Search results for: statistical%20methods

Authors: Haftay Abraha Tadesse, Dawit Gebreegziabiher Hagos, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli (E. coli) are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Method: A cross-sectional study was conducted from January to December 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli. Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI:(4.69 27.10) were associated with overall bacterial contamination. About 100% of the tested isolates were sensitive to ciprofloxacin, gentamicin, Co trimoxazole , sulphamethoxazole, ceftriaxone, and trimethoprim and ciprofloxacin, gentamicin, and norfloxacine of E. coli and Salmonella species, respectively, while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor handwashing practice and not using glove during meat handling showed a significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species, and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, E. coli, raw meat, salmonella species

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Authors: Wan-Ling Jiang, Hsin Chi, Jia-Lu Cheng, Ming-Fang Cheng

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Background: Investigating the risk factors for the fecal carriage of third-generation cephalosporin-resistant E.coli could contribute to further disease prevention. Previous research on third-generation cephalosporin-resistant prevalence in children in different regions of Taiwan is limited. This project aims to explore the risk factors and regional differences in the prevalence of third-generation cephalosporin-resistant and other antibiotic-resistant E. coli in the northern, southern, and eastern regions of Taiwan. Methods: We collected data from children aged 0 to 18 from community or outpatient clinics from July 2022 to May 2023 in southern, northern, and eastern Taiwan. The questionnaire was designed to survey the characteristics of participants and possible risk factors, such as clinical information, household environment, drinking water, and food habits. After collecting fecal samples and isolating stool culture with E.coli, antibiotic sensitivity tests and MLST typing were performed. Questionnaires were used to analyze the risk factors of third-generation cephalosporin-resistant E. coli in the three different regions of Taiwan. Results: In the total 246 stool samples, third-generation cephalosporin-resistant E.coli accounted for 37.4% (97/246) of all isolates. Among the three different regions of Taiwan, the highest prevalence of fecal carriage with third-generation cephalosporin-resistant E.coli was observed in southern Taiwan (42.7%), followed by northern Taiwan (35.5%) and eastern Taiwan (28.4%). Multi-drug resistant E. coli had prevalence rates of 51.9%, 66.3%, and 37.1% in the northern, southern, and eastern regions, respectively. MLST typing revealed that ST131 was the most prevalent type (11.8%). The prevalence of ST131 in northern, southern, and eastern Taiwan was 10.1%, 12.3%, and 13.2%, respectively. Risk factors analysis identified lower paternal education, overweight status, and non-vegetarian diet as statistical significance risk factors for third-generation cephalosporin-resistant E.coli. Conclusion: The fecal carriage rates of antibiotic-resistant E. coli among Taiwanese children were on the rise. This study found regional disparities in the prevalence of third-generation cephalosporin-resistant and multi-drug-resistant E. coli, with southern Taiwan having the highest prevalence. Lower paternal education, overweight, and non-vegetarian diet were the potential risk factors of third-generation cephalosporin-resistant E. coli in this study.

Keywords: Escherichia coli, fecal carriage, antimicrobial resistance, risk factors, prevalence

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Authors: Ozcan B., Koca B., Tuzcuoglu E., Cavusoglu S., Efe A., Bayraktar S.

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A washing machine is mainly used for removing any types of dirt and stains and also eliminating malodorous substances from textile surfaces. Stains originate from various sources from the human body to environmental contamination. Therefore, there are various methods for removing them. They are roughly classified into four different groups: oily (greasy) stains, particulate stains, enzymatic stains and bleachable (oxidizable) stains. Oily stains on clothes surfaces are a common result of being in contact with organic substances of the human body (e.g. perspiration, skin shedding and sebum) or by being exposed to an oily environmental pollutant (e.g. oily foods). Studies showed that human sebum is major component of oily soil found on the garments, and if it is aged under the several environmental conditions, it can generate obstacle yellow stains on the textile surface. In this study, a parametric study was carried out to investigate the key factors affecting the cleaning performance (specifically sebum removal performance) of a washing machine. These parameters are mechanical agitation percentage of tumble, consumed water and total washing period. A full factorial design of the experiment is used to capture all the possible parametric interactions using Minitab 2021 statistical program. Tests are carried out with commercial liquid detergent and 2 different types of sebum-soiled cotton and cotton + polyester fabrics. Parametric results revealed that for both test samples, increasing the washing time and the mechanical agitation could lead to a much better removal result of sebum. However, for each sample, the water amount had different outcomes. Increasing the water amount decreases the performance of cotton + polyester fabrics, while it is favorable for cotton fabric. Besides this, it was also discovered that the type of textile can greatly affect the sebum removal performance. Results showed that cotton + polyester fabrics are much easier to clean compared to cotton fabric

Keywords: laundry, washing machine, low-temperature washing, cold wash, washing efficiency index, sustainability, cleaning performance, stain removal, oily soil, sebum, yellowing

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Authors: Florenda B. Cardinoza

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This study was conducted to determine the determinants of Grade III and grade VI pupils’ performance in the National Achievement Test in the Division of Cavite City, School Year 2011-2012. Specifically, the research aimed to: (1) describe the demographic profile of the respondents in terms of age, sex, birth order, family size, family income, and occupation of parents; (2) determine the level of attitude towards NAT; and (3) describe the degree of relationship between the following variables: school support, teachers’ support, and lastly family support for the pupils’ performance in 2012 NAT. The study used the descriptive-correlation research method to investigate the determinants of pupils’ performance in the National Achievement Test of Public Elementary Schools in the Division of Cavite City. The instrument used in data gathering was a self-structured survey. The NAT result for SY 2011-2012 provided by NETRC and DepEd Cavite City was also utilized. The statistical tools used to process and analyze the data were frequency distribution, percentage, mean, standard deviation, Kruskall Wallis, Mann-Whitney, t-test for independent samples, One-way ANOVA, and Spearman Rank Correlational Coefficient. Results revealed that there were more female students than males in the Division of Cavite City; out of 659 respondents, 345 were 11 years old and above; 390 were females; 283 were categorized as first child in the family; 371 of the respondents were from small family; 327 had Php5000 and below family income; 450 of the fathers’ respondents were non professionals; and 431 of the mothers respondents had no occupation. The attitude towards NAT, with a mean of 1.65 and SD of .485, shows that respondents considered NAT important. The school support towards NAT, with a mean of 1.89 and SD of .520, shows that respondents received school support. The pupils had a very high attitude towards teachers’ support in NAT with a mean of 1.60 and SD of .572. Family support, with t-test of 16.201 with a p-value of 0.006, shows significant at 5 percent level. Thus, the determinants of pupils’ performance in NAT in terms of family support for NAT preparation is not significant according to their family income. The grade level, with the t-test is 4.420 and a p-value of 0.000, is significant at 5 percent level. Therefore, the determinants of pupils’ performance in NAT in terms of grade level for NAT preparation vary according to their grade level. For the determinants of pupils’ performance of NAT sample test for attitude towards NAT, school support, teachers’ support, and family support were noted highly significant with a p value of 0.000.

Keywords: achievement, determinants, national, performance, public, pupils', test

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Authors: Gopal Chandra Saha, Sumanta Daw

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Warm-up is an essential component for optimizing performance in various sports before a physical fitness training session. This study investigated the immediate comparative effect of Self-Myofascial Release through vibration rolling (VR), non-vibration rolling (NVR), and static stretching as a part of a warm-up treatment on the functional fitness of young adults. Functional fitness is a classification of training that prepares the body for real-life movements and activities. For the present study 20male physical education students were selected as subjects. The age of the subjects was ranged from 20-25 years. The functional fitness variables undertaken in the present study were flexibility, muscle strength, agility, static and dynamic balance of the lower extremity. Each of the three warm-up protocol was administered on consecutive days, i.e. 24 hr time gap and all tests were administered in the morning. The mean and SD were used as descriptive statistics. The significance of statistical differences among the groups was measured by applying ‘F’-test, and to find out the exact location of difference, Post Hoc Test (Least Significant Difference) was applied. It was found from the study that only flexibility showed significant difference among three types of warm-up exercise. The observed result depicted that VR has more impact on myofascial release in flexibility in comparison with NVR and stretching as a part of warm-up exercise as ‘p’ value was less than 0.05. In the present study, within the three means of warm-up exercises, vibration roller showed better mean difference in terms of NVR, and static stretching exercise on functional fitness of young physical education practitioners, although the results were found insignificant in case of muscle strength, agility, static and dynamic balance of the lower extremity. These findings suggest that sports professionals and coaches may take VR into account for designing more efficient and effective pre-performance routine for long term to improve exercise performances. VR has high potential to interpret into an on-field practical application means.

Keywords: self-myofascial release, functional fitness, foam roller, physical education

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Authors: Ravinder Singh, Pratima Syal

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Background: The rising prevalence and incidence of Acute Pancreatitis (AP) and its associated metabolic variables known as metabolic syndrome (MetS) are common medical conditions with catastrophic consequences and substantial treatment costs. The correlation between MetS and AP, as well as their impact on Health Related Quality of Life (HRQoL) is uncertain, and because there are so few published studies, further research is needed. As a result, we planned this study to determine the relationship between MetS components impact on HRQoL in AP patients. Patients and Methods: A prospective, observational study involving the recruitment of patients with AP with and without MetS was carried out in tertiary care hospital of North India. Patients were classified with AP if they were diagnosed with two or more components of the following criteria, abdominal pain, serum amylase and lipase levels two or more times normal, imaging trans-abdominal ultrasound, computed tomography, or magnetic resonance. The National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criterion was used to diagnose the MetS. The various socio-demographic variables were also taken into consideration for the calculation of statistical significance (P≤.05) in AP patients. Finally, the correlation between AP and MetS, along with their impact on HRQoL was assessed using Student's t test, Pearson Correlation Coefficient, and Short Form-36 (SF-36). Results: AP with MetS (n = 100) and AP without MetS (n = 100) patients were divided into two groups. Gender, Age, Educational Status, Tobacco use, Body Mass Index (B.M.I), and Waist Hip Ratio (W.H.R) were the socio-demographic parameters found to be statistically significant (P≤.05) in AP patients with MetS. Also, all the metabolic variables were also found to statistically significant (P≤.05) and found to be increased in patients with AP with MetS as compared to AP without MetS except HDL levels. Using the SF-36 form, a greater significant decline was observed in physical component summary (PCS) and mental component summary (MCS) in patients with AP with MetS as compared to patients without MetS (P≤.05). Furthermore, a negative association between all metabolic variables with the exception of HDL, and AP was found to be producing deterioration in PCS and MCS. Conclusion: The study demonstrated that patients with AP with MetS had a worse overall HRQOL than patients with AP without MetS due to number of socio-demographic and metabolic variables having direct correlation impacting physical and mental health of patients.

Keywords: metabolic disorers, QOL, cost effectiveness, pancreatitis

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Authors: Mahalakshmi Vivekanandan S.

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As per the recent changes happening in the global policies, climate-related changes and the impact it causes across every sector are viewed as green swan events – in essence, climate-related changes can often happen and lead to risk and a lot of uncertainty, but needs to be mitigated instead of considering them as black swan events. This brings about a question on how this risk can be computed so that the financial institutions can plan to mitigate it. Climate-related changes impact all risk types – credit risk, market risk, operational risk, liquidity risk, reputational risk and other risk types. And the models required to compute this has to consider the different industrial needs of the counterparty, as well as the factors that are contributing to this – be it in the form of different risk drivers, or the different transmission channels or the different approaches and the granular form of data availability. This brings out the suggestion that the climate-related changes, though it affects Pillar I risks, will be a Pillar II risk. This has to be modeled specifically based on the financial institution’s actual exposure to different industries instead of generalizing the risk charge. And this will have to be considered as the additional capital to be met by the financial institution in addition to their Pillar I risks, as well as the existing Pillar II risks. In this paper, the author presents a risk assessment framework to model and assess climate change risks - for both credit and market risks. This framework helps in assessing the different scenarios and how the different transition risks affect the risk associated with the different parties. This research paper delves into the topic of the increase in the concentration of greenhouse gases that in turn cause global warming. It then considers the various scenarios of having the different risk drivers impacting the Credit and market risk of an institution by understanding the transmission channels and also considering the transition risk. The paper then focuses on the industry that’s fast seeing a disruption: the automobile industry. The paper uses the framework to show how the climate changes and the change to the relevant policies have impacted the entire financial institution. Appropriate statistical models for forecasting, anomaly detection and scenario modeling are built to demonstrate how the framework can be used by the relevant agencies to understand their financial risks. The paper also focuses on the climate risk calculation for the Pillar II Capital calculations and how it will make sense for the bank to maintain this in addition to their regular Pillar I and Pillar II capital.

Keywords: capital calculation, climate risk, credit risk, pillar ii risk, scenario modeling

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Authors: Fulya Asena Uluç, Ehsan Tuzcuoğlu, Songül Bayraktar, Burak Koca, Alper Gürarslan

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Microplastics are contaminants that are widely distributed in the environment with a detrimental ecological effect. Besides this, recent research has proved the existence of microplastics in human blood and organs. Microplastics in the environment can be divided into two main categories: primary and secondary microplastics. Primary microplastics are plastics that are released into the environment as microscopic particles. On the other hand, secondary microplastics are the smaller particles that are shed as a result of the consumption of synthetic materials in textile products as well as other products. Textiles are the main source of microplastic contamination in aquatic ecosystems. Laundry of synthetic textiles (34.8%) accounts for an average annual discharge of 3.2 million tons of primary microplastics into the environment. Recently, microfiber shedding from laundry research has gained traction. However, no comprehensive study was conducted from the standpoint of rinsing parameters during laundry to analyze microfiber shedding. The purpose of the present study is to quantify microfiber shedding from fabric under different rinsing conditions and determine the effective rinsing parameters on microfiber release in a laundry environment. In this regard, a parametric study is carried out to investigate the key factors affecting the microfiber release from a front-load washing machine. These parameters are the amount of water used during the rinsing step and the spinning speed at the end of the washing cycle. Minitab statistical program is used to create a design of the experiment (DOE) and analyze the experimental results. Tests are repeated twice and besides the controlled parameters, other washing parameters are kept constant in the washing algorithm. At the end of each cycle, released microfibers are collected via a custom-made filtration system and weighted with precision balance. The results showed that by increasing the water amount during the rinsing step, the amount of microplastic released from the washing machine increased drastically. Also, the parametric study revealed that increasing the spinning speed results in an increase in the microfiber release from textiles.

Keywords: front load, laundry, microfiber, microfiber release, microfiber shedding, microplastic, pollution, rinsing parameters, sustainability, washing parameters, washing machine

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Authors: Ezil Sam Leni, Shalen S.

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Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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Authors: Laura Rodríguez Amaya

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The impact of natural disasters on food security can be devastating, especially in rural settings where livelihoods are closely tied to their productive assets. In hazards studies, absorptive capacity is seen as a threshold that impacts the degree of people’s recovery after a natural disaster. Increasing our understanding of households’ capacity to absorb natural disaster shocks can provide the international community with viable measurements for assessing at-risk communities’ resilience to food insecurities. The purpose of this study is to identify the most important factors in determining a household’s capacity to absorb the impact of a natural disaster. This is an empirical study conducted in six communities in Costa Rica affected by earthquakes. The Earthquake Impact Index was developed for the selection of the communities in this study. The households coded as total loss in the selected communities constituted the sampling frame from which the sample population was drawn. Because of the study area geographically dispersion over a large surface, the stratified clustered sampling hybrid technique was selected. Of the 302 households identified as total loss in the six communities, a total of 126 households were surveyed, constituting 42 percent of the sampling frame. A list of indicators compiled based on theoretical and exploratory grounds for the absorptive capacity construct served to guide the survey development. These indicators were included in the following variables: (1) use of informal safety nets, (2) Coping Strategy, (3) Physical Connectivity, and (4) Infrastructure Damage. A multivariate data analysis was conducted using Statistical Package for Social Sciences (SPSS). The results show that informal safety nets such as family and friends assistance exerted the greatest influence on the ability of households to absorb the impact of earthquakes. In conclusion, communities that experienced the highest environmental impact and human loss got disconnected from the social networks needed to absorb the shock’s impact. This resulted in higher levels of household food insecurity.

Keywords: absorptive capacity, earthquake, food security, rural

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Authors: Lebeza Alemu Tenaw, Fei Wan Ngai

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Background: Postpartum depression is the most common mental health disorder that occurs after childbirth, and it is more prevalent among teenage mothers compared to adults. Although there is emerging evidence suggesting psychosocial interventions can decrease postpartum depression, there are no consistent findings regarding the effectiveness of these interventions, especially for teenage mothers. The current review aimed to investigate the effectiveness of psychosocial interventions in preventing postpartum depression among teenage mothers. Methods: The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) manual was implemented to select articles from online databases. The articles were searched using the Population, Intervention, Control, and Outcome (PICO) model. The quality of the articles was assessed using the Cochrane Collaboration Risk of Bias assessment tool. The statistical analyses were performed using Stata 17, and the effect size was estimated using the standard mean difference score of depression between the intervention and control groups. Heterogeneity between the studies was assessed through the I2 statistic and Q statistic, while the publication bias was evaluated using the asymmetry of the funnel plot and Egger's test. Results: In this systematic review, a total of nine articles were included. While psychosocial interventions demonstrated in reducing the risk of postpartum depression compared to usual maternal care, it is important to note that the mean difference score of depression was significant in only three of the included studies. The overall meta-analysis finding revealed that psychosocial interventions were effective in preventing postpartum depression, with a pooled effect size of -0.5 (95% CI: -0.95, -0.06) during the final time postpartum depression assessment. The heterogeneity level was found to be substantial, with an I2 value of 82.3%. However, no publication bias was observed. Conclusion: The review findings suggest that psychosocial interventions initiated during the late antenatal and early postnatal periods effectively prevent postpartum depression. The interventions were found to be more beneficial during the first three months of the postpartum period. However, this review also highlighted that there is a scarcity of interventional studies conducted in low-income countries, indicating the need for further studies in diverse communities.

Keywords: teenage pregnancy, postpartum depression, review

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Authors: Tsung Chin Wu, Yu Chen Tsai, Rhay Hung Weng, Weir Sen Lin

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In recent years, nursing staff’s lower job satisfaction has led to higher turnover rates, and high turnover rates not only cause medical institution costs to increase but also the quality of medical care to decrease. From the perspective of internal marketing, institution staffs are internal customers, and institutions should focus and meet the needs of staff, so that staff will strive to meet the needs of external customers and provide them with the required care. However, few previous studies have investigated the impact of internal staff satisfaction on external customers. Therefore, this study aimed to conduct job satisfaction surveys on internal staff to investigate the relationship between job satisfaction and quality of medical care through statistical analysis of the study results. The related study results may serve as a reference for healthcare managers. This study was conducted using a questionnaire and the subjects were nursing staff from four hospitals. A total of 600 questionnaires were distributed and 577 valid questionnaires were returned with a response rate of 96.1%. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The impact of internal marketing and job satisfaction on turnover intention of nursing staff was analyzed using descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. The study results showed that there was a significant difference between nursing staff’s job title and ‘professional participation’ and ‘shifts’. There was a significant difference between salary and ‘shifts’ and ‘turnover intention’, as well as between marriage and ‘remuneration’ and ‘turnover intention’. A significant difference was found between professional advancement and ‘professional growth’ and ‘type of leave’, as well as between division of service and ‘shifts’ and ‘turnover intention’. Pearson correlation analysis revealed a significant negative correlation between turnover intention and ‘internal marketing’, ‘interaction’, ‘professional participation’, ‘grasp of environment’, ‘remuneration’ and ‘shifts’, meaning that the higher the satisfaction, the lower the turnover intention. It is recommended that hospitals establish a comprehensive internal marketing mechanism to enhance staff satisfaction and in turn, reduce intention to resign, and the key to increasing job satisfaction is by establishing effective methods of internal communication.

Keywords: internal marketing, job satisfaction, turnover intention, nursing staff

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Authors: Maha A. Al-Hsayni

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Title of the Study: The Effect of Using Augmented Reality Technique in a Computer Course Unit on the Academic Achievement and Attitudes of High School Female Students. This study aimed at identifying the effect of using the Augmented Reality technique on the academic achievement of computer course at the cognitive domains (Knowledge, comprehension and analysis) with third high school female students in Holy Makkah. The researcher used: The quasi-experimental approach. The sample of the study was comprised of (55) female students in the third high school level in Holy Makkah in the second semester of the academic year 1434/1435 H. These students were assigned to two groups: The experimental group of (28) students who were taught by using the Augmented Reality technology, and the control group of (27) students, who were taught by using the traditional method. The researcher prepared a set of tools and materials, which are represented in achievement test consisted of (30) clauses, direction instrument consisted of (25) clauses and the design of augmented reality for computer study unit. The study used the following statistical methods for data analysis: Cronbach's alpha coefficient, Pearson correlation coefficient, means, standard deviations, t-test and analysis of covariance test ANCOVA. The study reached the following results: 1- There are statistically significance difference at ( 0.05) among the adjusted means of the experimental and control groups in the posttest at the domains of (Knowledge, comprehension and analysis) of third high school graders after adjusting the pretest 2- There are statistically significance difference at ( 0.05) among the means of pre and post-test for female students of the experimental group in the scale of attitude towards using Augmented Reality Technique. In the light of the study results, the researcher recommends the followings: The necessity of using Augmented Reality Technique in teaching computer courses for high school students. Furthermore, emphasizing the need to provide schools with educational halls equipped with instruments and screens that enable teachers to use the Augmented Reality in teaching the other courses. Also, the researcher suggested conducting more studies in order to improve the process of teaching and learning.

Keywords: augmented reality technique, computer course unit, academic achievement, attitudes, high school female students

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Authors: Chaoge Wang, Xiquan Weng, Yan Meng, Wentao Lin

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Objective: Cold exposure and exercise serve as two physiological stimuli to glycolipid metabolism and insulin sensitivity. So far, it remains to be elucidated whether exercise plus cold exposure can produce an addictive effect on promoting glycolipid metabolism and insulin sensitivity. Methods: 64 SD rats were subjected to high-fat and high-sugar diets for 9-week and sucessfully to establish an obesity model. They were randomly divided into 8 groups: normal control group (NC), normal exercise group (NE), continuous cold control group (CC), continuous cold exercise group (CE), acute clod control group (AC), acute cold exercise group (AE), intermittent cold control group (IC) and intermittent cold exercise group (IE). For continuous cold exposure, the rats stayed in a cold environment all day; for acute cold exposure, the rats were exposed to cold for only 4h before the end of the experiment; for intermittent cold exposure, the rats were exposed to cold for 4h per day. The protocol for treadmill runnings were as follows: 25m/min (speed), 0°C (slope), 30 mins each time, an interval for 10 mins between two runnings, twice/two days, lasting for 5 weeks. Sampling were conducted on the 5th weekend. Blood lipids, free fatty acids, blood glucose (FBG), and serum insulin (FINS) were examined, and the insulin resistance index (HOMA-IR = FBG (mmol/L)×FINS(mIU/L)/22.5) was calculated. SPSS 22.0 was used for statistical analysis of the experimental results, and the ANOVA analysis was performed between groups (p < 0.05 was significant). Results: (1) Compared with the NC group, the FBG of the rats was significantly declined in the NE, CE, AC, AE, and IE groups (p < 0.05), the FINS of the rats was significantly declined in the AE group (p < 0.05), the HOMA-IR of the rats was significantly declined in the NE, CE, AC, AE and IE groups (p < 0.05). Compared with the NE group, the FBG of the rats was significantly declined in the CE, AE, and IE groups (p < 0.05), the FINS and HOMA-IR of the rats were significantly declined in the AE group (p < 0.05). (2) Compared with the NC group, the CHO, TG, LDL-C, and FFA of the rats were significantly declined in CE and IE groups (p < 0.05), the HDL-C of the rats was significantly higher in NE, CC, CE, AE, and IE groups (p < 0.05). Compared with the NE group, the HDL-C of the rats was significantly higher in the CE and IE groups (p < 0.05). Conclusions: Sedentariness or exercise in the acute cold doesn't make sense in the treatment of type 2 diabetes, which led to one-off increases of the body's insulin sensitivity. Exercise in the continuous and intermittent cold can effectively decline the FBG, TC, TG, LDL-C, and FFA levels and increase the HDL-C level and insulin sensitivity in obese rats. These results can impact the prevention and treatment of type 2 diabetes.

Keywords: cold, exercise, insulin sensitivity, obesity

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Authors: Philipp Galkin

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Government policy is a critical factor in the understanding of energy markets. Regardless, it is rarely approached systematically from a research perspective. Gaining a precise understanding of what policies exist, their intended outcomes, geographical extent, duration, evolution, etc. would enable the research community to answer a variety of questions that, for now, are either oversimplified or ignored. Policy, on its surface, also seems a rather unstructured and qualitative undertaking. There may be quantitative components, but incorporating the concept of policy analysis into quantitative analysis remains a challenge. The KAPSARC Energy Policy Database (KEPD) is intended to address these two energy policy research limitations. Our approach is to represent policies within a quantitative library of the specific policy measures contained within a set of legal documents. Each of these measures is recorded into the database as a single entry characterized by a set of qualitative and quantitative attributes. Initially, we have focused on the major laws at the national level that regulate coal in China. However, KAPSARC is engaged in various efforts to apply this methodology to other energy policy domains. To ensure scalability and sustainability of our project, we are exploring semantic processing using automated computer algorithms. Automated coding can provide a more convenient input data for human coders and serve as a quality control option. Our initial findings suggest that the methodology utilized in KEPD could be applied to any set of energy policies. It also provides a convenient tool to facilitate understanding in the energy policy realm enabling the researcher to quickly identify, summarize, and digest policy documents and specific policy measures. The KEPD captures a wide range of information about each individual policy contained within a single policy document. This enables a variety of analyses, such as structural comparison of policy documents, tracing policy evolution, stakeholder analysis, and exploring interdependencies of policies and their attributes with exogenous datasets using statistical tools. The usability and broad range of research implications suggest a need for the continued expansion of the KEPD to encompass a larger scope of policy documents across geographies and energy sectors.

Keywords: China, energy policy, policy analysis, policy database

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Authors: Dawd Ahmed, Venkatesh Uddameri

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Agriculture in Ethiopia is the main economic sector influenced by agricultural drought. A simultaneous assessment of drought trends using multiple drought indicators is useful for drought planning and management. Intra-season and seasonal drought trends in Ethiopia were studied using a suite of drought indicators. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), and Z-index for long-rainy, dry, and short-rainy seasons are used to identify drought-causing mechanisms. The Statistical software package R version 3.5.2 was used for data extraction and data analyses. Trend analysis indicated shifts in late-season long-rainy season precipitation into dry in the southwest and south-central portions of Ethiopia. Droughts during the dry season (October–January) were largely temperature controlled. Short-term temperature-controlled hydrologic processes exacerbated rainfall deficits during the short rainy season (February–May) and highlight the importance of temperature- and hydrology-induced soil dryness on the production of short-season crops such as tef. Droughts during the long-rainy season (June–September) were largely driven by precipitation declines arising from the narrowing of the intertropical convergence zone (ITCZ). Increased dryness during long-rainy season had severe consequences on the production of corn and sorghum. PDSI was an aggressive indicator of seasonal droughts suggesting the low natural resilience to combat the effects of slow-acting, moisture-depleting hydrologic processes. The lack of irrigation systems in the nation limits the ability to combat droughts and improve agricultural resilience. There is an urgent need to monitor soil moisture (a key agro-hydrologic variable) to better quantify the impacts of meteorological droughts on agricultural systems in Ethiopia.

Keywords: autocorrelation, climate change, droughts, Ethiopia, food security, palmer z-index, PDSI, SPEI, SPI, trend analysis

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Authors: María Teresa Baquero, Ester Higueras

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One of the challenges facing 21st century cities, is their adaptation to the phenomenon of an ageing population. International policies have been developed, such as the "Global Network for Age-friendly Cities and Communities". These cities must recognize the diversity of the elderly population, and facilitate an active, healthy, satisfied aging and promote inclusion. In order to promote active and healthy aging, older people should be encouraged to engage in physical activity, sunbathe, socialize and enjoy the public open spaces in the city. Some studies recognize thermal comfort as one of the factors that most influence the use of public open spaces. However, although some studies have shown vulnerability to thermal extremes and environmental conditions in older people, there is little research on thermal comfort for older adults, because it is usually analyzed based on the characteristics of the ¨average young person¨ without considering the physiological, physical and psychological differences that characterize the elderly. This study analyzes the relationship between the microclimate parameters as air temperature, relative humidity, wind speed and sky view factor (SVF) with the personal thermal perception of older adults in three public spaces in Madrid, through a mixed methodology that combines weather measurements with interviews, made during the year 2018. Statistical test like Chi-square, Spearman, and analysis of variance were used to analyze the relationship between preference votes and thermal sensation votes with environmental and personal parameters. The results show that there is a significant correlation between thermal sensation and thermal preference with the measured air temperature, age, level of clothing, the color of clothing, season, time of the day and kind of space while no influence of gender or other environmental variables was detected. These data would contribute to the design of comfortable public spaces that improve the welfare of the elderly contributing to "active and healthy aging" as one of the 21st century challenges cities face.

Keywords: healthy ageing, older adults, outdoor public space, thermal perception

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: S. Blanchard, D. Beladjine, K. Beddiar

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Since 2015, the arrival of BIM in the building sector in France has turned the corporation world upside down. Not only constructive practices have been impacted, but also the uses and the men who have undergone important changes. Thus, the new collaborative mode generated by the BIM and the digital model has challenged the supremacy of some construction actors because the process involves working together taking into account the needs of other contributors. New BIM tools have emerged and actors in the act of building must take ownership of them. It is in this context that under the impetus of a European directive and the French government's encouragement of new missions and job profiles have. Moreover, concurrent engineering requires that each actor can advance at the same time as the others, at the whim of the information that reaches him, and the information he has to transmit. However, in the French legal system around public procurement, things are not planned in this direction. Also, a consequent evolution must take place to adapt to the methodology. The new missions generated by the BIM in France require a good mastery of the tools and the process. Also, to meet the objectives of the BIM approach, it is possible to define a typical job profile around the BIM, adapted to the various sectors concerned. The multitude of job offers using the same terms with very different objectives and the complexity of the proposed missions motivated by our approach. In order to reinforce exchanges with professionals or specialists, we carried out a statistical study to answer this problem. Five topics are discussed around the business area: the BIM in the company, the function (business), software used and BIM missions practiced (39 items). About 1400 professionals were interviewed. These people work in companies (micro businesses, SMEs, and Groups) of construction, engineering offices or, architectural agencies. 77% of respondents have the status of employees. All participants are graduated in their trade, the majority having level 1. Most people have less than a year of experience in BIM, but some have 10 years. The results of our survey help to understand why it is not possible to define a single type of BIM Manager. Indeed, the specificities of the companies are so numerous and complex and the missions so varied, that there is not a single model for a function. On the other hand, it was possible to define 3 main professions around the BIM (Manager, Coordinator and Modeler) and 3 main missions for the BIM Manager (deployment of the method, assistance to project management and management of a project).

Keywords: BIM manager, BIM modeler, BIM coordinator, project management

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Authors: Burçin Saltık, Levent Genç

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In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.

Keywords: landsat 8 (OLI-TIRS), LST, LSWI, LULC, NDVI, rice

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Authors: Abram Zoltan

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Over the past hundred years, human activities, particularly the burning of fossil fuels, have released enough carbon dioxide and other greenhouse gases to dissipate additional heat into the lower atmosphere and affect the global climate. Climate change affects many social and environmental determinants of health: clean air, safe drinking water, and adequate food. Our aim is to draw attention to the effects of climate change on the health and health care system. Improving climate awareness and the knowledge related to climate change's health impacts are essential among medical students and practicing medical doctors. Therefore, in their everyday practice, they also need some assistance and up-to-date knowledge of how climate change can endanger human health and deal with these novel health problems. Our activity, based on the cooperation of more universities, aims to develop new curriculum outlines and learning materials on climate change's health impacts for medical schools. Special attention is intended to pay to the possible preventative measures against these impacts. For all of this, the project plans to create new curriculum outlines and learning materials for medical students, elaborate methodological guidelines and create training materials for medical doctors' postgraduate learning programs. The target groups of the project are medical students, educational staff of medical schools and universities, practicing medical doctors with special attention to the general practitioners and family doctors. We had searched various surveys, domestic and international studies about the effects of climate change and statistical estimation of the possible consequences. The health effects of climate change can be measured only approximately by considering only a fraction of the potential health effects and assuming continued economic growth and health progress. We can estimate that climate change is expected to cause about 250,000 more deaths. We conclude that climate change is one of the most serious problems of the 21st century, affecting all populations. In the short- to medium-term, the health effects of climate change will be determined mainly by human vulnerability. In the longer term, the effects depend increasingly on the extent to which transformational action is taken now to reduce emissions. We can contribute to reducing environmental pollution by raising awareness and by educating the population.

Keywords: climate change, health impacts, medical students, education

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Authors: Dilek Cetin Alisar, Oya Umit Yemisci, Selin Ozen, Seyhan Sozay

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New approaches and treatment modalities are being developed to make patients more functional and independent in stroke rehabilitation. One of these approaches is transcranial direct stimulation therapy (tDCS), which aims to improve the hemiplegic upper limb function of stroke patients. tDCS therapy is not in the routine rehabilitation program; however, the studies about tDCS therapy on stroke rehabilitation was increased in recent years. Evaluate the effect of tDCS treatment on upper extremity motor function in patients with subacute stroke was aimed in our study. 32 stroke patients (16 tDCS group, 16 sham groups) who were hospitalized for rehabilitation in Başkent University Physical Medicine and Rehabilitation Clinic between 01.08.2016-20.01-2018 were included in the study. The conventional upper limb rehabilitation program was used for both tDCS and control group patients for 3 weeks, 5 days a week, for 60-120 minutes a day. In addition to the conventional stroke rehabilitation program in the tDAS group, bihemispheric tDCS was administered for 30 minutes daily. Patients were evaluated before treatment and after 1 week of treatment. Functional independence measure self-care score (FIM), Brunnstorm Recovery Stage (BRS), and Fugl-Meyer (FM) upper extremity motor function scale were used. There was no difference in demographic characteristics between the groups. There were no significant differences between BRS and FM scores in two groups, but there was a significant difference FIM score (p=0.05. FIM, BRS, and FM scores are significantly in the tDCS group, when before therapy and after 1 week of therapy, however, no difference is found in the shame group (p < 0,001). When FBS and FM scores were compared, there were statistical significant differences in tDCS group (p < 0,001). In conclusion, this randomized double-blind study showed that bihemispheric tDCS treatment was found to be superior to upper extremity motor and functional enhancement in addition to conventional rehabilitation methods in subacute stroke patients. In order for tDCS therapy to be used routinely in stroke rehabilitation, there is a need for more comprehensive, long-termed, randomized controlled clinical trials in order to find answers to many questions, such as the duration and intensity of treatment.

Keywords: cortical stimulation, motor function, rehabilitation, stroke

Procedia PDF Downloads 115

Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Larissa Pliska, Isabel Neitzel, Michael Buschermöhle, Olga Kunina-Habenicht, Ute Ritterfeld

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Visual preferences, which can be assessed using eye tracking technologies, are considered one of the defining hallmarks of Autism Spectrum Disorder (ASD). Specifically, children with ASD show a decreased preference for social images rather than geometric images compared to typically developed (TD) children. Such differences are already prevalent at a very early age and indicate the severity of the disorder: toddlers with ASD who preferred geometric images when confronted with social and geometric images showed higher ASD symptom severity than toddlers with ASD who showed higher social attention. Furthermore, the complexity of social pictures (one child playing vs. two children playing together) as well as the mode of stimulus presentation (video or image), are not decisive for the marker. The average age of diagnosis for ASD in Germany is 6.5 years, and visual preference data on this age group is missing. In the present study, we therefore investigated whether visual preferences persist into school age. We examined the visual preferences of 16 boys aged 6 to 11 with ASD and unimpaired cognition as well as TD children (1:1 matching based on children's age and the parent's level of education) within an experimental setting. Different stimulus presentation formats (images vs. videos) and different levels of stimulus complexity were included. Children with and without ASD received pairs of social and non-social images and video stimuli on a screen while eye movements (i.e., eye position and gaze direction) were recorded. For this specific use case, KIZMO GmbH developed a customized, native iOS app (KIZMO Face-Analyzer) for use on iPads. Neither the format of stimulus presentation nor the complexity of the social images had a significant effect on the visual preference of children with and without ASD in this study. Despite the tendency for a difference between the groups for the video stimuli, there were no significant differences. Overall, no statistical differences in visual preference occurred between boys with and without ASD, suggesting that gaze preference in these groups is similar at primary school age. One limitation is that the children with ASD were already receiving Autism-specific intervention. The potential of a visual preference task as an indicator of ASD can be emphasized. The article discusses the clinical relevance of this marker in elementary school children.

Keywords: autism spectrum disorder, eye tracking, hallmark, visual preference

Procedia PDF Downloads 38

Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

Procedia PDF Downloads 192

Authors: Živilė Jurgelėnė, Vitalijus Karabanovas, Augustas Morkvėnas, Reda Dzingelevičienė, Nerijus Dzingelevičius, Saulius Raugelė, Boguslaw Buszewski

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The short- and long-term effects of COVID-19 antiviral drug molnupiravir and micro/nanoplastics on the early development of Salmo trutta were investigated using accumulation and exposure studies. Salmo trutta were used as standardized test organisms in toxicity studies of COVID-19 waste contaminants. The 2D/3D imaging was performed using confocal fluorescence spectral imaging microscopy to assess the uptake, bioaccumulation, and distribution of molnupiravir and micro/nanoplastics complex in live fish. Our study results demonstrated that molnupiravir may interact with a micro/nanoplastics and modify their spectroscopic parameters and toxicity to S. trutta embryos and larvae. The 0.2 µm size microplastics at a concentration of 10 mg/L were found to be stable in aqueous media than 0.02 µm, and 2 µm sizes polymeric particles. This study demonstrated that polymeric particles can adsorb molnupiravir that are present in mixtures and modify the accumulation of molnupiravir in Salmo trutta embryos and larvae. In addition, 2D/3D confocal fluorescence imaging showed that the single polymeric particle hardly accumulates and couldn't penetrate outer tissues of the tested organism. However, co-exposure micro/nanoplastics and molnupiravir could significantly enhance the polymeric particles capability of accumulating on surface tissues and penetrating surface tissue of fish in early development. Exposure to molnupiravir at 2 g/L concentration and co-exposure to micro/nanoplastics and molnupiravir did not bring about survival changes in in the early stages of Salmo trutta development, but we observed the reduction in heart rate and decrease in gill ventilation. The statistical analysis confirmed that micro/nanoplastics used in combination with molnupiravir enhance the toxicity of the latter micro/nanoplastics to embryos and larvae. This research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: fish, micro/nanoplastics, molnupiravir, toxicity

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Authors: Puran Prasad Adhikari

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Considering the fact that when we are able to communicate science and economics effectively to broader nonprofessional audiences, it promotes a great understanding of its wider relevance to society and encourages more informed and confident decision-making at all levels, from the government to communities to individuals. The study has been conducted. This study is aimed to examine the understanding of the general public of economics and the basic sciences functioning in our surroundings in our day-to-day life. Data was gathered through historical documents related to science communication and through interviews with the public. The statistical result shows that there is a great lack of knowledge in the general public about the basic sciences and how economics impacts their life daily. The difficulties faced by the public include the view that these things can only be understood by professionals and it is beyond their capacity to grasp these concepts, the use of technical words and jargon by the professionals, and the lack of the medium to understand even if they want to learn it. The result further indicates that the lack of this basic knowledge also leads to bad decision-making, which causes frustration and anxiety. The result shows the great correlation between the confidence level of a person and the knowledge of basic science and economics. The factor behind this was the right decision-making capacity of the individual, which boosts the happy hormones of the individual. So indirectly, we found the correlation between mental health and the understanding of science and economics. The public wants to have a basic understanding and concepts of these topics, but they complain that there is no effective medium through which they can gain the understanding; the medium which is available is full of jargon and technical terms directed to professional and highly educated which they consider is beyond their reach. So, communicating the basic concepts to the general public is of great importance in the 21st century for the overall progress of society. The professional one can make this possible by considering the level of public understanding and making the communication and the programs comprehensible to the layman. Various means can be used to make this successful and effective, e.g., cartoon guide books, Q&A with the layman, animations use, and daily life examples. This study’s implication will help educators of high-level institutions and policymakers improve general public [layman] access to comprehensible knowledge.

Keywords: layman, comprehensible, decision making, frustration, confidence

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Authors: Ubon Asuquo Essien, Okwudili Bismark Ibeagwa, Daberechi Peace Ubabuko

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The Broiler Poultry subsector is dominated by small scale production with low aggregate output. The high cost of inputs currently experienced in Nigeria tends to aggravate the situation; hence many broiler farmers struggle to break-even. This study was designed to examine income and input factors in small scale deep liter broiler production in Imo state, Nigeria. Specifically, the study examined; socio-economic characteristics of small scale deep liter broiler producing Poultry farmers; estimate cost and returns of broiler production in the area; analyze input factors in broiler production in the area and examined marketability, age and profitability of the enterprise. A multi-stage sampling technique was adopted in selecting 60 small scale broiler farmers who use deep liter system from 6 communities through the use of structured questionnaire. The socioeconomic characteristics of the broiler farmers and the profitability/ marketability age of the birds were described using descriptive statistical tools such as frequencies, means and percentages. Gross margin analysis was used to analyze the cost and returns to broiler production, while Cobb Douglas production function was employed to analyze input factors in broiler production. The result of the study revealed that the cost of feed (P<0.1), deep liter material (P<0.05) and medication (P<0.05) had a significant positive relationship with the gross return of broiler farmers in the study area, while cost of labour, fuel and day old chicks were not significant. Furthermore, Gross profit margin of the farmers who market their broiler at the 8th week of rearing was 80.7%; and 78.7% and 60.8% for farmers who market at the 10th week and 12th week of rearing, respectively. The business is, therefore, profitable but at varying degree. Government and Development partners should make deliberate efforts to curb the current rise in the prices of poultry feeds, drugs and timber materials used as bedding so as to widen the profit margin and encourage more farmers to go into the business. The farmers equally need more technical assistance from extension agents with regards to timely and profitable marketing.

Keywords: broilers, factor analysis, income, small scale

Procedia PDF Downloads 53

Authors: Rigers Dodaj

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Nowadays, the environment is a critical goal for civil engineers, human activity, construction projects, economic growth, and whole national development. Regarding the development of Albania's economy, people's living standards are increasing, and the requirements for the living environment are also increasing. Under these circumstances, environmental protection and sustainability this is the critical issue. The rising industrialization, urbanization, and energy demand affect the environment by emission of carbon dioxide gas (CO2), a significant parameter known to impact air pollution directly. Consequently, many governments and international organizations conducted policies and regulations to address environmental degradation in the pursuit of economic development, for instance in Albania, the CO2 emission calculated in metric tons per capita has increased by 23% in the last 20 years. This paper analyzes the importance of civil engineering and economic growth in the sustainability of the environment focusing on CO2 emission. The analyzed data are time series 2001 - 2020 (with annual frequency), based on official publications of the World Bank. The statistical approach with vector error correction model and time series forecasting model are used to perform the parameter’s estimations and long-run equilibrium. The research in this paper adds a new perspective to the evaluation of a sustainable environment in the context of carbon emission reduction. Also, it provides reference and technical support for the government toward green and sustainable environmental policies. In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and environmental protection. Also, the study reveals that civil engineering development projects impact greatly the environment in the long run, especially in areas of flooding, noise pollution, water pollution, erosion, ecological disorder, natural hazards, etc. The potential for reducing industrial carbon emissions in recent years indicates that reduction is becoming more difficult, it needs another economic growth policy and more civil engineering development, by improving the level of industrialization and promoting technological innovation in industrial low-carbonization.

Keywords: CO₂ emission, civil engineering, economic growth, environmental sustainability

Procedia PDF Downloads 63