bluuebunny/crossref_metadata_2025 huggingface dataset:
Pro-resolving and pro-inflammatory fatty acid-derived mediators in sputum of stable state bronchiectasis patients
Authors: Terranova Leonardo , Risé Patrizia , Gramegna Andrea , Pinna Christian , Agostoni Carlo , Syrén Marie-Louise , Turolo Stefano , Marchisio Paola , Amati Francesco , Aliberti Stefano , Sala Angelo , Blasi Francesco
Published: November 2022

Background: Bronchiectasis is characterized by neutrophilic inflammation and frequent exacerbations often associated with infections. Lipid mediators play critical roles in the inflammatory response, the balance between anti-inflammatory and pro-inflammatory mediators could drive to chronic inflammation. The aim of this study was to evaluate the metabolite of docosahexaenoic acid and arachidonic acid in sputum of adults with bronchiectasis defining their associations with clinical data, bacterial load and neutrophil elastase.
Methods: An observational, cross-sectional study was conducted at the bronchiectasis program of the Policlinico Hospital in Milan, Italy, where patients were enrolled. Active neutrophil elastase was measured by enzyme-linked immunosorbent assay, pro-resolving and pro-inflammatory fatty acid-derived mediators were evaluated by mass spectrometry and respiratory pathogens were carried out through real-time PCR. Analysis were performed on sputum collected during stable state and clinical data were also collected.
Results: Levels of pro-inflammatory mediators derived from arachidonic acid metabolism showed association with neutrophil elastase, were proportional to Pseudomonas aeruginosa identifications and were linked with radiological gravity index, while the concentrations of pro-resolution mediators derived from docosahexaenoic acidwere associated with a better health status highlighted by the inverse correlation with radiological gravity index, bacterial infections and sputum volume production.
Conclusion: Taking into account the clinical need to identify treatable traits in bronchiectasis useful to reduce exacerbation, lung infections and inflammatory reactions, could be helpful understand the role of pro-inflammatory and pro-resolving mediators derived from FA metabolisms in the modulation of these reaction. These information could be used to plan a personalized approach to try to reduce the symptoms of the disease.
Fermi liquid-like behaviour of cuprates in the pseudogap phase simulated via T-dependent electron-boson spectral density
Authors: Hwang Jungseek , Park Hwiwoo
Published: November 2022

We investigated the temperature- and frequency-dependent optical scattering rates in the pseudogap phase of cuprates using model pseudogap and electron-boson spectral density (EBSD) functions. We obtained the scattering rates at various temperatures below and above a given pseudogap temperature using a generalized Allen’s (or Sharapov’s) formula, which has been used to analyze the measured optical spectra of correlated electron systems with a non-constant density of states at finite temperatures. The pseudogap and EBSD functions should be temperature dependent to simulate the Fermi liquid-like behaviour of underdoped cuprate systems observed in optical studies. Therefore, the observed Fermi liquid-like behaviour can be understood by considering the combined contribution from the T-dependent EBSD function and the T-dependent pseudogap. We expect that our results will aid in understanding the Fermi liquid-like optical response in the pseudogap phase and in revealing the microscopic pairing mechanism for superconductivity in cuprates.
Exploring the mediation of DNA methylation across the epigenome between childhood adversity and First Episode of Psychosis – findings from the EU-GEI study
Authors: Alameda Luis , Liu Zhonghua , Sham Pak , Monica AAS , Giulia Trotta , Victoria Rodriguez , Forti Marta di , Simona Stilo , Radhika Kandaswamy , Arango Celso , Arrojo Manuel , Bernardo Miquel , Bobes Julio , de Haan Lieuwe , Del-Ben Cristina , Gayer-Anderson Charlotte , Lucia Sideli , Jones Peter , Jongsma Hannah , Kirkbride James , Cascia Caterina La , Lasalvia Antonio , Tosato Sarah , Llorca Pierre Michel , Menezes Paulo , Os Jim van , Diego Quattrone , Rutten Bart , Santos José , Sanjuan Julio , Selten Jean-Paul , Szöke Andrei , Tarricone Ilaria , Tortelli Andrea , Velthorst Eva , Morgan Craig , Dempster Emma , Hannon Eilis , Burrage Joe , Mill Jonathan , Murray Robin , Wong Chloe
Published: November 2022

Studies conducted in psychotic disorders have shown that DNA-methylation (DNAm) is sensitive to the impact of Childhood Adversity (CA). However, whether it mediates the association between CA and psychosis is yet to be explored. Epigenome-wide association studies (EWAS) using the Illumina Infinium-Methylation EPIC array in peripheral blood tissue from 366 First-episode of psychosis and 517 healthy controls was performed. Polyvictimization scores were created for abuse, neglect, and composite adversity with the Childhood Trauma Questionnaire (CTQ). Regressions examining (I) CTQ scores with psychosis; (II) with DNAm EWAS level and (III), then between DNAm and caseness, adjusted for a variety of confounders were conducted. Divide-Aggregate Composite-null Test for the composite null hypothesis of no mediation effect was conducted. Enrichment analyses were conducted with missMethyl package and the KEGG database. Our results show that CA was associated with psychosis (Composite: OR = 3.09; p = <0.001; abuse: OR = 2.95; p<0.001; neglect: OR = 3.25; p=<0.001). None of the CpG sites significantly mediated the adversity-psychosis association after Bonferroni correction (p<8.1x10-8). However, 28, 34 and 29 differentially methylated probes associated with 21, 27, 20 genes passed a less stringent discovery threshold (p<5x10-5) for composite, abuse, and neglect respectively, with a lack of overlap between abuse and neglect. These included genes previously associated with psychosis in EWAS studies, such as PANK1, SPEG TBKBP1, TSNARE1 or H2R. Downstream gene ontology analyses did not reveal any biological pathways that survived false discovery rate correction. Although at a non-significant level, DNAm changes in genes previously associated with schizophrenia in EWAS studies may mediate the CA-psychosis association. These results and associated involved processes such as mitochondrial or histaminergic dysfunction, immunity or neural signaling require replication in well-powered samples. Mediating genes were not associated with abuse and neglect, tentatively suggest differential biological trajectories linking CA subtypes and psychosis.
Affinity purification, identification and biochemical characterization of Gamma-Glutamyl Transpeptidase, a membrane anchored enzyme of Gigantocotyle explanatum
Authors: Farhat Faiza , Wasim Sobia , Rehman Lubna , Abidi S. M. A.
Published: November 2022

Gamma-glutamyl Transpeptidase is an enzyme that facilitates the transfer of glutamyl groups from glutamyl peptides to other peptides or water. Additionally, it also participates in important processes such amino acid transport, cellular redox control, drug detoxification, apoptosis, and DNA fragmentation in a various organism. In the present study, GGT activity in Gigantocotyle explanatum was examined in order to characterize the enzyme in the helminth system. GGT is isolated using membrane solubilization and purified through affinity column chromatography (Con-A Sepharose column). Km and Vmax values, as well as the optimal pH, optimal temperature, and incubation period, are also determined using enzyme kinetics. The hetero-dimeric property of the enzyme is demonstrated by the purified GGT, which yielded two subunits of 65.5 and 55 kDa. The optimal pH and temperature are found to be 8.0 and 37°C, respectively. While assessing the optimal incubation time of the enzyme, it was observed that the purified GGT not only retained its functional integrity up to 15 min but also reflected considerable thermostability at higher temperatures, by retaining 78% and 25% of its initial activities at 50°C and 60°C, respectively. 1 mM concentration of 6-Diazo-5-Oxo Nor-isoleucine (DON), a specific inhibitor of GGT, completely abolished GGT activity. These results suggest that GGT in these worms is a catalytically active enzyme with distinguishing characteristics that can be used for further study to comprehend its function in amphistome biology and in host-parasite relationships, especially since the potential therapeutic candidacy of the GGT enzyme has already been indicated in these groups of organisms.
Design of Edge Cloud Computing Recognition System for Intelligent Needs from the Perspective of Sports Psychology
Authors: Li Shuang , Liu Yu
Published: November 2022

This paper intends to meet society’s demand for intelligent recognition system design and improve the performance of the behavioral action recognition system. Based on the previous research, the behavior recognition system is optimized. The edge Cloud Computing (CLO) technology is introduced. Also, the idea of sports psychology is integrated. The overall scheme of the behavior recognition system is designed. The accuracy, precision, and recall of the recognition system in different behaviors are analyzed by training the data set. In addition, the cloud-based behavior recognition design model is compared with other algorithms to analyze the algorithm advantages. Finally, the training and validation tests are performed on the training set of expression images using the behavior recognition system mode. It is found that the behavior recognition system model can show high accuracy in different environments, all above 80%. The results show that the edge CLO recognition system that meets intelligence needs has good accuracy, precision, and recall in both action recognition and image expression recognition. The recognition effect is the best. This paper aims to provide some ideas for the research on intelligent behavior recognition and put forward some references for the field expansion of edge CLO technology applications. Besides, the intelligence level of the behavior recognition system is improved through software design.
A simplified model of tethered projectile systems wrapping around targets in space and a preliminary capture scheme based thereon
Authors: Ma Hongzhi , Lan Ding , Wang Tao , Wang Fude
Published: November 2022

The Euler-Eytelwein equation indicates that the tension from one end of the rope to the other end decays exponentially with the wrapping angle after wrapping around a target object, and the tensions at two ends can differ by several orders of magnitude. The ability to scale the force magnitude of this wrapping structure may be exploited for space captures. This paper simplifies the modeling of the actual scene of space capture, analyzes the kinematic characteristics of the wrapping process of tethered projectile systems, and obtains the trajectory equation of the projectile. Carrying out the force analysis of the element, forces acting on the satellite and the target object under different friction coefficients are obtained. Finally, considering two constraints of rope tension and wrapping time, as well as the number of wrapping turns for safe, a design scheme of projectile velocity and initial rope length required for successful capture is proposed.
Non-Autonomous Maximal Regularity Under Besov Regularity in Time
Authors: achache Mahdi
Published: November 2022

We consider the maximal regularity problem for non-autonomous Cauchy problems u′(t) + A(t)u(t) = f (t) t-a.e., u(0) = u0. Each operator A(t) arises from a time depending sesquilinear form a(t) on a Hilbert space H with constant domain V. We prove maximal Lp-regularity result for p ≤ 2 under min-imal regularity assumptions on the forms. Our main assumption is that (A(t))t∈[0,τ ] arepiecewise in the Besov space Bp1/2, 2 p with respect to the variable t. This improves previouslyknown results. We give three examples which illustrate our results.
Mathematics Subject Classification (2010): 35K90, 35K45, 47D06.
Multi-omics characterization of a scoring system to quantify hypoxia patterns in patients with head and neck squamous cell carcinoma
Authors: peng cong , Ye Huiping , Li Zhengyang , Yang Wen , Yi Zhuguang , Duan Xiaofeng
Published: November 2022

The 5-year survival rate of patients with head and neck squamous cell carcinoma (HNSCC) remains <50% due to risk of the recurrence and metastasis. Hypoxia patterns are a hallmark of HNSCC that are associated with its occurrence and progression. However, the precise role of hypoxia during HNSCC, such as the relationship between hypoxia, tumor immune landscape and cell communication orchestration remains largely unknown. The current study integrated data from bulk and single-cell RNA sequencing analyses to define the relationship between hypoxia and HNSCC. First, a scoring system named the hypoxia score (HS) was constructed based on hypoxia-related genes (HRGs) expression. The survival outcomes, stromal/immune/Estimate scores, responses to targeted inhibitors, and chemotherapeutic, and immunotherapy responses were distinct between a high HS group and a low HS group. Single-cell datasets showed different distributions of HS in immune cell populations. Furthermore, HLA-DPA1/CD4 axis was identified as a unique interaction between CD4+ T Conv and pDC cells. These findings may enhance the understanding of hypoxia characteristics associated with HNSCC.
Validity and Reliability of the Turkish Version of UPPS-P Impulsive Behavior Scale for Children (UPPS-P-C)
Authors: Tekeoğlu Uğur , Çöp Esra
Published: November 2022

Background
In this study we aimed to examine the Turkish validity and reliability of the UPPS-P Impulsive Behavior Scale for Children (UPPS-P-C) and to investigate whether there is a relationship between the UPPS-P-C subscales and Attention Deficit Hyperactivity Disorder (ADHD).
Method
The clinical sample of the study consisted of 50 children which are aged 10–14 with ADHD who applied to the Ankara City Hospital Child Psychiatry Clinic and did not receive treatment for at least 1 month. The community sample consisted of 525 children and adolescents. They were selected from the city of Sinop and their ages ranged from 10 to 14 years, all of whom were in middle school (5th to 8th grade). UPPS-P-C and Strengths and Difficulties Questionnaire (SDQ) – parent form were used in the study.
Results
Factor analysis showed that the five-factor model better explained the data. When the relationships between the subscales of the scale were examined, all relationships were found to be statistically significant. There was a lack of premeditation and lack of perseverance that had the highest ability to distinguish children with ADHD from the UPPS-P-C subscales. In the linear regression analysis, the model we tried to explain in the SDQ total and subscale scores with the UPPS-P-C subscale was found to be significant. The Cronbach α coefficient was found to be 0.894 for the UPPS-P-C scale. When the correlation between the total and subscales of the test and retest was examined, the Intra class Correlation Coefficient (ICC) was 0.782 and 0.771–0.897, respectively.
Discussion
Our findings show that the Turkish version of the UPPS-P-C has good validity and reliability and is successful in screening for features related to impulsivity. It has been shown that the UPPS-P-C scale can be used for symptom profiling and severity assessment rather than for solely diagnostic purposes.
On Feature Selection Algorithms for Effective Botnet Detection
Authors: Afroz Meher , Ibnath Muntaka , Rahman Ashikur , Sultana Jakia , Rab Raqeebir
Published: November 2022

The threats of botnets are becoming a growing concern infecting more and more computers every day. Although botnets can be detected from their behavioral patterns, it is becoming more challenging to differenti-ate the behavior between the malicious traffic and the legitimate trafficas with the advancement of the technologies the malicious traffics are fol-lowing the similar behavioral patterns of benign traffics. The detectionof malicious traffic largely depends on the traffic features that are beingused to feed in the detection process. Selecting the best features for effec-tive botnet detection is the main contribution of this paper. At the verybeginning, we show the impact of different features on botnet detectionprocess. Then we propose several heuristics to select the best featuresfrom a handful of possible features. Some proposed heuristics are trulyfeature-based and some are group-based, thus generating different accu-racy levels. We also analyze time complexity of each heuristic and providea detailed performance analysis. As working with all combinations of alarge number of features is not feasible, some heuristics work by groupingthe features based on their similarity in patterns and checking all combi-nations within the groups of small number of features which improves thetime complexity by a large margin. Through experiments we show the efficacy of the proposed feature selection heuristics. The result shows thatsome heuristics outperform state-of-the-art feature selection algorithms.
Mitochondrial lipid peroxidation and microsomal drug-metabolizing enzyme activity of rat hepatotoxicity under heavy metals from slag waste exposure
Authors: Mu Haishuo , Wan Wangjun , song Jingwu , Kuang Rong , Deng Tongle
Published: November 2022

Heavy metals from slag waste (HMSWs) have been a long-term concern around the world, posing serious environmental and visceral toxicity, especially hepatotoxicity. Investigating the leaching behavior and hepatotoxicity of HMSWs is of great significance. Based on the toxicogenomic analysis, the targets and related signaling pathways of heavy metal-induced liver injury were predicted, and the effects of different HMSWs on mitochondrial lipid peroxidation injury and microsomal drug-metabolizing enzyme activities in rats were experimentally explored. The results showed that different heavy metals might have the function of interfering with physiological processes such as oxidative stress, cell death, and energy metabolism regulation in vivo, and participate in the regulation of HIF-1 signaling pathway, peroxisomes, drug metabolism-cytochrome P450, ferroptosis, and other signaling pathways. HMSWs exposure caused weight loss, and significantly increased lactate dehydrogenase (LDH), malondialdehyde (MDA), alanine transaminase (ALT), and aspartate transaminase (AST) in different groups of rat liver, suggesting the presence of mitochondrial lipid peroxidation damage. Meanwhile, the activities of superoxide dismutase (SOD) and mitochondrial membrane potential (MMP) in the liver were significantly decreased, and microsomal Cytochrome P450 1A2 (CYP1A2) and 3A1 (CYP3A1) enzyme activities were induced, predicting the involvement of the microsomal drug-metabolizing enzymes. These results indicated that metabolic interplay between microsomes and other subcellular organelles including mitochondria and peroxisome could be involved in heavy metals-induced liver injury.
Factors impairing exclusive breastfeeding initiation in women who received labor neuraxial analgesia: A single-center retrospective observational study in Japan
Authors: Hirai Aki , Higuchi Misako , Wakabayashi Miho , Yagi Shigetaka , Minami Sawako , Ino Kazuhiko , Kawamata Tomoyuki
Published: November 2022

Background
Breastfeeding is beneficial for both the mother and infant. However, the factors impairing initiation of exclusive breastfeeding have not been sufficiently investigated in women that received labor neuraxial analgesia. This study aims to clarify the rate of successful initiation of exclusive breastfeeding in women that received labor neuraxial analgesia in our hospital, and any factors impairing it at one month postpartum.
Methods
We retrospectively reviewed the 376 women who had received labor neuraxial analgesia between January 2011 and May 2022. Univariate and multivariate logistic regression analyses were performed to determine factors influencing exclusive breastfeeding.
Results
The rate of exclusive breastfeeding at one month in women who received labor neuraxial analgesia was 43.1%. Exclusive breastfeeding was shown to have univariate association with multiparity (P = 0.0001), second stage of labor (P = 0.046), oxytocin use (P < 0.0001), vacuum extraction delivery (P = 0.001), amount of bleeding (P = 0.027), and neonatal birthweight (P = 0.010). Multivariate logistic regression analysis revealed that oxytocin use and vacuum extraction delivery were mother-related factors and lower birthweight was an infant-related factor that were significant predictors of impairment of the initiation of exclusive breastfeeding at one month after delivery.
Conclusion
Oxytocin use and vacuum extraction delivery as maternal factors and lower birthweight as an infant factor were shown to be a significant predictors of impairment of the initiation of exclusive breastfeeding at one month after delivery.
Echocardiographic assessment of left cardiac structure and function in ART-naïve people living with HIV/AIDS
Authors: Hu Xing , Zhang Yuan , Zhang Tong , Li Weihua , Han Jing , Zhang Xuhui , Meng Fankun
Published: November 2022

Background: Patients with human immunodeficiency virus (HIV) are at a significantly higher risk of cardiovascular disease (CVD) compared to HIV-negative people. CVD has become one of the leading causes of death from non-acquired immune deficiency syndrom (AIDS)-related events in people living with HIV/AIDS (PLWHA). Left heart dysfunction is the most common cardiac complication in PLWHA, and diastolic dysfunction is an important predictor of cardiovascular events. The aims of this study were 1) to detect changes in left cardiac structure and function in antiretroviral therapy (ART)-naive PLWHA using echocardiography; and 2) to investigate the risk factors for the development of left ventricular diastolic dysfunction (LVDD) in ART-naive PLWHA.
Methods: We retrospectively included 105 ART-naïve PLWHA and included 90 healthy subjects as controls to compare the differences in left heart structure and function between the two groups. Univariate and multifactorial logistic regression were employed to explore the risk factors of the development of LVDD in ART-naive PLWHA.
Results: The left ventricular end-diastolic internal diameter (LVEDD), left ventricular mass index (LVMI), and left atrial volume index (LAVI) were significantly greater in PLWHA than in controls (p＜0.05). The E/A ratio, lateral e' velocity, and mitral deceleration time (DT) were significantly lower in PLWHA than in controls (p < 0.05). Average E/e' ratio was significantly higher in PLWHA than in controls (p < 0.05). Left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were not significantly different between PLWHA and controls (p＞0.05). Multifactorial logistic regression analysis showed that age, body mass index (BMI), and CD4+ count < 200 cells/μL were independent influencing factors for LVDD in ART-naive PLWHA (OR=1.781, 1.228, 3.683, p＜0.05).
Conclusions: Left ventricular systolic function did not differ between PLWHA and controls, and left ventricular diastolic function was lower in PLWHA than in controls. Age, BMI, and CD4+ count were independent factors affecting LVDD in ART-naive PLWHA.
Trial registration: ChiCTR1900021008，2019/01/24
Transcriptome analysis reveals vimentin-induced downregulation of cell-cell associations augments cancer cell migration
Authors: Usman Saima , Jamal Ahmad , Bushaala Antesar , Waseem Naushin H , Al-Dehlawi Hebah , Yeudall Andrew , Teh Muy-Teck , Tummala Hemanth , Waseem Ahmad
Published: November 2022

Background Vimentin is a type III intermediate filament (IF) protein, whose expression correlates with advanced metastatic cancer, reduced patient survival and poor prognosis across many cancers. During EMT-induced metastasis when vimentin begins to express, the epithelial characteristics are lost, and cell motility is augmented. The molecular bases for these changes are not well defined. Methods Ectopic expression of vimentin was carried in MCF-7 using spinfection of retroviruses. shRNA was used to knockdown vimentin in vimentin overexpressing MCF-7 and MDM-MB-231 cells, which express vimentin endogenously. The transcriptome profiling was carried out by RNA-Seq and validated by qPCR. Protein expression was measured by western blotting. Effect of vimentin on MCF-7 was determined by cell proliferation, migration and adhesion assays. Results Vimentin expression elicited a change in cell shape by significantly decreasing major axis, major axis angle and increasing cell migration, with no change in cell proliferation. Vimentin suppresses expression of major keratin genesKRT18,KRT19andKRT8. Transcriptome-coupled GO and KEGG analyses revealed that vimentin-affected genes were linked to either cell-cell/cell-ECM or cell cycle/proliferation specific pathways. Using shRNA mediated downregulation of vimentin in two cell types; MCF-7FV (ectopically expressing vimentin) and MDA-MB-231 (endogenously expressing vimentin), we identified 13 vimentin-responsive protein encoding genes common in both approaches and two long non-coding RNAs,LINC00052andC15ORF9-AS1. Eight of these gene products CDH5, AXL, PTPRM, TGFBI, CDH10, FOXM1, BCL2 and NES were associated with cell-cell and cell-ECM interactions, E2F1, FOXM1 and CDC45 were in the cell proliferation group and the rest FSD1, BCL2, KIF26A and WISP2 were outside the two groups. Interestingly, downregulation of CDH5 significantly increased MCF-7 cell migration. Furthermore, vimentin expression in MCF-7 reduced nuclear area, altered expression of lamins, which was mostly reversed after its downregulation. Conclusion Collectively, we demonstrate, for the first time, that vimentin expression in cancer cells downregulates genes maintaining cell-cell junctions resulting in increased cell migration. Furthermore, this is the first report linking vimentin expression with LINC00052, which is dysregulated in many cancers.
Analyzing Noise Robustness of Cochleogram and Mel Spectrogram Features in Deep Learning Based Speaker Recogntion
Authors: Lambamo Wondimu , Srinivasa Ramasamy , Jifara Worku
Published: November 2022

The performance of speaker recognition is very well in a clean dataset or without mismatch between training and test set. However, the performance is degraded with noise, channel variation, physical and behavioral changes with the speaker. The studies confirmed that the features which represent speech in the Equal Rectangular Band (ERB) scale are more robust than Mel Scale at low Signal to Noise Ratio (SNR) level. Gammatone Frequency Cepstral Coefficient (GFCC) which represents speech in ERB scale is widely used in classical machine learning based speaker recognition at noisy conditions. Recently, deep learning models are widely applied in speaker recognition and show better performance than classical machine learning. Previous deep learning based speaker recognition models used Mel Spectrogram as an input rather than hand crafted features. However, the performance of Mel spectrogram drastically degraded at low SNR level because Mel Spectrogram represents speech in Mel Scale. Cochleogram is another important input to develop deep learning based speaker recognition models. Cochleogram represents speech in ERB scale, which is more robust at low SNR level. However, none of the studies used the Cochleogram feature to develop deep learning based speaker recognition models. In addition, none of the studies conduct analysis of noise robustness of Cochleogram and Mel Spectrogram features in speaker recognition using deep learning. In this study, we conducted an analysis of noise robustness of Cochleogram and Mel Spectrogram features in speaker recognition by using additive noises (such as: babble, street and restaurant noises).The train-clean-100 part of the LibriSpeech dataset, which consists of 251 speakers (126 male and 125 female speakers) and 28,539 utterances is used for the experiment. CNN model is used for training and classification of speakers into different classes. The evaluation results show that Cochleogram is more robust than Mel Spectrogram at low SNR level. Both Cochleogram and Mel Spectrogram features show approximately equal accuracy at high SNR and without additive noise. In conclusion, the Cochleogram feature improves performance of deep learning based speaker recognition in noisy conditions.
Application of Big Data Analysis and Cloud Computing Technology
Authors: Zhang Jinfang , Li Yajuan , Zhang Chunqian
Published: November 2022

With the swift growth of computer science, technologies such as big data and artificial intelligence are widely used in various fields of modern society. The types of network equipment and the scope of network coverage have also increased rapidly. While the network brings convenience to people, more attention must be paid to the security of the network platform. The purpose is to safely and effectively manage the current rapidly growing Internet data and improve the ability to detect abnormal network behaviors. Combining big data technology and machine learning (ML), the application of big data analysis and cloud computing technology for network security are studied. Firstly, the data collection technology of abnormal network behavior is introduced, and the Flume data collection component and Kafka distributed technology are discussed. Secondly, the data processing process and corresponding algorithm processing of abnormal network behavior are analyzed, including ML framework and stream processing technology. Finally, the model of network abnormal behavior detection based on big data is constructed, and compared with the related model based on the decision tree and random forest (RF) algorithm, and verified by experiments. The verification results reveal that among the 42 attack types against the dataset, the detection accuracy of network abnormal behavior by big data is 96.4%, and the false positive rate is 2.23%, which is higher than that of decision tree and RF algorithm. This experimental study denotes that the network abnormal behavior detection technology of big data based on the ML framework can effectively improve the type and efficiency of network abnormal behavior detection, and has certain reference significance for improving network security management and control capabilities.
Research on Martial Arts Cultural Resource Management Strategy Based on Edge Cloud Computing System
Authors: Xie Xiaoqing , Tan Fei
Published: November 2022

Edge Cloud Computing has only recently begun to gain popularity, there are not many uses for it in China's educational system. The primary characteristic of edge cloud computing is the utilization of virtualization to combine different resources including software and hardware and make them available to consumers online. The implementation of multimedia technology has considerably enriched the curriculum, revitalized the learning environment, and increased the effectiveness of instruction. A significant opportunity for reforming martial arts education is the use of cloud computing technologies in college-level martial arts instruction. This paper primarily examines the demerits in how aerobics is now taught in Chinese colleges and universities, using the teaching of martial arts as an instance. The study has implemented edge cloud computing system for analyzing resource management strategy in martial arts. The strategy's application may lead to some clarity for university martial arts instruction.
Integrating Artificial Intelligence Technology into Ideological and Political Education Innovation by Intelligent Edge Cloud Computing
Authors: Zheng Li
Published: November 2022

The new generation of Artificial Intelligence (AI) technologies, such as big data and natural language processing, have deeply affected all areas of social life. Ideological and political education (IPE) also faces development opportunities and negative impacts. AI should be used for IPE transformation strategies. The main solution to the limitation of educational places is online teaching, but the main problem is how to solve the viewing experience of webcast, and how to assist students in consolidating after-school knowledge. This paper aims to improve the live broadcast through edge cloud computing, and use the automatic marking system to assist students to build an overall knowledge system framework. Firstly, theoretical knowledge such as edge cloud computing, ideological education status, deep learning, Long Short-Term Memory ( LSTM ) and attention mechanism are further sorted out. The key technology of the automatic marking system of ideological and political knowledge points has been deeply studied. This paper focuses on extracting and representing specific information on ideological education subject issues to propose an automatic marking system for ideological and political knowledge points based on deep learning. Real collected data is used for some tests and applications. The test results show that the system has the highest accuracy when the convolution kernel size is 3, and the number is 120. The model's accuracy using the max pooling method is higher than that of the average pooling model. Different models are compared, and the accuracy of the created LSTM-Attention model is relatively higher. In the self-built question bank, the marking accuracy of ideological and political knowledge points reaches 85.2%. This paper hopes to improve the teaching experience of online ideological and political education. The designed automatic labeling system can quickly help students summarize the knowledge they have learned into the existing system to form a framework and alleviate the imbalance of educational resources.
College Physical Education Curriculum and Teaching Management Supported by Edge Cloud Computing and Deep Learning Technology
Authors: Zhao Jinkun , Zhang Liangyu
Published: November 2022

The physical education (PE) curriculum has important practical significance for contemporary college students and should be widely concerned and studied. The college PE curriculum and teaching management should be constantly improved and optimized to meet the diversified needs of college students for the PE curriculum in the new era and make the college PE curriculum a critical part of a college education. The methods of literature, questionnaire, and teaching experiment are adopted. Based on the deep learning technology, this exploration applies the flipped classroom teaching mode to the college PE curriculum, explores the impact of this teaching mode on the teaching effect, and provides a reference for the reform of the PE curriculum and the research of teaching management. Edge cloud computing technology has the advantages of multi-user sharing and resource expansion. Therefore, starting from the resource scheduling and management strategy of edge computing tasks, the research further optimizes the management strategy of physical education courses by migrating mobile data to the cloud data processing center. First, the problems existing in college PE at this stage are explored. Next, the PE curriculum and learners are analyzed to understand the factors affecting deep learning to better optimize and improve the teaching process. Finally, the objectives, contents, environment as well as evaluation of college PE teaching are studied to achieve the purpose of deep learning. The final conclusion shows that the flipped classroom teaching mode on the basis of deep learning has a significant teaching effect. It can enhance students' physical quality, improve their motivation for autonomous learning, and improve their understanding and cognitive level, that is, it can achieve the goal of promoting students' deep learning.
Adaptive Query Compilation in Graph Databases
Authors: Baumstark Alexander , Jibril Muhammad Attahir , Sattler Kai-Uwe
Published: November 2022

Compiling database queries into compact and efficient machine code has proven to be a great technique to improve query performance and to exploit characteristics of modern hardware. Particularly for graph database queries, which often execute the same instructions for processing, this technique can lead to an improvement. Furthermore, compilation frameworks like LLVM provide powerful optimization techniques and support different backends. However, the time for generating and optimizing machine code becomes an issue for short-running queries or queries which could produce early results quickly.In this work, we present an adaptive approach integrating graph query interpretation and compilation. While query compilation and code generation are running in the background, the query execution starts using the interpreter. As soon as the code generation is finished, the execution switches to the compiled code. Our evaluation shows that autonomously switching execution modes helps to hide compilation times and additionally the additional latencies of the underlying storage.
WITHDRAWN: Emotional Brain activity Evaluation in Diabetes mellitus type 2: A case report
Authors: Khalifa Samar
Published: November 2022

Diabetes is one of the major diseases that affects the nervous system of the body either in early or delayed age. The brain activity is affected in some manners during the affection of the body with diabetes as the signals of the blood impulses to the brain can cause unorganized brain activity. This paper reports the activity of the brain during different activities monitoring emotional distress and mood changes on a type 2 diabetes mellitus patient using EEG device and EMOTIV program.
Long-term adaptation and short-term acclimation to high-altitudes in Tibetan Partridges (Perdix hodgsoniae)
Authors: Lamichhaney Sangeet , Palacios Catalina , Wang Pengcheng , Wang Nan , Brown Megan , Capatosto Lukas , Du Juan , Jiang Jiahu , Zhang Qingze , Dahal Nishma
Published: November 2022

Short-term phenotypic plasticity and long-term genetic adaptation are two key evolutionary processes that mediate organismal persistence in a new environment. But generally, there are few vertebrate systems where the molecular architecture of such plastic and genetic changes has been simultaneously characterized. Birds residing across elevational gradients are known to thrive in rapid and long-term environmental stimuli, demonstrate quantifiable plastic and adaptive traits, and thus can be a suitable model system to study molecular mechanisms of phenotypic plasticity and genetic adaptation. Here, we studied three species from the genus Perdix (Phasianidae, Galliformes): Tibetan Partridge (Perdix hodgsoniae), Daurian Partridge (Perdix dauurica), and Grey Partridge (Perdix perdix) by using an integrative approach of population and comparative genomics, transcriptomics, and field-based transplantation experiments. We identified a 60-kilobase haplotype encompassing the ESR1 gene, a ligand-activated transcription factor, showing strong genetic divergence between populations of Tibetan partridges adapted to different altitudes. We identified six SNPs in the ESR1 gene fixed for derived alleles in high-altitude populations that are strongly conserved across vertebrates, which are likely key genetic changes associated with high-altitude adaptation in Tibetan partridge. We also identified strong genetic divergence in additional genes associated with the regulation of apoptosis pathways, possibly indicating genetic adaptation to long-term chronic hypoxia in a high-altitude environment. Transcriptome analysis identified regulation of apoptosis, glycolysis, and response to hypoxia as key pathways among differentially expressed genes between populations of Tibetan partridges residing across the elevational gradient. Similarly, transcriptome analysis in birds transplanted from high to low elevation have identified differential expressed genes related to the immune system, and to stress response (mainly heat). Comparative transcriptomics analyses among Tibetan partridges in their “native” and “transplanted” habitats indicated that there are different suites of genes responding to short-term physiological acclimation or long-term adaptation in this species. However, we found two genes associated with the HIF-1 signaling pathway; Lactate Dehydrogenase-A (LDHA) and Aldolase C (ALDOC) were differentially expressed both (a) across the native populations along the elevational gradient and (b) after experimental transplantation from high to low elevation. Our results highlight Tibetan partridges as a useful study system to explore the genetic architecture associated with short-term acclimation and long-term genetic adaptation to high altitudes.
Diversity and Identification of Aquatic Macrophytes of Four Lakes of Holalkere, Chitradurga District, Karnataka, India.
Authors: MALLAPPA PALLAVI , Takrya Parameswara Naik
Published: November 2022

The present investigation concerns the diversity of aquatic macrophytes in different lakes of Holalkere, Chitradurga district of Karnataka. Lakes are the natural habitat of macrophytic plants. Macrophytes are the common features of an aquatic ecosystem. Aquatic macrophytes play a prominent role in water ecosystems. Aquatic macrophyte diversity and its role in understanding the lake ecosystem dynamics have tremendous significance. Species composition of aquatic macrophytes, seasonal distribution in four lakes in Holalkere viz. Gangasamudra lake, Gowdihalli lake, Talikatte lake and Kudineerakatte lake were studied during 2019–2021. Fifteen different species of aquatic macrophytes were recorded from the studied lakes which include One free-floating, Eight Submerged, and Six Emergent Macrophytes present in the lake basin. Hydrilla verticillate, Polygonum glabrum, Cyperus longus, and Ipomoea fistulosa occur throughout the year. It indicates that aquatic macrophyte species are specific to environmental quality. The present findings revealed that the surface quality of the lakes is productive. The researches aiming to describe unknown species are still necessary.
The quasi-strong solutions of a degenerate electrorheological fluid equation
Authors: Zhan Huashui
Published: November 2022

An electrorheological fluid equation with a convection term is considered.
Based on the existence of weak solutions, the definition of quasi-strong solution is given and its existence is studied. Different from the other related works, it is permissable that there is a point $(x_0,t_0)\in \Omega\times [0,T)$ such that $a(x_0,t_0)=0$. In consideration of the uniqueness of solution, it is even permissable that the set $\{x\in \Omega: a(x,t)=0\}$ has an interior point, the equation may have hyperbolic characteristic, entropy condition should be quoted. Moreover, the boundary value condition is imposed on a submanifold $\Sigma_1\subset\Omega\times (0,T)$, and the submanifold $\Sigma_1$ can not be expressed as a cylinder such as $\Gamma\times (0,T)$, where $\Gamma\subset\partial\Omega$. Based on this partial boundary value condition, the stability of quasi-strong solutions is established, the uniqueness of entropy solution is proved
Bibliometric Mining of Research Directions and Trends for Big Data
Authors: Lundberg Lars
Published: November 2022

In this paper a program and methodology for bibliometric mining of research trends and directions is presented. The method is applied on the research area Big Data for the time period 2012 to 2021, using the Scopus database. It turns out that the 10 most important research directions in Big Data are Machine learning, Deep learning and neural networks, Internet of things, Data mining, Cloud computing, Artificial intelligence, Healthcare, Security and privacy, Review, and Manufacturing. For four geographical regions (North America, European Union, China, and The Rest of the World) we investigate different activity levels in Big Data during different parts of the time period. North America was the most active region during the first part of the time period. During the last years China is the most active region. The citation scores for documents from different regions and from different research directions within Big Data are also compared. North America has the highest average citation score among the geographical regions and the research direction Review has the highest average citation score among the research directions. The program and a methodology for bibliometric mining developed in this study can be used also for other large research areas than Big Data. Now that the program and methodology have been developed, one could probably perform a similar study in some other research area in a couple of days.
Modelling malaria in southernmost provinces of Thailand: a two-step process for analysis of highly right-skewed data with a large proportion of zeros
Authors: Ammatawiyanon Lumpoo , Tongkumchum Phattrawan , Lim Apiradee , McNeil Don
Published: November 2022

Background
Malaria remains a serious health problem in the southern border provinces of Thailand. The issue areas can be identified using an appropriate statistical model. This study aimed to investigate malaria for its spatial occurrence and incidence rate in the southern provinces of Thailand.
Methods
The Thai Office of Disease Prevention and Control, Ministry of Public Health, provided total hospital admissions of malaria cases from 2008 to 2020, which were classified by age, gender, and sub-district of residence. Sixty-two sub-districts were excluded since they had no malaria cases. A logistic model was used to identify spatial occurrence patterns of malaria, and a log-linear regression model was employed to model the incidence rate after eliminating records with zero cases.
Results
The overall occurrence rate was 9.8% and the overall median incidence rate was 4.3 cases per 1,000 population. Malaria occurence peaked at young adults aged 20-29, and subsequently fell with age for both sexes, whereas incidence rate increased with age for both sexes. Malaria occurrence and incidence rates fluctuated; they appeared to be on the decline. The area with the highest malaria occurrence and incidence rate was remarkably similar to the area with the highest number of malaria cases, which were mostly in Yala province's sub-districts bordering Malaysia.
Conclusions
Malaria is a serious problem in forest-covered border areas. The correct policies and strategies should be concentrated in these areas, in order to address this condition.
Infections due to Candida spp in a Brazilian Tertiary Hospital: Species and Susceptibility to Antifungals
Authors: De Carvalho Rafaela Durrer Parolina , Pavanello Larissa , Dos Santos Victor Augusto Benedicto , De Almeida Talita Bonato , Da Silva Diego Romário , Rosa Caroline Sanches , Rosa Fernanda Silveira , De Moraes Hamilton Antonio Bonilha , Cogo-Müller Karina
Published: November 2022

Introduction: Infections caused by Candida spp are a major public health concern, due to the high mortality rate and the limited therapeutic arsenal. Objectives: To assess the prevalence of Candida spp infections and susceptibility to antifungal agents in a general hospital. Methods: Descriptive, cross-sectional study with collection of epidemiological and laboratory data on Candida spp cultures (2014 to 2019), at a large tertiary and philanthropic hospital in the city of Piracicaba, São Paulo state, Brazil. Results: A total of 63 episodes of Candida spp infection were eligible, being more prevalent in adults (88.9%) aged ≥ 70 years (41.3%), causing 40 deaths (63.5%). The C. albicans species represented 41.3% of the infections, with a mortality rate of 37.5%, while non-albicans species accounted for 58.7%, highlighting C. tropicalis (25.4%) and C. glabrata (23.8%), with a mortality rate of 27.5% for both species. Regarding the susceptibility profile, most were sensitive to echinocandins and azoles over the years. C. glabrata presented one case of resistance and dose-dependent sensitivity to caspofungin and micafungin and fluconazole, which was expected due to the decreased sensitivity to azoles, while the results for echinocandins were in agreement with previous studies showing increased resistance to this group of drugs. Conclusion: Given the high prevalence of hospital fungal infections and the associated mortality rate, determining the local epidemiological profile and susceptibility to drugs is an important strategy for guiding antifungal therapy.