase-field method. The proposed algorithm utilizes a Fourier space solution in its core. The performance of the proposed algorithm is demonstrated using the St. Venant–Kirchhoff hyperelastic model, but the algorithm is also applicable to other hyperelastic models. The use of the fast Fourier transformation routines and fast convergence within several iterations for most common simulation scenarios makes the proposed algorithm suitable for phase-field simulations of rapidly evolving microstructures. Additionally, the proposed algorithm allows using different strain measures depending on the requirements of the underlying problem. The algorithm is implemented in the OpenPhase phase-field simulation library. A set of example simulations ranging from simple geometries to complex microstructures is presented. The effect of different externally applied mechanical boundary conditions and internal forces is also demonstrated. The proposed algorithm can be considered a straightforward update to already existing small strain solvers based on Fourier space solutions.
Future opportunities in solar system plasma science through ESA’s exploration programme
Authors: Holmstrom Mats , Lester Mark , Sanchez-Cano Beatriz
Published: March 2024

The solar wind interacts with all solar system bodies, inducing different types of dynamics depending on their atmospheric and magnetic environments. We here outline some key open scientific questions related to this interaction, with a focus on the Moon and Mars, that may be addressed by future Mars and Moon missions by the European Space Agency’s Human and Robotic Exploration programme. We describe possible studies of plasma interactions with bodies with and without an atmosphere, using multi-point and remote measurements, and energetic particle observations, as well as recommend some actions to take.
Field testing the transferability of behavioural science knowledge on promoting vaccinations
Authors: Saccardo Silvia , Dai Hengchen , Han Maria A. , Vangala Sitaram , Hoo Juyea , Fujimoto Jeffrey
Published: March 2024

As behavioural science is increasingly adopted by organizations, there is a growing need to assess the robustness and transferability of empirical findings. Here, we investigate the transferability of insights from various sources of behavioural science knowledge to field settings. Across three pre-registered randomized controlled trials (RCTs, N = 314,824) involving a critical policy domain—COVID-19 booster uptake—we field tested text-based interventions that either increased vaccinations in prior field work (RCT1, NCT05586204), elevated vaccination intentions in an online study (RCT2, NCT05586178) or were favoured by scientists and non-experts (RCT3, NCT05586165). Despite repeated exposure to COVID-19 vaccination messaging in our population, reminders and psychological ownership language increased booster uptake, replicating prior findings. However, strategies deemed effective by prediction or intention surveys, such as encouraging the bundling of COVID-19 boosters and flu shots or addressing misconceptions, yielded no detectable benefits over simple reminders. These findings underscore the importance of testing interventions’ transferability to real-world settings.
A Georeferenced Dataset for Mapping and Assessing Subgrade Defects in China’s High-Speed Railways
Authors: Wang Jinchen , Wang Luqi , Zhang Yinsheng , Zhang Jingyu , Li Jianlin , Li Sen
Published: March 2024

China has the world’s longest high-speed rail (HSR) network, marked by dense transportation and complex operations. However, frequent train use coupled with extreme weather conditions has led to rising subgrade issues. Existing railway defect records suffer from inconsistency, hindering direct applicability. Currently, there is a lack of a relevant dataset dedicated to HSR subgrade defects. To bridge this gap, we developed a comprehensive georeferenced dataset that encompasses defect records extracted from peer-reviewed literature published between 1999 and 2023 in China. Rigorous quality control procedures were implemented to eliminate duplicate data and ensure the accuracy of the dataset. The dataset consists of georeferenced records for eight different defects, spanning across 661 locations and categorized at various scales, ranging from provinces to townships. The most commonly reported defect types include subgrade settlement, frost damage, uplift deformation, and mud pumping. This dataset provides a comprehensive map of historical subgrade defects affecting high-speed railways in China. It could facilitate operational risk assessments and the prediction of subgrade performance.
A global dataset of publicly available dengue case count data
Authors: Clarke J. , Lim A. , Gupte P. , Pigott D. M. , van Panhuis W. G. , Brady O. J.
Published: March 2024

OpenDengue is a global database of dengue case data collated from public sources and standardised and formatted to facilitate easy reanalysis. Dataset version 1.2 of this database contains information on over 56 million dengue cases from 102 countries between 1924 and 2023, making it the largest and most comprehensive dengue case database currently available. Over 95% of records are at the weekly or monthly temporal resolution and subnational data is available for 40 countries. To build OpenDengue we systematically searched databases, ministry of health websites, peer reviewed literature and Pro-MED mail reports and extracted denominator-based case count data. We undertake standardisation and error checking protocols to ensure consistency and resolve discrepancies. We meticulously documented the extraction process to ensure records are attributable and reproducible. The OpenDengue database remains under development with plans for further disaggregation and user contributions are encouraged. This new dataset can be used to better understand the long-term drivers of dengue transmission, improve estimates of disease burden, targeting and evaluation of interventions and improving future projections.
Mendelian randomization study on insulin resistance and risk of hypertension and cardiovascular disease
Authors: Zhang Fangfang , Yu Zhimin
Published: March 2024

Observational studies have suggested that insulin resistance (IR) is associated with hypertension and various cardiovascular diseases. However, the presence of a causal relationship between IR and cardiovascular disease remains unclear. Here, we applied Mendelian randomization (MR) approaches to address the causal association between genetically determined IR and the risk of cardiovascular diseases. Our primary genetic instruments comprised 53 SNPs associated with IR phenotype from a GWAS of up to 188,577 participants. Genetic association estimates for hypertension and venous thromboembolism (VTE) were extracted from UK Biobank, estimates for atrial fibrillation (AF) were extracted from the hitherto largest GWAS meta-analysis on AF, estimates for heart failure were extracted from HERMES Consortium, estimates for peripheral artery disease (PAD) and aortic aneurysm were extracted from the FinnGen Study. The main analyses were performed using the random-effects inverse-variance weighted approach, and complemented by sensitivity analyses and multivariable MR analyses. Corresponding to 55% higher fasting insulin adjusted for body mass index, 0.46 mmol/L lower high-density lipoprotein cholesterol and 0.89 mmol/L higher triglyceride, one standard deviation change in genetically predicted IR was associated with increased risk of hypertension (odds ratio (OR) 1.06, 95% CI 1.04–1.08; P = 1.91 × 10–11) and PAD (OR 1.90, 95% CI 1.43–2.54; P = 1.19 × 10–5). Suggestive evidence was obtained for an association between IR and heart failure (OR per SD change in IR: 1.19, 95% CI 1.01–1.41, P = 0.041). There was no MR evidence for an association between genetically predicted IR and atrial fibrillation, VTE, and aortic aneurysm. Results were widely consistent across all sensitivity analyses. In multivariable MR, the association between IR and PAD was attenuated after adjustment for lipids (P = 0.347) or BMI (P = 0.163). Our findings support that genetically determined IR increases the risk of hypertension and PAD.
Preclinical systolic dysfunction relating to ankle-brachial index among high-risk PAD population with preserved left ventricular ejection fraction
Authors: Lin Yueh-Hung , Sung Kuo-Tzu , Tsai Cheng-Ting , Lai Yau-Huei , Lo Chi-In , Yu Fa-Chang , Lan Wei-Ran , Hung Ta-Chuan , Kuo Jen-Yuan , Hou Charles Jia-Yin , Yen Chih-Hsuan , Peng Ming-Cheng , Yeh Hung-I. , Wu Ming-Ting , Hung Chung-Lieh
Published: March 2024

Peripheral artery disease (PAD) shares common clinical risk factors, for example, endothelial dysfunction, with preserved ejection fraction (LVEF) heart failure (HFpEF). Whether PAD is associated with preclinical systolic dysfunction and higher HF risk among individuals presenting preserved LVEF remains uncertain. We retrospectively included outpatients with at least one known or established cardiovascular (CV) risk factor with LVEF ≥ 50%. Patients were categorized into high risk and low risk of developing PAD (PAD vs Non-PAD) by ankle-brachial index (ABI) (≤ 0.90 or > 1.4) and further stratified based on their history of HFpEF (HFpEF vs. Non-HFpEF), resulting in the formation of four distinct strata. Preclinical systolic dysfunction was defined using dedicated speckle-tracking algorithm. A total of 2130 consecutive patients were enrolled in the study, with a median follow-up of 4.4 years. The analysis revealed a higher prevalence of high risk of developing PAD in patients with HFpEF compared to those without HFpEF (25.1% vs. 9.4%). Both high risk of developing PAD and HFpEF were independently associated with preclinical systolic dysfunction (global longitudinal strain, GLS ≥ − 18%) (odds ratio, OR: 1.38; 95% confidence interval, CI: 1.03–1.86). In comparison to patients at low risk of developing PAD without HFpEF (Non-PAD/Non-HFpEF group), those categorized as having a high risk of developing PAD with HFpEF (PAD/HFpEF group) exhibited the most impaired GLS and a heightened susceptibility to heart failure hospitalization (hazard ratio, HR: 6.51; 95% CI: 4.43–9.55), a twofold increased risk of all-cause mortality (HR: 2.01; 95% CI: 1.17–3.38), cardiovascular mortality (HR: 2.44; 95% CI: 1.08–5.51), and non-cardiovascular mortality (HR: 1.78; 95% CI: 0.82–3.84). A high risk of developing PAD was strongly linked to impaired preclinical systolic function and an increased likelihood for subsequent hospitalization for HF, all-cause mortality, CV mortality and non-CV mortality. There is a clear need for preventive strategies aimed at reducing hospitalizations for HF and mortality in this high-risk population.
Analysis and evaluation of explainable artificial intelligence on suicide risk assessment
Authors: Tang Hao , Miri Rekavandi Aref , Rooprai Dharjinder , Dwivedi Girish , Sanfilippo Frank M. , Boussaid Farid , Bennamoun Mohammed
Published: March 2024

This study explores the effectiveness of Explainable Artificial Intelligence (XAI) for predicting suicide risk from medical tabular data. Given the common challenge of limited datasets in health-related Machine Learning (ML) applications, we use data augmentation in tandem with ML to enhance the identification of individuals at high risk of suicide. We use SHapley Additive exPlanations (SHAP) for XAI and traditional correlation analysis to rank feature importance, pinpointing primary factors influencing suicide risk and preventive measures. Experimental results show the Random Forest (RF) model is excelling in accuracy, F1 score, and AUC (>97% across metrics). According to SHAP, anger issues, depression, and social isolation emerge as top predictors of suicide risk, while individuals with high incomes, esteemed professions, and higher education present the lowest risk. Our findings underscore the effectiveness of ML and XAI in suicide risk assessment, offering valuable insights for psychiatrists and facilitating informed clinical decisions.
Experimental and computational studies of crystal violet removal from aqueous solution using sulfonated graphene oxide
Authors: Oluwasina Olayinka Oluwaseun , Adelodun Adedeji Adebukola , Oluwasina Olugbenga Oludayo , Duarte Helio A. , Olusegun Sunday Joseph
Published: March 2024

Positively charged contaminants can be strongly attracted by sulfanilic acid-functionalized graphene oxide. Here, sulfonated graphene oxide (GO-SO3H) was synthesized and characterized for cationic crystal violet (CV) adsorption. We further studied the effect of pH, initial concentration, and temperature on CV uptake. The highest CV uptake occurred at pH 8. A kinetic study was also carried out by applying the pseudo-first-order and pseudo-second-order models. The pseudo-second-order’s adsorption capacity (qe) value was much closer to the experimental qe (qeexp:0.13, qecal:0.12) than the pseudo-first-order model (qeexp:0.13, qecal:0.05). The adsorption performance was accomplished rapidly since the adsorption equilibrium was closely obtained within 30 min. Furthermore, the adsorption capacity was significantly increased from 42.85 to 79.23%. The maximum adsorption capacities of GO-SO3H where 97.65, 202.5, and 196.2 mg·g−1 for CV removal at 298, 308, and 328 K, respectively. The Langmuir and Freundlich adsorption isotherms were applied to the experimental data. The data fit well into Langmuir and Freundlich except at 298 K, where only Langmuir isotherm was most suitable. Thermodynamic studies established that the adsorption was spontaneous and endothermic. The adsorption mechanism was revealed by combining experimental and computational methods. These findings suggest that GO-SO3H is a highly adsorbent for removing harmful cationic dye from aqueous media.
Warming waters lead to increased habitat suitability for juvenile bull sharks (Carcharhinus leucas)
Authors: Mullins Lindsay , Cartwright John , Dykstra Steven L. , Evans Kristine , Mareska John , Matich Philip , Plumlee Jeffrey D. , Sparks Eric , Drymon J. Marcus
Published: March 2024

Coastal ecosystems are highly vulnerable to the impacts of climate change and other stressors, including urbanization and overfishing. Consequently, distributions of coastal fish have begun to change, particularly in response to increasing temperatures linked to climate change. However, few studies have evaluated how natural and anthropogenic disturbances can alter species distributions in conjunction with geophysical habitat alterations, such as changes to land use and land cover (LU/LC). Here, we examine the spatiotemporal changes in the distribution of juvenile bull sharks (Carcharhinus leucas) using a multi-decadal fishery-independent survey of coastal Alabama. Using a boosted regression tree (BRT) modeling framework, we assess the covariance of environmental conditions (sea surface temperature, depth, salinity, dissolved oxygen, riverine discharge, Chl-a) as well as historic changes to LU/LC to the distribution of bull sharks. Species distribution models resultant from BRTs for early (2003–2005) and recent (2018–2020) monitoring periods indicated a mean increase in habitat suitability (i.e., probability of capture) for juvenile bull sharks from 0.028 to 0.082, concomitant with substantial increases in mean annual temperature (0.058°C/yr), Chl-a (2.32 mg/m3), and urbanization (increased LU/LC) since 2000. These results align with observed five-fold increases in the relative abundance of juvenile bull sharks across the study period and demonstrate the impacts of changing environmental conditions on their distribution and relative abundance. As climate change persists, coastal communities will continue to change, altering the structure of ecological communities and the success of nearshore fisheries.
A new automatic geo-electric self-potential imaging technique for diverse sustainable development scenarios
Authors: Elhussein Mahmoud , Diab Zein E.
Published: March 2024

This study introduces a rapid and efficient inversion algorithm designed for the interpretation of self-potential responses originating from mineralized and ore sources and hydrothermal activity, specifically addressing spherical, vertical, and horizontal cylindrical structures. The algorithm leverages local wavenumber and correlation imaging techniques to enhance accuracy in modeling. The correlation factor (Cf value) is crucial in this approach, calculated as the correlation between the local wavenumber of the measured self-potential field and that of the computed field. The algorithm identifies the maximum correlation Cf value (CF-max) as indicative of the optimal true model parameters. To validate the proposed algorithm, it was applied to three theoretical examples—one with contamination from regional background and another with multiple sources with and without different types of noises (random Gaussian and white Gaussian noises). Additionally, the approach was tested on three distinct real field cases related to mining, ore investigation and hydrothermal activity in India, Germany and USA. Through a comprehensive analysis of results from theoretical and real-world scenarios, including comparisons with different available data and literature information, the study concludes that the method is effective, applicable to multiple sources, accurate, and does not necessitate prior knowledge of the source shape. This algorithm presents a promising advancement in the field of self-potential interpretation for mineral exploration and geothermal exploration.
Lifestyle behaviour changes associated with osteoarthritis: a prospective cohort study
Authors: Ng Norman , Parkinson Lynne , Brown Wendy J. , Moorin Rachael , Peeters G. M. E. E. Geeske
Published: March 2024

The aim of this prospective cohort study was to compare changes in lifestyle behaviours over nine years in women who were and were not diagnosed with osteoarthritis (OA). Data were from the 1945–51 cohort of the Australian Longitudinal Study on Women’s Health (aged 50–55 in 2001) who completed written surveys in 2001, 2004, 2007 and 2010. The sample included 610 women who were, and 3810 women who were not diagnosed with OA between 2004 and 2007. Descriptive statistics were used to assess changes in lifestyle behaviours (weight, sitting time, physical activity, alcohol and smoking) in the two groups, over three survey intervals: from 2001–2004 (prior to diagnosis); from 2004–2007 (around diagnosis); and from 2007–2010 (following diagnosis). Compared with women without OA (28%), a greater proportion of women with OA (38%) made at least one positive lifestyle change (p < 0.001). These included losing > 5 kg (9.8% vs. 14.4%, p < 0.001), and reducing sitting time by an hour (29.5% vs. 39.1%, p < 0.001) following diagnosis. However, women with OA also made negative lifestyle changes (35% vs. 29%, p < 0.001), for example, gaining > 5 kg around the time of diagnosis (21.4% vs. 14.5%, p < 0.001) and increasing sitting time by an hour following diagnosis (38.4% vs. 32.3%, p = 0.003). More women with OA also started smoking following diagnosis (8.9% vs. 0.8%, p < 0.001). While some women made positive changes in lifestyle behaviours during and following OA diagnosis, others made negative changes. Consistent support from clinicians for managing OA symptoms may enable patients to make more positive changes in lifestyle behaviours.
An improved transformer-based concrete crack classification method
Authors: Ye Guanting , Dai Wei , Tao Jintai , Qu Jinsheng , Zhu Lin , Jin Qiang
Published: March 2024

In concrete structures, surface cracks are an important indicator for assessing the durability and serviceability of the structure. Existing convolutional neural networks for concrete crack identification are inefficient and computationally costly. Therefore, a new Cross Swin transformer-skip (CSW-S) is proposed to classify concrete cracks. The method is optimized by adding residual links to the existing Cross Swin transformer network and then trained and tested using a dataset with 17,000 images. The experimental results show that the improved CSW-S network has an extended range of extracted image features, which improves the accuracy of crack recognition. A detection accuracy of 96.92% is obtained using the trained CSW-S without pretraining. The improved transformer model has higher recognition efficiency and accuracy than the traditional transformer model and the classical CNN model.
Python farming as a flexible and efficient form of agricultural food security
Authors: Natusch D. , Aust P. W. , Caraguel C. , Taggart P. L. , Ngo V. T. , Alexander G. J. , Shine R. , Coulson T.
Published: March 2024

Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons (Malayopython reticulatus and Python bivittatus) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus, depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.
cyp51A mutations, protein modeling, and efflux pump gene expression reveals multifactorial complexity towards understanding Aspergillus section Nigri azole resistance mechanism
Authors: Sen Pooja , Vijay Mukund , Kamboj Himanshu , Gupta Lovely , Shankar Jata , Vijayaraghavan Pooja
Published: March 2024

Black Aspergillus species are the most common etiological agents of otomycosis, and pulmonary aspergillosis. However, limited data is available on their antifungal susceptibility profiles and associated resistance mechanisms. Here, we determined the azole susceptibility profiles of black Aspergillus species isolated from the Indian environment and explored the potential resistance mechanisms through cyp51A gene sequencing, protein homology modeling, and expression analysis of selected genes cyp51A, cyp51B, mdr1, and mfs based on their role in imparting resistance against antifungal drugs. In this study, we have isolated a total of 161 black aspergilli isolates from 174 agricultural soil samples. Isolates had variable resistance towards medical azoles; approximately 11.80%, 3.10%, and 1.24% of isolates were resistant to itraconazole (ITC), posaconazole (POS), and voriconazole (VRC), respectively. Further, cyp51A sequence analysis showed that non-synonymous mutations were present in 20 azole-resistant Aspergillus section Nigri and 10 susceptible isolates. However, Cyp51A homology modeling indicated insignificant protein structural variations because of these mutations. Most of the isolates showed the overexpression of mdr1, and mfs genes. Hence, the study concluded that azole-resistance in section Nigri cannot be attributed exclusively to the cyp51A gene mutation or its overexpression. However, overexpression of mdr1 and mfs genes may have a potential role in drug resistance.
Identification of a hyperinflammatory sepsis phenotype using protein biomarker and clinical data in the ProCESS randomized trial
Authors: DeMerle Kimberley M. , Kennedy Jason N. , Chang Chung-Chou H. , Delucchi Kevin , Huang David T. , Kravitz Max S. , Shapiro Nathan I. , Yealy Donald M. , Angus Derek C. , Calfee Carolyn S. , Seymour Christopher W.
Published: March 2024

Sepsis is a heterogeneous syndrome and phenotypes have been proposed using clinical data. Less is known about the contribution of protein biomarkers to clinical sepsis phenotypes and their importance for treatment effects in randomized trials of resuscitation. The objective is to use both clinical and biomarker data in the Protocol-Based Care for Early Septic Shock (ProCESS) randomized trial to determine sepsis phenotypes and to test for heterogeneity of treatment effect by phenotype comparing usual care to protocolized early, goal-directed therapy(EGDT). In this secondary analysis of a subset of patients with biomarker sampling in the ProCESS trial (n = 543), we identified sepsis phenotypes prior to randomization using latent class analysis of 20 clinical and biomarker variables. Logistic regression was used to test for interaction between phenotype and treatment arm for 60-day inpatient mortality. Among 543 patients with severe sepsis or septic shock in the ProCESS trial, a 2-class model best fit the data (p = 0.01). Phenotype 1 (n = 66, 12%) had increased IL-6, ICAM, and total bilirubin and decreased platelets compared to phenotype 2 (n = 477, 88%, p < 0.01 for all). Phenotype 1 had greater 60-day inpatient mortality compared to Phenotype 2 (41% vs 16%; p < 0.01). Treatment with EGDT was associated with worse 60-day inpatient mortality compared to usual care (58% vs. 23%) in Phenotype 1 only (p-value for interaction = 0.05). The 60-day inpatient mortality was similar comparing EGDT to usual care in Phenotype 2 (16% vs. 17%). We identified 2 sepsis phenotypes using latent class analysis of clinical and protein biomarker data at randomization in the ProCESS trial. Phenotype 1 had increased inflammation, organ dysfunction and worse clinical outcomes compared to phenotype 2. Response to EGDT versus usual care differed by phenotype.
Investigation of the performance of a horizontal-axis dual rotor wind turbine
Authors: Salah Dina Ahmed Hosni , Nosier Mahmoud Abed El-Rasheed , Hamed Ashraf Mostafa
Published: March 2024

Recent years have seen a rise in interest in wind energy as a useful alternative to harmful energies like fossil fuels. The dual rotor wind turbine (DRWT) offers more rapid rates of wind energy extraction. The current study intends to compare the performance of the turbine with and without the addition of a second rotor. Additionally, it examines how tip speed ratio and phase shift angle will affect DRWT performance. Realizable k-shear stress transport turbulence models are used to solve the three-dimensional, turbulent, stable, and incompressible flow equations for the performance of dual-rotor wind turbines. Domain-independence tests and an impartial mesh test are run to assess the results and ensure their accuracy. The researcher relies on previous studies while constructing the single rotor wind turbine model. This model uses an S826 airfoil. The front and rear rotors are given streamlined representations using ANSYS, according to the researcher. The independent mesh test indicates that the mesh density has 11.5 million elements. The experiment's results show that the DRWT has a significant effect on the efficiency of wind energy.
Identification of additional body weight QTLs in the Berlin Fat Mouse BFMI861 lines using time series data
Authors: Delpero Manuel , Korkuć Paula , Arends Danny , Brockmann Gudrun A. , Hesse Deike
Published: March 2024

The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and metabolic syndrome. The sublines BFMI861-S1 and BFMI861-S2 differ in weight despite high genetic similarity and a shared obesity-related locus. This study focused on identifying additional body weight quantitative trait loci (QTLs) by analyzing weekly weight measurements in a male population of the advanced intercross line BFMI861-S1 x BFMI861-S2. QTL analysis, utilizing 200 selectively genotyped mice (GigaMUGA) and 197 males genotyped for top SNPs, revealed a genome-wide significant QTL on Chr 15 (68.46 to 81.40 Mb) for body weight between weeks 9 to 20. Notably, this QTL disappeared (weeks 21 to 23) and reappeared (weeks 24 and 25) coinciding with a diet change. Additionally, a significant body weight QTL on Chr 16 (3.89 to 22.79 Mb) was identified from weeks 6 to 25. Candidate genes, including Gpt, Cbx6, Apol6, Apol8, Sun2 (Chr 15) and Trap1, Rrn3, Mapk1 (Chr 16), were prioritized. This study unveiled two additional body weight QTLs, one of which is novel and responsive to diet changes. These findings illuminate genomic regions influencing weight in BFMI and emphasize the utility of time series data in uncovering novel genetic factors.
Impedance-based in vitro eye irritation testing enables the categorization of diluted chemicals
Authors: Weissinger H. , Knetzger N. , Cleve C. , Lotz C.
Published: March 2024

Products containing chemicals with eye irritation potential need to be labeled with the respective hazard symbol. To avoid the testing of numerous dilutions of chemicals on animals, their labeling is directed by a theoretical approach. In this report, a previously described in vitro tissue model of the cornea based on human epithelial cells was used for eye irritation testing of dilutions. As a sensitive and non-destructive method to analyze the barrier function of the epithelium, impedance spectroscopy was applied. Moreover, the morphology and viability of the epithelial models were assessed. We tested four chemicals that, neatly, cause severe damage to the eye: tetrahydrofuran, acetic acid, diethylethanolamine, and benzalkonium chloride. With our test method, we were able to determine the concentrations of the chemicals which are critical for the integrity of the cornea. The threshold was < 0.1% for the most and > 5% for the least toxic substance. The described test system is not only an alternative for animal models but also for the theoretical examination of the hazard potential of diluted chemicals. By using the advantages of tissue engineering and non-destructive analysis tools, we can achieve more precise and safer labeling of the eye irritation potential of products.
Dual ensemble system for polyp segmentation with submodels adaptive selection ensemble
Authors: Xu Cun , Fan Kefeng , Mo Wei , Cao Xuguang , Jiao Kaijie
Published: March 2024

Colonoscopy is one of the main methods to detect colon polyps, and its detection is widely used to prevent and diagnose colon cancer. With the rapid development of computer vision, deep learning-based semantic segmentation methods for colon polyps have been widely researched. However, the accuracy and stability of some methods in colon polyp segmentation tasks show potential for further improvement. In addition, the issue of selecting appropriate sub-models in ensemble learning for the colon polyp segmentation task still needs to be explored. In order to solve the above problems, we first implement the utilization of multi-complementary high-level semantic features through the Multi-Head Control Ensemble. Then, to solve the sub-model selection problem in training, we propose SDBH-PSO Ensemble for sub-model selection and optimization of ensemble weights for different datasets. The experiments were conducted on the public datasets CVC-ClinicDB, Kvasir, CVC-ColonDB, ETIS-LaribPolypDB and PolypGen. The results show that the DET-Former, constructed based on the Multi-Head Control Ensemble and the SDBH-PSO Ensemble, consistently provides improved accuracy across different datasets. Among them, the Multi-Head Control Ensemble demonstrated superior feature fusion capability in the experiments, and the SDBH-PSO Ensemble demonstrated excellent sub-model selection capability. The sub-model selection capabilities of the SDBH-PSO Ensemble will continue to have significant reference value and practical utility as deep learning networks evolve.
A multi-source molecular network representation model for protein–protein interactions prediction
Authors: Zou Hai-Tao , Ji Bo-Ya , Xie Xiao-Lan
Published: March 2024

The prediction of potential protein–protein interactions (PPIs) is a critical step in decoding diseases and understanding cellular mechanisms. Traditional biological experiments have identified plenty of potential PPIs in recent years, but this problem is still far from being solved. Hence, there is urgent to develop computational models with good performance and high efficiency to predict potential PPIs. In this study, we propose a multi-source molecular network representation learning model (called MultiPPIs) to predict potential protein–protein interactions. Specifically, we first extract the protein sequence features according to the physicochemical properties of amino acids by utilizing the auto covariance method. Second, a multi-source association network is constructed by integrating the known associations among miRNAs, proteins, lncRNAs, drugs, and diseases. The graph representation learning method, DeepWalk, is adopted to extract the multisource association information of proteins with other biomolecules. In this way, the known protein–protein interaction pairs can be represented as a concatenation of the protein sequence and the multi-source association features of proteins. Finally, the Random Forest classifier and corresponding optimal parameters are used for training and prediction. In the results, MultiPPIs obtains an average 86.03% prediction accuracy with 82.69% sensitivity at the AUC of 93.03% under five-fold cross-validation. The experimental results indicate that MultiPPIs has a good prediction performance and provides valuable insights into the field of potential protein–protein interactions prediction. MultiPPIs is free available at https://github.com/jiboyalab/multiPPIs.
Proposing TODD-graphene as a novel porous 2D carbon allotrope designed for superior lithium-ion battery efficiency
Authors: Santos E. A. J. , Lima K. A. L. , Ribeiro Junior L. A.
Published: March 2024

The category of 2D carbon allotropes has gained considerable interest due to its outstanding optoelectronic and mechanical characteristics, which are crucial for various device applications, including energy storage. This study uses density functional theory calculations, ab initio molecular dynamics (AIMD), and classical reactive molecular dynamics (MD) simulations to introduce TODD-Graphene, an innovative 2D planar carbon allotrope with a distinctive porous arrangement comprising 3-8-10-12 carbon rings. TODD-G exhibits intrinsic metallic properties with a low formation energy and stability in thermal and mechanical behavior. Calculations indicate a substantial theoretical capacity for adsorbing Li atoms, revealing a low average diffusion barrier of 0.83 eV. The metallic framework boasts excellent conductivity and positioning TODD-G as an active layer for superior lithium-ion battery efficiency. Charge carrier mobility calculations for electrons and holes in TODD-G surpass those of graphene. Classical reactive MD simulation results affirm its structural integrity, maintaining stability without bond reconstructions at 2200 K.
Study on the impact of digital transformation on the innovation potential based on evidence from Chinese listed companies
Authors: Zhao Xu , Chen Qi-an , Yuan Xiaoshu , Yu Yannan , Zhang Haitao
Published: March 2024

Digital transformation has emerged as a powerful force in reshaping the business landscape and enabling organizations to enhance their capabilities. One critical aspect of this change is how it impacts an enterprise’s innovation ability. To explore this question, we select data regarding China’s A-share listed enterprises from 2007 to 2021 as the research sample. We employ crawler technology to gather keywords related to “digital transformation” from annual reports, portraying detailed journeys of enterprises’ digital transformation. Through descriptive statistics and multiple covariance tests, a linear relationship is established between digital transformation and innovation ability. Benchmark regression is conducted and a robustness test is utilized to determine the robustness of the benchmark regression. The mechanism, heterogeneity, and moderating effects of this study are also tested. The results reveal that digital transformation makes a significant positive contribution to the innovation capability of enterprises. Meanwhile, among different types of enterprises, the impact of digital transformation on enterprise innovation capability shows heterogeneity. In terms of the impact mechanism, digital transformation can enhance the innovation output of enterprises by reducing the agency cost and improving the risk-taking level of enterprises, so as to further improve the innovation capability of enterprises. The research results of this paper provide essential theoretical support for the digital transformation of enterprises and the government’s formulation of enterprises’ digitalization strategies. More profoundly, it provides significant reference for how to further promote the digital transformation of Chinese enterprises.
Fruit encasing preserves the dispersal potential and viability of stranded Posidonia oceanica seeds
Authors: Sutera Alberto , Bonaviri Chiara , Spinelli Patrizia , Carimi Francesco , De Michele Roberto
Published: March 2024

Posidonia oceanica meadows are the most productive coastal ecosystem in the Mediterranean. Posidonia oceanica seeds are enclosed in buoyant fleshy fruits that allow dispersal. Many fruits eventually strand on beaches, imposing a remarkable energy cost for the plant. This study aims to assess whether stranded seeds retain functional reproductive potential under a variety of environmental conditions. First, we measured the possibility that seeds could be returned to the sea, by tagging fruits and seeds. Second, we quantified the effect of air, sun and heat exposure on the viability and fitness of stranded fruits and naked seeds. The results showed that on average more than half of fruits and seeds are returned to the sea after stranding events and that fruits significantly protect from desiccation and loss of viability. Furthermore, in fruits exposed to the sun and in naked seeds, seedlings development was slower. This study indicates that a significant portion of stranded P. oceanica fruits have a second chance to recruit and develop into young seedlings, relieving the paradox of large energy investment in seed production and apparent low recruitment rate. Additionally, we provide practical indications for seed collection aimed at maximizing seedling production, useful in meadow restoration campaigns.