bluuebunny/crossref_metadata_2025_split huggingface dataset:
Entropic stabilization of a structurally tolerant phase: The ionic phase of lithium alanate
Authors: Krummenacher Marco , Tayfuroglu Omer , Finkler Jonas , Huber Hannes , Goedecker Stefan 
Published: May 2024

Abstract

In materials simulations, formation energies can provide valuable information about the stability of different crystal polymorphs. However, to obtain a complete picture, it is often essential to go beyond simple energetics and include free energies into the analysis as many crystal phases are stabilized by entropic contributions and phase transitions at finite temperatures are common.
Traditionally, free energies of crystalline solids are computed through an analysis of the phonon band structure which is calculated within the harmonic approximation considering only the crystalline unit cell and its replication. But also methods that go beyond the harmonic approximation consider only one periodic structure to calculate free energies.
We show that such an approach can overlook substantial configurational free energy contributions and does not allow us to reach a well defined thermodynamic limit.
To overcome these problems, it is necessary to generate large periodic cells that can represent not only the perfect crystalline structure but also a very large number of defect structures.
Only with a configurational density of states that is well converged with respect to the size of the cell, it is possible to obtain reliable estimates of phase transition temperatures.
We illustrate this effect for lithium alanate where the configurational entropy contribution of the structurally tolerant ionic phase reduces the transition temperature to the polymeric phase by 150 K.
A unified cross-attention model for predicting antigen binding specificity to both HLA and TCR molecules
Authors: Liu Hui , Yu Chenpeng , Fang Xing , Tian Shiye 
Published: May 2024

Abstract

The immune checkpoint inhibitors have demonstrated promising clinical efficacy across various tumor types, yet the percentage of patients who benefit from them remains low. The bindings between tumor antigens and HLA-I/TCR molecules determine the antigen presentation and T-cell activation, thereby playing important role in the immunotherapy response. Some computational methods have been developed to predict peptide-HLA (pHLA) or peptide-TCR (pTCR) binding specificity, but they focus solely on one task at a time. In this paper, we propose UnifyImmun, a unified cross-attention transformer model designed to simultaneously predict the bindings of peptides to both receptors, thereby providing more comprehensive evaluation of antigen immunogenicity. We devise a two-phase progressive training strategy that enables these two tasks to mutually reinforce each other, by compelling the encoders to extract more expressive features. We also incorporate virtual adversarial training to enhance the model generalizability. Compared to over ten previously published methods for predicting pHLA and pTCR bindings, our method demonstrates better performance in both tasks on multiple independent and external test sets. Notably, on a large-scale COVID-19 pTCR binding test set, our method outperformed the current state-of-the-art methods by at least 9%. The validation experiments on three clinical cohorts confirm that our approach effectively predicts immunotherapy response and clinical outcomes. Furthermore, the cross-attention scores and integrated gradients reveal the amino-acid sites critical for peptide binding to receptors. In essence, our approach marks a significant step towards comprehensive evaluation of antigen immunogenicity.
Meta-Analysis and MaxEnt Model Prediction of the Distribution of the Phenacoccus solenopsis in China under the Background of Climate Change
Authors: liu zhiqian , Peng Yaqin , Danping Xu , Zhuo Zhihang 
Published: May 2024

Abstract

The Phenacoccus solenopsis poses a serious threat to global crops, and controlling climate change has become a crucial strategy. In this study,it through a comprehensive analysis of experimental data, found that within the suitable temperature range, the survival rate of the P.Tinsley increases with rising temperatures, indicating that climate plays a decisive role in its distribution. Using the MaxEnt model, in this study, it predicted that under three future climate scenarios (SSP1–2.6, SSP3–7.0, and SSP5–8.5), the distribution of the P.Tinsley will expand and move towards higher latitudes. Climate change is the primary factor influencing changes in pest distribution. In this study it was conducted a Meta-analysis of the P.Tinsley, including seven independent studies covering 221 observation results, and examined the impact of temperature ranging from 18°C to 39°C on the developmental cycle of the P.Tinsley. As the temperature rises, the development cycle of the P.Tinsley. gradually decreases.Additionally, in combination with the MaxEnt model, it predicted the current and potential future distribution range of the P.Tinsley. The results show that under future climate warming, the distribution area of P.Tinsley in China will expand.This research provides a theoretical basis for early monitoring and control of this pest's occurrence and spread. Therefore, the predictive results of this study will provide important information for managers in monitoring the P.Tinsley and help them formulate relevant control strategies.
Selective and Controllable Mechanism of the Temperature Field in Pig Skin under Radiofrequency Heating
Authors: Zhu Ping , Xie Chuanqi , Shu Fangjie , Li Liqiang , Su Zhaodi , Wang Zhichao , Mu Ziyu 
Published: May 2024

Abstract

Radiofrequency heating is widely used in medical aesthetics, which essentially achieves the contraction of collagen fibers in the dermis by increasing its temperature. The paper aimed to study the selective and controllable mechanism for the temperature field in 0.02 kg ex-vivo pig skin samples obtained from the 25 kg Bama pig under radiofrequency heating by the finite element method and relevant experiments. A heating model of pig skin was constructed at 4 MHz with a mixed heating mode of fixed-point and reciprocating sliding. Based on the mixed heating, the dermis was heated preferentially and uniformly due to its high electrical conductivity and thermal conductivity compared to other tissue layers. It allowed the dermis temperature 55.1 ℃ to remain at a dynamic plateau period with an error of 0.1 ℃, and the mean specific absorption rate across the entire pig was under 2 W/kg within 30 s in this period. The verification experiment on the pig skin samples under the same conditions showed consistent temperature distributions between the model and experiment, and the dermis collagen fibers structure was clear without tissue damage. The research results provide useful guidance for radiofrequency application practitioners to selectively control skin temperature distributions.
Food Insecurity and Chronic Diseases: Diabetes &amp; Hypertension Among Older Adults in South Africa
Authors: Mgwaba Mbongeleni. Thembalihle , Masuku Mfundo Mandla 
Published: May 2024

Abstract

Food security is a situation where all people, at all times, have physical, social and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for a healthy and active life. In 2021, a significant number of the South African households either had food inadequacy or severe food inadequacy challenges. More than half of South African population is at risk of hunger and limited access to nutritious food.
Food insecurity is often associated with negative health outcomes, including chronic diseases such as diabetes and hypertension. A secondary data obtained from the cross sectional 2021 South African General Household Survey (GHS) was analyzed to determine the association between food insecurity (independent variable) and diabetes and hypertension (dependent variables). The data was analysed in three phases namely univariate, bivariate, and multivariate.
Stratified random sampling was employed in the primary study whereas the sample frame of this study consisted of 3,324 primary sampling units (PSUs) with a total of 33,000 dwelling units/ enumeration areas. The results of this study show that the odds of having hypertension or diabetes were considerably higher among older adults who had inadequate access to food (odds ratio (OR) 1.14, p < 0.05) compared to those who had adequate access to food. More targeted food security programs could lower the odds of diabetes and hypertension amongst older adults. The promotion and provision of free health screening services at various government health facilities could assist with the early detection of hypertension and diabetes.
Exploring Pathogenic Genes in Frozen Shoulder through weighted gene co-expression network analysis and Mendelian Randomization
Authors: wen Dusu , Li Bin , Guo Shun , Chen Biao , Chen Liaobin 
Published: May 2024

Abstract

Background
Frozen shoulder (FS) is characterized by the thickening and fibrosis of the joint capsule. The precise etiology responsible for these pathological changes remains elusive. Consequently, the primary aim of this study was to explore the potential involvement of pathogenic genes in FS.
Methods
Differential expression analysis and WGCNA were employed to investigate the co-expressed genes. GO and KEGG were conducted to elucidate the potential roles of these co-expressed genes. Subsequently, Mendelian randomization (MR) analysis was performed using expression quantitative trait loci datasets for these co-expressed genes, combined with the genome-wide association study of FS. The identified hub genes were further validated through reverse transcription-quantitative PCR (RT-qPCR). In addition, a nomogram model and receiver operating characteristic (ROC) curves were established to assess the diagnostic value of the hub genes. Furthermore, the infiltration of immune cells was evaluated using the CIBERSORT algorithm and the relationship between hub genes and immune infiltrating cells was subsequently analyzed.
Result
The gene co-expression network was constructed using WGCNA and the top two most correlated modules were identified. These modules were then intersected with differentially expressed genes, yielding a set of 295 overlapping co-expressed genes. Utilizing MR analysis, four hub genes, namely ADAMTS1, NR4A2, PARD6G, and SMKR1 were found to exhibit positive causal relationships with FS, which were subsequently validated through RT-qPCR analysis. Moreover, the diagnostic value of the four hub genes was demonstrated through the development of a nomogram model and the construction of ROC curves. Notably, a causal relationship between ADAMTS1 and immune cell infiltration in frozen shoulder was observed.
Conclusion
Our study suggested a potential association between the upregulated expression of ADAMTS1, NR4A2, PARD6G, and SMKR1 and an increased susceptibility to FS. Further investigations elucidating the functional roles of these genes will enhance our understanding of the pathogenesis of FS.
Astaxanthin attenuates glucose-induced liver injury in largemouth bass: role of p38MAPK and PI3K/Akt signaling pathways
Authors: Liao Zhihong , He Xuanshu , Chen Anqi , Zhong Jian , Lin Sihan , Guo Yucai , Cui Xin , Chen Baoyang , Zhao Wei , niu jin 
Published: May 2024

Abstract

Background
Astaxanthin (ASX) has been documented to exert beneficial influence on various processes in fish. Largemouth bass serves as a common model for studying glucose-induced liver disease, making it imperative to investigate the regulatory mechanisms underlying its liver health.
Methods
Largemouth bass were fed with a control diet (CON), a high carbohydrate diet (HC), or a HC diet supplemented astaxanthin (HCA) for 8-weeks, followed by the glucose tolerance test (GTT). Primary hepatocytes were treated with low glucose and high glucose combined with different concentrations of astaxanthin for 48 h. The histopathology, enzymology, transcriptomics, molecular biology and cell biology were combined to investigate the mechanism of liver injury.
Results
This study provides evidence for the protective effects of ASX against growth performance reduction and hepatic liver injure in largemouth bass fed HC diet. In GTT, HCA diet exhibited an improvement in glucose tolerance following glucose loading. Although HCA diet did not restore the expression of insulin resistance-related genes in livers at different time during the GTT, the addition of ASX in the long-term diet did improve the insulin resistance pathway by regulating the PTP1B/PI3K/Akt signaling pathway. Hepatic transcriptome analyses showed that ASX plays an essential role in the modulation of glucose homeostasis in response to treatment with HC diet. In in vitro study, the treatment with ASX resulted in an exaltation in cell viability and a reduction in the rate of cell apoptosis and reactive oxygen species (ROS). Additionally, astaxanthin was observed to improve apoptosis induced by high-glucose via p38MAPK/bcl-2/caspase-3 signaling pathway.
Conclusions
Astaxanthin exhibited a protective effect against apoptosis by regulating p38MAPK/bcl-2/caspase-3 pathway, and ameliorated insulin resistance by activating the PTP1B/PI3K/Akt pathway. This study elucidated the mechanism of astaxanthin in the liver injury of largemouth bass from a new perspective and provided a new target for the treatment of insulin resistance.
Space-Time Video Super-Resolution via Multi-Scale Feature Interpolation and Temporal Feature Fusion
Authors: Yang Caisong , Kong Guangqian , Duan Xun , Long Huiyun , Zhao Jian 
Published: May 2024

Abstract

The goal of Space-Time Video Super-Resolution (STVSR) is to simultaneously increase the spatial resolution and frame rate of low-resolution, low-frame-rate video. In response to the problem that the STVSR method does not fully consider the spatio-temporal correlation between successive video frames, which makes the video frame reconstruction results unsatisfactory, and the problem that the inference speed of large models is slow. This paper proposes a STVSR method based on Multi-Scale Feature Interpolation and Temporal Feature Fusion (MSITF). First, feature interpolation is performed in the low-resolution feature space to obtain the features corresponding to the missing frames. The feature is then enhanced using deformable convolution with the aim of obtaining a more accurate feature of the missing frames. Finally, the temporal alignment and global context learning of sequence frame features are performed by a temporal feature fusion module to fully extract and utilize the useful spatio-temporal information in adjacent frames, resulting in better quality of the reconstructed video frames. Extensive experiments on the benchmark datasets Vid4 and Vimeo-90k show that the proposed method achieves better qualitative and quantitative performance, with PSNR and SSIM on the Vid4 dataset improving by 0.8\% and 1.9\%, respectively, over the state-of-the-art two-stage method AdaCof+TTVSR, and MSITF improved by 1.2\% and 2.5\%, respectively, compared to single-stage method RSTT. The number of parameters decreased by 80.4\% and 8.2\% compared to the AdaCof+TTVSR and RSTT, respectively.
Temporal context in paced finger tapping tunes the error-correction mechanism
Authors: Silva Ariel D. , Laje Rodrigo 
Published: May 2024

Abstract

Sensorimotor synchronization (SMS) is the mainly specifically human ability to move in sync with a periodic external stimulus, as in keeping pace with music. The most common experimental paradigm to study its largely unknown underlying mechanism is the paced finger-tapping task, where a participant taps to a periodic sequence of brief stimuli. Contrary to reaction time, this task involves temporal prediction because the participant needs to trigger the motor action in advance for the tap and the stimulus to occur simultaneously, then an error-correction mechanism takes the past performance as input to adjust the following prediction. In a different task, it has been shown that exposure to a distribution of individual temporal intervals creates a “temporal context” that can bias the estimation/production of a single target interval. As temporal estimation and production are also involved in SMS, we asked whether a paced finger-tapping task with period perturbations would show any temporal context effect. In this work we show that temporal context can indeed be generated during paced finger tapping as in other, simpler temporal tasks, and that the shape and size of the resynchronization curve after a period perturbation depends on temporal context. Response asymmetry is also affected by temporal context, thus evidencing an interplay between context and intrinsic nonlinearities of the correction mechanism. We conclude that temporal context calibrates the underlying error-correction mechanism in SMS.
Mechanism and regulation strategy of plasma-assisted shaped tube electrochemical machining for micro-hole drilling
Authors: Zhan Shunda , Yang Xiwu , Xiao Haibing , Liu Mingjun , Jiang Kai , tang Wenming 
Published: May 2024

Abstract

The deep micro-hole structure has important applications in the fields of aerospace, precision mold, automotive industry and medical equipment. Plasma-assisted electrochemical machining (PA-ECM) is an important method for deep micro-hole fabrication. However, when the machining depth is >500 μm (depth to diameter ratio of about 1:1), the electrolyte is difficult to flow into the machining area (inter-electrode gap), which is easy to cause abnormal spark discharge and even short circuit, affecting the processing stability. In order to solve the problem of lack of electrolyte in the machining area, a plasma-assisted shaped tube electrochemical machining (PA-STEM) method was proposed in this paper. In PA-STEM, the current is mainly conductive through the electrolyte jet, and the electric field of the tube electrode end face and sidewall is shielded by the gas film/plasma film, so the machining accuracy would not deteriorate under high machining voltage. As a hot gas medium, plasma can create a machining environment similar to electrochemical jet machining (EJM), hence a small pit is left at the bottom of the micro-hole. The higher voltage makes the gas film and plasma film more dense, which is beneficial to improve the machining accuracy of micro-hole. The tube electrode feeding rate should not be too fast to avoid damage to the machined surface caused by high-energy spark discharge. At high pulse frequency and low electrolyte flow rate, the energy of plasma is more stable, and it is more suitable for high-quality micro-hole machining. Through the optimization of the process parameters, a deep micro-hole with inlet diameter of 980 μm, outlet diameter of 750 μm, depth of 5 mm was obtained, and the depth-to-diameter ratio of the micro-hole is 5.1:1. Moreover, there is no recast layer on the sidewall subsurface of the micro-hole.
Exploring Hidden Patterns and Interests on Twitter through Contextual Focal Structure Analysis
Authors: Alassad Mustafa , Nwana Lotenna , Agarwal Nitin 
Published: May 2024

Abstract

The Contextual Focal Structure Analysis (CFSA) model represents an advanced methodology designed to enhance the identification and interpretation of key influencers and interaction patterns within social networks, such as Twitter. The CFSA model stratifies data into multiple layers by employing a multiplex networks approach, enabling a detailed examination of user activities and interests across different social contexts. At its core, the CFSA model employs a user-to-user network layer to capture complex interactions and gain deeper insights into user engagement on the platform. Additionally, it incorporates a second layer consisting of hashtag co-occurrence networks. To assess the CFSA model’s efficacy, this study focused on analyzing the spread of the Cheng Ho disinformation narrative within the Indo-Pacific region. Utilizing an extensive dataset containing over 64,519 tweets and 20,000 hashtags collected from January 2019 to October 2022, the analysis provided a comprehensive view of user behavior and the contextual nuances shaped by their interactions with different hashtags. The results highlighted significant patterns and the dynamics of user communities. Notably, the study identified several impactful contextual focal structures that were pivotal in driving discussions related to disinformation narratives. Moreover, the CFSA model exposed prevalent hashtags such as "#SouthChinaSea," "#NavyPartnerships," and "#United_States," linking some of these to accounts that spread information about oil and gas exploration and drilling activities, predominantly conducted by NATO alliances and China. These findings underscore the potential of the CFSA model to uncover and interpret latent influential patterns and interests on Twitter, providing valuable insights into the mechanisms of information dissemination and public discourse in digital environments.
STFT, LASSO and EHO based Feature Extraction with Integrated Machine Learning and Metaheuristic Classification Techniques for Colon Cancer detection from Microarray Gene Expressions
Authors: Nair Ajin R , Rajaguru Harikumar , S Karthika M , C Keerthivasan 
Published: May 2024

Abstract

The microarray gene expression data poses a tremendous challenge due to their curse of dimensionality problem. The sheer volume of features far surpasses available samples, leading to overfitting and reduced classification accuracy. Thus the dimensionality of microarray gene expression data must be reduced with efficient feature extraction methods to reduce the volume of data and extract meaningful information to enhance the classification accuracy and interpretability. In this research, we discover the uniqueness of applying STFT (Short Term Fourier Transform), LASSO (Least Absolute Shrinkage and Selection Operator), and EHO (Elephant Herding Optimisation) for extracting significant features from lung cancer and reducing the dimensionality of the microarray gene expression database. The classification of lung cancer is performed using the following classifiers: Gaussian Mixture Model (GMM), Particle Swarm Optimization (PSO) with GMM, Detrended Fluctuation Analysis (DFA), Naive Bayes classifier (NBC), Firefly with GMM, Support Vector Machine with Radial Basis Kernel (SVM-RBF) and Flower Pollination Optimization (FPO) with GMM. The EHO feature extraction with FPO-GMM classifier attained the highest accuracy in the range of 96.77, with an F1 score of 97.5, MCC of 0.92 and Kappa of 0.92.
Complete mitogenome structure and phylogenetic implications of the first Indian yak breed- Arunachali (Poephagus grunniens L.)
Authors: Pukhrambam Martina , Tribhuvan Kishor U. , Das Pranab J. , Sarkar Mihir 
Published: May 2024

Abstract

Arunachali is the first registered breed of yak in India inhabiting Tawang and West Kameng districts of Arunachal Pradesh. Arunachali yak breed accounts for half the yak population in India, however, the number has been declining. In order to conserve and propagate this majestic and unique animal, this study reports the first ever whole mitogenome of an Indian yak breed. The mitogenome of Arunachali yak was found to be circular and double stranded with a length of 16,324 bp comprising 13 protein coding genes (PCGs), 22 tRNAs, 2 rRNAs and an 894bp non-coding control region (D-loop). Out of the 37 genes, 29 genes were encoded on H-strand and 8 on the L-strand. The overall nucleotide composition was A = 33.70%, T = 27.28%, G = 13.21% and C = 25.80% with an AT biasness. Phylogenetic analysis was done with three datasets involving 27 whole mitogenome of Chinese yak breeds and a Bos indicus outgroup sequence. The Arunachali yak shows same ancestry with the other yak breeds and more closeness to Jinchuan yak based on D-loop sequence. The findings of this study elucidate the mitochondrial genomic architecture of Arunachali yak and its evolutionary status along with providing basis for characterisation and formulation of specific breeding policies for Indian yaks.