Search results for: the health improvement network (THIN)

Authors: Reza Pourjafar, Morteza Sohrabi-Gilani, Mostafa Jamshidi Avanaki, Malek Mohammad Ranjbar

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Cementitious composites like concrete, are the most widely used materials in civil infrastructures. Numerous investigations on fiber’s effect on the properties of cement-based composites have been conducted in the last few decades. The use of fibers such as carbon nanofibers (CNFs) and carbon nanotubes (CNTs) in these materials is an ongoing field and needs further researches and studies. Excellent mechanical, thermal, and electrical properties of carbon nanotubes and nanofibers have motivated the development of advanced nanocomposites with outstanding and multifunctional properties. In this study, the electrical resistance of CNF reinforced cement mortar was examined. Three different dosages of CNF were used, and the resistances were compared to plain cement mortar. One of the biggest challenges in this study is dispersing CNF particles in the mortar mixture. Therefore, polycarboxylate superplasticizer and ultrasonication of the mixture have been selected for the purpose of dispersing CNFs in the cement matrix. The obtained results indicated that the electrical resistance of the CNF reinforced mortar samples decreases with increasing CNF content, which would be the first step towards examining strain and damage monitoring ability of cementitious composites containing CNF for structural health monitoring purposes.

Keywords: carbon nanofiber, cement and concrete, CNF reinforced mortar, smart mater, strain monitoring, structural health monitoring

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Karina Santos Silvério, Fátima Carvalho, Maria Adelaide Almeida

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The impacts caused by anthropogenic actions on the water environment have been one of the main challenges of modern society. Population growth, added to water scarcity and climate change, points to a need to increase the resilience of production systems to increase efficiency regarding the management of wastewater generated in the different processes. Based on this context, the study developed under the NETA project (New Strategies in Wastewater Treatment) aimed to evaluate the efficiency of the Chemical Precipitation Process (CPP), using the hydrated lime (Ca(OH )₂) as a reagent in wastewater from the agroindustry sector, namely swine wastewater, slaughterhouse and urban wastewater, in order to make the productive means 100% circular, causing a direct positive impact on the environment. The purpose of CPP is to innovate in the field of effluent treatment technologies, as it allows rapid application and is economically profitable. In summary, the study was divided into four main stages: 1) Application of the reagent in a single step, raising the pH to 12.5 2) Obtaining sludge and treated effluent. 3) Natural neutralization of the effluent through Carbonation using atmospheric CO₂. 4) Characterization and evaluation of the feasibility of the chemical precipitation technique in the treatment of different wastewaters through the technique of determining the chemical oxygen demand (COD) and other supporting physical-chemical parameters. The results showed an approximate average removal efficiency above 80% for all effluents, highlighting the swine effluent with 90% removal, followed by urban effluent with 88% and slaughterhouse with 81% on average. Significant improvement was also obtained with regard to color and odor removal after Carbonation to pH 8.00.

Keywords: agroindustry wastewater, urban wastewater, natural carbonatation, chemical precipitation technique

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Authors: Adegoke A. Adeyelu, Adeola T. Adeyelu, S. D. Y. Alfred, O. O. Fasina

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This study examines the use of traditional medicines for the treatment of selected illnesses among crop-farming households in Edo State, Nigeria. A sample size of ninety (90) households were randomly selected for the study. Data were collected with a structured questionnaire alongside focus group discussions (FGD). Result shows that the mean age was 50 years old, the majority (76.7%) of the sampled farmers were below 60 years old. The majority (80.0%) of the farmers were married, about (92.2%) had formal education. It exposes that the majority of the respondents (76.7%) had household size of between 1-10 persons, about 55.6% had spent 11 years and above in crop farming. malaria (8th ), waist pains (7th ), farm injuries ( 6th ), cough (5th), acute headache(4th), skin infection (3rd), typhoid (2nd) and tuberculosis (1st ) were the most and least treated illness. Respondents (80%) had spent N10,000.00 ($27) and less on treatment of illnesses, 8.9% had spent N10,000.00-N20,000.0027 ($27-$55) 4.4% had spent between N20,100-N30,000.00 ($27-$83) while 6.7% had spent more than N30,100.00 ($83) on treatment of illnesses in the last one (1) year prior to the study. Age, years of farming, farm size, household size, level of income, cost of treatment, level of education, social network, and culture are some of the statistically significant factors influencing the utilization of traditional medicine. Farmers should be educated on methods of preventing illnesses, which is far cheaper than the curative.

Keywords: crop farming-households, selected illnesses, traditional medicines, Edo State

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Authors: Ghadeer Jalloul, Nour Hijazi, Cassia Boyadjian, Hussein Awala, Mohammad N. Ahmad, ‎Ahmad Albadarin

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In this study, we applied Fe-sensitized TiO₂ supported over embryonic Beta zeolite (BEA) zeolite ‎for the photocatalytic degradation of Tetracycline (TC) antibiotic under visible light. Four different ‎samples having 20, 40, 60, and 100% w/w as a ratio of TiO₂/BEA were prepared. The ‎immobilization of solgel TiO₂ (33 m²/g) over BEA (390 m²/g) increased its surface area to (227 ‎m²/g) and enhanced its adsorption capacity from 8% to 19%. To expand the activity of TiO₂ ‎photocatalyst towards the visible light region (λ>380 nm), we explored two different metal ‎sensitization techniques with Iron ions (Fe³⁺). In the ion-exchange method, the substitutional cations ‎in the zeolite in TiO₂/BEA were exchanged with (Fe³⁺) in an aqueous solution of FeCl₃. In the ‎doping technique, solgel TiO₂ was doped with (Fe³⁺) from FeCl₃ precursor during its synthesis and ‎before its immobilization over BEA. (Fe-TiO₂/BEA) catalysts were characterized using SEM, XRD, ‎BET, UV-VIS DRS, and FTIR. After testing the performance of the various ion-exchanged catalysts ‎under blue and white lights, only (Fe-TiO₂/BEA 60%) showed better activity as compared to pure ‎TiO₂ under white light with 100 ppm initial catalyst concentration and 20 ppm TC concentration. As ‎compared to ion-exchanged (Fe-TiO₂/BEA), doped (Fe-TiO₂/BEA) resulted in higher photocatalytic ‎efficiencies under blue and white lights. The 3%-Fe-doped TiO₂/BEA removed 92% of TC ‎compared to 54% by TiO₂ under white light. The catalysts were also tested under real solar ‎irradiations. This improvement in the photocatalytic performance of TiO₂ was due to its higher ‎adsorption capacity due to BEA support combined with the presence of Iron ions that enhance the ‎visible light absorption and minimize the recombination effect by the charge carriers. ‎

Keywords: Tetracycline, photocatalytic degradation, immobilized TiO₂, zeolite, iron-doped TiO₂, ion-exchange

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Authors: Kathie Records, R. Jeanne Ruiz, Kimberly Ayers, Rebecca Pasillas

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Background: Preterm births of less than 37 weeks gestation occur disproportionately to Hispanics living along the U.S.-Mexico border. Prematurity has devastating and costly effects on children, families and the health care system. Few preventive interventions have been tested for this vulnerable group. Objectives: To present the modeling and pilot testing of the theory-based Mastery Lifestyle Intervention (MLI), designed to reduce and prevent PTB among Mexican American women (the terms Hispanics or Latinas will also be used to represent this group) living in the United States. Design and Methods: The conceptualization of the problem of preterm births and the available literature underpinning the mastery lifestyle intervention will be reviewed. The lifestyle intervention includes foundational components of problem solving therapy and acceptance and commitment therapy. Findings from implementation of a one-group pilot test and focus group evaluated the feasibility and acceptability of the MLI. Summary: Participants found the MLI to be feasible and acceptable, and reported perceiving improved health status and familial relationships. Suggestions were provided for modifications prior to efficacy testing. The MLI appears to be a theoretically and empirically grounded intervention that holds promise for preventing preterm births among Latinas.

Keywords: birth, Hispanic, intervention, stress

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Authors: Iddrisu Ibrahim, Joseph Atia Ayariga, Junhuan Xu, Daniel A. Abugri, Robertson K. Boakai, Olufemi S. Ajayi

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The recalcitrance of pathogenic bacteria indicates that millions of people who are at risk of infection arising from chronic diseases, surgery, organ transplant, diabetes, and several other debilitating diseases present an aura of potentially untreatable illness due to resistance development. Antimicrobial resistance has successfully become a global health menace, and resistances are often acquired by bacteria through health-care-related incidence (HRI) orchestrated by multi-drug resistant (MDR) and extended drug-resistant pathogens (EDRP). To understand the mechanisms S. Typhimurium uses to resist CDB, we study the abundance of LPS modification, Ergosterols, Mysristic palmitic resistance, Oleic acid resistance of susceptible and resistant S. Typhimurium. Using qPCR, we also analyzed the expression of selected genes known for enabling resistance in S. Typhimurium. We found high abundance of LPS, Ergosterols, Mysristic palmitic resistance, Oleic acid resistance of and high expression of resistant genes in S. Typhimurium compared to the susceptible strain. LPS modification, Ergosterols, Mysristic palmitic resistance, Oleic acid and genes such as Fims, integrons, blaTEM are important indicators of resistance development of S. typhimurium.

Keywords: antimicrobials, resistance, Cannabidiol, Salmonella, blaTEM, fimA, Lipopolysaccharide, Ergosterols

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Abdelkader T. Ahmed

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Greywater is any wastewater draining from a household including kitchen sinks and bathroom tubs, except toilet wastes. Although this used water may contain grease, food particles, hair, and any number of other impurities, it may still be suitable for reuse after treatment. Greywater reusing serves two purposes including reduction the amount of freshwater needed to supply a household, and reduction the amount of wastewater entering sewer systems. This study aims to investigate and design a simple and cheap unit to treat the greywater in household via using ceramic membranes and reuse it in supplying water for toilet flushing. The study include an experimental program for manufacturing several tablet ceramic membranes from clay and sawdust with three different mixtures. The productivity and efficiency of these ceramic membranes were investigated by chemical and physical tests for greywater before and after filtration through these membranes. Then a treatment unit from this ceramic membrane was designed based on the experimental results of lab tests. Results showed that increase sawdust percent with the mixture increase the flow rate and productivity of treated water but decrease in the same time the water quality. The efficiency of the new ceramic membrane reached 95%. The treatment unit save 0.3 m3/day water for toilet flushing without need to consume them from the fresh water supply network.

Keywords: ceramic membranes, filtration, greywater, wastewater treatment

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Authors: Imran Altaf Wasil, Dinesh Ganvir

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Due to a scarcity of virgin aggregates, the use of reclaimed asphalt pavement (RAP) as a substitute for natural aggregates has gained popularity. Despite the fact that RAP is recycled in asphalt pavement, there is still excess RAP, and its use in concrete pavements has expanded in recent years. According to a survey, 98 percent of India's pavements are flexible. As a result, the maintenance and reconstruction of such pavements generate RAP, which can be reused in concrete pavements as well as surface course, base course, and sub-base of flexible pavements. Various studies on the properties of reclaimed asphalt pavement and its optimal requirements for usage in concrete has been conducted throughout the years. In this study a total of four different mixes were prepared by partially replacing natural aggregates by RAP in different proportions. It was found that with the increase in the replacement level of Natural aggregates by RAP the mechanical and durability properties got reduced. In order to increase the mechanical strength of mixes 40% Glass Granulated Blast Furnace Slag (GGBS) was used and it was found that with replacement of cement by 40% of GGBS, there was an enhancement in the mechanical and durability properties of RAP inclusive PQC mixes. The reason behind the improvement in the properties is due to the processing technique used in order to remove the contaminant layers present in the coarse RAP aggregates. The replacement level of Natural aggregate with RAP was done in proportions of 20%, 40% and 60% along with the partial replacement of cement by 40% GGBS. It was found that all the mixes surpassed the design target value of 40 MPa in compression and 4.5 MPa in flexure making it much more economical and feasible.

Keywords: reclaimed asphalt pavement, pavement quality concrete, glass granulated blast furnace slag, mechanical and durability properties

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Authors: Jameson Mirimu, Edward Mawejje, Ibra Twinomujuni

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Introduction: Adolescent girls and young women (AGYW) are a vulnerable category whose risk of acquiring HIV is 20 times compared to the general population accounting for 25% of the new infections. Despite proven scientific evidence of preventing HIV acquisition, Oral Pre-Exposure Prophylaxis (PreP) is less used as one of the biomedical interventions among the AGYW. By 2020, only 31000-32000 of the targeted 90,000 persons in Uganda enrolled on Oral PreP LPHS-EC project employed a combination of Expanded Peer Outreach Approach (EPOA) and Effective client follow-up to increase PreP initiation (PrEP_NEW) and continuation for more than three months (PrEP_CT). Method: Quantitatively, data from National Key population Combination tracker retrospectively analyzed by M&E, focused group discussion with AGYWs and Health care workers to identify barriers. Barriers found; hesitancy of AGYW, misconceptions about Oral PrEP, inadequate knowledge and skills in handling adolescent and Data quality issues. To address the mentioned barriers, youth friendly corners initiated in study sites, identified PrEP Champions among the AGYW, oral PrEP dialogues, group Antenatal counselling, CQI Projects initiated, weekly perfomance meetings to track performance. Results: Routine program data review PrEP_NEW and PrEP_CT increased from 5% (4/80) and 4% (2/54), respectively, in July 2022 to 90% (72/80) and 79% (43/54) respectively for PrEP_NEW and PrEP_CT at the end of March 2023. Lessons Learnt: Demystifying misconception about oral Prep through provision of adequate information by involving health care workers through skills enhancement, CQI projects are critical intervention. Conclusion: With improved safe spaces, skills enhancement of health workers, stakeholders’ engagement through Oral Prep dialogues is critical in improving PreP uptake and continuity among the AGYWS.

Keywords: prep, uptake, continuation, AGYW

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Authors: S. Farid F. Mojtahedi, Ali Khosravi, Behnaz Naeimian, S. Adel A. Hosseini

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Land subsidence is a gradual settling or sudden sinking of the land surface from changes that take place underground. There are different causes of land subsidence; most notably, ground-water overdraft and severe weather conditions. Subsidence of the land surface due to ground water overdraft is caused by an increase in the intergranular pressure in unconsolidated aquifers, which results in a loss of buoyancy of solid particles in the zone dewatered by the falling water table and accordingly compaction of the aquifer. On the other hand, exploitation of underground water may result in significant changes in degree of saturation of soil layers above the water table, increasing the effective stress in these layers, and considerable soil settlements. This study focuses on estimation of soil moisture at surface using different methods. Specifically, different methods for the estimation of moisture content at the soil surface, as an important term to solve Richard’s equation and estimate soil moisture profile are presented, and their results are discussed through comparison with field measurements obtained from Yanco1 station in south-eastern Australia. Surface soil moisture is not easy to measure at the spatial scale of a catchment. Due to the heterogeneity of soil type, land use, and topography, surface soil moisture may change considerably in space and time.

Keywords: artificial neural network, empirical method, remote sensing, surface soil moisture, unsaturated soil

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of machine learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. With the application of learning methods in such diverse domains, artificial intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been on developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and three defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt machine learning techniques in security-critical areas such as the nuclear industry without rigorous testing since they may be vulnerable to adversarial attacks. While common defence methods can effectively defend against different attacks, none of the three considered can provide protection against all five adversarial attacks analysed.

Keywords: adversarial machine learning, attacks, defences, nuclear industry, crack detection

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Authors: Mayowa A. Sofowora, Seraphin D. Eyono Obono

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The use of information and communication technologies such as computers, mobile phones and the internet is becoming prevalent in today’s world; and it is facilitating access to a vast amount of data, services, and applications for the improvement of people’s lives. However, this prevalence of ICTs is hampered by the problem of low income levels in developing countries to the point where people cannot timeously replace or repair their ICT devices when damaged or lost; and this problem serves as a motivation for this study whose aim is to examine the perceptions of teachers on the reliability of cellphones when used for teaching and learning purposes. The research objectives unfolding this aim are of two types: objectives on the selection and design of theories and models, and objectives on the empirical testing of these theories and models. The first type of objectives is achieved using content analysis in an extensive literature survey, and the second type of objectives is achieved through a survey of high school teachers from the ILembe and Umgungudlovu districts in the KwaZuluNatal province of South Africa. Data collected from this questionnaire based survey is analysed in SPSS using descriptive statistics and Pearson correlations after checking the reliability and validity of the questionnaire. The main hypothesis driving this study is that there is a relationship between the demographics and the attribution identity of teachers on one hand, and their perceptions on the reliability of cellphones on the other hand, as suggested by existing literature; except that attribution identities are considered in this study under three angles: intention, knowledge and ability, and action. The results of this study confirm that the perceptions of teachers on the reliability of cellphones for teaching and learning are affected by the school location of these teachers, and by their perceptions on learners’ cellphones usage intentions and actual use.

Keywords: attribution, cellphones, e-learning, reliability

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Authors: Yu-Wei Chu, Marie Aja-Herrera, Denis Antoine, Mengjie Di

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The purpose of this paper is to explore the innovative perspective of the local traditional culture of garments from different continents. The relationship between the local culture, the indigenous traditional technique of textile manufacture, and modern womenswear will be investigated. This will include exploring and discussing traditional techniques to create textiles reflecting different cultures and relevant handicrafts, including the history of these different peoples and regions. However, along with the improvement of technology, the diversity of culture is usually unified into a single aesthetic element, which makes fashion lack traditional cultural layers. Local cultural awareness has been gradually emerging in womenswear in recent years with the strong sweep of globalization. The possible loss of traditional art and crafts became an awareness for different cultures, who realized the necessity to protect and preserve their individual uniqueness. Modern womenswear is one of the largest markets in the fashion and apparel marketplace. Therefore, the commonalities of traditional textiles and garments for modern womenswear will be researched. Localized traditional fabrics have some elements, such as weaving techniques and other related crafts, in common with more modern manufacturing methods. In addition, the common point of traditional clothing is the use of draping, construction, and fabric manipulation. This paper aims to explore these factors, as discussed above, and also apply, in an innovative and creative manner, some of these traditional arts and crafts to modern womenswear. The combination of textile manipulation and different construction techniques can support the development of innovative womenswear to include a diversity of aesthetics. The main contribution of the paper is to find out the solution to bring local culture into the formal womenswear market with modern aesthetics to realize the ideal of traditional culture reconstruction.

Keywords: traditional culture, modern womenswear, diversity, aesthetics

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Authors: Imen Abid, Rachel Calvet, Michel Baltas

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Flavonoids are secondary metabolites that belong to a polyphenolic class, present in fruits and vegetables, playing a significant role in biological systems. The structural variations of these flavonoids are associated with many biological and pharmacological activities (antioxidant, anti-inflammatory, anticancer, antibacterial, antifungal, antiviral, and antimalarial). Given their importance in plants and health-promoting roles in humans, significant efforts have been devoted towards their isolation of flavonoids and chemical elaboration (organic synthesis). But with the increasing public concern over environmental degradation and future resources, it is of great importance for chemists to come up with different approaches, less hazardous to human health and the environment. Being employed in large amounts, the solvents used in organic synthesis are high on the list of environmental pollutants. To overcome these problems, our approach is to develop unconventional processes involving solvent-free conditions. The application of mechanical forces to solvent-free or solvent-less reaction mixtures through the use of ball mills offers many advantages over traditional solvent-based strategies. It is one of the unconventional activation methods, which makes it possible to overcome the use of solvents, in the context of green chemistry and more respectful of the environment.

Keywords: organic synthesis, green chemistry, mecanochemistry, pharmaceutical molecules

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Authors: Ivelise M. Strozberg, Juliana Sales Frota, Lucas de Oliveira Vale

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The state of Ceara, located in the northeast region of Brazil, is abundant in lateritic soil which has been usually discarded due to its lack of agricultural potential while materials of similar nature have been used as constituents of housing constructive elements in many parts of the world, such as India and Portugal, for decades. Since many of the semi-arid housing conditions in the state of Ceara fail to meet the minimum criteria regarding comfort and safety requirements, this research proposed to study the Ceara lateritic soil and the possibility of its use as a sustainable building block constituent for social housings, collaborating to the improvement of the region living conditions. In order to achieve this objective, soil samples were collected from five different locations within the specific region, three of which presented lateritic nature, being characterized according to the Unified Soil Classification System and the MCT methodology, which is a Brazilian methodology developed during the 80’s that aimed to better describe and approach tropical soils, its characterization and behavior. Two of these samples were used to build two different miniature block prototypes, which were manually molded, heated at low temperatures -( < 300 ºC) in order to save energy and lessen the CO₂ high emission rate common in traditional burning methods- and then submitted to load tests. Among the soils tested, the one with the highest degree of laterization and greater presence of fines constituted the block with the best performance in terms of flexural strength tensions, presenting resistance gains when heated at increasing temperatures, which can indicate that this type of soil has potential towards being used as constructing material.

Keywords: constructive blocks, lateritic soil, MCT methodology, sustainability

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Authors: Laura Mion

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The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of QA (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom

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Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

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Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: Wong Ka Fai

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Introduction: Many students are worried before an examination; that is a common picture worldwide. Health problems from stress before examination were insomnia, tiredness, isolation, stomach upset, and anxiety. Nursing students experienced high stress from the examination. Guided imagery is a healing process of applying imagination to help the body heal, survive, or live well. It can bring about significant physiological and biochemical changes, which can trigger the recovery process. A study of nursing students improving their anxiety before examination with guided imagery was proposed. Aim: The aim of this study was to explore the outcome of guided imagery on nursing students’ anxiety before examination in Hong Kong. Method: The qualitative study method was used. 16 first-year students studying nursing programme were invited to practice guided imagery to improve their anxiety before the examination period. One week before the examination, the semi-structured interviews with these students were carried out by the researcher. Result: From the content analysis of interview data, these nursing students showed considerable similarities in their anxiety perception. Nursing students’ perceived improved anxiety was evidenced by a reduction of stressful feelings, improved physical health, satisfaction with daily activities, and enhanced skills for solving problems and upcoming situations. Conclusion: This study indicated that guided imagery can be used as an alternative measure to improve students’ anxiety and psychological problems.

Keywords: nursing students, perception, anxiety, guided imagery

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Authors: Hanqing Yang, Xiang Meng, Qi Li, Weirong Chen

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The SOC (state of charge) based droop control has limitations on the load power sharing among different energy storage units, due to the line impedance. In this paper, a distributed control strategy for dispersed energy storage units in the DC microgrid based on discrete consensus is proposed. Firstly, a sparse information communication network is built. Thus, local controllers can communicate with its neighbors using voltage, current and SOC information. An average voltage of grid can be evaluated to compensate voltage offset by droop control, and an objective virtual resistance fulfilling above requirement can be dynamically calculated to distribute load power according to the SOC of the energy storage units. Then, the stability of the whole system and influence of communication delay are analyzed. It can be concluded that this control strategy can improve the robustness and flexibility, because of having no center controller. Finally, a model of DC microgrid with dispersed energy storage units and loads is built, the discrete distributed algorithm is established and communication protocol is developed. The co-simulation between Matlab/Simulink and JADE (Java agent development framework) has verified the effectiveness of proposed control strategy.

Keywords: dispersed energy storage units, discrete consensus algorithm, state of charge, communication delay

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Authors: Bethany Wood

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The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.

Keywords: journalism, generation z, digital, social media

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Authors: Amy Claridge, Tishra Beeson

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Background: Maternal depression is a serious health concern impacting between 10-16% of birthing persons. It is associated with difficulty in emotional interaction and the formation of attachment bonds between parent and infant. Longitudinally, maternal depression can have severe, lasting impacts on both parent and child, increasing the risk for mental, social, and physical health issues. Rates of prenatal depression have been higher among individuals who were pregnant during the first year of the COVID-19 pandemic. Pregnant persons are considered a high-risk group for poor clinical outcomes from COVID-19 infection and may also have faced or continue to face additional stressors such as financial burdens, loss of income or employment, and the benefits accompanying employment, especially among those in the United States (U.S.). It is less clear whether individuals who gave birth during the pandemic continue to experience high levels of depressive symptoms or whether symptoms have been reduced as a pandemic response has shifted. The current study examined longitudinal reports of depressive symptoms among individuals in the U.S. who gave birth between March 2020 and September 2021. Methods: This mixed-method study involved surveys and interviews with birthing persons (18-45 years old) in their third trimester of pregnancy and at 8 weeks postpartum. Participants also completed a follow-up survey at 12-18 months postpartum. Participants were recruited using convenience methods via an online survey. Survey participants included 242 U.S. women who self-reported depressive symptoms (10-item Edinburgh Postnatal Depression Scale) at each data collection wave. A subset of 23 women participated in semi-structured prenatal and 8-week postpartum qualitative interviews. Follow-up interviews are currently underway and will be integrated into the presentation. Preliminary Results: Prenatal depressive symptoms were significantly positively correlated to 8-week and 12-18-month postpartum depressive symptoms. Participants who reported clinical levels of depression prenatally were 3.29 times (SE = .32, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Those who reported clinical depression at 8-weeks postpartum were 6.52 times (SE = .41, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Participants who gave birth earlier in the pandemic reported significantly higher prenatal (t(103) = 2.84, p < .01) and 8-week postpartum depressive symptoms (t(126) = 3.31, p < .001). Data from qualitative interviews contextualize the findings. Participants reported negative emotions during pregnancy, including sadness, grief, and anxiety. They attributed this in part to their experiences of pregnancy during the pandemic and uncertainty related to the birth experience and postpartum period. Postpartum interviews revealed some stressors specific to childbirth during the COVID-19 pandemic; however, most women reflected on positive experiences of birth and postpartum. Conclusions: Taken together, findings reveal a pattern of persistent depressive symptoms among U.S. parents who gave birth during the pandemic. Depressive symptoms are of significant concern for the health of parents and children, and the findings of this study suggest a need for continued mental health intervention for parents who gave birth during the pandemic. Policy and practice implications will be discussed.

Keywords: maternal mental health, perinatal depression, postpartum depression, covid-19 pandemic

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Authors: Victor Abu

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Background: Social justice ideals are considered as the foundation of nursing practice. These ideals are not always clearly integrated into nursing professional standards or curricula. This hinders concerted global nursing agendas for becoming aware of social injustice or engaging in action for social justice to improve the health of individuals and groups. Aim and objectives: The aim was to create an educational framework for empowering nursing students for social justice awareness and action. This purpose was attained by understanding the meaning of social justice, the effect of social injustice, the visibility of social justice learning, and ways of integrating social justice in nursing education and practice. Methods: Critical interpretive methodologies and constructivist grounded theory research designs guided the processes of recruiting nursing students (n = 11) and nurse educators (n = 11) at a London nursing university to participate in interviews and focus groups, which were analysed by coding systems. Findings: Firstly, social justice was described as ethical practices that enable individuals and groups to have good access to health resources. Secondly, social injustice was understood as unfair practices that caused minimal access to resources, social deprivation, and poor health. Thirdly, social justice learning was considered to be invisible in nursing education due to a lack of explicit modules, educator knowledge, and organisational support. Lastly, explicit modules, educating educators, and attracting leaders’ support were suggested as approaches for the visible integration of social justice in nursing education and practice. Discussion: This research proposes approaches for nursing awareness and action for the development of critical active nurse-learner, critical conscious nurse-educator, and servant nurse leader. The framework on Awareness for Social Justice Action (ASJA) created in this research is an approach for empowering nursing students for social justice practices. Conclusion: This research contributes to and advocates for greater nursing scholarship to raise the spotlight on social justice in the profession.

Keywords: social justice, nursing practice, nursing education, nursing curriculum, social justice awareness, social justice action, constructivist grounded theory

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Authors: Ebrahim Izadi-Darbandi

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In order to investigation the effects of sowing methods, nitrogen and phosphorus application methods in wheat weeds management, an experiment was performed as split plot, based on randomized completely block design with three replications at Research Farm, Faculty of Agriculture, Ferdowsi University of Mashhad, in 2010. Treatments included, wheat sowing methods (single-row with 30 cm distance and twine row on 50 cm width ridges) as main plots and nitrogen and phosphorus application methods (Broadcast and Band) as sub plots. In this experiment, phosphorus and nitrogen sources for fertilization were super phosphate triple (150 kg ha-1) applied before wheat sowing and incorporated with soil and urea (200 kg ha-1) respectively, applied in 2 phases (pre-plant 50%) and near wheat shooting (50%). Results showed that the effect of fertilizers application methods and wheat sowing methods were significant (p≤0.01) on wheat yield increasing and reducing weed-wheat competition. Wheat twine row sowing method, reduced weeds biomass for 25% compared wheat single-row sowing method and increased wheat seed yield and biomass for 60% and 30% respectively. Phosphorus and nitrogen band application reduced weeds biomass for 46% and 53% respectively and increased wheat seed yield for 22% and 33% compared to their broadcast application. The effects of wheat sowing method plus phosphorus and nitrogen application methods interactions, showed that the fertilizers band application and wheat twine-row sowing method were the best methods in wheat yield improvement and reducing wheat-weeds interaction. These results shows that modifying of fertilization methods and wheat sowing method can have important role in fertilizers use efficiency and improving of weeds managements.

Keywords: competition, wheat yield, fertilizer management, biomass

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Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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