Search results for: audit risk

Authors: Sontana Mimapan, Phattarawadee Wattanasuntorn, Phanom Saijit

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Aflatoxin contamination in maize, one of several agriculture crops grown for livestock feeding, is still a problem throughout the world mainly under hot and humid weather conditions like Thailand. In this study Aspergillus flavus (A. Flavus), the key fungus for aflatoxin production especially aflatoxin B1 (AFB1), isolated from naturally infected maize were identified and characterized according to colony morphology and PCR using ITS, Beta-tubulin and calmodulin genes. The strains were analysed for the presence of four aflatoxigenic biosynthesis genes in relation to their capability to produce AFB1, Ver1, Omt1, Nor1, and aflR. Aflatoxin production was then confirmed using immunoaffinity column technique. A loop-mediated isothermal amplification (LAMP) was applied as an innovative technique for rapid detection of target nucleic acid. The reaction condition was optimized at 65C for 60 min. and calcein flurescent reagent was added before amplification. The LAMP results showed clear differences between positive and negative reactions in end point analysis under daylight and UV light by the naked eye. In daylight, the samples with AFB1 producing A. Flavus genes developed a yellow to green color, but those without the genes retained the orange color. When excited with UV light, the positive samples become visible by bright green fluorescence. LAMP reactions were positive after addition of purified target DNA until dilutions of 10⁻⁶. The reaction products were then confirmed and visualized with 1% agarose gel electrophoresis. In this regards, 50 maize samples were collected from dairy farms and tested for the presence of four aflatoxigenic biosynthesis genes using LAMP technique. The results were positive in 18 samples (36%) but negative in 32 samples (64%). All of the samples were rechecked by PCR and the results were the same as LAMP, indicating 100% specificity. Additionally, when compared with the immunoaffinity column-based aflatoxin analysis, there was a significant correlation between LAMP results and aflatoxin analysis (r= 0.83, P < 0.05) which suggested that positive maize samples were likely to be a high- risk feed. In conclusion, the LAMP developed in this study can provide a simple and rapid approach for detecting AFB1 producing A. Flavus genes from maize and appeared to be a promising tool for the prediction of potential aflatoxigenic risk in livestock feedings.

Keywords: Aflatoxin B1, Aspergillus flavus genes, maize, loop-mediated isothermal amplification

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Authors: Shaojian Li

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The traditional Chinese patterns, as an integral part of Chinese culture, possess unique values in history, culture, and art. However, with the passage of time and societal changes, many of these traditional patterns are at risk of being lost, damaged, or forgotten. To undertake the digital preservation and protection of these traditional patterns, this paper will collect and organize images of traditional Chinese patterns. It will provide exhaustive and comprehensive semantic annotations, creating a resource library of traditional Chinese pattern images. This will support the digital preservation and application of traditional Chinese patterns.

Keywords: digitization of cultural heritage, traditional Chinese patterns, digital humanities, database construction

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Authors: Chang Hsueh-Sheng, Chen Tzu-Ling

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Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience, and further increase vulnerability. Due to earthquakes do not kill people, buildings do. When buildings located nearby earthquake-prone areas and constructed upon poorer soil areas might result in earthquake-induced ground damage. In addition, many existing buildings built before any improved seismic provisions began to be required in building codes and inappropriate land usage with highly dense population might result in much serious earthquake disaster. Indeed, not only do earthquake disaster impact seriously on urban environment, but urban growth might increase the vulnerability. Since 1980s, ‘Cutting down risks and vulnerability’ has been brought up in both urban planning and architecture and such concept has way beyond retrofitting of seismic damages, seismic resistance, and better anti-seismic structures, and become the key action on disaster mitigation. Land use planning and zoning are two critical non-structural measures on controlling physical development while it is difficult for zoning boards and governing bodies restrict development of questionable lands to uses compatible with the hazard without credible earthquake loss projection. Therefore, identifying potential earthquake exposure, vulnerability people and places, and urban development areas might become strongly supported information for decision makers. Taiwan locates on the Pacific Ring of Fire where a seismically active zone is. Some of the active faults have been found close by densely populated and highly developed built environment in the cities. Therefore, this study attempts to base on the perspective of carrying capacity and draft out micro-zonation according to both vulnerability index and urban growth index while considering spatial variances of multi factors via geographical weighted principle components (GWPCA). The purpose in this study is to construct supported information for decision makers on revising existing zoning in high-risk areas for a more compatible use and the public on managing risks.

Keywords: earthquake disaster, vulnerability, urban growth, carrying capacity, /geographical weighted principle components (GWPCA), bivariate spatial association statistic

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Authors: A. Kourou, A. Ioakeimidou, A. Gakou

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Greece due to its location in the Eastern Mediterranean region is characterized by a high degree of seismicity and occurrence of severe earthquakes. It is generally accepted that preventive planning is vital in mitigating impacts, protecting those who are the most vulnerable namely children and increasing the degree of resilience of local communities. Worldwide, States have highlighted the need to ensure the safety of early childhood environments in case of disaster. A great number of children are enrolled in daycare facilities, so building and improving the preparedness of pre-primary schools to prevent injuries and fatalities in case of an earthquake becomes an important policy issue. It is more than evident that preparedness in early preschool level will be increased through awareness and education of the people who work to pre-primary classes and provide early childhood care. The aim of the present study is to assess the level of awareness and preparedness of the Greek pre-primary schools staff concerning earthquake protection issues, as well as their risk mitigation behaviors and earthquake management in case of a strong event. In this framework, specific questionnaire was developed and filled by the abovementioned target group at 30 different municipalities of Greece (2014-2016). Also in the framework of this study it is presented the Pre-Primary Schools’ Earthquake Safety Initiative that has been undertaken by Earthquake Planning and Protection Organization (EPPO) the last years. This initiative aims to develop disaster-resilient day care centers through awareness, self-help, cooperation and education. Recognizing the necessity of integration of the disaster safety concept at pre-primary environments, EPPO published practical guidelines that focused on earthquake planning of these workspaces. Furthermore, dozens of seminars are implemented in municipality or prefecture-level every year by EPPO, in order the early childhood schools’ staff to be appropriately educated and adequately trained to face the earthquake risk. Great progress has been made towards building awareness and increasing preschool preparedness in Greece but significant gaps still remain. Anyway, it is extremely important that the implementation of effective programs and practices and the broad collaboration of all involved parties have been recognized as essential in order to develop a comprehensive disaster management system at preschool environment.

Keywords: awareness, earthquake, education, emergency plans, preparedness, pre-primary schools

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Authors: Djelloul Chafia, Demagh Rafik, Kareche Toufik

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Human activities, made without precautions, accelerate the degradation of the soil structure and reduces its resistance. Operations, such as tunnel construction may exercise an influence more or less permanent on the grounds which surrounded them, these structures alter soil it is necessary to predict their impacts by suitable measures. This research is a numerical analysis that deals the risks and effects due to the weakening of the soil after digging two parallel vertical circular tunnels in urban areas, and suggests forecasting techniques based essentially on the organization of underground space. The simulations are performed using the finite-difference code FLAC in a two-dimensional case and with an elasto-plastic behavior of the soil.

Keywords: sol, weakening, degradation, prevention, tunnel

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

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Authors: Carl-Magnus Everitt, Bo Alfredsson

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Contact mechanics and tribology have been combined with fundamental fatigue and fracture mechanics to form the asperity mechanism which supplies an explanation for the surface-initiated rolling contact fatigue damage, called pitting or spalling. The cracks causing the pits initiates at one surface point and thereafter they slowly grow into the material before chipping of a material piece to form the pit. In the current study, the lubrication aspects on fatigue initiation are simulated by passing a single asperity through a thermal elastohydrodynamic lubricated, TEHL, contact. The physics of the lubricant was described with Reynolds equation and the lubricants pressure-viscosity relation was modeled by Roelands equation, formulated to include temperature dependence. A pressure dependent shear limit was incorporated. To capture the full phenomena of the sliding contact the temperature field was resolved through the incorporation of the energy flow. The heat was mainly generated due to shearing of the lubricant and from dry friction where metal contact occurred. The heat was then transported, and conducted, away by the solids and the lubricant. The fatigue damage caused by the asperities was evaluated through Findley’s fatigue criterion. The results show that asperities, in the size of surface roughness found in applications, may cause surface initiated fatigue damage and crack initiation. The simulations also show that the asperities broke through the lubricant in the inlet, causing metal to metal contact with high friction. When the asperities thereafter moved through the contact, the sliding provided the asperities with lubricant releasing the metal contact. The release of metal contact was possible due to the high viscosity the lubricant obtained from the high pressure. The metal contact in the inlet caused higher friction which increased the risk of fatigue damage. Since the metal contact occurred in the inlet it increased the fatigue risk more for asperities subjected to negative slip than positive slip. Therefore the fatigue evaluations showed that the asperities subjected to negative slip yielded higher fatigue stresses than the asperities subjected to positive slip of equal magnitude. This is one explanation for why pitting is more common in the dedendum than the addendum on pinion gear teeth. The simulations produced further validation for the asperity mechanism by showing that asperities cause surface initiated fatigue and crack initiation.

Keywords: fatigue, rolling, sliding, thermal elastohydrodynamic

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Authors: F. Boudet, V. Galano, D. Gmira, L. Munoz, A. Reina

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Commodities pricing needs a specific approach as they are often linked to each other and so are expectedly doing their prices. They are called co-integrated when at least one stationary linear combination exists between them. Though widespread in economic literature, and even if many equilibrium relations and co-movements exist in the economy, this principle of co-movement is not developed in derivatives field. The present study focuses on the following problem: How can the price of a forward agreement on a commodity be simulated, when it is co-integrated with other ones? Theoretical analysis is developed from Gibson-Schwartz model and an analytical solution is given for short maturities contracts and under risk-neutral conditions. The application has been made to crude oil and heating oil energy commodities and result confirms the applicability of proposed method.

Keywords: co-integration, commodities, forward pricing, Gibson-Schwartz

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Authors: Priti Kumari, Tricha Anjali

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Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.

Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys

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Authors: Felicia N. Obialo, Aliza Wingo, Thomas Wingo

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Psychosocial factors such as personality traits and social networks influence cognitive aging and dementia outcomes both positively and negatively. The inherent complexity of these factors makes defining the underlying mechanisms of their influence difficult; however, exploring their interactions affords promise in the field of cognitive aging. The objective of this study was to elucidate some of these interactions by determining the relationship between social network size and dementia outcomes and by determining whether personality traits mediate this relationship. The longitudinal Alzheimer’s Disease (AD) database provided by Rush University’s Religious Orders Study/Memory and Aging Project was utilized to perform retrospective regression and mediation analyses on 3,591 participants. Participants who were cognitively impaired at baseline were excluded, and analyses were adjusted for age, sex, common chronic diseases, and vascular risk factors. Dementia outcome measures included cognitive trajectory, clinical dementia diagnosis, and postmortem beta-amyloid plaque (AB), and neurofibrillary tangle (NT) accumulation. Personality traits included agreeableness (A), conscientiousness (C), extraversion (E), neuroticism (N), and openness (O). The results show a positive correlation between social network size and cognitive trajectory (p-value = 0.004) and a negative relationship between social network size and odds of dementia diagnosis (p = 0.024/ Odds Ratio (OR) = 0.974). Only neuroticism mediates the positive relationship between social network size and cognitive trajectory (p < 2e-16). Agreeableness, extraversion, and neuroticism all mediate the negative relationship between social network size and dementia diagnosis (p=0.098, p=0.054, and p < 2e-16, respectively). All personality traits are independently associated with dementia diagnosis (A: p = 0.016/ OR = 0.959; C: p = 0.000007/ OR = 0.945; E: p = 0.028/ OR = 0.961; N: p = 0.000019/ OR = 1.036; O: p = 0.027/ OR = 0.972). Only conscientiousness and neuroticism are associated with postmortem AD pathologies; specifically, conscientiousness is negatively associated (AB: p = 0.001, NT: p = 0.025) and neuroticism is positively associated with pathologies (AB: p = 0.002, NT: p = 0.002). These results support the study’s objectives, demonstrating that social network size and personality traits are strongly associated with dementia outcomes, particularly the odds of receiving a clinical diagnosis of dementia. Personality traits interact significantly and beneficially with social network size to influence the cognitive trajectory and future dementia diagnosis. These results reinforce previous literature linking social network size to dementia risk and provide novel insight into the differential roles of individual personality traits in cognitive protection.

Keywords: Alzheimer’s disease, cognitive trajectory, personality traits, social network size

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Authors: Miraji H. Mohamed

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The purpose of this study is to critique ‘radicalisation’ and more particularly ‘youth radicalisation’ by exploring its usage in online newspapers. ‘Radicalisation’ and ‘extremism’ have become the most common terms in terrorism studies since the 9/11 attacks. Regardless of the geographic location, when the word terrorism is used the terms ‘radicalisation’ and ‘extremism’ always follow to attempt to explore the journey of the perpetrators towards violence. These terms have come to represent a discourse of dominantly pejorative traits often used to describe spaces, groups, and processes identified as problematic. Even though ambiguously defined they feature widely in government documents, political statements, news articles, academic research, social media platforms, religious gatherings, and public discussions. Notably, ‘radicalisation’ and ‘extremism’ have been closely conflated with the term youth to form ‘youth radicalisation’ to refer to a discourse of ‘youth at risk’. The three terms largely continue to be used unquestioningly and interchangeably hence the reason why they are placed in single quotation marks to deliberately question their conventional usage. Albeit this comes timely in the Kenyan context where there has been a proliferation of academic and expert research on ‘youth radicalisation’ (used as a neutral label) without considering the political, cultural and socio-historical contexts that inform this label. This study seeks to draw these nuances by employing a genealogical approach that historicises and deconstructs ‘youth radicalisation’; and by applying a Discourse-Historical Approach (DHA) of Critical Discourse Analysis to analyse Kenyan online newspaper - The Daily Nation between 2015 and 2018. By applying the concept of representation to analyse written texts, the study reveals that the use of ‘youth radicalisation’ as a discursive strategy disproportionately affects young people especially those from cultural/ethnic/religious minority groups. Also, the ambiguous use of ‘radicalisation’ and ‘youth radicalisation’ by the media reinforces the discourse of ‘youth at risk’ which has become the major framework underpinning Countering Violent Extremism (CVE) interventions. Similarly, the findings indicate that the uncritical use of ‘youth radicalisation’ has been used to serve political interests; and has become an instrument of policing young people, thus contributing to their cultural shaping. From this, it is evident that the media could thwart rather than assist CVE efforts. By exposing the political nature of the three terms through evidence-based research, this study offers recommendations on how critical reflective reporting by the media could help to make CVE more nuanced.

Keywords: discourse, extremism, radicalisation, terrorism, youth

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Authors: Thayalan Nall, Andreas Putra

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A major offshore reclamation work is currently underway in Southeast Asia for a container terminal. The total extent of the reclamation extent is 2600m x 800m and the seabed level is around -5mRL below mean sea level. Subsoil profile below seabed comprises soft marine clays of thickness varying from 8m to 15m. To contain the dredging spoil within the reclamation area, perimeter bunds have been constructed to +2.5mRL. They include breakwaters of trapezoidal geometry, made of boulder size rock along the northern, eastern and western perimeters, with a sand bund along the southern perimeter. Breakwaters were constructed on a composite bamboo pile and raft foundation system. Bamboo clusters 8m long, with 7 individual Bamboos bundled together as one, have been installed within the footprint of the breakwater below seabed in soft marine clay. To facilitate drainage two prefabricated vertical drains (PVD) have been attached to each cluster. Once the cluster piles were installed, a bamboo raft was placed as a load transfer platform. Rafts were made up of 5 layers of bamboo mattress, and in each layer bamboos were spaced at 200mm centres. The rafts wouldn’t sink under their own weight, and hence, they were sunk by loading quarry run rock onto them. Bamboo is a building material available in abundance in Indonesia and obtained at a relatively low cost. They are commonly used as semi-rigid inclusions to improve compressibility and stability of soft soils. Although bamboo is widely used in soft soil engineering design, no local design guides are available and the designs are carried out based on local experience. In June 2015, when the 1st load of sand was pumped by a dredging vessel next to the breakwater, a 150m long section of the breakwater underwent failure and displaced the breakwater between 1.2m to 4.0m. The cause of the failure was investigated to implement remedial measures to reduce the risk of further failures. Analyses using both limit equilibrium approach and finite element modelling revealed two plausible modes of breakwater failure. This paper outlines: 1) Developed Geology and the ground model, 2) The techniques used for the installation of bamboo piles, 3) Details of the analyses including modes and mechanism of failure and 4) Design changes incorporated to reduce the risk of failure.

Keywords: bamboo piles, ground improvement, reclamation, breakwater failure

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Authors: Encarnación Álvarez, Rosa M. García-Fernández, Francisco J. Blanco-Encomienda, Juan F. Muñoz

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The European Union Survey on Income and Living Conditions (EU-SILC) is a popular survey which provides information on income, poverty, social exclusion and living conditions of households and individuals in the European Union. The EUSILC contains variables which may contain outliers. The presence of outliers can have an impact on the measures and indicators used by the EU-SILC. In this paper, we used data sets from various countries to analyze the presence of outliers. In addition, we obtain some indicators after removing these outliers, and a comparison between both situations can be observed. Finally, some conclusions are obtained.

Keywords: poverty line, headcount index, risk of poverty, skewness coefficient

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Authors: Y. S. Yusoff, G. Streftaris, H. R Waters

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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease

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Authors: Nino Damenia

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The agricultural sector plays an important role in the development of Georgia's economy, it contributes to employment and food security. It faces various types of risks that may lead to heavy financial losses. Agricultural insurance is one of the means of combating agricultural risks. The paper discusses the agricultural insurance experience of those countries (European countries and the USA) that have successfully implemented the agricultural insurance program. Analysis of international cases shows that a well-designed and implemented agri-insurance system can bring significant benefits to farmers, insurance companies and the economy as a whole. In the background of all this, the Government of Georgia recognized the importance of agro-insurance and took important steps for its development. In 2014, in cooperation with insurance companies, an agro-insurance program was introduced, the purpose of which is to increase the availability of insurance for farmers and stimulate the agro-insurance market. Despite such a step forward, challenges remain such as awareness of farmers, insufficient infrastructure for data collection and risk assessment, involvement of insurance companies and other important factors. With the support of the government and stakeholders, it is possible to overcome the existing challenges and establish a strong and effective agro-insurance system. Objectives. The purpose of the research is to analyze the development trends of the agricultural insurance market, to identify the main factors affecting its growth, and to further develop recommendations for development prospects for Georgia. Methodologies. The research uses mixed methods, which combine qualitative and quantitative research techniques. The qualitative method includes the study of the literature of Georgian and foreign economists, which allows us to get acquainted with the challenges, opportunities, legislative and regulatory frameworks of agricultural insurance. Quantitative analysis involves collecting data from stakeholders and then analyzing it. The paper also uses the methods of synthesis, comparison and statistical analysis of the agricultural insurance market in Georgia, Europe and the USA. Conclusions. As the main results of the research, we can consider that the analysis of the insurance market has been made and its main functions have been identified; The essence, features and functions of agricultural insurance are analyzed; European and US agricultural insurance market is researched; The stages of formation and development of the agricultural insurance market of Georgia are studied, its importance for the agricultural sector of Georgia is determined; The role of the state for the development of agro-insurance is analyzed and development prospects are established based on the study of the current trends of the agro-insurance market of Georgia.

Keywords: agricultural insurance, agriculture, agricultural insurance program, risk

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Authors: Athena Daniilidou, Maria Platsidou

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Resilience is considered to greatly affect the personal and occupational wellbeing and efficacy of individuals; therefore, it has been widely studied in the social and behavioral sciences. Given its significance, several scales have been created to assess resilience of children and adults. However, most of these scales focus on examining only the internal protective or risk factors that affect the levels of resilience. The aim of the present study is to create a reliable scale that assesses both the internal and the external protective factors that affect Greek teachers’ levels of resilience. Participants were 136 secondary school teachers (89 females, 47 males) from urban areas of Greece. Connor-Davidson Resilience Scale (CD-Risc) and Resilience Scale for Adults (RSA) were used to collect the data. First, exploratory factor analysis was employed to investigate the inner structure of each scale. For both scales, the analyses revealed a differentiated factor solution compared to the ones proposed by the creators. That prompt us to create a scale that would combine the best fitting subscales of the CD-Risc and the RSA. To this end, the items of the four factors with the best fit and highest reliability were used to create the ‘Teachers' resilience scale’. Exploratory factor analysis revealed that the scale assesses the following protective/risk factors: Personal Competence and Strength (9 items, α=.83), Family Cohesion Spiritual Influences (7 items, α=.80), Social Competence and Peers Support (7 items, α=.78) and Spiritual Influence (3 items, α=.58). This four-factor model explained 49,50% of the total variance. In the next step, a confirmatory factor analysis was performed on the 26 items of the derived scale to test the above factor solution. The fit of the model to the data was good (χ2/292 = 1.245, CFI = .921, GFI = .829, SRMR = .074, CI90% = .026-,056, RMSEA = 0.43), indicating that the proposed scale can validly measure the aforementioned four aspects of teachers' resilience and thus confirmed its factorial validity. Finally, analyses of variance were performed to check for individual differences in the levels of teachers' resilience in relation to their gender, age, marital status, level of studies, and teaching specialty. Results were consistent to previous findings, thus providing an indication of discriminant validity for the instrument. This scale has the advantage of assessing both the internal and the external protective factors of resilience in a brief yet comprehensive way, since it consists 26 items instead of the total of 58 of the CD-Risc and RSA scales. Its factorial inner structure is supported by the relevant literature on resilience, as it captures the major protective factors of resilience identified in previous studies.

Keywords: protective factors, resilience, scale development, teachers

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

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

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

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Authors: John Hang Leung, Shyh-Yau Wang, Hei-Tung Yip, Fion, Ho Tsung-chin, Agnes LF Chan

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Objectives: Platinum-resistant ovarian cancer has a short overall survival of 9–12 months and limited treatment options. The combination of immunotherapy and targeted therapy appears to be a promising treatment option for patients with ovarian cancer, particularly to patients with platinum-resistant recurrent ovarian cancer (PRrOC). However, there are no direct head-to-head clinical trials comparing their efficacy and toxicity. We, therefore, used a network to directly and indirectly compare seven newer immunotherapies or targeted therapies combined with chemotherapy in platinum-resistant relapsed ovarian cancer, including antibody-drug conjugates, PD-1 (Programmed death-1) and PD-L1 (Programmed death-ligand 1), PARP (Poly ADP-ribose polymerase) inhibitors, TKIs (Tyrosine kinase inhibitors), and antiangiogenic agents. Methods: We searched PubMed (Public/Publisher MEDLINE), EMBASE (Excerpta Medica Database), and the Cochrane Library electronic databases for phase II and III trials involving PRrOC patients treated with immunotherapy or targeted therapy plus chemotherapy. The quality of included trials was assessed using the GRADE method. The primary outcomes compared were progression-free survival, the secondary outcomes were overall survival and safety. Results: Seven randomized controlled trials involving a total of 2058 PRrOC patients were included in this analysis. Bevacizumab plus chemotherapy showed statistically significant differences in PFS (Progression-free survival) but not OS (Overall survival) for all interested targets and immunotherapy regimens; however, according to the heatmap analysis, bevacizumab plus chemotherapy had a statistically significant risk of ≥grade 3 SAEs (Severe adverse effects), particularly hematological severe adverse events (neutropenia, anemia, leukopenia, and thrombocytopenia). Conclusions: Bevacizumab plus chemotherapy resulted in better PFS as compared with all interested regimens for the treatment of PRrOC. However, statistical differences in SAEs as bevacizumab plus chemotherapy is associated with a greater risk for hematological SAE.

Keywords: platinum-resistant recurrent ovarian cancer, network meta-analysis, immune checkpoint inhibitors, target therapy, antiangiogenic agents

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Authors: Siti Noor Syahirah Mohd Sabri

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The oil and gas industry is committed to net zero carbon emissions because the consequences of climate change could be catastrophic unless responded to very soon. One way of reducing CO₂ emissions is to inject it into a depleted reservoir buried underground. This greenhouse gas reduction technique significantly reduces CO₂ released into the atmosphere. In general, depleted oil and gas reservoirs provide readily available sites for the storage of CO₂ in offshore areas. This is mainly due to the hydrocarbons have been optimally produced and the existence of voids for effective CO₂ storage. Hence, make it a good candidate for a CO₂ well injector location. Geological storage sites are often evaluated in terms of capacity, injectivity and containment. Leakage through the cap rock or existing well is the main concern in the depleted fields. In order to develop these fields as CO₂ storage sites, the long-term integrity of wells drilled in these oil & gas fields must be ascertained to ensure good CO₂ containment. Well, integrity is often defined as the ability to contain fluids without significant leakage through the project lifecycle. Most plugged and abandoned (P & A) wells in Peninsular Malaysia have drilled 20 – 30 years ago and were not designed to withstand downhole conditions having >50%vol CO₂ and CO₂/H₂O mixture. In addition, Corrosive-Resistant Alloy (CRA) tubular and CO₂-resistant cement was not used during good construction. The reservoir pressure and temperature conditions may have further degraded the material strength and elevated the corrosion rate. Understanding all the uncertainties that may have affected cement-casing bonds, such as the quality of cement behind the casing, subsidence effect, corrosion rate, etc., is the first step toward well integrity evaluation. Secondly, proper quantification of all the uncertainties involved needs to be done to ensure long-term underground storage objectives of CO₂ are achieved. This paper will discuss challenges associated with estimating the performance of well barrier elements in existing P&A wells. Risk ranking of the existing P&A wells is to be carried out in order to ensure the integrity of the storage site is maintained for long-term CO₂ storage. High-risk existing P&A wells are to be re-entered to restore good integrity and to reduce future leakage that may happen. In addition, the requirement to design a fit-for-purpose monitoring and mitigation technology package for potential CO₂ leakage/seepage in the marine environment will be discussed accordingly. The holistic approach will ensure that the integrity is maintained, and CO₂ is contained underground for years to come.

Keywords: CCUS, well integrity, co₂ storage, offshore

Procedia PDF Downloads 91

Authors: Kimberly J. Cribbs, Ryan M. Lefers, TorOve Leiknes, Noreddine Ghaffour

Abstract:

In Gulf Cooperation Council (GCC) countries, domestic agriculture is hindered by a lack of freshwater, poor soil quality, and ambient temperatures unsuitable for cultivation resulting in a heavy reliance on imported food. Attempts to minimize the risk of food insecurity by growing crops domestically creates a significant demand on limited freshwater resources in this region. Cultivating food in a greenhouse allows some of these challenges, such as poor soil quality and temperatures unsuitable for cultivation, to be overcome. One of the most common methods for greenhouse cooling is evaporative cooling. This method cools the air by the evaporation of water and requires a large amount of water relative to that needed for plant growth and air with a low relative humidity. Considering that much of the population in GCC countries live within 100 km of a coast and that sea water can be utilized for evaporative cooling, coastal agriculture could reduce the risk of food insecurity and water demand. Unfortunately, coastal regions tend to experience both high temperatures and high relative humidity causing evaporative cooling by itself to be inadequate. Therefore, dehumidification is needed prior to utilizing evaporative cooling. Utilizing a liquid desiccant for air dehumidification is promising, but the desiccant regeneration to retain its dehumidification potential remains a significant obstacle for the adoption of this technology. This project studied the regeneration of a magnesium chloride (MgCl₂) desiccant solution from 20wt% to 30wt% by direct contact membrane distillation (DCMD) and explored the possibility of using the recovered water for irrigation. Two 0.2 µm hydrophobic PTFE membranes were tested at feed temperatures of 80, 70, and 60°C and with a permeate temperature of 20°C. It was observed that the permeate flux increases as the difference between the feed and coolant temperature increases and also as the feed concentration decreases. At 21wt% the permeate flux was 34,17, and 14 L m⁻² h⁻¹ for feed temperatures of 80, 70, and 60°C, respectively. Salt rejection decreased overtime; however, it remained greater than 99.9% over an experimental time span of 10 hours. The results show that DCMD can successfully regenerate the magnesium chloride desiccant solution.

Keywords: agriculture, direct contact membrane distillation, GCC countries, liquid desiccant, water recovery

Procedia PDF Downloads 151

Authors: Soheila Sadeghi

Abstract:

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

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

Procedia PDF Downloads 61

Authors: Rebecca-Lee Kuhnert, Ron Rapee

Abstract:

Up to 15% of Australian youth will experience an emotional disorder, yet relatively few get the help they need. Schools provide an ideal environment through which we can identify young people who are struggling and provide them with appropriate help. Universal mental health screening is a method by which all young people in school can be quickly assessed for emotional disorders, after which identified youth can be linked to appropriate health services. Despite the obvious logic of this process, universal mental health screening has received little scientific evaluation and even less application in Australian schools. This study will develop methods for Australian education systems to help identify young people (aged 9-17 years old) who are struggling with existing and emerging emotional disorders. Prior to testing, a series of focus groups will be run to get feedback and input from young people, parents, teachers, and mental health professionals. They will be asked about their thoughts on school-based screening methods and and how to best help students at risk of emotional distress. Schools (n=91) across New South Wales, Australia will be randomised to do either immediate screening (in May 2021) or delayed screening (in February 2022). Students in immediate screening schools will complete a long online mental health screener consisting of standard emotional health questionnaires. Ultimately, this large set of items will be reduced to a small number of items to form the final brief screener. Students who score in the “at-risk” range on any measure of emotional health problems will be identified to schools and offered pathways to relevant help according to the most accepted and approved processes identified by the focus groups. Nine months later, the same process will occur among delayed screening schools. At this same time, students in the immediate screening schools will complete screening for a second time. This will allow a direct comparison of the emotional health and help-seeking between youth whose schools had engaged in the screening and pathways to care process (immediate) and those whose schools had not engaged in the process (delayed). It is hypothesised that there will be a significant increase in students who receive help from mental health support services after screening, compared with baseline. It is also predicted that all students will show significantly less emotional distress after screening and access to pathways of care. This study will be an important contribution to Australian youth mental health prevention and early intervention by determining whether school screening leads to a greater number of young people with emotional disorders getting the help that they need and improving their mental health outcomes.

Keywords: children and young people, early intervention, mental health, mental health screening, prevention, school-based mental health

Procedia PDF Downloads 97

Authors: Alvin Han, Reema Shafi, Alishba Afaq, Jennifer Gommerman, Valeria Ramaglia, Shannon E. Dunn

Abstract:

Adolescents engaged in contact-sports can suffer from recurrent brain concussions with no loss of consciousness and no need for hospitalization, yet they face the possibility of long-term neurocognitive problems. Recent studies suggest that head concussive injuries during adolescence can also predispose individuals to multiple sclerosis (MS). The underlying mechanisms of how brain concussions predispose to MS is not understood. Here, we hypothesize that: (1) recurrent brain concussions prime microglial cells, the tissue resident myeloid cells of the brain, setting them up for exacerbated responses when exposed to additional challenges later in life; and (2) brain concussions lead to the sensitization of myelin-specific T cells in the peripheral lymphoid organs. Towards addressing these hypotheses, we implemented a mouse model of closed head injury that uses a weight-drop device. First, we calibrated the model in male 12 week-old mice and established that a weight drop from a 3 cm height induced mild neurological symptoms (mean neurological score of 1.6+0.4 at 1 hour post-injury) from which the mice fully recovered by 72 hours post-trauma. Then, we performed immunohistochemistry on the brain of concussed mice at 72 hours post-trauma. Despite mice having recovered from all neurological symptoms, immunostaining for leukocytes (CD45) and IBA-1 revealed no peripheral immune infiltration, but an increase in the intensity of IBA1+ staining compared to uninjured controls, suggesting that resident microglia had acquired a more active phenotype. This microglia activation was most apparent in the white matter tracts in the brain and in the olfactory bulb. Immunostaining for the microglia-specific homeostatic marker TMEM119, showed a reduction in TMEM119+ area in the brain of concussed mice compared to uninjured controls, confirming a loss of this homeostatic signal by microglia after injury. Future studies will test whether single or repetitive concussive injury can worsen or accelerate autoimmunity in male and female mice. Understanding these mechanisms will guide the development of timed and targeted therapies to prevent MS from getting started in people at risk.

Keywords: concussion, microglia, microglial priming, multiple sclerosis

Procedia PDF Downloads 106

Authors: Xiaoyuan Chen

Abstract:

Background: This study aimed to characterize the epidemiological and clinical features of five rare subtypes of hepatocellular carcinoma (HCC) and to create a competing risk nomogram for predicting cancer-specific survival. Methods: This study used the Surveillance, Epidemiology, and End Results database to analyze the clinicopathological data of 50,218 patients with classic HCC and five rare subtypes (ICD-O-3 Histology Code=8170/3-8175/3) between 2004 and 2018. The annual percent change (APC) was calculated using Joinpoint regression, and a nomogram was developed based on multivariable competing risk survival analyses. The prognostic performance of the nomogram was evaluated using the Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve. Decision curve analysis was used to assess the clinical value of the models. Results: The incidence of scirrhous carcinoma showed a decreasing trend (APC=-6.8%, P=0.025), while the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality plateau in all subtypes during the period. Clear cell carcinoma was the most common subtype (n=551, 1.1%), followed by fibrolamellar (n=241, 0.5%), scirrhous (n=82, 0.2%), spindle cell (n=61, 0.1%), and pleomorphic (n=17, ~0%) carcinomas. Patients with fibrolamellar carcinoma were younger and more likely to have non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro clinical characteristics and outcomes as classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were identified as independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice. Conclusion: The rare subtypes of HCC had distinct clinicopathological features and biological behaviors compared with classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could accurately predict prognoses, which is beneficial for individualized management.

Keywords: hepatocellular carcinoma, pathological subtype, fibrolamellar carcinoma, scirrhous carcinoma, clear cell carcinoma, spindle cell carcinoma, pleomorphic carcinoma

Procedia PDF Downloads 80

Authors: Corina E. Niculaescu, Ivan Sangiorgi, Adrian R. Bell

Abstract:

The COVID-19 pandemic has been life-changing in many aspects of people’s daily and social lives, but has it also changed attitudes towards investments? This paper explores the effect of the COVID-19 pandemic on retail investors’ levels of investments in the U.S. during the first COVID-19 wave in summer 2020. This is an unprecedented health crisis, which could lead to changes in investment behavior, including irrational behavior in retail investors. As such, this study aims to inform policymakers of what happened to investment decisions during the COVID-19 pandemic so that they can protect retail investors during extreme events like a global health crisis. The study aims to answer two research questions. First, was the level of investments affected by the COVID-19 pandemic, and if so, why? Second, how were investments affected by retail investors’ personal experience with COVID-19? The research analysis is based on primary survey data collected on the Amazon Mechanical Turk platform from a representative sample of U.S. respondents. Responses were collected between the 15th of July and 28th of August 2020 from 1,148 U.S. retail investors who hold mutual fund investments and a savings account. The research explores whether being affected by COVID-19, change in the level of savings, and risk capacity can explain the change in the level of investments by using regression analysis. The dependent variable is changed in investments measured as decrease, no change, and increase. For this reason, the methodology used is ordered probit regression models. The results show that retail investors in the U.S. increased their investments during the first wave of COVID-19, which is unexpected as investors are usually more cautious in crisis times. Moreover, the study finds that those who were affected personally by COVID-19 (e.g., tested positive) were more likely to increase their investments, which is irrational behavior and contradicts expectations. An increase in the level of savings and risk capacity was also associated with increased investments. Overall, the findings show that having personal experience with a health crisis can have an impact on one’s investment decisions as well. Those findings are important for both retail investors and policymakers, especially now that online trading platforms have made trading easily accessible to everyone. There are risks and potential irrational behaviors associated with investment decisions during times of crisis, and it is important that retail investors are aware of them before making financial decisions.

Keywords: COVID-19, financial decision-making, health crisis retail investors, survey

Procedia PDF Downloads 193

Authors: Soheila Sadeghi

Abstract:

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

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

Procedia PDF Downloads 41

Authors: Oladele V. Adeniyi, B. Longo-Mbenza, Daniel T. Goon

Abstract:

Background: Lipids are often low or in the normal ranges and controversial in the atherogenesis among Black Africans. The effect of the severity of obesity on some traditional and novel cardiovascular disease risk factors is unclear before and after a diet and exercise maintenance programme among obese black South Africans with type 2 diabetes mellitus (T2DM). Therefore, this study aimed to identify the risk factors to discriminate obesity classes among patients with T2DM before and after a diet and exercise programme. Methods: This interventional cohort of Black South Africans with T2DM was followed by a very – low calorie diet and exercise programme in Mthatha, between August and November 2013. Gender, age, and the levels of body mass index (BMI), blood pressure, monthly income, daily frequency of meals, blood random plasma glucose (RPG), serum creatinine, total cholesterol (TC), triglycerides (TG), LDL –C, HDL – C, Non-HDL, ratios of TC/HDL, TG/HDL, and LDL/HDL were recorded. Univariate analysis (ANOVA) and multivariate discriminant analysis were performed to separate obesity classes: normal weight (BMI = 18.5 – 24.9 kg/m2), overweight (BMI = 25 – 29.9 kg/m2), obesity Class 1 (BMI = 30 – 34.9 kg/m2), obesity Class 2 (BMI = 35 – 39.9 kg/m2), and obesity Class 3 (BMI ≥ 40 kg/m2). Results: At the baseline (1st Month September), all 327 patients were overweight/obese: 19.6% overweight, 42.8% obese class 1, 22.3% obese class 2, and 15.3% obese class 3. In discriminant analysis, only systolic blood pressure (SBP with positive association) and LDL/HDL ratio (negative association) significantly separated increasing obesity classes. At the post – evaluation (3rd Month November), out of all 327 patients, 19.9%, 19.3%, 37.6%, 15%, and 8.3% had normal weight, overweight, obesity class 1, obesity class 2, and obesity class 3, respectively. There was a significant negative association between serum creatinine and increase in BMI. In discriminant analysis, only age (positive association), SBP (U – shaped relationship), monthly income (inverted U – shaped association), daily frequency of meals (positive association), and LDL/HDL ratio (positive association) classified significantly increasing obesity classes. Conclusion: There is an epidemic of diabesity (Obesity + T2DM) in this Black South Africans with some weight loss. Further studies are needed to understand positive or negative linear correlations and paradoxical curvilinear correlations between these markers and increase in BMI among black South African T2DM patients.

Keywords: atherogenic dyslipidaemia, dietary interventions, obesity, south africans

Procedia PDF Downloads 371

Authors: Fatemeh Nemati, Lucinda Leonard, Gwyn Lintern, Richard Thomson

Abstract:

In this study, we will use modern numerical modeling approaches to estimate tsunami risks to the southern coast of British Columbia from landslides. Wave generation is to be simulated using the NHWAVE model, which solves the Navier-Stokes equations due to the more complex behavior of flow near the landslide source; far-field wave propagation will be simulated using the simpler model FUNWAVE_TVD with high-order Boussinesq-type wave equations, with a focus on the accurate simulation of wave propagation and regional- or coastal-scale inundation predictions.

Keywords: FUNWAVE-TVD, landslide-generated tsunami, NHWAVE, tsunami risk

Procedia PDF Downloads 156

Authors: Abdikarim Yusuf

Abstract:

This study uses data from Somalia to analyse child labour using a descriptive and qualitative method. The study set out to identify root causes of child labour in Hargeisa and its implications for children. The study shows that poverty, droughts, family separation, and loss of properties are primary drivers of child labour in Hargeisa. The study found that children work in very difficult jobs such as car wash, casual work, and shoe shining for boys while girls work as housemaids, selling tea, Khat and sometimes are at risk of exploitation such as sexual abuse, rape and harassment. The majority of the parents responded that they don’t know any policy, act or law that protects children. Men showed greater awareness than the women respondents in recognizing child labour as a child rights violation.

Keywords: abuse, child, violence, protection

Procedia PDF Downloads 154

Authors: Armin Taheri

Abstract:

Testosterone levels can impact physical and mental health, with abnormal levels potentially leading to chronic diseases and attention disorders. Further exploration is needed to understand how extremely high testosterone levels affect different population groups. The primary aim of this study is to examine the impact of extremely high levels of testosterone in the blood on chronic diseases and attention disorders. The specific objectives are as follows: i. to compare testosterone levels in athletes and non-athletes, ii. to analyze the association between extremely high testosterone levels and the incidence of chronic diseases, iii. to evaluate the impact of testosterone on attention in hyperactive and typical students. This research was conducted as a cross-sectional study using advanced statistical and technological methods. The study population included male students from boys' schools and male athletes from sports clubs in Shiraz, Iran. Random sampling was performed from 10 schools and 5 sports clubs. The total sample size was 300 participants divided into three groups: 100 professional athletes from sports clubs, 100 non-athletes with no physical activity from boys' schools, 100 students (50 hyperactive and 50 typical) from boys' schools. Testosterone levels were measured using Liquid Chromatography-Mass Spectrometry (LC-MS/MS). This method provides high accuracy in determining hormone concentrations in blood. Data were analyzed using statistical tests, including ANOVA and linear regression, to examine differences and correlations. Professional athletes had significantly higher testosterone levels compared to non-athletes. This increase was associated with improved physical performance and a reduced risk of chronic diseases. Non-athletes with no physical activity generally exhibited lower testosterone levels, which were linked to a higher risk of diabetes and cardiovascular diseases. Hyperactive students had higher testosterone levels, which may be associated with attention disorders and impulsive behaviors. Typical students showed balanced testosterone levels, correlating with better cognitive performance and increased attention. The findings of this study indicate that extremely high levels of testosterone can have varying effects on physical and mental health. While athletes benefit from higher testosterone levels, such levels in hyperactive students may lead to attention disorders and unstable behaviors. The use of LC-MS/MS for precise testosterone measurement is a valuable tool for analyzing these effects. These results emphasize the importance of regulating physical activity and managing hormone levels to promote health.

Keywords: attention disorders, chronic diseases, different population groups, extremely high testosterone levels

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