bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Intrusion Detection Framework for Multi-Clouds – Iot Environment Using Swarm-Based Deep Learning Classifier
Authors: Nizamudeen Syed Mohamed Thameem 
Published: January 2023

Abstract
In current era, a tremendous volume of data has been generated by the use of web technologies. The association between different devices and services have also been explored to wisely and widely use recent technologies. Due to the restriction in the available resources, the chance of security violation is increasing highly on the constrained devices. IoT backend with the multi-cloud infrastructure to extend the public services in terms of better scalability and reliability. Several users might access the multi-cloud resources that lead to data threats while handling user requests for IoT services. It poses a new challenge in proposing new functional elements and security schemes. In this paper, an intelligent Intrusion Detection Framework (IDF) is introduced to detect network and application-based attacks. The proposed framework has three phases: data pre-processing, feature selection and classification. Initially, the collected datasets are pre-processed using Integer- Grading Normalization (I-GN) technique that ensures a fair-scaled data transformation process. Secondly, Opposition-based Learning- Rat Inspired Optimizer (OBL-RIO) is designed for the feature selection phase. The progressive nature of rats chooses the significant features. The fittest value ensures the stability of the features from OBL-RIO. Finally, a 2D-Array-based Convolutional Neural Network (2D-ACNN) is proposed as the binary class classifier. The input features are preserved in a 2D-array model to perform on the convoluted set of layers. It detects the normal (or) abnormal traffic. The proposed framework is trained and tested on the Netflow-based datasets. The proposed framework yields 95.20% accuracy, 2.5% false positive rate and 97.24% detection rate.
Prediction of People Sentiments on Twitter Using Machine Learning Classifiers During Russian-Ukrainian Conflict
Authors: Baker Mohammed Rashad , Taher Yalmaz Najmaldin , Jihad Kamal h. 
Published: January 2023

Abstract
Social media has become an excellent way to discover people's thoughts about various topics and situations. In recent years, many studies have focused on social media during crises, including natural disasters or wars caused by individuals. This study looks at how people expressed their feelings on Twitter during the conflict between Russia and Ukraine. This study met two goals: the collected data was unique, and it used machine learning (ML) to classify the tweets based on their effect on people's feelings. The first goal was to find the most relevant hashtags about the conflict to locate the data set. The second goal was to use several well-known ML models to organize the tweets into groups. The experimental results have shown that most of the performed ML classifiers have higher accuracy with a balanced dataset. However, the findings of the demonstrated experiments using data balancing strategies would not necessarily indicate that all classes would perform better. Therefore, it is important to highlight the importance of comparing and contrasting the data balancing strategies employed in SA and ML studies, including more classifiers and a more comprehensive range of use cases.
A novel Chongqing index of post-TIPS survival for predicting survival in Chinese cirrhotic patients after transjugular intrahepatic portosystemic shunt: A multicenter, retrospective study
Authors: Mu Zhiyong , Liu Yuyi , Wang Lei , Yang Jinhui , Xiong Wei , Hu Hong , Liu Aimin , An Xuan , Xu Yuqiang , Tian Chuan , Wang Jinneng , Yu Haodong , Wang Jun , Chen Dongfeng , Liu Fuquan , Wen Liangzhi 
Published: January 2023

Abstract
Background & Aims: Transjugular intrahepatic portosystemic shunt is an important method for the treatment of complications related to portal hypertension. However, a prediction model based on Chinese population has not been established. The aim of our study was to develop a prognostic model based on the Chinese population.
Methods: We screened cirrhotic patients received TIPS between January 2014 and December 2021 at 11 hospitals in China and collected the available clinical data of all eligible patients. Using random assignment, patients were divided into training and validation cohorts in a 7:3 ratio. Independent risk factors for prognosis were screened by multivariate Cox regression and were used to develop a nomogram based on the training cohort. Validation cohort data was used to conduct external validation.
Results: A total of 794 patients were recruited, 556 in the training cohort and 238 in the validation cohort. Age, ascites, serum albumin, total bilirubin and serum sodium levels were independent prognostic factors, and these variables were incorporated to establish nomogram scoring model named the Chongqing index of post-TIPS survival (CIPS). The C-indices were 0.753 [0.684-0.812] in the training cohort and 0.786 [0.715-0.857] in the validation cohort. Compared with the Child-Pugh, iMELD, ALBI and FIPS scores, the CIPS showed better prognosis discrimination at 1 and 3 years after TIPS. The CIPS could identify high-risk patients after TIPS implantation with a cutoff point of 149.
Conclusion: The CIPS is more superior to predict 1-year and 3-years survival in Chinese patient cohorts and can identify high-risk patients with poor prognosis after TIPS implantation, which can be used to guide clinical patient management.
Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases
Authors: Lin Yu-Ting , Lin Chin-Sheng , Lee Yung-Tsai , Tsai Dung-Jang , Lou Yu-Sheng , Fang Wen-Hui , Lee Chia-Cheng , Ho Ching-Liang , Wang Chih-Hung , Lin Chin 
Published: January 2023

Abstract

BACKGROUND
Valvular heart disease (VHD) is becoming increasingly important to manage the risk of future complications. Electrocardiographic (ECG) changes may be related to multiple VHDs, and (AI)-enabled ECG has been able to detect some VHDs. We aimed to develop five deep learning models (DLMs) to identify aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation.
METHODS
Between 2010 and 2021, 77,047 patients with echocardiography and 12-lead ECG performed within 7 days were identified from an academic medical center to provide DLM development (122,728 ECGs), and internal validation (7,637 ECGs). Additional 11,800 patients from a community hospital were identified to external validation. The ECGs were classified as with or without moderate-to-severe VHDs according to transthoracic echocardiography (TTE) records, and we also collected the other echocardiographic data and follow-up TTE records to identify new-onset valvular heart diseases.
RESULTS
AI-ECG adjusted for age and sex achieved areas under the curves (AUCs) of >0.84, >0.80, >0.77, >0.83, and >0.81 for detecting aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation, respectively. Since predictions of each DLM shared similar components of ECG rhythms, the positive findings of each DLM were highly correlated with other valvular heart diseases. Of note, a total of 37.5%-51.7% of false-positive predictions had at least one significant echocardiographic finding, which may lead to a significantly higher risk of future moderate-to-severe VHDs in patients with initially minimal-to-mild VHDs.
CONCLUSION
AI-ECG may be used as a large-scale screening tool for detecting VHDs and a basis to undergo an echocardiography.
Exploring the mechanism of Wu Ling San plus flavor for the treatment of diabetic macular edema based on network pharmacology and molecular docking techniques
Authors: Ke Kunmao , An Meixia , Jiang Xiaoyun 
Published: January 2023

Abstract
Aim
To explore the possible mechanism of action of Wu Ling San Plus for the treatment of diabetic macular edema (DME) through network pharmacology and molecular docking.
Methods
DME-related genes were searched in drugbank database, GeneCards database, Online Mendelian Human Genetic (OMIM) database, and TTD database. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was applied to screen for potential chemically active substances and related target proteins in the drug pairs. A “drug-disease target” regulatory network was constructed with Cytoscape (3.7.2) software, and a protein-protein interaction (PPI) network was established by Bisogenet and CytoNCA, followed by GO and KEGG enrichment analysis using the Bioconductor platform and R software. Finally, molecular docking of potential chemi-cally active substances and key targets was performed using MOE soft-ware.
Results
63 compounds were screened from Wu Ling San Plus, in-cluding 71 targets for the treatment of DME, and the PPI core genes were AKT1, JUN, TP53, IL10, VEGFA, IL6, MMP9, CASP3, CCL2, PTGS2, MAPK8; GO biofunctional analysis contained 2143 enrichment results, mainly involving the hypoxic responses, the KEGG enrichment yielded 122 related signaling pathways consisting of the AGE-RAGE signaling pathway, cellular senescence pathway, TNF signaling pathway, IL-17 signaling pathway, C-type lectin receptor signaling pathway, FoxO sig-naling pathway, MAPK signaling pathway, T cell receptor signaling pathway, etc. Molecular docking results indicated that quercetin may have an effect on AKT1, TPP53, VEGFA, IL6, MMP9, CASP3, CCL2, PTGS2, and kaempferol also had a better binding ability to MAPK8.
Conclusion
The treatment of DME with Wu Ling San Plus shows the multi-component and multitarget features of traditional Chinese medicine, which may achieve the management of DME’s developing process through many routes, offering certain insights and a foundation for further research.
Genome-wide analysis of the FIGLA gene in Mammals
Authors: Choudhury Shouhartha 
Published: January 2023

Abstract
Background: The FIGLA or BHLHC8 plays a dominant role in ovary formation and folliculogenesis and controls oocyte maturation and somatic cell function. The FIGLA gene encodes a bHLH domain in the germ cell as an activator and inhibitor of the oocyte. The oocyte-specific gene is necessary for oogenesis, pluripotency, and embryonic growth. FIGLA (POF6) gene preferentially expresses in oocytes and plays a dominant role in germ cell development. The POF6 gene regulates the sexual life rhythm and represents a candidate gene for reproductive symptoms such as hypogonadotropic abnormality, infertility and ovarian failure. A prior ovarian failure is a cause of BHLHC8 (POF6) haploinsufficiency, which breaks the genesis of primordial follicles. So, the oocyte-specific factors regulate attractive targets for fertility.
Objective: The study aimed to investigate whether a human homologous gene is present in other organisms and plays a similar role in ovary growth and fertilization. So, observation of the BHLHC8 gene is the ultimate target for controlling ovarian failure, infertility and germ-cell apoptosis. Therefore, perform powerful bioinformatics and computational techniques and tools for analysis of the BHLHC8 (FIGLA) gene in mammals.
Results: So, investigated mammalian genomes like Homo sapiens, Bos tarsus, Sus scrofa, Pan Troglodytes, and Mus musculus for comparative analysis. The finding data provided evidence of the FIGALPHA gene and its specific domain, motifs, phylogeny, gene expression, chromosome location, and gene network in humans. The observation suggested BHLHC8 (FIGLA) gene is present in all organisms and plays an essential role during development. An experiment in an animal model is required to determine the natural oocyte growth and fertility.
Conclusion: Observation data concluded that the FIGALPHA gene is present in all organisms and plays crucial roles during maturation. The oocyte-specific genes regulate attractive targets to govern ovary growth and fertility. Therefore, germ-specific and other species-specific transcription factors are essential for germ-cell development.
Optimized Feature Selection and Classification of Arabic Speech Disorders: A Case Study of Letter /r/ Difficulties
Authors: Abdo Mohamed S. , Ghanem Ahmed A. , Hammami Nacereddine , Youness Hassan A. , Hassan Abdallah A. 
Published: January 2023

Abstract
The reliable and automatic recognition of speech sound problems is critical for assisting in the early detection and treatment of defective phonological processes in children. This study addresses the issue of speech sound error classification in Arabic children when they mispronounce Arabic words, including the letter r (pronounced /ra/). A determination was made regarding whether a speech sound problem existed when the letter appeared at the beginning, middle, or end of words. The speech signal was characterized by different classifier models using the number of times and frequency features to aid in the automatic diagnosis of speech disorders in children. Utilizing a real-world library of voice recordings, the highest accuracy of 92.4% was achieved using a bagged trees classifier with a combination of effective frequency features under the holdout method.
Nomogram constructions and prognostic analyses for patients with synovial sarcomas resections: A Single Asian Cohort of 179 Cases
Authors: Lin Qiaowei , Sun Zhengwang , Yu Lin , Wang Qifeng , Sun Yangbai , Yan Wangjun 
Published: January 2023

Abstract
Background: Synovial sarcoma (SS) is a relatively rare soft tissue sarcoma. As SS had high potentials of recurrence and metastasis, we designed two nomograms to predict overall survival (OS) and time to recurrence (TTR) for SS patients.
Methods: The data of 179 SS patients underwent curative surgery were extracted from Shanghai Cancer Center, Fudan University. Cox regression analyses were performed to identify independent prognostic factors. Kaplan-Meier curves were used to compare differences in OS and TTR. Nomograms were created using R software and validated by calibration curves and receiver operating characteristic curves.
Results: Kaplan-Meier curves showed that patients with older age, larger tumors, necrosis, vessel infiltration, higher Ki-67, G3 FNCLCC classification and deeper location had shorter OS and TTR than other patients. Multivariate analyses demonstrated that age and tumor size were independent factors for TTR while tumor size and necrosis were independent factors for OS. Five clinicopathological parameters were adopted to build the nomograms for 3- and 5-year OS and TTR. The Area Under Curve of the nomograms at 3- and 5-year OS reached 0.815, 0.84, respectively, while TTR reached 0.766, 0.777, respectively. Calibration curves further demonstrated considerable consistency between the prediction by our nomograms and actual survival.
Conclusions: Age and tumor size were independent factors for TTR while tumor size and necrosis were independent factors for OS. Under such circumstances, we established two accurate and practicable nomograms which could predict 3- and 5-year OS and TTR for SS patients, which might be instructive for modern medical decision-making process.
Fluoride – influenced presynaptic and MAPK – mediated TrkB signaling alterations, induced neurotoxicity
Authors: Gopalan Jayanthi , Venkatramanan Akshaya 
Published: January 2023

Abstract
Fluoride (F), an inorganic substance, is everywhere in the environment. Fluoride exposure is caused mainly by geogenic sources, such as drinking wells and deep soil water. Excess fluoride-containing water usage for many years may cause neurotoxic damage. The mechanism underlying the neurotoxicology of endemic fluorosis remains obscure. Fluoride crosses the blood-brain barrier and accumulates within neurons. In our study, chronic exposure to fluoride-induced epileptogenesis in neuroblastoma (SK-N-SH) cells was followed with tools like Brain-derived neurotrophic factor (BDNF) and Synapsin 1 (SYN 1) protein expression. SK-N-SH cells were incubated with fluoride water (1 mg/L and 6 mg/L) for 24 h in-vitro. Prolonged ingestion of fluoride causes chronic fluorosis. Fluoride exposure reduced cell viability gradually from 48 to 96 h. The standard structure of axon spines and dendritic outgrowth in high fluoride water vanished. TrkB activated MAPK/ERK downstream signaling pathway is triggered by increased BDNF protein expression and decreased SYN 1 protein levels observed in fluoride water incubation. Further 96 hours incubation with fluoride-cleared water increased viability of SK-N-SH cells and a normal expression of BDNF and SYN 1 protein levels, suggests that fluoride-blocked BDNF-TrkB pathway might have been replaced by high-levels expression of BDNF protein where incubation medium contains concomitant lowered levels of fluoride. Hypothesis is that scaffold proteins regained normal expression might have influenced conducted normal excitation and transmission could reduce neurotoxic effect or even might control seizures.
O‎n ‎some ‎inequa‎lities ‎from ‎‎positive ‎‎matrices ‎to‎ ‎sector‎ matrices‎‎‎
Authors: ‎Nasiri‎ Leila , Yang Chaojun 
Published: January 2023

Abstract
Note: Please see pdf for full abstract with equations.
In the present paper, we discuss some inequalities related to sector matrices such as relative entropy, the Kantorovich inequality and Heron inequality. Among other results, we prove that if A ∈ Mn be such that W(A) ⊆ Sθ and 0 < m ≤ ℜA ≤ M. Then
ℜΦ(A−1) ≤ K(h) sec2(θ)ℜΦ−1(A),
where K(h) = (M+m)2/4Mm with h = M/m is the Kantorovich constant.
Government subsidies, cooperation between land and sea enterprises and profit maximization --Data simulation based differential game study
Authors: Wu Shujuan , Liu Xiaohao 
Published: January 2023

Abstract
Government subsidies are a crucial tool for encouraging cooperation between land and sea enterprises, but it is unclear how to quantitatively distribute these subsidies to ensure the best possible level of cooperation and profit maximization for both. The Nash non-cooperative game, master-slave game, and cooperative game are the three different cooperation modes that are used in the differential game model of government subsidies, which is built using the dynamic framework theory. Simulations are run using the data from two different enterprises, and it is discovered that:(1) Prior to government subsidies, the cooperation efforts and profits of land and sea businesses are at their highest levels under the cooperative game, whereas the profit goal of marine businesses is at its highest level under the master-slave game. (2) After government subsidies, the cooperative efforts of all three cooperative modes are the same, the target profit of land enterprises is maximized by the Nash non-cooperative game, and the target profit of sea businesses is maximized by the master-slave game. The three parties—the sea, the land, and the government—have different demands for the cooperative efforts. (3) Although government cost subsidies can boost the profit maximization of sea and land enterprises, the competitiveness of sea and land enterprises is instead reduced due to the rise in environmental costs, and the financial burden of the government continues to rise, which is not conducive to social development. Thus, it is important to take into account all three parties—the sea, the land, and the government—and it is crucial that government cost subsidies use their subsidy strategy in a way that is reasonable given the circumstances. Government subsidies that boost overall revenue may also influence future subsidy policies.
Biosurfactants from marine bacteria to control anthracnose in Mango Fruits
Authors: Holguín-Sterling Laura C. , Páez Alberto R. , Patiño Albert D. , Gómez-León Javier , Blandón Lina Marcela 
Published: January 2023

Abstract
Anthracnose is one of the most severe post-harvest diseases in mango fruits. Species of the Colletotrichum fungus cause it, affecting the quality of the fruit and, consequently, its commercialization. The current disease handling is based on frequent spraying of synthetic fungicides. However, their extensive and intensive use has disturbed the ecological balance of microorganisms present in the habitat, thus resulting in the development of resistant pathogenic strains, pollution of the environment, and risks to human health. As a handling alternative, extracts from six marine bacteria were evaluated against four Colletotrichum strains. The bacteria Bacillus velezensis INV FIR31, Bacillus subtilis INV FIR48, and Bacillus safensis INV FIR26 inhibited the mycelial growth of the strains by 40, 34, and 21%, respectively. Then, the antifungal activity of the extracellular extract BS57 obtained from B. velezensis INV FIR31 was evaluated in mango fruits of the Hilaza variety inoculated with Colletotrichum strains, obtaining disease percentages control of 42, 89, 91, and 92%. Finally, the lipopeptide Bacillomycin D in the BS57 extract was identified, indicating it was possibly responsible for the antifungal activity. Additionally, the toxicity tests of the extract show low toxicity. The results suggest that the extract obtained from the marine bacterium Bacillus velezensis INV FIR31 is a good resource for developing effective biopesticides that are environmentally friendly and safe for the consumer.
Hybrid Method for Constrained Bayesian Optimization
Authors: Chowdhury Raju , Upadhye Neelesh S 
Published: January 2023

AbstractIn this article, we propose a hybrid Bayesian Optimization framework using an indicator function to solve constrained optimization problems efficiently. In our hybrid method, the revised acquisition function is used to effectively guide the search that explores both the feasible and infeasible regions.We demonstrate the proposed method on five test problems, including two black-box problems, to evaluate the performance of our hybrid method and compare the results to hybrid methods based on Augmented Lagrangian and Log-barrier.