bluuebunny/crossref_metadata_2025 huggingface dataset:
How Australian First Nations peoples living in the Torres Strait and Northern Peninsula Area of Australia describe and discuss social and emotional well-being: a qualitative study protocol
Authors: Meldrum Kathryn , Andersson Ellaina , Sagigi Betty , Webb Torres , Wapau Chenoa , Quigley Rachel , Strivens Edward , Russell Sarah
Published: December 2022

Introduction

Colonisation has, and continues to, negatively impact the mental well-being of Australia’s First Nations peoples. However, the true magnitude of the impact is not known, partially because clinicians have low levels of confidence in using many existing screening tools with First Nations clients. In addition, many authors have critiqued the use of tools designed for Western populations with First Nations peoples, because their worldview of health and well-being is different. Therefore, the aim of the overarching study is to develop an appropriate mental well-being screening tool(s) for older adults (aged 45 and over) living in the Torres Strait that can be used across primary health and geriatric settings. This protocol describes the first phase designed to achieve the overarching aim—yarning about social and emotional well-being (inclusive of mental well-being) in First Nations peoples living in the Torres Strait and Northern Peninsula Area of Australia.

Method and analysis

The study will be guided by decolonising and participatory action research methodologies. Yarning is an Australian First Nations relational method that relies on storytelling as a way of sharing knowledge. Yarning circles will be conducted with community members and health and aged care workers living on six different island communities of the Torres Strait. Participants will be recruited using purposive sampling. Thematic analysis of the data will be led by Torres Strait Islander members of the research team.

Ethics and dissemination

The Far North Queensland, Human Research Ethics Committee (HREC) (HREC/2021/QCH/73 638-1518) and James Cook University HREC (H8606) have approved this study. Dissemination of study findings will be led by Torres Strait members of the research team through conferences and peer-reviewed publications.
ImmunoSep (Personalised Immunotherapy in Sepsis) international double-blind, double-dummy, placebo-controlled randomised clinical trial: study protocol
Authors: Kotsaki Antigone , Pickkers Peter , Bauer Michael , Calandra Thierry , Lupse Mihaela , Wiersinga W Joost , Meylan Sylvain , Bloos Frank , van der Poll Tom , Slim Marleen A , van Mourik Niels , Müller Marcella C A , van Vught Lonneke , Vlaar Alexander P J , de Nooijer Aline , Bakkerus Lieke , Weis Sebastian , Antonakos Nikolaos , Netea Mihai G , Giamarellos-Bourboulis Evangelos J
Published: December 2022

Introduction

Sepsis is a major cause of death among hospitalised patients. Accumulating evidence suggests that immune response during sepsis cascade lies within a spectrum of dysregulated host responses. On the one side of the spectrum there are patients whose response is characterised by fulminant hyperinflammation or macrophage activation-like syndrome (MALS), and on the other side patients whose immune response is characterised by immunoparalysis. A sizeable group of patients are situated between the two extremes. Recognising immune endotype is very important in order to choose the appropriate immunotherapeutic approach for each patient resulting in the best chance to improve the outcome.

Methods and analysis

ImmunoSep is a randomised placebo-controlled phase 2 clinical trial with a double-dummy design in which the effect of precision immunotherapy on sepsis phenotypes with MALS and immunoparalysis is studied. Patients are stratified using biomarkers. Specifically, 280 patients will be 1:1 randomly assigned to placebo or active immunotherapy as adjunct to standard-of-care treatment. In the active immunotherapy arm, patients with MALS will receive anakinra (recombinant interleukin-1 receptor antagonist) intravenously, and patients with immunoparalysis will receive subcutaneous recombinant human interferon-gamma. Τhe primary endpoint is the comparative decrease of the mean total Sequential Organ Failure Assessment score by at least 1.4 points by day 9 from randomisation.

Ethics and dissemination

The protocol is approved by the German Federal Institute for Drugs and Medical Devices; the National Ethics Committee of Greece and by the National Organization for Medicines of Greece; the Central Committee on Research Involving Human Subjects and METC Oost Netherland for the Netherlands; the National Agency for Medicine and Medical Products of Romania; and the Commission Cantonale d’éthique de la recherche sur l’être human of Switzerland. The results will be submitted for publication in peer-reviewed journals.

Trial registration number

NCT04990232.
Characteristics of HIV pre-exposure prophylaxis users at first PrEP counselling visit: the CSL-PrEP cohort
Authors: Nozza Silvia , Raccagni Angelo Roberto , Lolatto Riccardo , Ceccarelli Daniele , Galli Laura , Alberton Francesca , Bruzzesi Elena , Canetti Diana , Strano Martina , Ripa Marco , Bertoni Costanza , Castagna Antonella
Published: December 2022

Objectives

Pre-exposure prophylaxis (PrEP) is effective for HIV prevention and is mostly used by men who have sex with men (MSM). The aim of this study was to describe the characteristics of a cohort of PrEP users at first PrEP counselling visits (baseline, BL).

Design

Cross-sectional study of a cohort of MSM receiving PrEP (Centro San Luigi, CSL-PrEP Cohort).

Setting

Secondary-level sexually transmitted infections (STI) centre in Milan, Italy, from May 2017 to May 2022.

Participants

Overall, 624 MSM PrEP users were included; most users were Caucasian (97%), attended university (64%), with a median BL age of 34.5 years.

Results

Overall, 45% choose the daily-based PrEP regimen, 55% the event-based one. An increasing trend in PrEP counselling visits was observed (p=0.024). The majority had between 10 and 19 partners in the 3 months before BL and 41% were chemsex users. All had a HIV Incidence Risk Index for MSM (HIRI-MSM)>10, 54% between 20 and 29. Overall, 50% had ≥1 previous STI and 22% ≥1 BL STI. BL chlamydia (10%) was often more frequent than in the past (7%). The number of sexual partners was associated with BL chlamydia (p<0.001), gonorrhoea (p=0.002) and syphilis (p=<0.001), HIRI-MSM with chlamydia (p=0.001) and gonorrhoea (p=0.008), chemsex use with chlamydia (p=0.003) and gonorrhoea (p=0.030).

Conclusions

We observed an unbalanced access to PrEP in respect to all key populations which might benefit from PrEP, with a similar choice for event-based or daily-based regimens. High-risk behaviours and STIs were frequently observed. History of chlamydia was very frequently high in asymptomatic MSM at BL, compared with what observed before access to PrEP. High-risk behaviours and HIRI-MSM were associated with most of STIs.
Responding to COVID-19 with integrative health and sheltering models for persons experiencing homelessness in Southern Ontario, Canada: protocol for a qualitative study exploring implementation and sustainability
Authors: Elliott Jacobi , Forchuk Cheryl , Sacco Veronica , Hiebert Bradley , Tong Catherine E , Whate Alexandra , Bondy Jessica , Stolee Paul
Published: December 2022

Introduction

COVID-19 has disproportionately impacted persons experiencing homelessness in Canada, who are at an increased risk of infection and severe outcomes. In response to the pandemic, several regions have adopted programmes that aim to address the intersecting nature of health and social challenges faced by persons facing homelessness. These programmes adopted during the pandemic may contribute to broader health and social impacts beyond limiting COVID-19 transmission, but the processes involved in developing and implementing these types of programmes and their sustainability after the pandemic are unknown. Our overall goal is to understand the processes of developing and implementing integrative health and sheltering initiatives in Ontario during COVID-19, as well as their sustainability post-pandemic.

Methods and analysis

This study will use a multiple case study design—two cases over 1 year—enabling us to investigate how integrative health and sheltering approaches have been implemented in two mid-sized cities in Ontario, Canada. Each case will offer a unique narrative; through cross-case analysis, the cases will highlight programme operations, successes and challenges. Data will be collected using semi-structured interviews with programme staff and managers, and document analysis. Project partners will be brought together to further explore and interpret findings, along with co-creating a sustainability action plan and policy documents.

Ethics and dissemination

Ethics clearance was obtained through the Western University Research Ethics Board and the University of Waterloo Office of Research Ethics. Findings will be disseminated through publications, conference presentations and lay summary reports.
Prevalence and associated factors of symptomatic dry eye among undergraduate students in Hawassa University College of Medicine and Health Sciences, Hawassa, Ethiopia
Authors: Mohammed Seid , Kefyalew Biruktawit , Kebede Balcha Negese , Markos Lorato Merkineh
Published: December 2022

Objective

This study aimed to assess the prevalence and associated factors of symptomatic dry eye (SDE) among undergraduate students at the College of Medicine and Health Science, Hawassa University, Ethiopia.

Methods and analysis

Institution-based cross-sectional study was conducted using a systematic random sampling technique. A total of 311 undergraduate students were recruited to execute the study. Ethical clearance was obtained from the ethical review committee of the school of Medicine and Health Science. A standardised self-administered questionnaire was used to collect the data. Data were entered using Epi Info V.7 and cleaned and analysed using SPSS V.23. Binary and multivariable logistic regression analysis was done to select candidate variables and to identify statistically significant factors. Variables with a p value of <0.05 on multivariable analysis were reported as statistically significant.

Results and conclusion

The overall prevalence of SDE was found to be 49.4% (95% CI 43.7% to 55.1%). In this study, the history of ophthalmic drop use (adjusted OR, AOR 2.063; 95% CI 1.073 to 3.957) and being second (AOR 5.99; 95% CI 1.10 to 32.56) and third (AOR 11.55; 95% CI 2.12 to 62.94) year student were factors that significantly associated with SDE.

In this study, the prevalence of SDE was significantly high. The factors associated with SDE were the use of ophthalmic drops and the class year of students. Therefore, public health education about protective measures should be considered to minimise the effects of SDE on the quality of life of students.
Impact of cardiovascular health and genetic risk on coronary artery disease in Chinese adults
Authors: Cui Qingmei , Liu Zhongying , Li Jianxin , Liu Fangchao , Niu Xiaoge , Shen Chong , Hu Dongsheng , Huang Keyong , Chen Shufeng , Zhao Yingxin , Lu Fanghong , Liu Xiaoqing , Cao Jie , Wang Laiyuan , Ma Hongxia , Yu Ling , Wu Xianping , Li Ying , Zhang Huan , Mo Xingbo , Zhao Liancheng , Hu Zhibin , Shen Hongbing , Huang Jianfeng , Lu Xiangfeng , Gu Dongfeng
Published: December 2022

Objective

To examine whether adherence to ideal cardiovascular health (CVH) can mitigate the genetic risk of coronary artery disease (CAD) in non-European populations.

Methods

Fine and Grey’s models were used to calculate HRs and their corresponding 95% CIs, as well as the lifetime risk of CVH metrics across Polygenic Risk Score (PRS) categories.

Results

We included 39 755 individuals aged 30–75 years in Chinese prospective cohorts. 1275 CAD cases were recorded over a mean follow-up of 12.9 years. Compared with unfavourable CVH profile (zero to three ideal CVH metrics), favourable CVH profile (six to seven ideal CVH metrics) demonstrated similar relative effects across PRS categories, with the HRs of 0.40 (95% CI 0.24 to 0.67), 0.41 (95% CI 0.32 to 0.52) and 0.36 (95% CI 0.26 to 0.52) in low (bottom quintile of PRS), intermediate (two to four quintiles of PRS) and high (top quintile of PRS) PRS categories, respectively. For the absolute risk reduction (ARR), individuals with high PRS achieved the greatest benefit from favourable CVH, mitigating the risk to the average level of population (from 21.1% to 8.7%), and the gradient was strengthened in individuals at the top 5% of PRS. Moreover, compared with individuals at low PRS, those at high PRS obtained longer CAD-free years (2.6 vs 1.1) from favourable CVH at the index age of 35 years.

Conclusion

Favourable CVH profile reduced the CAD relative risk by similar magnitude across PRS categories, while the ARR from favourable CVH was most pronounced in high PRS category. Attaining favourable CVH should be encouraged for all individuals, especially in individuals with high genetic susceptibility.
Discrepancy in the use and interpretation of marker sutures among plastic surgeons and pathologists
Authors: Jones Elizabeth , Patel Chantal , Mudaliar Vivek , Ismail Amir
Published: December 2022

Marker sutures are often used for excised cutaneous lesions to aid histological analysis, however, there are no current guidelines to facilitate this in practice. The authors hypothesised that a lack of guidelines causes a variation in clinical practice and confusion of meaning between plastic surgeons and pathologists. This questionnaire-based study confirms the authors’ hypothesis and highlights a discrepancy both between surgeons and in individual surgical practice. More importantly, we identify discord between histopathologists and plastic surgeons in relation to marker suture placement and report interpretation, leading to potential undertreatment of patients. This paper adds to the growing literature calling for guidelines regarding marker suture placement for cutaneous excision biopsies.
Geo- and reactor antineutrino sensitivity at THEIA
Authors: Zsoldos Stephane , Bagdasarian Zara , Orebi Gann Gabriel D. , Barna Andrew , Dye Stephen
Published: December 2022

We present the sensitivity of the Theia experiment to low-energy geo- and reactor antineutrinos. For this study, we consider one of the possible proposed designs, a 17.8-ktonne fiducial volume Theia-25 detector filled with water-based liquid scintillator placed at Sanford Underground Research Facility (SURF). We demonstrate Theia’s sensitivity to measure the geo- and reactor antineutrinos via inverse-beta decay interactions after one year of data taking with $$11.9 \times 10^{32}$$

11.9
×

10
32

free target protons. Considering all uncertainties on input throughout the whole analysis chain, the expected number of geo- and reactor antineutrinos is $$220\,^{+30}_{-24}$$

220

-
24

+
30

(stats+syst) and $$168\,^{+26}_{-24}$$

168

-
24

+
26

(stat+sys), respectively, after one year of data taking. The corresponding expected fit precision of a sole experiment is evaluated at 8.7% and 10.1%, respectively. We also demonstrate the sensitivity towards fitting individual Th and U contributions, with best fit values of $$N_\text {Th}=40^{+26}_{-22}$$

N
Th

=

40

-
22

+
26

(stat+sys) and $$N_\text {U}=180^{+30}_{-24}$$

N
U

=

180

-
24

+
30

(stat+sys). Finally, from the fit results of individual Th and U contributions, we evaluate the mantle signal to be $$S_\text {mantle} = 9.3\,\pm [5.2,5.4]$$

S
mantle

=
9.3

±

[
5.2
,
5.4
]

 NIU (stat+sys). This was obtained assuming a full-range positive correlation ($$\rho _c\in [0, 1]$$

ρ
c

∈

[
0
,
1
]

) between Th and U, and the projected uncertainties on the crust contributions of 8.3% (Th) and 7.0% (U).
Application of Intelligent Voice Technology and Sensor Network in Production and Operation Management VR Intelligent Teaching System
Authors: Yang Sijia
Published: December 2022

In this paper, first, we discuss the status quo of research and development of intelligent speech technology and analyze the problems existing in today’s education. The second is to explain the related concepts of intelligent speech technology, and, at the same time, to conduct in-depth research on the intelligent speech technology tools used in the experimental research and the related functions of the educational applications cited in this research, and briefly describe the correlation between information education and language learning basic knowledge. Then we summarize the structure, attributes, scope and existing solutions to solve the energy efficiency of the sensor network, focus on the classification and analysis of the existing routing protocols of the wireless sensor network, and summarize the characteristics of the protocol. In addition, this paper conducts extensive research on the relationship between LEACH protocol cluster division and energy consumption. This paper focuses on the shortcomings of the mainstream virtual reality (VR) system creation method, and proposes a method of interactive design, which significantly reduces the threshold for creating VR content and improves the efficiency of VR creation. Wisdom teaching technology not only mobilizes the enthusiasm of students in learning, but also helps to improve the teaching effect. Finally, it summarizes the specific work and importance of the research, and shows the application and development prospects of intelligent teaching technology in future education. Through the research of intelligent voice technology and sensor network, this paper applies it to the VR intelligent teaching system, and promotes the development of the VR intelligent teaching system in future education.
Making AI Fair, and How to Use It
Authors: Rotenberg Marc , Roschelle Jeremy
Published: December 2022

The
Communications
website, https://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.

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Follow us on Twitter at http://twitter.com/blogCACM

https://cacm.acm.org/blogs/blog-cacm

Marc Rotenberg looks at how an early AI study led to the 1974 Privacy Act, while Jeremy Roschelle considers different aspects of human-centric AI.
The Outlook for Crypto
Authors: Savage Neil
Published: December 2022

Can cryptocurrencies cut their environmental impact?
Research for Practice
Authors: Alagappan Ramnatthan , Alvaro Peter
Published: December 2022

Keeping data safe in the presence of crashes is a fundamental problem.
A Flexible, Low-Cost, Disposable Non-Enzymatic Electrochemical Sensor Based on MnO2/Cellulose Nanostructure
Authors: Tohamy Hebat-Allah S. , Magar Hend S.
Published: December 2022

In this investigation, a new class of polysaccharide (cellulose nanowhiskers ) in the presence of manganese oxide nanoparticles (MnO2 NPs) to produce hybrid materials was synthesized and used as a new sensor platform with high and fast electrochemical responses. A simple method of synthesis for producing different cellulosic nanostructures has been evaluated and characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscope (SEM),cyclic voltammogram (CV) and electrochemical impedance spectra (EIS). The FTIR analysis data approved the formation of cellulose and MnO2 nanostructures. The uniform distribution of MnO2 nanostructure over the cellulose nanowhiskers surface has been approved by using SEM. In addition, From CV and EIS characterization MnO2/Cellulose hybrid materials have electrocatalytic properties and promising applications in biosensors and non-enzymatic sensors fields. The MnO2/cellulose non-enzymatic sensor have been used for hydrogen peroxide choronoamperometric detection with high sensitivity 0.70 μA μM−1, a linear concentration range from 0.2 − 400 μM, lower of detection limit (LOD) of 0.04 μM (S/N = 3) and R2 of 0.98. The sensor was used for hydrogen peroxide detection in real samples with a high percentage of recovery from 93 to 110 %.
Decision Support System Based on Complex
q
-Rung Orthopair Fuzzy Rough Hamacher Aggregation Operator through Modified EDAS Method
Authors: Qiyas Muhammad , Abdullah Saleem , Naeem Muhammad , Khan Neelam , Okyere Samuel , Botmart Thongchi
Published: December 2022

The best mathematical tools for combining numerous inputs into a single result are aggregation operators. The aggregation operators work to combine all of the individual evaluation values provided in a uniform form, and they are very useful for evaluating the options provided in the decision-making process. To provide a larger space for decision makers, complex

q

-rung orthopair fuzzy rough sets can express their uncertain information. As a generalization of the algebraic operations, the Einstein

t

-norm and

t

-conorm, Hamacher operations have become significant in aggregation theory. The Hamacher aggregation operator’s major characteristic is that it can capture the interrelationship between several input arguments. In this article, some Hamacher aggregation operators for complex

q

-rung orthopair fuzzy rough sets are presented. We define a complex

q

-rung orthopair fuzzy rough Hamacher operation laws and a new score function. In addition, we propose a serious of averaging aggregation operators for complex

q

-rung orthopair fuzzy rough set. We present the essential properties of these operators. We use the defined operators and modified EDAS (evaluation based on distance from average solution) method to propose an approach for solving a multicriteria decision making problem. To demonstrate the practicality and effectiveness of our propose model, we consider a numerical example of area selection for an arboretum. Finally, a comparison between the suggested approach with existing operators has been presented for authenticity and reliability.
Utilizing the power controller, enhance the operation of a single-phase AC to DC converter
Authors: Hameed Ahmed Raghad , Taha Yunis Mohammed , Taresh Dawood Basima
Published: December 2022

Smooth switching technology with a single-phase converter from AC to DC is existing in this work. A study of implementing a buck-batch converter was explored and the implementation details assessed. The system explaining the versatile balanced power control (VPBC) has advantages, the suggested boost buck processor is charged during the downtime; the voltage is relieved via the MOSFET switch. It has enhanced the power factor to 0.9715 at full load in further development. The advanced model of the AC to DC converter design will maintain stability and its reliability will depend on the average “charge” and “discharge” with the help of the VPBC-controlled current of the inductor, compensate automatically. Because of this process, a linear construction between line current and voltage is achieved by running normal work at regular intervals. As a result, they almost realized the PF at the input source. The output voltage of the planned for any load condition in the transformer model is always constant (0-1,000) watts. Suggested circuit has a great dynamic reaction.  Suggested PFC circuit is usable for a range of loads. From the simulation, the efficiency of the suggested transformer is 91.11% upper at the rated load. Designed by MATLAB.
Degradation assessment of two silicon photovoltaic technologies under subtropical desert climate
Authors: Oum'bark Fatimazahra , Lotfi Hicham , Bennouna Amin , Ouacha El Houssaine
Published: December 2022

The prediction of performance of photovoltaic technologies is crucial, not only to improve the reliability and durability of these technologies but also to increase the confidence of investors and consumers in them. The accurate calculation of the degradation rate DR (%) in real operating conditions under specific climatic stresses is, therefore, paramount. The present study provides a comparison of performance losses of two silicon PV technologies installed on the rooftop of the Higher School of Technology in Laâyoune-Morocco. The two systems are a polycristalline array (pc-Si: 1.82 kWp) and an amorphous array (a-Si: 1.55 KWp), which are grid connected. In the light of related performance gathered over three-year, the degradation rates of the two systems were estimated using four statistical methods under the open-source software R. The techniques engaged in this paper are: classical seasonal decomposition (CSD), holt-winters (HW), autoregressive integrated moving average (ARIMA), and seasonal and trend decomposition by LOESS (STL). The results obtained using those methods show that DR(%) varies between 0.39% and 0.99% for pc-Si and between 0.29% and 0.64% for a-Si. The analysis of degradation accuracy shows that STL and CSD techniques provide results with high accuracy than ARIMA and HW for the two systems. The present study adds to knowledge on PV degradation under the subtropical desert climate of Laâyoune.
Optimization of location and rating of unified power flow controllers for congestion management
Authors: Alagapuri Vengadesan , Bakkiyaraj Radhakrishnan Ashok , Sithangkathan Sakthivel , Kalikrishnan Jayanthi
Published: December 2022

Large number of contracted power exchanges among sellers and purchasers, in a deregulated power market causes transmission line congestion. Congestion of lines undermines the security and economy of power networks. Flexible AC transmission system (FACTS) devices are introduced at appropriate spots to change the power flow in order to keep the flow of the lines within their capability. In this work, the most commonly used unified power flow controller (UPFC) is proposed for achievement of changing the line flow and for easing congestion from the over loaded lines. The size and site of UPFC controllers significantly impact their performance in congestion management task. The location and size of the UPFC devices are to be optimized by using an optimization algorithm. Whale optimization algorithm (WOA) is exploited in this effort for realizing the aim of determination of site and size of the FACTS converters. The present method has lesser quantity of variables which are tuned to get best outcomes. The suggested WOA based technique is executed on the IEEE 57 bus system. The outcomes comparison is made with particle swarm optimization algorithm (PSO) and firefly algorithm (FFA) and the better improved outcomes are found.
PI controller for photovoltaic-fed novel multilevel inverter topologies
Authors: Karthikeyan Dhandapani , Rajiv Khiani Simran , Alice Hepzibah Albert , Jothilingam Uthayakumar , Ramkumar Ravindran , Venkadasamy Prathaban Arumbu , Vijayakumar Krishnasamy
Published: December 2022

This research describes the analysis and design of a unique 7-level and 9-level multi-level inverter topology with fewer DC power supplies and power switches, and a comparison using pulse width modulation (PWM). Comparisons of 7-level and 9-level multi-level inverters that analyze characteristics using optimal nearest level modulation (ONLM) technology are made using various PWM approaches such as nearest level modulation (NLM) technique, phase disposition (PD), phase opposition disposition (POD), and alternate phase opposition disposition (APOD). The output is evaluated based on a high Vrms, low total harmonic distortion (THD) harmonic profile. The controller is based on artificial intelligence (AI) and machine learning (ML) techniques. ONLM techniques are used to measure the voltage harmonics of the full load, several DC offset values are used. The control technology provided is validated using MATLAB/Simulink simulation tools and laboratory-based experimental testing.
Performance improvement of dye-sensitized solar cells by using natural chlorophyll and anthocyanin dyes
Authors: Rizka Aziza Miladina , Maulana Eka , Mudjirahardjo Panca , Jumiadi Jumiadi
Published: December 2022

Natural dye-sensitized solar cells (DSSC) have gained so much attention in recent years due to its low-cost fabrication process, ease of fabrication, and environmentally friendly. In order to improve the DSSC performance, the absorbance spectral of dyes must reach the maximum visible spectrum values. The combination of two dyes with different absorbance spectra can be utilized to expand the absorbance spectral. Here, we demonstrated the combination of natural chlorophyll and anthocyanin dyes from cassava leaves and black sticky rice, respectively, to enhance the DSSC performance. Our findings provide insights for increasing the DSSC performance by varying the combination of natural dyes. The highest efficiency was obtained from Chlorophyll:Anthocyanin 3:1.
Real-time implementation of SVPWM-sensorless vector control of induction motor using an extended Kalman filter
Authors: Bendjima Mustapha , Hazzab Abdeldjebar , Bechar Mansour , Khessam Medjdoub , Rezkallah Miloud , Chandra Ambrish , Ibrahim Hussein
Published: December 2022

In this research paper, space vector pulse width modulation (SVPWM)-sensorless vector control of an induction motor using an extended Kalman filter is presented. The aim of the proposed sensorless control method is to design, implement, and test a sensorless vector control scheme by simulation and experimental implementation. An extended Kalman filter (EKF) simultaneously estimates the rotor speed, the stator stationary axis components (iαs, iβs), and the rotor fluxes (jαs, jβs). The measured stator voltages and currents are employed as inputs for a recursive filter. Simulation results under various operating conditions validate the performances and effectiveness of the proposed observer. The experimental system consists of a host computer with two subsystems: console (SC) and master (SM). The SM subsystem converts to real-time C code, and this code is uploaded into OP5600 real time digital simulation (RTDS) for real-time execution. The obtained experimental results prove that the EKF speed observer can replace the speed or position sensor. This has the benefits of reducing the drive system’s size and overall cost as well as high system reliability.
Optimization of wireless sensor networks energy consumption by the clustering method based on the firefly algorithm
Authors: Diakhate Ismaila , Niang Boudal , Dooguy Kora Ahmed , Marcelain Faye Roger
Published: December 2022

Wireless sensor networks (WSNs) contain an inordinate number of sensor nodes that are spatially distributed. The network is composed of entities that determine its lifetime. The WSN nodes are equipped with a battery whose autonomy is limited in duration. In this paper, different solutions are introduced to improve the overall energy consumption of the network in order to improve its lifetime. Contrary to many works considering the clustering algorithm as one potential candidate to improve the network's lifetime, this study has investigated the firefly algorithm optimization where an optimal cluster head is selected from a group of nodes. The set-up process of the cluster head is based on a set of conditions. To measure the performance of the proposed approach, the number of dead nodes and data packets received by the base station (BS) or sink node are considered. The results are tested on 100 nodes for 5000 transmission rounds, the amount of data transported is 20 million bits a little more than the other methods. It has been shown that the proposed solution outperformed the traditional low energy adaptive clustering hierarchy (LEACH), threshold sensitive energy efficient sensor network (TEEN), and developed distributed energy-efficient clustering (DEEC) approaches.
A new design of 5G multilayers planar antenna with the enhancement of bandwidth and gain
Authors: Bellekhiri Abderrahim , Chahboun Noha , Zbitou Jamal , Laaziz Yassin , El Oualkadi Ahmed
Published: December 2022

In this work, we design a microstrip patch antenna having a dimension of 3.279x4.232 mm2 and consisting of a Foam-like substrate, of a relative dielectric permittivity of 1 and with a width of 0.5 mm, placed between two identical Rogers RT5880 substrates, having a value of 2.2 as relative dielectric permittivity, a loss tangent of 0.0009 and a height of 0.508 mm. The designed antenna resonates at 28 GHz, featuring a maximum gain of 9.77 dBi and a wide frequency bandwidth of 2.9 GHz. Compared to the conventional antenna, this proposed structure achieved an important enhancement of the directivity, with a value around 38.8°. The CST Microwave Studio software was used for all designs and analysis.
Reputation-based Security model for detecting biased attacks in BigData
Authors: Desai Vinod , Hagare Annappaiah Dinesha
Published: December 2022

As internet of things (IoT) devices are increasing since the emergence of these devices in 2010, the data stored by these devices should have a proper security measure so that it can be stored without getting in hands of an attacker. The data stored has to be analyzed whether the data is safe or malicious, as the malicious data can corrupt the whole information. The security model in BigData has many challenges such as vulnerability to fake data generation, troubles with cryptographic protection, and absent security audits. As cyberattacks are increasing the main objective of each organization is to secure the data efficiently. This paper presents a model of reputation security for the detection of biased attacks on BigData. The proposed model provides various evaluation models to identify biased attack in malicious IoT devices and provide a secure communication metric for BigData. The results show better rates in terms of attack detection rate, attack detection failure rata, system throughput and number of dead nodes when the attack rate is increased when compared with the existing reputation-based security (ERS) model. Moreover, this model reputation-based biased attack detection (RBAD) increases the security of the IoT devices in the BigData and reduces the biased attack coming from various malicious nodes.
Preconditioned successive over relaxation iterative method via semi-approximate approach for Burgers’ equation
Authors: Farah Azira Zainal Nur , Sulaiman Jumat , Saudi Azali , Afza Mat Ali Nur
Published: December 2022

This paper proposes the combination of a preconditioner applied with successive over relaxation (SOR) iterative method for solving a sparse and huge scale linear system (LS) in which its coefficient matrix is a tridiagonal matrix. The purpose for applying the preconditioner is to enhance the convergence rate of SOR iterative method. Hence, in order to examine the feasibility of the proposed iterative method which is preconditioner SOR (PSOR) iterative method, first we need to derive the approximation equation of one-dimensional (1D) Burgers’ equation through the discretization process in which the second-order implicit finite difference (SIFD) scheme together with semi-approximate (SA) approach have been applied to the proposed problem. Then, the generated LS is modified into preconditioned linear system (PLS) to construct the formulation of PSOR iterative method. Furthemore, to analyze the feasibility of PSOR iterative method compared with other point iterative methods, three examples of 1D Burgers’ equation are considered. In conclusion, the PSOR iterative method is superior than PGS iterative method. The simulation results showed that our proposed iterative method has low iteration numbers and execution time.
Optimization artificial neural network classification analysis model diagnosis Gingivitis disease
Authors: Ariandi Vicky , Yanto Musli , Jamhur Annisak Izzaty , Firdaus Firdaus , Afira Riandana
Published: December 2022

Gingivitis is a disease that can be caused by the buildup of bacteria and plaque caused by leftover food. This disease can attack anyone, especially children who are not aware of maintaining dental and oral health. This study aims to build and optimize the classification analysis model for the diagnosis of Gingivitis. The classification analysis model was built using the artificial neural network (ANN) method which was optimized using fuzzy logic and the multiple linear regression (MRL) method. Optimization with fuzzy aims to develop a pattern of rules in the detection. The MRL method is also used as a process of measuring analysis patterns to ensure the analytical model presents maximum results. The results study indicate that the optimization of fuzzy and MRL methods provides excellent output. These results are based on the fuzzy output which can provide a pattern of 40 rules. The MRL method is can present the level of correlation of each analysis variable with a significant output having an average value of 94.2%. Based on the results of this study, the analysis model that is optimized with the fuzzy logic method and MRL contributes to maximizing the process of diagnosing Gingivitis.
Mobile application with business intelligence to optimize the control process of tourist agencies
Authors: Angel Valenzuela Ygnacio Luis , Giraldo Retuerto Margarita , Andrade-Arenas Laberiano
Published: December 2022

Currently, tourism companies do not have a strict control of clients, drivers, buses, guides and tickets; Drivers are known to drive at excessive speed and put their lives and the lives of their customers at risk, this occurs because drivers want to gain more passengers or race with a car from the same company. For this reason, the research work aims to optimize the travel control process for tourism companies by applying business intelligence. The kimball methodology was used, which allows making a dimensional model with dimensions and a central table of the process or event that occurs in real time, tourism companies would be benefiting since in decision-making in the field of travel control, they would have the most relevant data. In addition, users are also beneficiaries, clients who minimize risks when acquiring the tourism service, this would increase more profits for the tourism company and increase its clientele.
Cloud computing: google firebase firestore optimization analysis
Authors: Bahtiar Semma Andi , Ali Mukti , Saerozi Muh , Mansur Mansur , Kusrini Kusrini
Published: December 2022

Cloud computing is a new paradigm that provides end users with a secure, personalized, dynamic computing environment with guaranteed service quality. One popular solution is Google cloud firestore, a global-scale not only structured query language (NoSQL) document database for mobile and web apps. Recent research on cloud-based NoSQL databases often discusses the difference between them and SQL databases and their performance. However, using cloud-based NoSQL databases such as firestore is tricky without any scientific comparison methodology, and it needs analysis of how its particular systems work. This study aims to discover what is the best design that could be implemented to optimize data read cost, response size, and time regarding the cloud firestore database. In this study, we develop a grade point average (GPA)-report mocking application to assess data read based on our institution’s needs. This application consists of three functions. Add the graduated GPA and students’ names, and view the ten highest GPAs, GPA average, and total graduated students. The finding indicates that aggregating data on the client side or utilizing the Google cloud function trigger, then updating aggregation data in one transaction significantly reduces document read count (cost), response size, and time.
Mobile application for care and health control of camelids
Authors: Demmis Muñoz Villacorta Roberto , Manuel Oscco Aguero Carlos , Andrade-Arenas Laberiano
Published: December 2022

Due to the events caused by COVID-19, several activities were paralyzed, such as the export of camelids. In the present study, it was observed that many of the camelids that are located in the highest of the Andes, are exposed to diseases that originate from climatic changes or from the infrastructure in which they are inhabiting. For this reason, the veterinary mobile application for camelids was implemented, which will help care as well as sanitary control, this application was developed through the agile scrum methodology, since it adapts to the various modules used, which would be consulta of diseases, recommendations for breeding and contacts with veterinary experts. As a result, the optimal mobile application was obtained for the needs of the people who live in that sector. In addition, it made it easier for the farms, as well as for the people who are in the frozen areas, so that they have better care and control of this species of animals, since the camelids are part of the fauna of the Andes and above all all its fiber and its derivatives are exported, which generates great economic sustenance for that sector.
COVID-19 classification using hybrid deep learning and standard feature extraction techniques
Authors: Shenbary Hassan Ahmed El , Ebeid Ebeid Ali , Baleanu Dumitru
Published: December 2022

There is no doubt that COVID-19 disease rapidly spread all over the world, and effected the daily lives of all of the people. Nowadays, the reverse transcription polymerase chain reaction is the most way used to detect COVID-19 infection. Due to time consumed in this method and material limitation in the hospitals, there is a need for developing a robust decision support system depending on artificial intelligence (AI) techniques to recognize the infection at an early stage from a medical images. The main contribution in this research is to develop a robust hybrid feature extraction method for recognizing the COVID-19 infection. Firstly, we train the Alexnet on the images database and extract the first feature matrix. Then we used discrete wavelet transform (DWT) and principal component analysis (PCA) to extract the second feature matrix from the same images. After that, the desired feature matrices were merged. Finally, support vector machine (SVM) was used to classify the images. Training, validating, and testing of the proposed method were performed. Experimental results gave (97.6%, 98.5%) average accuracy rate on both chest X-ray and computed tomography (CT) images databases. The proposed hybrid method outperform a lot of standard methods and deep learning neural networks like Alexnet, Googlenet and other related methods.
Adaptation issues of machine learning in safety digitization
Authors: Ranjana Panigrahi Gyana , Kanta Barpanda Nalini , Anitha Komma , Rathore Shanti , Biswas Preesat , Kumar Sethy Prabira
Published: December 2022

The internet community is the only set of irreplaceable spaces in today’s world and is used by millions for knowledge acquittance via the digital exchange between the landed gentry. The torrent of available e-contents in the Internet community attracts corporates and researchers to find the factual weightage of formed data. It is high time for digital diversification, which is the objective of using various learning-based machine learning (ML) systems for hands-on fortification. The main idea is to make stylistic communication more understandable. Here, the authors try to adapt the factual weightage procedure of formed data through the Internet community using machine learning schemes. Hence, the authors have chosen to emphasize cyber security, which is not well discussed and concerned with ethical contemplation from hackers' forums amidst internet communities. There are disparities in the continual growth of connotations, acronyms, spellings, and even technical jargon, which need periodic re-learning and their prototype implications through the proposed model.
A review of the genus Bifidocoelotes Wang, 2002, with the description of three new species from China (Araneae, Agelenidae)
Authors: LIAO RONGRONG , WANG ZIWEI , YIN HAIQIANG , XU XIANG
Published: December 2022

Three new species of the agelenid spider genus Bifidocoelotes Wang, 2002 are described from the mainland of China: Bifidocoelotes elongatus sp. nov. (♀; Guangxi, south China), B. mammiformis sp. nov. (♀, ♂; Guangdong, south China) and B. quadratus sp. nov. (♀; Guangxi, south China). The generic diagnosis is revised, and with the discovery of the three new species, the number of species in Bifidocoelotes doubles to six. Descriptions and illustrations of the three new species, a key to all the six species, and a distribution map for the genus are provided.
“We Want to Make our Customers Happy”: How Principals of Zoned Elementary Schools Navigate Inequity and Marketing Across Neighborhood Contexts
Authors: Schock Natalie , Cossyleon Jennifer E. , Nerenberg Kiara Millay
Published: December 2022

Despite rich and growing school choice and school marketing literatures, little is known about if and how principals of zoned public elementary schools engage in marketing. We address this gap by drawing on in-depth interviews with principals of nine schools—in different neighborhoods—in the Baltimore school district. We find that principals have internalized marketing as a key component of school leadership. Further, marketing strategies differ depending on school and community contexts (e.g., enrollment, neighborhood, and resources, and principals' perceptions thereof). Our study reveals how differences in neighborhood conditions and inequities in school resources affect marketing pressure, capacity, and actions. Our findings underscore a need to support urban principals as they navigate marketing pressures and also show how neglecting to do so may exacerbate inequity among students.
Young Men’s Health Matters: Implementing a Community-Academic Partnership in an Urban Federally Qualified Health Center
Authors: Burns Jade , Reeves Jaquetta , Adams Mackenzie , Darville-Sanders Gabrielle , Johnstone Keith A. , Ozuna-Harrison Rico , Johnson Kedar , Ware Derek , Shade George H. , Bradley Wayne W.
Published: December 2022

Community-based participatory research (CBPR) approaches are being leveraged more and more in efforts to improve health equity. Informing the building of community-academic partnerships, CBPR draws on the community’s expressed needs and engages stakeholders in future intervention development. To date, however, little has been published on such efforts targeting the health of young Black men (ages 18-24), despite this population’s disproportionate need. In this paper, we describe the formation of a community-academic partnership in a federally qualified health center, with the goal of improving the health of young Black men in Detroit, Michigan. After conducting a needs assessment, we built upon existing networks to form a Community Advisory Board (CAB). We held three community forums during which CAB members highlighted key health issues in their community and described how they could be addressed. We developed a plan for future research and community engagement based on community input. Finally, we provide insights on community engagement strategies, forum structure, setting boundaries, trust-building, and valuable information in addressing the inequities in health that affect young Black men.
Surgical management of severe mitral annular calcification
Authors: Elde Stefan , Zhu Yuanjia , MacArthur John W. , Woo Y. Joseph
Published: December 2022

Background

Surgical management of severe mitral annular calcification (MAC) presents a challenging problem for even the most experienced surgeons. Preoperative planning is the most effective strategy to mitigate risk in these scenarios. MAC alone should not disqualify a patient from consideration for mitral valve repair, although the presence of concurrent greater than moderate stenosis warrants consideration of mitral valve replacement.

Methods

While repair and replacement techniques for mitral regurgitation in the setting of MAC overlap with those used to repair a non-calcified mitral apparatus, there are unique considerations to the surgical conduct of these procedures. Specifically, this article describes techniques that may be employed when the severity of MAC precludes typical repair or replacement strategies.

Results

Between 2014 and 2021, 77 patients were operated on by a single surgeon for mitral valve disease complicated by severe MAC. Using the systematic approach described herein, 1-year mortality was 7.8% and overall mortality over a follow-up period extending 1 to 8 years was 9.1%.

Conclusions

Despite the inherent challenges of mitral valve repair or replacement in the setting of severe MAC, a systematic approach beginning with preoperative planning, modification of annular suture placement, and techniques to mitigate severe complications have, in our experience, resulting in a reliable methodology for managing severe MAC with excellent outcomes.