bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multichannel Resonant Acoustic Rheometry System for Rapid and Efficient Quantification of Human Plasma Coagulation
Authors: Hendren Christina , Li Weiping , Stegemann Jan P. , Hall Timothy L. , Deng Cheri X. 
Published: July 2023

Abstract
Resonant Acoustic Rheometry (RAR), a newly developed ultrasound-based technique for non-contact characterization of soft viscoelastic materials, has shown promise for quantitative assessment of plasma coagulation by monitoring the entire dynamic process in real time. Here, we report the development of a multichannel RAR (mRAR) system for simultaneous monitoring of the coagulation of multiple small-volume plasma samples, a capability that is critical to efficiently provide improved assessment of coagulation. The mRAR system was constructed using an array of 4 custom-designed ultrasound transducers at 5.0 MHz and an electronic driving system that controlled the generation of synchronized ultrasound pulses for real time monitoring of multiple samples simultaneously. The mRAR system was tested using Coumadin-treated plasma samples with a range of International Normalized Ratio (INR) values, as well as normal pooled plasma samples. Tracking of dynamic changes in clotting of plasma samples triggered by either kaolin or tissue factor was performed for the entire duration of coagulation. The mRAR system captured distinct changes in the samples and identified parameters including clotting time, clotting speed, and the mechanical properties of the clots that were consistent with Coumadin dose and INR levels Data from this study demonstrate the feasibility of the mRAR system for the rapid, efficient, and accurate characterization of plasma coagulation.
Polaritonic and Excitonic Semiclassical Time Crystals based on TMDC strips in an external periodic potential
Authors: Martins Gabriel , Berman Oleg , Gumbs Godfrey 
Published: July 2023

Abstract
We investigated the dynamics of Bose-Einstein condensates (BECs) under an external periodic potential. We consider two such systems, the first being made of exciton-polaritons in a nanoribbon of transition metal dichalcogenides (TMDCs), such as MoSe2, embedded in a microcavity with a spatial curvature, which serves as the source of the external periodic potential. The second, made of bare excitons in a nanoribbon of twisted TMDC bilayer, which naturally creates a periodic Moiré potential that can be controlled by the twist angle. We proved that such systems behave as semiclassical Time Crystals (TCs). This was demonstrated by the fact that the calculated BEC spatial density profile shows a non-trivial long-range two-point correlator that oscillates in time. These BECs density profiles were calculated by solving the quantum Lindblad master equations for the density matrix within the mean-field approximation. We then go beyond the usual mean-field approach, by adding a stochastic term to the master equation, which corresponds to quantum corrections, and we show that the TC phase is still present.
Ethnic Diversity in Motion: Understanding the Relationship between Dynamic Ethnic Fractionalization and Economic Growth
Authors: Miladinovic Luka 
Published: July 2023

Abstract
The study explores the relationship between dynamic ethnic fractionalization and economic growth using a panel of 76 countries over four decades. This panel is the most extensive dataset on the topic to date. Results from the replication of previous approaches to the topic – both with time-invariant and dynamic ethnic diversity – underscore the importance of including the temporal component of ethnic diversity in an analysis of its effects on economic growth and challenge the prevalent assumption of constant ethnic diversity. In addition, we exploit the time variability of ethnic diversity by employing, for the first time, maximum likelihood dynamic panel data modeling – a rigorous methodological approach that enhances confidence in the conclusions. Our results show that ethnic diversity does not directly determine economic growth but rather influences other growth determinants, thereby impeding economic performance when the nation-state is the unit of observation. This sheds light on the contrasting conclusions observed in previous studies regarding the impact of ethnic diversity on economic performance.
JEL classification: O11; J15
Prognostic value of total, free and lipoprotein fraction-bound plasma mitotane levels in advanced adrenocortical carcinoma: a prospective study of the ENDOCAN-COMETE-Cancer network
Authors: Faron Matthieu , NAMAN Annabelle , Delahousse Julia , Hescot Segolene , Hadoux Julien , Castinetti Frederic , DRUI Delphine , Renoult-Pierre Peggy , Libe Rossella , Lamartina Livia , Leboulleux Sophie , Ghuzlan Abir Al , Lombes Marc , Paci Angelo , Baudin Eric 
Published: July 2023

Abstract
Purpose
Mitotane is the only approved treatment for metastatic adrenocortical carcinoma (ACC). Monitoring plasma levels is recommended, but its positive predictive value is insufficient.
Methods
This prospective study of the French ENDOCAN-COMETE network aimed to investigate the prognostic role of early plasma mitotane levels pharmacokinetics and free or bound to lipoprotein fraction dosages during six consecutive months. Lipoprotein fractions were isolated by ultracentrifugation, and mitotane level was determined by HPLC-UV. Total, free, and lipoprotein fraction bound plasma mitotane were monitored every two months for six months with a clinical and morphological assessment. The primary endpoint was overall survival (OS) since the initiation of mitotane.
Results
Twenty-one patients with metastatic ACC and at least two measurements of mitotane level during the MITOLIPO period were included. Median overall survival was 23 months. The median free mitotane level per patient was 12% (± 7%), and the majority (88%) was bound to lipoprotein fractions. Several pharmacokinetics measures of total mitotane were related to OS: the first level at one month (p: 0.047), the mean level (p: 0.082), and the area under the curve (AUC) (p: 0.089), with higher exposure associated to longer OS. Free mitotane (not bounded) and mitotane bounded to lipoprotein subfraction added no prognostic values. The relationship between the mitotane level and OS suggested a minimum "effective" threshold of 10-15mg/L or an area under the curve above 100mg/L/month with no individualized maximum value.
Conclusion
This prospective study did not identify any added prognostic value of free mitotane level over the total level. Early total mitotane level measurements (before 3–6 months) were related to OS with a higher and faster exposure related to more prolonged survival.
Conformational Dynamics of α-Synuclein: A Study of its Intramolecular Forces in the Presence of Selected Compounds
Authors: khatooni Zahed , Akhtari Keivan , Wilson Heather L. 
Published: July 2023

Abstract
Protein misfolding and aggregation play a role in amyloidogenic diseases through the self-assembly of intrinsically disordered proteins (IDPs) in type II diabetes (T2D), Alzheimer's (AD) and Parkinson's (PD) diseases. PD is the most common neurodegenerative disorder after AD, known for the loss of dopaminergic signaling, which causes motor and non-motor signs and symptoms. Lewy bodies and Lewy neurites are common pathological hallmarks of PD that are mainly composed of an aggregate of the disordered protein, α-synuclein (α-Syn). There have been many efforts to develop chemical-based compounds to prevent aggregation or facilitate disruption of the fibrils. These have been tested in wet labs, but most fail to generate a robust impact. Further, the atomistic roles and interactions of such compounds have yet to be revealed. The conformational diversity and detailed interactions among homo-oligomer chains of α-Syn are also unknown; identifying these might help uncover a practical approach to developing a potent therapy. In this study, we use an in-silico investigation to address the conformational diversity of α-Syn oligomers. The roles of several point mutations in protein aggregation in PD are known; we take this further by evaluating the interactional energies and contributions of all residues in stability and chain–chain interactions. We dock three chemical derivatives of known compounds with high-score drug-likeness to evaluate the roles of our ligands in the conformational dynamicity of the oligomers, with emphasis on intramolecular forces. Preventing fibril formations is a heated topic in this area. Free energy evaluation of the modeled inter- and intramolecular interactions through MD simulation shows strong binding between α-Syn compounds. However, we find that they do not disrupt or even weaken the interactions, and in some cases, they contributed to boosting interactions between oligomer chains.
Differentially expressed male infertility-associated genes in sperm as prospective diagnostic biomarkers
Authors: Ebrahimi Amir , Ghavi Davood , Mirzaei Zohreh , Barati Tahereh , Mansoori Sima 
Published: July 2023

Abstract
Background
Genetic defects in sperm are responsible for a great percentage of male infertility. The association between numerous genes and spermatogenesis has been observed. Dysregulation of these genes greatly influence sperm morphology, motility and viability. Therefore, analyzing gene expression aberrancies is a must in male infertility. Microarray analysis is practically used for several aspects in male infertility including detection of differentially expressed genes (DEGs), selection of finest sperm for assisted reproductive therapy (ART) and identification of potential infertility biomarkers.
Methods
We conducted a meta-analysis using microarray datasets from NCBI.GEO. We have included datasets containing sperm tissues from both healthy and infertile males. Seven datasets qualified for inclusion in this study. These data were then transformed into a single set of meta-data. For these genes, expression and diagnostic analyses were conducted. In addition, enrichment analysis revealed the role and function of these genes in cellular processes.
Results
Six genes, including S100Z, SLC2A2, IMPG1, HOXD12, RAPGEFL1, and DMBX1, were identified as being significantly down-regulated in infertile men's sperm. Notably, the expression of these genes was highly correlated in sterile sperm. In addition, an analysis of the receiver operating curve indicated that these genes may serve as useful biomarkers for infertility diagnosis. The role of these genes in transporting glucose, vitamins and fructose as the sperm's primary fuel source, was suggested by pathway analysis.
Conclusion
Overall, our results suggest genes with expression abnormalities that may mediate the underlying mechanisms of infertility and also offer promising diagnostic values.
EDKSANet: An Efficient Dual-Kernel Split Attention Neural Network for the classification of Tibetan medicinal materials
Authors: Qi Jindong , Wangdui Bianba , Jiang Jun , Yang Jie , Zhou Yanxia 
Published: July 2023

Abstract
Tibetan medicine has received wide acclaim for its unique diagnosis and treatment methods. The identification of Tibetan medicinal materials, which are a vital component of Tibetan medicine, is a key research area in this field. However, traditional deep learning-based visual neural networks face significant challenges in efficiently and accurately identifying Tibetan medicinal materials, due to their large number, complex morphology, and the scarcity of public visual datasets. To address this issue, we constructed a computer vision dataset with 300 Tibetan medicinal materials and proposed a lightweight and efficient cross-dimensional attention mechanism, the Dual-Kernel Split Attention (DKSA) module, which can adaptively share parameters of the kernel in both spatial and channel dimensions. We then replaced the 3×3 convolutional kernel in the bottleneck blocks of ResNet with the DKSA module, obtaining an EDKSA block that can be embedded into various backbone architectures to enhance the model?s performance. Based on the EDKSA blocks, we developed a novel lightweight backbone architecture, EDKSANet, and demonstrated its competitive performance in image classification, object detection, and instance segmentation on the ImageNet and MS COCO public datasets. Moreover, EDKSANet achieved excellent classification performance on the Tibetan medicinal materials dataset, with an accuracy of up to 96.85%.
Novel Residual Hybrid Machine Learning for Solar Activity Prediction in Smart Cities
Authors: Abdulkadir Rabiu Aliyu , Hasan Mohammad Kamrul , Islam Shayla , ReddyGadekallu Thippa , Pandey Bishwajeet , Safie Nurhizam , Syväjärvi Mikael 
Published: July 2023

Abstract
Predicting global solar activity is crucial for smart cities, especially space activities, communication industries, and climate change monitoring. The recently developed models to predict solar activity based on stand-alone artificial intelligence, based on machine and deep learning models, and hybrid models are promising. Yet they may not be effective at capturing simpler linear patterns in the data and often fail to provide reliable predictions due to the computationally expensive and complex. This article proposed a novel residual hybrid machine learning method integrating linear regression machine learning, and deep learning neural networks for solving predictive accuracy in individual machine learning models that reduces complexity. The residual hybrid model leverages the capacities of the support vector machine (SVM) and long short-term memory neural network (LSTM) for hybrid SVM-LSTM model. The performance of the model is evaluated using the correlation coefficient, determination coefficient, root-mean-squared error (RMSE) and mean-absolute error. The simulation results indicated that compared to the SVM-LSTM, the training and testing RMSE of the LSTM is reduced by 76.62% and 71.18%, respectively. It also decreases the training and testing RMSE of the SVM by 77.06% and 71.81%, respectively. The proposed model can be implemented as reliable solution for accurately predicting solar activities in smart cities.
The efficacy of c-di-AMP as an immunopotentiator for inactivated PRV vaccine
Authors: Hou Liting , Zhang Chenxin , Yu Xiaoming , Du Luping , Cheng Haiwei , Chen Jin , Zheng Qisheng , Hou Jibo 
Published: July 2023

Abstract

Pseudorabies is an acute infectious disease caused by pseudorabies virus which bring huge losses to the swine industry. Compared to live vaccine, the inactivated Pseudorabies virus (PRV)vaccine is generally safe, but it could not elicit strong immunity protection as live vaccine. Improve the efficacy of the inactivated vaccines with immunopotentiator is a research hotspot. Viability-associated pathogen-related molecular patterns(vita-PAMPs) are a type of PAMPs that only exist in active microorganisms. Once entering the body, vita-PAMPs could quickly and efficiently initiate the immune response, and then produce a high level and lasting immune efficacy similar to live vaccine immunity. C-di-AMP is a type of vita-PAMPs which recognized by antigen presenting cell (APC), they can mobilize a high degree of inflammation and activate the adaptive immune response. Hence, we evaluate the effect of c-di-AMP on the efficacy of the pseudorabies inactivated vaccine using a murine model. The immunological enhancement characteristics of c-di-AMP were evaluated for PRV inactivated vaccine in mice. In this study, we measured the level of early inflammatory factors and the recruitment of antigen presenting cells in draining lymph nodes, the activation of follicular helper T cells (Tfh) and the formation of germinal center (GC) by flow cytometry analysis. We also tested the level of serum antibody and the duration of it. The result showed that PRV inactivated vaccine adding c-di-AMP promote the secretion of TNF-α, IL-1β, and IFN-β, recruitment of DCs, Mo and MPh at 7days post-immunization(dpi), and enhance murine antibody levels of PRV by promoting Tfh activated, which directly controls the magnitude of the GC B cell response. These results indicate that c-di-AMP can enhance the immunogenicity of PRV inactivated vaccines, thus providing a novel strategy for improving its efficacy.
Regeneration and Valorization of Spent Bleaching Earth in Edible Oil Refining Industry
Authors: Benkhoud Ikhlas , MANSOUR Lassaad BEN 
Published: July 2023

AbstractThe spent bleaching earth (SBE) from the edible oil refining industry was successfully regenerated through an extraction process using different organic solvents for removal of residual oil, followed by through heat treatment. The total percentage of extracted oil (PEO) for the solvents used showed the following order: PEO (Hexane) > PEO(Acetone) >PEO(Xylene) >PEO(MEK)>PEO (MIBK). The experimental results showed that regeneration by extraction process is insufficient to regenerate SBE, thus requiring also a high temperature treatment. In the current study, the effects of factors, such as liquid to solid ratio [1:1-5:1], temperature [20-40°C], and stirring time [30-60min] on the efficiency of extracted oil were investigated by maceration method. In order to determine the optimal condition, the Experience Planning Methodology (EPM) was adopted. To enhance the oil bleaching efficiency the regenerated SBE by solvent extraction was also treated at different temperatures (300°C – 500°C).
Tool condition monitoring for cavity milling based on bispectrum analysis and Bayesian optimized SVM
Authors: Li Yuhang , Wang Guofeng , Hu Mantang , Ma Kaile 
Published: July 2023

Abstract

Tool wear status seriously affects the dimensional accuracy and surface quality of the machined parts. Therefore, tool condition monitoring (TCM) is essential in the milling process of aerospace structural parts due to the use of difficult-to-cut materials and complex cutting trajectories. The Higher order spectrum (HOS) was first employed to analyze the vibration signals, and then bispectral features extracted from de-noised signals were used to characterize the tool wear status. The improved Pearson’s correlation coefficient was used for feature selection to reduce the influence of periodic components on feature selection process. Furthermore, a novel objective function was proposed to guide the hyperparameters optimization process of support vector machine based on Bayesian optimization algorithm, in which the effect of imbalanced data on the recognition rates was considered. To demonstrate the effectiveness of the proposed method, a structural part milling experiment was performed on a vertical machining center and vibration signals of spindle were collected. Based on this, an online TCM model was established. The present study suggests that the proposed TCM system is accurate and robust.
Experimental study on the transporting and crushing effect of gas on coal powder during the develop stage of coal and gas outburst in roadway
Authors: Cao Jie , Hu Qianting , Dai Linchao , Yang Xuelin 
Published: July 2023

Abstract
In recent years, coal and gas outburst (CGO) disasters are still occurring and difficult to prevent, seriously endangering the safe production in coal mine. It is well known that the transporting and crushing of outburst coal is the major pathway of energy dissipation of CGO process. However, a consensus regarding how gas involves in outburst and affects energy dissipation is still lacking. Quantitative study on the gas effect on migration and fragmentation characteristics of outburst coal in restricted roadway space can improve the energy model. In this study, an improved visual CGO dynamic effect simulation experiment system was utilized to conduct CGO simulation experiments at different gas pressure conditions. The results showed that the ejected coal has experienced various flow patterns in the roadway. In the initial stage, the motion of ejected coal was dominated by stratified flow. However, with the increase of gas pressure, the initial acceleration increases, and the outburst coal mainly move forward rapidly in the form of plug flow. The average velocity at 0.3, 0.5, and 0.8 MPa gas pressure condition were 6.75, 22.22, and 35.81 m/s, respectively. Gas also has a crushing effect on outburst coal bodies. With gas pressure increasing, the number of coal powder particles of the same mass increased significantly, the range of the particle size distribution of decreaed, and the median particle size decreased. In addition, the outburst intensity gradually increases with gas pressure, and the total energy involved in the outburst work also increases. However, the energy dissipation pathways are different. At 0.3 MPa, the energy dissipation is dominated by crushing energy, which is about six times the ejection energy. When the gas pressure increased to 0.8 MPa, the proportion of the ejection energy gradually increases to about twice that of the crushing energy. Under the experimental conditions, 2.71–13.43% of the adsorbed gas involves in the outburst (AGIO) through rapid desorption, and the proportion increases with gas pressure increasing. This paper improves the energy model of CGO, which is applicable to risk assessment and prevention of outburst disasters.
State-dependent Modulation of Low-threshold-current-regulated Dendritic Ca 2+ Response in Thalamic Reticular Neurons with Extracellular Electric Fields
Authors: Fan Yaqin , Wei Xile , Lu Meili , Wang Jiang , Yi Guosheng 
Published: July 2023

Abstract
Deep brain stimulation (DBS) in thalamic reticular nucleus (TRN) neuron provides a novel treatment for drug-resistant epilepsy via the induced electrical field (EFs). However, the mechanisms underlying EF effects remain unclear. This paper investigated how EFs regulate low-threshold dendritic Ca2+ (dCa) response and thus contribute to the input-output relationship of TRN cell. Our results showed that EFs modulate firing modes differently in a neuronal state-dependent manner. At the depolarized state, EFs only regulate the spike timing of a somatic stimulus-evoked single action potential (AP) with less contribution in the regulation of dCa response but could induce the transition between a dendritic stimulus-evoked single AP and a tonic burst of APs via the moderate regulation of dCa response. At the hyperpolarized state, EFs have significant effects on the dCa response, which modulate the large dCa response-dependent burst discharge and even cause a transition from this type of burst discharge to a single AP with less dCa response. Moreover, EF effects on stimulation threshold of somatic spiking prominently depend on EF-regulated dCa responses and the onset time differences between the stimulus and EF give rise to the distinct effect in the EF regulation of dCa responses. Finally, the larger neuronal axial resistance tends to result in the dendritic stimulus-evoked dCa response independent of somatic state. Interestingly, in this case, the EF application could reproduce the similar somatic state-dependent dCa response to dendritic stimulus which occurs in the case of lower axial resistance. These results suggest that the influence of EF on neuronal activities depends on neuronal intrinsic properties, which provides insight into understanding how DBS in TRN neuron modulates epilepsy from the point of view of biophysics.