Search results for: weighted risk scores

Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Kishore K. Pochampally

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The success of a supply chain heavily relies on the efficiency of the suppliers involved. In this paper, we propose a neural network approach to evaluate the efficiency of a supplier, which is being considered for inclusion in a supply chain, using the available linguistic (fuzzy) data of suppliers that already exist in the supply chain. The approach is carried out in three phases, as follows: In phase one, we identify criteria for evaluation of the supplier of interest. Then, in phase two, we use performance measures of already existing suppliers to construct a neural network that gives weights (importance values) of criteria identified in phase one. Finally, in phase three, we calculate the overall rating of the supplier of interest. The following are the major findings of the research conducted for this paper: (i) linguistic (fuzzy) ratings of suppliers such as 'good', 'bad', etc., can be converted (defuzzified) to numerical ratings (1 – 10 scale) using fuzzy logic so that those ratings can be used for further quantitative analysis; (ii) it is possible to construct and train a multi-level neural network in order to determine the weights of the criteria that are used to evaluate a supplier; and (iii) Borda’s rule can be used to group the weighted ratings and calculate the overall efficiency of the supplier.

Keywords: fuzzy data, neural network, supplier, supply chain

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Delva Richard, Zahibo Narcisse, Yalciner Ahmet

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The Republic of Haiti is one of the poor countries of the world, therefore the authorities must make choices to provide timely solutions to the many difficulties that this Caribbean country is experiencing. There is a very acute lack of scientific research to study natural phenomena in depth. A working group meeting was established under the aegis of the World Bank, UNESCO and the authorities, to study the level of exposure of the Hispaniola. The devastating earthquake of August 2021 killed about 2100 and caused massive material damage; and the 14 12 January 2010 killed more than 250,000 people and caused massive material damage, the evidence of which is still 11 years later. In this paper we want to contribute to the assessment of the risk of tsunami on the southern peninsula of the Republic of Haiti. For the realization of this work we have the bathymetric and topographic data of very good qualities from the private measurement campaigns that we have combined with GEBCO for the inundation grids. We use two numerical models MOST and NAMI DANCE for the calculation of the parameters required in any tsunami risk assessment.

Keywords: modélisation numérique, ondes longues océaniques, bathymetrie, evaluation risque, tsunamis

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Riona Dighe

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This research attempts to identify an alternative approach to the measurement of Gross National Happiness (GNH). It uses artificial intelligence (AI), incorporating natural language processing (NLP) and sentiment analysis to measure GNH. We use ‘off the shelf’ NLP models responsible for the sentiment analysis of a sentence as a building block for this research. We constructed an algorithm using NLP models to derive a sentiment analysis score against sentences. This was then tested against a sample of 20 respondents to derive a sentiment analysis score. The scores generated resembled human responses. By utilising the MLP classifier, decision tree, linear model, and K-nearest neighbors, we were able to obtain a test accuracy of 89.97%, 54.63%, 52.13%, and 47.9%, respectively. This gave us the confidence to use the NLP models against sentences in websites to measure the GNH of a country.

Keywords: artificial intelligence, NLP, sentiment analysis, gross national happiness

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Sepehr Moradi, Mehdi Asadi Rad

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This study is to evaluate the live weight of adult pigeons to investigate about their sex, race, their mutual effects and some auxiliary variables in 4 races of Kabood, Tizpar, Parvazy, and Namebar. In this paper, 152 pieces of pigeons as 76 male and female pairs with equal age are studied randomly. Then the birds were weighted by a scale with one gram precision. Software was used for statistical analysis. Mean live weight of adult male and female pigeons in 4 races (Kabood, Tizpar, Parvazy and Namebar with (15, 20, 20, 21) and (20, 21, 18, 17) records were, (530±56, 388.75±32, 392±34, 552±48) and (446±34, 342±32, 341±46, 457±57) gr, respectively. Difference weight of adult live of male with female was significant in 1% level (P < 0.01). Difference live weight of male adult pigeon was significant in 5% level (P < 0.05). Different live weight of female adult pigeon between Kabood, Parvazy and Tizpar races were significant in 5% level (P < 0.05) but mean live weight Kabood race with Namebar race and Parvazy with Tizpar were not significant. The results showed that most and least mean live weights belonged to Namebar of the male pigeon race and Parvazy of the female pigeon race.

Keywords: Iranian Native Pigeons, adult weight, live weight, adult pigeons

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Authors: Rajkumar Ghosh

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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: Foozhan Gharehkhani

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Global concerns regarding food safety and quality, especially in the wake of industrial development and increasing environmental pollution, are expanding rapidly. One of the primary concerns is the contamination of meat products such as sausages, mortadella, and hamburgers with heavy metals, which may be transferred to these products from various sources, including environmental pollution, metallic equipment, and protective coatings. Protective coatings, such as metal cans and packaging layers, especially under conditions such as corrosion, high temperatures, or long-term storage, can act as primary sources for the transfer of heavy metals to these products. Metals such as lead (Pb), cadmium (Cd), and tin (Sn) are among the contaminants that can enter food products from these sources. This study was conducted to assess the level of heavy metal contamination in 200 samples of sausages, mortadella, and hamburgers produced by various companies. The samples were randomly collected from local markets and production sites and were then processed using an acid digestion method combined with nitric acid and hydrogen peroxide. The concentration of heavy metals was measured using atomic absorption spectrometry (AAS). The results of this study showed that the average concentrations of lead, cadmium, and tin were 0.08, 0.03, and 110 mg/kg, respectively, and in 15% of the samples, the levels of lead and cadmium exceeded the maximum allowable limits set by the WHO (0.1 mg/kg for lead and 0.05 mg/kg for cadmium). The data were analyzed and compared using ANOVA and independent T-tests in SPSS software. Additionally, to assess the health risk for consumers, the Hazard Quotient (HQ) was calculated, which was found to be above the acceptable limit (HQ > 1) in some samples, indicating potential risks to consumer health. These findings emphasize the need for more rigorous monitoring of production processes, packaging, and raw material selection to prevent contamination with heavy metals in food products.

Keywords: heavy metal contamination, health risk assessment, sources of contamination, various Iranian companies

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Authors: Sai Hung Cheung, Zhe Shao

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It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Sara De Pelsmaeker, Catarina Ferreira da Silva, Janne Prawit

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Recent studies show that enzymatically hydrolysed collagen is absorbed and distributed to joint tissues, where it has analgesic and active anti-inflammatory properties. Reviews of the associated relevant literature also support this theory. However, these studies are all using hydrolyzed collagen from animal hide or skin. This study looks into the effect of daily supplementation of hydrolyzed cartilage collagen (HCC), which has a different composition. A consumer study was set up using a double-blind placebo-controlled design with a control group using twice a day 0.5gr of maltodextrin and an experimental group using twice 0.5g of HCC, over a trial period of 12 weeks. A follow-up phase of 4 weeks without supplementation was taken into the experiment to investigate the ‘wash-out’ phase. As this consumer study was conducted during the lockdown periods, a specific app was designed to follow up with the participants. The app had the advantage that in this way, the motivation of the participants was enhanced and the drop-out range of participants was lower than normally seen in consumer studies. Participants were recruited via various sports and health clubs across the UK as we targeted a general population of people that considered themselves in good health. Exclusion criteria were ‘not experiencing any medical conditions’ and ‘not taking any prescribed medication’. A minimum requirement was that they regularly engaged in some level of physical activity. The participants had to log the type of activity that they conducted and the duration of the activity. Weekly, participants were providing feedback on their joint health and subjective pain using the validated pain measuring instrument Visual Analogue Scale (VAS). The weekly repoAbstract Public Health and Wellbeing Conferencerting section in the app was designed with simplicity and based on the accuracy demonstrated in previous similar studies to track subjective pain measures of participants. At the beginning of the trial, each participant indicated their baseline on joint pain. The results of this consumer study indicated that HCC significantly improved joint health and subjective pain scores compared to the placebo group. No significant differences were found between different demographic groups (age or gender). The level of activity, going from high intensive training to regular walking, did not significantly influence the effect of the HCC. The results of the wash-out phase indicated that when the participants stopped the HCC supplementation, their subjective pain scores increased again to the baseline. In conclusion, the results gave a positive indication that the daily supplementation of HCC can contribute to the overall mobility and wellbeing of a general active population

Keywords: VAS-score, food supplement, mobility, joint health

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Authors: Woolfrey K., Woolfrey M., Bolton C. L., Warchuk D.

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Objectives: Osteoarthritis is the most common joint disease of adults worldwide. Despite total knee arthroplasty (TKA) demonstrating high levels of success, 20% of patients report dissatisfaction with their result. VOXX Wellness Stasis Socks are embedded with a proprietary pattern of neuro-receptor activation points that have been proven to activate a precise neuro-response, according to the pattern theory of haptic perception, which stimulates improvements in pain and function. The use of this technology in TKA patients may prove beneficial as an adjunct to recovery as many patients suffer from deficits to their proprioceptive system caused by ligamentous damage and alterations to mechanoreceptors during the procedure. We hypothesized that VOXX Wellness Stasis Socks are a safe, cost-effective, and easily scalable strategy to support TKA patients through their recovery. Design: Double-blinded, placebo-controlled randomized trial. Participants: Patients scheduled to receive TKA were considered eligible for inclusion in the trial. Interventions: Intervention group (I): VOXX Wellness Stasis socks containing receptor point-activation technology. Control group (C): VOXX Wellness Stasis socks without receptor point-activation technology. Sock use during the waking hours x 6 weeks. Main Outcome Measures: Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) questionnaire completed at baseline, 2 weeks, and 6 weeks to assess pain, stiffness, and physical function. Results: Data analysis using SPSS software. P-values, effect sizes, and confidence intervals are reported to assess clinical relevance of the finding. Physical status classifications were compared using t-test. Within-subject and between-subject differences in the mean WOMAC were analyzed by ANOVA. Effect size was analyzed using Cramer’s V. Consistent improvement in WOMAC scores for pain and stiffness at 2 weeks post op in the I over the C group. The womac scores assessing physical function showed a consistent improvement at both 2 and 6 weeks post op in the I group compared to C group. Conclusions: VOXX proved to be a low cost, safe intervention in TKA to help patients improve with regard to pain, stiffness, and physical function. Disclosures: None

Keywords: osteoarthritis, RCT, pain management, total knee arthroplasty

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Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

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Authors: Peng Guo

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Objective: This study investigates the clinical characteristics of sleep disorders (SD) in patients with Alzheimer's disease (AD) and their relationship with cognitive impairment. Methods: According to the inclusion and exclusion criteria of AD, 460 AD patients were consecutively included in Beijing Tiantan Hospital from January 2016 to April 2022. Demographic data, including gender, age, age of onset, course of disease, years of education and body mass index, were collected. The Pittsburgh sleep quality index (PSQI) scale was used to evaluate the overall sleep status. AD patients with PSQI ≥7 was divided into AD with SD (AD-SD) group, and those with PSQI < 7 were divided into AD with no SD (AD-nSD) group. The overall cognitive function of AD patients was evaluated by the scales of Mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA), memory was evaluated by the AVLT-immediate recall, AVLT-delayed recall and CFT-delayed memory scales, the language was evaluated by BNT scale, visuospatial ability was evaluated by CFT-imitation, executive function was evaluated by Stroop-A, Stroop-B and Stroop-C scales, attention was evaluated by TMT-A, TMT-B, and SDMT scales. The correlation between cognitive function and PSQI score in AD-SD group was analyzed. Results: Among the 460 AD patients, 173 cases (37.61%) had SD. There was no significant difference in gender, age, age of onset, course of disease, years of education and body mass index between AD-SD and AD-nSD groups (P>0.05). The factors with significant difference in PSQI scale between AD-SD and AD-nSD groups include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleeping medication and daytime dysfunction (P<0.05). Compared with AD-nSD group, the total scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales in AD-SD group were significantly lower（P＜0.01，P＜0.01，P＜0.01，P＜0.05）. In AD-SD group, subjective sleep quality was significantly and negatively correlated with the scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales (r=-0.277，P=0.000; r=-0.216，P=0.004; r=-0.253，P=0.001; r=-0.239, P=0.004), daytime dysfunction was significantly and negatively correlated with the score of AVLT-immediate recall scale (r=-0.160，P=0.043). Conclusion The incidence of AD-SD is 37.61%. AD-SD patients have worse subjective sleep quality, longer time to fall asleep, shorter sleep time, lower sleep efficiency, severer nighttime SD, more use of sleep medicine, and severer daytime dysfunction. The overall cognitive function, immediate recall and visuospatial ability of AD-SD patients are significantly impaired and are closely correlated with the decline of subjective sleep quality. The impairment of immediate recall is highly correlated with daytime dysfunction in AD-SD patients.

Keywords: Alzheimer's disease, sleep disorders, cognitive impairment, correlation

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Authors: Cristina Cirone, Katrina Cirone, Monali S. Malvankar-Mehta

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Purpose: An increased risk of visual impairment has been observed in individuals lacking a balanced diet. The purpose of this paper is to characterize the relationship between plant-based diets and specific ocular outcomes among adults. Design: Systematic review and meta-analysis. Methods: This systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines. The databases MEDLINE, EMBASE, Cochrane, and PubMed, were systematically searched up until May 27, 2021. Of the 503 articles independently screened by two reviewers, 21 were included in this review. Quality assessment and data extraction were performed by both reviewers. Meta-analysis was conducted using STATA 15.0. Fixed-effect and random-effect models were computed based on heterogeneity. Results: A total of 503 studies were identified which then underwent duplicate removal and a title and abstract screen. The remaining 61 studies underwent a full-text screen, 21 progressed to data extraction and fifteen were included in the quantitative analysis. Meta-analysis indicated that regular consumption of fish (OR = 0.70; CI: [0.62-0.79]) and skim milk, poultry, and non-meat animal products (OR = 0.70; CI: [0.61-0.79]) is positively correlated with a reduced risk of visual impairment (age-related macular degeneration, age-related maculopathy, cataract development, and central geographic atrophy) among adults. Consumption of red meat [OR = 1.41; CI: [1.07-1.86]) is associated with an increased risk of visual impairment. Conclusion: Overall, a pescatarian diet is associated with the most favorable visual outcomes among adults, while the consumption of red meat appears to negatively impact vision. Results suggest a need for more local and government-led interventions promoting a healthy and balanced diet.

Keywords: plant-based diet, pescatarian diet, visual impairment, systematic review, meta-analysis

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: apartment complex, big data, life-cycle building value analysis, machine learning

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Authors: Jing Zhang

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Sustainable development in the new energy vehicles field is the requirement of the net zero aim. Green bonds are accepted as a practical financial tool to boost the transformation of relevant enterprises. The paper analyzes the interactions among governments, enterprises of new energy vehicles, and financial institutions by an evolutionary game theory model and offers advice to stakeholders in China. The decision-making subjects of green behavior are affected by experiences, interests, perception ability, and risk preference, so it is difficult for them to be completely rational. Based on the bounded rationality hypothesis, this paper applies prospect theory in the evolutionary game analysis framework and analyses the costs of government regulation of enterprises adopting green bonds. The influence of the perceived value of revenue prospect and the probability and risk transfer coefficient of the government's active regulation on the decision-making agent's strategy is verified by numerical simulation. Finally, according to the research conclusions, policy suggestions are given to promote green bonds.

Keywords: green bonds, new energy vehicles, sustainable development, evolutionary Game Theory model

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Authors: Tingneyuc Sekac, Sujoy Kumar Jana, Indrajit Pal, Dilip Kumar Pal

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Tectonism induced Tsunami, landslide, ground shaking leading to liquefaction, infrastructure collapse, conflagration are the common earthquake hazards that are experienced worldwide. Apart from human casualty, the damage to built-up infrastructures like roads, bridges, buildings and other properties are the collateral episodes. The appropriate planning must precede with a view to safeguarding people’s welfare, infrastructures and other properties at a site based on proper evaluation and assessments of the potential level of earthquake hazard. The information or output results can be used as a tool that can assist in minimizing risk from earthquakes and also can foster appropriate construction design and formulation of building codes at a particular site. Different disciplines adopt different approaches in assessing and monitoring earthquake hazard throughout the world. For the present study, GIS and Remote Sensing potentials were utilized to evaluate and assess earthquake hazards of the study region. Subsurface geology and geomorphology were the common features or factors that were assessed and integrated within GIS environment coupling with seismicity data layers like; Peak Ground Acceleration (PGA), historical earthquake magnitude and earthquake depth to evaluate and prepare liquefaction potential zones (LPZ) culminating in earthquake hazard zonation of our study sites. The liquefaction can eventuate in the aftermath of severe ground shaking with amenable site soil condition, geology and geomorphology. The latter site conditions or the wave propagation media were assessed to identify the potential zones. The precept has been that during any earthquake event the seismic wave is generated and propagates from earthquake focus to the surface. As it propagates, it passes through certain geological or geomorphological and specific soil features, where these features according to their strength/stiffness/moisture content, aggravates or attenuates the strength of wave propagation to the surface. Accordingly, the resulting intensity of shaking may or may not culminate in the collapse of built-up infrastructures. For the case of earthquake hazard zonation, the overall assessment was carried out through integrating seismicity data layers with LPZ. Multi-criteria Evaluation (MCE) with Saaty’s Analytical Hierarchy Process (AHP) was adopted for this study. It is a GIS technology that involves integration of several factors (thematic layers) that can have a potential contribution to liquefaction triggered by earthquake hazard. The factors are to be weighted and ranked in the order of their contribution to earthquake induced liquefaction. The weightage and ranking assigned to each factor are to be normalized with AHP technique. The spatial analysis tools i.e., Raster calculator, reclassify, overlay analysis in ArcGIS 10 software were mainly employed in the study. The final output of LPZ and Earthquake hazard zones were reclassified to ‘Very high’, ‘High’, ‘Moderate’, ‘Low’ and ‘Very Low’ to indicate levels of hazard within a study region.

Keywords: hazard micro-zonation, liquefaction, multi criteria evaluation, tectonism

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Authors: Sastry Y. Kandukuri, Isak Andersen

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Despite recent advances in the manufacturing sector, quality issues remain a frequent occurrence, and can result in fatal accidents, equipment downtime, and loss of life. Adequate quality is of high importance in high-risk industries such as sea-going vessels and offshore installations in which third party quality assurance and product control play an important essential role in ensuring manufacturing quality of critical components. Classification societies play a vital role in mitigating risk in these industries by making sure that all the stakeholders i.e. manufacturers, builders, and end users are provided with adequate rules and standards that effectively ensures components produced at a high level of quality based on the area of application and risk of its failure. Quality issues have also been linked to the lack of competence or negligence of stakeholders in supply value chain. However, continued actions and regulatory reforms through modernization of rules and requirements has provided additional tools for purchasers and manufacturers to confront these issues. Included among these tools are updated ‘approval of manufacturer class programs’ aimed at developing and implementing a set of standardized manufacturing quality metrics for use by the manufacturer and verified by the classification society. The establishment and collection of manufacturing and testing requirements described in these programs could provide various stakeholders – from industry to vessel owners – with greater insight into the state of quality at a given manufacturing facility, and allow stakeholders to anticipate better and address quality issues while simultaneously reducing unnecessary failures that are costly to the industry. The publication introduces, explains and discusses critical manufacturing and testing requirements set in a leading class society’s approval of manufacturer regime and its rationale and some case studies.

Keywords: classification society, manufacturing, materials processing, materials testing, quality control

Procedia PDF Downloads 358

Authors: N. C. Okoronkwo, I. E. Mbaeyi-Nwaoha, C. P. Agbata

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Childhood malnutrition is one of the most persistent public health problems throughout developing countries, including Nigeria. Demographic and Health survey data from twenty-one developing countries indicated that poor complementary feeding of children aged 6- 23 months contributes to negative growth trends. To reduce malnutrition among children in the society, formulation of complimentary food rich in essential nutrient for optimum growth and development of infants is essential. This study focused on the evaluation of complementary food produced by solid-state fermentation of Acha and Soybean using Rhizopus oligosporus (2710) and Orange-fleshed sweet potatoes (OFSP) using Lactobacillus planterum (B-41621). The raw materials were soaked separately, each in four volumes of 0.9M acetic acid for 16 hours, rinsed with clean water, steam cooked and cooled. Solid-state fermentation (SSF) was carried out by inoculating Acha and Soybean with spore suspension (1x 10⁶spores/ml) of Rhizopus oligosporus (2710) and OFSP with spore suspension (1x 106spores/ml) of Lactobacillus planterum (B-41621). Fermentation which lasted for 72hours was carried out with 24hours sampling. The samples were blended in the following ratios: Acha and soybean 100: 100 (AS), Acha/soybean and OFSP 50: 50(ASO), made into gruel and compared with a commercial infant formula (Cerelac) which served as the control (CTRL). The samples were analyzed for proximate composition using AOAC methods and sensory attributes using a hedonic scale. Results showed that moisture, crude protein, fibre and ash content increased significantly (p<0.05) as fermentation progressed, while carbohydrate and fat content decreased. The protein, moisture, fibre and ash content ranged from 17.10-19.02%, 54.97-56.27%, 7.08-7.60% and2.09-2.38%, respectively, while carbohydrate and fat content ranged from 12.95-10.21% and 5.81-4.52%, respectively. In sensory scores, there were no significant (p>0.05) difference between the average mean scores of colours, texture and consistency of the samples. The sensory score for the overall acceptability ranged from 6.20-7.80. Sample CTRL had the highest score, while sample ASO had the least score. There was no significant (p>0.05) difference between samples CTRL and AS. Solid-state fermentation improved the nutritional content and flavour of the developed complementary food, which is needed for infant growth and development.

Keywords: Complementary food, malnutrition, proximate composition, solid-state fermentation

Procedia PDF Downloads 163

Authors: Serpil Kilic, Ihsan Burak Cam, Murat Kilic, Timur Tongur

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Interest in the lead (Pb) has considerably increased due to knowledge about the potential toxic effects of this element, recently. Exposure to heavy metals above the acceptable limit affects human health. Indeed, Pb is accumulated through food chains up to toxic concentrations; therefore, it can pose an adverse potential threat to human health. A sensitive and reliable method for determination of Pb element in red pepper were improved in the present study. Samples (33 red pepper products having different brands) were purchased from different markets in Turkey. The selected method validation criteria (linearity, Limit of Detection, Limit of Quantification, recovery, and trueness) demonstrated. Recovery values close to 100% showed adequate precision and accuracy for analysis. According to the results of red pepper analysis, all of the tested lead element in the samples was determined at various concentrations. A Perkin- Elmer ELAN DRC-e model ICP-MS system was used for detection of Pb. Organic red pepper was used to obtain a matrix for all method validation studies. The certified reference material, Fapas chili powder, was digested and analyzed, together with the different sample batches. Three replicates from each sample were digested and analyzed. The results of the exposure levels of the elements were discussed considering the scientific opinions of the European Food Safety Authority (EFSA), which is the European Union’s (EU) risk assessment source associated with food safety. The Target Hazard Quotient (THQ) was described by the United States Environmental Protection Agency (USEPA) for the calculation of potential health risks associated with long-term exposure to chemical pollutants. THQ value contains intake of elements, exposure frequency and duration, body weight and the oral reference dose (RfD). If the THQ value is lower than one, it means that the exposed population is assumed to be safe and 1 < THQ < 5 means that the exposed population is in a level of concern interval. In this study, the THQ of Pb was obtained as < 1. The results of THQ calculations showed that the values were below one for all the tested, meaning the samples did not pose a health risk to the local population. This work was supported by The Scientific Research Projects Coordination Unit of Akdeniz University. Project Number: FBA-2017-2494.

Keywords: lead analyses, red pepper, risk assessment, daily exposure

Procedia PDF Downloads 173

Authors: Olumuyiwa Idowu Ojo, Oluwatobi Peter Olowo

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The study developed a Geographical Information Systems (GIS) database and mapped inter-annual changes in crop yields of cassava, cowpea, maize, rice, melon and yam as a response to inter-annual rainfall and temperature variability in Southwest, Nigeria. The aim of this project is to study the comparative analysis of the weather variability impact of six crops yield (Rice, melon, yam, cassava, Maize and cowpea) in South Western States of Nigeria (Oyo, Osun, Ekiti, Ondo, Ogun and Lagos) from 1991 – 2007. The data was imported and analysed in the Arch GIS 9 – 3 software environment. The various parameters (temperature, rainfall, crop yields) were interpolated using the kriging method. The results generated through interpolation were clipped to the study area. Geographically weighted regression was chosen from the spatial statistics toolbox in Arch GIS 9.3 software to analyse and predict the relationship between temperature, rainfall and the different crops (Cowpea, maize, rice, melon, yam, and cassava).

Keywords: GIS, crop yields, comparative analysis, temperature, rainfall, weather variability

Procedia PDF Downloads 330

Authors: Sepehr Moradi, Mehdi Asadi Rad

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The aim of this study is to evaluate and compare live weight of pure and mixed races Tizpar 30-day pigeons to investigate about their sex, race, and some auxiliary variables. In this paper, 70 pieces of pigeons as 35 male and female pairs with equal age are studied randomly. A natural incubation was done from each pair. All produced chickens were weighted at 30 days age before and after hunger by a scale with one gram precision. A covariance analysis was used since there were many auxiliary variables and unequal observations. SAS software was used for statistical analysis. Mean weight of live in pure race (Tizpar-Tizpar) with 12 records, 182.3±60.9 gr and mixed races of Tizpar-Kabood, Tizpar-Parvazy, Tizpar-Namebar, Kabood-Tizpar, Namebar-Tizpar, and Parvazy-Tizpar with 10, 10, 8, 6, 12, and 12 records were 114.3±71.6, 210.6±71.7, 353.2±86, 520.8±81.5, 288.3±65.6, and 382.6±70.4 gr, respectively. Effects of sex, race and some auxiliary variables were also significant in 1% level (P < 0.01). Difference live weight of 30-day of Tizpar-Tizpar race with Tizpar-Namebar and Parvazi-Tizpar mixed races was significant in 5% level (P < 0.05) and with Kabood-Tizpar mixed races was significant in 1% level (P < 0.01) but with Tizpar-Kabood, Nmaebar-Tizpar and Tizpar-Parvazy mixed races was not significant. The results showed that most and least weights of live belonged to Kabood-Tizpar and Tizpar-Kabood.

Keywords: squabs, Tizpar race, 30-day live weight, pigeons

Procedia PDF Downloads 179

Authors: Beate Englich, Linda Schlittenbauer, Christiane Pfeifer, Isabel Kratochvil, Michael Borte, Gabriele I. Stangl, Martin von Bergen, Thorsten Reemtsma, Irina Lehmann, Kristin M. Junge

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The worldwide production of endocrine disrupting compounds (EDC) has risen dramatically over the last decades, as so has the prevalence for obesity. Many EDCs are believed to contribute to this obesity epidemic, by enhancing adipogenesis or disrupting relevant metabolism. This effect is most tremendous in the early prenatal period when priming effects find a highly vulnerable time window. Therefore, we investigate the impact of parabens on childhood overweight development and adipogenesis in general. Parabens are ester of 4-hydroxy-benzoic acid and part of many cosmetic products or food packing. Therefore, ubiquitous exposure can be found in the westernized world, with exposure already starting during the sensitive prenatal period. We assessed maternal cosmetic product consumption, prenatal paraben exposure and infant BMI z-scores in the prospective German LINA cohort. In detail, maternal urinary concentrations (34 weeks of gestation) of methyl paraben (MeP), ethyl paraben (EtP), n-propyl paraben (PrP) and n-butyl paraben (BuP) were quantified using UPLC-MS/MS. Body weight and height of their children was assessed during annual clinical visits. Further, we investigated the direct influence of those parabens on adipogenesis in-vitro using a human mesenchymal stem cell (MSC) differentiation assay to mimic a prenatal exposure scenario. MSC were exposed to 0.1 – 50 µM paraben during the entire differentiation period. Differentiation outcome was monitored by impedance spectrometry, real-time PCR and triglyceride staining. We found that maternal cosmetic product consumption was highly correlated with urinary paraben concentrations at pregnancy. Further, prenatal paraben exposure was linked to higher BMI Z-scores in children. Our in-vitro analysis revealed that especially the long chained paraben BuP stimulates adipogenesis by increasing the expression of adipocyte specific genes (PPARγ, ADIPOQ, LPL, etc.) and triglyceride storage. Moreover, we found that adiponectin secretion is increased whereas leptin secretion is reduced under BuP exposure in-vitro. Further mechanistic analysis for receptor binding and activation of PPARγ and other key players in adipogenesis are currently in process. We conclude that maternal cosmetic product consumption is linked to prenatal paraben exposure of children and contributes to the development of infant overweight development by triggering key pathways of adipogenesis.

Keywords: adipogenesis, endocrine disruptors, paraben, prenatal exposure

Procedia PDF Downloads 275

Authors: Rusnardi Rahmat Putra, Junji Kiyono, Aiko Furukawa

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Several powerful earthquakes have struck Padang during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009 and caused more than 1000 casualties. Following the event, we conducted a 12-site microtremor array investigation to gain a representative determination of the soil condition of subsurface structures in Padang. From the dispersion curve of array observations, the central business district of Padang corresponds to relatively soft soil condition with Vs30 less than 400 m/s. because only one accelerometer existed, we simulated the 2009 Padang earthquake to obtain peak ground acceleration for all sites in Padang city. By considering the damage data of the 2009 Padang earthquake, we produced seismic risk vulnerability estimation of non-engineered houses for rock, medium and soft soil condition. We estimated the loss ratio based on the ground response, seismic hazard of Padang and the existing damaged to non-engineered structure houses due to Padang earthquake in 2009 data for several return periods of earthquake events.

Keywords: profile, Padang earthquake, microtremor array, seismic vulnerability

Procedia PDF Downloads 417

Authors: Yu-Ping Chiu, Dung-Ying Lin

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Traditional staff scheduling methods, relying on employee experience, often lead to inefficiencies and resource waste. The challenges of transferring scheduling expertise and adapting to changing labor regulations further complicate this process. Manual approaches become increasingly impractical as companies accumulate complex scheduling rules over time. This study proposes an algorithmic optimization approach to address these issues, aiming to expedite scheduling while ensuring strict compliance with labor regulations and company policies. The method focuses on generating optimal schedules that minimize weighted company objectives within a compressed timeframe. Recognizing the limitations of conventional commercial software in modeling and solving complex real-world scheduling problems efficiently, this research employs Tabu Search with both long-term and short-term memory structures. The study will present numerical results and managerial insights to demonstrate the effectiveness of this approach in achieving intelligent and efficient staff scheduling.

Keywords: intelligent memory structures, mixed integer programming, meta-heuristics, staff scheduling problem, tabu search

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Authors: Kelly S. Parkinson, Katherine Y. Teh-White

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Futureye has a bespoke social licence to operate methodology which has successfully secured community approval and commercial return for fisheries which have faced regulatory and financial risk. This unique approach to fisheries management focuses on delivering improved social and environmental outcomes to support the fishing industry make steps towards achieving the United Nations SDGs. An SLO is the community’s implicit consent for a business or project to exist. An SLO must be earned and maintained alongside regulatory licences. In current and new operations, it helps you to anticipate and measure community concerns around your operations – leading to more predictable and sensible policy outcomes that will not jeopardise your commercial returns. Rising societal expectations and increasing activist sophistication mean the international fishing industry needs to resolve community concerns at each stage their supply chain. Futureye applied our tested social licence to operate (SLO) methodology to help Austral Fisheries who was being attacked by activists concerned about the sustainability of Patagonian Toothfish. Austral was Marine Stewardship Council certified, but pirates were making the overall catch unsustainable. Austral wanted to be carbon neutral. SLO provides a lens on the risk that helps industries and companies act before regulatory and political risk escalates. To do this assessment, we have a methodology that assesses the risk that we can then translate into a process to create a strategy. 1) Audience: we understand the drivers of change and the transmission of those drivers across all audience segments. 2) Expectation: we understand the level of social norming of changing expectations. 3) Outrage: we understand the technical and perceptual aspects of risk and the opportunities to mitigate these. 4) Inter-relationships: we understand the political, regulatory, and reputation system so that we can understand the levers of change. 5) Strategy: we understand whether the strategy will achieve a social licence through bringing the internal and external stakeholders on the journey. Futureye’s SLO methodologies helped Austral to understand risks and opportunities to enhance its resilience. Futureye reviewed the issues, assessed outrage and materiality and mapped SLO threats to the company. Austral was introduced to a new way that it could manage activism, climate action, and responsible consumption. As a result of Futureye’s work, Austral worked closely with Sea Shepherd who was campaigning against pirates illegally fishing Patagonian Toothfish as well as international governments. In 2016 Austral launched the world’s first carbon neutral fish which won Austral a thirteen percent premium for tender on the open market. In 2017, Austral received the prestigious Banksia Foundation Sustainability Leadership Award for seafood that is sustainable, healthy and carbon neutral. Austral’s position as a leader in sustainable development has opened doors for retailers all over the world. Futureye’s SLO methodology can identify the societal, political and regulatory risks facing fisheries and position them to proactively address the issues and become an industry leader in sustainability.

Keywords: carbon neutral, fisheries management, risk communication, social licence to operate, sustainable development

Procedia PDF Downloads 123

Authors: Tauseef-ur-Rehman, Rao Zahid Abbas, Wasim Babar, Arbab Sikandar

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Babesiosis is an infection due to the multiplication of tick borne parasite, Babesia sp., in erythrocytes of host (variety of vertebrates) including small ruminants and is responsible for decreased livestock output and hence economic losses. A cross-sectional study was designed in order to evaluate the prevalence of Babesia and its relation with various associated factors in district Toba Tek Singh, Central Punjab, Pakistan in 2009-2010. A total 10.84% (50/461) out of 461 examined cases for Babesia were found positive for Babesia infection. Month-wise peak prevalence was observed in July (17.95%), while no positive case was recorded in Dec-2009 and Jan-2010. The prevalence of infection in different goat breeds was found as non-significant (P < 0.05) for Babesia infection. The prevalence of Babesia was found significantly (P < 0.05) dependent to the goat age and sex. The feeding system, housing system, floor type and herd size revealed strong correlation with Babesia prevalence, while watering system and body conditions were found to be non-significant (P < 0.05), and hence it is suggested that with the improvement of management precautions Babesiosis can be avoided.

Keywords: Babesia, goat, prevalence, Pakistan, risk factors

Procedia PDF Downloads 522