bluuebunny/crossref_metadata_2025 huggingface dataset:
B⟶P,VForm Factors with theB-Meson Light-Cone Sum Rules
Authors: Shen Yue-Long , Wei Yan-Bing
Published: February 2022

In this review, we discuss the calculation of theB⟶P,Vform factors within the framework of the light-cone sum rules with the light-cone distribution amplitudes of theB-meson. A detailed introduction to the definition, scale evolution, and phenomenological models of theB-meson distribution amplitudes is presented. We show two equivalent approaches of calculating the next-to-leading order QCD corrections to the sum rules for the form factors, i.e., the method of regions and the step-by-step matching in the soft-collinear effective theory. The power suppressed corrections to theB⟶P,Vform factors especially the contributions from the higher-twistB-meson distribution amplitudes are displayed. We also present numerical results of the form factors including both the QCD and the power corrections, and phenomenological applications of the predicted form factors such as the determination of the CKM matrix elementVub.
Correlation of HMGB1, PON-1, MCP-1, and Periodontal P. gingivalis with Amniotic Fluid Fecal Dye
Authors: Jin Zhen-Ai , Li Ying , Chen Wei-Bing , Wang Yu-Ying , Zhao Yi-Kun , Sun Xiang-Lan , He Jia-Jun , Jie Guo , Sun Yu-Mei
Published: February 2022

Background. This paper aims to investigate the correlation between high mobility group protein-1 (HMG-b1), antioxidant enzyme-1 (paraoxon-1, PON-1), monocyte chemoattractant protein-1 (monocyte chemoattractant protein-1, MCP-1), P. gingivalis, and MSAF. Materials and Methods. The total sample size comprised of 73 cases in both groups. These patients were further subdivided into 2 groups: the MSAF group and the control group. 38 women were in the MSAF group and 35 women with term amniotic fluid serum were in the control group. The MSAF group was selected as a full-term singleton amniotic fluid fecal infection group. Clinical data were collected, and specimens were collected. Fecal staining of amniotic fluid and full-term amniotic fluid removes the placenta and umbilical cord blood. The expression of HMGB1 in the placenta was observed by immune-histochemical staining of MSAF and control groups. The content of PON-1 in cord blood was determined by ELISA. Results. Correlation between maternal and neonatal clinical data and MSAF was done; MSAF group mean gestational age was 41.38 ± 1.40 weeks; control group mean gestational age was 39.20 ± 1.24 weeks. This study found no correlation between the birth weight, maternal age, sex, first/transmaternal, hyperthyroidism, hypothyroidism, and anemia between the MSAF and control group with nonsignificant P value (P>0.05). However, the fatal age, gestational diabetes, gestational hypertension, umbilical cord abnormalities, placental abnormalities, and neonatal asphyxia factors were statistically different with a significant P value of <0.05 between both groups. HMGB1 and Periodontal P. gingivalis are mostly expressed in placental trophoblast, vascular endothelial cells, and amniotic epithelial and interstitial cells. After HE staining of 72 placentas by HE in MSAF and control, 6 had acute chorioamnionitis (5.1 control), 32 had chronic (23.9), 35 had abnormal placentas, and three in MSAF had chorionic columnar metaplasia. In immune-histochemistry experiments, the HMGB1 expression intensity of placental tissue was higher in the MSAF group (P<0.05); however, the level of PON-1 was lower in the MSAF group as compared to the controls (P<0.05). Conclusions. Gestational age and placental abnormalities are clinical high-risk factors for MSAF. HMGB1, PON-1, MCP-1, and Periodontal P. gingivalis may be involved in the development of MSAF, suggesting an oxidative/antioxidant imbalance with inflammation, and may be one of the mechanisms for MSAF development.
Prediction of PM2.5 in an Urban Area of Northern Thailand Using Multivariate Linear Regression Model
Authors: Amnuaylojaroen Teerachai
Published: February 2022

As a result of considerable changes in rural areas in Northern Thailand, the frequency and intensity of haze outbreaks from particulate pollution, particularly fine particulate matter (PM2.5), has increased in this region. To supplement ground-based monitoring where PM2.5 observation is limited, this study applied a multivariate linear regression model to predict PM2.5 concentrations in 2020 using aerosol optical depth (AOD); meteorological parameters of wind velocity, temperature, and relative humidity; and gaseous pollutants such as SO2, NO2, CO, and O3 from ground-based measurements at three locations: Chiang Mai, Lampang, and Nan provinces in Northern Thailand. Two multivariate linear regression models were conducted in this study. The first model (model 1) is a generic model with meteorological parameters of aerosol optical depth (AOD), temperature, relative humidity, and wind speed. The second model (model 2) includes meteorological parameters and several gaseous pollutants, such as SO2, NO2, CO, and O3. In general, the regression model, which used hourly data from 2020 of the three provinces, adequately characterized the PM2.5 concentrations. The performance of model 2 was good for the prediction of PM2.5 concentrations at Chiang Mai (R2 = 0.52) and Lampang (R2 = 0.60). Model 2 improved the prediction of PM2.5 concentration compared to model 1 for both wet and dry seasons. However, model uncertainties were also present, which lays a foundation for further study.
Influences of Partial Substitution of Fish Meal with Defatted Black Soldier Fly (Hermetia illucens) Larvae Meal in Diets on Growth Performance, Biochemical Parameters, and Body Composition of Juvenile Chinese Soft-Shelled Turtles (Pelodiscus sinensis)
Authors: Shang Rongsheng , Man Limin , Wang Guiying , Li Mengfei , Liu Chengjun , Li Lusheng
Published: February 2022

The black soldier fly (Hermetia illucens) larvae meal (BSFM) has been widely applied in aquaculture production due to its rich nutritional value, easy availability, and renewability. However, to our knowledge, it has not been used in the diets for turtles. Here, we evaluated the acceptability of partial substitution of fish meal (FM) with defatted BSFM in the diets of juvenile Chinese soft-shelled turtles (Pelodiscus sinensis). A total of 225 juvenile turtles were randomly divided into D1, D2, D3, D4, and D5 groups, which were fed with BSFM replacing 0, 5%, 10%, 15%, and 20% FM, respectively, for 70 days. The results showed that growth performances of groups D2 and D3 were not significantly different (

P
>
0.05

) from that of group D1, whereas the growth performance compromised (

P
<
0.05

) in groups D4 and D5. The activity of serum alkaline phosphatase was higher (

P
<
0.05

) in group D3 relative to other groups, while alanine aminotransferase and aspartate aminotransferase activities were higher (

P
<
0.05

) in group D4 when compared with groups D1, D2, and D3. Liver lysozyme activity and malonaldehyde level were significantly higher (

P
<
0.05

) in group D1 relative to other groups, whereas total antioxidant capacity activity showed the opposite trend (

P
<
0.05

). The activities of hepatic total superoxide dismutase and glutathione peroxidase displayed a linear elevation (

P
=
0.011

and

P
<
0.001

, respectively) from groups D1 to D3. Intestinal amylase and protease activities linearly increased (

P
<
0.001

) with increasing BSFM levels, while intestinal lipase activity showed a quadratic increase and then a decrease with increasing BSFM levels (

P
=
0.011

). Muscle crude protein and fat contents increased (

P
<
0.05

) in group D3 when compared with groups D1 and D2. Muscle phenylalanine, glutamic, tryptophan, and arginine levels increased in group D1 in comparison with the other groups (

P
<
0.05

), whereas the opposite was true for isoleucine and proline levels. The broken-line analysis based on specific growth rate estimated that the optimal level for replacing dietary FM with BSFM is 5.0%, which could elicit benefits on both the growth performance and physiological health condition of the juvenile Chinese soft-shelled turtles.
A Simple Method to Detect SARS‐CoV‐2 in Wastewater at Low Virus Concentration
Authors: Thongpradit Supranee , Prasongtanakij Somsak , Srisala Supanart , Kumsang Yothin , Chanprasertyothin Suwannee , Boonkongchuen Pairoj , Pitidhammabhorn Dhanesh , Manomaipiboon Parnrudee , Somchaiyanon Peeraya , Chandanachulaka Siriwan , Hirunrueng Taiyatach , Ongphiphadhanakul Boonsong
Published: February 2022

Background. Since its initial appearance in December 2019, coronavirus disease 2019 (COVID‐19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has spread globally. Wastewater surveillance has been demonstrated as capable of identifying infection clusters early. The purpose of this study was to investigate a quick and simple method to detect SARS‐CoV‐2 in wastewater in Thailand during the early stages of the second outbreak wave when the prevalence of the disease and the virus concentration in wastewater were low. Methods. Wastewater samples were collected from a hospital caring for patients with COVID‐19 and from 35 markets, two of which were associated with recently reported COVID‐19 cases. Then, samples were concentrated by membrane filtering prior to SARS‐CoV‐2 detection by RT‐qPCR. Results. SARS‐CoV‐2 RNA was detected in the wastewater samples from the hospital; the Ct values for the N, ORF1ab, and S genes progressively increased as the number of patients admitted to the treatment floor decreased. Notably, the ORF1ab and S genes were still detectable in wastewater even when only one patient with COVID‐19 remained at the hospital. SARS‐CoV‐2 RNA was detected in the wastewater samples from fresh market where COVID‐19 cases were reported. Conclusions. Our findings suggest that wastewater surveillance for SARS‐CoV‐2 is sensitive and can detect the virus even in places with a high ambient temperature and relatively low prevalence of COVID‐19.
Energy-Efficient Hybrid Power System Model Based on Solar and Wind Energy for Integrated Grids
Authors: Jha Nishant , Prashar Deepak , Rashid Mamoon , Khanam Zeba , Nagpal Amandeep , AlGhamdi Ahmed Saeed , Alshamrani Sultan S.
Published: February 2022

Global energy needs have risen in recent years, and traditional energy sources such as fossil fuels are no longer viable. To meet the growing electricity demand, attention has moved to renewable energy sources such as solar and wind energy. Furthermore, the development of clean energy is vital for combating climate change. Various studies have shown the effectiveness of using hybrid systems (combination of solar photovoltaic and wind energy systems) for generating power. However, a significant amount of energy gets wasted. To prevent the wastage of energy, a dual-energy generation system for integrated grids has been suggested in this paper. The load data have been collected from various regions in Rajasthan, India. An optimal grid system configuration is designed using net present cost and cost per unit of energy. Other factors such as the tilt angle of PV array optimization, wind energy, and inverter optimization have also been used for increasing the reliability and stability of the system. Sensitivity analysis has been performed to analyze the effective variations of the capital costs on the developed system economy. The results obtained from the simulations show that the overall costs of generating electricity from diesel systems and nongrid-based systems have been reduced to 20% at 10% annual capacity shortage allowance. Upon cost analysis, we found that the total cost for installing the suggested system is 49,500 USD, whereas for other systems, the costs came out as 66,000 USD, 56,500 USD, and 56,300 USD, respectively.
Yunnan Baiyao Adjuvant Treatment for Patients with Hemoptysis: A Systematic Review and Meta-Analysis
Authors: Wang Yilan , Wang Xiaomin , Fu Hongfang , Kou Shuo , Huang Demei , Shen Zherui , Wang Fei , Wang Zhenxing
Published: February 2022

Background. Yunnan Baiyao (YNBY) is a traditional Chinese medicine used to treat bleeding. We evaluated the efficacy of YNBY plus conventional pharmaceutical treatment (CPT) versus CPT alone in patients with hemoptysis. Methods. A total of eight electronic databases were searched. The outcomes in the included studies were effective rate, hemoptysis volume, duration of hemoptysis and hospitalization, number of cases requiring endotracheal intubation, and adverse events (AEs). The studies were used to calculate risk ratios (RRs) or mean differences (MDs) with corresponding 95% confidence intervals. Risk of bias for included trials was assessed using the Cochrane risk of bias tool. Results. Thirteen RCTs were analyzed consisting of a total of 1379 patients. Treatment with YNBY + CPT had a greater effective rate than CPT alone (RR: 1.18; 95% CI: 1.13 to 1.23;

P
<
0.001

; I2 = 0%), a lower hemoptysis volume (MD: −107.37; 95% CI: −121.69 to −93.06;

P
<
0.001

; I2 = 0%), a shorter duration of hemoptysis (MD: −2.70; 95% CI: −2.96 to 2.43;

P
<
0.001

; I2 = 0%) and hospitalization (MD: −2.38; 95% CI: −2.93 to −1.83;

P
<
0.001

; I2 = 9%), and a reduction in the incidence of AEs (RR: 0.34; 95% CI: 0.23 to 0.51;

P
<
0.001

; I2 = 0%). YNBY + CPT treatment provided no significant difference in reducing the number of cases requiring endotracheal intubation compared to CPT alone (RR: 0.49; 95% CI: 0.15 to 1.60;

P
=
0.24

; I2 = 0%). Conclusion. YNBY plus CPT showed better efficacy than CPT for patients with hemoptysis. Our study provides medical evidence for the efficacy and safety of YNBY for hemoptysis.
Towards Building Cyberphysical Systems with Agile Architecture
Authors: Vodyaho Alexander , Zhukova Nataly , Schichkina Yulia , Abbas Saddam , Chernokulsky Vladimir
Published: February 2022

The current stage of technology development is characterized by an increase in the complexity of the created anthropogenic systems, a constant expansion of the scope of information technologies, an increase in the intelligence level of the created systems, and the appearance of new paradigms for building information-oriented systems such as cyber-physical systems, the Internet of things, and cloud and fog systems. Modern information-oriented systems very often have dynamic structure, implement complex adaptive behavior, and can be considered as systems with agile architecture. The article discusses one of the possible approaches for building cyberphysical systems with agile architecture on fog platforms. The idea of the proposed approach is to accumulate knowledge about the current state of the observed cyberphysical systems in the form of knowledge graphs. As a model, it is proposed to use multilevel relatively finite state operating automaton at the upper level and knowledge graphs at the lower level. A distinctive feature of the developed approach is that models that describe the current state of the observed system can be built automatically.
An Experimental and Modeling Study on the Combustion of Gasoline-Ethanol Surrogates for HCCI Engines
Authors: Yin Peng , Liu Wenfu , Yang Yong , Gao Haining , Zhang Chunhua
Published: February 2022

As an effective clean fuel, ethanol has the characteristics of improving antiknock quality and reducing emissions. It is an ideal antiknock additive for Homogeneous Charge Compression Ignition (HCCI) engines. The oxidation of gasoline-ethanol surrogates in HCCI engines is a very complex process which is dominated by the reaction kinetics. This oxidation process directly determines the performance and emissions of HCCI engines. Coupling the computational fluid dynamic (CFD) model with the gasoline-ethanol surrogate mechanism can be used for fuel design, so the construction of a reduced mechanism with high accuracy is necessary. A mechanism (278 species, 1439 reactions) at medium and low temperatures and experiments in a HCCI engine for the oxidation of gasoline-ethanol surrogates were presented in this paper. Directed relation graph with error propagation (DRGEP) method and quasi-steady-state assumption (QSSA) method were used in order to get a reduced model. Then, the kinetics of the vital reactions related to the formation and consumption of H and OH were adjusted. To validate the model, the HCCI experiments for the oxidation of gasoline-ethanol surrogates were conducted under different operating conditions. The verification result indicated that the present model can predict the oxidation process of gasoline-ethanol effectively.
Mobile Learning Platform in Cloud Computing with Information Security and Android System
Authors: Guan Dejun
Published: February 2022

In order to meet the real-time communication between teachers and students and improve students' interest and efficiency in learning, this paper designs a mobile learning communication system based on information security and Android system with cloud computing. By using the method of combining database records and web logs to mine the user's browsing records and behaviors, these implicit user behaviors are transformed into explicit user evaluations of the project. Then, the cosine similarity calculation method is used to calculate users and the similarity between the users. The users are clustered by the K-means clustering method, so that the users are automatically divided into several user clusters according to their behaviors. Finally, the user's nearest neighbor score is used to predict the pair. Based on the above method, a mobile learning communication system based on Android is realized, and the system basically meets the functional needs of users. The development of this system not only promotes the mutual communication between students but also facilitates the students' learning, which has a certain promoting effect on the improvement of their academic performance.
On the Use of Elzaki Decomposition Method for Solving Higher-Order Integro-Differential Equations
Authors: Al-Rawi Ekhlass S. , Samarchi Merna A.
Published: February 2022

In this article, we implemented the Elzaki decomposition technique (EDM) to solve Volterra–Fredholm integro-differential equations of higher-order. Illustrations are used to test the technique’s accuracy and validity. Comparison among the acquired consequences by EDM and actual solutions have proven the power and accuracy of this technique. This technique is dependable and able to supply analytic remedies for solving such equations.
The Rate of Clinical Outcomes in Atrial Fibrillation according to Antithrombotic Strategy: The COOL-AF Registry
Authors: Krittayaphong Rungroj , Winijkul Arjbordin , Methavigul Komsing , Sairat Poom , investigators C. O. O. L.-A. F.
Published: February 2022

Background. Ischemic stroke/transient ischemic attack (TIA), major bleeding, and death are common outcomes in atrial fibrillation (AF) patients, so appropriate antithrombotic therapy is crucial. The objective of this study was to investigate the rate of ischemic stroke/TIA, major bleeding, and death compared among AF patients who received oral anticoagulant (OAC) alone, antiplatelet alone, or OAC plus antiplatelet. Methods. Prospective data from the COOL-AF Registry (Thailand’s largest multicenter nationwide AF registry) were analyzed. Clinical, laboratory, and medication data were collected at baseline and during follow-up. Clinical outcomes, including ischemic stroke/TIA, major bleeding, and death, were collected. Results. There were 3,148 patients included. Mean age was68.1±10.8years and 1,826 (57.7%) were male. AF was paroxysmal in 998 (31.7%), persistent in 603 (19.2%), and permanent in 1,547 (49.1%). The mean follow-up duration was25.7±10.6months. The median rates of ischemic stroke/TIA, major bleeding, and death were 1.49 (1.21-1.81), 2.29 (1.94-2.68), and 3.89 (3.43-4.40) per 100 person-years. Antiplatelet alone, OAC plus antiplatelet, and OAC alone were used in 582 (18.5%), 308 (9.8%), and 2,258 (71.7%) patients, respectively. Antiplatelet alone significantly increased the risk of ischemic stroke/TIA and death compared to OAC alone. OAC plus antiplatelet significantly increased the risk of death compared to OAC alone. Conclusions. Antiplatelet was used in 890 (28.3%) AF, of whom 582 (18.5%) received antiplatelet alone, and 308 (9.8%) received antiplatelet and OAC. OAC plus antiplatelet significantly increased the risk of death without additional stroke prevention benefit. Antiplatelet alone should not be used in patients with AF.
Cancer Categorization Using Genetic Algorithm to Identify Biomarker Genes
Authors: Sathya M. , Jeyaselvi M. , Joshi Shubham , Pandey Ekta , Pareek Piyush Kumar , Jamal Sajjad Shaukat , Kumar Vinay , Atiglah Henry Kwame
Published: February 2022

In the microarray gene expression data, there are a large number of genes that are expressed at varying levels of expression. Given that there are only a few critically significant genes, it is challenging to analyze and categorize datasets that span the whole gene space. In order to aid in the diagnosis of cancer disease and, as a consequence, the suggestion of individualized treatment, the discovery of biomarker genes is essential. Starting with a large pool of candidates, the parallelized minimal redundancy and maximum relevance ensemble (mRMRe) is used to choose the top m informative genes from a huge pool of candidates. A Genetic Algorithm (GA) is used to heuristically compute the ideal set of genes by applying the Mahalanobis Distance (MD) as a distance metric. Once the genes have been identified, they are input into the GA. It is used as a classifier to four microarray datasets using the approved approach (mRMRe-GA), with the Support Vector Machine (SVM) serving as the classification basis. Leave-One-Out-Cross-Validation (LOOCV) is a cross-validation technique for assessing the performance of a classifier. It is now being investigated if the proposed mRMRe-GA strategy can be compared to other approaches. It has been shown that the proposed mRMRe-GA approach enhances classification accuracy while employing less genetic material than previous methods. Microarray, Gene Expression Data, GA, Feature Selection, SVM, and Cancer Classification are some of the terms used in this paper.
An Online Weighted Bayesian Fuzzy Clustering Method for Large Medical Data Sets
Authors: Zhang Cong , Xue Jing , Gu Xiaoqing
Published: February 2022

With the rapid development of artificial intelligence, various medical devices and wearable devices have emerged, enabling people to collect various health data of themselves in hospitals or other places. This has led to a substantial increase in the scale of medical data, and it is impossible to import these data into memory at one time. As a result, the hardware requirements of the computer become higher and the time consumption increases. This paper introduces an online clustering framework, divides the large data set into several small data blocks, processes each data block by weighting clustering, and obtains the cluster center and corresponding weight of each data block. Finally, the final cluster center is obtained by processing these cluster centers and corresponding weights, so as to accelerate clustering processing and reduce memory consumption. Extensive experiments are performed on UCI standard database, real cancer data set, and brain CT image data set. The experimental results show that the proposed method is superior to previous methods in less time consumption and good clustering performance.
A Simple and Efficient Deep Learning-Based Framework for Automatic Fruit Recognition
Authors: Hussain Dostdar , Hussain Israr , Ismail Muhammad , Alabrah Amerah , Ullah Syed Sajid , Alaghbari Hayat Mansoor
Published: February 2022

Accurate detection and recognition of various kinds of fruits and vegetables by using the artificial intelligence (AI) approach always remain a challenging task due to similarity between various types of fruits and challenging environments such as lighting and background variations. Therefore, developing and exploring an expert system for automatic fruits’ recognition is getting more and more important after many successful approaches; however, this technology is still far from being mature. The deep learning-based models have emerged as state-of-the-art techniques for image segmentation and classification and have a lot of promise in challenging domains such as agriculture, where they can deal with the large variability in data better than classical computer vision methods. In this study, we proposed a deep learning-based framework to detect and recognize fruits and vegetables automatically with difficult real-world scenarios. The proposed method might be helpful for the fruit sellers to identify and differentiate various kinds of fruits and vegetables that have similarities. The proposed method has applied deep convolutional neural network (DCNN) to the undertakings of distinguishing natural fruit images of the Gilgit-Baltistan (GB) region as this area is famous for fruits’ production in Pakistan as well as in the world. The experimental outcomes demonstrate that the suggested deep learning algorithm has the effective capability of automatically recognizing the fruit with high accuracy of 96%. This high accuracy exhibits that the proposed approach can meet world application requirements.
Factors Affecting Car Sickness of Passengers Traveled by Vehicles in North Shewa Zone, Oromia, Ethiopia
Authors: Tadese Zelalem , Teshome Berhanu , Mengistu Endeshaw
Published: February 2022

Introduction. Car sickness is the state of being unhealthy as a result of motions that occur while traveling by vehicles. Passengers traveled by vehicles had experienced car sickness not only as a result of the biological effects but also other associated factors. Therefore, this study aimed to identify sociocultural, individual behavioral factors and situational factors resulting in car sickness of passengers traveling by minibus or bus or both. Methods. This study was designed in a cross‐sectional study and employed a quantitative approach to collect data among 384 passengers. Primary data were collected by a survey method. Both adult male and female passengers without any confirmed disease participated in the study. Car sickness was measured as whether a passenger traveling by vehicle in the past six months had at least one of the signs and symptoms either vomiting, nausea, headache, and (cold) sweating. Quantitative data were analyzed using descriptive statistics, bivariate analysis, and binary logistic regression. The multivariate logistic regression model was employed and used to execute the associated risk factors by declaring all statistical tests significantly at p‐value ≤0.05. Results. The results indicated that being older (aOR = 0.972, 95% CI: 0.947, 0.999) and male passengers (aOR = 0.357, 95% CI: 0.190, 0.673) significantly decreased occurrences of car sickness. However, sleep deprivation (aOR = 8.540, 95% CI: 2.575, 28.328), eating heavy meals before starting traveling (aOR = 4.147, 95% CI: 1.659, 10.366), the aggressiveness of drivers (aOR = 5.467, 95% CI: 2.456, 12.172), and travel with other passengers in overcrowded vehicles (aOR = 9.5212, 95% CI: 5.194, 17.455) were significantly contributed to car sickness. Conclusions. The findings suggested that younger passengers should take medications that reduce the sensation of car sickness before starting traveling and female passengers should reduce unpaid domestic work before their travels. In order to prevent or reduce the sensation of car sickness, passengers should take enough physical rest, sleep well, and avoid eating heavy meals before a journey. Furthermore, passengers should strongly advise or kindly request aggressive drivers to drive slowly and uniformly. Last, the passengers should avoid traveling with other passengers in overcrowded vehicles as much as possible.
Patterns and Determinants of Change in Cortisol Levels and Thyroid Function as a Function of Cardiac Risk in Children Undergoing Cardiac Surgery
Authors: Al-Sofyani Khouloud Abdulrahman , Uddin Mohammed Shahab , Qulisy Ebtehal Ahmed , Al-Radi Osman Osama
Published: February 2022

Background. Children undergoing cardiac surgery with cardiopulmonary bypass (CPB) are exposed to the risk of hormonal imbalances resulting from acute stress, which may eventually result in high postoperative mortality and morbidity. Objective. We assessed adrenal and thyroid hormonal changes and their determinants following cardiac surgery in children and explored their prognostic value in predicting cardiac outcomes. Study Design and Methods. A prospective cohort study was conducted at King Abdulaziz University Hospital (KAUH), between 2017 and 2018. The study involved 46 children aged 14 years or younger who underwent elective cardiac surgery with cardiopulmonary bypass. Serum levels of cortisol, TSH, fT3, and fT4 were measured preoperatively and 24, 48, and 72 hours after surgery. The cardiac risk was assessed using the risk adjustment for congenital heart surgery (RACHS) scale. A composite cardiovascular outcome was analyzed as a numerical variable and calculated as the number of cardiovascular events. Results. Overall, the changes in thyroid function parameters resulted in a U-shaped curve, while cortisol levels yielded a bell-shaped curve. The most significant changes occurred at 24 hours postop, including a decrease in mean TSH by 2.08 μIU/L (

p
<
0.001

), fT3 by 2.39 pmol/L (

p
<
0.001

), and fT4 by 2.45 pmol/L (

p
<
0.001

) and an increase in cortisol levels by 406.48 nmol/L (

p
<
0.001

) with respect to the baseline. Cortisol concentration peaked higher and recovered slower among patients with high cardiac risk than their counterparts. Cardiovascular outcomes were independently predicted by the extent of the decline in fT4 and TSH at 48 and 72 hours postop, with reference to the baseline, and by the cortisol level at 24 h postop, independent of the baseline, besides the RACHS category. Conclusion. Cardiac surgery among children yields a high adrenocortical response and a high incidence of nonthyroidal illness syndrome, increasing cardiovascular risk. A preventive management strategy involves improving surgical techniques to minimize trauma-related stress.
Relationship between Serum FGF21 and vWF Expression and Carotid Atherosclerosis in Elderly Patients with Hypertension
Authors: Bian Jing , Chen Lairong , Li Qin , Zhao Yunfeng , Yin Delu , Sun Shanhong
Published: February 2022

Cardiovascular (CV) and cerebrovascular (CBV) diseases are common in the elderly and cause severe damage, with high morbidity, disability, and mortality. Hypertension, as a risk factor for a variety of CV and CBV diseases, also affects many elderly patients. This study aimed to investigate the relationship between serum FGF21 and vWF expression and carotid atherosclerosis (CAS) in elderly patients with hypertension. We recruited 143 elderly hypertensive patients admitted to our hospital from July 2017 to November 2019 to this study, including 75 patients with comorbid CAS (the observation group, OG) and 68 patients without CAS (the control group, CG). Enzyme-linked immunosorbent assay (ELISA) was used to test serum expression levels of FGF21 and vWF; receiver operating characteristic (ROC) curves to evaluate the value of FGF21 and vWF in diagnosing CAS and predicting the 6-month prognosis in elderly hypertensive patients; Pearson’s correlation analysis to analyze the correlation of FGF21/vWF with the plaque thickness and stenosis area in hypertensive patients with CAS. The incidence of CV and CBV events was markedly higher in the high FGF21/vWF group than in the low FGF21/vWF group. Patients from OG were divided into the high FGF21/vWF group and the low FGF21/vWF group based on the median expression level of FGF21/vWF, then the incidence of cardiovascular (CV) and cerebrovascular (CBV) events was compared between the high and low expression groups. Serum levels of FGF21 and vWF were markedly higher in patients from OG than in patients from CG. Both FGF21 and vWF were in positive correlation with the plaque thickness and stenosis area in patients from OG. The area under the ROC curve (AUC) for diagnosing CAS was 0.790 by FGF21 and 0.807 by vWF; the AUC for predicting the occurrence of CV and CBV events was 0.771 by FGF21 and 0.754 by vWF. Serum levels of FGF21 and vWF are increased in elderly patients with hypertension and comorbid CAS, so they can be used for diagnosing CAS and predicting prognosis.
Classification of Breast Cancer Images by Implementing Improved DCNN with Artificial Fish School Model
Authors: Thilagaraj M , Arunkumar N. , Govindan Petchinathan
Published: February 2022

Breast cancer is an important factor affecting human health. This issue has various diagnosis process which were evolved such as mammography, fine needle aspirate, and surgical biopsy. These techniques use pathological breast cancer images for diagnosis. Breast cancer surgery allows the forensic doctor to histologist to access the microscopic level of breast tissues. The conventional method uses an optimized radial basis neural network using a cuckoo search algorithm. Existing radial basis neural network techniques utilized feature extraction and reduction parts separately. It is proposed that it overcomes the CNN approach for all the feature extraction and classification process to reduce time complexity. In this proposed method, a convolutional neural network is proposed based on an artificial fish school algorithm. The breast cancer image dataset is taken from cancer imaging archives. In the preprocessing step of classification, the breast cancer image is filtered with the support of a wiener filter for classification. The convolutional neural network has set the intense data of an image and is used to remove the features. After executing the extraction procedure, the reduction process is performed to speed up the train and test data processing. Here, the artificial fish school optimization algorithm is utilized to give the direct training data to the deep convolutional neural network. The extraction, reduction, and classification of features are utilized in the single deep convolutional neural network process. In this process, the optimization technique helps to decrease the error rate and increases the performance efficiency by finding the number of epochs and training images to the Deep CNN. In this system, the normal, benign, and malignant tissues are predicted. By comparing the existing RBF technique with the cuckoo search algorithm, the presented model attains the outcome in the way of sensitivity, accuracy, specificity, F1 score, and recall.
A Novel One-Shot Object Detection via Multifeature Auxiliary Information
Authors: Song Yu , Li Min , Du Weidong , Gou Yao , Wu Zhaoqing , He Yujie
Published: February 2022

With the advantage of using only a limited number of samples, few-shot learning has been developed rapidly in recent years. It is mostly applied in the object classification or detection of a small number of samples which is typically less than ten. However, there is not much research related to few-shot detection, especially one-shot detection. In this paper, the multifeature information-assisted one-shot detection method is proposed to improve the accuracy of one-shot object detection. Specifically, two auxiliary modules are applied to the detection algorithm: Semantic Feature Module (SFM) and Detail Feature Module (DFM), which, respectively, extract semantic feature information and detailed feature information of samples in the support set. Then these two kinds of information are then calculated with the feature image extracted from the query image to obtain the corresponding auxiliary information that is used to complete one-shot detection. Thanks to the two auxiliary modules, which can retain more semantic and detailed information of samples in the support set, the proposed method can enhance the utilization rate of sample feature information and improve object detection accuracy by 2.97% compared to the benchmark method.
Broadband Circularly Polarized CPW-Fed Monopole Antenna with a Via-Free CRLH-TL Unit Cell
Authors: Liu Liangyuan , Shi Xiangqun
Published: February 2022

This article presents a broadband circularly polarized composite right/left-hand (CRLH) antenna. A compact microstrip line inductor and an interdigital capacitor are used to form a left-handed parallel inductor and a left-handed series capacitor. The metamaterial parameters of the series inductor and the parallel inductor are optimized. The asymmetric perturbation is introduced to excite the circularly polarized (CP) electromagnetic wave. The influence of interdigital capacitance on the electrical performance of the antenna is analyzed theoretically and experimentally. The value of CL is changed to reduce the electrical size of the antenna, and the resonant frequency of the antenna is reduced accordingly. The physical dimensions of this CPW-Fed monopole antenna are 25 mm

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24 mm

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1 mm. The measured 10 dB wide impedance bandwidth is 79.5%, and the measured 3 dB axial ratio (AR) bandwidth is 56.2%.
[Retracted] Mitochondrial ROS Produced by Skeletal Muscle Mitochondria Promote the Decisive Signal for UPRmt Activation
Authors: Wang Zhe , Bo Hai , Song Yu , Li Can , Zhang Yong
Published: February 2022

The mitochondrial unfolded protein response (UPRmt) can repair and remove misfolded or unfolded proteins in mitochondria and enhance mitochondrial protein homeostasis. Reactive oxygen species (ROS) produced by regular exercise is a crucial signal for promoting health, and skeletal muscle mitochondria are the primary source of ROS during exercise. To verify whether UPRmt is related to ROS produced by mitochondria in skeletal muscle during regular exercise, we adapted MitoTEMPO, mitochondrially targeted antioxidants, and ROS production by mitochondria. Our results showed that mitochondrial ROS is the key factor for activating UPRmt in different pathways.
Prediction of Train Station Delay Based on Multiattention Graph Convolution Network
Authors: Zhang Dalin , Xu Yi , Peng Yunjuan , Zhang Yumei , Wu Daohua , Wang Hongwei , Liu Jintao , Mohammed Sabah , Calvi Alessandro
Published: February 2022

Train station delay prediction is always one of the core research issues in high-speed railway dispatching. Reliable prediction of station delay can help dispatchers to accurately estimate the train operation status and make reasonable dispatching decisions to improve the operation and service quality of rail transit. The delay of one station is affected by many factors, such as spatiotemporal factor, speed limitation or suspension caused by strong wind or bad weather, and high passenger flow caused by major holiday. But previous studies have not fully combined the spatiotemporal characteristics of station delay and the impact of external factors. This paper makes good use of the train operation data, proposes the multiattention mechanism to capture the spatiotemporal characteristics of train operation data and process the external factors, and establishes a Multiattention Train Station Delay Graph Convolution Network (MATGCN) model to predict the train delay at high-speed railway stations, so as to provide references for train dispatching and emergency plan. This paper uses real train operation data coming from China high-speed railway network to prove that our model is superior to ANN, SVR, LSTM, RF, and TSTGCN models in the prediction effect of MAE, RMSE, and MAPE.
The E3 Ubiquitin Ligase TRIM11 Facilitates Gastric Cancer Progression by Activating the Wnt/β-Catenin Pathway via Destabilizing Axin1 Protein
Authors: Zhou Ling , Wang Heng , Zhong Min , Fang Zhi , Le Yi , Nie Fengting , Zhou Juanjuan , Xiong Jianping , Xiang Xiaojun , Fang Ziling
Published: February 2022

Background. Aberrant expression of tripartite motif 11 (TRIM11) and the Wnt/β-catenin pathway are essential for facilitating tumorigenesis and progression in multiple types of cancer. Aim. To investigate the molecular changes linking the dysregulation of TRIM11 and Wnt/β-catenin pathway activation in gastric cancer (GC) progression. Methods. The expression levels of TRIM11 were detected in GC tissues and cells by immunohistochemistry and western blotting. The role of TRIM11 in the growth, proliferation, and invasion of gastric cancer cells was observed by a series of cell functional experiments and further verified in vivo. Co-immunoprecipitation (Co-IP), immunofluorescence, cycloheximide, and western blotting assays and other experiments were conducted to explore the mechanisms of TRIM11 underlying the regulation of the Wnt/β-catenin pathway. For further verification, rescue experiments were performed by cotransfection of TRIM11 and Axin1 siRNA in GC cells. Results. Using Co-IP assays, we identified TRIM11 as a potent binding partner of Axin1 in GC cells. Elevated TRIM11 levels were significantly correlated with unfavorable clinical outcomes and poor survival in patients with GC. In addition, TRIM11 promoted the cell proliferation and invasion capacities of GC cells in vitro and tumor growth in vivo. Mechanistic investigations revealed that TRIM11 destabilized Axin1 protein by interacting with Axin1, thus inducing the activation of the Wnt/β-catenin pathway. Moreover, we found that the oncogenic effects of TRIM11 on GC cells were partly mediated by suppression of Axin1. Furthermore, the protein expression of TRIM11 and Axin1 was negatively correlated in GC tissues. Conclusion. Collectively, our findings not only establish a pivotal TRIM11-Axin1-β-catenin axis in driving GC progression but also indicate that TRIM11 serves as a valuable therapeutic target for the treatment of GC patients.
Deferoxamine Inhibits Acute Lymphoblastic Leukemia Progression through Repression of ROS/HIF-1α, Wnt/β-Catenin, and p38MAPK/ERK Pathways
Authors: You Hongliang , Wang Dao , Wei Linlin , Chen Jiao , Li Huanhuan , Liu Yufeng
Published: February 2022

Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer, with a feature of easy to induce multidrug resistance and relapse. Abundant studies have proved that iron overload strengthens the growth and metastasis of tumor cells. Herein, we found that deferoxamine (DFO) effectively decreased the concentration of intracellular iron in ALL cells. DFO inhibited proliferation, induced apoptosis, and obstructed cell cycle of ALL cells, whereas DFO and dextriferron (Dex) used in combination significantly decreased the sensitivity of ALL cells to DFO. Reactive oxygen species (ROS) level was reduced in ALL cells treated with DFO, and the combination of DFO and Dex reversed the effects of DFO. In vivo, DFO inhibited mouse tumor growth. Besides, cyclinD1, β-catenin, c-Myc, hypoxia inducible factor 1 (HIF-1), p-p38MAPK, and p-ERK1/2 protein levels were significantly downregulated, and the levels of prolyl hydroxylase-2 (PHD-2) were upregulated after treated with DFO, whereas Dex treatment reversed those in vivo and in vitro. In conclusion, DFO inhibited the proliferation and ALL xenograft tumor growth, obstructed the cell cycle, and induced apoptosis of ALL cells, probably via inactivating the ROS/HIF-1α, Wnt/β-catenin, and p38MAPK/ERK signaling.
Analyzing Rail Traffic Diversion Based on Machine Learning Technique considering Transportation Security
Authors: Luo Jing , Zhou Dai , Ma Wenjun , Zhao Guohua
Published: February 2022

Based on a stated preference survey, we comprehensively analyze the travel psychology of residents and the advantages and disadvantages of rail transit and conventional buses, travel time, travel cost, travel security, and vehicle comfort and investigate the relationship between the relevant influencing factors and the transition probability from rail transit to buses. A stochastic utility theory is introduced to describe the transfer behavior pertaining to travel modes, and a binary Logit model for diversion transfer is constructed. The decision tree is also used to predict the diversion transfer. Then, based on the large amount of travel willingness data obtained through the stated preference survey, a maximum likelihood estimation method is used to calibrate the parameters of the binary Logit model. The performance of the binary Logit proves to be better than that of the decision tree. Results show that the travel time most notably affects the passenger flow transfer, followed by the vehicle comfort. Finally, Guangzhou Rail Transit Line 3 is considered an example, and the diversion route planning and design are performed according to the constructed diversion transfer probability model to verify the effectiveness and practicability of the model. The research provides an effective theoretical basis and technical reference for other cities to perform rail traffic diversion planning. Based on these results, the following suggestions can be made: (1) the organization of public transportation routes, delivery volume, and travel speed outside should be improved; (2) undertaking combined operation of bus and rail transportation and integrated development is preferred; (3) the transportation management should focus on the comprehensive function development and hardware support of public transportation stations. The convenience and comfort of rail transit are closely related to the facilities and functions of the stations and their connections, which should be highly valued.
Diosmetin Protects against Cardiac Hypertrophy via p62/Keap1/Nrf2 Signaling Pathway
Authors: Guo Yingying , Li Dan , Cen Xian-feng , Qiu Hong-liang , Ma Yu-lan , Liu Yi , Huang Si-hui , Liu Li-bo , Xu Man , Tang Qi-Zhu
Published: February 2022

An important pathophysiological consequence of pressure overload-induced cardiac hypertrophy is adverse cardiac remodeling, including structural changes in cardiomyocytes and extracellular matrix. Diosmetin (DIO), a monomethoxyflavone isolated from citrus fruits, had antioxidative stress effects in multiple organs. The purpose of this study was to examine the biological effect of diosmetin on pathological cardiac hypertrophy. In mice, diosmetin treatment reduced cardiac hypertrophy and dysfunction in an aortic banding- (AB-) induced pressure overload model and reducing myocardial oxidative stress by increasing antioxidant gene expression. In vitro, diosmetin (10 or 50 μm, 12 h or 24 h) protected PE-induced cardiomyocyte hypertrophy in neonatal rat cardiomyocytes. Mechanistically, diosmetin inhibited autophagy by activating the PI3K/Akt pathway. In particular, diosmetin induced the accumulation of p62 and its interaction with Keap1, promoted the nuclear translocation of Nrf2, and increased the expression of antioxidant stress genes in the process of cardiac hypertrophy. Furthermore, knockdown of p62 in rat primary cardiomyocytes abrogate the protective effect of diosmetin on cardiomyocyte hypertrophy. Similarly, the Nrf2 inhibitor ML385 obviously abolished the above effects by diosmetin treatment. In conclusion, our results suggest that diosmetin protects cardiac hypertrophy under pressure overload through the p62/Keap1/Nrf2 signaling pathway, suggesting the potential of diosmetin as a novel therapy for pathological cardiac hypertrophy.