bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the relationship between the expression of EBV-related antibodies and ET-1 axis in gastric cancer
Authors: Zhang Yan , Zhang Qianqian , Xu Lin , Wang Weiwen , Xiao Hua , Luo Bing
Published: November 2022

BACKGROUND AND OBJECTIVE: EBV-associated gastric cancer (EBVaGC) is a distinct subtype of GC, and EBV plays an important role in tumor progress. The standard method to identify EBV-positive tumor is determined by in situ hybridization for EBV-encoded EBERs in tumor tissues. The present study aims to detect the serological expression of EBV-related antibodies and ET-1 axis to provide a noninvasive method for diagnosis of EBVaGC. METHODS: The content of EBV-related antibodies and ET-1 axis in preoperative peripheral blood of GC was performed by Chemiluminescence and ELISA assay. The EBV DNA copy number was measured by qRT-PCR. RESULTS: The results showed that the levels of anti-EBV early antigen (EA) IgG, viral capsid antigen (VCA) IgA, nuclear antigen (NA) IgG, and EBV DNA copy number were significantly higher in EBVaGC. The ET-1 axis level was much lower in EBVaGC than EBVnGC. CONCLUSIONS: The combined detection of specific anti-EBV antibodies and ET-1 axis might provide new molecular markers for the identification of EBVaGC.
Associations of biomarkers for exposure to tobacco smoke with lung cancer risk in Korea
Authors: Kim Guen Hui , Kim Joyce Mary , Jee Sun Ha , Jung Keum Ji
Published: November 2022

BACKGROUND: Nicotine metabolite ratio (NMR) can be used to predict total nicotine clearance. However, it is unknown whether NMR could be used as a marker of lung cancer risk. OBJECTIVE: To evaluate the blood metabolites of nicotine relating to the risk of developing lung cancer and investigate the combined effects of NMR and cigarette per day on the risk of lung cancer. METHODS: Among the 1,054 eligible subjects from the Korean Cancer Prevention Study-II biobank cohort, those with cotinine values below 0 ng/ml were excluded. Slow and fast metabolizer groups were defined using the median value of the NMR, calculated with the control group data, as the cut-point. RESULTS: The multivariable Cox proportional hazard models demonstrated that, the fast metabolizer group had a significantly higher risk of lung cancer than the slow metabolizer group (Adjusted HR: 2.02, 95% CI: 1.32–3.10). Fast metabolizers who smoked more than 15 cigarettes per day had an even higher risk of lung cancer (Adjusted HR: 3.51, 95% CI: 1.96–6.29) than the slow metabolizers who smoked less than 15 cigarettes per day. CONCLUSIONS: In summary, the NMR may be an effective marker for estimating tobacco-related disease risks such as lung cancer.
Identification of prognostic biomarkers among ICAMs in the breast cancer microenvironment
Authors: Chen Heyan , Pu Shengyu , Mei Nan , Liu Xiaoxu , He Jianjun , Zhang Huimin
Published: November 2022

BACKGROUND: Intercellular adhesion molecules (ICAMs) in the tumor microenvironment are closely related to immunity and affect the prognosis of cancer patients. OBJECTIVE: The aim of our study is to explore the correlation between ICAM expression, mutation, methylation and immunity and their prognostic value in breast cancer (BC) is not clear. METHODS: Online databases and tools such as UALCAN, COSMIC, cBioPortal, MethSurv, PrognoScan, Kaplan-Meier Plotter, GSCA and TIMER were utilized in this study. RESULTS: We found that the mRNA and protein expression levels of ICAM1 were upregulated in triple-negative breast cancer (TNBC) compared with normal tissues, and TNBC patients with high expression of ICAM1 had better overall survival (OS) and recurrence-free survival (RFS). The main types of ICAM1 gene variants were missense mutation and amplification, and ICAM1 showed a lower level of methylation in TNBC cancer tissues than in normal tissues, which was contrary to the high expression levels of ICAM1 mRNA and protein. Next, the function of ICAM1 was mainly related to the activation of apoptosis, epithelial-mesenchymal transition (EMT) and inhibition of the androgen receptor (AR) and estrogen receptor (ER) pathways. Meanwhile, functional pathway enrichment results showed that ICAM1 was also involved in the immune regulation process of BC. Furthermore, the expression of ICAM1 was positively associated with 6 types of tumor-infiltrating immune cells (CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages and dendritic cells) and was also positively related to the expression of programmed cell death-1 (PD-1), programmed cell death-ligand 1 (PD-L1) and cytotoxic T lymphocyte-associated antigen-4 (CTLA4). CONCLUSIONS: Our research indicated that ICAM1 was likely to be a potential therapeutic target in TNBC.
Differentiation of Subjective Cognitive Decline, Mild Cognitive Impairment, and Dementia Using qEEG/ERP-Based Cognitive Testing and Volumetric MRI in an Outpatient Specialty Memory Clinic
Authors: Ganapathi Aarthi S. , Glatt Ryan M. , Bookheimer Tess H. , Popa Emily S. , Ingemanson Morgan L. , Richards Casey J. , Hodes John F. , Pierce Kyron P. , Slyapich Colby B. , Iqbal Fatima , Mattinson Jenna , Lampa Melanie G. , Gill Jaya M. , Tongson Ynez M. , Wong Claudia L. , Kim Mihae , Porter Verna R. , Kesari Santosh , Meysami Somayeh , Miller Karen J. , Bramen Jennifer E. , Merrill David A. , Siddarth Prabha
Published: November 2022

Background: Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention. Objective: We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader® by Brainreader). Methods: Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n = 161) and quantitative vMRI (n = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models. Results: The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87). Conclusion: This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia.
Digestion of preserved and unpreserved fish intestines for microplastic analysis with emphasis on quality assurance
Authors: Avila Fabiola Lopez , Stürmer Sophie , Monteleone Adrian , Neely Dave , Kuhajda Bernard R. , George Anna , Knoll Martin , Schary Weronika , Fath Andreas
Published: November 2022

BACKGROUND, Different preservation media used on fish samples may influence the digestion of organic matter for microplastic (MP) particle detection. Comparison of fresh and conserved fish is thereby problematic. OBJECTIVE, For quality assurance purposes and comparability of MP research, a method for digestion of preserved tissue like intestine with little impact on most MP particles was implemented. METHODS, Conserved fish samples were digested using SDS, KOH and Fenton’s reagents. The effect of the different chemicals used on different MP particles was then analyzed using Raman hit quality. Therefore, different filter materials were investigated using PMMA particles. RESULTS, Moist grided nitrocellulose filter was found best suited for this study. The effects of this digestion protocol on different polymer particles differed among polymers. Two of the used polymer particles dissolved during SDS + KOH treatment. PVC hard showed the highest loss of Raman hit quality (29.5 %). Some fish showed residues of sand or chitin from insects depending on their feeding strategy which could not be digested using this protocol. CONCLUSION, Not every polymer could be detected reliably using this protocol. For residues like sand or chitin, a density separation and enzymatic chitin degradation using chitinase may be needed, which could be implemented into this protocol.
Stochastic asymptotic stability for stochastic inertial Cohen-Grossberg neural networks with time-varying delay
Authors: Xu Danning , Liu Wei
Published: November 2022

This paper studies stochastic asymptotic stability for stochastic inertial Cohen-Grossberg neural networks with time-varying delay. Firstly, the second-order differential equation is converted into the first-order differential equation by appropriate variable substitution. Secondly, the existence of the equilibrium point is derived by using homeomorphic mapping, finite increment formula of Lagrange mean value theorem and linear matrix inequality. The sufficient conditions for the stochastic asymptotic stability of the equilibrium point of the system are derived by defining the appropriate operator, and constructing the appropriate positive Lyapunov function and positive-definite matrix. Thirdly, a numerical example illustrates the correctness of these theorems.
A study on the integration of digital language teaching system into English teaching
Authors: Xiang Meng , Mao Fengfan , Xiao Li
Published: November 2022

At present, many schools in China have built digital language classrooms, using digital language teaching system to assist English teaching, and combining computer and network technology to promote students’ English learning. However, in order to integrate digital language teaching system into English teaching curriculum, teachers should design multimedia audio and video teaching materials, teaching strategies and learning activities in order to make the digital language teaching system and teaching complement each other. Then promote the professional development of teachers and learners’ learning motivation and effectiveness.
Trajectory tracking control method of mobile robot based on AVRX operating system
Authors: Shi Qiguo
Published: November 2022

In order to improve the trajectory tracking control effect of mobile robot, a mobile robot trajectory tracking control (TRC) method based on AVRX operating system is proposed. The principle of AVRX operating system is analyzed and the hardware structure of mobile robot is designed. The input-output relationship of mobile robot trajectory is determined according to multivariable fuzzy controller and the wrong data of mobile robot trajectory tracking information is eliminated by radar point cloud measurement. The TRC model of mobile robot is designed through Euler Lagrange equation to realize the TRC of mobile robot. The experimental results show that the trajectory tracking accuracy of mobile robot is as high as 97.9%, the trajectory tracking time is 16.2 s, and the trajectory tracking error of mobile robot is only 0.04. It shows that the TRC effect of mobile robot is improved, which provides a reference for the trajectory tracking control of mobile robots.
Intelligent detection of IT assets in power grid enterprises based on signal processing and cyberspace
Authors: Zhang Yuanlin
Published: November 2022

Signal processing can complete the processing of various types of signals to obtain key data. Signal processing can also filter out redundant noise signals and ensure the quality of source signals. Due to the various functions of signal processing technology, it is widely used in network security, especially in IT asset detection and other aspects. Cyberspace is a general concept, which represents all devices associated with network connections. Detecting network assets in cyberspace means finding all networked devices. The detection of IT assets for power grid enterprises can help power grid enterprise IT administrators understand enterprise IT assets. At the same time, it can also discover the security loopholes existing in the operation of the current enterprise IT assets, and use the detection results to fix the loopholes as soon as possible to prevent the occurrence of network security incidents. This paper firstly sorts out the concepts of signal processing, cyberspace and power grid IT assets, then combines CNN and signal processing technology to design an intelligent detection strategy for power grid IT assets, and compares the designed strategy with the efficiency and other indicators of traditional detection methods. In contrast, finally, a cyberspace-based IT asset intelligent detection strategy was designed, and a power grid enterprise IT asset intelligent detection system was designed. Through the deployment strategy test environment, a test case was written in Python language, and the cyberspace-based IT asset intelligent detection was found. Compared with the traditional power grid enterprise IT asset detection scheme, the strategy has better performance in all aspects. The research adopts the method of modeling and analysis to calculate the signal values of the IT assets involved as much as possible, thereby greatly reducing the possible errors in the evaluation of enterprise IT assets. The test of the results obtained by the formula shows that the IT asset detection combined with the cyberspace search method shows superiority in different indicators.
Layout design and optimization of industrial robot automated production line based on genetic algorithm
Authors: Zhang Yang
Published: November 2022

With the development of the world consumption economy, the demand of the society on the production efficiency of the workshop is increasing. In order to improve the production efficiency of the industrial robot automatic production line, the working mathematical model of the industrial robot automatic production line is built, and the improved genetic algorithm is used to optimize the layout of the industrial robot automatic production line. The simulation results show that, compared with the selected design method based on a standardized production line and the optimization method based on genetic algorithm, the layout production scheme output by the improved genetic algorithm has higher space utilization efficiency, shorter material handling distance in the workshop, and better overall layout effect. When the experimental time is 14 units, the space utilization rate of the output solution of the improved genetic algorithm is 94%, and the index of the other methods is lower than 70%. Moreover, the material handling distance of the former is the closest to the straight line, and the zoning planning of production equipment and materials is the most reasonable. The experimental data show that the layout optimization method of industrial robot automatic production line based on improved genetic algorithm can effectively improve the planning quality of the production line and improve the production efficiency.
Peanut kernel integrity detection based on deep learning convolution neural network
Authors: Xia Ying , Sun Chuanqing
Published: November 2022

The edge features of peanut grain image are not considered in peanut grain integrity detection, and there are many noises, resulting in low accuracy of peanut grain integrity detection and poor effect of image edge noise removal. Therefore, this paper designs a peanut seed integrity detection method based on deep learning convolution neural network. The edge contour of peanut grain image is closed, the edge contour curve characteristics of peanut grain image are extracted, the noise area of peanut grain edge image is determined according to the filter window of Gaussian kernel function, and the wavelet descriptor in contour description operator is used to reduce the edge noise of peanut grain image. Input the image into the convolution neural network, update the weight by gradient descent method, construct the peanut seed integrity detection model, output the peanut seed integrity detection results, and realize the peanut seed integrity detection. The experimental results show that the proposed detection method can improve the accuracy of peanut grain detection and has certain feasibility.
Forestry english corpus construction and application in foreign language teaching under the background of big data and internet of things
Authors: Fang Mingyuan
Published: November 2022

With the development of science and technology, the concept of big data and the Internet of Things is being used in the social life of ordinary people widely more and more. Realizing the efficient use of big data and Internet of Things technology, has become an important means to improve work efficiency and scientific research results. Such a rapid development trend makes each team actively participate in the application of these technologies, hoping to make their work more in line with the trend of the times. Especially for the collection and construction of some databases, it has more advantages than traditional tools. This research makes full use of this technical advantage, selects the abstracts of the core journals of forestry at home and abroad as the corpus source, and builds a small English corpus of forestry. The corpus is used in English teaching in colleges and universities, uses a combination of comparative analysis and sampling surveys, and can play an active role in vocabulary learning and translation practice, semantics, grammar, syntax teaching, thesis writing, etc. Stimulate students’ interest in learning and enhance their independent learning ability and spirit of exploration. The experimental data shows that the English corpus constructed under the background of big data and the Internet of Things improves the average retrieval efficiency of college students by 27.3%, and the comprehensiveness of retrieval items increases by 9.6% on average. These improvements have a very positive effect on the development of foreign language teaching in related professional colleges and universities.
Experimental study on heat storing and release properties of fluidized bed regenerative device
Authors: Xu Feng , Shi Huiwen , Wu Xingdong , Li Xinlin , Sun Yong
Published: November 2022

By using the fluidization technique and electromagnetic heating technique, this paper designed a new type solid electric regenerative device using quartz sand particles to store heat, completed the setting of experimental bench of fluidized bed regenerative device, and analyzed the heat storing and release properties of this regenerative device. The experimental results show that the fluidized bed regenerative device has a good heat storing and release performance. When the metal wall surface of regenerative device was heated by electromagnetic heating to 600∘C and later kept at this temperature, the heat storing temperature of quartz sand particle material can reach above 500∘C after storing heat for 12 hours. After the 12-hour heat storing was finished, the total power of regenerative device’s heat storage obtained according to the temperatures of measuring points in fluidized bed and the physical properties of quartz sand can satisfy the design requirement. The 12-hour total effective heat release of this device is 29.5 kW⋅h and its heat release per unit time is kept at 2–3 kW, indicating that this device has a stable and controllable heat release process and is of actual application value.
Generalized moment estimation of multi-dimensional uncertain differential equations
Authors: Yao Linjie , Zhang Guidong , Sheng Yuhong
Published: November 2022

Multi-dimensional uncertain differential equations (MUDEs) are often used to describe complex systems that vary with time. In this paper, the generalized moment estimation method is employed to estimate the MUDEs’ unknown parameters. A method to optimize parameters with multiple estimation results is proposed. The hypothesis test and α-path are proposed to verify the feasibility of the parameter results. Several examples of parameter estimation for MUDEs are given, as well as two numerical examples to verify the feasibility of the method.
Rumor detection model fused with static spatiotemporal information
Authors: Wang Biao , Wei Hongquan , Li Ran , Liu Shuxin , Wang Kai
Published: November 2022

Spotting rumors from social media and intervening early has always been a daunting challenge. In recent years, Deep neural networks have begun to discover rumors by exploring the way of rumor propagation. The existing static graph models either only focus on the spatial structure information of rumor propagation or on time series propagation information but do not effectively combine them. This paper proposes the Static Spatiotemporal Model (SSM), which first extracts the textual semantic information and constructs undirected and directed propagation trees. Then obtains spatial structure information of rumor propagation through Graph Convolutional Network and extracts time series propagation information through the Recurrent Neural Network. The extracted spatiotemporal information is enhanced using different source node information hopping. Finally, SSM uses a weighted connection ensemble to rumor classification. Experimentally validated on datasets such as Weibo and Twitter, the results show that the proposed method outperforms several state-of-the-art static graph models. To better apply SSM in early detection and characterize early concepts, this paper presents a new data collection index for early detection, which can detect events that spread faster and have more significant influence in a targeted manner. The experimental results on the new indicators further verify the superiority of SSM as it can extract sufficient information in early detection or events with fewer participants.
Performance improvement and complexity reduction in the classification of EMG signals with mRMR-based CNN-KNN combined model
Authors: Little Flower X. , Poonguzhali S.
Published: November 2022

For real-time applications, the performance in classifying the movements should be as high as possible, and the computational complexity should be low. This paper focuses on the classification of five upper arm movements which can be provided as a control for human-machine interface (HMI) based applications. The conventional machine learning algorithms are used for classification with both time and frequency domain features, and k-nearest neighbor (KNN) outplay others. To further improve the classification accuracy, pretrained CNN architectures are employed which leads to computational complexity and memory requirements. To overcome this, the deep convolutional neural network (CNN) model is introduced with three convolutional layers. To further improve the performance which is the key idea behind real-time applications, a hybrid CNN-KNN model is proposed. Even though the performance is high, the computation costs of the hybrid method are more. Minimum redundancy maximum relevance (mRMR), a feature selection method makes an effort to reduce feature dimensions. As a result, better performance is achieved by our proposed method CNN-KNN with mRMR which reduces computational complexity and memory requirement with a mean prediction accuracy of about 99.05±0.25% with 100 features.
An integrated methodology for commercial concrete supplier selection with intuitionistic fuzzy CPT-VIKOR
Authors: Han Yongguang , Zhang Shanshan , Deng Dexue
Published: November 2022

Aiming at the multi-attribute group decision-making (MAGDM) problem with unclear index weights values, and thinking about the bounded rational behavior of decision makers (DMs), we proposed a new improved CPT-VIKOR decision method under intuitionistic fuzzy (IF-CPT-VIKOR). Due to the emergence of special cases in IFSs, a new IFS score function and distance formula are defined. Meanwhile, the use of entropy weight method to obtain the weight information of indicators enhances the objectivity of the model. Furthermore, CPT is integrated into the IFS environment, which fully reflects the psychological behavior of DMs, and take advantage of the VIKOR method to determine the final sorting of the scheme. Finally, through the application cases of the commercial concrete supplier selection (CCSS) and the comparison with the existing authoritative methods to verify the feasibility and validity of the method.
Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)
Authors: Kamarudin Nur Khairani , Firdaus Ahmad , Zabidi Azlee , Ernawan Ferda , Hisham Syifak Izhar , Ab Razak Mohd Faizal
Published: November 2022

Many smart mobile devices, including smartphones, smart televisions, smart watches, and smart vacuums, have been powered by Android devices. Therefore, mobile devices have become the prime target for malware attacks due to their rapid development and utilization. Many security practitioners have adopted different approaches to detect malware. However, its attacks continuously evolve and spread, and the number of attacks is still increasing. Hence, it is important to detect Android malware since it could expose a great threat to the users. However, in machine learning intelligence detection, too many insignificant features will decrease the percentage of the detection’s accuracy. Therefore, there is a need to discover the significant features in a minimal amount to assist with machine learning detection. Consequently, this study proposes the Pearson correlation coefficient (PMCC), a coefficient that measures the linear relationship between all features. Afterwards, this study adopts the heatmap method to visualize the PMCC value in the color of the heat version. For machine learning classification algorithms, we used a type of fuzzy logic called lattice reasoning. This experiment used real 3799 Android samples with 217 features and achieved the best accuracy rate of detection of more than 98% by using Unordered Fuzzy Rule Induction (FURIA).
Newborn Screening for the Diagnosis and Treatment of Duchenne Muscular Dystrophy
Authors: Farrar Michelle A. , Kariyawasam Didu , Grattan Sarah , Bayley Klair , Davis Mark , Holland Sandra , Waddel Leigh B. , Jones Kristi , Lorentzos Michelle , Ravine Anja , Wotton Tiffany , Wiley Veronica ,   on behalf of the DMD NBS Working Group
Published: November 2022

A pilot newborn screening (NBS) program for Duchenne muscular dystrophy (DMD) study proposes to assess the feasibility of the screening procedure, temporal course of the various steps of screening, and the public acceptability of the program. This is particularly vital to ascertain as DMD is considered a ‘non-treatable’ disease and thus does not fit the traditional criteria for newborn screening. However, modern perspectives of NBS for DMD are changing and point to possible net benefits for children and their families undertaking NBS for DMD. The aim of this workshop was to establish pathways for the successful implementation and evaluation of a pilot NBS for DMD program in Australia. Consensus was reached as to the rationale for, potential benefits, risks, barriers and facilitators of screening, alongside the establishment of screening protocols and clinical referral pathways.
Sex Is the Main Determinant of Levodopa Clinical Pharmacokinetics: Evidence from a Large Series of Levodopa Therapeutic Monitoring
Authors: Contin Manuela , Lopane Giovanna , Belotti Laura M.B. , Galletti Margherita , Cortelli Pietro , Calandra-Buonaura Giovanna
Published: November 2022

Background: Different studies, mostly with limited cohorts, have suggested the effects of patients’ characteristics on levodopa (LD) pharmacokinetics. Objective: We primarily aimed at investigating in a large population the relationship between patients’ features and LD kinetic variables, to assess the main demographic and clinical predictors of LD clinical pharmacokinetics. Methods: The study was retrospective, based on data collected from subjects with parkinsonism on chronic LD undergoing LD therapeutic monitoring (TM). LD TM includes serial quantitative motor tests and blood samples to measure plasma drug concentrations after each subject’s chronically taken first-morning LD dose intake. Results: Five hundred patients, 308 males (61.6%), mean (SD) age of 65 (10.1) years were included. Parkinsonian symptoms and LD therapy lasted 5.5 (4.5) and 3.4 (3.9) years, respectively. MDS-UPDRS part III “off” score was 28.8 (15.2). LD dose was 348.2 (187.1) mg/day. From multiple linear regression analysis, test dose, sex, type of LD decarboxylase inhibitor, weight and MDS-UPDRS part III score were linear predictors of both LD peak plasma concentration (Cmax) (R2 = 0.52) and area under the 3-h plasma concentration-time curve (AUC) (R2 = 0.71), while age was a further predictor only for AUC. Besides test dose, sex was the strongest independent contributing variable to LD AUC, which resulted 27% higher in females compared to males. Conclusion: This is the largest collection of data on the relationship between demographic and clinical-therapeutic variables and LD kinetics in patients with parkinsonian symptoms. As a main clinically practical finding, women might require a 25% reduced weight-normalized LD dose compared with men to achieve the same LD bioavailability.
Security Issues of Cloud-Based SCADA Systems
Authors: Alakbarov Rashid , Hashimov Mammad
Published: November 2022

The article reviews the security issues of cloud-based SCADA (Supervisory Control and Data Acquisition) systems that are widely used in monitoring and management of the oil and gas industry. Recently, extensive research has been conducted regarding the migration of SCADA systems to the cloud infrastructure. Transfer of applications used in the management and control of the SCADA system to cloud servers allows for efficient management of the system, solving resource problems and reducing costs. The article analyzes the advantages of cloud-based SCADA systems. Existing gaps have been identified that could obstruct the security of cloud-based SCADA systems. Security problems and risks in the use of cloud-based SCADA systems were analyzed and suggestions were made to help solve them to some extent.
BANK INTEREST HALAL: DISTINCTION INTERPRETATION OF CONTEMPORARY ULAMA THOUGHT UMER CAPHRA AND MUHAMMAD SAYYID THANTHAWI
Authors: Huda Miftahul , Nabila Fikriyyatun , Fajriati Isma Fathya , Rahmah Listya , Mokan Zaimudin Al-Mahdi
Published: November 2022

Life is controlled by two great forces, namely economy, and religion.  All things based on Sharia law are clearly about halal and haram. Bank interest is something that is no longer common among the public, with the law and practice still being debated by some scholars. Therefore, this study aims to answer public confusion about the law of halal interest according to Umer Caphra and Muhammad Sayyid Thanthawi and the reasons for making legal decisions regarding bank interest. The research is in the form of a qualitative method with a literature study using several references from books and journals in concluding the views of the two figures. The primary data used is from the book Prohibition of Interest: Does it make sense? The work of Umer Chapra. While secondary data comes from various books and journals related to bank interest. The results of this study indicate that the two scholars have different opinions regarding bank interest. Umer Chapra argues that the practice of bank interest is prohibited in Islam because usury interest can harm the poor. Meanwhile, Muhammad Sayyid Thanthawi argues that bank interest is not part of usury because bank interest is not part of faith and worship.
KREMENETS’S FIXATION PLAN OF THE 1930S AS A SOURCE OF RESEARCH ON THE URBAN HISTORY OF THE CITY
Authors: Yahodka Yuliia
Published: November 2022

The article covers the urban formation of Kremenets on the basis of the fixation site plan of the city of the second half of the 1930s and other project documentation of the Second Polish Republic period. The relevance of the research topic is determined by the relatively limited array of cartographic sources capturing the features of Kremenets planning pattern in the interwar period.
This publication aims to substantiate the evolution of the architecture of Kremenets that was based on the identification of the architectural heritage of the Polish, and the involvement of avant-garde ideas. A special factor of relevance is the emphasis on the value of the architectural and landscape ensemble of Kremenets as an exceptional example of the vernacular town of Western Volhynia.
The research methodology is based on general, interdisciplinary and disciplinary, that include architectural and town-planning research methods.
A comparative analysis of the found documents makes it possible to identify features of urban development of Kremenets under the influence of various factors: spatial and landscape situation, social and cultural context, trends in urban development in the relevant periods of European history.
The object of research is the fixation plan of the city of Kremenets in the 1930s, which was discovered by the author as a result of working with materials from the funds of the State Archives of Ternopil region. The research is accompanied by other published documents and primary sources of the Second Polish Republic period.
MANUFACTURABILITY FACTORS OF PREFAB-CONSTRUCTION FROM STEEL THIN-WALLED COLDFORMED ELEMENTS
Authors: Khokhrіakova Daria
Published: November 2022

The article systematizes the factors and their influence on the manufacturability of prefab structures from steel thin-walled cold-formed elements. It is known that LSTS are modern building structures that are efficient in terms of material consumption. Despite this, many of them, due to labor costs during manufacture and installation, are characterized by increased cost, and cannot always be considered technologically advanced. Since the study of manufacturability factors opens up new opportunities for their effective use in the design of objects from LSTS, the author classifies them into two groups: factors determined by the level of development of means of production; factors determined by the properties of objects of labor. As a result of a brief review of the development of manufacturability ideas, a number of provisions have been formulated regarding a clear distinction between factors and indicators of the manufacturability of objects and structures. Based on the performed comparative analysis, two types of equipment for the production of LSTS were identified: type I – for low-rise frame-panel construction; type ІІ – for all options for the use of LSTS in construction, incl. for multistorey and commercial construction. The efficiency of modern LSTS production depends on the following parameters: design time, time for transferring details to equipment, speed of the production process, production changeover time. It is noted that the speed of profiling is not a key parameter for the production of LSTS. More important is the issue of equipment readjustment to other profile sizes, which can cause significantly more time than the rolling process itself, and, accordingly, reduces the manufacturability of LSTS. A significant characteristic of a modern line, which ensures the manufacturability of the production of LSTS, is the presence of a minimum set of presses to perform the necessary operations on the produced profile (bulging, profile bending, cutout in the fabric, holes for screws, crimping of the ends of the profile), which reduce labor intensity and speed up the subsequent assembly of structures from steel thin-walled cold-formed elements. It seems promising to design LSTS only from C-profiles of the same section and thickness due to an increase in their manufacturability by eliminating such factors as changing equipment to a profile of a different type, sorting elements when assembling a bundle of panels, transporting structures from the factory when using compact lines directly on the construction site. It is substantiated that the use of lines of the first type is effective for the implementation of this approach.
Convergence of Dermoscopic and Histopathological Findings in Diagnosing Cutaneous Lichen Planus (CLP)
Authors: Sumera Hanif  , Tariq Rashid  , Farooq Muhammad Talha , Mahrukh Javaid  , Areesha Fatima  , Bushra Hassan  , Muhammad Umair Iqbal  , Amina Akram
Published: November 2022

Lichen planus (LP) is an immune mediated disorder that is usually diagnosed clinically. Dermoscopy is a non-invasive diagnostic technique. It can act as an alternative technique to skin biopsy that remains the gold standard for the diagnosis of the disease. The current study aimed to evaluate the degree of convergence between dermoscopy and histopathology in diagnosing LP. It is a cross-sectional study conducted at Jinnah Hospital, Lahore for six (6) months. Sixty (60) patients who met the inclusion criteria were recorded. After taking their informed consent and detailed history, clinical examination and relevant investigations were carried out and recorded in a pre-structured proforma. All patients were subjected to dermoscopic examination. A total of 4 mm punch biopsy were taken from the same site for histopathological examination and sent to JHL Histopathology lab. The results of dermoscopic and histopathological examinations were recorded. Effect of modifiers such as age, gender, and duration of disease were addressed through the stratification of data.Data was analyzed using SPSS 23. The mean age of subjects was 35 years. Of the total 60 patients, 56.6% were female and 43.3% were male. Among the subjects, 94.7% cases diagnosed on histopathology were also diagnosed on dermoscopy, while 5.3% cases were not diagnosed on dermoscopy. Kappa statistics showed a substantial convergence between the two diagnostic modalities: (X2=29.697, p=.000) and (k= .700, p =.000). It was determined that dermoscopy is as effective as hitopathology in the diagnosis of CLP.
Narrative Review of Factors Affecting Lower Back Pain among Workers in Pakistan
Authors: Arooj Ayesha , Aziz Aamir , Khalid Fariha , Iqbal M. Hussain
Published: November 2022

According to the world health organization (WHO), lower back pain (LBP) is the most common healthhazard among workers and is among the top ten health hazards around the globe. The Global Burden ofDisease (GBD) 2010 stated LBP as amongst the top 6 diseases which cause disability injuries and otherchronic diseases. This is the impairment that poses the most economic burden on society as a whole,including individuals, businesses, and the government. This study aims to find out the factors that affectlower back pain among workers associated with different professions in Pakistan. Data were collectedfrom different databases, such as PubMed, Google scholar, and PEDro by using a predefined searchstrategy with proper Boolean terms ‘AND’ or ‘OR’ or ‘NOT’. The data were collected from theliterature available for past 10 years. Additionally, articles with relevant material and titles werereviewed for conducting the current research review. The most common risk factors that were seenalmost among all professions were static position and prolonged working hours, any work that demandsprolonged standing or sitting, bending or twisting, and improper lifting. Several professional workers areat high risk for developing LBP but among all the professions physiotherapists, sonographers, bankers,and shopkeepers were at higher verge for developing LBP. It was found that the prevalence of LBP isincreasing day by day and significantly affecting workers in every profession. Therefore, timelytrainings with proper ergonomic techniques could decrease LBP and increase economic productivity inPakistan. It can be said that good ergonomics for good economics.
Social Isolation, Mindfulness, and Mental Wellbeing among Covid-19 Survivor University Students
Authors: Sana khan  , Masha Asad Khan
Published: November 2022

This study explains the relationship between social isolation, mindfulness, and mental well-being among Covid-19 survivor university students. Data were collected from 200 Covid-19 survivor university students (M=94; F=106) from Punjab Pakistan. Results found high social isolation to be linked with low mental well-being, however, a significant positive relationship between mindfulness and mental well-being was found. Further, social isolation and mindfulness emerged as significant predictors of mental well-being. This research sheds light on the significance of mindfulness, and social connections in daily life, especially during periods of isolation during Covid-19. Present findings have implications for psychologists, counselors, mental health practitioners, teachers, and parents.
Strategi Komunikasi Pemasaran Oleh Bukit Air Wedding Dalam Menarik Minat Konsumen selama Pandemi Covid-19 Melalui Media Sosial Instagram
Authors: Hilmiyati Fitri Laili , Nurfebiaraning Sylvie
Published: November 2022

Bukit Air Wedding, salah satu wedding organizer yang berada di Kota Bogor merupakan salah satu usaha jasa yang turut terkena dampak pandemi Covid-19. Tujuan dilakukannya penelitian ini adalah untuk mengetahui dan menganalisis strategi pesan dan media yang dilakukan oleh Bukit Air Wedding melalui platform Instagram sebagai media utama komunikasi pemasaran mereka. Penelitian ini dilakukan dengan menggunakan jenis penelitian kualitatif deskriptif dan pengumpulan data dilakukan dengan observasi, wawancara secara mendalam dengan informan kunci, dan diperkuat oleh pernyataan dari informan ahli, dan empat informan pendukung. Dasar teori yang digunakan dalam penelitian ini adalah teori komunikasi pemasaran Mahmud Machfoeds dengan fokus utama pada strategi pesan dan strategi media. Strategi pesan meliputi isi informasi dan bentuk kreatif, sedangkan strategi media meliputi pemilihan media dan celah konsumen. Berdasarkan hasil penelitian, Bukit Air Wedding menggunakan konten edukasi sebagai dasar utama strategi pesan dan Instagram sebagai media utama, namun, tidak ada perubahan strategi media yang dilakukan Bukit Air Wedding baik sebelum pandemi maupun saat pandemi.
Pengaruh Faktor Pribadi dan Faktor Psikologis Terhadap Keputusan Pembelian Album Fisik Boy Group EXO di Indonesia
Authors: Haida Rhodiatul , Sari Aida , Bursan Rinaldi , Nabila Nuzul Inas
Published: November 2022

Kpop (Korean Pop) saat ini sangat digemari berbagai kalangan penikmat musik di seluruh dunia. Popularitas musik Kpop menyebabkan maraknya pembelian album fisik (CD) dikalangan para fans Kpop. EXO merupakan salah satu boy group dengan penjualan album fisik yang sangat mengagumkan. Penelitian ini bertujuan untuk menganalisis faktor yang mendorong keputusan pembelian album fisik boy group EXO di era digital, faktor yang diteliti yaitu faktor pribadi dan faktor psikologis. Penelitian ini menggunakan metode non-probability sampling dengan teknik purposive sampling, dengan sampel sebanyak 100 responden yang memiliki album fisik EXO dan berdomisili di Indonesia. Hasil penelitian ini mendukung hipotesis yang diajukan dalam penelitian. Dibuktikan dengan nilai F 150.442 dengan angka signifikan sebesar 0.000. Hasil analisis diperoleh bahwa faktor pribadi dan faktor psikologis memiliki pengaruh sebesar 75% terhadap keputusan pembelian album fisik EXO dengan nilai pengaruh terbesar yaitu faktor psikologis. Hasil penemuan ini diharapkan dapat digunakan sebagai bahan pertimbangan untuk melakukan pengembangan strategi yang lebih efektif dalam upaya menaikkan penjualan album fisik di era digital.
Pengaruh Mental Kewirausahaan, Kreativitas dan Sosial Ekonomi Orang Tua Terhadap Minat Berwirausaha Mahasiswa
Authors: Delvanty Mayrizza Ega
Published: November 2022

Tujuan dari penelitian ini adalah ingin mengetahui pengaruh mental kewirausahaan, kreativitas dan sosial ekonomi orang tua terhadap minat berwirausaha pada mahasiswa. Penelitian ini menggunakan metode kuantitiatif dengan jumlah subjek penelitian sebanyak 282 mahasiswa Akuntansi Universitas Pembangunan Nasional “Veteran” Jawa Timur. Metode pengumpulan data menggunakan kuesioner, sehingga diperoleh sebanyak 52 subjek penelitian yang mengembalikan kuesioner penelitian. Teknik analisis data pada penelitian ini menggunakan teknik Partial Least Square. Hasil penelitian menunjukkan bahwa variabel independen yaitu mental kewirausahaan, kreativitas dan sosial ekonomi orang tua menjelaskan variabel dependen minat berwirausaha sebesar 61,2%. Selanjutnya hasil analisis menunjukkan variabel mental kewirausahaan dan kreativitas berpengaruh terhadap minat berwisausaha pada mahasiswa (T-Statistics > 1,96). Sedangkan variabel sosial ekonomi orang tua menunjukkan tidak ada pengaruh terhadap minat berwirausaha pada mahasiswa (T-Statistics < 1,96).
Strategi Pemasaran Jasa Pendidikan Anak Usia Dini Untuk Membangun Kepercayaan Target Pasar
Authors: Yudaninggar Kartika Sari
Published: November 2022

The pandemic has indeed changed almost all aspects of life and activities in society. Early childhood is one of the groups experiencing the impact of these changes. One of them is the inhibition of the learning process in early childhood. On the other hand, parents are also busy and often run out of ideas to play with their children. Seeing this opportunity, Kelas Main Harmoni offers a children's play class program online via a zoom meeting. Uniquely, Kelas Main Harmoni is still new, and is not a formal educational institution, but Kelas Main Harmoni can build the trust of parents to register their children and play together in Kelas Main Harmoni program. This study used descriptive qualitative method. This study involved informants who are founders, as well as parents of Kelas Main Harmoni participants to conduct interviews to find out the marketing strategy carried out by Kelas Main Harmoni. The results of this study indicate that the strategy taken to build the trust of parents is to continue to develop and focus on aspects of the product in the form of services, as well as people, or the quality of teachers in Kelas Main Harmoni.
Pengaruh YouTube Vloggers terhadap Food Branding
Authors: Liling Jenary Randa , Lyawati Mercy , Lim Stephani , Lim Tevin , Jiang Kelvin
Published: November 2022

Dampak dari era globalisasi yang terjadi pada saat ini sangat mempengaruhi pelaku bisnis dalam memasarkan produknya kepada konsumen. Pemasaran produk melalui media cetak saja sudah tidak cukup pada zaman sekarang. Pemasaran lewat media digital adalah cara yang paling efektif untuk dilakukan sekarang. Salah satu contohnya adalah pemasaran adalah media sosial, melalui konten YouTube yang dibagikan oleh vlogger.  Akan tetapi, belum diketahui secara pasti dampak atau pengaruh dari konten YouTube yang dibuat oleh vloggers terhadap citra merek produk makanan dan keputusan pembelian oleh konsumen. Oleh karena itu, penelitian ini dilakukan untuk mengetahui apakah pengaruh vlogger berdampak pada citra merek produk makanan dan keputusan pembelian oleh konsumen. Penelitian ini di lakukan dengan metode kuantitatif. Hasil dari penelitian menunjukan bahwa keunikan dari konten YouTube vloggers memiliki pengaruh besar dalam citra merek produk makanan. Hasil tersebut akan berguna untuk vloggers dan pemilik usaha dalam memasarkan produk mereka secara efektif.