bluuebunny/crossref_metadata_2025 huggingface dataset:
The New Economic Era Analysis of the Structure System of Chinese Household Consumption Expenditure Based on the ELES Model
Authors: Fan Chaozhi , Law Siong Hook , Ibrahim Saifuzzaman , Naseem N. A. M.
Published: August 2022

In recent years, the new economy has entered a phase of rapid development and upgrading China’s service consumption is driving the continuous optimization of the population’s consumption structure. To realize the rationalization of the Chinese household consumption structure, the ELES model is used to analyze the structure system of Chinese household consumption expenditure. This article constructs the ELES model, divides the types of Chinese household consumption expenditure structure systems, establishes consumption expenditure function, analyzes the influencing factors of the consumption expenditure structure system, and obtains the analysis results from static and dynamic aspects. Based on the statistics of Chinese household consumption expenditure data in recent years, this article obtains the analysis results of the consumption expenditure structure system: the basic consumption demand and marginal consumption tendency of food are in the first place, and the consumption expenditure structure system has gradually changed into the development-type and enjoyment-type consumption mode. Through increasing the income of rural residents, guiding reasonable consumption concept, optimizing consumption environment, and so on, we can promote the proposal and implementation of the optimization of China’s household consumption expenditure structure system to improve the rationalization of China’s household consumption structure system.
Deep Learning for College English Education Evaluation
Authors: Shi Jing
Published: August 2022

With the expanding and growth of the present reform of English education and teaching, the study of English education quality is receiving more and more attention. The focus of enhancing the quality of English education is to enhance the quality of teaching, and English education assessment is a main initiative to improve the quality of English education and teaching. So, the formation and development of the English education quality assessment system are of great importance to education management. This paper is based on an in-depth study of the present condition and characteristics of English education quality evaluation in colleges and combines the characteristics of deep learning. To provide a feasible solution for the English education evaluation model, this paper constructs a deep learning-based English education quality evaluation model and theoretically analyzes and compares the training results of the deep learning algorithm and the algebraic algorithm used in the model, respectively. Through simulation analysis, we can conclude that the English education evaluation based on deep learning suggested in this paper has achieved good evaluation results.
Strengthening Shear Resistance of Beams without Web Reinforcements Using Vertical Prestressed Steel Bars
Authors: Liu Zihui , Cui Yujun , Wang Weiqi , Cao Wei , Wang Xuan , Xue Xingwei
Published: August 2022

Ensuring the shear capacity of concrete structures is crucial. The vertical prestressed steel bar (VPSB) strengthening method is effective for improving the shear behaviour of concrete structures. Four concrete beams are investigated to reveal the effect of VPSBs on the shear capacity of concrete beams without web reinforcement. Test results indicate that the shear capacity of the test beam strengthened by VPSBs in the beam is significantly increased by more than 95%, and the failure mode of the test beam changes from diagonal tension failure to shear compression failure. Additionally, the results provide insights into the strengthening mechanism of VPSBs, i.e., the shear contribution of the VPSBs can be categorised into two stages. The vertical compressive stress provides shear contribution in the first stage and provides control in terms of crack development; meanwhile, in the second stage, the stirrup action by VPSBs contributes to shear.
A Similarity-Based Hesitant Fuzzy Group Decision Making Approach and Its Application in Hydraulic Engineering Project Management
Authors: Zhu Sulu , Gao Pengqun , Cheng Qunzhi , Zhou Yang , Yang Shiliang , Zhang Tianming
Published: August 2022

Hesitancy and uncertainty features of experts are common in the decision-making process, especially for the project management events. To solve this problem, a novel similarity-based decision-making approach is put forward, as well as an application to the hydraulic engineering project management. Several experts, who are invited in the decision-making process, are suggested to adopt hesitant fuzzy preference relations (HFPRs) to show their evaluations. To measure the similarity degree of experts, a novel integrated similarity index (SI) is given combining the alternative ranking-based similarity index (SIAR) and distance-based similarity index (SID) between HFPRs. The SIAR can be derived from the comparison of the alternative rankings, while the SID depends on evaluations’ distance degree. After that, on the basic of opinion transition probabilities, experts’ weights are allocated, which is necessary for the aggregation process. Then, the collective preferences can be aggregated from the individuals’ evaluations. Afterwards, the above methods along with a score function are adopted to obtain the optimal solution for an actual hydraulic engineering project management event. Finally, for verifying the feasible and effective features of the presented methods, some significative discussions and comparative analyses are provided.
The In Vitro Antimicrobial and Antibiofilm Activities of Lysozyme against Gram-Positive Bacteria
Authors: Liu Fang , Wang Xing , Huang Lijie , Wang Xinling , Kong Lili , Duan Jinyou , Zhang Xiaoli , Mu Haibo , He Jianguo
Published: August 2022

Objective. To analyze the in vitro antibacterial and antibiofilm activities of lysozyme (LYS) and its combination with various drugs against Gram-positive bacteria (GPB,

n
=
9

), thus to provide an exploration direction for drug development. Methods. The minimum inhibitory concentrations (MICs) of linezolid (LZD), amikacin (AMK), ceftriaxone/sulbactam (CRO/SBT), cefotaxime/sulbactam (CTX/SBT), piperacillin/sulbactam (PIP/SBT), doxycycline (DOX), levofloxacin (LVX), amoxicillin/clavulanate potassium (7 : 1, AK71), imipenem (IPM), azithromycin (AZM), and their combinations with LYS were determined with tuber twice dilution. The antimicrobial and antibiofilm activities of LYS, AZM, LVX, and their combinations with others were evaluated through MTT and crystal violet assay. Results. High-dose LYS (30 μg/mL) combined with PIP/SBT and AK71, respectively, showed synergistic antibacterial activities against methicillin-resistant Staphylococcus aureus (MRSA), while it showed no synergistic activities when combined with other drugs. LYS and AZM inhibited the biofilm formation of one MRSA strain, but they and LVX had no similar activities against methicillin-resistant Staphylococcus epidermidis (MRSE) or vancomycin-resistant Enterococcus faecium (VREF). Particularly, LYS increased the permeability of biofilms of MRSA 33 and exhibited antibiofilm activities against MRSA 31 (

inhibition
 
rate
=
38.1
%

) and MRSE 61 (

inhibition
 
rate
=
46.6
%

). The combinations of PIP/SBT+LYS, AMK+LYS, and LZD+LYS showed stronger antibiofilm activities against MRSA 62, MRSE 62, MRSE 63, and VREF 11. Conclusion. The antimicrobial and antibiofilm activities of LYS against MRSA were better than AZM, while that of LYS against MRSE and VREF, respectively, was similar with AZM and LVX.
Integrating Entrepreneurship and Innovation Education into Higher Vocational Education Teaching Methods Based on Big Data Analysis
Authors: Tan Longyan , Du Feng
Published: August 2022

At present, IT plays an increasingly important role in promoting the various industries in society. Similarly, IT is inseparable from the application of IT. To this end, the article first expounds the important role that IT can play in providing a platform for IT, providing information support, and providing new opportunities in the colleges. Secondly, it points out that there are problems such as insufficient application, imperfect facilities, and one-sided application of IT in colleges. Finally, it discusses the establishment of an incentive mechanism for IT with it, the improvement of its facilities, the construction of an intelligent service system based on IT, and the construction of a virtual practice venue based on education. This paper puts forward the realization ways of IT in colleges.
Detecting Personal Medication Intake in Twitter via Domain Attention-Based RNN with Multi-Level Features
Authors: Xiong Shufeng , Batra Vishwash , Liu Liangliang , Xi Lei , Sun Changxia
Published: August 2022

Personal medication intake detection aims to automatically detect tweets that show clear evidence of personal medication consumption. It is a research topic that has attracted considerable attention to drug safety surveillance. This task is inevitably dependent on medical domain information, and the current main model for this task does not explicitly consider domain information. To tackle this problem, we propose a domain attention mechanism for recurrent neural networks, LSTMs, with a multi-level feature representation of Twitter data. Specifically, we utilize character-level CNN to capture morphological features at the word level. Subsequently, we feed them with word embeddings into a BiLSTM to get the hidden representation of a tweet. An attention mechanism is introduced over the hidden state of the BiLSTM to attend to special medical information. Finally, a classification is performed on the weighted hidden representation of tweets. Experiments over a publicly available benchmark dataset show that our model can exploit a domain attention mechanism to consider medical information to improve performance. For example, our approach achieves a precision score of 0.708, a recall score of 0.694, and a F1 score of 0.697, which is significantly outperforming multiple strong and relevant baselines.
Creation of Drama Art Based on Deep Learning and Evolution Strategy
Authors: Tang Xin
Published: August 2022

The rapid development of information technology has promoted the growth of deep learning, artificial intelligence, and big data technology. Nowadays, the artistic form of traditional opera creation is accepted and respected by people—more and more people like the art form. However, the artistic creation of traditional opera needs inspiration. The essence of inspiration creation is to reconstruct its objective structure. The deep learning algorithm’s essence is to extract all of the attributes of sample self-learning input data and use them as inspiration for artistic production. First, this paper briefly introduces the deep learning and evolution strategy and uses these algorithms in opera art creation to construct 1 + λ. With the help of this evolutionary algorithm, an optimal solution is obtained through random evolution. The evolution strategy establishes the evolution function matrix. Starting from the situation of students learning opera art, this article examines the process of creating opera art using an in-depth learning and evolution technique. The results show that 96 percent of the students have contact with opera while watching an opera tour. During this, they were not interested in the performance of literary drama in traditional opera. However, it was noticed that they were deeply interested in martial arts, clown performances, and drama stage performances. Finally, the audience group of opera artistic creation is analyzed in the form of opera animation of “A Journey to the West: The Return of the Great Sage.” It signifies that the opera’s leading audience group is aged 25 to 29. However, they account for only 30 percent.
Application of Three-Dimensional Arterial Spin Labeling Technique in the Assessment of Cerebral Blood Perfusion in Patients with Middle Cerebral Artery Occlusion: Analysis of Clinical Implications and Prognostic Factors
Authors: Zhou Jianguo , Fu Dayong , Meng Yun , Lu Mingcong , Hu Fangyun , Cheng Hongke
Published: August 2022

Objective. To explore the value of three-dimensional- (3D-) arterial spin labeling (ASL) technique in evaluating cerebral perfusion in patients with unilateral middle cerebral artery occlusion (MCAO) and to observe the influencing factors of poor prognosis via long-term follow-up of patients who survived the disease. Methods. The clinical data of 60 patients with unilateral middle cerebral artery (MCA) M1 segment occlusion diagnosed by magnetic resonance angiography (MRA) from January 2018 to January 2022 were retrospectively analyzed. All patients were examined by routine MRI, MRA, and 3D-ASL, in which two postlabeling delays (PLDs; 1525 ms and 2525 ms) were used in 3D-ASL. Cerebral blood flow (CBF) in the regions of interest (ROIs) of MCA on the affected side and the mirror side was measured. The clinical data and laboratory indexes of patients were collected and evaluated by clinical scales. With the modified Rankin Score (mRS) as the outcome indicator, patients were assigned to either the poor or the good prognosis group to analyze the factors influencing patient prognosis via univariate and multivariate analyses. Results. Among unilateral MCAO patients, there was a significant difference in the CBF of the affected side between the PLD 1525 ms and 2525 ms groups (

P
<
0.05

), but there was no significant difference in the CBF of the mirror side (

P
>
0.05

). Compared with the mirror side, 43 cases (71.7%) of the affected CBF presented with hypoperfusion, 9 cases (15.0%) with normal perfusion, and 8 cases (13.3%) with hyperperfusion. Age, NIHSS score, collateral circulation, and homocysteine (Hcy) were identified by multivariate Logistic regression analysis as independent risk factors for adverse outcomes. Conclusion. MCAO can lead to cerebral blood perfusion decline, and 3D-ASL technique can evaluate the post-MCAO cerebral blood perfusion level. Old age, high NIHSS scores, poor collateral circulation, and high Hcy levels are associated with poor clinical outcomes.
Effect of Methomyl on Growth, Antioxidant System of GIFT (Oreochromis niloticus), and Residue in the Presence of Water Spinach (Ipomoea aquatica Forsk)
Authors: Jing Xiaojun , Zheng Yao , Mulbah James P. , Chen Jiazhang , Xu Gangchun
Published: August 2022

This study was conducted to investigate the effect of methomyl (MET) on the growth and antioxidant system of GIFT (5.28 ± 0.12, n = 180) in the presence of water spinach (Ipomoea aquatica) aas a floating bed. Four treatment groups have been established, named control (0), 2, 20, and 200 μg/L MET. Results showed that at moderate temperatures such as 25°C to 30°C, tilapia’s feed consumption increased and body weight improved. SOD, CAT, and GSH in the liver of GIFT indicated the significant increase under MET exposure. MET reduced the growth rate of GIFT, and water spinach reduced part of the water quality indexes in the MET (<200 μg/L) groups. Water spinach altered GIFT’s hepatic oxidation system to some extent and effectively absorbed MET in water and transferred it to itself, and the degradation time was lower than the dietary standard time which termed as 15–20 days. Growing water spinach in farmed waters partially decomposes MET and prevents it from causing damage to GIFT’s liver.
Antiulcer Effect of Senna multiglandulosa via Increased Secretion of Mucus and Nonprotein Sulfhydryl Groups in an Experimental Murine Model
Authors: Palomino-Pacheco Miriam , Rojas-Armas Juan Pedro , Arroyo-Acevedo Jorge Luis , Ortiz-Sánchez José Manuel , Justil-Guerrero Hugo Jesús , Cieza-Macedo Edwin César , Ramos-Cevallos Norma , Alshahrani Mohammed Merae , Mahmud Shafi , Herrera-Calderon Oscar
Published: August 2022

Peptic ulcer is a universal condition that is a public health problem due to its prevalence, risk of complications and socioeconomic impact. This study aimed to determine the antiulcer effect of the hydroalcoholic extract from Senna multiglandulosa leaves against ethanol-induced gastric ulcer in rats. Thirty-six male albino Holtzman rats were assigned to six groups. Group I received physiological saline (PS) at doses of 10 mL/kg; group II: ethanol (PS + ethanol 5 mL/kg); group III; omeprazole 100 mg/kg/day (gold standard); groups IV, V and VI received doses of 100, 250 and 500 mg/kg/day of S. multiglandulosa extract, respectively. The stomach was removed to determine the ulcerative lesions and two sections of the glandular zone to carry out the analysis of the gastric mucus and sulfhydryl groups content. As result, S. multiglandulosa at doses of 250 and 500 mg/kg produced a significant decrease of the injured area, with values of 46.28 ± 7.95 mm2 and 6.91 ± 2.48 mm2, respectively (P<0.001). The protective effect was showed at dose of 500 mg/kg (92.27%) and a significant increase in the production of mucus with a value of 83.13 ± 13.09 mg/mL/g of tissue (61.14%). The production of nonprotein sulfhydryl groups (NP-SG) also increased significantly at the three evaluated doses, being 250.34 ± 21.16 μg/g tissue at dose of 500 mg/kg (119.94%). It is concluded that S. multiglandulosa extract protected against ethanol-induced gastric ulcer due to increased gastric mucus secretion and its antioxidant activity due to the generation of nonprotein sulfhydryl groups.
A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction
Authors: Xu He , Zheng Qunli , Zhu Jingshu , Xie Zuoling , Cheng Haitao , Li Peng , Ji Yimu
Published: August 2022

The deep learning methods for various disease prediction tasks have become very effective and even surpass human experts. However, the lack of interpretability and medical expertise limits its clinical application. This paper combines knowledge representation learning and deep learning methods, and a disease prediction model is constructed. The model initially constructs the relationship graph between the physical indicator and the test value based on the normal range of human physical examination index. And the human physical examination index for testing value by knowledge representation learning model is encoded. Then, the patient physical examination data is represented as a vector and input into a deep learning model built with self-attention mechanism and convolutional neural network to implement disease prediction. The experimental results show that the model which is used in diabetes prediction yields an accuracy of 97.18% and the recall of 87.55%, which outperforms other machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost). Compared with the best performing random forest method, the recall is increased by 5.34%, respectively. Therefore, it can be concluded that the application of medical knowledge into deep learning through knowledge representation learning can be used in diabetes prediction for the purpose of early detection and assisting diagnosis.
Attribution Interpretation of Urban Marathon Events Based on Random Matrix Model
Authors: Li Xinyue
Published: August 2022

The arrival of the national fitness boom has enabled the marathon as a large-scale sports event to attract the attention of a sufficient number of sports enthusiasts in a relatively short period of time. These people attracted by the event will have a series of expenses and expenditures also precisely reflect the prominent role of sports events on social and economic effects. In this paper, the AISAS consumption behavior model is used as the theoretical research model, and the survey data of urban marathon participants is used as the basis for analysis. The methods of generating attention, interest surveys, information search methods, actual consumption items and amounts during the action, and postmatch satisfaction and information sharing willingness and methods have been analyzed and counted in detail, and spss21.0 software is used to analyze the statistics. The results are analyzed. In addition, this paper studies the effect of the subspace weighting algorithm based on the singular value of random matrix on the urban marathon. Using the results of the eigenvalues of the sample covariance matrix in random matrix theory, the energy of each subspace is estimated, and then the subspace weighting matrix is constructed with the estimated energy. Through the calculation of the weights of the indicators, the weights of the three-level indicators of the event quality are ranked in the order of participation experience, cooperative media level, enthusiasm of local residents to watch the competition, registration status of the competition, number of sponsors, quality of sponsors, enthusiasm of local residents to participate in the competition, media value, and number of cooperative media algorithm, in which the marathon economic effect is defined as the estimated angle where the deviation between the estimated value and the true value exceeds 20%, that is, the root mean square error of the estimated angle is greater than 10%. In the first-level indicators, the quality of the event to evaluate the impact of the event itself has been added. The quality of the event is the influence of the urban marathon itself, which originates from the quality of the marathon itself. At the same time, the quality of the urban marathon is also the foundation of its economic, social, and environmental impact on the host site, so the quality of the urban marathon is an important impact indicator.
Staring Imaging Attitude Tracking Control Laws for Video Satellites Based on Image Information by Hyperbolic Tangent Fuzzy Sliding Mode Control
Authors: Pei Wenjing
Published: August 2022

This paper studies the staring imaging attitude tracking and control for satellite videos based on image information. An improved temporal-spatial context learning algorithm is employed to extract the image information. Based on this, a hyperbolic tangent fuzzy sliding mode control law is proposed to achieve the attitude tracking and control. Furthermore, the hyperbolic tangent function and fuzzy logic system are introduced into the sliding mode controller. In the experiments, the improved temporal-spatial context learning algorithm is applied for the image information of the space target video sequence captured by Jilin-1 in orbit, where the image information is used as the input of the control loop. Moreover, the proposed method is realized through simulation. Besides, the image change caused by attitude adjustment is achieved successfully, and the target imaging can be located in the center of the image plane to realize the gaze tracking control of the space target effectively.
Prevalence and Significance of Antinuclear Antibodies in Biopsy-Proven Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis
Authors: Luo Ling , Ma Qianqian , Lin Limin , Wang Hao , Ye Junzhao , Zhong Bihui
Published: August 2022

Aim. Associations between antinuclear antibodies (ANAs) and disease severity in nonalcoholic fatty liver disease (NAFLD) remain unclear. This study aimed to provide reliable estimates of ANA prevalence in subjects with biopsy-proven NAFLD and to investigate whether its associations with liver disease severity were established. Methods. Observational studies measuring ANA in NAFLD patients were derived from the PubMed, Embase, and Web of Science databases from inception to March 30, 2022. The effect size was presented as the pooled risk difference, unstandardized mean differences (MDs), and odds ratio (OR) with a 95% confidence interval (CI). Results. Thirteen articles involving 2331 patients were finally included. Among the subjects with biopsy-proven NAFLD, the overall prevalence of ANA positivity was high as 23% (95% CI: 19%-28%), but there were no statistically significant differences between ANA-positive and ANA-negative NAFLD patients in the levels of liver enzymes and blood lipids, grades of hepatocellular ballooning, lobular and portal inflammation, or risks of moderate-severe steatosis and significant fibrosis. However, the subgroup analysis showed that different geographic regions led to diverse results. ANA positivity was associated with a significantly elevated risk of significant fibrosis in the Eastern population (

OR
=
2.30

, 95% CI: 1.30-4.06) but not in the Western population (

OR
=
1.00

, 95% CI: 0.54-1.83). Conclusions. Serum ANA was present in approximately one-quarter of subjects with biopsy-proven NAFLD, but it conferred a greater risk of significant fibrosis only in Eastern but not Western populations.
System Dynamics Models of Online Lending Platform Based on Vensim Simulation Technology and Analysis of Interest Rate Evolution Trend
Authors: Pang Sulin , Deng Chao , Chen Susong
Published: August 2022

This paper mainly focuses on the construction of a system dynamics model of an online lending platform and the application of Vensim simulation technology in the analysis of the evolution trend of the investment interest rate. The system dynamics flow graph models of the investment subsystem, loan subsystem, and interest rate subsystem of the online lending platform were innovatively constructed; the level variable, flow rate variable, auxiliary variable, and mathematical relations between these variables as they relate to the platform were innovatively studied. Based on the key variables of the online lending platform, a system dynamics model of the online lending platform was innovatively constructed. The parameters were assigned using data from China’s online lending industry, and the logical consistency, sensitivity, and validity of the simulation data of the system dynamics model were tested. Finally, we used Vensim simulation technology to simulate and analyze the impact of emergency scenarios on the interest rate evolution trend. Overall, this paper provides a scientific simulation technology and data analysis method for examining online lending platforms.
Bifunctional Blockade: A Novel Immunotherapy Approach for Cervical Cancer
Authors: Miller Kathryn M. , Friedman Claire F.
Published: August 2022

SHR-1701, a bispecific fusion protein directed against PD-L1 and TGFβ, demonstrates promising clinical activity in advanced/recurrent cervical cancer. A recent study serves as a proof of principle that the TGFβ pathway may be successfully targeted, and that bispecific antibodies offer a novel therapeutic approach to do so.

See related article by Feng et al., p. 5297
Pharmacogenomic Profiling of Pediatric Acute Myeloid Leukemia to Identify Therapeutic Vulnerabilities and Inform Functional Precision Medicine
Authors: Wang Han , Chan Kathy Yuen Yee , Cheng Chi Keung , Ng Margaret H.L. , Lee Po Yi , Cheng Frankie Wai Tsoi , Lam Grace Kee See , Chow Tin Wai , Ha Shau Yin , Chiang Alan K.S. , Leung Wing Hang , Leung Anskar Y.H. , Wang Chi Chiu , Zhang Tao , Zhang Xiao-Bing , So Chi Chiu , Yuen Yuet Ping , Sun Qiwei , Zhang Chi , Xu Yaqun , Cheung John Tak Kit , Ng Wing Hei , Tang Patrick Ming-Kuen , Kang Wei , To Ka-Fai , Lee Wayne Yuk Wai , Wong Raymond S.M. , Poon Ellen Ngar Yun , Zhao Qi , Huang Junbin , Chen Chun , Yuen Patrick Man Pan , Li Chi-kong , Leung Alex Wing Kwan , Leung Kam Tong
Published: August 2022

Despite the expanding portfolio of targeted therapies for adults with acute myeloid leukemia (AML), direct implementation in children is challenging due to inherent differences in underlying genetics. Here we established the pharmacologic profile of pediatric AML by screening myeloblast sensitivity to approved and investigational agents, revealing candidates of immediate clinical relevance. Drug responses ex vivo correlated with patient characteristics, exhibited age-specific alterations, and concorded with activities in xenograft models. Integration with genomic data uncovered new gene–drug associations, suggesting actionable therapeutic vulnerabilities. Transcriptome profiling further identified gene-expression signatures associated with on- and off-target drug responses. We also demonstrated the feasibility of drug screening–guided treatment for children with high-risk AML, with two evaluable cases achieving remission. Collectively, this study offers a high-dimensional gene–drug clinical data set that could be leveraged to research the unique biology of pediatric AML and sets the stage for realizing functional precision medicine for the clinical management of the disease.

Significance:

We conducted integrated drug and genomic profiling of patient biopsies to build the functional genomic landscape of pediatric AML. Age-specific differences in drug response and new gene–drug interactions were identified. The feasibility of functional precision medicine–guided management of children with high-risk AML was successfully demonstrated in two evaluable clinical cases.

This article is highlighted in the In This Issue feature, p. 476
Improved security and stability of grid connected the wind energy conversion system by unified power flow controller
Authors: Wartana I Made , Agustini Ni Putu , Sreedharan Sasidharan
Published: August 2022

The stability and security improvements of the grid-connected to the wind energy conversion system (WECS) can be made by optimizing the placement of a flexible alternating current transmission system (FACTS). This study discusses the optimal placement of one type of WECS, namely the doubly-fed induction generator (DFIG) with a series and a shunt-FACTS control device called unified power flow controller (UPFC). The DFIG and UPFC connected grid dynamic perfor mance improvement with a maximum load bus system scenario. The optimal placement of DFIG and UPFC on the grid is formulated as a multi - objective problem, namely maximizing load bus system (Max. LBS) while minimizing active power loss (Min. P loss ) by pleasi ng numerous security and stability constraints. The non-dominated sorting genetic algorithm II (NSGA-II) have been utilized to settle this opposed bi-objective enhancement problem. The validity of the suggested method was examined on a modified IEEE 14-bus and a utilitarian examine system connected to DFIG with UPFC in power system analysis toolbox ( PSAT ) software. The optimal placement of DFIG and UPFC on the grid has increased the system's dynamic performance, with all the specified particular constraints being encountered.
Optimal energy management of a photovoltaic-batteries-grid system
Authors: Obaid Diana Sabah , Jaffar Mahdi Ali , Husham Alkhafaji Mohammed
Published: August 2022

Microgrid becomes an attractive concept to meet the rapidly increasing demands for energy in worldwide and deal with air pollutions. Distributed energy resources (DERs) in Microgrid are the vital role to meet the demand of the grid locally. The performance and the PV source grid connected system's response depend on vital parameters like transient response, voltage or current overshoot, steady state error, and harmonics distortions. This research aims to optimize the proportional-integral (PI) controller for improving power quality performance and energy management of the PV battery of three phase inverter of grid connected mode scheme. Besides to the PI conventional method, three different meta-heuristic optimization algorithms are proposed and implemented in order to enhance the PI and hence all system parameters. These three algorithms are (Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Dragonfly Algorithm (DA)) that can tune the PI controller's parameters by minimizing voltage regulator error, hence approving the goal of optimization in finding the optimal local or global solutions. The experimental results have been demonstrating the variety and the effectiveness of these optimization methods in convergence generation, computation time, and improving all required system parameters.
Diagnosis of induction motor failures using discrete wavelet transform of an auxiliary winding voltage
Authors: Khadouj Jelbaoui Yakout , El Menzhi Lamiaa , Saad Abdallah
Published: August 2022

Over last years, great attention has been developed to avoid the machines breakdown especially in the squirrel cage induction motor which suffer from different failures. The aim of this paper is to present a new method for the diagnosis of rotor bar breakage and end ring in induction machine fed by an inverter based on discrete wavelet transform applied on the voltage of an auxiliary winding as a new monitoring signature. The expression of the auxiliary winding voltage related to a small coil inserted between two stator phases is presented. The study is focused on the high-level signals of approximation and details coefficients. Thus, the evolution of any frequency of interest in the waveform is given in this paper. The method is validated by simulations of four broken bars and end ring cases under unloaded and loaded machine.
The impacts of green Cs2ZnSi5O12:Eu2+ phosphor for white light emitting diode
Authors: Liem Bui Van , Xuan Le Phan
Published: August 2022

We created the green-light phosphor Cs2ZnSi5O12 (CZSO) with Eu2+ replacement for the practical use of ultraviolet white illumination through the solid-state technique. The phosphor displays many different forms and crystallizes in the space group Pbca along with Pa , with formation resembling CsAlSi2O6, the leucite in cube form. We utilized the X-ray powder diffraction as well as the spectroscopic knowledge to validate that the crystal formation in the phosphor CZSO:Eu2+ belongs to the space group Pa . CZSO can generate wide green emission with a wavelength of 504 nm when excited by ultraviolet. We enveloped the blend using the translucent silicone resin and the red-light phosphor Sr2Si5N8:Eu2+ as well as excited it using an ultraviolet light emitting diode (LED) device with a wavelength of 370 nm to generate white illumination that yields remarkable chromatic output. The generation of illumination utilizing the phosphor CZSO benefits from the wide green emission, which does not require the integration of the three phosphors that are critical to the ultraviolet pumping. Such benefit will allow the model of the apparatus to become simpler and simultaneously create a desirable ultraviolet white illumination. When the augmentation the emission efficacy as well as the heat consistency for the phosphor CZSO is realized, we can easily incorporate the ultraviolet LED devices to create better white illumination.
A new Ca15(PO4)2(SiO4)6:Eu2+ phosphor with green emission for use in n-UV based w-LEDs
Authors: Dang Huu Phuc , Ton That Phung , Xuan Le Phan
Published: August 2022

We have produced a novel phosphor using Eu2+, which is green in color coupled to Ca15(PO4)2(SiO4)6 (abbreviated as Ca15P2Si6) by deriving it structurally from α-Ca2SiO4 with a typical solit reaction method. Additionally, the decrease of Eu2+ concentration as well as heat endurance is being studied. 330 nm is the wavelength at which the substance is stimulated. At 491nm, it attain the greatest radiation energy  when filled with the ideal concentration of Eu2+, which is 0.5 mol%. The primary mechanism of concentration reduction is discovered to be the fast transfer of stimulation through exchanging coupling among stimulated Eu2+ ions. The heat activating power boundary has been determined to be 0.244 eV. Additionally, we assess the productivity of this matter by fabricating alight-emitting diodes (LED)with converted phosphor (pc-LED) and integrating a light-emitting diode (LED) with an InGaN-foundation near-ultraviolet and running it at currents between 50 mA and 300 mA. All of the efforts result in an optimal for pc-LED to be able to ecedewhite light-emitting diodes (WLED) implementations.
TiO2 nanoparticles impacts over color deviation in white light-emitting diodes
Authors: Binh Ly Thanh , Quoc Anh Nguyen Doan , Xuan Le Phan
Published: August 2022

The effects of injecting TiO2nanoparticles with phosphorus silicone packing on white color light-emitting diodes (WLEDs) are examined. In WLED packages, the proposed approach may increase luminance emission by 2.7%, while the coordinated color temperature will increase by 39%. At the same time, the required phosphorus quantity will be lowered by 5% along with the joint temperature of 6.5°C. The modifications, which boost illuminating performance and also reduce temperature aggregation, are because of the packing material's increased illuminating dispersion efficiency or even refracting indices, along with lower illuminating reduction, for which colour fusing inside the parcels is responsible. Consequently, the results suggest improved-WLED lighting system performance makes the products more appropriate in solid-state lighting.
Maximization of the power delivered from permanent magnet synchronous generator wind energy conversion system to the grid based on using moth flame optimization
Authors: Hussien Shimaa Aly , Deab Mahmoud Adel , Alrowais Fadwa
Published: August 2022

In recent years, optimization techniques have been developed to improve accuracy and reduce execution time. The moth flame optimization technique (MFO) adapts to moth behavior. This design is based on the moth's transverse orientation. Over long distances, they maintain a fixed angle with respect to the moon at night. They spiral around the lights, however. Moths are trapped in a deadly spiral as the light approaches; eventually, they all converge on it. Furthermore, they are created by artificial light and fly similarly. To maximize the power delivered to the grid, moth flame optimization (MFO) is used to optimize the controller parameters of the wind energy conversion system (WECS). A permanent magnet synchronous generator (PMSG) implements a grid-connected WECS. a grid side converter (GSC) and a generator machine side converter (MSC) are used. A simulation package was used to model the proposed model. PSIM software was used to simulate power circuits and converters. Simulations were done in MATLAB. As a result, the obtained controller coefficients minimize both overshoot and steady-state error. Particle swarm optimization (PSO) and harmony search optimization (HSO) results were compared. MFO is a reliable method.
Quantification of retinal artery-vein ratio for vascular disease diagnosis using spatial U-Net
Authors: Pampana Lakshmi Kala , Rayudu Manjula Sri
Published: August 2022

The retinal vascular morphological caliber changes reveal the signs of systemic health disorder and life threat diseases such as cardio and cerebral diseases. The quantitative vascular parameters like narrowed arteries, widened venules, reduced artery-vein ratio (AVR) have been associated with aforesaid disorders and diseases. Hence the quantitative biomarker AVR is important parameter in diagnosing variety of diseases. The accurate quantification of AVR be possible if and only if accurate classification of arteries and vein is done. In this paper, we proposed a deep learning based robust vessel segmentation and classification algorithm based on spatial
 U-Net and the accuracy of the algorithm is 97.8%. In the quantification process, this algorithm is applied on region of interest (RoI) of a fundus image and measured the AVR values using central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE). The experimentation is carried on the digital retinal images for vessel extraction (DRIVE) dataset. The outcome of this work is the AVR observed to be >0.4 in normal retinal case and AVR value <0.4 for unhealthy case.
Comparative evaluation of optical amplifiers in passive optical access networks
Authors: Armel Bimogo Joseph , Jean-Francois Essiben Dikoundou , Luc Ihonock Eyembe
Published: August 2022

In this paper, the parameters of optical amplifiers are evaluated using numerical methods with the Optisystem software. The main objective of this evaluation is the implementation of an optical telecommunication architecture, able to push back the current limits, due to a more and more restricted bandwidth following a demand which does not stop growing. We start from a study of the classical architecture of an optical telecommunication network with an external modulation provided by the mach zehnder modulator, the non return to zero (NRZ) coding, a pseudo random bit generator and a continuous wave (CW) laser diode of frequency 193.1 THz. The results obtained show a transmission possibility at 30.8 dBm and an output power of 25 dBm (316 mW) with an electrical rate signal to noise (SNR) and optical rate signal to noise (OSNR) beyond 34 dBm. The successive integration of the different amplifiers will improve these results with a gain of more than 10 dBm and also provide a better signal quality.
Prediction of patient survival from heart failure using a cox-based model
Authors: Admassu Assegie Tsehay , Karpagam Thulasi , Subramanian Sathya , Janakiraman Senthil Murugan , Arumugam Jayanthi , Ahmed Dawed Omer
Published: August 2022

The existing heart failure risk prediction models are developed based on machine learning predictors. The objective of this study is to identify the key risk factors that affect the survival time of heart patients and to develop a heart failure survival prediction model using the identified risk factors. A cox proportional hazard regression method is applied to generate the proposed heart failure survival model. We used the dataset from the University of California Irvine (UCI) clinical heart failure data repository. To develop the model we have used multiple risk factors such as age, anemia, creatinine phosphokinase, diabetes history, ejection fraction, presence of high blood pressure, platelet count, serum creatinine, sex, and smoking history. Among the risk factors, high blood pressure is identified as one of the novel risk factors for heart failure. We have validated the performance of the model via statistical and empirical validation. The experimental result shows that the proposed model achieved good discrimination and calibration ability with a C-index (receiver operating characteristic (ROC) of being 0.74 and a log-likelihood ratio of 81.95 using 11 degrees of freedom on the validation dataset.
The role of web engineering in e-learning application development: a review study
Authors: Hamzah Hussin Ahmad , Sadry Abu Seman Muhamad
Published: August 2022

Web engineering is a growing multidisciplinary paradigm that has hardly begun to curiosity the interest, researchers, and other key actors involved in developing web-based systems. Therefore, the effect of web engineering applications on e-learning systems should be investigated to guarantee that the web’s potential for supporting the learning process is appropriately used. The objective of the study highlights the advantages, benefits, and contributions of web engineering in developing e-learning systems. This is qualitative research. The primary data was collected via an in-depth study of pertinent research studies. The second tool was an interview with the e-learning systems developers. The results showed that the most influential web engineering tools to develop e-learning systems. Moreover, the main areas of development of e-learning systems include changing the learning environment characteristics, changing student behaviour, changing roles, and incorporating artificial intelligence (AI). The results also showed that web applications' main challenges in e-learning systems include technologies, adaptability, lack of experience and training, lack of funding, changing student preferences and needs, the gap between the mobile and computer versions, and security threats, job-overload, and time. It was found that web engineering has a significant role in developing e-learning applications.
Controller placement problem in software defined networks
Authors: Hadi Saleh Hassan , Adnan Mishkal Israa , Salman Ibrahim Dheyab
Published: August 2022

The requirements for the network are increasing by the expanding and spreading the Internet. The Previous techniques of the network do not meet the modern needs, thus, a new technical presents software-defined networking (SDN). SDN recognizes as a promising new model that separates the control plane (traffic routing and network topology) from the data plane (network architecture layers). The architecture of SDN has some features that find in a single controller or many controllers instance of programmable, flexible, and scalable. In the current SDN, multiple controllers are essential. Therefore, the optimal number of the controllers and their locations is the most significant challenge, known as the controller placement problem (CPP). It deploys the optimal number of controllers within the network while meeting presentations requirements considered conflicting in nature example: credibility, load balancing, latency, energy efficiency, and computation time. Many studies researched the ways to develop solutions for improving scalability, place selection for SDN. This paper presents the CPP and gives a comprehensive review of SDN issues based on the recent well-known research to extract available solution strategies. Finally, it discusses the limitations and future study directions that can support researchers in this field.
Um tópico de aproximação ao pensamento político grego: fins e meios na democracia ateniense do século V a. C.
Authors: Tierno Patricio
Published: August 2022

O artigo tenta se aproximar do pensamento político grego mediante a breve introdução de algumas representações em que se faz relevante o problema da relação entre fins e meios.  Nesse percurso, busca-se mostrar como essa temática se liga a diferentes modos de entender a comunidade política e a experiência democrática ateniense do século V a. C., usando como ponto de partida o papel reformador de Sólon e dando uma maior atenção às doutrinas de Protágoras e Górgias. Para finalizar, suscita-se uma reflexão de caráter formal em torno das implicações atuais que a discussão antiga sobre os fins da política possibilita.
Kultura sigurnosti bolesnika u vrijeme COVID-19 pandemije u Klinici za infektivne bolesti „Dr. Fran Mihaljević“
Authors: Hrain Leonarda , Brborović Hana
Published: August 2022

Uvod: Svjetska zdravstvena organizacija definira sigurnost pacijenata kao „prevenciju, otklanjanje i unapređenje zaštite od neželjenih događaja tijekom procesa zdravstvene skrbi“. Sigurnost bolesnika važno je javnozdravstveno pitanje i najpouzdaniji indikator kvalitete zdravstvenog sustava.Ispitanici i metode: U istraživanju je sudjelovalo ukupno 228 ispitanika – stopa odgovora iznosi 61,13 %. Upitnik korišten u ovom radu jest Upitnik o kulturi bolesnikove sigurnosti u bolnici. Upitnikom se ispituju stavovi zdravstvenih djelatnika o bolesnikovoj sigurnosti, pogreškama u liječenju te o izvještavanju o neželjenim događajima u bolnici. Distribucije kvantitativnih podataka analizirane na normalnost Smirnov-Kolmogorovljevim testom pokazale su da distribucija nije normalna, stoga su u analizi korišteni neparametrijski analitički postupci. Distribucije kvalitativnih podataka analizirane su Fisherovim egzaktnim testom. Rezultati su interpretirani na 5 %-tnoj razini značajnosti.Rezultati: Na razini Klinike, većina dimenzija imala je visoku razinu, osim dimenzije Popunjenost osobljem. Najviša je izmjerena snaga u dimenzijama Timski rad unutar odjela i Očekivanja rukovoditelja i aktivnosti koje promiču bolesnikovu sigurnost.Rasprava: Iako se kao Klinika za infektivne bolesti pronašla na prvoj liniji obrane od novog koronavirusa, zajedno sa svojim djelatnicima pokazala je izvrsnost u novonastaloj situaciji borbe s novom bolesti.Zaključak: Visoka je razina sigurnosti bolesnika u Klinici za infektivne bolesti „Dr. Fran Mihaljević“. Osim kontinuiranog truda da se visoka razina i dalje održava, važno je zapošljavanje zdravstvenih djelatnika kako bi se poboljšala popunjenost osobljem.