bluuebunny/crossref_metadata_2025 huggingface dataset:
Persian Sentiment Analysis via a Transformer Model concerning Banking Sector
Authors: Haddadi Seyed Jamal , Khoeini Elham , Salmani Pezhman , Beygi Mehdi , Khoshkar Mehrdad Haddad
Published: August 2023

The competitive landscape of a country's banking sector necessitates an in-depth understanding of customer satisfaction levels concerning the services provided. Presently, customers predominantly express their feedback via social media platforms in the form of posts and comments. This study endeavors to create a highly accurate sentiment detection algorithm for the Iranian banking system, utilizing a transformer model. In the initial stages, we collected data by crawling comments from Twitter, which are subsequently labeled and filtered according to the names of Iranian banks, dating from 2019. Following this, an optimized Deep Neural Network (DNN)-based pre-trained ParsBERT model, a monolingual Persian model, is fine-tuned using this data. Finally, our model is evaluated on a test dataset, and the results are validated by comparing them with the original multilingual BERT, Bidirectional Long Short-Term Memory (Bi-LSTM) network, and four other classification methods. To address the Out-Of-Vocabulary (OOV) issue, a character-level embedding is incorporated in conjunction with the word-level embedding. This approach aids in tackling the multitude of variations observed in non-native words, extracting character-level features using a character-level Bi-LSTM. The proposed model highlights the statistical superiority of our method when compared to the other methods evaluated.
Associations of Transport and Recreational Walkability with Health and Life Satisfaction
Authors: Hsieh Hsu-Sheng
Published: August 2023

Background: The relationships of well-being with walking and built environments have been investigated. However, few studies have differentiated the impacts of environment walkability for transport and recreation on well-being. Therefore, this study identified perceived environment walkability (PEW) for transport and recreation separately and examined their associations with health status and life satisfaction.
Methods: Data were collected from 300 residents in Taiwan by face-to-face questionnaire interviews. Structural equation modeling was used to examine the relationship between PEW, transport and recreational walking, body mass index, and health and life satisfaction, incorporating the influences of sociodemographics.
Results: Land use mix-access and street connectivity reflecting PEW for transport facilitated transport walking, which did not impact well-being. By contrast, these two factors, aesthetics, land use mix-diversity, and walking facilities reflecting PEW for recreation facilitated recreational walking, improving health and life satisfaction. Moreover, car ownership increased body mass index, undermining health and life satisfaction.
Conclusions: Policies should shape different environments for transport and recreational walking, improve recreational walking environments for well-being, and reduce car ownership to prevent obesity.
The effect of Nordic Hamstring Exercise on the muscle strength and architecture of Hamstring：A Systematic Review and Meta-analyses
Authors: Wang zhenmin , Su MeiHua , Xu YaMin , Jin JiaHui , Chen DeQuan , Zou YongQiang
Published: August 2023

Purposes: In this paper, we used Meta-analysis to study the effect of NHE on hamstrings and to find the scientific evaluation index of NHE effect.
Method: In this paper, we systematically searched all data since the establishment of the database through PubMed, Embase, Web of science, and Cochrane Library databases, with PubMed search formula (((Nordic) OR (Russian)) OR (NHE)) AND (((((((Hamstring) OR (Hamstring Muscle)) OR (Muscle, Hamstring)) OR (Muscles, Hamstring)) OR (Biceps Femoris)) OR (Semimembranosus)) OR (Semitendinosus)).The search field was full text and the search date of April 7, 2022. The quality evaluation, Meta-analysis, sensitivity analysis and publication bias analysis of the included literature were performed using Review manager 5.4 software.
Results: A total of 950 studies were retrieved for this study, and after strict inclusion and exclusion, a total of 11 studies were included, with 497 subjects, including 282 in the test group and 215 in the control group, and the overall quality of the literature was high. NHE can be used as an effective intervention method, which can significantly improve the eccentric hamstring strength peak(MD=46.16, 95% Cl: 28.70-63.63, P=0.00001<0.01) and the eccentric peak torque of the hamstrings (MD=10.87，95%CI：3.86-17.89，P=0.002<0.01) and the eccentric peak torque of the hamstrings muscles to body weight (MD=0.17, 95% CI: 0.01-0.33, P=0.04<0.05), increase BFLH fascicle length (MD=0.62, 95% CL: 0.11-1.12，P=0.02<0.05),improve H:Q functional ratio(MD=0.07,95%CI: 0.02-0.13, P=0.01<0.05),and decrease the hamstrings eccentric angle of peak torque（APT） (MD=2.53, 95% CI: 4.63-0.43, P=0.02<0.05).
Immigrated students’ voices at school environment: an analysis of policy documents through school websites
Authors: Välimäki Maritta , Hipp Kirsi , Acton Faye , Echsel Angelika , Grădinaru Ioan-Alexandru , Hahn-Laudenberg Katrin , Schulze Christina , Stefanek Elisabeth , O'Brien Niamh
Published: August 2023

Background
The development of immigrant friendly schools is an important target across educational settings. However, relatively few studies have specifically examined mechanism how student voices are heard in European school context. This study examined the extent to which student voices have been addressed in European schools as evidenced from websites of schools located in high migrant areas in six European countries: Austria, England, Finland, Germany, Romania, and Switzerland.
Methods
Between 2 March and 8 April 2021, we reviewed the publicly available policy documents on school websites to ascertain how student voice practices are carried out in schools as described in the documents. The selected schools were in areas of high immigration. Pre-designed categories were applied to the documents extracted from the websites using a four-step analytic approach (finding, selecting, appraising, and synthesizing the data). A combination of qualitative and quantitative approaches with descriptive statistics (n, %, Mean, SD, range) was used for the data analysis.
Results
A total of 412 documents from 305 schools were extracted (49–110 documents per country). The most common documents were anti-bullying or violence prevention strategies (75/412) and mission statements (72/412). There were disparities between countries and schools about how hearing students’ voices and including students in decision-making in schools were described in the documents. Limited evidence was apparent as to how students are listened to in their schools based on policy documents.
Conclusions
Our document analysis based on publicly accessible school websites suggest that student voices are less frequently described in school written policy documents in our sample of European schools. Our findings provide a baseline to further monitor activities, not only at school level but also to any governmental and local authorities whose intention is to serve the public and openly share their values and practices with community members.
Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction
Authors: Li Guanghui , Bai Peihao , Liang Cheng , Luo Jiawei
Published: August 2023

Background Long noncoding RNAs (lncRNAs) are integral to a plethora of critical cellular biological processes, including the regulation of gene expression, cell differentiation, and the development of tumors and cancers. Predicting the relationships between lncRNAs and diseases can contribute to a better understanding of the pathogenic mechanisms of disease and provide strong support for the development of advanced treatment methods.Results Therefore, we present an innovative node-adaptive Transformer model for predicting unknown associations between lncRNAs and diseases (GNATLDA). First, we utilize the node-adaptive feature smoothing (NAFS) method to learn the local feature information of nodes and encode the structural information of the fusion similarity network of diseases and lncRNAs using Structural Deep Network Embedding (SDNE). Next, the Transformer module, which contains a multi-headed attention layer, is used to learn global feature information about the nodes of the heterogeneous network, which is used to capture potential association information between the network nodes. Finally, we employ a Transformer module with two multi-headed attention layers for learning global-level embedding fusion. Network structure coding is added as the structural inductive bias of the network to compensate for the missing message-passing mechanism in Transformer. Our model accounts for both local-level and global-level node information and exploits the global horizon of the Transformer model, which fuses the structural inductive bias of the network to comprehensively investigate unidentified associations between nodes, significantly increasing the predictive effectiveness of potential interactions between diseases and lncRNAs. We conducted case studies on four diseases; 55 out of 60 interactions between diseases and lncRNAs were confirmed by the literature.Conclusions Our proposed GNATLDA model can serve as a highly efficient computational method for predicting biological information associations.
Strengthening Virtual Learning Strategies for Active Learning in Crisis Situations; A Mixed-Method Study in the COVID-19 Pandemic
Authors: Jahani Mohammad-Ali , Ghanavatizadeh Aram , Delavari Sahar , Abbasi Mahdi , Nikbakht Hossein-Ali , Farhadi Zeinab , Darzi Alameh , Mahmoudi Ghahraman
Published: August 2023

Background
Medical universities are responsible for educating and training healthcare workers. One of the fields significantly impacted by the pandemic is medical education. The aim of this study is to identify strategies for enhancing virtual learning for active learning and finding solutions for improving its quality.
Methodology:
This mixed-method (quantitative-qualitative) research was conducted in 2023 at three selected universities in the Mazandaran province. In the quantitative phase, 507 students participated via stratified random sampling using a standard questionnaire. In the qualitative phase, data was collected through semi-structured interviews with 16 experts until data saturation was achieved. SPSS21 and MAXQDA10 software were used for data analysis.
Results
In multivariate regression analysis, an increase in one point in the dimensions of student-teacher interaction, active time, immediate feedback, and active learning corresponded to an average increase in learning scores of 0.11, 0.17, 0.16, and 1.42 respectively (p ≤ 0.001). After the final analysis in the qualitative phase, four main domains (infrastructure, resources, quantity of education, and quality of education) and 16 sub-domains with 84 items were identified.
Conclusion
The greatest challenge in virtual education is the interaction and cooperation between students and teachers. The implementation of the identified strategies in this research could provide useful evidence for policymakers and educational administrators to implement interventions aimed at addressing deficiencies and enhancing virtual learning.
Global burden and influencing factors of chronic kidney disease due to type 2 diabetes in adults aged 20-59 years, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019
Authors: Xie Dandan , Ma Tianpeng , Cui Haoliang , Li Jing , Zhang Aihua , Sheng Zhifeng , Xie Yiqiang
Published: August 2023

Background
This study aimed to investigate the burden of chronic kidney disease due to type 2 diabetes (CKD-T2D) and its influencing factors in the population aged 20–59 years from 1990 to 2019, utilizing data from the Global Burden of Disease (GBD) Study.
Methods
The GBD Study data were analyzed to assess the global age-standardized incidence, death, and disability adjusted life years (DALY) rate of CKD-T2D. Decomposition analysis was employed to explore the effects and contributions of population growth, aging, and epidemiological changes on CKD-T2D DALY. Additionally, the study investigated the correlation between attributable risk factors and the socioeconomic development index (SDI).
Results
Globally, the age-standardized incidence of CKD-T2D showed an upward trend (AAPC = 0.7%, P < 0.05), with slight increases observed in the age-standardized death rate (AAPC = 0.2%, P < 0.05) and DALY rate (AAPC = 0.3%, P < 0.05). Incidence, mortality, and DALY rates were higher with increasing age and among males. Population growth and aging were identified as significant drivers of CKD-T2D DALY burden in the 20–59 age group, while high systolic blood pressure and high body-mass index were the primary attributable risk factors. High SDI countries exhibited higher contributions from body-mass index, whereas low SDI countries were more impacted by high systolic blood pressure. The population attributable fraction of CKD-T2D DALY caused by high body-mass index positively correlated with SDI (R = 0.62 to 0.65, P < 0.001), while high temperature (R = -0.35 to -0.38, P < 0.001) and lead exposure (R = -0.62 to -0.64, P < 0.001) showed negative correlations.
Conclusions
The burden of CKD-T2D represents an increasing concerning global public health issue. Targeted disease screening and early intervention measures for individuals aged 20–59 years can effectively alleviate the burden of CKD-T2D. High systolic blood pressure and high body-mass index are major attributable risk factors, and their correlation with SDI should be considered when formulating prevention and control strategies.
Cell-free DNA as prognostic and diagnostic biomarkers for adult sepsis: a systematic review and meta-analysis
Authors: Charoensappakit Awirut , Sae-khow Kritsanawan , Rattanaliam Pongpera , Vutthikraivit Nuntanuj , Pecheenbuvan Monvasi , Udomkarnjananun Suwasin , leelahavanichkul Asada
Published: August 2023

Background: Although cell-free DNA (cfDNA) is an emerging sepsis biomarker, the use of cfDNA, especially as diagnostic and prognostic indicators, has surprisingly not been systemically analyzed.
Methods: Data of adult patients with sepsis that conducted cfDNA measurement within 24 h of the admission was collected from PubMed, ScienceDirect, Scopus, and Cochrane Library until October 2022. The Quality in Prognosis Studies (QUIPS) and Quality Assessment in Diagnostic Studies-2 (QUADAS-2) tools were used to reduce the risk of biased assessment. The mean difference (MD) of cfDNA concentration and the standardized mean difference (SMD) between populations was calculated using Review Manager (RevMan) version 5.4.1 package software.
Results: Pooled analysis from 18 included studies demonstrated increased serum cfDNA levels in sepsis when compared with healthy control (SMD = 1.02; 95% confidence interval (CI) 0.46-1.57) or non-sepsis patients in the intensive care unit (ICU) (SMD = 1.03; 95% CI 0.65-1.40), respectively. Meanwhile, a slight decrease in the statistical value was observed when compared with non-sepsis ICU patients with SIRS (SMD = 0.74; 95% 0.41-1.06). The lower cfDNA levels were also observed in sepsis survivors compared to the non-survivors (SMD at 1.43; 95%CI 0.69-2.17) with the pooled area under the receiver operating characteristic curve (AUC) of 0.76 (95% CI 0.64-0.87) for the mortality prediction. Levels of cfDNA showed a pooled sensitivity of 0.81 (95% CI 0.75 - 0.86) and specificity of 0.72 (95% CI 0.65 - 0.78) with pooled diagnostic odd ratio (DOR) at 25.03 (95% CI 5.48 – 114.43) for the identification of sepsis in critically ill conditions.
Conclusions: The cfDNA levels were significantly higher in patients with sepsis and being a helpful indicator for the critically ill conditions of sepsis. Nevertheless, results of the test must be interpreted carefully with the context of all clinical situations.
It’s time for bed! General procrastination and bedtime procrastination as serial mediators of the relationship between temporal perspective and sleep outcomes.
Authors: Herzog-Krzywoszanska Radoslawa , Krzywoszanski Lukasz , Jewula Beata
Published: August 2023

Adequate and sufficient sleep is essential for good health, effective functioning and well-being. However, recent trends indicate an increase in sleep deprivation, with adolescents and young adults being a particularly vulnerable group. General procrastination (GP) and bedtime procrastination (BP), understood as the tendency to delay going to bed without external pressure, are factors that can contribute to sleep deprivation and fatigue. In our study, we used a serial mediation model to test whether the relationship between time perspective and sleep sufficiency and daytime fatigue may be serially mediated by procrastination and bedtime procrastination. The Zimbardo Time Perspective Inventory, the Irrational Procrastination Scale, the Bedtime Procrastination Scale, and the Sleep Inventory were completed online by 399 university students between the ages of 19 and 27. Results showed that future time perspective predicted lower general procrastination, which in turn was associated with lower BP, and consequently higher sleep sufficiency and lower daytime fatigue. Past negative time perspective predicted higher GP, which in turn was associated with higher BP and consequently lower sleep sufficiency and higher daytime fatigue. These findings suggest that time perspective, general procrastination and bedtime procrastination may play an important role in predicting sleep sufficiency and daytime fatigue.
SIRT1 profile update in high-risk pregnancies and preeclampsia: A novel comprehensive cohort study
Authors: Mukminah Aisyatul , Sargowo Djanggan , Sujarwoto Sujarwoto , Raharjo Bambang , Nurwidyaningtyas Wiwit
Published: August 2023

The preeclampsia etiology is unclearly understood, becoming considerable concern as an aging-related disease. Accelerated prematurity of cell death associated with decreased Sirtuin (SIRT)1 activity. This study was designed to estimate the SIRT1 serum profile in high-risk pregnancies to preeclampsia development probability. This study was conducted from January to October 2020, 305 screened pregnant women with a gestational age of 4 weeks up to < 20 weeks were enrolled in a prospective cohort study up to sixth weeks postpartum. Women with existing complications during follow-up such as antenatal bleeding, placental abruption, hepatitis, abortion, death, and rejection under follow-up were excluded. Serum SIRT1 variance that was measured by ELISA at the baseline and endline of the study were investigated with the preeclampsia progression. Our results demonstrate, that constan serum SIRT1 concentration until third trimester of pregnancy tend to increased development of preeclampsia. In contrast, SIRT1 concentrations at normal pregnancy outcomes appear to be higher in late pregnancy (gestational age > 37 weeks). Importantly, we found that serum SIRT1 concentration was significantly reduced in pregnancy-developed preeclampsia than in normal pregnancy (p < 0.001). We concluded that the lack of elevating serum SIRT1 concentrations until > 20 weeks of gestation increases the likelihood of developing preeclampsia. Ultimately, we provide a translational perspective to driving accelerating SIRT1 serum concentrations in women with at-risk pregnancies from early pregnancy towards > 20 weeks gestation, becoming a further study that promises effort to prevent preeclampsia and improve women's quality of life.
Inter-relationship between residual stresses, microstructural evolutions, and mechanical responses of heat treatable aluminum alloys during welding: a numerical and experimental study
Authors: Sarmast Ardeshir , Serajzadeh Siamak
Published: August 2023

Welding of heat treatable aluminum alloys poses a significant challenge due to the formation of unwanted microstructural changes, inferior mechanical properties, and formation of residual stresses (RS). An understanding of the inter-relationship between these aspects is crucial for the successful design of welding procedures. Given the complexity of these materials, a combination of numerical and experimental investigations is necessary to address this inter-relationship. In this work, the effect of welding heat input on the post-weld precipitation hardening, changes in mechanical properties, RS formation, and their inter-relationship in different welding regions of the heat treatable AA2024 was numerically and experimentally studied. Two different thicknesses of the base material, 3.5 mm and 6 mm were chosen to investigate the effect of different heat inputs and geometries. The results show that the highest RS are formed in the partially melted zone (PMZ) and heat affected zone (HAZ), with values of 300 MPa and 221 MPa, respectively, for the 6 mm sample, where the mechanical properties and microstructure were most affected. These high tensile RS accelerate the age hardening process of these regions, resulting in 20 HV changes in the PMZ and 14 HV changes in the HAZ in 70 days. The strength of the material due to these microstructural evolutions determined the load bearing of each region and their maximum RS.
Association between Angiotensin Converting Enzyme Gene I/D and Promoter Polymorphisms and Diabetic Nephropathy in Type2 Diabetic Patients in Ismailia, Egypt
Authors: Hassan Nashwa R. , Tolba Shrouq M. , Leheta Ola F. , Mossad Ahmed Mohammed , Abdalla Mohamed O.
Published: August 2023

BACKGROUND: There is mounting evidence that the chronic activation of renal and systemic ACE, which results in the production of Angiotensin II, is a critical step in the pathogenesis of DN. Chronic ACE activation causes an increase in intraglomerular pressure, tissue damage, pro-inflammatory effects, and promotes fibrosis.
AIM: The purpose of this study was to determine if ACE polymorphisms (I/D rs4646994 and promoter SNP, rs4292) and ACE level were related to the DN development in T2DM patients in the Egyptian community.
PATIENTS AND METHODS: This study is designed as a case control study which enrolled 90 subjects divided into three groups: 30 diabetic patients without DN, 30 diabetic patients with DN and 30 healthy individuals as control group. We measured for each patient the following: serum creatinine, eGFR, ACR, lipid prolife, HbA1C, as well as serum ACE level. Genotyping of ACE I/D and promoter SNP, rs4292, polymorphisms in ACE gene were performed using conventional PCR assays.
RESULTS: The laboratory data analysis revealed that the only variables across the trial groups that indicated a significant statistical difference were serum creatinine, eGFR, ACR, HDL-C, LDL-C, and HbA1c. Total cholesterol and triglycerides did not. Between the study groups, there was a substantial statistical difference in the level of serum ACE. In our population, the genotype and allele frequencies of the ACE I/D gene polymorphism varied considerably between research groups, suggesting that it may be a risk factor for DN. In comparison to individuals of the wild type (II), the (DD) genotype considerably raised the probability of progression to T2DM by about six times and of progression to DN by about ten folds. This study found that the ACE promoter rs4292 (C/T) polymorphism is a risk factor for developing DN. The (TT) genotype is associated with increased susceptibility to DN as it was higher in diabetic patients with nephropathy than the two other study groups. However, there was no statistically significant difference in the study variables among different genotypes subgroups.
CONCLUSION:According to our research, the mutant alleles (T) of the ACE promoter rs4292 (C/T) polymorphism and the ACE I/D rs4646994 polymorphism may both be risk factors for DN in the Egyptian population.
Calcium concentration regulates interspecific interaction of algae along the nutrient gradient
Authors: Zhou Qing Shi , Hou Jing Ming , Gao Yang , Wang Tian , Li Bing Yao , Pan Zhan Peng , Sun Xue Liang , Duan Chang Hui
Published: August 2023

Although many studies have focused on the influence of abiotic stress gradients on biological interactions, few studies explained the effects of both resource and non-resource stress on the facilitation. We conducted a controlled experiment to study the effects of nutrient stress on the interspecific between Phormidium corium and Scenedesmus quadricauda along calcium gradient. The results showed that when the calcium concentration was high, the competitive interaction changed into positive interaction along the nutrient stress. In the stress environment, the population density is low and the encounter rate is low. Moreover, facilitation may improve the harsh environment and make it more beneficial to the beneficiary species. When the calcium concentration was low, the facilitation reached the peak under medium resource stress. This phenomenon may be caused by the interaction between salt stress and nutrient. When calcium stress was high, it may not be conducive to the absorption of nutrients by algae. While the facilitation effect may be strongest in the medium stress environment due to the relatively sufficient resource. These results emphasized the importance of non-resource stress in interspecific relationships, pointed out a new direction for the study of facilitation, and provided theoretical guidance for the prevention of freshwater blooms.
Research on digital twin modeling and monitoring technology for smoke alarm calibration system
Authors: Wu Min , Ying Wenfeng
Published: August 2023

Aiming at the problems of backward calibration method of smoke alarm, low production efficiency and difficult real-time monitoring, a digital twin system modeling and monitoring method of smoke alarm calibration is proposed First, through the analysis of smoke alarm calibration requirements, the overall framework design of the digital twin calibration system for smoke alarm is proposed, and then the twin model of smoke box is constructed by running the digital twin five-dimensional model The physical smoke box, geometric model, physical model, rule model and behavior model are introduced in detail; Then the communication system architecture, data acquisition and data mapping are used to construct the twin data model; Finally, the feasibility was verified by the calibration system of an enterprise Through the system, the qualified rate of smoke alarm calibration was increased from 98% to 99.6%, and the repair rate of defective products was reduced by 1.6%.
Screening and functional verification of drought resistance-related genes in castor bean seeds
Authors: Luo Rui , Wang Zhiyan , Wen Qi , Liang Xiaotian , Zhao Huibo , Zhao Yong , Yin Mingda , Wen Yanpeng , Hu Xuemei , Huang Fenglan
Published: August 2023

Due to its limited freshwater resources, China has large arid and semiarid regions. Drought is one of the natural stresses that greatly impact plants. Castor bean (Ricinus communis L.) is an oil crop with high economic value. Drought is one of the factors limiting castor bean growth. The drought resistance mechanisms of castor bean have become a research focus. In this study, we screened out the genes related to drought resistance in castor bean embryos at the germination stage through combined physiological measurements、proteomic and metabolomic analysis. These genes were heterologously overexpressed and complementarily expressed in Arabidopsis thaliana to analyze their roles in the response mechanism of A. thaliana to drought resistance. The experimental results are as follows: The germination stage embryos of castor oil treated with water for 48 h (S48), 60 h (S60), and 15% PEG 6000 for 48 h (P48) and 60 h (P60) were used as experimental materials, and the embryos of S48 and S60 were used as experimental materials. As a control, the physiological activity (CAT, SOD, POD, GST, T-AOC), content (MDA, H2O2, Pro) and hydroxyl radical scavenging ability of embryo samples P48 and P60 treated with 15% PEG 6000 for the same time were measured. The results showed that compared with the control, with the increase of treatment time, the CAT activity, SOD activity, POD activity, H2O2 content, Pro content and hydroxyl radical scavenging ability of castor embryos all showed an upward trend, while GST activity, T-AOC activity and T-AOC activity increased. The activity and MDA content showed a downward trend. Based on combined physiological measurements、proteomic and metabolomic analysis and RT-qPCR validation, three significantly upregulated genes, RcECP63 (LOC8274875), RcDDX31 (LOC8282119), and RcA/HD1 (LOC8277163), were finally selected for study. We compared the growth, germination, expression of RcECP63, RcDDX31, and RcA/HD1, and physiological indicators of four types (mutant, complementary-expression, wild-type, and overexpression) of A. thaliana under drought stress. The comparison showed that as the mannitol concentration increased, the A. thaliana plants on mannitol medium exhibited shorter root lengths, less lateral roots, and lower germination rates. Compared with the controls, the drought-stressed overexpression and complementary-expression transgenic plants showed an overall trend of upregulation of RcECP63, RcDDX31, and RcA/HD1. The functions of the three genes in drought stress response were further verified by the measurement of physiological indicators.
Exploring the Potency of Machine Learning Approaches in Enhancing Spam Detection Accuracy
Authors: Fathima Afrah , Devi G Shree , Faizaanuddin Mohd
Published: August 2023

Spam in mobile communication networks is a serious problem since it interferes with user experience and jeopardises user privacy. A precise and reliable spam detection technique is required for mobile Short Message Service (SMS) communication to successfully combat this issue. In our study, we suggest utilising machine learning-based spam detection strategies to achieve precise identification. With this technique, ham and spam messages in mobile communication are categorised using machine learning classifiers including Support Vector Machine (SVM), K Nearest Neighbour (KNN), Logistic Regression (LR), and Light GBM (LGBM). The SMS spam collection dataset, which was split into two groups for training and testing, was used in our trials to assess the methodology. In terms of classification performance, the trials' findings demonstrated that LGBM performed better than others, obtaining a remarkable accuracy of 98%. This shows how successfully we have addressed the problem of spam in mobile SMS communication.
PDIA3 knockout abrogate effects of 1,25(OH)2D3 on cellular respiration and glycolysis in squamous cell carcinoma
Authors: Nowak Joanna I. , Olszewska Anna , Król Oliwia , Żmijewski Michal A.
Published: August 2023

PDIA3 is an endoplasmic reticulum disulfide isomerase which is involved in the folding and trafficking of newly synthesized proteins. PDIA3 was also described as an alternative receptor for the active form of vitamin D 1,25(OH)2D3. Here, we investigated the impact of PDIA3 in mitochondrial morphology and bioenergetics in squamous cell carcinoma line A431 treated with 1,25(OH)2D3. It was observed that PDIA3 deletion resulted in changes in morphology of mitochondria including a decrease in the percentage of mitochondrial section area, maximal diameter, and perimeter. 1,25(OH)2D3 treatment of A431∆PDIA3 cells partially reversed the effect of PDIA3 deletion increasing aforementioned parameters, while in A431WT cells only an increase in mitochondrial section area was observed. Moreover, PDIA3 knockout affected mitochondrial bioenergetics and modulated STAT3 signaling. Oxygen Consumption Rate (OCR) was significantly increased, with no visible effect of 1,25(OH)2D3 treatment in A431∆PDIA3 cells. In the case of Extracellular Acidification Rate (ECAR) rate an increase was observed for glycolysis and glycolytic capacity parameters in the case of non-treated A431WT cells versus A431∆PDIA3 cells. 1,25(OH)2D3 treatment had no significant effect on glycolytic parameters. Taken together presented results suggests that PDIA3 is strongly involved in the regulation of mitochondrial bioenergetics in cancerous cells and modulation of its response to 1,25(OH)2D3, possibly through STAT3.
IoT devices and data availability optimization by ANN and KNN
Authors: Chen Zhiqiang , Song Zhihua , Zhang Tao , Wei Yong
Published: August 2023

To improve the availability of IoT devices and data, research has been conducted on rapid prediction of instantaneous fault rates and temperatures. An IoT device and data availability optimization scheme based on artificial neural networks and K-nearest Neighbo drivers is proposed, using artificial neural network algorithms and K-nearest Neighbo driven neural network algorithms. The preliminary algorithm for achieving availability optimization is selected, and the objectives are divided into data optimization and device optimization. Applicable models are constructed separately, and the proposed optimization model is solved using the K-neighborhood driven neural network algorithm. The validation results showed that the proposed scheme reduced the maximum temperature to 2.0750 ℃ compared to the benchmark method, availability forward fault-tolerant method, and heuristic optimization algorithm. Compared with the first three methods, the improved method can improve the average availability of IoT devices by 27.03%, 15.76%, and 10.85%; The instantaneous fault rates of the three algorithms reached 100%, 87.89%, and 84.4%. This optimization algorithm has high efficiency in eliminating fault signals and optimizing the prediction of time limited satisfaction, and has strategic foresight in the decision plans of decision implementers.
Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort
Authors: S Fahira Haseen , P Lakshmi , P Aathirai S
Published: August 2023

A suspension system plays an active role in balancing the conflicting requirements of stability and ride comfort in an automobile. The health of the driver is an important aspect since continuous exposure to vehicle vibrations may lead to severe health hazards in long run. In this study, full car with driver model of 13 Degrees of Freedom (DOF) is considered. The vehicle is tested under bump, pulse, half-sine and different classes of random road profiles (ISO 8608) for analysis in Matlab/Simulink environment. Initially the vehicle suspension is tested for a Proportional Integral and Derivative (PID) controller. To deal with higher complexity of the vehicle design, intelligent controllers are implemented. Fuzzy Logic Controller (FLC) is designed for the vehicle which plays a role in vibration suppression and ride comfort (ISO 2631-1 standard) improvement. This design is further enhanced by Adaptive Neuro-Fuzzy Inference System (ANFIS) controller which incorporates the advantages of both fuzzy and neural control system. The time domain analysis and ride comfort analysis show that ANFIS controller gives better control over linear PID controller, FLC and Passive Suspension System (PSS). To evaluate the effectiveness of the controller, it is tested for various classes of random road profile for varying speed condition. Simulation results show that ANFIS controller fed system gives better ride comfort and passenger safety by reducing the Root Mean Square (RMS) values of Head Acceleration (HA), Frequency Weighted RMS (FWRMS) values of HA, Vibration Dose Value (VDV) at the driver head and Power Spectrum Density (PSD) analysis of HA. Also, the proposed ANFIS controller is experimentally verified on laboratory Quarter car setup. It is tested on two road inputs namely pulse input and half-sine input. This analysis also proves that the ANFIS controller performs better than FLC and PSS.
1,3-diphenylureido hydroxamate: a promising scaffold for generation of potent antimalarial histone deacetylase inhibitors
Authors: Tavares Maurício T. , Krüger Arne , Yan Sun L. Rei , Gomes Vinícius M. , Oliveira Daffiny Sumam , Paz Franciarli , Waitman Karoline , Ruiz Claudia , Toledo Mônica F. Z. J. , Hassimotto Neuza M. A. , Machado-Neto João A. , Poso Antti , Cameron Michael D. , Bannister Thomas D. , Palmisano Giuseppe , Wrengler Carsten , Kronenberger Thales , Parise-Filho Roberto
Published: August 2023

We report a series of 1,3-diphenylureido hydroxamate HDAC inhibitors evaluated against sensitive and drug-resistant P. falciparum strains. Compounds 8a-d show potent antiplasmodial activity, indicating that a phenyl spacer allows improved potency relative to cinnamyl and di-hydrocinnamyl linkers. In vitro, mechanistic studies demonstrated target activity for PfHDAC1 on a recombinant level, which agreed with cell quantification of the acetylated histone levels. In silico studies suggest that the phenyl linker has an ideal length in the series for permitting effective interactions of the hydroxamate with PfHDAC1 and that this compound series could bind as well as in HsHDAC1. Taken together, these results highlight the potential of diphenylurea hydroxamates as a privileged scaffold for the generation of potent antimalarial HDAC inhibitors with improved selectivity over human HDACs.
Organic enrichment negatively impacts meiobenthic copepods on Argentinean coasts
Authors: Sciberras Michel , MENECHELLA AGUSTIN G. , PÉREZ-MÉNDEZ NÉSTOR , CAZZANIGA NÉSTOR J. , MARRERO HUGO J.
Published: August 2023

Organic enrichment is a major threat to coastal environments, yet its impact on meiobenthic animals remains poorly understood. In marine sediments, copepods belong to the dominant taxa and they are known to regulate organic matter degradation and nutrient cycling. Here we performed a large-scale observational study to assess the impact of an increase in organic matter on meiobenthic copepod. We established a relation between the content of organic matter that reaches the coasts through eight rivers and the richness and diversity of meiobenthic copepods. In each site, three sampling points were considered (river-mouth, 200 m north, and 200 m south) and for each of these we estimated taxa diversity and taxa richness, organic matter concentration, and environmental parameters. We found that organic enrichment was negatively correlated with both taxa diversity and taxa richness, and this relation was stronger at river mouths. We also found a synergic interaction between salinity and organic matter content; instead, temperature and pH seemed not to be structuring the copepod community. This study provides evidence of the potential negative impact of coastal organic enrichment on the copepod diversity.
The Classification of the Bladder Cancer based on Vision Transformers (ViT)
Authors: Khedr Ola S. , Wahed Mohamed E. , Al-Attar Al-Sayed R. , Abdel-Rehim E. A.
Published: August 2023

Bladder cancer is a prevalent malignancy with diverse subtypes, including invasive, non-invasive, and normal tissue. Accurate classification of these subtypes is crucial for personalized treatment and prognosis. In this paper, we present a comprehensive study on the classification of bladder cancer into three classes using various deep-learning models. We utilized a dataset containing histopathological images of bladder tissue samples, split into a training set (70%), a validation set (15%), and a test set (15%). Four different deep-learning architectures were evaluated for their performance in classifying bladder cancer, EfficientNetB2, InceptionResNetV2, InceptionV3, and ResNet50V2. Additionally, we explored the potential of Vision Transformers with two different configurations, ViT_B32 and ViT_B16, for this classification task. Our experimental results revealed significant variations in the models' accuracies for classifying bladder cancer. The highest accuracy was achieved using the InceptionResNetV2 model, with an impressive accuracy of 98.73%. Vision Transformers also showed promising results, with ViT_B32 achieving an accuracy of 99.49%, and ViT_B16 achieving an accuracy of 99.23%. EfficientNetB2 and ResNet50V2 also exhibited competitive performances, achieving accuracies of 95.43% and 93%, respectively. In conclusion, our study demonstrates that deep learning models, particularly Vision Transformers (ViT_B32 and ViT_B16), can effectively classify bladder cancer into its three classes with high accuracy. These findings have potential implications for aiding clinical decision-making and improving patient outcomes in the field of oncology.
Effect of intracerebroventricular (ICV) injection of adrenomedullin and its interaction with NPY and CCK pathways on food intake regulation in neonatal layer-type chicks
Authors: Soleymani Maryam , Alimohammadi Samad , Hassanpour Shahin
Published: August 2023

Background
Adrenomedullin has various physiological roles including appetite regulation. The objective of present study was to determine the effects of intracerebroventricular injection of adrenomedullin and its interaction with NPY and CCK receptors on food intake regulation in layer-type chicks. In experiment 1, chickens received ICV injection of saline and adrenomedullin (1, 2 and 3 nmol). In experiment 2, birds injected with saline, B5063 (NPY1 receptor antagonist, 1.25 µg), adrenomedullin (3 nmol) and co-injection of B5063 + adrenomedullin. Experiments 3–5 were similar to experiment 2 and only SF22 (NPY2 receptor antagonist, 1.25 µg), SML0891 (NPY5 receptor antagonist, 1.25 µg) and CCK4 (1 nmol) were injected instead of B5063. In experiment 6, ICV injection of saline and CCK8s (0.125, 0.25 and 0.5 nmol) were done. In experiment 7, chickens injected with saline, CCK8s (0.125 nmol), adrenomedullin (3 nmol) and co-injection of CCK8s + adrenomedullin. After the ICV injection, birds were returned to their individual cages immediately and cumulative food intake was measured at 30, 60 and 120 min after injection.
Results
According to the results, adrenomedullin (2 and 3 nmol) decreased food intake compared to control group (P < 0.05). Co-injection of the adrenomedullin + B5063 amplified hypophagic effect of adrenomedullin (P < 0.05). The ICV injection of the CCK8s (0.25 and 0.5 nmol) reduced food intake (P < 0.05). Co-injection of the CCK8s + adrenomedullin significantly potentiated adrenomedullin-induced hypophagia (P < 0.05). Nevertheless, administration of the SF22, SML0891 and CCK4 had no effect on the anorexigenic response evoked by adrenomedullin in chickens (P > 0.05).
Conclusion
These results suggested that the hypophagic effect of the adrenomedullin is mediated by NPY1 and CCK8s receptors. However, our novel results should form the basis for future experiments.
A method of constructing highly durable conductive materials by growing metal particles inside and outside fibers through solvation and multivalent bonding forces
Authors: Wen Yan , Du Peibo , Sun Chao , Zhan Xiongwei , Cai Zaisheng , Ge Fengyan
Published: August 2023

Metallized textiles have shown promising applications in the fields of electrical conductivity, Joule heating and electromagnetic shielding. Poor durabilities, especially washability, which caused by the significant mechanical mismatch between rigid metal parts and textiles have hindered commercialization process of these functional textiles. This work constructed ultra-durable conductive cotton fabrics by growing copper nanoparticles with amorphous region-controlled swelling and multivalent bonding forces to complex the metal particles. The enlarged fiber amorphous zone and phen-amine molecules are used as templates to provide further possibilities for the internal and external enrichment growth of copper nanoparticles, providing good conductivity and high durability of the processed cotton fabric. The constructed fabric exhibits excellent electrical conductivity (6.09±0.36×10-3 Ω/sq), electrothermal conversion (60 s, 1 V, ~140 °C) and electromagnetic shielding efficiency (65.32 dB). Notably, the electrical conductivity of the fabric remains essentially unchanged (Rs/R0=1.106) after 100 standard washing tests. This is attributed to the increase in metal particle loading and the enhancement of metal-fiber bonding fastness. Therefore, this work might provide a novel insight for constructing ultra-washable conductive clothing textiles with heating and EMI shielding performance.
A Novel Framework to Classify Cancer through a Consecutive Utilization of Hybrid Feature Selection and Deep Learning
Authors: Mahto Rajul , Ahmed Saboor Uddin , Rahman Rizwan ur , Aziz Rabia Musheer , Roy Priyanka , Mallik Saurav , Li Aimin , Shah Mohd Asif
Published: August 2023

Cancer prediction in the early stage is a topic of major interest in medicine since it allows accurate and efficient actions for successful medical treatments of cancer. Mostly cancer datasets contain various gene expression levels as features with less samples, so firstly there is a need to eliminate similar features to permit faster convergence rate of prediction algorithms. These features (genes) enable us to identify cancer disease, choose the best prescription to prevent cancer and discover deviations amid different techniques. To resolve this problem, we proposed a hybrid novel technique CSSMO-based gene selection for cancer prediction. First, we made alteration of the fitness of Spider Monkey Optimization (SMO) with Cuckoo search (CS) algorithm viz., CSSMO for feature selection, which helps to combine the benefit of both metaheuristic algorithms to discover a subset of genes which helps to predict a cancer disease in early stage. Further, to enhance the accuracy of the CSSMO algorithm, we choose a cleaning process, minimum redundancy maximum relevance (mRMR) to lessen the gene expression of cancer datasets. Next, these subsets of genes are classified using Deep Learning (DL) to identify different groups or classes related to a particular cancer disease. Six different datasets have been utilized to analyze the performance of the proposed approach in terms of cancer sample classification and prediction with Recall, Precision, F1-Score, and confusion matrix. The proposed gene selection method with DL achieves much better prediction accuracy than other existing Deep Learning (DL) and Machine learning models with large gene expression dataset.
Impact of chronic infections in pregnancy: Association between maternal seropositivity for Toxoplasma gondii and fetal growth restriction
Authors: Martinez Victor Otero , Santos Nathália Ribeiro dos , Bah Homègnon Antonin Ferréol , Junior Erival Amorim Gomes , Costa Daisy Oliveira , Menezes-Filho José Antônio
Published: August 2023

Insults caused by acute infections during the gestational period on fetal development are known; however, new evidence suggests that chronic infectious diseases can also impact the maternal immune status and lead to negative consequences for the neonate. This study investigated the association between the prevalence of specific antibodies in pregnant women and alterations in fetal development at birth. A follow-up study evaluated women during the gestational period and their respective newborns at delivery time. The pregnant women were tested for the presence of antibodies to infectious agents: Toxoplasma gondii (T. gondii), cytomegalovirus (CMV), syphilis, human immunodeficiency virus (HIV), Hepatitis B, and C. Semi-structured questionnaires were administered to the pregnant women at the time of recruitment after obtaining informed consent. Detailed information about the newborns was extracted from medical records. The overall seroprevalence of T. gondii infection was 56.2%, and the general prevalence of CMV IgG antibodies was 96.3%. Non-primiparous pregnant women from socio-economic classes D-E and C2 had higher chances of testing positive for specific T. gondii IgG antibodies. Newborns classified as small for gestational age represented 12.9% of the total. Those born to mothers seropositive for anti-T. gondii IgG antibodies were 9.4 times more likely to be born small for gestational age (p = 0.035). The results suggest that chronic T. gondii infection may contribute to higher rates of newborns with growth restriction. These findings add to a growing body of evidence regarding the impact of chronic infectious diseases on intrauterine fetal development.