Search results for: threat factors

Authors: José Manuel Palma, Paula Pereira, Margarida Tomás

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Foreseen the future: Human factors integration in European Horizon Projects The development of new technology as artificial intelligence, smart sensing, robotics, cobotics or intelligent machinery must integrate human factors to address the need to optimize systems and processes, thereby contributing to the creation of a safe and accident-free work environment. Human Factors Integration (HFI) consistently pose a challenge for organizations when applied to daily operations. AGILEHAND and FORTIS projects are grounded in the development of cutting-edge technology - industry 4.0 and 5.0. AGILEHAND aims to create advanced technologies for autonomously sort, handle, and package soft and deformable products, whereas FORTIS focuses on developing a comprehensive Human-Robot Interaction (HRI) solution. Both projects employ different approaches to explore HFI. AGILEHAND is mainly empirical, involving a comparison between the current and future work conditions reality, coupled with an understanding of best practices and the enhancement of safety aspects, primarily through management. FORTIS applies HFI throughout the project, developing a human-centric approach that includes understanding human behavior, perceiving activities, and facilitating contextual human-robot information exchange. it intervention is holistic, merging technology with the physical and social contexts, based on a total safety culture model. In AGILEHAND we will identify safety emergent risks, challenges, their causes and how to overcome them by resorting to interviews, questionnaires, literature review and case studies. Findings and results will be presented in “Strategies for Workers’ Skills Development, Health and Safety, Communication and Engagement” Handbook. The FORTIS project will implement continuous monitoring and guidance of activities, with a critical focus on early detection and elimination (or mitigation) of risks associated with the new technology, as well as guidance to adhere correctly with European Union safety and privacy regulations, ensuring HFI, thereby contributing to an optimized safe work environment. To achieve this, we will embed safety by design, and apply questionnaires, perform site visits, provide risk assessments, and closely track progress while suggesting and recommending best practices. The outcomes of these measures will be compiled in the project deliverable titled “Human Safety and Privacy Measures”. These projects received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND) and No 101135707 (FORTIS).

Keywords: human factors integration, automation, digitalization, human robot interaction, industry 4.0 and 5.0

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Authors: Shabnam Dadparvar, Laijin Shen

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This paper focuses on China’s policy in the Middle East and the rivalry with the U.S. The question is that what are the main factors on China’s Middle East policy and its competition with the U.S? The hypothesis regards to three effective factors: 'China’s energy dependency' on the Middle East, 'economy' and support for 'stability' in the Middle East. What is important in China’s competition with the U.S regarding to its Middle East policy is the substantial difference in ways of treating the countries of the region; China is committed to Westphalia model based on non-interference in internal affairs of the countries and respect the sovereignty of the governments. However, after 9/11, the U.S is seeking a balance between stability and change through intervention in the international affairs and in some cases is looking for a regime change. From the other hand, China, due to its dependency on the region’s energy welcomes America’s military presence in the region for providing stability. The authors by using a descriptive analytical method try to explain the situation of rivalry between China and the United States in Middle East. China is an 'emerging power' with high economic growth and in demand of more energy supply. The problem is that a rising power in the region is often a source of concern for hegemony.

Keywords: China's foreign policy, energy, hegemony, the Middle East

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Authors: Morolake Josephine Adeagbo

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South Africa is one of those countries that openly rejected racism, and this is entrenched in its Bill of Rights. Despite the acceptance and incorporation of racial integration into the South Africa Constitution, the implementation within some sectors, most especially the educational sector, seems difficult. Recent occurrences of racism in some higher institutions of learning in South Africa are indications that racial integration / racial transformation is still farfetched in the country’s higher educational sector. It is against this background that this study was conducted to understand how gender and residential background influence racial integration in a South African university which was predominantly a white Afrikaner institution. Using a quantitative method to test the attitude of different categories of undergraduate students at the university, this study found that the factors- residential background and gender- used in measuring student’s attitude do not necessarily have a significant relationship towards racial integration. However, this study concludes with a call for more research with a range of other factors in order to better understand how racial integration can be promoted in South African institutions of higher learning.

Keywords: racial integration, gender, residential background, transformation

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Authors: Theodosios Paralikas, Evangelia Kotrotsiou, Mairy Gouva, Manolis Mentis, Stiliani Stavrotheodorou, Stiliani Kotrotsiou, Maria Malliarou

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There is a big discussion in the international literature on empathy, job satisfaction and job occupational among various of disciplines, including social workers. Νevertheless these parameters have not been specifically studied in the Greek territory. This paper aims to study empathy of social workers, to produce results related to whether empathy is influenced by demographic factors such as gender, age, marital status, level of education and study their perceived stress levels and also the satisfaction they derive from their work. For the first time, an attempt is made to link the empathy of these professionals to their job satisfaction and their anxiety. The sample of this survey consists of 165 social workers working on providers of public and private social services. The results showed that social workers have high levels of empathy contrary to the perceived stress levels which were low to moderate. Regarding the field of the job satisfaction, the survey showed that social workers are very satisfied with their workpiece and workplace. The survey shows no significant relationship between empathy and demographic factors, but there is a significant relationship between empathy and the workpiece/job satisfaction and the feeling of success.

Keywords: empathy, stress, job satisfaction, social workers

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Authors: Mukesh Roy, Basant Singh Sikarwar, Ravi Prakash, Priya Ranjan, Ayush Goyal

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More than 11% of people suffer from weakness in the bone resulting in inability in walking or climbing stairs or from limited upper body and limb immobility. This motivates a fresh bio-mimicking solution to the design of an exo-skeleton to support human movement in the case of partial or total immobility either due to congenital or genetic factors or due to some accident or due to geratological factors. A deeper insight and detailed understanding is required into the workings of the ball and socket joints. Our research is to mimic ball and socket joints to design snugly fitting exoskeletons. Our objective is to design an exoskeleton which is comfortable and the presence of which is not felt if not in use. Towards this goal, a parametric study is conducted to provide detailed design parameters to fabricate an exoskeleton. This work builds up on real data of the design of the exoskeleton, so that the designed exo-skeleton will be able to provide required strength and support to the subject.

Keywords: bio-mimicking, exoskeleton, ball joint, socket joint, artificial limb, patient rehabilitation, joints, human-machine interface, wearable robotics

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Authors: Velly Anatasia

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The worldwide annual expenditure for cosmetics is estimated at U.S. $18 billion and many players in the field are competing aggressively to capture more and more markets. Players in the cosmetics industry strive to be the foremost by establish customer loyalty. Furthermore, customer loyalty is portrayed by brand loyalty. Therefore, brand loyalty is the key determine of winning the competition in tight market. This study examines the influence of brand loyalty on cosmetics buying behavior of female consumers in Jakarta as capital of Indonesia. The seven factors of brand loyalty are brand name, Product quality, price, design, promotion, servicesquality and store environment. The paper adopted descriptive analysis, factor loading and multiple regression approach to test the hypotheses. The data has been collected by using questionnaires which were distributed and self-administered to 125female respondents accustomed using cosmetics. The findings of this study indicated that promotion has shown strong correlation with brand loyalty. The research results showed that there is positive and significant relationship between factors of brand loyalty (brand name, product quality, price, design, promotion, services quality and store environment) with cosmetics brand loyalty.

Keywords: brand loyalty, brand name, product quality, service quality, promotion

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Authors: E. Zarei, M. Bazaei, A. seifi, A. Keshavarzi

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Contextuallism has been always the main component of urban science. It not only has great direct and indirect impact on behaviors, events and interactions, but also is one of the basic factors of an urban values and identity. Nowadays there might be some deficiencies in the cities. In the theories of environment designing, humanistic orientations with the focus on culture and cultural variables would enable us to transfer information. To communicate with the context in which human lives, he needs some common memories, understandable symbols and daily activities in that context. The configuration of a place can impact on human’s behaviors. The goal of this research is to review 7 projects in different parts of the world with various usages and some factors such as ‘sense of place’, ‘sense of belonging’ and ‘social and cultural relations’ will be discussed in these projects. The method used for research in this project is descriptive- analytic. Library information and Internet are the main sources of gathering information and the method of reasoning used in this project is inductive. The consequence of this research will be some data in the form of tables that has been extracted from mentioned projects.

Keywords: contextuallism with humanistic approach, sense of place, sense of belonging, social and cultural relations

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Authors: Kutub Uddin Chisty, Md. Kamrul Islam, Md. Ashraful Islam

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Growth pattern is an important factor for a city because it can help to predict future growth trend and development of a city. Khagrachari District is one of the three hill tracts districts in Bangladesh. It is bordered by the Indian State of Tripura on the north, Rangamati and Chittagong districts on the south, Rangamati district on the east, Chittagong district and the Indian State of Tripura on the west. Khagrachari Pourashava is surrounded by hills and waterways. The Pourashava area is mostly inhibited by non-tribal population, while tribal population lives in hilly regions within and around the Pourashava area. The hilly area growth is different. Based on questioners and expert opinions survey, growth pattern of Khagrachari is evaluated. Different culture, history, tribal people, non-tribal people enrich the hilly heritages. In our study, we analyse the city growth pattern and identify the prominent factors that influence the city growth. Thus, it can help us to identify growth trend of the city.

Keywords: growth pattern, growth trend, prominent factors, regional development

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Authors: Hamd Rezaeifar, Hamid Reza Sahriari

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Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.

Keywords: accident, data mining, neural network, GIS

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Authors: Bryan M. Baltazar, Marjorie V. Remolador, Klathea H. Sevilla, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Biomass energy is a traditional source of sustainable energy, which has been widely used in developing countries. The Philippines, specifically Central Luzon, has an abundant source of biomass. Hence, it could supply abundant agricultural residues (rice husks), as feedstock in a biomass power plant. However, locating a potential site for biomass development is a complex process which involves different factors, such as physical, environmental, socio-economic, and risks that are usually diverse and conflicting. Moreover, biomass distribution is highly dispersed geographically. Thus, this study develops an integrated method combining Geographical Information Systems (GIS) and methods for energy planning; Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP), for locating suitable site for biomass power plant development in Central Luzon, Philippines by considering different constraints and factors. Using MCDA, a three level hierarchy of factors and constraints was produced, with corresponding weights determined by experts by using AHP. Applying the results, a suitability map for Biomass power plant development in Central Luzon was generated. It showed that the central part of the region has the highest potential for biomass power plant development. It is because of the characteristics of the area such as the abundance of rice fields, with generally flat land surfaces, accessible roads and grid networks, and low risks to flooding and landslide. This study recommends the use of higher accuracy resource maps, and further analysis in selecting the optimum site for biomass power plant development that would account for the cost and transportation of biomass residues.

Keywords: analytic hierarchy process, biomass energy, GIS, multi-criteria decision analysis, site suitability analysis

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Authors: Pruethipong Xinghatiraj, Rajwanlop Kumpoopong

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Considering the current situation of road safety, Thailand has the world’s second-highest road fatality rate. Therefore, decreasing the road accidents in Thailand is a prime policy of the Thai government seeking to accomplish. One of the approaches to reduce the accident rate is to improve road environments to fit with the local behavior of the road users. The Department of Highways ensures that choosing the road median types right to the road characteristics, e.g. roadside characteristics, traffic volume, truck traffic percentage, etc., can decrease the possibility of accident occurrence. Presently, raised median, depressed median, painted median and median barriers are typically used in Thailand Highways. In this study, factors affecting road accident for each median type will be discovered through the analysis of the collecting of accident data, death numbers on sample of 600 Kilometers length across the country together with its roadside characteristics, traffic volume, heavy vehicles percentage, and other key factors. The benefits of this study can assist the Highway designers to select type of road medians that can match local environments and then cause less accident prone.

Keywords: highways, road safety, road median, forecasting model

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Anika Pallapothu

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Periodontitis, a severe gum disease, poses a significant threat to the integrity of bone and soft tissues supporting teeth, primarily initiated by bacterial accumulation around the gum line. Conventional treatments like scaling/root planning and plaque removal are widely employed, but integrating modern technologies such as nanotechnology holds promise for innovative therapeutic approaches. This study explores the utilization of silver nanoparticles encapsulated within cellulose nanofiber (CNF) and mesoporous bioactive glass hydrogel matrices for periodontitis management. Silver nanoparticles exhibit potent antimicrobial properties by disrupting microbial cell membranes, inducing reactive oxygen species (ROS) generation, and interfering with vital cellular processes like ATP production and nucleic acid synthesis. Mesoporous bioactive glass, renowned for its high surface area, osteoconductive, and bioactivity, presents a favorable platform for pharmaceutical applications. Incorporating CNF enhances the properties of the hydrogel due to its biocompatibility, biodegradability, and water absorption capacity. The proposed composite material is anticipated to exert beneficial effects in periodontitis treatment by demonstrating antibacterial and anti-inflammatory activities, offering a promising avenue for future therapeutic interventions.

Keywords: periodontitis, cellulose nanofibers, silver nanoparticles, mesoporous bioactive glass, antibacterial activity, anti-inflammatory activity

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Authors: V. Mathad, S. Shivprasad, P. Shivsharannappa, M. K. Patil

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Introduction: Non-communicable diseases are emerging diseases in India. Government of India launched National Programme for Prevention and Control of Cardiovascular Diseases, Cancer and Stroke (NPCDCS) during the year 2008. The aim of the programme was to reduce the burden of non communicable diseases by health promotion and prompt treatment. Objective: The present study was intended to assess the impact of National Program for prevention and control of Cardiovascular Diseases, Diabetes, Cancer and Stroke Programme on biochemical and physiological factors influencing Type 2 diabetes in Kalaburagi District. Material and Method: NCD Clinic was established at District Hospital during April 2016. All the patients attending District Hospital Kalaburagi above the age of 30 years are screened for Non Communicable Diseases under NPCDCS Programme. A total sample of 7447 patients attending NCD Clinic situated at Kalaburagi district was assessed in this study. Pre structured and pretested schedule seeking information was obtained from all the patients by the counselor working under NPCDCS programme. All the Patients attending District Hospital were screened for Diabetes using Glucometer at NCD clinic. The suspected cases were further confirmed through Biochemical investigations like Fasting Blood glucose, HBA1c, Urine Glucose, Kidney Function test. SPSS 20 version was used for analysis of data. Chi square test, P values and odds ratio was used to study the association of factors. Results: A Total of 7447 patients attended NCD clinic during the year 2017-18 were analyzed, Diabetes was seen among 3028 individuals were as comorbidities along with Hypertension was seen among 757 individuals. The mean age of the population was 50 ± 2.84. 3440(46.2%) were males whereas Female constituted 4007(53.8%) of population. The incidence and prevalence of Diabetes being 8.6 and 12.8 respectively. Diabetes was more commonly seen during the age group of 40 to 69 years. Diabetes was significantly associated with Age group 40 to 69 years, obesity and female gender (p < 0.05). The risk of developing Hypertension and comorbidity conditions of hypertension and Diabetes was 1.224 and 1.305 times higher among males, whereas the risk of diabetes was 1.127 higher among females as compared to males. Conclusion: The screening for NCD has significantly increased after launching of NPCDCS programme. NCD was significantly associated with obesity, female gender, increased age as well as comorbid conditions like hypertension and tuberculosis.

Keywords: non-communicable diseases, NPCDCS programme, type 2 Diabetes, physiological factors

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Authors: Parvin Mirmiran, Zahra Bahadoran, Sahar Mirzae, Fereidoun Azizi

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Background and aim: Lifestyle factors, especially dietary intakes play an important role in metabolism of lipids and lipoproteins. In this study, we assessed the association between dietary factors and 3-year changes of serum triglycerides (TG), HDL-C and the atherogenic index of plasma among Iranian adults. This longitudinal study was conducted on 1938 subjects, aged 19-70 years, who participated in the Tehran Lipid and Glucose Study. Demographics, anthropometrics and biochemical measurements including serum TG were assessed at baseline (2006-2008) and after a 3-year follow-up (2009-2011). Dietary data were collected by using a 168-food item, validated semi-quantitative food frequency questionnaire at baseline. The risk of hypertriglyceridemia in the quartiles of dietary factors was evaluated using logistic regression models with adjustment for age, gender, body mass index, smoking, physical activity and energy intakes. Results: Mean age of the participants at baseline was 41.0±13.0 y. Mean TG and HDL-C at baseline was 143±86 and 42.2±10.0 mg/dl, respectively. Three-year change of serum TG were inversely related energy intake from phytochemical rich foods, whole grains, and legumes (P<0.05). Higher intakes compared to lower ones of dietary fiber and phytochemical-rich foods had similar impact on decreased risk of hyper-triglyceridemia (OR=0.58, 95% CI=0.34-1.00). Higher- compared to lower-dietary sodium to potassium ratios (Na/K ratio) increased the risk of hypertriglyceridemia by 63% (OR=0.1.63, 95% CI= 0.34-1.00). Conclusion: Findings showed that higher intakes of fiber and phytochemical rich foods especially whole grain and legumes could have protective effects against lipid disorders; in contrast higher sodium to potassium ratio had undesirable effect on triglycerides.

Keywords: lipid disorders, hypertriglyceridemia, diet, food science

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Authors: Neusa Fernanda Torres, Buyisile Chibi, Lyn E. Middleton, Vernon P. Solomon, Tivani P. Mashamba-Thompson

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Background: Self-medication with antibiotics (SMA) is a global concern, with a higher incidence in low and middle-income countries (LMICs). Despite intense world-wide efforts to control and promote the rational use of antibiotics, continuing practices of SMA systematically exposes individuals and communities to the risk of antibiotic resistance and other undesirable antibiotic side effects. Moreover, it increases the health systems costs of acquiring more powerful antibiotics to treat the resistant infection. This review thus maps evidence on the factors influencing self-medication with antibiotics in these settings. Methods: The search strategy for this review involved electronic databases including PubMed, Web of Knowledge, Science Direct, EBSCOhost (PubMed, CINAHL with Full Text, Health Source - Consumer Edition, MEDLINE), Google Scholar, BioMed Central and World Health Organization library, using the search terms:’ Self-Medication’, ‘antibiotics’, ‘factors’ and ‘reasons’. Our search included studies published from 2007 to 2017. Thematic analysis was performed to identify the patterns of evidence on SMA in LMICs. The mixed method quality appraisal tool (MMAT) version 2011 was employed to assess the quality of the included primary studies. Results: Fifteen studies met the inclusion criteria. Studies included population from the rural (46,4%), urban (33,6%) and combined (20%) settings, of the following LMICs: Guatemala (2 studies), India (2), Indonesia (2), Kenya (1), Laos (1), Nepal (1), Nigeria (2), Pakistan (2), Sri Lanka (1), and Yemen (1). The total sample size of all 15 included studies was 7676 participants. The findings of the review show a high prevalence of SMA ranging from 8,1% to 93%. Accessibility, affordability, conditions of health facilities (long waiting, quality of services and workers) as long well as poor health-seeking behavior and lack of information are factors that influence SMA in LMICs. Antibiotics such as amoxicillin, metronidazole, amoxicillin/clavulanic, ampicillin, ciprofloxacin, azithromycin, penicillin, and tetracycline, were the most frequently used for SMA. The major sources of antibiotics included pharmacies, drug stores, leftover drugs, family/friends and old prescription. Sore throat, common cold, cough with mucus, headache, toothache, flu-like symptoms, pain relief, fever, running nose, toothache, upper respiratory tract infections, urinary symptoms, urinary tract infection were the common disease symptoms managed with SMA. Conclusion: Although the information on factors influencing SMA in LMICs is unevenly distributed, the available information revealed the existence of research evidence on antibiotic self-medication in some countries of LMICs. SMA practices are influenced by social-cultural determinants of health and frequently associated with poor dispensing and prescribing practices, deficient health-seeking behavior and consequently with inappropriate drug use. Therefore, there is still a need to conduct further studies (qualitative, quantitative and randomized control trial) on factors and reasons for SMA to correctly address the public health problem in LMICs.

Keywords: antibiotics, factors, reasons, self-medication, low and middle-income countries (LMICs)

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Authors: Bundit Pungnirund

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This research aimed to study the relationship between marketing mix attitudes, motivation of buying decision and tendency of consumer decision making in buying the condominiums in Thailand. This study employed by survey and quantitative research. The questionnaire was used to collect the data from 400 sampled of customers who interested in buying condominium in Bangkok. The descriptive statistics and Pearson’s correlation coefficient analysis were used to analyze data. The research found that marketing mixed factors in terms of product and price were related to buying decision making tendency in terms of price and room size. Marketing mixed factors in terms of price, place and promotion were related to buying decision making tendency in term of word of mouth. Consumers’ buying motivation in terms of social acceptance, self-esteemed and self-actualization were related to buying decision making tendency in term of room size. In addition, motivation in self-esteemed was related to buying decision making tendency within a year.

Keywords: condominium, marketing mix, motivation, tendency of consumer decision making

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

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Authors: Xiuguo Zhao, He Li, Alireza Yazdani, Xiaoning Zheng, Xinxi Xu

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Wound infected poses a serious threat to the surgery on the patient during the process of surgery. Understanding the bacteria-carrying particles (BCPs) transportation and deposition in the open surgical wound model play essential role in protecting wound against being infected. Therefore BCPs transportation and deposition in the surgical wound model were investigated using force-coupling method (FCM) based computational fluid dynamics. The BCPs deposition in the wound was strongly associated with BCPs diameter and concentration. The results showed that the rise on the BCPs deposition was increasing not only with the increase of BCPs diameters but also with the increase of the BCPs concentration. BCPs deposition morphology was impacted by the combination of size distribution, airflow patterns and model geometry. The deposition morphology exhibited the characteristic with BCPs deposition on the sidewall in wound model and no BCPs deposition on the bottom of the wound model mainly because the airflow movement in one direction from up to down and then side created by laminar system constructing airflow patterns and then made BCPs hard deposit in the bottom of the wound model due to wound geometry limit. It was also observed that inertial impact becomes a main mechanism of the BCPs deposition. This work may contribute to next study in BCPs deposition limit, as well as wound infected estimation in surgical-site infections.

Keywords: BCPs deposition, computational fluid dynamics, force-coupling method (FCM), numerical simulation, open surgical wound model

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Ehsan Asgari, Meisam Afazeli, Nezhla Attarchian

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Post-earthquake fire is considered as a major threat in seismic areas. After an earthquake, fire is possible in structures. In this research, the effect of post-earthquake fire on steel moment frames with and without fireproofing coating is investigated. For this purpose, finite element method is employed. For the verification of finite element results, the results of an experimental study carried out by previous researchers are used, and the predicted FE results are compared with the test results, and good agreement is observed. After ensuring the accuracy of the predictions of finite element models, the effect of post-earthquake fire on the frames is investigated taking into account the parameters including the presence or absence of fire protection, frame design assumptions, earthquake type and different fire scenario. Ordinary fire and post-earthquake fire effect on the frames is also studied. The plastic hinges induced by earthquake in the structure are determined in the beam to the column connection and in panel zone. These areas should be accurately considered when providing fireproofing coatings. The results of the study show that the occurrence of fire beside corner columns is the most damaging scenario that results in progressive collapse of structure. It was also concluded that the behavior of structure in fire after a strong ground motion is significantly different from that in a normal fire.

Keywords: post earthquake fire, moment frame, finite element simulation, coupled temperature-displacement analysis, fire scenario

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Authors: Yutong Xu, Wanting Zhang, Jia Wang, Zihan Guo, Weiguang Ma

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Background: The resilience education of intern nursing students has significant implications for the development and improvement of the nursing workforce. The clinical internship period is a critical time for enhancing resilience. Aims: To evaluate the resilience level of Chinese nursing interns and identify the factors affecting resilience early in their careers. Methods: The cross-sectional study design was adopted. From March 2022 to May 2023, 512 nursing interns in tertiary care hospitals were surveyed online with the Connor-Davidson Resilience Scale, the Clinical Learning Environment scale for Nurse, and the Career Adapt-Abilities Scale. Structural equation modeling was used to clarify the relationships among these factors. Indirect effects were tested using bootstrapped Confidence Intervals. Results: The nursing interns showed a moderately high level of resilience[M(SD)=70.15(19.90)]. Gender, scholastic attainment, had a scholarship, career adaptability and clinical learning environment were influencing factors of nursing interns’ resilience. Career adaptability and clinical learning environment positively and directly affected their resilience level (β = 0.58, 0.12, respectively, p＜0.01). career adaptability also positively affected career adaptability (β = 0.26, p < 0.01), and played a fully mediating role in the relationship between clinical learning environment and resilience. Conclusion: Career adaptability can enhance the influence of clinical learning environment on resilience. The promotion of career adaptability and the clinical teaching environment should be the potential strategies for nursing interns to improve their resilience, especially for those female nursing interns with low academic performance. Implications for Nursing Educators Nursing educators should pay attention to the cultivation of nursing students' resilience; for example, by helping them integrate to the clinical learning environment and improving their career adaptability. Reporting Method: The STROBE criteria were used to report the results of the observations critically. Patient or Public Contribution No patient or public contribution.

Keywords: resilience, clinical learning environment, career adaptability, nursing interns

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Authors: T. Prommi, P. Thamsenanupap

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The influence of physicochemical water quality parameters on the abundance and diversity of caddisfly larvae was studied in seven sampling stations in Mae Tao and Mae Ku watersheds, Mae Sot District, Tak Province, northern Thailand. The streams: MK2 and MK8 as reference site, and impacted streams (MT1-MT5) were sampled bi-monthly during July 2011 to May 2012. A total of 4,584 individual of caddisfly larvae belonging to 10 family and 17 genera were found. The larvae of family Hydropsychidae were the most abundance, followed by Philopotamidae, Odontoceridae, and Leptoceridae, respectively. The genus Cheumatopsyche, Hydropsyche, and Chimarra were the most abundance genera in this study. Results of CCA ordination showed the total dissolved solids, sulfate, water temperature, dissolved oxygen and pH were the most important physicochemical factors to affect distribution of caddisflies communities. Changes in the caddisfly fauna may indicate changes in physicochemical factors owing to agricultural pollution, urbanization, or other human activities. Results revealed that the order Trichoptera, identified to species or genus, can be potentially used to assess environmental water quality status in freshwater ecosystems.

Keywords: Caddisfly larvae, environmental variables, diversity, streams

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Authors: Li-Ting Chen, Chih-Tao Cheng, I-Ping Huang, Jen-Ho Chang, Nien-Tzu Chang, Fei-Hsiu Hsiao

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Background: Insecurity adult attachment style may be triggered by cancer threat, which in turn influences depression symptoms. Dispositional mindfulness may have benefits of insecure attachment on depression for colorectal patient transfer to survivor. Objective: This study examined the mediating and moderating effects of quality of life (QOL) and dispositional mindfulness on the relationship between insecure attachment style and depression symptoms. Methods: A cross-sectional study design was used. Data were collected using the QOL functional and symptoms (EORTC-C30 and EORTC CR29), dispositional mindfulness (FFMQ), Short form of Experience in Close Relationships Revised Questionnaire (SF-ECRRQ), and depressive symptoms (BDI-II scale). Results: Of the 90 CRC survivors who participated, the indirect effect of both ECR anxiety (β=0.23, CI=0.05-0.44) and ECR avoidance (β=0.12, CI=0.02-0.24) on depression were significantly mediated through EORTC-C29 colorectal symptoms. Three components of dispositional mindfulness (i.e., acting of awareness, non-judging, non-reactivity) as the moderator in the relationship between ECR anxiety and depressive symptoms. Acting of awareness was a moderator in the relationship between ECR avoidance and depressive symptoms. Conclusions: There are two pathways from insecure attachment to depression: through the mediator of colorectal symptoms and the moderator of dispositional mindfulness. Cancer symptom management and mindfulness practices could improve the impact of insecure attachment on depression among CRC patients in a post-treatment transition period.

Keywords: acting of awareness, attachment style, colorectal cancer, disposisitonal mindfulness, depression

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Authors: Tamirat Solomon, Tadesse Faltamo, Belete Limani

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This study was conducted on the mountain Damota of Wolaita to assess the abundance and spatial distribution of two locally important indigenous medicinal plants on the mountain landscape. A total of 130 plots measuring 20x20m were established along eight systematically laid transect lines. In each plot, the abundance and distribution of Hagenia abyssinica (tree) and Pentas schiperiana Vatke (shrub) were evaluated. The abundance and distribution of H. abyssinica were evaluated by measuring height and DBH for mature trees and counting seedlings and saplings, whereas the P. schiperiana Vatke was assessed for its abundance and distribution by counting in each plot. In the entire study plots, a total of 485 H. abyssinica and 760 P. schiperiana vatake were recorded. It was observed that the distribution of the species increased while the altitude increased and the highest abundance of the species was recorded at an altitude range between 2332 and 2661m.a.s.l. However, at the altitudes below 2320 m.a.s.l., the species distributions and abundance was decreased, indicating either the ecological preference of the species or the extraction of the local community surrounding the mountain influenced the species. On average, only 28 seedlings/ha of H. abyssinica and 146/ha of P. schiperiana vatke were recorded in the study areas showing the tendency of decline in the abundance and distribution of both species. Finally, we recommend management intervention for the socially important species which are under threat on the mountain landscape.

Keywords: indigenous medicinal plants, H.abyssinic, P. schiperiana, distribution, abundance, socio-economic importance

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Moustafa M. S. Sanad

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The worsening of energy supply crisis and the exacerbation of climate change by environmental pollution problems have become the greatest threat to human life. One of the ways to confront these problems is to rely on renewable energy and its storage systems. Nowadays, huge attention has been directed to the development of lithium-ion batteries (LIBs) as efficient tools for storing the clean energy produced by green sources like solar and wind energies. Accordingly, the demand for powerful electrode materials with excellent electrochemical characteristics has been progressively increased to meet fast and continuous growth in the market of energy storage systems. Therefore, the electronic and electrical properties of conversion anode materials for rechargeable lithium-ion batteries (LIBs) can be enhanced by introducing lattice defects and oxygen vacancies in the crystal structure. In this regard, the intended presentation will demonstrate new insights and effective ways for enhancing the electrical conductivity and improving the electrochemical performance of different anode materials such as MgFe₂O₄, CdFe₂O₄, Fe₃O₄, LiNbO₃ and Nb₂O₅. The changes in the physicochemical and morphological properties have been deeply investigated via structural and spectroscopic analyses (e.g., XRD, FESEM, HRTEM, and XPS). Moreover, the enhancement in the electrochemical properties of these anode materials will be discussed through Galvanostatic Cycling (GC), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) techniques.

Keywords: structure modification, cationic substitution, non-stoichiometric synthesis, plasma treatment, lithium-ion batteries

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Authors: Mustafa Avsever

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Throughout history, states have attached great importance to seas in terms of economic and security. Advanced civilizations have always founded in coastal regions. Over time, human being has tended to trade and naturally always aimed get more and more. Seas by covering 71% of the earth, provide the greatest economic opportunities for access to raw material resources and the world market. As a result, seas have become the most important areas of conflict over the course of time. Coastal states, use seas as a tool for defense zone, trade, marine transportation and power transfer, they have acquired colonies overseas and increased their capital, raw materials and labor. Societies, have increased their economic prosperity, though their navies in order to retain their welfare and achieve their foreign policy objectives. Sometimes they have imposed their demands through the use or threat of limited naval force in accordance with their interests that is gunboat diplomacy. Today we can see samples of gunboat diplomacy used in the Eastern Mediterranean, during Ukraine crisis, in dispute between North Korea and South Korea and the ongoing power struggle in Asia-Pacific. Gunboat diplomacy has been and continues to be applied consistently in solving problems by the stronger side of the problem. The purpose of this article is to examine using navy under the gunboat diplomacy as an active instrument of foreign policy and security policy and reveal the strategic sea areas in which gunboat diplomacy is used effectively in the matrix of international politics in the 21st century.

Keywords: gunboat diplomacy, maritime strategy, sea power, strategic sea lands

Procedia PDF Downloads 432

Authors: Omar Nouri, Wafa Mnejja, Nejla Fourati, Fatma Dhouib, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Jamel Daoud

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Background and objective: Induction chemotherapy (IC) followed by concomitant chemo radiotherapy with intensity modulated radiation (IMRT) technique is actually the recommended treatment modality for locally advanced nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the prognostic factors predicting loco regional relapse with this new treatment protocol. Patients and methods: A retrospective study of 52 patients with NPC treated between June 2016 and July 2019. All patients received IC according to the protocol of the Head and Neck Radiotherapy Oncology Group (Gortec) NPC 2006 (3 TPF courses) followed by concomitant chemo radiotherapy with weekly cisplatin (40 mg / m2). Patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. Median age was 49 years (19-69) with a sex ratio of 3.3. Forty five tumors (86.5%) were classified as stages III - IV according to the 2017 UICC TNM classification. Loco regional relapse (LRR) was defined as a local and/or regional progression that occurs at least 6 months after the end of treatment. Survival analysis was performed according to Kaplan-Meier method and Log-rank test was used to compare anatomy clinical and therapeutic factors that may influence loco regional free survival (LRFS). Results: After a median follow up of 42 months, 6 patients (11.5%) experienced LRR. A metastatic relapse was also noted for 3 of these patients (50%). Target volumes coverage was optimal for all patient with LRR. Four relapses (66.6%) were in high-risk target volume and two (33.3%) were borderline. Three years LRFS was 85,9%. Four factors predicted loco regional relapses: histologic type other than undifferentiated (UCNT) (p=0.027), a macroscopic pre chemotherapy tumor volume exceeding 100 cm³ (p=0.005), a reduction in IC doses exceeding 20% (p=0.016) and a total cumulative cisplatin dose less than 380 mg/m² (p=0.0.34). TNM classification and response to IC did not impact loco regional relapses. Conclusion: For nasopharyngeal carcinoma, tumors with initial high volume and/or histologic type other than UCNT, have a higher risk of loco regional relapse. Therefore, they require a more aggressive therapeutic approaches and a suitable monitoring protocol.

Keywords: loco regional relapse, modulation intensity radiotherapy, nasopharyngeal carcinoma, prognostic factors

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