bluuebunny/crossref_metadata_2025 huggingface dataset:
Agreement of point of care ultrasound and final clinical diagnosis in patients with acute heart failure, acute coronary syndrome, and shock: POCUS not missing the target
Authors: Núñez-Ramos José Atilio , Duarte-Misol Dagoberto , Petro María Andrea Burgos , Pérez Keren Jemima Sarmiento , Echeverry Vanessa Paola Gutiérrez , Malagón Sergio Velasco
Published: June 2024

Point-of-care ultrasound (POCUS) is an important tool for clinical diagnosis and decision-making in critical and non-critical scenarios. Dyspnea, chest pain, and shock are conditions susceptible to evaluation with ultrasound considering diagnostic accuracy and clinical impact already proven. There is scarce evidence in diagnosis agreement using ultrasound as an extension of physical examination. We aimed to evaluate ED patients in whom POCUS was performed, to analyze agreement between clinical initial diagnosis using ultrasound images and final diagnosis. Furthermore, we analyze failed diagnosis, inconclusive POCUS exams, and discuss details. A cross-sectional analytical study was conducted on adults who visited the emergency department with any of these three chief complaints: dyspnea, chest pain, and shock. All were evaluated with ultrasound at admission. Agreement between initial diagnosis using POCUS and final definite diagnosis was calculated. Failed diagnosis and inconclusive exams were analyzed. A total of 209 patients were analyzed. Populations: mostly males, mean age 64 years old, hypertensive. Agreement on patients with dyspnea and suspicion of acute decompensated heart failure was 0.98; agreement on chest pain suspicion of non-ST acute coronary syndrome was 0.96; agreement on type of shock was 0.90. Among the population, 12 patients had an inconclusive POCUS exam, and 16 patients had a failed diagnosis. The use of POCUS in the emergency department shows almost perfect agreement when compared with the final diagnosis in individuals experiencing acutely decompensated heart failure, acute coronary syndrome, and shock. Prospective studies are needed to evaluate the impact of this tool on mortality and prognosis when there are diagnostic errors.
The AI Act, gender equality and non-discrimination: what role for the AI office?
Authors: Lütz Fabian
Published: June 2024

This article assesses whether the Artificial Intelligence Act sufficiently addresses issues of gender equality and non-discrimination law. To this end, the substantive provisions of the AI Act are analysed through the lens of gender equality and non-discrimination law, highlighting the proposed tools of fundamental rights impact assessments and bias audits to reduce gender biases and discriminatory risk. Furthermore, the role of the AI Office and its cooperation with national, European, and international bodies for gender equality enforcement are discussed and positioned within the global landscape of AI regulation.
Velocity-Vorticity Geometric Constraints for the Energy Conservation of 3D Ideal Incompressible Fluids
Authors: Berselli Luigi C. , Sannipoli Rossano
Published: June 2024

In this paper we consider the 3D Euler equations and we first prove a criterion for energy conservation for weak solutions, where the velocity satisfies additional assumptions in fractional Sobolev spaces with respect to the space variables, balanced by proper integrability with respect to time. Next, we apply the criterion to study the energy conservation of solution of the Beltrami type, carefully applying properties of products in (fractional and possibly negative) Sobolev spaces and employing a suitable bootstrap argument.
A Lactobacillus Combination Ameliorates Lung Inflammation in an Elastase/LPS—induced Mouse Model of Chronic Obstructive Pulmonary Disease
Authors: Shen Huan-Ting , Fang Yi-Ting , Tsai Wan-Hua , Chou Chia-Hsuan , Huang Ming-Shyan , Yeh Yao-Tsung , Wu Jiun-Ting , Huang Cheng-Hsieh , Wang Bing-Yen , Chang Wen-Wei
Published: June 2024

Chronic obstructive pulmonary disease (COPD) is the world's leading lung disease and lacks effective and specific clinical strategies. Probiotics are increasingly used to support the improvement of the course of inflammatory diseases. In this study, we evaluated the potential of a lactic acid bacteria (LAB) combination containing Limosilactobacillus reuteri GMNL-89 and Lacticaseibacillus paracasei GMNL-133 to decrease lung inflammation and emphysema in a COPD mouse model. This model was induced by intranasal stimulation with elastase and LPS for 4 weeks, followed by 2 weeks of oral LAB administration. The results showed that the LAB combination decreased lung emphysema and reduced inflammatory cytokines (IL-1β, IL-6, TNF-α) in the lung tissue of COPD mice. Microbiome analysis revealed that Bifidobacterium and Akkermansia muciniphila, reduced in the gut of COPD mice, could be restored after LAB treatment. Microbial α-diversity in the lungs decreased in COPD mice but was reversed after LAB administration, which also increased the relative abundance of Candidatus arthromitus in the gut and decreased Burkholderia in the lungs. Furthermore, LAB-treated COPD mice exhibited increased levels of short-chain fatty acids, specifically acetic acid and propionic acid, in the cecum. Additionally, pulmonary emphysema and inflammation negatively correlated with C. arthromitus and Adlercreutzia levels. In conclusion, the combination of L. reuteri GMNL-89 and L. paracasei GMNL-133 demonstrates beneficial effects on pulmonary emphysema and inflammation in experimental COPD mice, correlating with changes in gut and lung microbiota, and providing a potential strategy for future adjuvant therapy.
Study on automatic lithology identification based on convolutional neural network and deep transfer learning
Authors: Li Shiliang , Dong Yuelong , Zhang Zhanrong , Lin Chengyuan , Liu Huaji , Wang Yafei , Bian Youyan , Xiong Feng , Zhang Guohua
Published: June 2024

Automatic and fast rock classification identification is an important part of geotechnical intelligent survey system. Image based supervised deep learning analysis, especially for convolutional neural networks (CNN), has potential in optimizing lithologic classification and interpretation using borehole core images. However, the accuracy and efficiency of lithology identification models are low at present. In this work, a systematic and enormous rock data framework based on the geological rock classification system is firstly established to provide rock learning datasets. The dataset is composed of approximately 150,000 images of rock samples, which covers igneous rocks, sedimentary rocks, and metamorphic rocks. Secondly, based on CNN-deep transfer learning algorithm, an end-to-end, image-to-label rock lithology identification is established. Finally, the generalization of the proposed model and the field drilling core verification test show that the constructed intelligent rock recognition model has an ability to identify rocks quickly and accurately, and the recognition accuracy of 12 kinds of common engineering rocks is more than 95%. The proposed rock intelligent classification model provides a convenient and fast tool for field geologists and scientific researchers.
Improving credit risk assessment in P2P lending with explainable machine learning survival analysis
Authors: Bone-Winkel Gero Friedrich , Reichenbach Felix
Published: June 2024

Recent research using explainable machine learning survival analysis demonstrated its ability to identify new risk factors in the medical field. In this study, we adapted this methodology to credit risk assessment. We used a comprehensive dataset from the Estonian P2P lending platform Bondora, consisting of over 350,000 loans and 112 features with a loan volume of 915 million euros. First, we applied classical (linear) and machine learning (extreme gradient-boosted) Cox models to estimate the risk of these loans and then risk-rated them using risk stratification. For each rating category we calculated default rates, rates of return, and plotted Kaplan–Meier curves. These performance criteria revealed that the boosted Cox model outperformed both the classical Cox model and the platform’s rating. For instance, the boosted model’s highest rating category had an annual excess return of 18% and a lower default rate compared to the platform’s best rating. Second, we explained the machine learning model’s output using Shapley Additive Explanations. This analysis revealed novel nonlinear relationships (e.g., higher risk for borrowers over age 55) and interaction effects (e.g., between age and housing situation) that provide promising avenues for future research. The machine-learning model also found feature contributions aligning with existing research, such as lower default risk associated with older borrowers, females, individuals with mortgages, or those with higher education. Overall, our results reveal that explainable machine learning survival analysis excels at risk rating, profit scoring, and risk factor analysis, facilitating more precise and transparent credit risk assessments.
Functional biochar as sustainable precursors to boost the anaerobic digestion of waste activated sludge from a circular economy perspective: a review
Authors: Chen Bi , Zeng Hong , Yang Fan , Yang Yafei , Qiao Zhi , Zhao Xiaoli , Wang Li , Wu Fengchang
Published: June 2024

Waste activated sludge (WAS) is attracting attention for its energy and resource potential. Anaerobic digestion (AD) can be used to efficiently recover energy resources and stabilize pollutants in WAS, with biochar emerging as an ideal additive to boost this process. However, the low abundance of surface functional groups and small pore structure of raw biochar may limit its performance in the AD of WAS. These limitations can be overcome by using functional biochar. In this review, the preparation and modification methods for functional biochar and its role in the AD of WAS are systematically summarized and discussed. Notably, the role of functional biochar in electron transfer, buffering effects, microbial immobilization, alleviation of inhibitory effects, and functional microbial modulation are analyzed. Additionally, the impacts of biochar on digestate utilization, pollutant removal, and carbon fixation are discussed. Special attention is given to functional biochar for its ability to promote circular economy and carbon neutrality. Finally, future perspectives on the use of functional biochar in the AD of WAS are presented. The aim of this review is to provide insights into the application of functional biochar in the AD of WAS from the perspective of performance improvement, resource utilization, and circular economy.

Graphical Abstract
A Novel Method to Train Classification Models for Structure Detection in In Situ Spacecraft Data
Authors: Bergstedt K. , Ji H.
Published: June 2024

We present a method for creating spacecraft‐like data which can be used to train Machine Learning (ML) models to detect and classify structures in in situ spacecraft data. First, we use the Grad‐Shafranov equation to numerically solve for several magnetohydrostatic equilibria which are variations on a known analytic equilibrium. These equilibria are then used as the initial conditions for Particle‐In‐Cell simulations in which the structures of interest are observed and labeled. We then take one‐dimensional slices through the simulations to replicate what a spacecraft collecting data from the simulation would observe. This sliced data then can be used as training data for the initial training of ML models intended for use on spacecraft data. We demonstrate the method applied to the problem of detecting small‐scale plasmoids in the magnetotail, which is important for understanding complex magnetotail reconnection dynamics. The simple 1D classifier we train is able to detect more than 70% of the plasmoid points in the data set but also produces a large number of false positives. Our further work on this example problem is detailed, and further potential uses of the method are discussed.
Transition between cardiometabolic conditions and body weight among women: which paths increase the risk of diabetes and cardiovascular diseases?
Authors: Baneshi Mohammad R. , Dobson Annette , Mishra Gita D.
Published: June 2024

Previous studies investigated the association of body weight and hypertension with risk of incident cardiometabolic multimorbidity. Our aim was to estimate the risk of diabetes and cardiovascular disease later in life for subjects with different progression patterns of overweight, obesity, and hypertension in mid-life. This was a prospective cohort study in which data from 12,784 participants in the Australian Longitudinal Study on Women’s Health were used. Multistate model was used to study the progression pattern of overweight, obesity, hypertension, diabetes, and cardiovascular disease over the life course. The cumulative incidence of diabetes and cardiovascular disease up to the age of 73 was estimated for women with different patterns of other conditions. The six most common paths and corresponding cumulative incidences for diabetes were overweight 5.1%, obesity 11.5%, hypertension 6.9%, progression from overweight to obesity 8.2%, overweight and hypertension 12.1%, and obesity and hypertension 36.8%. For women with diabetes and other conditions, the cumulative incidence of cardiovascular disease (heart disease or stroke) as the next immediate condition was 22.4%. The corresponding figure for women who only had a report of diabetes but did not have high body weight or hypertension was 8.3%. The higher risk of transition from healthy state to a cardiometabolic condition was associated with low education, income stress, smoking, not drinking alcohol (compared to low drinkers), physical inactivity, and high perceived stress. Women with obesity and hypertension in middle-age had a substantially higher risk of developing diabetes and cardiovascular disease than women without these potentially preventable conditions.
Genomic tailoring of autogenous poultry vaccines to reduce Campylobacter from farm to fork
Authors: Calland Jessica K. , Pesonen Maiju E. , Mehat Jai , Pascoe Ben , Haydon David J. , Lourenco Jose , Lukasiewicz Barbara , Mourkas Evangelos , Hitchings Matthew D. , La Ragione Roberto M. , Hammond Philip , Wallis Timothy S. , Corander Jukka , Sheppard Samuel K.
Published: June 2024

Campylobacter is a leading cause of food-borne gastroenteritis worldwide, linked to the consumption of contaminated poultry meat. Targeting this pathogen at source, vaccines for poultry can provide short-term caecal reductions in Campylobacter numbers in the chicken intestine. However, this approach is unlikely to reduce Campylobacter in the food chain or human incidence. This is likely as vaccines typically target only a subset of the high genomic strain diversity circulating among chicken flocks, and rapid evolution diminishes vaccine efficacy over time. To address this, we used a genomic approach to develop a whole-cell autogenous vaccine targeting isolates harbouring genes linked to survival outside of the host. We hyper-immunised a whole major UK breeder farm to passively target offspring colonisation using maternally-derived antibody. Monitoring progeny, broiler flocks revealed a near-complete shift in the post-vaccination Campylobacter population with an ~50% reduction in isolates harbouring extra-intestinal survival genes and a significant reduction of Campylobacter cells surviving on the surface of meat. Based on these findings, we developed a logistic regression model that predicted that vaccine efficacy could be extended to target 65% of a population of clinically relevant strains. Immuno-manipulation of poultry microbiomes towards less harmful commensal isolates by competitive exclusion, has major potential for reducing pathogens in the food production chain.
Hybrid working from home improves retention without damaging performance
Authors: Bloom Nicholas , Han Ruobing , Liang James
Published: June 2024

Working from home has become standard for employees with a university degree. The most common scheme, which has been adopted by around 100 million employees in Europe and North America, is a hybrid schedule, in which individuals spend a mix of days at home and at work each week1,2. However, the effects of hybrid working on employees and firms have been debated, and some executives argue that it damages productivity, innovation and career development3–5. Here we ran a six-month randomized control trial investigating the effects of hybrid working from home on 1,612 employees in a Chinese technology company in 2021–2022. We found that hybrid working improved job satisfaction and reduced quit rates by one-third. The reduction in quit rates was significant for non-managers, female employees and those with long commutes. Null equivalence tests showed that hybrid working did not affect performance grades over the next two years of reviews. We found no evidence for a difference in promotions over the next two years overall, or for any major employee subgroup. Finally, null equivalence tests showed that hybrid working had no effect on the lines of code written by computer-engineer employees. We also found that the 395 managers in the experiment revised their surveyed views about the effect of hybrid working on productivity, from a perceived negative effect (−2.6% on average) before the experiment to a perceived positive one (+1.0%) after the experiment. These results indicate that a hybrid schedule with two days a week working from home does not damage performance.
Tunable entangled photon-pair generation in a liquid crystal
Authors: Sultanov Vitaliy , Kavčič Aljaž , Kokkinakis Emmanouil , Sebastián Nerea , Chekhova Maria V. , Humar Matjaž
Published: June 2024

Liquid crystals, with their ability to self-assemble, strong response to an electric field and integrability into complex systems, are key materials in light-beam manipulation1. The recently discovered ferroelectric nematic liquid crystals2,3 also have considerable second-order optical nonlinearity, making them a potential material for nonlinear optics4,5. Their use as sources of quantum light could considerably extend the boundaries of photonic quantum technologies6. However, spontaneous parametric down-conversion, the basic source of entangled photons7, heralded single photons8 and squeezed light9, has so far not been observed in liquid crystals—or in any liquids or organic materials. Here we implement spontaneous parametric down-conversion in a ferroelectric nematic liquid crystal and demonstrate electric-field tunable broadband generation of entangled photons, with an efficiency comparable to that of the best nonlinear crystals. The emission rate and polarization state of photon pairs is markedly varied by applying a few volts or twisting the molecular orientation along the sample. A liquid-crystal source enables a special type of quasi-phase matching10, which is based on the molecular twist structure and is therefore reconfigurable for the desired spectral and polarization properties of photon pairs. Such sources promise to outperform standard nonlinear optical materials in terms of functionality, brightness and the tunability of the generated quantum state. The concepts developed here can be extended to complex topological structures, macroscopic devices and multi-pixel tunable quantum light sources.
Broadband PM6Y6 coreshell hybrid composites for photocurrent improvement and light trapping
Authors: Sanad S. , Ghanim AbdelRahman M. , Gad Nasr , El-Aasser M. , Yahia Ashraf , Swillam Mohamed A.
Published: June 2024

Our research focuses on enhancing the broadband absorption capability of organic solar cells (OSCs) by integrating plasmonic nanostructures made of Titanium nitride (TiN). Traditional OSCs face limitations in absorption efficiency due to their thickness, but incorporating plasmonic nanostructures can extend the path length of light within the active material, thereby improving optical efficiency. In our study, we explore the use of refractory plasmonics, a novel type of nanostructure, with TiN as an example of a refractory metal. TiN offers high-quality localized surface plasmon resonance in the visible spectrum and is cost-effective, readily available, and compatible with CMOS technology. We conducted detailed numerical simulations to optimize the design of nanostructured OSCs, considering various shapes and sizes of nanoparticles within the active layer (PM6Y6). Our investigation focused on different TiN plasmonic nanostructures such as nanospheres, nanocubes, and nanocylinders, analyzing their absorption spectra in a polymer environment. We assessed the impact of their incorporation on the absorbed power and short-circuit current (Jsc) of the organic solar cell.
Dominance of Cotton leaf curl Multan virus-Rajasthan strain associated with third epidemic of cotton leaf curl disease in Pakistan
Authors: Mahmood Muhammad Arslan , Ahmed Nasim , Hussain Athar , Naqvi Rubab Zahra , Amin Imran , Mansoor Shahid
Published: June 2024

Cotton (Gossypium hirsutum) is an economically potent crop in many countries including Pakistan, India, and China. For the last three decades, cotton production is under the constant stress of cotton leaf curl disease (CLCuD) caused by begomoviruses/satellites complex that is transmitted through the insect pest, whitefly (Bemisia tabaci). In 2018, we identified a highly recombinant strain; Cotton leaf curl Multan virus-Rajasthan (CLCuMuV-Raj), associated with the Cotton leaf curl Multan betasatellite-Vehari (CLCuMuBVeh). This strain is dominant in cotton-growing hub areas of central Punjab, Pakistan, causing the third epidemic of CLCuD. In the present study, we have explored the CLCuD diversity from central to southern districts of Punjab (Faisalabad, Lodhran, Bahawalpur, Rahimyar Khan) and the major cotton-growing region of Sindh (Tandojam), Pakistan for 2 years (2020–2021). Interestingly, we found same virus (CLCuMuV-Raj) and associated betasatellite (CLCuMuBVeh) strain that was previously reported with the third epidemic in the central Punjab region. Furthermore, we found minor mutations in two genes of CLCuMuV-Raj C4 and C1 in 2020 and 2021 respectively as compared to its isolates in 2018, which exhibited virus evolution. Surprisingly, we did not find these mutations in CLCuMuV-Raj isolates identified from Sindh province. The findings of the current study represent the stability of CLCuMuV-Raj and its spread toward the Sindh province where previously Cotton leaf curl Kokhran virus (CLCuKoV) and Cotton leaf curl Shahdadpur virus (CLCuShV) have been reported. The findings of the current study demand future research on CLCuD complex to explore the possible reasons for prevalence in the field and how the virus-host-vector compatible interaction can be broken to develop resistant cultivars.
An improved deep learning network for image detection and its application in Dendrobii caulis decoction piece
Authors: Chang Yonghu , Zhou Dejin , Tang Yongchuan , Ou Shuiping , Wang Sen
Published: June 2024

In recent years, with the increasing demand for high-quality Dendrobii caulis decoction piece, the identification of D. caulis decoction piece species has become an urgent issue. However, the current methods are primarily designed for professional quality control and supervision. Therefore, ordinary consumers should not rely on these methods to assess the quality of products when making purchases. This research proposes a deep learning network called improved YOLOv5 for detecting different types of D. caulis decoction piece from images. In the main architecture of improved YOLOv5, we have designed the C2S module to replace the C3 module in YOLOv5, thereby enhancing the network’s feature extraction capability for dense and small targets. Additionally, we have introduced the Reparameterized Generalized Feature Pyramid Network (RepGFPN) module and Optimal Transport Assignment (OTA) operator to more effectively integrate the high-dimensional and low-dimensional features of the network. Furthermore, a new large-scale dataset of Dendrobium images has been established. Compared to other models with similar computational complexity, improved YOLOv5 achieves the highest detection accuracy, with an average mAP@.05 of 96.5%. It is computationally equivalent to YOLOv5 but surpasses YOLOv5 by 2 percentage points in terms of accuracy.
Effectiveness of feeding different biochars on growth, digestibility, body composition, hematology and mineral status of the Nile tilapia, Oreochromis niloticus
Authors: Amjad Muhammad , Hussain Syed Makhdoom , Ali Shafaqat , Rizwan Muhammad , Al-Ghanim Khalid A. , Yong Jean Wan Hong
Published: June 2024

Oreochromis niloticus fingerlings (5.15 ± 0.02 g; n = 315) were fed with different types of biochar (BC)-supplemented sunflower meal-based (SFM) diet to investigate the effects of various BC inclusions on their nutritional digestibility, body composition, hematology and mineral status for 60 days. Seven different diets were formulated based on the SFM based diet: one was a control (TD-I, CON) and the other six diets were supplemented with 2% BC derived from different sources. These BCs were derived from the following: cotton stick (CSBC, TD-II), wheat straw (WSBC, TD-III), corn cob (CCBC, TD-IV), house waste (HWBC, TD-V), grass waste (GWBC, TD-VI), and green waste (GwBC, TD-VII) biochar. There were three replicates for each test diet. Each tank had fifteen tilapia fingerlings, and they were fed with 5% of their live wet weight and twice daily. The outcomes showed that the supplementation of CCBC significantly elevated the growth, nutrient absorption, and body composition of the O. niloticus fingerlings (p < 0.05); with concomitant lowering of the quantity of nutrients released into the water bodies whereas HWBC gave negative impacts. The maximal mineral absorption efficiency (Ca, Na, K, Cu, Fe, P, and Zn) was achieved by the supplementation of 2% CCBC. All hematological parameters showed positive improvements (p < 0.05) with CCBC. Interestingly, CCBC significantly improved the growth, digestibility, body composition, hematology, and mineral status of O. niloticus.
Pharmacophore modelling based virtual screening and molecular dynamics identified the novel inhibitors and drug targets against Waddlia chondrophila
Authors: Aslam Sidra , Aljawdah Hossam M. , Murshed Mutee , Serrano Geidy E.
Published: June 2024

Waddlia chondrophila is a possible cause of fetal death in humans. This Chlamydia-related bacterium is an emergent pathogen that causes human miscarriages and ruminant abortions, which results in financial losses. Despite the years of efforts, the underlying mechanism behind the pathogenesis of W. chondrophila is little known which hindered the development of novel treatment options. In the framework of current study, computational approaches were used to identify novel inhibitors (phytocompounds) and drug targets against W. chondrophila. At first, RNA polymerase sigma factor SigA and 3-deoxy-d-manno-octulosonic acid transferase were identified through subtractive proteomics pipeline. Afterwards, extensive docking and simulation analyses were conducted to optimize potentially novel phytocompounds by assessing their binding affinity to target proteins. A 100ns molecular dynamics simulation well complimented the compound's binding affinity and indicated strong stability of predicted compounds at the docked site. The calculation of binding free energies with MMGBSA corroborated the significant binding affinity between phytocompounds and target protein binding sites. The proposed phytocompounds may be a viable treatment option for patients infected with W. chondrophila; however, further research is required to ensure their safety.
RNA-seq-based transcriptome profiling of early fruit development in Chieh-qua and analysis of related transcription factors
Authors: Du Xuan , Liu Na , Lu Panling , Wang Ying , Lu Bo , Tian Shoubo , Zhang Zhaohui
Published: June 2024

Chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How.) fruit development starts post pollination. With the continuous expansion of the fruit, the soluble solid content of the fruit decreases. Because there are no reports on the early development of Chieh-qua fruit, this study compared fruit transcriptomes at 0-, 3-, and 7 day post pollination (dpp). 104,747 unigenes were assembled from clean reads and compared using six public databases for similarity searching. Compared with those of 0 dpp (C), there were differences in the expression of 12,982 and 6541 genes in the fruit tissue at 3 dpp and 7 dpp, respectively. Compared with 3 dpp (B), there were 14,314 differentially expressed genes in the fruit at 7 dpp (A). Based on the analysis of transcription factors, 213 nucleotides in the MYB superfamily were identified; among them, 94 unigenes of the MYB superfamily were differentially expressed at the three stages. In the pairwise comparison of differential expression, eight unigenes (Gene_id: TRINITY_DN32880_c1_g2, TRINITY_DN35142_c2_g2, TRINITY_DN32454_c11_g6, TRINITY_DN34105_c2_g7, TRINITY_DN32758_c3_g3, TRINITY_DN33604_c4_g10, TRINITY_DN34466_c3_g1, TRINITY_DN35924_c3_g2) were homologous to those of MYB59, MYB-GT3b, MYB18, MYB4, MYB108, MYB306, MYB340, and MYB-bHLH13. These unigenes differed significantly among the three stages. Furthermore, MYB59 and MYB18 exhibited higher expression at 7 dpp. MYB4, MYB-GT3b, MYB108, and MYB306 showed the highest expression levels in fruits at 3 dpp. In addition, MYB340 and MYB-bHLH13 showed higher expression levels during the unpollinated stage. MYB59, MYB-GT3b, MYB18, MYB4, MYB108, MYB306, MYB340, and MYB-bHLH13 may play crucial roles in Chieh-qua fruit development, defense, and blossoming. This study provides a basis for further investigation of MYB superfamily genes involved in early fruit expansion in chieh-qua.
Divergence and convergence: a cross-generational study on local food consumption
Authors: Chen Jianhong , Xu Anxin , Tang Decong , Zheng Manhua
Published: June 2024

In the context of the expanding local food market, grasping the evolutionary trajectory of consumer purchasing behavior is crucial for understanding market dynamics. This study adopts a cross-generational perspective to delve into and elucidate the similarities and differences in local food consumption behaviors between Gen Z and Gen Y. Through the analysis of online survey data from 251 individuals of Gen Z and 319 of Gen Y and utilizing the Theory of Planned Behavior as a theoretical framework, and the study identifies eight key variables. The findings reveal that while Gen Z and Gen Y exhibit a range of common characteristics in their choice of local food,including attention to word of mouth, health consciousness, subjective norms, perceived behavioral control, and attitude.there is a significant divergence in their motivating factors for purchasing. Specifically, convenience is the primary driver for Gen Z when selecting local food; conversely, price is the decisive factor in the decision-making process of Gen Y. By unveiling these significant differences and similarities, the research offers significant understanding beneficial to the food sector, particularly in formulating market strategies targeted at different generations.
To explore the prognostic characteristics of colon cancer based on tertiary lymphoid structure-related genes and reveal the characteristics of tumor microenvironment and drug prediction
Authors: Wang Zhanmei , Niu Dongguang
Published: June 2024

In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive system. At present, there is no effective prognostic marker to predict the prognosis of patients. Tertiary lymphoid structure (TLS) affects cancer progression by regulating immune microenvironment. Mining COAD biomarkers based on TLS-related genes helps to improve the prognosis of patients. In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. The mRNA expression data and clinical information of COAD and adjacent tissues were downloaded from the Cancer Genome Atlas database. The differentially expressed TLS-related genes of COAD relative to adjacent tissues were obtained by differential analysis. TLS gene co-expression analysis was used to mine genes highly related to TLS, and the intersection of the two was used to obtain candidate genes. Univariate, LASSO, and multivariate Cox regression analysis were performed on candidate genes to screen prognostic markers to construct a risk assessment model. The differences of immune characteristics were evaluated by ESTIMATE, ssGSEA and CIBERSORT in high and low risk groups of prognostic model. The difference of genomic mutation between groups was evaluated by tumor mutation burden score. Screening small molecule drugs through the GDSC library. Finally, a nomogram was drawn to evaluate the clinical value of the prognostic model. Seven TLS-related genes ADAM8, SLC6A1, PAXX, RIMKLB, PTH1R, CD1B, and MMP10 were screened to construct a prognostic model. Survival analysis showed that patients in the high-risk group had significantly lower overall survival rates. Immune microenvironment analysis showed that patients in the high-risk group had higher immune indicators, indicating higher immunity. The genomic mutation patterns of the high-risk and low-risk groups were significantly different, especially the KRAS mutation frequency was significantly higher in the high-risk group. Drug sensitivity analysis showed that the low-risk group was more sensitive to Erlotinib, Savolitinib and VE _ 822, which may be used as a potential drug for COAD treatment. Finally, the nomogram constructed by pathological features combined with RiskScore can accurately evaluate the prognosis of COAD patients. This study constructed and verified a TLS model that can predict COAD. More importantly, it provides a reference standard for guiding the prognosis and immunotherapy of COAD patients.
LHHW/RSM reaction rate modeling for Co-Mn/SiO2 nanocatalyst in Fishcher-Tropsch synthesis
Authors: Azizi Hamid Reza , Mansouri Mohsen , Farshchi Tabrizi Farshad , Mansouri Ghobad , Setareshenas Naimeh
Published: June 2024

This study aims to assess the kinetics of Fischer–Tropsch (FT) reaction over the cobalt-manganese nanoparticles supported by silica oxide. Nanoparticles were synthesized by the thermal decomposition method using "[Co(NH3)4CO3]MnO4" complex and characterized by XRD, TEM, and BET techniques. The kinetics of the process were evaluated using a combination of Langmuir–Hinshelwood-Hougen-Watson (LHHW) and response surface methodology. Correlation factors of 0.9902 and 0.962 were obtained for the response surface method (RSM) and LHHW, respectively. The two methods were in good agreement, and the results showed that the rate-determining step was the reaction of the adsorbed methylene with the adsorbed hydrogen atom, and only carbon monoxide molecules were the most active species on the catalyst surface. A temperature of 502.53 K and a CO partial pressure of 2.76 bar are proposed as the optimal conditions by RSM analysis. The activation energy of CO consumption reaction was estimated to be 61.06 kJ/mol.
Optimization design of battery bracket for new energy vehicles based on 3D printing technology
Authors: Zhang Guoqing , Li Xueyan , Li Junxin , Zhou Xiaoyu , Zhou Yongsheng
Published: June 2024

Nowadays, what captures consumers' primary attention is how to purchase electric vehicles with long range and desirable price. Lightweight construction stands as one of the most effective approaches for prolonging range and lowering costs. As a consequence, it is particularly imperative to undertake lightweight design optimization for the battery bracket of new energy vehicles by applying 3D printing technology. To actualize this goal, Rhino software was initially employed for 3D modeling to design the battery bracket system for a pure electric vehicle in China. Subsequently, topology optimization design of the battery bracket was carried out by adopting Altair Inspire software. Last but not least, manufacturing and assembly inspection were completed using a 3D printer. The results show that the maximum displacement of the battery lower tray bracket after topology optimization is 3.20 mm, which is slightly higher than before, but still relatively small. The maximum Mises equivalent stress rose to 240.7 MPa post-optimization, but brought about a uniform stress distribution at the bottom of the bracket. In comparison, the minimum factor of safety met design requirements at 1. The mass was lessened to 0.348 kg, representing a 49.2% decrease in comparison with pre-optimization levels. The 3D-printed bracket was fabricated by employing a 3D printer, thereby achieving the aforementioned mass abatement. The battery pack parts exhibited a bright surface with low roughness and no discernible warping or deformation defects. As revealed by the assembly results, the components of the battery pack bracket are tightly coordinated with each other, with no evident assembly conflicts, revealing that the dimensional accuracy and fit of the completed parts meet production requirements. These findings lay solid groundwork for the mass production of high-performance battery pack brackets.
Analytical and experimental analysis of concrete temperature and energy considering open-air environmental variations
Authors: Yang Wen-Jian , Li Peng , Zhuo Li , Pang Ming-Liang , Xie Hong-Qiang , Xiao Ming-Li
Published: June 2024

Longwave radiation is an important open-air environmental factor that can significantly affect the temperature of concrete, but it has often been ignored in the temperature analysis of open-air concrete structures. In this article, an improved analytical model of concrete temperature was proposed by considering solar radiation, thermal convection, thermal conduction and especially longwave radiation. Temperature monitoring of an open-air concrete block was carried out to verify the proposed model and analyze the heat energy characteristics of open-air concrete. As demonstrated by the open-air experiment, under the influence of longwave radiation, the temperature at the top of the concrete block could decrease rapidly at night and even become lower than the minimum temperature at its bottom. Compared with the analytical model that ignores longwave radiation, the improved model that includes it better matches the measured temperature. According to the energy analysis, although solar radiation controls the transient variation in heat energy, the heat exchange caused by longwave radiation were more than that caused by convection on sunlit surfaces, which indicates the importance of considering longwave radiation.
Historical sensible-heat-flux variations key to predicting future hydrologic sensitivity
Authors: Norris Jesse , Thackeray Chad W. , Hall Alex , Madakumbura Gavin D.
Published: June 2024

Under anthropogenic climate change (CC), the global hydrological cycle intensifies at a rate known as hydrologic sensitivity (HS). Global climate models (GCMs) exhibit substantial uncertainty in HS. Past work suggests that another form of HS, derived from internal climate variability (IV), is useful for constraining this uncertainty. However, these two forms of HS are weakly related. Here we show that decomposing HS under both CC and IV, based on the global energy budget, provides insight into the likely range of future HS. We find that sensible heat exchange between the atmosphere and ocean is not accounted for in the atmospheric energy budget under IV, masking the connection between HS under IV and CC. Removing this term, a closer relationship emerges. We use observations in conjunction with this relationship to suggest an upward shift in the likely range of future HS (66% confidence interval: 2.00–2.36 W m−2 K−1).
Dual nature of magnetism driven by momentum dependent f-d Kondo hybridization
Authors: Kang Byungkyun , Lee Yongbin , Ke Liqin , Kim Hyunsoo , Kim Myoung-Hwan , Park Chul Hong
Published: June 2024

The intricate nature of magnetism in uranium-based Kondo lattices is a consequence of correlations between U-5f and conduction electrons. Previously, the source of magnetism has been ascribed to either Mott physics or Ruderman-Kittel-Kasuya-Yosida interaction, both of which are not fully applicable to uranium-based Kondo lattices. Using linearized quasiparticle self-consistent GW plus dynamical mean-field theory, we demonstrate a crossover from incoherent to coherent f-d Kondo cloud in the paramagnetic phase of UTe2, USbTe and USbSe. As the transition occurs, we observe an augmented f-d coherence and Pauli-like magnetic susceptibility, with a substantial frozen magnetic moment of U-5f persisting. We show that momentum dependent f-d hybridization is responsible for the magnetic moments arising from the renormalized f electrons’ van Hove singularity. Our findings provide a perspective to explain the dual nature of magnetism and the long-range magnetic ordering induced by pressure in UTe2.
Association of western US compound hydrometeorological extremes with Madden-Julian oscillation and ENSO interaction
Authors: Wang Jiabao , DeFlorio Michael J. , Gershunov Alexander , Guirguis Kristen , Delle Monache Luca , Ralph F. Martin
Published: June 2024

Extreme weather and climate events can have substantial impacts on society and the environment. Compound extremes (two or more extreme events occurring simultaneously or successively) may exert even larger impacts than individual events. Here we examine physical drivers behind variability in hydrometeorological (precipitation and temperature) compound extremes on subseasonal-to-seasonal timescales. Observational evidence presented here through composite analysis indicates that compound extreme frequency is linked to the Madden-Julian oscillation, a unique type of organized tropical convection varying primarily on subseasonal-to-seasonal timescales. The linkage between Madden-Julian oscillation and compound extremes is largely dependent on ENSO phases, which can be seen through different magnitudes or changes in sign of the canonical relationship conditioned on ENSO states. Similarly, the Madden-Julian oscillation can interrupt the canonical ENSO-compound extreme relationship. Our results suggest a potential route to improve subseasonal-to-seasonal prediction of western US compound extremes by considering the combined effect of both Madden-Julian oscillation and ENSO.
A microfluidic approach to study variations in Chlamydomonas reinhardtii alkaline phosphatase activity in response to phosphate availability
Authors: Rahnama Alireza , Vaithiyanathan Manibarathi , Briceno-Mena Luis , Dugas Travis M. , Yates Kelly L. , Romagnoli Jose A. , Melvin Adam T.
Published: June 2024

The single-cell response of algal cells with regards to alkaline phosphatase activity (APA) is heavily dependent on variations in phosphorus (P) availability.
Synthesis of (1-silyl)allylboronates by KOtBu-catalyzed ring-opening gem-silylborylation of cyclopropenes
Authors: Fujii Ikuya , Hirata Haruka , Moniwa Hirokazu , Shintani Ryo
Published: June 2024

A KOtBu-catalyzed ring-opening gem-silylborylation of cyclopropenes with silylboronates has been developed for the synthesis of (1-silyl)allylboronates, a useful class of compounds in organic synthesis.
Methyl methacrylate-modified polystyrene microspheres: an effective strategy to enhance the fluorescence of Eu-complexes
Authors: Yuan Yuwen , Wang Yunpeng , Awasthi Pragati , Dong Wenkun , Chen Dong , Qiao Xvsheng , Wang Zhiyu , Qian Guodong , Fan Xianping
Published: June 2024

The in vitro detection applications of europium complex-doped microspheres mainly rely on strong fluorescence intensity and a well-defined morphology.
Towards a better understanding of the HO2uptake coefficient to aerosol particles measured during laboratory experiments
Authors: Lakey P. S. J. , Berkemeier T. , Baeza-Romero M. T. , Pöschl U. , Shiraiwa M. , Heard D. E.
Published: June 2024

The first measurements of HO2uptake coefficients (γHO2) onto suspended aerosol particles as a function of temperature are reported in the range 314 K to 263 K.
A novel LIBS method for quantitative and high-throughput analysis of macro- and micronutrients in plants
Authors: Mikkelsted Frederikke Neergaard , Adén Daniel , Nikolajsen Thomas , Laursen Kristian Holst
Published: June 2024

A novel Laser Induced Breakdown Spectroscopy (LIBS) method enables quantitative and high-throughput analysis of macro- and micronutrients in plants.
Discovery of new 1,3-diphenylurea appended aryl pyridine derivatives as apoptosis inducers through c-MET and VEGFR-2 inhibition: design, synthesis, in vivo and in silico studies
Authors: Elsebaie Heba A. , Nafie Mohamed S. , Tawfik Haytham O. , Belal Amany , Ghoneim Mohammed M. , Obaidullah Ahmad J. , Shaaban Salwa , Ayed Abdelmoneim A. , El-Naggar Mohamed , Mehany Ahmed B. M. , Shaldam Moataz A.
Published: June 2024

A new 1,3-diphenylurea appended aryl pyridine derivative was designed, synthesized and characterized as c-MET and VEGFR-2 inhibitors to induce apoptosis against MCF-7 cells.
Improved electrochemical performance of defect-induced supercapacitor electrodes based on MnS-incorporated MnO2 nanorods
Authors: Rahaman Mizanur , Islam Md. Roxy , Islam Muhammad Rakibul
Published: June 2024

In this paper, we report the effect of MnS nanoparticles on the electrochemical performance of 1D-MnO2 stable nanorods for supercapacitor electrodes.
A multidentate copper complex on magnetic biochar nanoparticles as a practical and recoverable nanocatalyst for the selective synthesis of tetrazole derivatives
Authors: Maseer Marwan Majeed , Kikhavani Tavan , Tahmasbi Bahman
Published: June 2024

Waste recycling, novel and easy methods of recycling catalysts, use of green solvents, use of selective catalysts and preventing the production of by-products are the most important principles of green chemistry and modern technology.
Magnetically recyclable adsorption of anionic pollutants from wastewater using 3,5-diaminobenzoic acid-functionalized magnetic iron oxide nanoparticles
Authors: Munsi Md. Abdullah , Rahman Md. Abdur , Islam Md. Muhyminul , Alam Md. Ashraful , Nuri Md. Aksaruzzaman , Mefford O. Thompson , Miah M. A. Jalil , Ahmad Hasan
Published: June 2024

Simple one-step synthesis of magnetic Fe3O4@PABA nanoadsorbents for magnetically recyclable adsorption of anionic azo dye pollutants from wastewater.
Dexamethasone–tamoxifen combination exerts synergistic therapeutic effects in tamoxifen-resistance breast cancer cells
Authors: Gaballah Aliaa I. , Elsherbiny Aliaa A. , Sharaky Marwa , Hamed Najat O. , Raslan Nahed A. , Almilaibary Abdullah , Fayyad Reda Mohamed Abdrabbou , Ousman Mona S. , Hamdan Ahmed M.E. , Fahim Sally A.
Published: June 2024

Tamoxifen (TAM) is a key player in estrogen receptor-positive (ER+) breast cancer (BC); however, ∼30% of patients experience relapse and a lower survival rate due to TAM resistance. TAM resistance was related to the over expression of SOX-2 gene, which is regulated by the E2F3 transcription factor in the Wnt signaling pathway. It was suggested that SOX-2 overexpression was suppressed by dexamethasone (DEX), a glucocorticoid commonly prescribed to BC patients. The aim of the present study is to explore the effect of combining DEX and TAM on the inhibition of TAM-resistant LCC-2 cells (TAMR-1) through modulating the E2F3/SOX-2-mediated Wnt signaling pathway. The effect of the combination therapy on MCF-7 and TAMR-1 cell viability was assessed. Drug interactions were analyzed using CompuSyn and SynergyFinder softwares. Cell cycle distribution, apoptotic protein expression, gene expression levels of SOX-2 and E2F3, and cell migration were also assessed. Combining DEX with TAM led to synergistic inhibition of TAMR-1 cell proliferation and migration, induced apoptosis, reduced SOX-2 and E2F3 expression and was also associated with S and G2-M phase arrest. Therefore, combining DEX with TAM may present an effective therapeutic option to overcome TAM resistance, by targeting the E2F3/SOX-2/Wnt signaling pathway, in addition to its anti-inflammatory effect.