bluuebunny/crossref_metadata_2025_split huggingface dataset:
PM2.5 prediction based on attention mechanism and Bi-LSTM
Authors: Huang Xin , Liu Zuhan 
Published: December 2023

Abstract
This study enhances the Bi-LSTM model by incorporating an attention mechanism, which could provide the model with stronger data generalization capabilities. Moreover, it can predict a broader range of data and exhibits enhanced handling and adaptability to anomalies. Through the utilization of the attention mechanism, this research partitions the weights of the feature values, precisely dividing the input LSTM's feature values based on their weights. This enables the Bi-LSTM to more accurately capture relationships between different feature values in time series and dependencies on various features. Given the diverse air quality conditions in different regions, the introduced attention mechanism in Bi-LSTM manages the weights of different feature values. The Bi-LSTM, enhanced with attention mechanisms, excels at handling relationships in time series data, allowing it to predict PM2.5 values in more complex air quality environments. It demonstrates improved capabilities in handling anomalies. Even in air quality scenarios with various complex conditions, the model maintains satisfactory predictive quality.
WITHDRAWN: Anti-diabetic and hemolytic activity of Antimicrobial Peptide Parapolybia-MP
Authors: Vanathi Grace , Rajesh RP 
Published: December 2023

Abstract

Parapolybia-MP, an antimicrobial peptide belonging to the family of Mastoparans are cationic tetra decapeptide. This peptide is composed of 14 amino acid residues, (INWKKMAATALKMI) and mostly resides in the venom of the Polistes wasp. It has a molecular weight of 1619.00KDa. Parapolybia-MP was custom-synthesized to test its activity. Parapolybia-MP is a group of mast cell degranulating peptides possessing various activities such as anticancer, anti-inflammatory, and cytolytic properties. They also possess strong anti-diabetic activity and hemolytic activity. This peptide is linear in configuration and modifies itself into a cyclic one upon binding to the plasma membrane of the microbes.
Dynamics of structures with a rotational clutching inertia system considering supplemental friction damping
Authors: Bai Xiaoyu , Liang Qigang , Li Luyu , Ou Jinping 
Published: December 2023

Abstract
The innovative Clutching Inertia System (CIS), has garnered increasing recognition for its effectiveness in mitigating structural vibrations. To enhance the efficiency of passive CIS, introducing suitable energy dissipation mechanisms for the rotational inertia component is imperative. This study delves into the dynamic behavior of CIS, augmented with additional friction damping. Initially, the influence of supplementary friction damping within the CIS framework is examined through a dynamic model of a Single-Degree-of-Freedom (SDOF) system, integrated with the CIS and incorporating the Coulomb friction model. Subsequently, to streamline the dynamic analysis of the CIS and optimize the friction force thereby enhancing control efficiency while minimizing inactive durations, the paper introduces two distinct Equivalent Linearization Methods (ELMs). These methods aid in the linearization of the nonlinear dynamics of the CIS. Furthermore, an assessment of the CIS's dynamic performance, subjected to various external excitations, is presented. The findings highlight the crucial role of supplemental friction damping in reducing the inactivity of CIS and enhancing its overall control effectiveness. The employed ELMs demonstrate commendable accuracy and practicality for both response assessment and CIS performance optimization. In essence, the CIS, when integrated with supplemental friction damping, exhibits superior performance in suppressing structural displacement responses across diverse excitations, particularly in longer-period structures. Conversely, a more pronounced efficacy in managing structural acceleration responses is observed in structures with shorter periods. The study concludes that for specific structural applications, enhancing supplemental friction damping is more advantageous for vibration control than increasing the CIS's inertia.
Crucial effect of interleukin-17/IL-17RC signaling on bio-functions of alveolar type II epithelial cell through Akt and STAT pathways
Authors: jin xiaoer , Huang Fang , pu yufan , wang miao , Xue Chunmeng , liao qingbo , Ding Qi 
Published: December 2023

Abstract
The aim of this study was to explore the role of interleukin (IL)-17/IL-17RC signaling in the function of human alveolar type II epithelial cell-derived cell line of A549 cells. An in vitro LPS-challenged A549 cell model was established to assess the expression of IL-17RC. The effects of IL-17 alone or with LPS in A549 were evaluated by detecting the expression of surfactant protein A (SPA), epithelial sodium channel (ENaC), inflammatory cytokine tumor necrosis factor (TNF)-α and IL-8. Moreover, IL-17RC neutralizing antibody and STAT inhibitor were employed to explore the mechanism underlying IL-17/IL-17RC signaling influencing on A549 cell biological behavior. IL-17RC was expressed on A549 cells and showed a time and LPS dose dependent manner. IL-17 treatment could exert a synergistic effect with LPS, which could result in significantly elevated expression level of TNF-α and IL-8 and reduced expression level of SPA and ENaC. Activation of phosphorylation Akt and STAT were involved in the process of IL-17/IL-17RC signaling effects on A549 cell biological behavior and inhibition the Akt and STAT pathway with AG490 could reverse the effects exerted by IL-17/IL-17RC signaling. The results demonstrated that IL-17/IL-17RC signaling could modulate the biological function of human alveolar type II epithelial cell-derived A549 cells via promoting TNF-α and IL-8 expression, suppressing SPA and ENaC expression, and through activating Akt and STAT signaling pathway.
Pre-operative Prediction of Histopathological Growth Patterns of Colorectal Cancer Liver Metastasis Using an MRI-based Radiomic Models
Authors: Song Chunlin , Li Wenhui , Cui Jingjing , Miao Qi , Liu Yi , Zhang Zitian , Nie Siru , Zhou Meihong , Chai Ruimei 
Published: December 2023

Abstract

Purpose
Histopathological growth patterns (HGPs) of colorectal liver metastases (CRLMs) have prognostic value. However, the differentiation of HGPs relies on postoperative pathology. This study aimed to develop a magnetic resonance imaging (MRI)-based radiomic model to predict HGP pre-operatively, following the latest guidelines.
Methods
This retrospective study included 93 chemotherapy-naïve patients with CRLMs who underwent contrast-enhanced liver MRI and partial hepatectomy between 2014 and 2022. Radiomic features were extracted from the tumor zone (RTumor), a 2-mm inner ring (RT−2), a 2-mm outer ring (RT+2), and a combined ring (R2 + 2) on late arterial phase MR images. ANOVA and LASSO algorithms were used for feature selection. Logistic regression with five-fold cross-validation was used for model con-struction. Receiver operating characteristic curves, calibrated curves, and decision curve analyses were used to assess model performance. Delong’s test was used to compare different models.
Results
Twenty-nine desmoplastic and 64 non-desmoplastic CRLMs were included. The radiomic models achieved area under the curve (AUC) values of 0.736, 0.906, 0.804, and 0.794 for RTumor, RT−2, RT+2, and R2 + 2, respectively, in the training cohorts. The AUC values were 0.713, 0.876, 0.785, and 0.777 for RTumor, RT−2, RT+2, and R2 + 2, respectively, in the validation cohort. RT−2 exhibited the best performance.
Conclusion
The MRI-based radiomic models could predict HGPs in CRLMs pre-operatively. The differences between dHGP and non-dHGP are primarily observed near the tumor margins, particularly the internal edges.
Elucidating the Correlation between Leupaxin as a Prognostic Biomarker and Immunotherapeutic Efficacy in Esophageal Squamous Cell Carcinoma
Authors: Teng Fei , Chen Yang , Liao Fei , Wang Yingzhao , Jiang YueQuan , Wang ZhiQiang 
Published: December 2023

Abstract
Background: Oesophageal cancer is a prevalent malignant tumour globally, yet it often receives subpar treatment. Recent interest in immunotherapy has instilled hope for cancer patients. However, further research is necessary to comprehend the mechanisms and roles of effective biomarker in oesophageal squamous carcinoma (ESCC).
Methods: We investigated the expression, pathological and prognostic significance, protein interactions, pathway enrichment, immune microenvironment, correlations between immune regulators and infiltration of immune cells, associations with drug resistance genes, as well as chemosensitivity of leupaxin (LPXN) in ESCC. The relative expression of LPXN mRNA and protein was evaluated in both healthy surrounding tissues and ESCC tissues using quantitative polymerase chain reaction and immunohistochemistry, utilizing samples obtained from clinical cases. Furthermore, we investigated the potential role of LPXN in ESCC through a variety of techniques including cell proliferation assays, apoptosis assays, clonogenic assays, migration assays with or without extracellular matrix support. The co-expression of LPXN and PD-L1 at the protein level in oesophageal squamous cell lines was determined by western blotting. We validated the expression of the LPXN gene in ESCC using clinical samples and investigated the correlation between LPXN gene expression and the efficacy of immune therapy for ESCC.
Results:Bioinformatic analysis revealed a favourable association between LPXN and prognosis in ESCC. LPXN and PD-L1 were found to be co-expressed, with LPXN strongly associated with the immune system, related pathways, microenvironment, regulators, cell infiltration levels, genes related to drug resistance, and chemosensitivity. The expression of LPXN in ESCC at both mRNA and protein levels was confirmed in clinical samples of cancerous and normal tissues. Cell-based experiments demonstrated that knockdown of LPXN resulted in decreased cell viability, invasion, proliferation, and migration in ESCC cell lines. In samples that responded well to therapy, LPXN and PD-L1 were overexpressed at the mRNA and protein levels.
Conclusion: The results of our study have revealed the significance and involvement of the immune-related biomarker LPXN in the proliferation and migration processes of ESCC, thereby establishing a novel framework for the treatment of this disease.
Three-dimensional measurement of the depth of invasion in oral squamous cell carcinoma samples using Lugol’s iodine-enhanced micro-computed tomography
Authors: Yu Jiaxin , Liu Kunyu , Zhang Qian , Pu Yumei , Hu Qingang , Xia Chengwan , Wang Yuxin 
Published: December 2023

Abstract
Purpose
Depth of invasion (DOI) in oral squamous cell carcinoma (OSCC) guides treatment and prognosis but lacks three-dimensional (3D) insight. We used Lugol’s iodine-enhanced micro-computed tomography (CT) for 3D analysis.
Methods
Fifteen in vitro OSCC samples from Nanjing Stomatological Hospital (July to December 2022) were micro-CT imaged with a slice thickness of 50 µm following 3% Lugol’s iodine staining for 12 h and then pathologically sectioned and stained. The panoramic diagnostic scanner measured pathological DOI digitally. The micro-CT DOI was measured by evaluating the CT value of the boundary of the tumor lesion and comparison with the pathological examination results. Experienced physicians analyzed both measurements, and a statistical analysis was performed to determine their correlation.
Results
Lugol’s iodine-enhanced micro-CT imaging can clearly distinguish various tissue structures, such as tumor tissue, epithelial tissue, muscle tissue, blood vessel structure, and other major tissue structures in three-dimensional space. This imaging technique can help identify and localize suspicious micro-tumor lesions (1.82 × 1.5 × 1 mm) when used in conjunction with pathological sections. The statistical analysis results indicate a strong correlation between pathological DOI and micro-CT DOI (p < 0.001), with a correlation coefficient of 0.995. During the measurement of DOI information, Lugol’s iodine-enhanced micro-CT imaging effectively compensates for the loss of three-dimensional space information in pathological measurements, thereby improving the accuracy of DOI measurement.
Conclusion
Lugol’s iodine-enhanced micro-CT improves OSCC DOI 3D measurement, enhances pathological staging accuracy, and aids treatment decisions and prognosis.
Detection of Sarcocystis albifronsi, Eimeria alpacae, and Cystoisospora felis in Eurasian Lynx (Lynx Lynx) in Northwestern China
Authors: Cui Nannan , Wang Shiyi , Wang Ziqi , Wang Huiqian , Lu Xiao bo , Liu Gang , Wang Yuanzhi 
Published: December 2023

Abstract
Background
Eurasian lynx (Lynx Lynx) is widely distributed in various habitats in Asia and Europe, and it may harbor multiple pathogens. Currently, the information on protozoan infection in Eurasian lynx is scarce. In this study, we performed nested polymerase chain reaction (nPCR) analysis to detect intestinal protozoan infection in three dead Eurasian lynxes, in northwestern China.
Methods
Three dead Eurasian lynxes, an adult female (#1), an adult male (#2), and a cub male (#3), were sampled in West Junggar Mountain, the northwestern region of Xinjiang Uyghur Autonomous Region. The intestine samples were analyzed using nPCR. We used primers targeting the cytochrome C oxidase subunit I gene (COI) for detection of Sarcocystis and Eimeria species and those targeting the small subunit 18S ribosomal RNA gene (18S rRNA) for detection of Cystoisospora species. The nPCR-positive products were sequenced, aligned, and phylogenetically analyzed.
Results
Three intestinal protozoa, Sarcocystis albifronsi, Eimeria alpacae, and Cystoisospora felis, were found in three Eurasian lynxes. The intestine sample of Eurasian lynx #2 was co-infected with S. albifronsi and E. alpacae. In addition, C. felis was only found in the intestine sample of Eurasian lynx #3.
Conclusions
To the best of our knowledge, S. albifronsi and E. alpacae were detected in Eurasian lynx for the first time. In addition, C. felis was detected in Eurasian lynx. These findings extend our knowledge of the geographical distribution and host range of intestinal protozoa.
An analysis of transition-resulted goal scoring patterns in football leagues: a comparison of the first 5 rounds and the last 5 rounds prior midway of the season.
Authors: Eusebio Pedro , Prieto-González Pablo , Marcelino Rui 
Published: December 2023

Abstract

Objective: This study investigated the concept of 'game style' in football, focusing on a team's distinctive approach characterized by tactics, formations, and strategies. The objective is to compare goal-scoring patterns related to "non-offensive transition," "set pieces," "offensive transition," and "positive outcomes" across different league groups.
Methodology: The sample comprises 702 football games, categorized into three league groups: Top Leagues, Marginal Leagues, and Emerging Leagues. A total of 2140 goals were analyzed, classifying them into four types: “No Transitions”, “Set Pieces”, “Offensive Transitions (direct), and “Positive Outcomes” of offensive transitions. The study aims to identify relevant differences between two distinct competitive periods, namely "Rounds 1 to 5" and "Rounds Last 5."
Results: The analysis reveals no significant differences in scoring methods between "Rounds 1 to 5" and "Rounds Last 5" across all variables in the analyzed league groups, except for goals conceded by “No Transition” in the Emerging Leagues. Additionally, results indicate that goals resulting from direct offensive transitions and positive outcomes substantially impact the Top Leagues, constituting 54% of the total scoring.
Conclusion: The study emphasizes the importance of establishing and maintaining consolidated game patterns, as demonstrated by the consistent scoring patterns across different league groups. While most leagues show no variations in scoring methods between early and late rounds, attention to goals conceded by “No Transition” in Emerging Leagues is warranted. The prominence of direct offensive transitions and positive outcomes in Top Leagues highlights the relevance of these strategies in the scoring process, emphasizing the need for teams to focus on developing and implementing effective game patterns.
Regional Variations in Italy’s COVID-19 death toll: An Analysis of Excess Mortality and Associated Factors from 2020 to 2021
Authors: Sanmarchi Francesco , Capodici Angelo , Golinelli Davide , Lenzi Jacopo , Zamparini Manuel , Toth Federico , De Girolamo Giovanni , Stoto Michael A. 
Published: December 2023

Abstract
Background
Italy implemented various measures, including lockdowns and a mass vaccination campaign, to address the COVID-19 pandemic. This study aims to describe the temporal and regional impact of these measures on mortality between March 2020 and December 2021, partitioning the time series into five periods.
Methods
We used National Ministry of Health data on COVID-19 mortality, excess mortality (EM), and vaccine uptake, along with survey data. Avertable mortality was calculated as observed EM minus the lowest EM at the macro-regional level for each study period.
Results
In 2020–21, the estimated total EM was 180,169 deaths, with 76.4% officially attributed to COVID-19. This ranged from 13.5% in the South and Islands (June–October 2020) to 140.0% in the Northeast (March–July 2021). Excess and avertable mortality peaked in the North during the first two periods (March 2020 – February 2021) and in the South and Islands thereafter (March–December 2021). Survey data revealed reduced adherence to stay-at-home orders in the North and lower trust in hospitals and reduced vaccine uptake, especially among the elderly, in the South and Islands. After the initial period, 33,587 excess deaths (18.6%) could have been averted if each macro-region had matched the lowest rates observed post-June 2020. An estimated 40.7% of avertable deaths occurred in Southern and Insular Italy, which constitutes 33.7% of the national population.
Conclusions
Due to differential under-reporting, EM estimates offer a comprehensive view of regional and temporal patterns in COVID-19 mortality. The higher EM in northern Italy during the first year of the pandemic might be linked to lesser adherence to control policies, possibly associated with higher private sector employment. The higher EM in the South and Islands post-March 2021, contributing to 40.7% of avertable EM, could be partly explained by the lower vaccination rates in the population age 80 and older, who experienced the highest age-specific mortality rates and lower trust in the healthcare system in this macro-region.
Preparation and electro-catalytic performance of SBA15 modified carbon- supported PtNi catalyst
Authors: Xia Li , Liu Yang , Zhang Sensen , Hu Tiangui , Li Xiang 
Published: December 2023

Abstract
Maximizing catalyst activity and stability while minimizing costs remains a formidable challenge. In this study, we employed the straightforward and easily executed ethylene glycol reduction method to synthesize highly active and stable Pt-Ni alloy catalysts, utilizing SBA15-modified carbon as the supporting material. Subsequent meticulous examinations delved into their physicochemical properties and electrocatalytic activities.Transmission electron microscopy (TEM) analyses unveiled a uniform distribution of PtNi particles on the support, showcasing a narrow particle size distribution centered around approximately 1.91 nm with minimal aggregation. Electrochemical assessments demonstrated that Pt3Ni/SBA15-C outperforms Pt/C, exhibiting 50 and 150 mV higher half-wave potentials (E1/2) and onset potential (Eonset), respectively. Furthermore, our meticulously prepared Pt3Ni/SBA15-C, featuring a cage structure, displayed remarkable stability while sustaining superior catalytic durability under an applied potential of + 0.7 V. These findings underscore the effectiveness of the cage structure catalyst, comprising porous nanoparticles, in ensuring both catalytic activity and stability. The results collectively contribute to advancing our understanding of catalyst design and performance optimization in electrochemical applications.
BrainWave Diagnostics: An Extensive Examination of Determinants of Multiple Neurological Disease from EEG Signals
Authors: jain shraddha 
Published: December 2023

Abstract
BrainWave Diagnostics, an emerging field, leverages electroencephalography (EEG) data for cost-effective and resource-efficient neurological disorder detection. Although EEGs are commonly used for neurological disease detection, their low signal intensity and nonlinear features pose analytical challenges. This review explores the use of high-performance computational tools, machine learning, and deep learning methods in diagnosing a range of neurological disorders, including epilepsy, Parkinson's disease, autism, ADHD, stroke, tumors, schizophrenia, Alzheimer's, depression, and alcohol use disorder. The increasing prevalence of neurological disorders and their resource burden underscores the urgency of these diagnostic advancements. Future research can consider multi-modal approaches, providing practical solutions for neurological disorder detection beyond EEGs, with potential applications in diverse signal analysis domains.
Enhancing Simplified Chinese Poetry Comprehension in LLaMA-7B: A Novel Approach to Mimic Mixture of Experts Effect
Authors: Zhang Yiqun , Chen Xin 
Published: December 2023

Abstract
This study explored the potential of manual augmentation in enhancing the comprehension and translation capabilities of large language models, specifically focusing on the LLaMA-7B model in the context of Chinese poetry. Chinese poetry, with its rich cultural and historical complexities, presents a unique challenge for AI models predominantly trained on modern English datasets. Our research introduced a novel approach by manually augmenting LLaMA-7B, emulating a mixture-of-experts model integration. This method involved integrating specialized linguistic and cultural processing units, which significantly improved the model's ability to interpret the complex tonal patterns, metaphorical richness, and cultural allusions inherent in Chinese poetry. We conducted rigorous evaluations, measuring the augmented model's performance against expert translations and noting a 23% increase in comprehension accuracy and a 37% reduction in semantic hallucinations. Our findings not only demonstrated the efficacy of manual augmentation in bridging the gap between AI capabilities and the demands of classical literary texts, but also opened new avenues for applying similar techniques to other culturally-rich languages. Our study underscored the importance of cultural and contextual awareness in AI language processing, marking a step towards more advanced and culturally sensitive AI models.