bluuebunny/crossref_metadata_2025 huggingface dataset:
Dendritic Cell Vaccine Loaded with MG-7 Antigen Induces Cytotoxic T Lymphocyte Responses against Gastric Cancer
Authors: Zhu Bohui , Sun Yiyuan , Wei Xiaoqing , Zhou Huibin , Cao Jingchen , Li Chenwei , Wu Ning
Published: April 2022

Dendritic cells (DCs) are antigen-presenting cells that can activate T cells and initiate a primary immune response. Personalized DC vaccines have demonstrated a modest antitumor potential in some clinical pilot studies. However, those vaccines are difficult to manufacture and have a limited antitumor response. In this study, a lentiviral vector-programmed DC vaccine with high antitumor responses is developed. By transfecting with a lentiviral vector, the DC vaccine is loaded with MG-7 antigen (MG-7Ag). Three representative gastric cancer cell lines, such as KATO-3, MKN45, and SNU16, are used to estimate the in vitro cytotoxic effect of the MG-7Ag DC vaccine. Furthermore, we examine the in vivo antitumor efficacy of specific cytotoxic T lymphocytes (CTLs) induced by the MG-7Ag DC vaccine in patient-derived xenograft (PDX) mice models. The current data demonstrate that the MG-7Ag DC vaccine induced a potent CTL activity. Those CTLs have a significant cytotoxic effect on both KATO-3 and MKN45 with high level of MG-7 expression. In addition, MG-7Ag DC vaccine-mediated CTLs significantly inhibit the growth of tumor xenografts in nude mice. The MG-7Ag DC vaccine activate the cytotoxic effect of lymphocytes and can be employed as a vaccine in gastric cancer immunotherapy.
Evolutionary Game Analysis of Debt Restructuring Involved by Asset Management Companies
Authors: Zhao Danyu , Song Li , Han Liangliang
Published: April 2022

Based on the evolutionary game theory, this article constructs a quartet evolutionary game model for debt restructuring with the participation of asset management companies; studies the interactive mechanism of complex behaviors among the government, banks, asset management companies, and enterprises; and analyzes the stability of the strategies of each game subject. It also analyzes the stability of the equilibrium points in the system and finds the stable points that maximize the interests of each subject. Research shows that the government chooses to give specific support, banks choose debt‐to‐equity swaps, asset management companies choose to provide liquidity, and enterprises choose to work hard, which can better promote the debt restructuring process. Finally, using Matlab2018 software to analyze the impact of each essential element in the debt restructuring on the stability of system evolution, the research results provide a basis for the successful debt restructuring of the enterprises.
Factors Affecting ICU Stay and Length of Stay in the ICU in Patients with HELLP Syndrome in a Tertiary Referral Hospital
Authors: Ağaçayak Elif , Bugday Rezan , Peker Nurullah , Deger Ugur , Ölmez Kavak Gönül , Evsen Mehmet Siddik , Gul Talip
Published: April 2022

Objective. The study aimed to compare patients with HELLP syndrome who require intensive care and who do not require intensive care and evaluate the factors affecting the length of stay in the intensive care unit. Methods. Patients were divided into two groups as follows: requiring intensive care (group 1) and not requiring intensive care (group 2). The data of both groups were compared in terms of demographic characteristics, transfusion amounts, length of stay in the intensive care unit, maternal complications, and mortality. Results. 14032 births in a tertiary center between 2011 and 2018 were evaluated in this study. During the study period, 342 patients were diagnosed with HELLP, and 32 (9.4%) of these were followed up in the intensive care unit. The length of stay in the intensive care unit was determined as 8.1 (7.2) days on average. Fresh frozen plasma, erythrocyte suspension, apheresis, and random thrombocyte transfusion were observed to be significantly more in group 1 patients. In the regression analysis, the most effective factor was found to be erythrocyte suspension and the length of stay in the intensive care unit was significantly longer in patients who had erythrocyte suspension transfusion. The receiver operating characteristic curve showed that the area under the curve value for erythrocyte transfusion was 70.6%. When the cutoff value of erythrocyte suspension was 450 (95% CI: 365–681) ml, the sensitivity was 43.8% and the specificity was 91.6%. Conclusion. We think that physicians should be careful that maternal morbidity and mortality may increase as the need for erythrocyte suspension transfusion increases in patients with HELLP syndrome. Minimum transfusion to hemodynamically stable patients can be more suitable in terms of morbidity and mortality in managing patients with HELLP syndrome requiring erythrocyte suspension transfusion. Precautions and measures should be taken in this regard.
Study on Spontaneous Combustion “Three Zones” of the Distribution Law and Integrated Fire Prevention Technology in Mined-Out Area of Lingquan Mine
Authors: Liu Linjie , Shen Zhuo , Chen Jian , Jia Baoshan , Su Guorui , Liu Rongzheng
Published: April 2022

To determine the risk range of remaining coal in the goaf of the higher slice on the seventh mining and fifth face of Lingquan Mine, the beam tube monitoring system was adopted to supervise the temperature and gas content changes in the goaf during the normal mining period of the working face. As per the principle of dividing spontaneous combustion “three zones” (SCTZ), numerical simulation of the distribution of SCTZ in the goaf of the work face was performed. The O2 content and index gas in the goaf were measured and analyzed, and combined with the in-situ measurement outcomes, the distribution of SCTZ in the goaf was determined through the FLUENT numerical modeling program. The outcomes show that the distribution pattern of SCTZ in the goaf of fully mechanized mining face is: the heat dissipation zone is 0–41 m, the oxidation zone is 41–97 m, the suffocation zone is more than 97 m away from the work face, and the increment of temperature is 0.7/°C. Based on the judgement result of SCTZ, the minimum recovery rate of work face is above 3.7 m/d. The use of new polymer materials validly solves the problem of excessive CO in the return air corner of the goaf and prevents self-ignition accidents in the goaf.
Dynamic Modeling of Influencing Factors and Change Trend of College Students' Mental Health Based on Big Data
Authors: Fu Qi
Published: April 2022

With the great changes of social development environment and the lack of psychological preparation of many students, many college students have many psychological problems in the process of adapting to the environment. If the problem cannot be solved in time, it will seriously affect their future adaptation and mental health. In order to solve the psychological problems of college students, the networked dynamic model constructed by using big data modeling technology can realize the system functions required by users and model the model accordingly. The main research direction of this paper is to study the influencing factors and change trend of college students' mental health under the background of big data. In the network-oriented scenario, the missing value of the data is supplemented, and the sequence prediction technology is added to the data. Finally, by adding corresponding data samples to the improved big data dynamic model, the results of the addition completion method and data sequence prediction technology are analyzed.
The Roles of KIFC1 in the Development of Osteosarcoma: Characterization of Potential Therapeutic Targets
Authors: Liang Li-Yan , Li Gui-Shi
Published: April 2022

Background. As an important member of the mitotic kinesin family, kinesin family member C1 (KIFC1) is abnormally expressed in a variety of tumors. However, the roles of KIFC1 in the development of osteosarcoma (OS) have never been elucidated. Methods. The expression of KIFC1 in OS tissues which was detected by immunohistochemistry (IHC) staining was further confirmed by Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database. The relationship between KIFC1 and CDC20 was analyzed by clinical data, STRING database, and GEPIA2 database. Survival analysis was performed through GEPIA2 database. To elucidate the roles of KIFC1 in OS, MG-63 and U-2 OS cells were treated with short hairpin RNA (shRNA) to knock down KIFC1 expression, and the knockdown efficiency was validated with quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting (WB). Moreover, colony formation and Cell Counting Kit-8 (CCK-8) assays were utilized to evaluate cell proliferation. Results. According to IHC staining and GEPIA2 analysis, the expression of KIFC1 in OS tissues was significantly higher than that in adjacent normal tissues, which was inversely connected to the prognosis. These results were consistent with our clinical data. Besides, KIFC1 was positively correlated with CDC20. In addition, KIFC1 shRNA could effectively silence KIFC1 expression in MG-63 and U-2 OS cells. Furthermore, the knockdown of KIFC1 inhibited the cell proliferation ability with increased cell apoptosis in MG-63 and U-2 OS cells. Conclusion. KIFC1 was significantly upregulated in OS and promoted OS progression by cell proliferation. These findings offered new clues for OS diagnosis and prognosis, suggesting KIFC1 could be a potential therapeutic target for OS in further study.
Regarding on the Results for the Fractional Clannish Random Walker’s Parabolic Equation and the Nonlinear Fractional Cahn-Allen Equation
Authors: Alam Md. Nur , İlhan Onur Alp , Uddin Md. Sabur , Rahim Md. Abdur
Published: April 2022

In this research, the

Ψ
,
Φ

-expansion scheme has been implemented for the exact solutions of the fractional Clannish Random Walker’s parabolic (FCRWP) equation and the nonlinear fractional Cahn-Allen (NFCA) equation. Some new solutions of the FCRWP equation and the NFCA equation have been obtained by using this method. The diverse variety of exact outcomes such as intersection between rough wave and kinky soliton wave profiles, intersection between lump wave and kinky soliton wave profiles, soliton wave profiles, kink wave profiles, intersection between lump wave and periodic wave profiles, intersection between rough wave and periodic wave profiles, periodic wave profiles, and kink wave profiles are taken. Comparing our developed answers and that got in previously written research papers presents the novelty of our investigation. The above techniques could also be employed to get exact solutions for other fractional nonlinear models in physics, applied mathematics, and engineering.
Profile of Twenty-Three Human Milk Oligosaccharides in Han Chinese Mothers throughout Postpartum 1 year
Authors: Xun Yiping , Feng Xiaoying , Xue Yuling , Feng Lili , Zhang Dong , Ma Rui , Yuan Huizhi , Yang Wanqiu , Yu Wenhua , Jia Xiaojiang , Yuan Qingbin , Wang Shijie
Published: April 2022

Human milk oligosaccharides (HMOs) are multifunctional carbohydrates in breast milk, which are composed by a variety of structures. This study aimed to identified HMOs concentration profile, milk microbiota composition, and the associations with major maternal characteristics in Han Chinese mothers in the one-year lactation period. Seventeen healthy mothers aged from 28 to 36 years, who gave birth to healthy term infants, were recruited. Carbohydrates were detected using the MIRIS human milk analyzer (HMA), and twenty-three HMOs were quantified using ultra-performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-MS). Results showed that carbohydrates were relatively stable, while total HMO concentrations ranged from 1.74 to 9.72 g/L and decreased gradually over lactation in breast milk. Based on the structure, seven sialylated HMOs concentration showed the significant decline (p<0.05) after three months in lactation. In addition, the relationships between maternal factors, containing the lactation period, genetic status, delivery mode, parity, and milk microbiota profile, and the HMO composition in healthy women, which still need further investigations, were observed.
Research on Fuzzy Comprehensive Evaluation Index System of Mental Health Education for College Students
Authors: Wang Tao
Published: April 2022

With the economic development and social progress, psychological crisis has become a very serious social problem, and the university campus is also inevitably affected. College students’ ability to resist pressure is poor, their psychology fluctuates greatly and changes constantly, and they are easily influenced by the outside world. Mental health assessment is a scientific means to quantitatively analyze and infer the characteristics of psychological changes in people’s behaviors by measuring and observing people’s representative behaviors in a strictly controlled environment. Analytic hierarchy process (AHP) is a method to determine the relative importance weight and relative order of advantages and disadvantages of various factors in the system, while fuzzy comprehensive evaluation is an effective method to evaluate fuzzy things comprehensively. This paper introduces the principle of the fuzzy comprehensive evaluation method, analyzes the feasibility and applicability of the fuzzy comprehensive evaluation method in social work evaluation of college students’ mental health schools, and draws relevant research conclusions and suggestions.
Nursing Students’ Perception of Clinical Teaching and Learning in Ghana: A Descriptive Qualitative Study
Authors: Amoo Sarah Ama , Aderoju Yaa Boahemaa Gyasi , Sarfo-Walters Richard , Doe Patience Fakornam , Okantey Christiana , Boso Christian Makafui , Abraham Susanna Aba , Druye Andrews Adjei , Ebu Enyan Nancy Innocentia
Published: April 2022

Background. Clinical teaching and learning are critical in bridging the theory-practice gap in nursing education. This study aimed at exploring nursing students’ perception of clinical teaching and learning in Ghana. In particular, this study sought to (1) describe the factors that promote clinical teaching, (2) examine students’ perception of clinical teaching, (3) describe the impact of clinical learning on students, and (4) explore ways of improving clinical teaching and learning. Methods. A descriptive qualitative study was conducted with 16 final-year nursing students using telephone-based interviews. Individual in-depth interviews were conducted with a semistructured interview guide, and data were analysed by the qualitative thematic analysis. Results. The findings indicate that being taught new things, being supervised, and having autonomy were the most significant factors that promoted clinical learning. Participants also reported that clinical experience created learning opportunities that helped develop clinical competence. They described learning experiences in the clinical setting as good, albeit gaps in practice. Poor staff attitude, lack of equipment, poor student attitude, inadequate learning opportunities, and lack of clinical supervisors were perceived as challenges in the clinical environment. Conclusions. Efforts to consciously teach, supervise, and challenge students to have independence in the clinical area will promote clinical teaching and learning. Therefore, nursing educational institutions and all other stakeholders need to collaborate in eliminating the numerous challenges students encounter in the clinical environment.
Collocating Recommendation Method for E‐Commerce Based on Fuzzy C‐Means Clustering Algorithm
Authors: Wang LiJia , Jiang Yanyan
Published: April 2022

In order to reduce the time for customers to select commodities they are interested in, improve the purchase efficiency, improve the success rate of sales of merchants, and create greater economic benefits for enterprises and merchants, this project collects information and data of e‐commerce users, using neural network model to analyze and mine data characteristics and shopping records of e‐commerce users. According to the analysis results, a user commodity recommendation system based on e‐commerce is implemented by using data mining technology. Through the combination of database technology, the transaction and browsing data generated in the process of e‐commerce transactions are collected. The collected data is preformatted and used as the input of data mining. Then, it uses data mining technology to mine and analyze the commodities that users are interested in, makes matching according to the types of commodities, and recommends the commodities that users are interested in under a given scene according to the established prediction model. By combining fuzzy clustering with collaborative filtering algorithm, this paper recommends the products that users are interested in, which are mined from historical data and commodity information.
A New Precise High Flow Oxygen Therapy System Based on Sliding Mode Control Strategy
Authors: Shi Yan , Xu Luyu , Xie Fei , Cai Maolin , Wang Yixuan
Published: April 2022

In recent years, precise high flow oxygen therapy as a new type of oxygen therapy machine has gradually attracted people’s attention and has been widely used in hospital emergency and clinical treatment of respiratory diseases; especially in recent years, severe coronavirus disease (COVID‐19) has played an important role in the treatment of patients. This paper presents a new type of precise high flow oxygen therapy machine with electromagnetic pneumatic flow valve as the core control element. A sliding mode control strategy based on the system is proposed to realize the accurate control of oxygen concentration and output flow of oxygen therapy mixture. The physical equipment of the precision high flow system is established, and its working performance is verified through the test platform. The optimization design goal of the precision high flow equipment is achieved.
Music Feature Extraction Method Based on Internet of Things Technology and Its Application
Authors: Chen Bo , Kou Heung , Hou Bowen , Zhou Yanbing
Published: April 2022

Due to the influence of factors such as strong music specialization, complex music theory knowledge, and various variations, it is difficult to identify music features. We have developed a music characteristic identification system using the Internet-based method. The physical sensing layer of our designed system deploys audio sensors on various coordinates to capture the raw audio signal and performs audio signal processing and analysis using the TMS320VC5402 digital signal processor; the Internet transport layer places audio sensors at various locations to capture the raw audio signal. The TMS320VC5402 digital signal processor is used for audio signal diagnosis and treatment. The network transport layer transmits the finished audio signal to the data base of song signal in the application layer of the system; the song characteristic analysis block in the application layer adopts dynamics. The music characteristic analysis block in the applied layer adopts dynamic time warping algorithm to acquire the maximal resemblance between the test template and the reference template to achieve music signal characteristic identification and identify music tunes and music modes based on the identification results. The application layer music feature analysis block adopts dynamic time regularization algorithm and mel-frequency cepstrum coefficient to achieve music signal feature recognition and identify music tunes and music patterns based on the recognition results. We have verified through experiments, and the results show that the system operates consistently, can obtain high-quality music samples, and can extract good music characteristics.
Alpha-Fetoprotein as a Potential Surrogate Biomarker for Atezolizumab + Bevacizumab Treatment of Hepatocellular Carcinoma
Authors: Zhu Andrew X. , Dayyani Farshid , Yen Chia-Jui , Ren Zhenggang , Bai Yuxian , Meng Zhiqiang , Pan Hongming , Dillon Paul , Mhatre Shivani K. , Gaillard Vincent E. , Hernandez Sairy , Kelley Robin Kate , Sangro Bruno
Published: April 2022

Purpose:

Atezolizumab + bevacizumab is the new standard of care for systemic treatment-naïve, unresectable hepatocellular carcinoma (HCC). This exploratory study investigated on-treatment alpha-fetoprotein (AFP) response as a potential surrogate biomarker of prognosis for the combination therapy.

Experimental Design:

Data from Group A of the phase Ib GO30140 study were used to identify the optimal time for AFP measurement and AFP cutoffs to differentiate patients by their best confirmed response per independent review facility–assessed RECIST (IRF-RECIST) version 1.1: responders from nonresponders and patients with disease control from primary progressors. We applied these cutoffs to independent data from the atezolizumab + bevacizumab arm of the phase III IMbrave150 trial to distinguish patients based on (i) overall survival (OS) and progression-free survival (PFS) per IRF-RECIST 1.1 and (ii) best confirmed response per IRF-RECIST 1.1.

Results:

We derived AFP cutoffs of ≥75% decrease and ≤10% increase from baseline at 6 weeks to identify responders and those who had disease control, respectively. These cutoffs had high sensitivity and specificity in GO30140. In IMbrave150 patients, sensitivity was 0.59 and specificity was 0.86 for the ≥75% decrease AFP cutoff; the sensitivity was 0.77 and specificity was 0.44 for the ≤10% increase AFP cutoff. Both AFP cutoffs were associated with longer OS and PFS, particularly in patients with hepatitis B virus etiology (HR < 0.5; P < 0.01).

Conclusions:

AFP response at 6 weeks after initiating treatment is a potential surrogate biomarker of prognosis for patients with HCC receiving atezolizumab + bevacizumab.

See related commentary by Cappuyns and Llovet, p. 3405
Autologous Nanobody-Derived Fratricide-Resistant CD7-CAR T-cell Therapy for Patients with Relapsed and Refractory T-cell Acute Lymphoblastic Leukemia/Lymphoma
Authors: Zhang Mingzhi , Chen Dan , Fu Xiaorui , Meng Huimin , Nan Feifei , Sun Zhenchang , Yu Hui , Zhang Lei , Li Ling , Li Xin , Wang Xinhua , Wang Min , You Fengtao , Li Zhaoming , Chang Yu , Zhou Zhiyuan , Yan Jiaqin , Li Jiwei , Wu Xiaolong , Wang Yu , Wang Yinyan , Xiang Shufen , Chen YuSheng , Pan Guifang , Xu Hanying , Zhang Bozhen , Yang Lin
Published: April 2022

Purpose:

Since CD7 may represent a potent target for T-lymphoblastic leukemia/lymphoma (T-ALL/LBL) immunotherapy, this study aimed to investigate safety and efficacy of autologous CD7–chimeric antigen receptor (CAR) T cells in patients with relapsed and refractory (R/R) T-ALL/LBL, as well as its manufacturing feasibility.

Patients and Methods:

Preclinical phase was conducted in NPG mice injected with Luc+ GFP+CCRF-CEM cells. Open-label phase I clinical trial (NCT04004637) enrolled patients with R/R CD7-positive T-ALL/LBL who received autologous CD7-CAR T-cell infusion. Primary endpoint was safety; secondary endpoints included efficacy and pharmacokinetic and pharmacodynamic parameters.

Results:

CD7 blockade strategy was developed using tandem CD7 nanobody VHH6 coupled with an endoplasmic reticulum/Golgi-retention motif peptide to intracellularly fasten CD7 molecules. In preclinical phase CD7 blockade CAR T cells prevented fratricide and exerted potent cytolytic activity, significantly relieving leukemia progression and prolonged the median survival of mice. In clinical phase, the complete remission (CR) rate was 87.5% (7/8) 3 months after CAR T-cell infusion; 1 patient with leukemia achieved minimal residual disease–negative CR and 1 patient with lymphoma achieved CR for more than 12 months. Majority of patients (87.5%) only had grade 1 or 2 cytokine release syndrome with no T-cell hypoplasia or any neurologic toxicities observed. The median maximum concentration of CAR T cells was 857.2 cells/μL at approximately 12 days and remained detectable up to 270 days.

Conclusions:

Autologous nanobody-derived fratricide-resistant CD7-CAR T cells demonstrated a promising and durable antitumor response in R/R T-ALL/LBL with tolerable toxicity, warranting further studies in highly aggressive CD7-positive malignancies.
Hardware impairments aware full-duplex non-orthogonal multiple access networks over Nakagami-m channels
Authors: Do Dinh-Thuan , Nguyen Tu-Trinh
Published: April 2022

Non-orthogonal multiple access (NOMA) and full-duplex (FD) relaying communications are promising candidates for 5G cellular networks. In this paper, by exploiting the impact of hardware impairment, we study FD NOMA communications with a downlink scheme. In a group of two users, we find that the target rates and power allocation strategies are main factors affecting the system performance metric. We derive the closed-form formula of outage probability for two users. As main contribution, numerical results are considered to illustrate the performance of the FD NOMA. We also study the base station (BS) can adjust its transmit signal to noise ratio (SNR) to achieve relevant outage probability in several scenarios.
Ergodic capacity of internet of things’ devices in presence of channel state information imperfection
Authors: Do Dinh-Thuan , Le Anh-Tu
Published: April 2022

Non-orthogonal multiple access (NOMA) is deployed to improve spectral efficiency for applications in fifth generation networks. NOMA system splits power domain to many parts to further serve massive users by relaxing the orthogonal use of radioresources. In this paper, a relay is required to help the source communicate with destinations with a fixed power allocation scheme. We derive expressions to highlight ergodic performance of two users the deployment of NOMA is suitable to different rate requirements from destinations (e.g., a cellular users have different requirements compared with internet of things devices). By conducting Monte-Carlo simulations, we find main system parameters which have crucial impacts on ergodic capacity. This paper is different other recent studies since we emphasize on imperfect channel state information (CSI) and Rician fading model for our analytical results.
Design Ultra-Wideband Antenna have A Band Rejection Desired to Avoid Interference from Existing Bands
Authors: Kamil Ansam Qasim , Jassim ِAli Khalid
Published: April 2022

Ultra-wideband antenna with band notch for rejecting bands. Rectangular slots are introduced on an arborescent patch to get UWB, coverage from 3.1–10.6 GHz. The antenna structure is fancied on FR4 the substrate with a size of 24 mm×24 mm×1.6 mm, a band notch located at 4.7 GHz is generated by adding the rectangular slot on the patch this microstrip antenna is simulated by computer simulation technology, the simulated and manufactured results show the antenna for wireless communication,to reduce the problem of interference in bands in communication systems by using the current distribution techniques, large bandwidths are reduced and unwanted bands are rejected by inserting notch such as rectangular slit and side slot on the patch. The presented antenna, use current redistribution technology, for the antenna designed by adding a rectangular aperture on a rectangular patch to change the current path to a zero value. Despite the fact that these antennas have strong band-notch characteristics and can match the criteria of UWB communication applications.
Design of triband antenna for telecommunications and network applications
Authors: AlShaikhli Noor Qusay A. , Neamah Mustafa Abdulkadhim , Aal-Nouman Mohammed Imad
Published: April 2022

In today’s world, the need for multifunctioning with the minimum possible physical size of the appliances has gone very vast. This paper presents a novel triband microstrip antenna with two slit cuts that is designed and simulated by exploiting CST microwave studio suite 2016. Proposed antenna is composed of one square patch on the top layer and an incised ground bottom layer. Designed antenna operates on three wireless bands and can be utilized for various wireless and networking applications. Bands of interest are 3.3 GHz (lower WIMAX possibly sub-6 GHz 5G applications), 4.5 GHz (data link system for UAV drones) 5.8 GHz (WLAN). This work also focuses on the physical layer of the TCP/IP networking Paradigm model, the optimized design and fabrication in the physical layer is vital because any design issue will create a bottlenecking effect even if the upper networking layer were optimized. Designing an efficient wireless antenna will benefit service providers as they will depend on such robust physical layer to push more traffic reliably and efficiently. Antenna is low profile, with low fabrication cost. Antenna size is 29.6×30.5×1.5 mm3. Parameters such as input reflection coefficient and far-field radiation pattern have been simulated and analyzed.
CaS: Sb3+, Na and ZnS:Sn2+: phosphor materials for the improvement of WLEDs
Authors: Huu Phuc Dang , Phung Ton That
Published: April 2022

The remote phosphor configuration, though not the best choice for WLED color quality, is superior to the luminous flux of LEDs compared to the conformal or in-cup structures. Realizing the capability of the remote phosphor design, several studies have been done to overcome the drawback of this structure, which is the color quality. A two-film distant phosphor configuration with improved color rendering index (CRI) and color quality ratio (CQS) for WLEDs is offered in this study paper. The hue temperature of the WLEDs packets employed in this research is 8500 K. This phosphor structure is constructed by layering of a green CaS:Sb3+,Na or red ZnS:Sn2+ phosphor above the yellow YAG:Ce3+ phosphor. The additional phosphor ZnS:Sn2+ concentration will then be modified to get the best color quality. The results demonstrated an increase in CRI and CQS along with the presence of ZnS:Sn2+, indicating that the existence of ZnS:Sn2+ influences significantly on these two aspects. As a result of the increased concentration of red illumination elements inside packets, the higher the concentration of ZnS:Sn2+, the higher the CRI and CQS. The green phosphor CaS:Sb3+,Na, in the meantime, improves the luminous flux.
Comparative study of BER With NOMA system in different fading channels
Authors: Jesudoss Roselin Suganthi , Kaleeswaran Rajeswari , Alagarsamy Manjunathan , Thangaraju Dineshkumar , Mani Dinesh Paramathi , Suriyan Kannadhasan
Published: April 2022

In today's world, cellular communication is rapidly expanding. One of the most common strategies for assigning the spectrum of users in cellular communication is the multiple access strategy. Because the number of people using cellular communication is continually expanding, spectrum allotment is an important factor to consider. To access the channel in fifth-generation mobile communication, a method known as non-orthogonal multiple access (NOMA) is used. NOMA is a promising method for improving sum rate and spectral efficiency. In this research, we used the NOMA approach to compare the bit error rate (BER) versus signal to noise ratio (SNR) of two users in rayleigh, rician, and nakagami fading channels. A single antenna with two users is used in this NOMA system. Two users can tolerate the same frequency with differing power levels in the power domain using 5G NOMA technology. Non-orthogonality ensures that NOMA users are treated equally to OMA users. According to the MATLAB simulation findings, the BER vs. SNR of two user NOMA in the Nakagami channel is substantially better than the rayleigh and rician channels.
Power analyzer of linear feedback shift register techniques using built in self test
Authors: Suriyan Kannadhasan , Ramalingam Nagarajan , Venusamy Kanagaraj , Sivaraman Sathish , Balasubramaniyan Kiruthiga , Alagarsamy Manjunathan
Published: April 2022

Wasteful patterns that don't lead to fault dropping squander a tone of energy in the linear-feedback shift register and circuit under examination in a random research region. Random switching actions in the CUT and scan pathways between applications with two consecutive vectors are another significant cause of energy loss. This study proposes a unique built-in self-test (BIST) technique for scan-based circuits that might help save energy. Only the available vectors are produced in a fixed series thanks to a mapping logic that alters the LFSR's state transitions. As a consequence, and without reducing fault coverage, the time it takes to execute trials has decreased. Experiments on circuits demonstrated that during random testing, the linear feedback shift register saves a significant amount of power.
Surveillance system of mask detection with infrared temperature sensor on Jetson Nano Kit
Authors: Hassan Noor Faleh Abdul , Abed Ali A. , Abdalla Turki Y.
Published: April 2022

Coronavirus desease-19 (COVID-19) has made it mandatory for people to cover their faces in public areas since the right use of a mask is effective at protecting people from viral infection. It has been also shown that body temperature may indicate an individual's health state. Deep learning is being used in this work to construct an actual strategy to meet the current demand for mask-wearing status and facial temperature detection before entering a public venue. For the mask detection service provider, a surveillance system is constructed utilizing a deep learning technique employing a Jetson Nano. The alert is triggered by an infrared temperature sensor and a buzzer. AMG8833 and C920e camera are used to take input images and measure a person's body temperature at the same time. A warning sound is produced when the temperature of a person's face exceeds the normal range for human beings during these tests, which result in a live video showing the right information on whether the individual is wearing a mask correctly and how hot his or her face is. The model is light and fast, with a 99% accuracy rate for training and a 100% accuracy rate while testing.
Extraction of human understandable insight from machine learning model for diabetes prediction
Authors: Assegie Tsehay Admassu , Karpagam Thulasi , Mothukuri Radha , Tulasi Ravulapalli Lakshmi , Fentahun Engidaye Minychil
Published: April 2022

Explaining the reason for model’s output as diabetes positive or negative is crucial for diabetes diagnosis. Because, reasoning the predictive outcome of model helps to understand why the model predicted an instance into diabetes positive or negative class. In recent years, highest predictive accuracy and promising result is achieved with simple linear model to complex deep neural network. However, the use of complex model such as ensemble and deep learning have trade-off between accuracy and interpretability. In response to the problem of interpretability, different approaches have been proposed to explain the predictive outcome of complex model. However, the relationship between the proposed approaches and the preferred approach for diabetes prediction is not clear. To address this problem, the authors aimed to implement and compare existing model interpretation approaches, local interpretable model agnostic explanation (LIME), shapely additive explanation (SHAP) and permutation feature importance by employing extreme boosting (XGBoost). Experiment is conducted on diabetes dataset with the aim of investigating the most influencing feature on model output. Overall, experimental result evidently appears to reveal that blood glucose has the highest impact on model prediction outcome.
A mitigation technique for torque ripple in a brushless DC motor by controlled switching of small DC link capacitor
Authors: Sirisha Bogimi , Yalakanti Laxminarayana
Published: April 2022

High performance applications are now days utilizing the brushless DC motor (BLDC) drives due to its ruggedness, compactness, high torque to weight ratio, high dynamic response etc. the feature of square-wave current excitation waveforms in BLDC motor drives allows some major system simplifications for trapezoidal BLDC motors. The developed torque is constant in ideal conditions in this motor when its back emf waveform is of trapezoidal type. Despite this, due to the physical construction of the motor and its settings, torque ripple exists in the output torque and is an undesired phenomenon in the BLDC motor drives and are also linked to the motor's control and driver sides. This paper provides a new way for reducing torque ripple and is simple, compact and cost effective. To prove the correctness of the compensation technique, circuit is modelled and simulations are carried to examine the theoretical performance of the BLDC motor drive. Experiments on a prototype drive were conducted to further validate the theoretical analysis as well as the utility of the proposed technique.
Traffic simulation in the LoRaWAN network
Authors: Mukhamejanova Almira D. , Grabs Elans A. , Tumanbayeva Kumyssay K. , Lechshinskaya Eleonora M.
Published: April 2022

LoRaWAN is one of the most commonly used technologies serving the internet of things (IoT) and machine-to-machine (M2M) devices. The traffic growth in the LoRaWAN network gives rise to many problems, which are solved using mathematical modelling. The actual task, in this case, is the development of a traffic simulation model in the LoRaWAN network. This article discusses the issues of traffic simulation in the LoRaWAN network and its research using the MATLAB system. The authors have developed a LoRaWAN network server model as a queuing system with incoming self-similar traffic in the MATLAB system using a separate subsystem for the input traffic modelling allowing to change the number of sources in the LoRaWAN network. The simulation results made it possible to establish the dependences of the network server’s buffer memory, the probability of packet loss from the incoming self-similar traffic parameters, and reveal the possibilities of traffic modelling in the MATLAB system.
Comparison of transfer learning method for COVID-19 detection using convolution neural network
Authors: Imaduddin Helmi , Yusfida Ala Fiddin , Fatmawati Azizah , Hermansyah Brian Aditya
Published: April 2022

Currently, one of the most dangerous diseases is Coronavirus disease 2019 (COVID-19). COVID-19 is a threat to the whole world, and almost all countries are experiencing the COVID-19 pandemic, including Indonesia. Various ways to detect COVID-19 sufferers have been carried out, such as swab tests, rapid tests, and antigens. One way that can be done to detect COVID-19 infection is to look at X-ray images of the patient's lungs because someone infected with COVID-19 has a different lung shape from normal people. Many studies have been carried out to detect COVID-19, using either machine learning (ML) or deep learning (DL). In this study, we propose to use transfer learning as an extraction feature in the classification of the covid dataset. The study was conducted four times using four different methods, namely ResNet 50, MobileNet V2, Inception V3, and DensNet-201. After experimenting, we compared the results to find out which method has the best results in detecting COVID-19. From this research, it was found that the ResNet 50 model has the best results with 92.3% accuracy, 93% precision, 93% F1-Score, 99% sensitivity, and 90.7% specificity.
Improved sensorless backstepping controller using extended Kalman filter of a permanent magnet synchronous machine
Authors: Kirad Abderrahmen , Groini Said , Soufi Youcef
Published: April 2022

This paper deals with an improved backstepping control strategy for sensorless control of a permanent magnet synchronous motor (PMSM) based on field-oriented control (FOC), using a backstepping controller to improve its performances. However, this control requires the precise knowledge of some machine’s variables which could not be available. In electric drives control, sensors are generally used as the main devices for feedback information. Some practical constraints could affect the system performances, due to the lack of measurement material or maintenance difficulties caused by the dysfunction or faults of the used sensors such as: encoder or resolver sensors of speed-position. In this paper, a sensorless control is proposed based on a dynamic backstepping method and an extended Kalman filter (EKF) which uses the state space formulation with a set of mathematical equations to recursively estimate future observations and minimizes the mean square error of the estimated variables (rotor speed position and torque) to design controllers for nonlinear systems. The proposed control scheme achieves the asymptotically uniformed stability. The effectiveness of this method is illustrated by the stabilization and tracking numerical examples and the obtained simulation results show the effectiveness and the feasibility of the proposed controller using Lyapunov approach.
A new ranking approach for E-commerce websites based on fuzzy TOPSIS algorithm
Authors: Belouaar Houcine , Kazar Okba , Zouai Meftah , Merizig Abdelhak
Published: April 2022

With the gigantic growth of the E-commerce market, E-commerce websites are becoming more and more numerous. Customers of E-commerce websites are spoiled for choice and have encountered several problems in choosing not only the right products but also the E-commerce website from which they want to purchase the desired products. E-commerce websites ranking is recognized as a complex multi-criteria decision-making (MCDM) problem. In practice, clients of E-commerce websites generally have difficulty expressing their judgments in precise numbers because the criteria are some- times imprecise and sometimes uncertain and ambiguous. In this context, we propose to use fuzzy logic to allow clients to express their ratings in natural language and propose an approach based fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) for E-commerce websites ranking. A numerical experimentation was conducted for validate the effectiveness of the proposed approach.
Implementation of FOC algorithm using FPGA for GaN-based three phase induction motor drive
Authors: Do Tung Duong , Duong Le Nam , Phuong Vu Hoang , Lam Nguyen Tung
Published: April 2022

Induction motor is widely used in industrial applications due to its low cost, simple design, and reliability. In this paper, the induction motor control structure FOC will be implemented on the FPGA platform for the drive system using GaN devices. By using GaN technology, the switching frequency can be up to 100 kHz instead of 2 to 20 kHz when using IGBT transistors. It leads to a significant reduction in switching loss as well as increasing the power density of the power electronic converter. The control structure will be programmed in VHDL language on the system-on-chip environment of Xilinx Zybo z7010 FPGA development board. The validity of the research is verified by some results when operating with HIL device.
Contemporary and future research of digital humanities: a scientometric analysis
Authors: Chansanam Wirapong , Ahmad Abdul Rahman , Li Chunqiu
Published: April 2022

This article analyses the special publications from 1999 to 2021, focusing on the scope and effect of digital humanities relevance research. The bibliometric analysis offers information on article publishing patterns, notable authors, cited references, institutions, nations, etc. Additionally, this paper covers the structure of knowledge of Digital humanities, including famous themes, co-citations, and bibliographic networks. Scopus database was used to obtain bibliographic data on September 25th, 2021, from papers published between 1999 and 2021. The bibliographic data for 1,249 publications using open-source analytic tools like the biblioshiny package in RStudio and the VOSviewer software shows it already. It employed the bibliometric package. These programmes visualized bibliography data based on their co-occurrence, co-citation, and coupling. The journal's publishing output and status in the area continue to rise, with 3,270 research papers indexed by Scopus to date. Additionally, the examination provides a thorough grasp of preceding patterns and forecasts a journal's future propensity.
Vehicles detection and counting based on internet of things technology and video processing techniques
Authors: A. Marzouk Marwa , El Azeem Amr Abd
Published: April 2022

Recent studies have proven that vehicle tracking and detection play an important role in traffic density monitoring. Traffic overcrowding can be effectively controlled if the number of vehicles expected to pass through a congested intersection can be predicted ahead of time. To overcome such impact of traffic congestion the proposed system presents a framework, using motion detection algorithms and “ThingSpeak” internet of things (IoT) platform which is used in to calculate traffic density, the proposed system capturing video with wireless internet protocol (IP) cameras and broadcasting it to the server where motion detection algorithms as background subtraction are used to obtain a quick overview of traffic density, To save cost and improve the solution, the suggested system utilizes image processing techniques as well as the IoT analytic platform “ThingSpeak” to monitor traffic density. Finally, the suggested method is used to manage traffic flow and avoid traffic crowded. The results of the studies show that the integration of IoT-based technologies with a modified background subtraction technique is effective. This method might be enhanced further to detect vehicles that break traffic laws. We may also improve this system by detecting the presence of emergency vehicles (including an ambulance or fire truck) and granting priority to those cars.
A proposed architecture for convolutional neural networks to detect skin cancers
Authors: Maher Ahmed Hasan , Younis Kashmola Manar
Published: April 2022

The goal of the research paper is to design and development of a computer-based system for the segmentation and classification of malignant skin diseases and a comparison between the accuracy of their detection, as two malignant diseases of skin diseases were detected. Namely, basal cell carcinoma and melanoma separately with images of nevus, and the images were collected from the ISIC 2020 archive group, as the total, The images used: 17,846 images include 3,008 images of basal cell carcinoma (BCC), 5,272 images of melanoma, and 9,566 images of a nevus, and validation data contains 20% of the images used which are not classified and randomly taken from the set of images, and the final test data contains 1,500 anonymous images. An architecture for the convolutional neural network technology in deep learning has been proposed that consists of a set of layers for processing. Processing raw input images for a group of pre-treatment transformations, the data augmentation process, so the number of images used became 86094 images of nevus, 27,072 images of BCC, and 47,448 images of melanoma. Through the detection process, the classification and detection accuracy of BCC was 98.25%, which is higher than the classification accuracy of melanoma is 91.61%.
Evaluation of efficiency of hedging strategies with option portfolios for buyers of the currency US dollar/Colombian peso
Authors: Gutierrez-Salazar Manuela , Jiménez-Gómez Miguel , Acevedo-Prins Natalia
Published: April 2022

This paper evaluates the efficiency to mitigate the exchange rate risk of nine hedging strategies with financial options. Strategies to hedging the purchase of US dollar Colombian peso (USDCOP) by importers in Colombia were raised. In this way, the traditional strategy with call options and eight strategies with investment portfolios were evaluated. These portfolios of options for hedge are offered by financial entities in Colombia. These nine hedged scenarios were compared with the unhedged scenario that corresponds to the foreign exchange risk exposure of importers. The USDCOP currencies were modeled with a mean reversion with jumps models, option premiums were valued with the black-scholes method and the best hedging strategy was determined through a Monte Carlo simulation. According to the results obtained, the nine hedging strategies manage to mitigate risk, but the most efficient was the option portfolio called collar.