Search results for: USD/IDR volatility statistical analysis

Authors: Jaseel C. K., Surya M.

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The study explored the post-traumatic growth experiences among divorcees. Although research studies on post-traumatic growth (PTG) are not few in number, the ones conducted in the population are quite rare and lack depth as most of them were solely dependent on the post-traumatic growth inventory scale and its statistical analyses. A total of 10 participants were interviewed (telephonic) using a semi-structured interview schedule prepared based on the research questions and the theoretical framework of post traumatic growth. The interviews were analyzed using thematic analysis, which generated five major themes and 17 subthemes. From the analysis, it was found that enhanced interpersonal relationships, changed perceptions about love and marriage, better management of emotions, prioritization of self, increased pro-social behavior, better character strengths, etc., are the most prominent positive shifts in the lives of divorcees. It was also found that factors like good relationships, professional support, work engagement, response to social stigma, and time facilitated post-traumatic growth in the population. Another interesting finding that came out of the study was that socio-economic status, educational background, and occupational status all have a positive impact on the PTG experiences among the divorced. The results of the study can hopefully help professionals working with divorcees to impart positivity to them and facilitate post-traumatic growth.

Keywords: divorcees, meaning making, positive changes, post traumatic growth, trauma

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Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Changes in textural properties of zucchini slices under effects of frying conditions were investigated. Frying time and temperature were interested process variables like slice thickness. Slice thickness was studied at three levels (2, 3, and 4 mm). Frying process was performed at two temperature levels (160 and 180 °C) and each for five different process time periods (1, 2, 3, 5, 8 and 10 min). As frying oil sunflower oil was used. Before frying zucchini slices were thermally processes in boiling water for 90 seconds to inactivate at least 80% of plant’s enzymes. After thermal process, zucchini slices were fried in an industrial fryer at specified temperature and time pairs. Fried slices were subjected to textural profile analysis (TPA) to determine textural properties. In this extent hardness, elasticity, cohesion, chewiness, firmness values of slices were figured out. Statistical analysis indicated significant variations in the studied textural properties with process conditions (p < 0.05). Hardness and firmness were determined for fresh and thermally processes zucchini slices to compare each others. Differences in hardness and firmness of fresh, thermally processed and fried slices were found to be significant (p < 0.05). This project (113R015) has been supported by TUBITAK.

Keywords: sunflower oil, hardness, firmness, slice thickness, frying temperature, frying time

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Authors: Idris Haruna Muhammad, Okorie Austine Uche

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This paper presents a study on reliability of shear connector exposed to fire situation in accordance with Eurocode 4. The reliability analysis i reliability analysis is based on First Order Second Moment Integration Technique (FOSMIT) using FORM 5. Performance functions for shear connector are derived for normal and under fire condition and their implied safety levels are evaluated. Four (4) design variables which include ultimate tensile strength, diameter of the stud, temperature and span of the steel beam are treated as random variables with their statistical characteristic adopted from literature. Results show that for normal condition the β – value decrease from 7.95 to 5.43 which show it is conservative in safety level for normal condition. Under fire condition, β – value decrease from 2.88 to – 0.32 with corresponding load ratio of 0.2 to 1.2. It was also shown from sensitivity assessment, that the temperature and span of the beam decrease with increase in their β – values while ultimate tensile strength and diameter of the stud increase with increase in their β – values for a given load ratio of 0.2 to 1.2.

Keywords: Composite steel beam, Fire condition, Shear stud, Sensitivity study

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Authors: Alexis Dorado, Aralyn Quintos

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This study explores the utilization of natural dyes for wood stains as a transformative agent for wood, encompassing color alteration, grain enhancement, and protection against harm. Commonly, wood stains are petroleum-based and synthetically derived. Notably, commercially accessible wood stains exhibit around 4% greater volatility than the formulated wood stain (FWS), potentially indicating a heightened environmental impact. The application of FWS does not significantly affect the performance of polyurethane varnish. The impact of incorporating an FWS when was applied to Gmelina arborea wood sample, the initial lightness value (L*) of 68.5, a* 7.7, b* 29.2 decreased to 44.36, a* 23.49, b* 32.60, where a* denotes the red/ green value, b* denotes the yellow/ blue, indicating a shift towards darker shades. This alteration in lightness suggests that the FWS contains compounds or pigments that effectively absorb or scatter light, resulting in a change in the perceived color and visual appearance of the wood surface. Moreover, the successful formulation of an eco-friendly natural wood stain is detailed, presenting a promising alternative. This method finds applicability in the domains of furniture and handicraft creation, offering a sustainable choice for creative artisans.

Keywords: formulated wood stain (FWS), natural dyes, wood stains, eco-friendly natural wood stain,

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Authors: Mimoza Canga, Alketa Qafmolla, Vergjini Mulo, Irene Malagnino

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Aim: Assessment of oral health in young people aged 18-29 years after the Covid-19 pandemic in Albania. Materials and methods: The present study was conducted at the University of Medicine in Tirana, Albania, from March 2023 to September 2023. This is s cross-sectional study. In our research, 104 students participated, of which 64 were females (61.5%) and 40 were males (38.5%). In the present survey, the participants were divided into four age groups: 18-20, 21-23, 24-26, and 27-29 years old. Majority of the sample (69%) were 18-20 years. Participants were instructed to complete the questionnaire. The study had no dropouts. The current study was conducted in accordance to Helsinki declaration. Statistical analysis was performed using IBM SPSS Statistics Version 23.0, Microsoft Windows Linux, Chicago, IL, USA. Data were analyzed using analysis of variance (ANOVA). P ≤ 0.05 was considered statistically significant. Results: This study reported that 80 (76.9%) of the participants had passed Covid-19, while 24 (23.1%) of them had not passed Covid-19. Based on our data analysis, 70 (67.3%) of the participants had symptoms such as of fever 38°C- 40.5°C and headache. They stated that were treated with Azithromycin 500 mg tablets, Augmentin 625 mg tablets, Vitamin C 1000 mg, Magnesium, and Vitamin D. 40(38.4%) of the participants noticed hypersensitivity in gums (p = 0.004) and sensitive teeth (p = 0.001) after having passed Covid-19 compared to pre-pandemic. Nearly 40 (38.4%) of the participants who passed Covid-19 were treated with painful relievers for the gums and teeth, such as ibuprofen (Advil), used Sensodyne Toothpaste for sensitive teeth and Clove oil. Conclusion: Within the limitations of this study conducted in Albania, can concluded that Covid-19 has a direct impact on oral health.

Keywords: albania, Covid19, cross-sectional study, oral health

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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Authors: S. Aberkane, N. Djabali, S. Fafi, A. Baghezza

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Chronic illnesses affect many Algerians. It is possible to investigate the impact of illness representations and coping on quality of life and whether illness representations are indirectly associated with quality of life through their influence on coping. This study aims at investigating the relationship between illness perception, coping strategies and quality of life with chronic illness. Illness perceptions are indirectly associated with the quality of life through their influence on coping mediation. A sample of 316 participants with chronic illness living in the region of Batna, Algeria, has been adopted in this study. A correlation statistical analysis is used to determine the relationship between illness perception, coping strategies, and quality of life. Multiple regression analysis was employed to highlight the predictive ability of the dimensions of illness perception and coping strategies on the dependent variables of quality of life, where mediation analysis is considered in the exploration of the indirect effect significance of the mediator. This study provides insights about the relationship between illness perception, coping strategies and quality of life in the considered sample (r = 0.39, p < 0.01). Therefore, it proves that there is an effect of illness identity perception, external and medical attributions related to emotional role, physical functioning, and mental health perceived, and these were fully mediated by the asking for assistance (c’= 0.04, p < 0.05), the guarding (c’= 0.00, p < 0.05), and the task persistence strategy (c’= 0.05, p < 0.05). The findings imply partial support for the common-sense model of illness representations in a chronic illness population. Directions for future research are highlighted, as well as implications for psychotherapeutic interventions which target unhelpful beliefs and maladaptive coping strategies (e.g., cognitive behavioral therapy).

Keywords: chronic illness, coping, illness perception, quality of life, self- regulation model

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Authors: Riyadh Alsultani, Ali Majdi

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It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

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Authors: A. A. Betah

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This research was performed to evaluate the attitudes of rural women towards education, health and work outside the home. The study was based on a random sample of 147 rural women, Kafr-Rahmaniyah village was chosen for the study because its life expectancy at birth for females, education and percentage of females in the labor force, were the highest in the district. The study data were collected from rural female respondents, using a face-to-face questionnaire. In addition, the study estimated several factors like age, main occupation, family size, monthly household income, geographic cosmopolites, and degree of social participation for rural women respondents. Using Statistical Package for the Social Sciences (SPSS), data were analyzed by non-parametric statistical methods. The main finding in this study was a significant relationship between each of the previous variables and each of rural women’s attitudes toward education, health, and work outside home. The study concluded with some recommendations. The most important element is ensuring attention to rural women’s needs, requirements and rights via raising their health awareness, education and their contributions in their society.

Keywords: attitudes, education, health, rural women, work outside home

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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: Punam Kumari Mandal, Namita Yangden, Bhumika Rai, Achala Niraula, Sabitra Subedi

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introduction: Family planning not only improves women’s health but also promotes gender equality, better child health, and improved education outcomes, including poverty reduction. The objective of this study is to assess the utilization of family planning methods and associated factors in Sunsari, Nepal. methodology: A cross-sectional analytical study was conducted among women of the reproductive age group (15-49 years) in Sunsari in 2020. Nonprobability purposive sampling was used to collect information from 212 respondents through face-to-face interviews using a Semi-structured interview schedule from ward no 1 of Barju rural municipality. Data processing was done by using SPSS “statistics for windows, version 17.0(SPSS Inc., Chicago, III.USA”). Descriptive analysis and inferential analysis (binary logistic regression) were used to find the association of the utilization of family planning methods with selected demographic variables. All the variables with P-value <0.1 in bivariate analysis were included in multivariate analysis. A P-value of <0.05 was considered to indicate statistical significance at a level of significance of 5%. results: This study showed that the mean age and standard deviation of the respondents were 26±7.03, and 91.5 % of respondent’s age at marriage was less than 20 years. Likewise, 67.5% of respondents use any methods of family planning, and 55.2% of respondents use family planning services from the government health facility. Furthermore, education (AOR 1.579, CI 1.013-2.462)., husband’s occupation (AOR 1.095, CI 0.744-1.610)., type of family (AOR 2.741, CI 1.210-6.210)., and no of living son (AOR 0.259 CI 0.077-0.872)are the factors associated with the utilization of family planning methods. conclusion: This study concludes that two-thirds of reproductive-age women utilize family planning methods. Furthermore, education, the husband’s occupation, the type of family, and no of living sons are the factors associated with the utilization of family planning methods. This reflects that awareness through mass media, including behavioral communication, is needed to increase the utilization of family planning methods.

Keywords: family planning methods, utilization. factors, women, community

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Authors: Isyaku Labaran Fagge

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This study investigated on appraisal of civil servants level of participation in recreational activities in North Western States of Nigeria. To achieve this purpose, a descriptive survey was employed for the designed questionnaire which were administered on 300 respondents, who served as subject for this study, in North Western States of Nigeria. Descriptive statistics of simple frequency count, percentage and Chi square (x2) statistical techniques at 0.05 alpha level were used for all statistical tests of significance. The findings of the study revealed that senior civil servants by (gender, status and location) do participate in recreational activities. On the knowledgeable personnels, all the recreational centres (by gender, status and location) had no knowledgeable personnels to handle the centres across North Western States. Many recreational centers should be create. Government should train and employ more knowledgeable personnel to handle the centres. Civil servants in urban areas do participate more than the civil servants in rural areas.

Keywords: recreation, civil servants, participation, recreational activities

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Authors: Kang-Mo Jung

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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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Authors: Marc S. Paolella, Pawel Polak

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The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

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Authors: T. Qasim, M. Obeidat, S. Al-Sharairi

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The objective of this study is to investigate the effect of the excessive use of smartphones. Smartphones have enormous effects on the human body in that some musculoskeletal disorders (MSDs) and health problems might evolve. These days, there is a wide use of the smartphones among all age groups of society, thus, the focus on smartphone effects on human behavior and health, especially on the young and elderly people, becomes a crucial issue. This study was conducted in Jordan on smartphone users for different genders and ages, by conducting a survey to collect data related to the symptoms and MSDs that are resulted from the excessive use of smartphones. A total of 357 responses were used in the analysis. The main related symptoms were numbness, fingers pain, and pain in arm, all linked to age and gender for comparative reasons. A statistical analysis was performed to find the effects of extensive usage of a smartphone for long periods of time on the human body. Results show that the significant variables were the vision problems and the time spent when using the smartphone that cause vision problems. Other variables including age of user and ear problems due to the use of the headsets were found to be a border line significant.

Keywords: smart phone, age group, musculoskeletal disorders (MSDs), health problems

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Authors: Shannon Steinmetz, Ellen Gethner

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In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.

Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2022 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decision-making and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical regression

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Authors: Aboozar Dehghan, S. Sharifi, A. Ardeshiri, F. Jafari, F. Samani

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Ultrasonography is a safe, particular, available and easy to use method to evaluate soft tissues. Tendons play the main role to body locomotors system. Ultrasonography performed in tarsus and metatarsus region of rare limb of eight adult, Dromedary camels (camelus dromedaries) in both sex. Clinical examination and gate analysis was performed before slaughtering. From the tarsus to the 1st phalanx was divided to 4 equal region include 1a, 2a, 1b and 2b. Flexor surface was clipped and covered by enough ultrasonography gel. Ultrasonography was performed by linear phased array 8-12 Mhz transducer in transverse and longitudinal section and Superficial digital flexor tendon (SDFT), deep digital flexor tendon (DDFT) and suspensory ligament (SL) were imaged. Echogenicity and diameter of these structures were recorded. Size of tendons and SL measured after necropsy too. statistical analysis obtained that SDFT diameter larger than others in all described regions and mean of DDFT diameter larger than suspensory ligament. Echogenicity of SL more than SDFT and DDFT. No Significant relationship was seen between left and right rare limb structures size. Between sex and tendons and SL diameter, significant relationship not seen.

Keywords: dromedary camel, tars and metatars, ultrasonography

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Authors: Hosseini Siahi Zohreh, Sana Mohammad Jafar

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With increase in fat and over weight in children and its undesirable effects on different organisms of the body and since many of the sicknesses are due to over weight and with losing weight these sicknesses disappear, and on the other hand with mal nutrition and under weight in children other kind of sicknesses such as derogation of body's security system, frequent infection, insufficient growth, shortness, and delay in maturity etc. are some of the signs of being under weight. Therefore recognition of signs of over weight and under weight and their prevalence in children are important. To determine this difficulty we have used the body mass index as screening tool since it is very prevalent and a good and important guide and has very good relation with body fat in children. In this study 2321 students from primary schools in Behbahan have been chosen randomly and evaluated by height and weight and their body mass index have been calculated and then recorded on the BMI percentile diagram which is for age and gender. The following results obtained: The amount of total fat, over weight and slimness are 9.3, 12.1 and 12.32 percent respectively. Therefore 21.4% of the children were over weighted. It did not show any meaningful statistical relation in fat conditions among boys and girls, but there has been a meaningful statistical relation in slimness among boys and girls.

Keywords: assessment, students, Behbahan, Body Mass Index

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Authors: Diego F. Carrillo-González, Milena Osorio, Natalia M. Cerro, Yasser Y. Lenis

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Introduction: mortality during the implantation and early embryonic development periods reach around 30% in different mammalian species. It has been described that progesterone (P4) and Arginine (Arg) play a beneficial role in establishing and maintaining early pregnancy in mammals. The combined effect between Arg and P4 on reproductive parameters in the rabbit species is not yet elucidated, to our best knowledge. Objective: to assess the effect of L-arginine and progesterone during the post-breeding period in female rabbits on the composition of the amniotic fluid, the placental structure, and the bone growth in their fetuses. Methods: crossbred female rabbits (n=16) were randomly distributed into four experimental groups (Ctrl, Arg, P4, and Arg+P4). In the control group, 0.9% saline solution was administered as a placebo, the Arg group was administered arginine (50 mg/kg BW) from day 4.5 to day 19 post-breeding, the P4 group was administered progesterone (Gestavec®, 1.5 mg/kg BW) from 24 hours to day 4 post-breeding and for the Arg+P4 group, an administration was performed under the same time and dose guidelines as the Arg and P4 treatments. Four females were sacrificed, and the amniotic fluid was collected and analyzed with rapid urine test strips, while the placenta and fetuses were processed in the laboratory to obtain histological plates. The percentage of deciduous, labyrinthine, and junctional zones was determined, and the length of the femur for each fetus was measured as an indicator of growth. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, A one-way analysis of variance (ANOVA) was performed, and a comparison of means was conducted by Tukey's test. Results: a higher density (p<0.05) was observed in the amniotic fluid for fetuses in the control group (1022±2.5g/mL) compared to the P4 (1015±5.3g/mL) and Arg+P4 (1016±4,9g/mL) groups. Additionally, the density of amniotic fluid in the Arg group (1021±2.5g/mL) was higher (p<0.05) than in the P4 group. The concentration of protein, glucose, and ascorbic acid had no statistical difference between treatments (p>0.05). The histological analysis of the uteroplacental regions, a statistical difference (p<0,05) in the proportion of deciduous zone was found between the P4 group (9.6±2.6%) when compared with the Ctrl (28.15±12.3%), and Arg+P4 (26.3±4.9) groups. In the analysis of the fetuses, the weight was higher for the Arg group (2.69±0.18), compared to the other groups (p<0.05), while a shorter length was observed (p<0.05) in the fetuses for the Arg+P4 group (25.97±1.17). However, no difference (p>0.05) was found when comparing the length of the developing femurs between the experimental groups. Conclusion: the combination of L-arginine and progesterone allows a reduction in the density of amniotic fluid, without affecting the protein, energy, and antioxidant components. However, the use of L-arginine stimulates weight gain in fetuses, without affecting size, which could be used to improve production parameters in rabbit production systems. In addition, the modification in the deciduous zone could show a placental adaptation based on the fetal growth process, however more specific studies on the placentation process are required.

Keywords: arginine, progesterone, rabbits, reproduction

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Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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Authors: Befekadu Urga Wakayo

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Introduction: Bacterial infections represent major human and animal health problems in Ethiopia. In the face of poor antibiotic regulatory mechanisms, development of antimicrobial resistance (AMR) to commonly used drugs has become a growing health and livelihood threat in the country. Monitoring and control of AMR demand close coloration between human and veterinary services as well as other relevant stakeholders. However, risk of AMR transfer from animal to human population’s remains poorly explored in Ethiopia. This systematic research literature review attempted to give an overview on AMR challenges of bovine mastitis bacteria in Ethiopia. Methodology: A web based research literature search and analysis strategy was used. Databases are considered including; PubMed, Google Scholar, Ethiopian Veterinary Association (EVA) and Ethiopian Society of Animal Production (ESAP). The key search terms and phrases were; Ethiopia, dairy, cattle, mastitis, bacteria isolation, antibiotic sensitivity and antimicrobial resistance. Ultimately, 15 research reports were used for the current analysis. Data extraction was performed using a structured Microsoft Excel format. Frequency AMR prevalence (%) was registered directly or calculated from reported values. Statistical analysis was performed on SPSS – 16. Variables were summarized by giving frequencies (n or %), Mean ± SE and demonstrative box plots. One way ANOVA and independent t test were used to evaluate variations in AMR prevalence estimates (Ln transformed). Statistical significance was determined at p < 0.050). Results: AMR in bovine mastitis bacteria was investigated in a total of 592 in vitro antibiotic sensitivity trials involving 12 different mastitis bacteria (including 1126 Gram positive and 77 Gram negative isolates) and 14 antibiotics. Bovine mastitis bacteria exhibited AMR to most of the antibiotics tested. Gentamycin had the lowest average AMR in both Gram positive (2%) and negative (1.8%) bacteria. Gram negative mastitis bacteria showed higher mean in vitro resistance levels to; Erythromycin (72.6%), Tetracycline (56.65%), Amoxicillin (49.6%), Ampicillin (47.6%), Clindamycin (47.2%) and Penicillin (40.6%). Among Gram positive mastitis bacteria higher mean in vitro resistance was observed in; Ampicillin (32.8%), Amoxicillin (32.6%), Penicillin (24.9%), Streptomycin (20.2%), Penicillinase Resistant Penicillin’s (15.4%) and Tetracycline (14.9%). More specifically, S. aurues exhibited high mean AMR against Penicillin (76.3%) and Ampicillin (70.3%) followed by Amoxicillin (45%), Streptomycin (40.6%), Tetracycline (24.5%) and Clindamycin (23.5%). E. coli showed high mean AMR to Erythromycin (78.7%), Tetracycline (51.5%), Ampicillin (49.25%), Amoxicillin (43.3%), Clindamycin (38.4%) and Penicillin (33.8%). Streptococcus spp. demonstrated higher (p =0.005) mean AMR against Kanamycin (> 20%) and full sensitivity (100%) to Clindamycin. Overall, mean Tetracycline (p = 0.013), Gentamycin (p = 0.001), Polymixin (p = 0.034), Erythromycin (p = 0.011) and Ampicillin (p = 0.009) resistance increased from the 2010’s than the 2000’s. Conclusion; the review indicated a rising AMR challenge among bovine mastitis bacteria in Ethiopia. Corresponding, public health implications demand a deeper, integrated investigation.

Keywords: antimicrobial resistance, dairy cattle, Ethiopia, Mastitis bacteria

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

Abstract:

Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Abdul Rauf, Xiaoxing Liu, Rizwan Qaisar Danish, Waqas Amin

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The core intention of this study is to analyze the linkage of training, job attitudes and motivation through a mediation model in the banking sector of Pakistan. Moreover, this study is executed to answer a range of queries regarding the consideration of employees about training, job satisfaction, motivation and organizational commitment. Hence, the association of training with job satisfaction, job satisfaction with motivation, organizational commitment with job satisfaction, organization commitment as independently with motivation and training directly related to motivation is determined in this course of study. A questionnaire crafted for comprehending the purpose of this study by including four variables such as training, job satisfaction, motivation and organizational commitment which have to measure. A sample of 450 employees from seventeen private (17) banks and two (2) public banks was taken on the basis of convenience sampling from Pakistan. However, 357 questionnaires, completely filled were received back. AMOS used for assessing the conformity factor analysis (CFA) model and statistical techniques practiced to scan the collected data (i.e.) descriptive statistics, regression analysis and correlation analysis. The empirical findings revealed that training and organizational commitment has a significant and positive impact directly on job satisfaction and motivation as well as through the mediator (job satisfaction) also the impact sensing in the same way on the motivation of employees in the financial Banks of Pakistan. In this research study, the banking sector is under discussion, so the findings could not generalize on other sectors such as manufacturing, textiles, telecom, and medicine, etc. The low sample size is also the limitation of this study. On the foundation of these results the management fascinates to make the revised strategies regarding training program for the employees as it enhances their motivation level, and job satisfaction on a regular basis.

Keywords: job satisfaction, motivation, organizational commitment, Pakistan, training

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Authors: Gulnaz Erkomaishvili

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Introduction. One of the most important issues of state economic policy in the 21st century is the problem of environmental protection. The Georgian government considers the green economy as one of the most important means of sustainable economic development and takes the initiative to implement voluntary measures to promote sustainable development. In this context, it is important to promote the development of ecosystem services, clean production, environmental education and green jobs.The development of the green economy significantly reduces the inefficient use of natural resources, waste generation, emissions into the atmosphere and the discharge of untreated water into bodies of water.It is, therefore, an important instrument in the environmental orientation of sustainable development. Objectives.The aim of the paper is to analyze the current status of the green economy in Georgia and identify effective ways to improve the environmental, economic policy of sustainable development. Methodologies: This paper uses general and specific methods, in particular, analysis, synthesis, induction, deduction, scientific abstraction, comparative and statistical methods, as well as experts’ evaluation. bibliographic research of scientific works and reports of organizations was conducted; Publications of the National Statistics Office of Georgia are used to determine the regularity between analytical and statistical estimations. Also, theoretical and applied research of international organizations and scientist-economists are used. Contributions: The country should implement such an economic policy that ensures the transition to a green economy, in particular, revising water, air and waste laws, strengthening existing environmental management tools and introcing new tools (including economic tools). Perfecting the regulatory legal framework of the environmental impact assessment system, which includes the harmonization of Georgian legislation with the requirements of the European Union. To ensure the protection and rational use of Georgia's forests, emphasis should be placed on sustainable forestry, protection and restoration of forests.

Keywords: green economy, environmental protection, environmental protection economic policy, environmental protection policy challanges

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Authors: Shreya Borthakur, Aastha Vartak

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This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education.

Keywords: RSVP, attention, visual processing, attentional blink, EEG

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Ozgu Turgut

Abstract:

Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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