Search results for: predicting factors

Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

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Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

Procedia PDF Downloads 189

Authors: Simon J. Wilde, David M. Herold, Michael J. Bryant

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Social media networks have become the hotbed for advertising activities, due mainly to their increasing consumer/user base, and secondly, owing to the ability of marketers to accurately measure ad exposure and consumer-based insights on such networks. More than half of the world’s population (4.8 billion) now uses social media (60%), with 150 million new users having come online within the last 12 months (to June 2022). As the use of social media networks by users grows, key business strategies used for interacting with these potential customers have matured, especially social media advertising. Unlike other traditional media outlets, social media advertising is highly interactive and digital channel-specific. Social media advertisements are clearly targetable, providing marketers with an extremely powerful marketing tool. Yet despite the measurable benefits afforded to businesses engaged in social media advertising, recent controversies (such as the relationship between Facebook and Cambridge Analytica in 2018) have only heightened the role trust and privacy play within these social media networks. The purpose of this exploratory paper is to investigate the extent to which social media users trust social media advertising. Understanding this relationship will fundamentally assist marketers in better understanding social media interactions and their implications for society. Using a web-based quantitative survey instrument, survey participants were recruited via a reputable online panel survey site. Respondents to the survey represented social media users from all states and territories within Australia. Completed responses were received from a total of 258 social media users. Survey respondents represented all core age demographic groupings, including Gen Z/Millennials (18-45 years = 60.5% of respondents) and Gen X/Boomers (46-66+ years = 39.5% of respondents). An adapted ADTRUST scale, using a 20 item 7-point Likert scale, measured trust in social media advertising. The ADTRUST scale has been shown to be a valid measure of trust in advertising within traditional different media, such as broadcast media and print media, and more recently, the Internet (as a broader platform). The adapted scale was validated through exploratory factor analysis (EFA), resulting in a three-factor solution. These three factors were named reliability, usefulness and affect, and the willingness to rely on. Factor scores (weighted measures) were then calculated for these factors. Factor scores are estimates of the scores survey participants would have received on each of the factors had they been measured directly, with the following results recorded (Reliability = 4.68/7; Usefulness and Affect = 4.53/7; and Willingness to Rely On = 3.94/7). Further statistical analysis (independent samples t-test) determined the difference in factor scores between the factors when age (Gen Z/Millennials vs. Gen X/Boomers) was utilised as the independent, categorical variable. The results showed the difference in mean scores across all three factors to be statistically significant (p<0.05) for these two core age groupings: Gen Z/Millennials Reliability = 4.90/7 vs Gen X/Boomers Reliability = 4.34/7; Gen Z/Millennials Usefulness and Affect = 4.85/7 vs Gen X/Boomers Usefulness and Affect = 4.05/7; and Gen Z/Millennials Willingness to Rely On = 4.53/7 vs Gen X/Boomers Willingness to Rely On = 3.03/7. The results clearly indicate that older social media users lack trust in the quality of information conveyed in social media ads, when compared to younger, more social media-savvy consumers. This is especially evident with respect to Factor 3 (Willingness to Rely On), whose underlying variables reflect one’s behavioural intent to act based on the information conveyed in advertising. These findings can be useful to marketers, advertisers, and brand managers in that the results highlight a critical need to design ‘authentic’ advertisements on social media sites to better connect with these older users, in an attempt to foster positive behavioural responses from within this large demographic group – whose engagement with social media sites continues to increase year on year.

Keywords: social media advertising, trust, older consumers, online

Procedia PDF Downloads 81

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 127

Authors: A. Reum Son, Jin Seon Kwon, Seung Hun Park, Hai Bang Lee, Moon Suk Kim

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These days, stem cell therapy is focused on for promising source of treatment in clinical human disease. As a supporter of stem cells, in situ-forming hydrogels with growth factors and cells appear to be a promising approach in tissue engineering. To examine osteogenic differentiation of hTMSCs which is one of mesenchymal stem cells in vivo in an injectable hydrogel, we use a methoxy polyethylene glycol-polycaprolactone blockcopolymer (MPEG-PCL) solution with osteogenic factors. We synthesized MPEG-PCL hydrogel and measured viscosity to check sol-gel transition. In order to demonstrate osteogenic ability of hTMSCs, we conducted in vitro osteogenesis experiment. Then, to confirm the cell cytotoxicity, we performed WST-1 with hTMSCs and MPEG-PCL. As the result of in vitro experiment, we implanted cell and hydrogel mixture into animal model and checked degree of osteogenesis with histological analysis and amount of expression genes. Through these experimental data, MPEG-PCL hydrogel has sol-gel transition in temperature change and is biocompatible with stem cells. In histological analysis and gene expression, hTMSCs are very good source of osteogenesis with hydrogel and will use it to tissue engineering as important treatment method. hTMSCs could be a good adult stem cell source for usability of isolation and high proliferation. When hTMSCs are used as cell therapy method with in situ-formed hydrogel, they may provide various benefits like a noninvasive alternative for bone tissue engineering applications.

Keywords: injectable hydrogel, stem cell, osteogenic differentiation, tissue engineering

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Authors: Julide Yildirim, Nadir Ocal

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Even though there are many studies investigating the extent and determinants of poverty, there is paucity of research investigating the issue of energy poverty in Turkey. The aim of this paper is threefold: First to investigate the extend of energy poverty in Turkey by using Household Budget Survey datasets belonging to 2005 - 2016 period. Second, to examine the risk factors for energy poverty. Finally, to assess the impact of social assistance program participation on energy poverty. Existing literature employs alternative methods to measure energy poverty. In this study energy poverty is measured by employing expenditure approach, where people are considered as energy poor if they disburse more than 10 per cent of their income to meet their energy requirements. Empirical results indicate that energy poverty rate is around 20 per cent during the time period under consideration. Since Household Budget Survey panel data is not available for 2005 - 2016 period, a pseudo panel has been constructed. Panel logistic regression method is utilized to determine the risk factors for energy poverty. The empirical results demonstrate that there is a statistically significant impact of work status and education level on energy poverty likelihood. In the final part of the paper the impact of social transfers on energy poverty has been examined by utilizing panel biprobit model, where social transfer participation and energy poverty incidences are jointly modeled. The empirical findings indicate that social transfer program participation reduces energy poverty. The negative association between energy poverty and social transfer program participation is more pronounced in urban areas compared with the rural areas.

Keywords: energy poverty, social transfers, panel data models, Turkey

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Samar Mohamed Magdy Abdelrahim

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This study is an attempt to investigate the phenomenon of code-switching that takes place between Arabic and English in social discourse among high, well-educated, and young people in Egypt. The study aims at digging deeper to extract the trigger factors of such occurrences, namely when people encounter embarrassing situations in their daily conversations. Nowadays, most young Egyptians tend to use English words in certain situations that might make them feel embarrassed. To disguise their feelings and soften the impact of these words in the context, they code-switch (CS) from Arabic into English. To obtain accurate results, the study utilized a quantitative analysis approach that combines personal observations and a questionnaire to examine the phenomenon appropriately. The questionnaire was designed to categorize different types of embarrassing topics to be evaluated by participants. These topics include certain parts of the human body, types of clothes, taboo words, and specific medical conditions. Many studies have examined the use of CS as a prestigious way of communicating and expressing solidarity between Arabic and English. Other studies have dealt with switches that take place in classrooms. However, not many studies have paid attention to this angle of CS, especially in Egypt. The results conclude that gender and the circumstances that surround the conversation are essential factors of CS since females tend to switch codes more than males in embarrassing situations. According to the study, CS serves the socio-pragmatic function in terms of helping young, well-educated bilinguals express themselves in a second language that would be distressing in the first.

Keywords: code-switching, embarrassment, Arabic, English

Procedia PDF Downloads 97

Authors: Yan Zi, Han Xiao

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Across the globe, ICTs are influencing employment both as an industry that creates jobs and as a tool that empowers disabled people to access new forms of work, in innovative and more flexible ways. The advancements in ICT and the number of apps and solutions that support persons with physical, cognitive and intellectual disabilities challenge traditional biased notions and offer a pathway out of traditional sheltered workshops. As the global leader in digital technology innovation, China is arguably a leader in the use of digital technology as a 'lever' in ending the economic and social marginalization of the disabled. This study investigates factors that influence adoption and use of employment-oriented ICT applications among disabled people in China and seeks to integrate three theoretical approaches: the technology acceptance model (TAM), the uses and gratifications (U&G) approach, and the social model of disability. To that end, the study used data from self-reported survey of 214 disabled adults who have been involved in two top-down 'Internet + employment' programs promoted by local disabled persons’ federation in Shanghai. A structural equation model employed in the study demonstrates that the use of employment-oriented ICT applications is affected by demographic factors of gender, categories of disability, education and marital status. The organizational support of local social organizations demonstrates significate effects on the motivations of disabled people. Results from the focus group interviews particularly suggested that to maximize the positive impact of ICTs on employment, there is significant need to build stakeholder capacity on how ICTs could benefits persons with disabilities.

Keywords: disabled people, ICTs, technology acceptance model, uses and gratifications, the social model of disability

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Authors: Broccolo Cinzia, Grigaliunaite Ruta, Saint-Nom Cloé, Savasta Guido

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The present article analyses the root causes of under-reporting and under-recording of hate crimes against Muslim women in Italy. The main findings emerged from the survey conducted between May and September 2022 within the framework of the TRUST project (co-funded by the CERV programme (CERV-2021-EQUAL) of the European Union) with relevant practitioners and members of the Muslim community, including first-generation and second-generation Muslim women residing in Italy. The findings reveal that multiple factors contribute to the low reporting rate as well as to the flaws in recording episodes of intolerance and hatred against the above-mentioned group. Lack of trust in the judiciary or the police may represent one of the main causes of under-reporting; however, the phenomenon is not limited to such aspects, and additional factors and sources of discrimination paving the way to under-recording have been identified during the survey. The significant “tendency” to not report a case of intolerance as the difficulties in identifying the discriminatory nature of the crime are two faces of the same coin and are particularly intertwined; despite this, at first, both issues need to be assessed and analysed separately in order to take their own specificities into duly consideration. By contrast, the potential solution to low recording and reporting trends should be found collectively, namely by involving all the relevant parties and bodies facing the above-mentioned issues. In this regard, a participatory and multi-agency approach may curb the root causes leading Muslim women not to report and, besides this, support law enforcement officials as well as public authorities in providing a more effective service to the victims of hatred, whether offline or online.

Keywords: hate crime, under-reporting, under-recording, Islamophobia, Muslim women

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Authors: Yusser Olguín, Diego Benavente, Fernando Dorta, Nicole Orellana, Cristian Acevedo

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One of the greatest challenges of tissue engineering is the generation of materials in which the highest possible number of conditions can be incorporated to stimulate the proliferation and differentiation of cells, which will be transformed together with the material into new functional tissue. In this sense, considering the properties of microfluidics and its relationship with cellular micro-environments, the possibility of controlling flow patterns and the ability to design diverse patterns in the chips, a microfluidic cell culture system can be established as a means for the evaluation of the effect of different parameters in a controlled and precise manner. Specifically in relation to the study and development of alternatives in peripheral nervous tissue engineering, it is necessary to consider different physical and chemical neurotrophic stimuli that promote cell growth and differentiation. Chemical stimuli include certain vitamins, glucocorticoids, gangliosides, and growth factors, while physical stimuli include topological stimuli, mechanical forces of the cellular environment and electrical stimulation. In this context, the present investigation shows the results of cell stimulation in a microbioreactor using electrical and chemical stimuli, where the differentiation of PC12 cells as a neuronal model is evidenced by neurite expression, dependent on the stimuli and their combination. The results were analysed with a multi-factor statistical approach, showing several relationships and dependencies between different parameters. Chip design, operating parameters and concentrations of neurotrophic chemical factors were found to be preponderant, based on the characteristics of the electrical stimuli.

Keywords: microfluidics, nerve tissue engineering, microbioreactor, electrical stimuli

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Authors: John Allbutt, Andrew Murray, Jonathan Ling, Thomas M. Heffernan

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Ultra-endurance events place unique physical and psychological pressures on participants. In this study, we examined the psychologically challenging aspects of taking part in a 3000 mile transatlantic rowing race using a qualitative approach. To date, more people have been into space than have rowed an ocean and only one psychological study has been conducted on this experience which had a specific research focus. The current study was a qualitative study using semi-structured interviews. Participants were an opportunity sample of seven competitors from a recent ocean rowing race. Participants were asked about the psychological aspects of the event after it had finished. The data were analysed using thematic analysis. Several themes emerged from the analysis. These related to: 1) preparation; 2) bodily aches/pains, 3) race setbacks; 4) boat conditions; 5) interpersonal factors and communication; 6) strategies for managing stress and interpersonal tensions. While participants were generally very positive about the event, the analysis showed that they experienced significant psychological challenges during their voyage. Competitors paid considerable attention to preparing for the physical challenges of the event. However, not all prospective competitors gave the same time to preparing for psychological factors or were aware how they might play out during their voyage. All Atlantic rowing crews should be aware of the psychological challenges they face, and have strategies in place to help cope with the psychological strain of taking part.

Keywords: confinement experiences, ocean rowing, stress, ultra-endurance sport

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Authors: Usama Bin Zubair, Muhammad Azeem

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Introduction: Depression has been one of the most commonly diagnosed mental health disorders in Pakistan. A Census conducted by the government of Pakistan in 2017 showed that more than 10000 trans-genders live in Pakistan. HIV, illicit substance use and mental health issues, including depression, have been the main health problems faced by them. Trans-gender population has been suffering from depressive illness more than normal population all over the world. Aim: To assess the prevalence of depression among the transgender population and analyze the relationship of socio-demographic factors with depression. Subjects and Methods: The sample population comprised of one hundred and forty-two transgender people of Rawalpindi and Islamabad. Beck depressive inventory II (BDI-II) was used to record the presence and severity of the depressive symptoms. Depressive symptoms were categorized as mild, moderate and severe. Relationship of the age, smoking, family income, illicit substance use and education were studied with the presence of depressive symptoms among these transgender people of twin cities of Pakistan. Results: A total of 142 transgender people were included in the final analysis. The mean age of the study participants was 39.55 ± 6.18. Out of these, 45.1% had no depressive symptoms while 31.7% had mild, 12.7% had moderate and 10.6% had severe depressive symptomatology. After applying the binary logistic regression, we found that the presence of depressive symptoms had a significant association with illicit substance use among the target population. Conclusion: This study showed a high prevalence of depressive symptoms among the transgender population in the twin cities of Pakistan. Use of illicit substances like tobacco, cannabis, opiates, and alcohol should be discouraged to prevent mental health problems.

Keywords: depression, transgender, prevalence, sociodemographic factors

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Authors: Cledinaldo A. Dias, Isabela C. Santos, Marcus V. S. Siqueira

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In the contemporary globalization, the competitiveness generated in the search of new markets aiming at the growth of productivity and, consequently, of profits, implies the redefinition of productive processes and new forms of work organization. As a result of this structuring, unemployment, labor force turnover and the increase in outsourcing and informal work occur. Considering the different relationships and working conditions of outsourced employees, this study aims to identify the most present stressors among outsourced service providers from a Federal Institution of Higher Education in Brazil. To reach this objective, a descriptive exploratory study with a quantitative approach was carried out. The qualitative approach was chosen to provide an in-depth analysis of the occupational conditions of outsourced workers since this method seeks to focus on the social as a world of investigated meanings and the language or speech of each subject as the object of this approach. The survey was conducted in the city of Montes Claros - Minas Gerais (Brazil) and involved eighty workers from companies hired by the institution, including armed security guards, porters, cleaners, drivers, gardeners, and administrative assistants. The choice of professionals obeyed non-probabilistic criteria for convenience or accessibility. Data collection was performed by means of a structured questionnaire composed of sixty questions, in a Likert-type frequency interval scale format, in order to identify potential organizational stressors. The results obtained evidence that the stress factors pointed out by the workers are, in most cases, a determining factor due to the low productive performance at work. Amongst the factors associated with stress, the ones that stood out most were those related to organizational communication failures, the incentive to competition, lack of expectations of professional growth, insecurity and job instability. Based on the results, the need for greater concern and organizational responsibility with the well-being and mental health of the outsourced worker and the recognition of their physical and psychological limitations, and care that goes beyond the functional capacity for the work. Specifically for the preservation of mental health, physical and quality of life, it is concluded that it is necessary for the professional to be inserted in the external world that favors it internally since this set is complemented so that the individual remains in balance and obtain satisfaction in your work.

Keywords: occupational health, outsourced, organizational studies, stressors

Procedia PDF Downloads 104

Authors: Fangfei Li

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This research was conducted to explore how Chinese overseas students, who rarely received teacher feedback during their undergraduate studies in China, engaged in a different feedback provision context in the UK universities. In particular, this research provides some insights into Chinese students’ perspectives on how they made sense of the teacher feedback they obtained and how they took it on board in their assignments. Research questions in this study are 1) What are Chinese overseas students’ perceptions of teacher feedback on courses in UK higher education? 2) How do they respond to the teacher feedback they obtained? 3) What factors might influence their engagement with teacher feedback? Multiple case studies of five Chinese overseas students in a UK university have been carried out to address the research questions. The main data collection instruments are various types of semi-structured interviews, consisting of background interviews, scenario-based activities, stimulated recall sessions and retrospective interviews. Research findings indicate that student engagement with teacher feedback is a complex learning process incorporating several stages: from initial teacher input to ultimate transformational learning. Apart from students interpreting teachers’ comments/suggestions by themselves, students’ understandings of and responses to teacher feedback could also be influenced by pre-submission guidance, peer discussion, use of exemplars and post-submission discussion with teachers. These are key factors influencing students to make use of teacher feedback. Findings also reveal that the level of students’ reflections on tutor feedback influences the quality of their assignments and even their future learning. To sum up, this paper will discuss the current concepts of teacher feedback in existing studies and research findings of this study from which reconceptualization of teacher feedback has occurred.

Keywords: Chinese students, student engagement, teacher feedback, the UK higher education

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Authors: Bhavna Rajagopal, Mrinmoyi Kulkarni

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Today women experience more menstrual cycles than their ancestors did a hundred years ago, owing to early puberty, fewer pregnancies and dietary changes. Much of the research in menstruation is located in the medical domain with a focus on physical symptoms. The research in psychology is largely concerned with premenstrual syndrome (PMS), whereas the focus in sociology is on social and cultural practices relating to menstruation. Research that simultaneously studies the physical, psychological, social and cultural aspects is lacking. Therefore, in this study, an attempt has been made to identify socio-cultural, psychological and physical factors that interact to influence a woman’s experience of menstruation in the urban setting. The study included seven unmarried women in the age group of 24-30 and data was obtained through a focus group discussion. The transcript of the focus group discussion was thematically analysed. Two major themes relating to the self and social experience of menstruation emerged. Themes relating to the self included menarcheal experiences, self-perception, mood and management of menstrual hygiene and symptoms while themes relating to social experience included the construction of menstruation by family and peers, and cultural factors. Attitudes towards the menstrual cycle appeared to be primarily influenced by severity of symptoms and the resulting disruption to daily life. Outcomes of this study have indicated that future research needs to study menstruation and its impact on women’s wellbeing by adopting a socio-ecological approach and by collecting data using the whole cycle approach across a woman’s reproductive years.

Keywords: India, menstrual cycle, psychosocial approach, wellbeing

Procedia PDF Downloads 133

Authors: Hsien Hua Kuo, Wen Chun Lin, Chia Chi Hsu, Hsien Wen Kuo

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Objective: Despite the high prevalence of musculoskeletal disorders (MSDs) among nurses, which has been consistently observed in the studies of Western countries, very little information regarding intensity of workload and work-related quality of life (WRQOL) related to MSDs among nurses is available in Taiwan. The objective of this study is to investigate the factors affecting musculoskeletal disorders in nurses from a hospital. Methods: 550 nurses from a hospital in Taoyuan were interviewed using a modified standardized Nordic Musculoskeletal (NMQ) questionnaire which contained the demographic information, workplace condition and musculoskeletal disorders. Results: Response rate of nurses were 92.5% from a teaching hospital. Based on medical diagnosis by physician, neck of musculoskeletal disorders had the highest percentage in nine body portions. The higher percentage of musculoskeletal disorders in nurses found from wards of internal and surgery. Severity and symptoms of musculoskeletal disorders diagnosed by self-reported questionnaire significantly correlated with WRQOL, job satisfaction and intensity of workload among nurses based on the logistic regression model. Conclusion: The severity and symptoms of musculoskeletal disorders among nurses showed a dose-dependent with WRQOL and workload. When work characteristics in hospital were modified, the severity of musculoskeletal disorders among nurses will be decreased and alleviated. Comment: Multifaceted ergonomic intervention programme to reduce the prevalence of MSDs among nurses was by encouraging nurses to do more physical activity which will make them more flexible and increase their strength. Therefore, the head nurse should encourage nurses to regularly physical activity and to modify unfitting ergonomic environment in order to reduce the prevalence of MSDs.

Keywords: musculoskeletal disorders, nurse, WRQOL, job satisfaction

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Authors: Nurliani, Ida Rosada

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The national rice consumption keeps increasing along with raising income of the households and the rapid growth of population. However, food availability, particularly rice, is limited. Impacts of rice-field conversion have run cumulatively, as we can see on potential losses of rice and crops production, as well as work opportunity that keeps increasing year-by-year. Therefore, it requires policy recommendation to control rice-field conversion through economic, social, and ecological approaches. The research was a survey method intended to: (1) Identify internal factors; quality and productivity of the land as the cause of land conversion, (2) Identify external factors of land conversion, value of the rice-field and the competitor’s land, workforce absorption, and regulation, as well as (3) Formulate strategies in controlling rice-field conversion. Population of the research was farmers who applied land conversion at Pangkep Regency, South Sulawesi. Samples were determined using the incidental sampling method. Data analysis used productivity analysis, land quality analysis, total economic value analysis, and SWOT analysis. Results of the research showed that the quality of rice-field was low as well as productivity of the grains (unhulled-rice). So that, average productivity of the grains and quality of rice-field were low as well. Total economic value of rice-field was lower than the economic value of the embankment. Workforce absorption value on rice-field was higher than on the embankment. Strategies in controlling such rice-field conversion can be done by increasing rice-field productivity, improving land quality, applying cultivation technique of specific location, improving the irrigation lines, and socializing regulation and sanction about the transfer of land use.

Keywords: land conversion, quality of rice-field, productivity, land economic value.

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Authors: Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, Ahmad Albaqsami, Al Warith Al Rushaidi, Masoud Al Rawahi

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Predicting the interaction between drugs and their molecular targets is pivotal for advancing drug development processes. Due to the time and cost limitations, computational approaches have emerged as an effective approach to drug-target interaction (DTI) prediction. Most of the introduced computational based approaches utilize the drug molecule and protein sequence as input. This study does not only utilize these inputs, it also introduces a protein representation developed using a masked protein language model. In this representation, for every individual amino acid residue within the protein sequence, there exists a corresponding probability distribution that indicates the likelihood of each amino acid being present at that particular position. Then, the similarity between each pair of amino-acids is computed to create similarity matrix. To encode the knowledge of the similarity matrix, Bi-Level Routing Attention (BiFormer) is utilized, which combines aspects of transformer-based models with protein sequence analysis and represents a significant advancement in the field of drug-protein interaction prediction. BiFormer has the ability to pinpoint the most effective regions of the protein sequence that are responsible for facilitating interactions between the protein and drugs, thereby enhancing the understanding of these critical interactions. Thus, it appears promising in its ability to capture the local structural relationship of the proteins by enhancing the understanding of how it contributes to drug protein interactions, thereby facilitating more accurate predictions. To evaluate the proposed method, it was tested on two widely recognized datasets: Davis and KIBA. A comprehensive series of experiments was conducted to illustrate its effectiveness in comparison to cuttingedge techniques.

Keywords: BiFormer, transformer, protein language processing, self-attention mechanism, binding affinity, drug target interaction, similarity matrix, protein masked representation, protein language model

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Authors: Tafadzwa Shumba, Rose C. Nyatondo, Regret Sunge

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This research analyses the impact of budget deficits on the economic performance of Zimbabwe. The study employs the autoregressive distributed lag (ARDL) confines testing method to co-integration and long-run estimation using time series data from 1980-2018. The Augmented Dick Fuller (ADF) and the Granger approach were used to testing for stationarity and causality among the factors. Co-integration test results affirm a long term association between GDP development rate and descriptive factors. Causality test results show a unidirectional connection between budget shortfall to GDP development and bi-directional causality amid debt and budget deficit. This study also found unidirectional causality from debt to GDP growth rate. ARDL estimates indicate a significantly positive long term and significantly negative short term impact of budget shortfall on GDP. This suggests that budget deficits have a short-run growth retarding effect and a long-run growth-inducing effect. The long-run results follow the Keynesian theory that posits that fiscal deficits result in an increase in GDP growth. Short-run outcomes follow the neoclassical theory. In light of these findings, the government is recommended to minimize financing of recurrent expenditure using a budget deficit. To achieve sustainable growth and development, the government needs to spend an absorbable budget deficit focusing on capital projects such as the development of human capital and infrastructure.

Keywords: ARDL, budget deficit, economic performance, long run

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Authors: Chinyama Lukama, Million Phiri, Namuunda Mutombo

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Background: Improving access and utilization to high-quality sexual and reproductive health (SRH) information and services, including family planning (FP) commodities, is central to the global developmental agenda of sub-Saharan Africa (SSA). Despite the importance of family planning use in enhancing maternal health outcomes and fertility reduction, the prevalence of adolescents and young women using modern contraception is generally low in SSA. Zambia is one of the countries in Southern Africa with a high prevalence of teenage pregnancies and fertility rates. Despite many initiatives that have been implemented to improve access and demand for family planning commodities, utilization of FP, especially among adolescents and young women, has generally been low. The objective of this research agenda was to better understand the determinants of modern contraceptive use in adolescents and young women in Zambia. This analysis produced findings that will be critical for informing the strengthening of sexual and reproductive health policy strategies aimed at bolstering the provision and use of maternal health services in order to further improve maternal health outcomes in the country. Method: The study used the recent data from the Demographic and Health Survey of 2018. A sample of 3,513 adolescents and young women (ADYW) were included in the analysis. Multilevel logistic regression models were employed to examine the association of individual and contextual factors with modern contraceptive use among adolescents and young women. Results: The prevalence of modern contraception among sexually active ADYW in Zambia was 38.1% [95% CI, 35.9, 40.4]. ADYW who had secondary or higher level education [aOR = 2.16, 95% CI=1.35–3.47], those with exposure to listening to the radio or watching television [aOR = 1.26, 95% CI=1.01–1.57], and those who had decision-making power at household level [aOR = 2.18, 95% CI=1.71–2.77] were more likely to use modern contraceptives. Conversely, strong neighborhood desire for large family size among ADYW [aOR = 0.65 95% CI = 0.47–0.88] was associated with less likelihood to use modern contraceptives. Community access to family planning information through community health worker visits increased the likelihood [aOR = 1.48, 95% CI=1.16–1.91] of using modern contraception among ADYW. Conclusion: The study found that both individual and community factors were key in influencing modern contraceptive use among adolescents and young women in Zambia. Therefore, when designing family planning interventions, the Government of Zambia, through its policymakers and sexual reproductive health program implementers at the Ministry of Health, in collaboration with stakeholders, should consider the community context. There should also be deliberate actions to encourage family planning education through the media.

Keywords: adolescents, young women, modern contraception use, fertility, family planning

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Authors: Vijaya Nirmala Pangi, K. V. Subhramanyam, C. Vijay Lakshmi

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Background: The prevalence of Type 2 Diabetes Mellitus is increasing drastically at a vigorous rate all over the world population. Aim: The present study aims to determine the prevalence of type-2 diabetes mellitus in Paderu tribal area population of Visakhapatnam district, located in northeastern region of Andhra Pradesh. Methods: A random sampling method was followed in 1025 subjects including controls (n=25) and determined 75-g oral glucose tolerance test to assess the presence of type 2 diabetes mellitus. The effect of anthropometric factors like age, gender, literacy, socio economic status, and environmental risk factors such as body fat response, hypertension and psychophysical stress response were determined in the studied subjects. Results: 78 (7.8%) were diabetic. Type 2 Diabetes Mellitus was found to be comparable between the two genders. Prevalence of diabetes was observed to be high in illiterate, low economic status subjects. Body fat response was comparable between control and diabetic subjects. However hypertension, stress associated enzymes showed significant (p < 0.05) decrease in diabetic subjects compared to controls in both the genders. Conclusion: It appears that there is a rising pattern in the prevalence of diabetes mellitus in tribal area, Paderu, Andhra Pradesh, India compared to previous rural studies.

Keywords: anthropometric studies, hypertension, oral glucose tolerance test, stress enzymes, type-2 diabetes mellitus

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Authors: Anietie J. Atangwho, Udeme E. Asibong, Item J. Atangwho, Ndifreke E. Udonwa

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Diabesity, a syndrome where diabetes and obesity occur simultaneously in a single patient, has emerged as a recent challenge to the medical world and is already at epidemic proportion in some countries. Therefore, this study aimed to determine the prevalence of diabesity among adult patients attending the General Outpatient clinic of three healthcare facilities in Calabar in a bid to improve healthcare delivery to patients at risk. A cross-sectional descriptive study design was employed using a mixed method approach that comprised quantitative and qualitative components i.e., Focused Group Discussion (FGD) and Key Informant Interview (KII). One hundred and ninety (190) participants aged 18 to 72 years and body mass index (BMI) ≥ 30kg/m2 were recruited as the study population for the quantitative study using systematic random sampling technique and analysed using SPSS version 25. The qualitative component performed 4 FGDs and 3 KIIs. Results of sociodemographic variables showed respondents aged 35 – 44 as highest in number (37.3%). Of this number, 83.7% were females, 76.8% married, and 3.7% earned USD1,110.00 monthly. Whereas majority of the participants (65.8 %) were within class 1 obesity, only 38% considered themselves obese. Diabesity occurrence was found to be 12.6% (i.e. BMI ≥ 30 to 45.2kg/m2 vs FBS ≥ 7.0 – 14.8mmo/l), with 38% of them being previously undiagnosed. About 48.4 % of the respondents ate two meals only per day; with 90.5% eating between meals. Snacking was predominant, mostly pastries (67.9%), with 58.9% taking cola drinks alongside. Sixty-one percent participated in one form of exercise or the other, with walking/trekking as the most common; 34.4 % had no regular exercise schedule. Only about 39.5% of the participants spent less than an hour on devices like phone, television, and laptops. Additionally, previously known and newly diagnosed hypertensive patients were 27.9% and 7.2%, respectively. Qualitative assessment with KII and FGDs showed eating unhealthy diets and lack of exercise as major factors responsible for diabesity. The bivariate analysis revealed significant association between diabesity with marital status and hypertension (p = 0.007 and p = 0.005, respectively). Also, positive association with diabesity were eating snacking (p = 0.017) and number of times a respondent snacks per day (p = 0.035). Overall, the study has revealed the occurrence of diabesity in Calabar at 12.6 % of the study population, with 38 % of them previously undiagnosed; it identified unhealthy diets and lack of exercise as causative factors as well as hypertension as snacking associatory indicators of diabesity.

Keywords: diabesity, obesity, diabetes, unhealthy diet

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Authors: Lazaro E. Nnko, Japhet J. Kashaigili, Gerald C. Monela, Pantaleo K. T. Munishi

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Agroforestry systems and practices are perceived to improve livelihood and sustainable management of natural resources. However, their adoption in various regions differs with the biophysical conditions and societal characteristics. This study was conducted in Kilombero District to investigate the factors influencing the adoption of different agroforestry systems and practices in agro-ecosystems and farming systems. A household survey, key informant interviews, and focus group discussion was used for data collection in three villages. Descriptive statistics and multinomial logistic regression in SPSS were applied for analysis. Results show that Igima and Ngajengwa villages had home garden practices dominated, as revealed by 63.3% and 66.7%, respectively, while Mbingu village had mixed intercropping practice with 56.67%. Agrosilvopasture systems were dominant in Igima and Ngajengwa villages with 56.7% and 66.7%, respectively, while in Mbingu village, the dominant system was agrosilviculture with 66.7%. The results from multinomial logistic regression show that different explanatory variable was statistical significance as predictors of the adoption of agroforestry systems and practices. Residence type and sex were the most dominant factor influencing the adoption of agroforestry systems. Duration of stay in the village, availability of extension education, residence, and sex were the dominant factor influencing the adoption of agroforestry practices. The most important and statistically significant factors among these were residence type and sex. The study concludes that agroforestry will be more successful if the local priorities, which include social-economic need characteristics of the society, will be considered in designing systems and practices. The socio-economic need of the community should be addressed in the process of expanding the adoption of agroforestry systems and practices.

Keywords: agroforestry adoption, agroforestry systems, agroforestry practices, agroforestry, Kilombero

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Authors: U.K. Sarkar, G. Karnatak, P. Mishal, Lianthuamluaia, S. Kumari, S.K. Das, B.K. Das

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Inland open water fisheries provide food, income, livelihood and nutritional security to millions of fishers across the globe. However, the open water ecosystem and fisheries are threatened due to climate change and anthropogenic pressures, which are more visible in the recent six decades, making the resources vulnerable. Understanding the interaction between meteorological parameters and inland fisheries is imperative to develop mitigation and adaptation strategies. As per IPCC 5th assessment report, the earth is warming at a faster rate in recent decades. Global mean surface temperature (GMST) for the decade 2006–2015 (0.87°C) was 6 times higher than the average over the 1850–1900 period. The direct and indirect impacts of climatic parameters on the ecology of fisheries ecosystem have a great bearing on fisheries due to alterations in fish physiology. The impact of meteorological factors on ecosystem health and fish food organisms brings about changes in fish diversity, assemblage, reproduction and natural recruitment. India’s average temperature has risen by around 0.7°C during 1901–2018. The studies show that the mean air temperature in the Ganga basin has increased in the range of 0.20 - 0.47 °C and annual rainfall decreased in the range of 257-580 mm during the last three decades. The studies clearly indicate visible impacts of climatic and environmental factors on inland open water fisheries. Besides, a significant reduction in-depth and area (37.20–57.68% reduction), diversity of natural indigenous fish fauna (ranging from 22.85 to 54%) in wetlands and progression of trophic state from mesotrophic to eutrophic were recorded. In this communication, different applications of biometeorology in inland fisheries management with special reference to the assessment of ecosystem and species vulnerability to climatic variability and change have been discussed. Further, the paper discusses the impact of climate anomaly and extreme climatic events on inland fisheries and emphasizes novel modeling approaches for understanding the impact of climatic and environmental factors on reproductive phenology for identification of climate-sensitive/resilient fish species for the adoption of climate-smart fisheries in the future. Adaptation and mitigation strategies to enhance fish production and the role of culture-based fisheries and enclosure culture in converting sequestered carbon into blue carbon have also been discussed. In general, the type and direction of influence of meteorological parameters on fish biology in open water fisheries ecosystems are not adequately understood. The optimum range of meteorological parameters for sustaining inland open water fisheries is yet to be established. Therefore, the application of biometeorology in inland fisheries offers ample scope for understanding the dynamics in changing climate, which would help to develop a database on such least, addressed research frontier area. This would further help to project fisheries scenarios in changing climate regimes and develop adaptation and mitigation strategies to cope up with adverse meteorological factors to sustain fisheries and to conserve aquatic ecosystem and biodiversity.

Keywords: biometeorology, inland fisheries, aquatic ecosystem, modeling, India

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Authors: Kulvinder Bajwa, Narsi R. Bishnoi

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Finding a sustainable alternative for today’s petrochemical industry is a major challenge facing by researchers, scientists, chemical engineers, and society at the global level. Microorganisms are considered to be sustainable feedstock for 3rd generation biofuel production. In this study, we have investigated the potential of a native bacterial strain isolated from a petrol contaminated site for the production of biodiesel. The bacterium was identified to be Rhodococcus opacus by biochemical test and 16S rRNA. Compositional analysis of bacterial biomass has been carried out by Fourier transform infrared spectroscopy (FTIR) in order to confirm lipid profile. Lipid and biomass were optimized by combination with Box Behnken design (BBD) of response surface methodology. The factors selected for the optimization of growth condition were glucose, yeast extract, and ammonium nitrate concentration. The experimental model developed through RSM in terms of effective operational factors (BBD) was found to be suitable to describe the lipid and biomass production, which indicated higher lipid and biomass with a minimum concentration of ammonium nitrate, yeast extract, and quite higher dose of glucose supplementation. Optimum results of the experiments were found to be 2.88 gL⁻¹ biomass and lipid content 38.75% at glucose 20 gL⁻¹, ammonium nitrate 0.5 gL⁻¹ and yeast extract 1.25 gL⁻¹. Furthermore, GCMS study revealed that Rhodococcus opacus has favorable fatty acid profile for biodiesel production.

Keywords: biofuel, Oleaginious bacteria, Rhodococcus opacus, FTIR, BBD, free fatty acids

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Decreasing mortality has led to increased focus on patient-reported outcomes such as quality of life (QoL) in breast cancer. Breast cancer patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment breast cancer patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 3,150 total participants (mean = 197) with a mean age of 51.9 years. There was substantial heterogeneity in measures of QoL. The most common was the European Organisation for Research and Treatment of Cancer QLQ-C30 (n=7, 41.1%). Most studies (n=12, 70.5%) found that emotional distress correlated with poor QoL, while 3 found no significant association. The most common measure of emotional distress was the Hospital Anxiety and Depression Scale (n=12, 70.5%). Other psychosocial factors associated with QoL were unmet needs, problematic social support, and negative affect. Clinicopathologic determinants included mastectomy without reconstruction, stage IV disease, and adjuvant chemotherapy. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment breast cancer patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: breast cancer, quality of life, psychosocial determinants, cancer surgery

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Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

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Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

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Authors: A. Abdullah, N. Faghih Mirzaei, S. Hany Haron

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Neighbourhood environment walkability on reported physical activity (PA) levels of students of Universiti Sains Malaysia (USM) in Malaysia. Compared with previous generations, today’s young people spend less time playing outdoors and have lower participation rates in PA. Research suggests that negative perceptions of neighbourhood walkability may be a potential barrier to adolescents’ PA. The sample consisted of 200 USM students (to 24 years old) who live outside of the main campus and engage in PA in sport halls and sport fields of USM. The data were analysed using the t-test, binary logistic regression, and discriminant analysis techniques. The present study found that youth PA was affected by neighbourhood environment walkability factors, including neighbourhood infrastructures, neighbourhood safety (crime), and recreation facilities, as well as street characteristics and neighbourhood design variables such as facades of sidewalks, roadside trees, green spaces, and aesthetics. The finding also illustrated that active students were influenced by street connectivity, neighbourhood infrastructures, recreation facilities, facades of sidewalks, and aesthetics, whereas students in the less active group were affected by access to destinations, neighbourhood safety (crime), and roadside trees and green spaces for their PAs. These results report which factors of built environments have more effect on youth PA and they message to the public to create more awareness about the benefits of PA on youth health.

Keywords: fear of crime, neighbourhood built environment, physical activities, street characteristics design

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Authors: Oyedele Ogundana, Amon Simba, Kostas Galanakis, Lynn Oxborrow

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The debate about factors influencing the business growth of women-owned businesses has been a topical issue in business management. Currently, scholars have identified the issues of access to money, market, and management as canvasing factors influencing the business growth of women-owned businesses. However, the influence of motherhood (household/family context) on business growth is inconclusive in the literature; despite that women are more family-oriented than their male counterparts. Therefore, this research study considers the influence of motherhood factor (household/family context) on the business growth of women-owned sewing businesses (WOSBs) in Lagos, Nigeria. The sewing business sector is chosen as the fashion industry (which includes sewing businesses) currently accounts for the second largest number of jobs in Sub-Saharan Africa, following agriculture. Thus, sewing businesses provide a rich ground for contributing to existing scholarly work. Research questions; (1) In what way does the motherhood factor influence the business growth of WOSBs in Lagos? (2) To what extent does the motherhood factor influence the business growth of WOSBs in Lagos? For the method design, a pragmatic approach, a mixed-methods technique and an abductive form of reasoning are adopted. The method design is chosen because it fits, better than other research perspectives, with the research questions posed in this study. For instance, using a positivist approach will not sufficiently answer research question 1, neither will an interpretive approach sufficiently answer research question 2. Therefore, the research method design is divided into 2 phases, and the results from one phase are used to inform the development of the subsequent phases (only phase 1 has been completed at the moment). The first phase uses qualitative data and analytical method to answer research question 1. While the second phase of the research uses quantitative data and analytical method to answer research question 2. For the qualitative phase, 5 WOSBs were purposefully selected and interviewed. The sampling technique is selected as it was not the intention of the researcher to make any statistical inferences, at this phase, rather the purpose was just exploratory. Therefore, the 5 sampled women comprised of 2 unmarried women, 1 married woman with no child, and 2 married women with children. A 40-60 minutes interview was conducted per participants. The interviews were audio-recorded and transcribed. Thereafter, the data were analysed using thematic analysis in order to unearth patterns and relationships. Findings for the first phase of this research reveals that motherhood (household/family context) directly influences (positively/negatively) the performance of WOSBs in Lagos. Apart from a direct influence on WOSBs, motherhood also moderates (positively/negatively) other factors–e.g., access to money, management/human resources and market/opportunities– influencing WOSBs in Lagos. To further strengthen this conclusion, a word frequency query result shows that ‘family,’ ‘husband’ and ‘children’ are among the 10 words used frequently in all the interview transcripts. This first phase contributes to existing studies by showing the various forms by which motherhood influences WOSBs. The second phase (which data are yet to be collected) would reveal the extent to which motherhood influence the business growth of WOSBs in Lagos.

Keywords: women-owned sewing businesses, business growth, motherhood, Lagos

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Authors: Han Song, Tingting Wei, Dong Chen

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The combination of capital and rural areas in China has shown its great significance in promoting urban-rural integration and new-style urbanization, enhancing regional capacity for sustainable rural development and optimizing human settlement environment. The purpose of this study is to find capital operation mechanism in rural area and rural planning guidance in China. Based on case studies in Chinese rural areas, two types of capital operation mechanism in rural areas are summed up: intervention in the field of agriculture promoting the upgrading and innovation of agricultural industry chain, intervention in rural life and leisure areas updating rural connotation and form. In the light of experiences in Japan and Taiwan, it is proposed that government's norms and guidance, rural investment intensity and rural self-organization are three important factors for capital to drive rural development. It is also found that the unique land tenure and rural governance tradition are two important factors effecting the combination of capital and rural regions in China, which requires full attention in rational policy-making and rural planning. It comes to a conclusion as four directions of the overall reform of the rural planning: targeting at enhancing the viability of rural and sustainable capacity, encouraging differences in investment incentives and planning policies, providing land usage in the rural areas with planning support and reforming the village system. Directional guidance is also made for different types of capital investments, suggesting that capital should be rooted in agriculture and rural land to benefit farmers and update human settlements.

Keywords: capital, rural areas, rural planning, rural governance

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