bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent progress on heteroepitaxial growth of single crystal diamond films
Authors: Uwihoreye Vedaste , Hu Yushuo , Cao Guangyu , Zhang Xing , Oropeza Freddy E. , Zhang Kelvin H. L. 
Published: November 2024

AbstractDiamond is an ultimate semiconductor with exceptional physical and chemical properties, such as an ultra‐wide bandgap, excellent carrier mobility, extreme thermal conductivity, and stability, making it highly desirable for various applications including power electronics, sensors, and optoelectronic devices. However, the challenge lies in growing the large‐size and high‐quality single‐crystal diamond films, which are crucial for realizing the full potential of this wonder material. Heteroepitaxial growth has emerged as a promising approach to achieve single‐crystal diamond wafers with large sizes of up to 3 inches and controlled electrical properties. This review provides an overview of the advancements in diamond heteroepitaxy using microwave plasma‐assisted chemical vapor deposition, including the mechanism of heteroepitaxial growth, selection of substrates, film optimization, chemistry of defects, and doping. Moreover, recent progress on the device applications and perspectives is also discussed.
Land Use Legacy Landforms at the UNESCO Heritage Site Tarnowskie Góry, Upper Silesia, Poland—Stratigraphy, Soils and Age
Authors: Bonhage Alexander , Raab Thomas , Raab Alexandra , Schneider Anna , Malik Ireneusz , Wistuba Malgorzata , Verschoof‐van der Vaart Wouter 
Published: November 2024

ABSTRACTMetallurgy in Upper Silesia (Poland) has a long tradition of international significance, which was emphasized in 2017 when the historic silver mine in Tarnowskie Góry was inscribed as a UNESCO World Heritage site. The area consists of various anthropogenic landforms, the stratigraphy of which has hardly been studied so far. In this study, we describe five main morphological units: Unit I (RCH) and Unit II (RCH pit), resulting from charcoal production; Unit III (shaft) and Unit IV (shaft heap), resulting from mining; and Unit V (reference forest soil). The first four units are a variation of a Technosol with inherently different properties from the reference forest soil. Unit I exhibits typical properties of a relict charcoal hearth (RCH), whereas Unit II resembles a pit. Unit III consists of a mostly infilled mining shaft remain (MSR), characterized by relocated subsoil. Unit IV consists of material from the adjacent Unit III that has been dumped directly aside. The studied RCH was used no earlier than during the second half of the 17th century, probably between 1725 and 1813. The studied MSR was used most likely between the 3rd and 5th centuries, which is much older than described so far. Together, the units reflect the characteristic heterogeneity of soils in shaft mining and RCH areas.
Patient outcome following selective serotonin reuptake inhibitor prescribing in primary care in Wales (UK)
Authors: Ahmed Shaila , Chaplin Katherine , Young Richard S. , Deslandes Paul N. 
Published: November 2024

AbstractObjectiveThis study investigated prescribing patterns of two cohorts of patients treated with selective serotonin reuptake inhibitors (SSRI) in primary care in Wales (UK), to better understand drivers for increased usage.MethodsThis e‐cohort study included patients receiving a first READ‐coded SSRI prescription in SAIL in either 2005 or 2015. Patients were followed up for 3 years from date of SSRI prescription. Influence of age and other demographic data on prescribing patterns, and details of mental health or medication reviews that took place were identified.ResultsIn total 67,006 patients were included across the two cohorts; 29,534 in 2005, and 37,472 in 2015. Citalopram was the most commonly prescribed SSRI in both cohorts. A READ‐coded diagnosis relating to SSRI treatment could not be identified in 24,797 patients. The percentage of patients continuing treatment for 3 years was 6.9% and 11.3% in 2005 and 2015, respectively. In total, 21,150 (72%) patients in the 2005 cohort and 23,947 (64%) in the 2015 cohort received at least one medication review during follow‐up.ConclusionsThe proportion of patients continuing longer term treatment was small, whilst the number of recorded mental health and medication reviews offers some reassurance that prescribing remained appropriate.
Identification of Vesicle‐Mediated Transport‐Related Genes for Predicting Prognosis, Immunotherapy Response, and Drug Screening in Cervical Cancer
Authors: Lou Shuai , Lv Hongqing , Zhang Lin 
Published: November 2024

ABSTRACTBackgroundCervical cancer is one of the most common malignancies among women. Vesicle‐mediated transport mechanisms significantly influence tumor cell behavior through intercellular material exchange. However, prognostic significance in CC patients remains underexplored.Research Design and MethodsWe identified differentially expressed vesicle‐mediated transport‐related genes from TCGA and GeneCards datasets through differential expression analysis. We constructed a prognostic model using Cox regression and LASSO regression, categorized patients into high‐ and low‐risk groups, and validated the model in the GEO data set. A nomogram integrating clinical features and risk scores demonstrated the model's independent prognostic capability. We analyzed tumor immune cell infiltration, immune checkpoints, and predicted immunotherapy responses in the high‐ and low‐risk groups. Finally, we screened potential drugs for targeting CC and conducted drug‐sensitivity analysis.ResultsWe successfully established a 10‐gene prognostic model based on VMTRGs. The low‐risk group exhibited favorable prognosis, significant immune cell infiltration, and promising immunotherapy response, whereas the high‐risk group showed higher sensitivity to chemotherapeutic agents such as Docetaxel and Paclitaxel. Potential drugs identified for targeting CC patients included Megestrol acetate, Lenvatinib, Adavosertib, and Barasertib.ConclusionsThe VMTRG‐based prognostic model demonstrates reliable clinical prognostic value and enhances understanding of vesicle‐mediated transport mechanisms in CC.
Deep Learning and Handcrafted Features for Thyroid Nodule Classification
Authors: Maarouf Ayoub Abderrazak , meriem Hacini , Hachouf Fella 
Published: November 2024

ABSTRACTIn this research, we present a refined image‐based computer‐aided diagnosis (CAD) system for thyroid cancer detection using ultrasound imagery. This system integrates a specialized convolutional neural network (CNN) architecture designed to address the unique aspects of thyroid image datasets. Additionally, it incorporates a novel statistical model that utilizes a two‐dimensional random coefficient autoregressive (2D‐RCA) method to precisely analyze the textural characteristics of thyroid images, thereby capturing essential texture‐related information. The classification framework relies on a composite feature vector that combines deep learning features from the CNN and handcrafted features from the 2D‐RCA model, processed through a support vector machine (SVM) algorithm. Our evaluation methodology is structured in three phases: initial assessment of the 2D‐RCA features, analysis of the CNN‐derived features, and a final evaluation of their combined effect on classification performance. Comparative analyses with well‐known networks such as VGG16, VGG19, ResNet50, and AlexNet highlight the superior performance of our approach. The outcomes indicate a significant enhancement in diagnostic accuracy, achieving a classification accuracy of 97.2%, a sensitivity of 84.42%, and a specificity of 95.23%. These results not only demonstrate a notable advancement in the classification of thyroid nodules but also establish a new standard in the efficiency of CAD systems.
DC24: A new density coherence functional for multiconfiguration density‐coherence functional theory
Authors: Zhang Dayou , Shu Yinan , Truhlar Donald G. 
Published: November 2024

AbstractIn this study, we explored several alternative functional forms to construct more accurate and more physical density coherence (DC) functionals for multiconfiguration density‐coherence functional theory. Each functional is parameterized against the same database as used in our previous work. The best DC functional, which is called DC24, has a more physical interpretation, and—as a side benefit—it also has a mean unsigned error of 1.73 kcal/mol, which is a 9% improvement as compared to the previous functional. The article also contains a new definition of the unpaired electron density, which may be useful in other contexts as well.
Time perception and delay discounting in the FMR1 knockout rat
Authors: Fox Adam E. , Cooper Abbie R. , Pape Amelia L. , Tobias‐Wallingford Hannah M. , DeCoteau William E. 
Published: November 2024

AbstractThere is substantial evidence for timing (time perception) abnormalities related to developmental disabilities, particularly autism spectrum disorder. These findings have been reported in humans and nonhuman preclinical models. Our research objective was to extend that work to a genetic knockout (KO) model of fragile X/developmental disability, the FMR1 KO rat. We also sought to test delay discounting in the model and assess potential relations between timing and choice behavior. Consistent with previous human and nonhuman work, we found reduced timing precision in the FMR1 KO rats. We also discovered significantly increased smaller, sooner reward choice in the FMR1 KO rats. Performance on the timing task appeared to be unrelated to performance on the choice task for both model and control rats. These results add to what has become increasingly clear: timing is disrupted in humans diagnosed with developmental disabilities and in nonhuman models designed to model developmental disabilities. Our findings are consistent with those of previous work and the first to our knowledge to show such effects in the FMR1 KO rat. We discuss the potential clinical implications and future directions surrounding potential “timing interventions” for individuals diagnosed with developmental disabilities.
A Stepwise‐Clustered Precipitation Downscaling Method for Ensemble Climatic Projections in the Mediterranean Region
Authors: Wang Siyu , Huang Guohe , Zhang Chong , Lu Chen 
Published: November 2024

ABSTRACTPrecipitation changes dynamically in the Mediterranean region. Therefore, the projection of future precipitation and its historical distribution mechanism is essential for climate mitigation and adaptation. In this study, a stepwise clustered precipitation downscaling method (SCPD) was developed and adopted in the Mediterranean region to reveal the inherent variation rules and trends over the future 100 years under two SSP scenarios. A cutting and merging multivariate process is introduced to build a cluster tree for supporting further downscaling and projecting steps. The ensemble average from the global climate model (GCM) dataset is used for precipitation projections. The precipitation performance of SCPD, evaluated by R
2, is fairly decent. The precipitation projections vary with the original rainfall patterns over the gauge stations. Dry places tend to become comparably drier in the future. Precipitation in the northern Mediterranean region shows a drier winter–spring and wetter summer–autumn. Opposite trends emerged in the southern part, with increasing winter precipitation and decreasing summer rainfall. The rising carbon dioxide concentration will further intensify the decrease in rainfall. However, the centres of these two EOFs are not identical. The contributions of NAO (positive) and Niño 3.4 (negative) to PC1 are relatively high. Accordingly, the strongest positive correlation with PC2 is SCAND, as well as negative correlations with AO, NAO and EAWR. Positive anomaly precipitation is attributed to PC1, whereas PC2 is responsible for most of the negative variance precipitation.
Assessment of Basin‐Scale Concurrent Dry and Wet Extreme Dynamics Under Multimodel CORDEX Climate Scenarios
Authors: Swain Sushree Swagatika , Mishra Ashok , Chatterjee Chandranath 
Published: November 2024

ABSTRACTThe impact of extreme events in risk analysis depends on factors such as magnitude, duration, timing and whether the system recovers fully before the next event occurs. While previous studies have primarily examined the drivers and characteristics of individual extremes, less focus has been given to the concurrent or compounding nature of extremes across adjacent seasons. Thus, understanding the dynamics of such compound extremes, particularly dryness and wetness, is crucial. To address these concerns, a Multi Scalar Drought Index (MSDI) is formulated using precipitation and temperature data from three river basins (Brahmani, Baitarani and Cauvery) of eastern and southern India. The combinations of dryness and wetness, such as Dry‐Dry, Dry‐Wet, Wet‐Dry and Wet‐Wet, between consecutive seasons are analysed across four seasons (summer, rainy, autumn and winter). The prolonged dryness/wetness along with dry/wet year are evaluated from baseline (1979–2018) to projected COrdinated Regional Climate Downscaling Experiment (CORDEX) future period (2020–2099). The spatio‐temporal variations in intra‐annual dry‐wet extremes are identified using the Mann–Kendall test. The results suggest that the eastern Indian river basins, particularly the Brahmani and Baitarani basins, experience more frequent occurrences of compounding dryness‐wetness compared to Cauvery river which is a southern Indian basin. Future scenarios indicate a trend towards dryness during the monsoon season in Brahmani and Baitarani basins, with frequent wet extremes in late autumn and winter. Abrupt transitions between dryness and wetness are prevalent during the Rainy‐Autumn and Autumn‐Winter seasons in Brahmani and Baitarani basins. The increased frequency of compound dry‐wet extremes poses significant socio‐economic risks, including reduced agricultural productivity, water management challenges and heightened vulnerability of local livelihoods dependent on consistent water availability. The results of this study provide a scientific reference for sustainable agriculture and water resource management to predict future seasonal dry and wet alternations and develop effective mitigation strategies.
Extracellular vesicles from cartilage progenitors stimulate type II collagen expression and wound healing in meniscal cells
Authors: Betensky Daniel J. , Chen Maxwell D. , Trivedi Jay , Desai Salomi , Twomey‐Kozak John , Wen Sicheng , Jayasuriya Chathuraka T. 
Published: November 2024

AbstractKnee meniscus tearing is a common orthopaedic injury that can heal poorly if left untreated, increasing the risk of post‐traumatic Osteoarthritis. Intraarticular injection of human cartilage‐derived progenitor cells (CPCs) has been shown to promote meniscus healing after injury. However, the mechanism by which CPCs stimulated this effect was unclear. The purpose of this study was to determine the paracrine effects that CPC‐derived extracellular vesicles (EVs) have on native meniscal cells during healing. EVs from human CPCs and marrow‐derived stromal cells were isolated via ultracentrifugation. EVs produced by each cell type were quantified, and their sizes were determined via NanoSight. EV protein expression was characterized via western blot. Meniscal fibrochondrocyte cellular metabolic activity (as an indicator of cell viability and proliferation) following treatment with EVs, was quantified using MTT and ATP assays. A 2D wound healing assay was used to determine the effects of treating inner meniscal fibrochondrocytes with EVs in a dose‐dependent manner. Gene expression analysis for chondrogenesis genes was performed via RT‐qPCR on inner meniscal fibrochondrocytes following treatment with EVs. Our results showed that CPCs produced a wide size range of EVs expressing CD9, CD81, and HSP70. Treatment of inner meniscal fibrochondrocytes with CPC‐EVs improved 2D wound healing, in comparison to EVs isolated from marrow‐derived stromal cell controls. CPC‐EV treatment increased Type II Collagen mRNA expression in inner meniscal fibrochondrocytes. These findings demonstrate that CPC‐EVs stimulate chondrogenic matrix production and wound healing in meniscal cells at the optimal dose of 1.0 × 107 particles/mL, significantly outperforming the effects of marrow stromal cell‐derived EVs.
Polyamino Acid Based Zwitterionic Coating can Inhibit Coagulation and Inflammation Through Anti‐Fouling and Restoring Microenvironment
Authors: Xiang Zehong , Chen Honghong , Wu Feng , Pan Haobo 
Published: November 2024

AbstractProtein adhesion and thrombosis formation caused by limited surface properties pose great challenges to biomedical implants. Although various hydrophilic coating or drug release coatings are reported, the single coating cannot cope with cases under the condition of complex physiological environment, which causes the coating effect is limited. In this study, a polyamino acid‐derived zwitterionic coating is constructed to eliminate reactive oxygen species (ROS) in the microenvironment. It is demonstrated that the coating has excellent hydrophilicity, stability, and lubricity, and can obviously prevent protein adhesion. At the same time, the coating can eliminate hydrogen peroxide and maintain the stability of the microenvironment. The in vivo and in vitro experiments show that the coating has good biocompatibility, and inhibits thrombus. Amino acid zwitterion coating prevents protein deposition, alleviates the inflammatory process, inhibit of thrombosis, reduces the risk of implantable medical devices, and prolongs their service time. Hence, the work paves a new way to develop amino acid based zwitterionic polymer coating that can reduce the implant complications.
The Mechanism of TRIM21 Inhibiting the Invasion and Migration of ccRCC by Stabilizing ASS1
Authors: Yang Zhe , Cai Jihao , Li Jingjing , Liu Xiangjie , Liu Wenjing , Cui Kun , Bai Ziyuan , Dong Yurong , Peng Dongmei , Duan Qiuxin , Shahzad Asif , Zhang Qiao 
Published: November 2024

ABSTRACTClear cell renal cell carcinoma (ccRCC) is characterized by its aggressive invasion and metastasis, presenting significant clinical challenges. Gaining insights into the molecular mechanisms underlying its progression is crucial for the development of effective therapeutic strategies. Addressing a critical knowledge gap in understanding ccRCC tumorigenesis, this study aims to elucidate the expression patterns of TRIM21 in ccRCC, unravel its impact on ccRCC patient prognosis, and investigate the regulatory role of TRIM21 in ASS1 expression and urea cycle dysregulation within the context of ccRCC. The results demonstrate that TRIM21 is downregulated in ccRCC, and low expression of TRIM21 predicts an unfavorable prognosis for ccRCC patients. Furthermore, the upregulation of TRIM21 can inhibit the migration and invasion of ccRCC cells by regulating the ubiquitination modification of ASS1. This not only expands the functional role of TRIM21 in ccRCC tumorigenesis but also demonstrates its ability to reverse urea cycle dysregulation through stabilizing ASS1 expression. Specifically, abnormal downregulation of TRIM21 in ccRCC reduces K63 ubiquitination modification of ASS1, leading to decreased stability of the ASS1 protein, aggravated urea cycle dysregulation, and facilitated migration and invasion of ccRCC cells. Additionally, reduction in ASS1 reverses the depressed migration and invasion caused by overexpression of TRIM21 in ccRCC cells. In summary, our findings contribute to a deeper understanding of the functional role played by TRIM21 in ccRCC progression, pinpoint a unique and novel regulatory mechanism involving ectopic downregulation‐mediated ASS1 ubiquitination modification and urea cycle dysfunction during ccRCC progression, and provide fresh insights for further investigation into the pathogenesis and metabolic reprogramming associated with ccRCC.
Differential Game Analysis of Carbon Emission Reduction Effect and Price Strategy Considering Government Intervention and Manufacturer Competition
Authors: Sun Hongxia , Liu Jinzhou , Zhang Linlin 
Published: November 2024

ABSTRACTGovernments and enterprises are paying more and more attention to carbon emissions. Considering the dynamic of carbon emissions reduction (CER) and the government intervention, this study discusses the optimal CER effort level, price, and government intervention intensity in a two‐echelon supply chain consisting of a government and two manufacturers. The two manufacturers have two competitive behaviors: Cournot and Stackelberg. Two differential game models are constructed for the two different behaviors, and the optimal decisions under the two models are obtained. The comparisons of these optimal solutions are analyzed, and the influence of some parameters on the optimal solution in the two models is investigated under two scenarios. Furthermore, the optimal government intervention intensity is obtained with the goal of maximizing government utility. The results show that the Stackelberg game allows manufacturers to achieve higher profits and CER but is disadvantageous to consumers, and the manufacturer as the leader has a first‐mover advantage. Fierce market competition leads to greater CER and profits, but higher prices reduce consumer surplus. Larger penalties can promote enterprises to reduce carbon emissions when carbon emissions are large. Compared with the Cournot behavior game, the Stackelberg allows manufacturers to obtain higher profits and CER, but the prices are higher that are detrimental for consumers. The fierce market competition is good for manufacturers, the environment, and the society, but it reduces the consumer surplus. The low CER efficiency causes high costs and reduces the manufacturer's motivation to CER, which harm the environment and reduce profits. The government intervention is negatively correlated with the intensity of market competition and the sensitivity of manufacturers to policies.
Indigenous Technical Knowledge and Its Potential Application to Uganda's Pig Sub‐Sector
Authors: Kasima Junior Senyonga , Mugonola Basil , Muyinza Harriet , Kizza‐Nkambwe Sarah , Beyihayo Geoffrey Akiiki , Kidega Kenneth , Nokrach James , Mpewo Maxmillan , Kisaame Marx , Ndyomugyenyi Elly Kurobuza 
Published: November 2024

ABSTRACTUganda's pork consumption is speculated to exceed any other livestock meat consumption by 2050. However, the current trend in pig production may not meet the demand due to pig production constraints such as recurrent disease incidences and high feeding costs. The proposed modern practices are not cost‐effective, especially for resource‐constrained pig farmers. This review, therefore, synthesises previous studies on the practicability of integrating Indigenous Technical Knowledge (ITK) in pig production to mitigate the prevailing pig production challenges in Uganda. By employing ITK, smallholder farmers have realised that indigenous pig breeds are disease‐resistant and suit the prevailing harsh tropical conditions. In addition, affordable plant‐based concoctions have been developed to cure diseases in pigs. For example, Centella asiatica has been identified as a potential purgative for diarrhoeal infections. Integrating pigs in cropping systems has also been adopted as a low‐cost alternative to effectively feed pigs for optimal performance. Fortunately, most of the ITK options for solving pig production challenges are feasible in Uganda. Thus, ITK should be embedded in the country's extension system to increase smallholder farmers' awareness about its potential of improving pig production. An ITK‐modern technology integration would probably meet the acceptance and be suitable for commercial pig producers.