Search results for: poverty prediction

Authors: Amiya Kumar Pati, Spandan Sahu, Kishanjit Kumar Khatua

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River is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. A river flow consisting of small and shallow channels sometimes divide and recombine numerous times because of the slow water flow or the built up sediments. The pattern formed during this process resembles the strands of a braid. Braided streams form where the sediment load is so heavy that some of the sediments are deposited as shifting islands. Braided rivers often exist near the mountainous regions and typically carry coarse-grained and heterogeneous sediments down a fairly steep gradient. In this paper, the apparent shear stress formulae were suitably modified, and the Energy Concept Method (ECM) was applied for the prediction of discharges at the junction of a two-flow braided compound channel. The Energy Concept Method has not been applied for estimating the discharges in the braided channels. The energy loss in the channels is analyzed based on mechanical analysis. The cross-section of channel is divided into two sub-areas, namely the main-channel below the bank-full level and region above the bank-full level for estimating the total discharge. The experimental data are compared with a wide range of theoretical data available in the published literature to verify this model. The accuracy of this approach is also compared with Divided Channel Method (DCM). From error analysis of this method, it is observed that the relative error is less for the data-sets having smooth floodplains when compared to rough floodplains. Comparisons with other models indicate that the present method has reasonable accuracy for engineering purposes.

Keywords: critical flow, energy concept, open channel flow, sediment, two-flow braided compound channel

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Authors: Mahtab Makaremi Masouleh, Günter Wozniak

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This research is part of an interdisciplinary project, promoting the design of a light temporary installable textile defence system against flood. In case river water levels increase abruptly especially in winter time, one can expect massive extra load on a textile protective structure in term of impact as a result of floating debris and even tree trunks. Estimation of this impulsive force on such structures is of a great importance, as it can ensure the reliability of the design in critical cases. This fact provides the motivation for the numerical analysis of a fluid structure interaction application, comprising flexible slender shaped and free-surface water flow, where an accelerated heavy flotsam tends to approach the membrane. In this context, the analysis on both the behavior of the flexible membrane and its interaction with moving flotsam is conducted by finite elements based solvers of the explicit solver and implicit Abacus solver available as products of SIMULIA software. On the other hand, a study on how free surface water flow behaves in response to moving structures, has been investigated using the finite volume solver of Star CCM+ from Siemens PLM Software. An automatic communication tool (CSE, SIMULIA Co-Simulation Engine) and the implementation of an effective partitioned strategy in form of an implicit coupling algorithm makes it possible for partitioned domains to be interconnected powerfully. The applied procedure ensures stability and convergence in the solution of these complicated issues, albeit with high computational cost; however, the other complexity of this study stems from mesh criterion in the fluid domain, where the two structures approach each other. This contribution presents the approaches for the establishment of a convergent numerical solution and compares the results with experimental findings.

Keywords: co-simulation, flexible thin structure, fluid-structure interaction, implicit coupling algorithm, moving flotsam

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Authors: Haoyu Zhao, Qianshu Ma, Min Xie, Yunqi Huang, Yunjia Liu, Huan Song, Hongsheng Gui, Mingli Li, Qiang Wang

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Rationale: Bipolar disorder (BD) and major depressive disorder (MDD), as severe chronic illnesses that restrict patients’ psychosocial functioning and reduce their quality of life, are both categorized into mood disorders. Emerging evidence has suggested that the reliability of self-rated health (SRH) was wellvalidated and that the risk of various health outcomes, including mortality and health care costs, could be predicted by SRH. Compared with other lengthy multi-item patient-reported outcomes (PRO) measures, SRH was proven to have a comparable predictive ability to predict mortality and healthcare utilization. However, to our knowledge, no study has been conducted to assess the association between SRH and hospitalization among people with mental disorders. Therefore, our study aims to determine the association between SRH and subsequent all-cause hospitalizations in patients with BD and MDD. Methods: We conducted a prospective cohort study on people with BD or MDD in the UK from 2006 to 2010 using UK Biobank touchscreen questionnaire data and linked administrative health databases. The association between SRH and 2-year all-cause hospitalizations was assessed using proportional hazard regression after adjustment for sociodemographics, lifestyle behaviors, previous hospitalization use, the Elixhauser comorbidity index, and environmental factors. Results: A total of 29,966 participants were identified, experiencing 10,279 hospitalization events. Among the cohort, the average age was 55.88 (SD 8.01) years, 64.02% were female, and 3,029 (10.11%), 15,972 (53.30%), 8,313 (27.74%), and 2,652 (8.85%) reported excellent, good, fair, and poor SRH, respectively. Among patients reporting poor SRH, 54.19% had a hospitalization event within 2 years compared with 22.65% for those having excellent SRH. In the adjusted analysis, patients with good, fair, and poor SRH had 1.31 (95% CI 1.21-1.42), 1.82 (95% CI 1.68-1.98), and 2.45 (95% CI 2.22, 2.70) higher hazards of hospitalization, respectively, than those with excellent SRH. Conclusion: SRH was independently associated with subsequent all-cause hospitalizations in patients with BD or MDD. This large study facilitates rapid interpretation of SRH values and underscores the need for proactive SRH screening in this population, which might inform resource allocation and enhance high-risk population detection.

Keywords: severe mental illnesses, hospitalization, risk prediction, patient-reported outcomes

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: H. Jung, N. Kim, B. Kang, J. Choe

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History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

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Authors: Umar Hayatu Sidik

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Application of liquid base petroleum fuel (petrol and diesel) for transportation fuel causes emissions of greenhouse gases (GHGs), while natural gas (NG) reduces the emissions of greenhouse gases (GHGs). At present, compression and liquefaction are the most matured technology used for transportation system. For transportation use, compression requires high pressure (200–300 bar) while liquefaction is impractical. A relatively low pressure of 30-40 bar is achievable by adsorbed natural gas (ANG) to store nearly compressed natural gas (CNG). In this study, adsorbents for high-pressure adsorption of methane (CH4) was prepared from coconut shells and polyetheretherketone (PEEK) using potassium hydroxide (KOH) and microwave-assisted activation. Design expert software version 7.1.6 was used for optimization and prediction of preparation conditions of the adsorbents for CH₄ adsorption. Effects of microwave power, activation time and quantity of PEEK on the adsorbents performance toward CH₄ adsorption was investigated. The adsorbents were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric (TG) and derivative thermogravimetric (DTG) and scanning electron microscopy (SEM). The ideal CH4 adsorption capacities of adsorbents were determined using volumetric method at pressures of 5, 17, and 35 bar at an ambient temperature and 5 oC respectively. Isotherm and kinetics models were used to validate the experimental results. The optimum preparation conditions were found to be 15 wt% amount of PEEK, 3 minutes activation time and 300 W microwave power. The highest CH4 uptake of 9.7045 mmol CH4 adsorbed/g adsorbent was recorded by M33P15 (300 W of microwave power, 3 min activation time and 15 wt% amount of PEEK) among the sorbents at an ambient temperature and 35 bar. The CH4 equilibrium data is well correlated with Sips, Toth, Freundlich and Langmuir. Isotherms revealed that the Sips isotherm has the best fit, while the kinetics studies revealed that the pseudo-second-order kinetic model best describes the adsorption process. In all scenarios studied, a decrease in temperature led to an increase in adsorption of both gases. The adsorbent (M33P15) maintained its stability even after seven adsorption/desorption cycles. The findings revealed the potential of coconut shell-PEEK as CH₄ adsorbents.

Keywords: adsorption, desorption, activated carbon, coconut shells, polyetheretherketone

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Authors: Ojochenemi J. Onubi, Debbi Marais, Lorna Aucott, Friday Okonofua, Amudha Poobalan

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Background: Obesity is a worldwide epidemic with major health and economic consequences. Pregnancy is a trigger point for the development of obesity, and maternal obesity is associated with significant adverse effects in the mother and child. Nigeria is experiencing a double burden of under- and over-nutrition with rising levels of obesity particularly in women. However, there is scarcity of data on maternal obesity in Nigeria and other African countries. Aims and Objectives: This project aimed at identifying crucial components of potential interventions for maternal obesity in Nigeria. The objectives were to assess the prevalence, effects, and distribution of maternal obesity; knowledge, attitude and practice (KAP) of pregnant women and maternal healthcare providers; and identify existing interventions for maternal obesity in Nigeria. Methodology: A systematic review and meta-analysis were initially conducted to appraise the existing literature on maternal obesity in Africa. Following this, a quantitative questionnaire survey of the KAP of pregnant women and a qualitative interview study of the KAP of Health Care Workers (HCW) were conducted in seven secondary and tertiary hospitals across Nigeria. Quantitative data was analysed using SPSS statistical software, while thematic analysis was conducted for qualitative data. Results: Twenty-nine studies included in the systematic review showed significant prevalence, socio-demographic associations, and adverse effects of maternal obesity on labour, maternal, and child outcomes in Africa. The questionnaire survey of 435 mothers revealed a maternal obesity prevalence of 17.9% among mothers who registered for antenatal care in the first trimester. The mothers received nutrition information from different sources and had insufficient knowledge of their own weight category or recommended Gestational Weight Gain (GWG), causes, complications, and safe ways to manage maternal obesity. However, majority of the mothers were of the opinion that excess GWG is avoided in pregnancy and some practiced weight management (diet and exercise) during pregnancy. For the qualitative study, four main themes were identified: ‘Concerns about obesity in pregnancy’, ‘Barriers to care for obese pregnant women’, ‘Practice of care for obese pregnant women’, and ‘Improving care for obese pregnant women’. HCW expressed concerns about rising levels of maternal obesity, lack of guidelines for the management of obese pregnant women and worries about unintended consequences of antenatal interventions. ‘Barriers’ included lack of contact with obese women before pregnancy, late registration for antenatal care, and perceived maternal barriers such as socio-cultural beliefs of mothers and poverty. ‘Practice’ included anticipatory care and screening for possible complications, general nutrition education during antenatal care and interdisciplinary care for mothers with complications. HCW offered suggestions on improving care for obese women including timing, type, and settings of interventions; and the need for involvement of other stake holders in caring for obese pregnant women. Conclusions: Culturally adaptable/sensitive interventions should be developed for the management of obese pregnant women in Africa. Education and training of mothers and health care workers, and provision of guidelines are some of the components of potential interventions in Nigeria.

Keywords: Africa, maternal, obesity, pregnancy

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Authors: Khairy M. A. Zoheir, Nehma A. Ali, Ahmed M. Darwish, Mohamed S. Kishta, Ahmed A. Abd-Rabou, Mohamed A. Abdelhafez, Karima F. Mahrous

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The study comprehensively investigated the multifaceted therapeutic properties of the IQGAP1shRNA plasmid, encompassing its hepatoprotective, immunomodulatory, and anticancer activities. The study employed a Prednisolone-induced immunosuppressed rat model to assess the hepatoprotective and immunomodulatory effects of IQGAP1shRNA plasmid. Using this model, IQGAP1shRNA plasmid was found to modulate haematopoiesis, improving RBC, platelet, and WBC counts, underscoring its potential in hematopoietic homeostasis. Organ atrophy, a hallmark of immunosuppression in spleen, heart, liver, ovaries, and kidneys, was reversed with IQGAP1shRNA plasmid treatment, reinforcing its hepatotrophic and organotropic capabilities. Elevated hepatic biomarkers (ALT, AST, ALP, LPO) indicative of hepatocellular injury and oxidative stress were reduced with GST, highlighting its hepatoprotective and antioxidative effects. IQGAP1shRNA plasmid also restored depleted antioxidants (GSH and SOD), emphasizing its potent antioxidative and free radical scavenging capabilities. Molecular insights into immune dysregulation revealed downregulation of IQGAP1, IQGAP3 interleukin-2 (IL-2), and interleukin-4 (IL-4) mRNA expression in the liver of immunosuppressed rats. IL-2 and IL-4 play pivotal roles in immune regulation, T-cell activation, and B-cell differentiation. Notably, treatment with IQGAP1shRNA plasmid exhibited a significant upregulation of IL-2 and IL-4 mRNA expression, thereby accentuating its immunomodulatory potential in orchestrating immune homeostasis. Additionally, immune dysregulation was associated with increased levels of TNF-α. However, treatment with IQGAP1shRNA plasmid effectively decreased the levels of TNF-α, further underscoring its role in modulating inflammatory responses and restoring immune balance in immunosuppressed rats. Additionally, pharmacokinetics, bioavailability, drug-likeness, and toxicity risk assessment prediction suggest its potential as a pharmacologically favourable agent with no serious adverse effects. In conclusion, this study confirms the therapeutic potential of the IQGAP1shRNA plasmid, showcasing its effectiveness against hepatotoxicity, oxidative stress, immunosuppression, and its notable anticancer activity.

Keywords: IQGAP1, shRNA, cancer, liver, rat

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Authors: Melanie Redding

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Historic widespread nitrate contamination of the Lower Yakima Valley aquifer in Washington State initiated a community-based effort to reduce nitrate concentrations to below-drinking water standards. This group commissioned studies on characterizing local nitrogen sources, deep soil assessments, drinking water, and assessing nitrate concentrations at the water table. Nitrate is the most prevalent groundwater contaminant with common sources from animal and human waste, fertilizers, plants and precipitation. It is challenging to address groundwater contamination when common sources, such as agriculture, on-site sewage systems, and animal production, are widespread. Remediation is not possible, so mitigation is essential. The Lower Yakima Valley is located over 175,000 acres, with a population of 56,000 residents. Approximately 25% of the population do not have access to safe, clean drinking water, and 20% of the population is at or below the poverty level. Agriculture is the primary economic land-use activity. Irrigated agriculture and livestock production make up the largest percentage of acreage and nitrogen load. Commodities include apples, grapes, hops, dairy, silage corn, triticale, alfalfa and cherries. These commodities are important to the economic viability of the residents of the Lower Yakima Valley, as well as Washington State. Mitigation of nitrate in groundwater is challenging. The goal is to ensure everyone has safe drinking water. There are no easy remedies due to the extensive and pervasiveness of the contamination. Monitoring at the water table indicates that 45% of the 30 spatially distributed monitoring wells exceeded the drinking water standard. This indicates that there are multiple sources that are impacting water quality. Washington State has several areas which have extensive groundwater nitrate contamination. The groundwater in these areas continues to degrade over time. However, the Lower Yakima Valley is being successful in addressing this health issue because of the following reasons: the community is engaged and committed; there is one common goal; there has been extensive public education and outreach to citizens; and generating credible data using sound scientific methods. Work in this area is continuing as an ambient groundwater monitoring network is established to assess the condition of the aquifer over time. Nitrate samples are being collected from 170 wells, spatially distributed across the aquifer. This research entails quarterly sampling for two years to characterize seasonal variability and then continue annually afterward. This assessment will provide the data to statistically determine trends in nitrate concentrations across the aquifer, over time. Thirty-three of these wells are monitoring wells that are screened across the aquifer. The water quality from these wells are indicative of activities at the land surface. Additional work is being conducted to identify land use management practices that are effective in limiting nitrate migration through the soil column. Tracking nitrate in the soil column every season is an important component of bridging land-use practices with the fate and transport of nitrate through the subsurface. Patience, tenacity, and the ability to think outside the box are essential for dealing with widespread nitrate contamination of groundwater.

Keywords: community, groundwater, monitoring, nitrate

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Chow Jeng Hei, Pavel Tkalich, Low Kai Sheng Bryan

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Due to the growing demand for sustainability in the maritime industry, there has been a significant increase in focus on alternative fuels such as biofuels, liquefied natural gas (LNG), hydrogen, methanol and ammonia to reduce the carbon footprint of vessels. Alternative fuels offer efficient transportability and significantly reduce carbon dioxide emissions, a critical factor in combating global warming. In an era where the world is determined to tackle climate change, the utilization of methanol is projected to witness a consistent rise in demand, even during downturns in the oil and gas industry. Since 2022, there has been an increase in methanol loading and discharging operations for industrial use in Singapore. These operations were conducted across various storage tank terminals at Jurong Island of varying capacities, which are also used to store alternative fuels for bunkering requirements. The key objective of this research is to support the green shipping industries in the transformation to new fuels such as methanol and ammonia, especially in evolving the capability to inform risk assessment and management of spills. In the unlikely event of accidental spills, a highly reliable forecasting system must be in place to provide mitigation measures and ahead planning. The outcomes of this research would lead to an enhanced metocean prediction capability and, together with advanced sensing, will continuously build up a robust digital twin of the bunkering operating environment. Outputs from the developments will contribute to management strategies for alternative marine fuel spills, including best practices, safety challenges and crisis management. The outputs can also benefit key port operators and the various bunkering, petrochemicals, shipping, protection and indemnity, and emergency response sectors. The forecasted datasets provide a forecast of the expected atmosphere and hydrodynamic conditions prior to bunkering exercises, enabling a better understanding of the metocean conditions ahead and allowing for more refined spill incident management planning

Keywords: clean fuels, hydrodynamics, coastal engineering, impact assessments

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: O. O. Oku, K. S. Jerry-Alagbaoso

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It is universally acknowledged that the primary function of universities is the generation and dissemination of knowledge. This mission is pursued through the research component of the university programme especially at the post-graduate level. The senior academic staff teach, supervise and provide general academic leadership to post-graduate students who are expected to carry out research leading to the presentation of dissertation as requirement for the award of doctoral degree in their various disciplines. Carrying out the research enterprises involves a lot of corroboration among individuals and communities. The need to safeguard the interest of everyone involved in the enterprise makes the development of ethical standard in research imperative. Ensuring the development and effective application of such ethical standard falls within the leadership role of the vice –chancellors, Deans of post-graduate schools/ faculties, Heads of Departments and supervisors. It is the relevance and application of such ethical standard in Nigerian university research efforts that this study discussed. The study adopted the descriptive research design. A researcher-made 4 point rating scale was used to elicit information from the post-graduate dissertation supervisors sampled from one university each from the six geo-political zones in Nigeria using the purposive sampling technique. The data collected was analysed using the mean score and standard deviation. The findings of the study include among others that there are several cases of unethical practices by Ph.D dissertation students in Nigerian universities. Prominent among these include duplicating research topics, making unauthorized copies of data paper or computer programme, failing to acknowledge contributions of relevant people and authors, rigging an experiment to prempt the result among others. Some of the causes of the unethical practices according to the respondents include inadequate funding of universities resulting in inadequate remuneration for university teachers, inadequacy of equipment and infrastructures, poor supervision of Ph.D students,’ poverty on the side of the student researchers and non-application of sanctions on violators. Improved funding of the Nigerian universities system with emphasis on both staff and student research efforts, admitting academic oriented students into the Ph.D programme and ensuring the application of appropriate sanctions in cases of unethical conduct in research featured prominently in the needed leadership imperatives. Based on the findings of the study, the researchers recommend the development of university research policies that is closely tied to each university’s strategic plan. Such plan should explain the research focus that will attract more funding and direct students interest towards it without violating the principle of academic freedom. The plan should also incorporate the establishment of a research administration office to provide the necessary link between the students and funding agencies and also organise training for supervisors on leadership activities expected of them while educating students on the processes involved in carrying out a qualitative and acceptable research study. Such exercise should include the ethical principles and guidelines that comprise all parts of research from research topic through the literature review to the design and the truthful reporting of results.

Keywords: academic leadership, ethical standards, research stakeholders, research enterprise

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: M. Petunia Tsweleng

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Statement of the Problem: Research and aid organisations report that children and adolescents orphaned due to HIV and AIDS are particularly vulnerable as they are often exposed to negative effects of both HIV and AIDS and orphanhood. Without much-needed parental love, care, and support, these children and adolescents are at risk of poor developmental outcomes. A cursory look at the available literature on AIDS-orphaned adolescents, and the quality of caregiving relationships with caregivers, shows that this is a relatively under-researched terrain. This article is a review of the literature on caregiving relationships of adolescents orphaned due to AIDS and their current primary caregivers. It aims to inform community programmes and policymakers by providing insight into the qualities of these relationships. Methodology: A comprehensive search of both peer-reviewed and non-peer-reviewed literature was conducted through EBSCOhost, SpringLINK, PsycINFO, SAGE, PubMed, Elsevier ScienceDirect, JSTOR, Wiley Online Library databases, and Google Scholar. The combination of keywords used for the search were: (caregiving relationships); (orphans OR AIDS orphaned children OR AIDS orphaned adolescents); (primary caregivers); and (quality caregiving); (orphans); (HIV and AIDS). The search took place between 24 January and 28 February 2022. Both qualitative and quantitative research studies published between 2010 and 2020 were reviewed. However, only qualitative studies were selected in the end -as they presented more profound findings concerning orphan-caregiver relationships. The following three stages of meta-synthesis analysis were used to analyse data: refutational syntheses, reciprocal syntheses, and line of argument. Results: The search resulted in a total of 2090 titles, of which 750 were duplicates and therefore subtracted. The researcher reviewed all the titles and abstracts of the remaining 1340 articles. 329 articles were identified as relevant, and full texts were reviewed. Following the review of the full texts, 313 studies were excluded for relevance and 4 for methodology. Twelve articles representing 11 studies fulfilled the inclusion criteria and were selected. These studies, representing different countries across the globe, reported similar forms of hardships experienced by caregivers economically, psychosocially, and healthwise. However, the studies also show that the majority of caregivers found contentment in caring for orphans, particularly grandmother carers, and were thus enabled to provide love, care, and support despite hardships. This resulted in positive caregiving relationships -as orphans fared well emotionally and psychosocially. Some relationships, however, were found negative due to unhealed emotional wounds suffered by both caregivers and orphans and others due to the caregiver’s lack of interest in providing care. These findings were based on self-report data from both orphans and caregivers. Conclusion: Findings suggest that intervention efforts need to be intensified to: alleviate poverty in households that are affected by HIV and AIDS pandemic, strengthen the community psychosocial support programmes for orphans and their caregivers; and integrate clinical services with community programmes for the healing of emotional and psychological wounds. Contributions: Findings inform community programmes and policymakers by providing insight into the qualities of the mentioned relationships as well as identifying factors commonly associated with high-quality caregiving and poor-quality caregiving.

Keywords: systematic review, caregiving relationships, orphans and primary caregivers, AIDS

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Authors: Atlal El-Assaad

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Viruses change with time through mutations and result in new variants that may persist or disappear. A Mutation refers to an actual change in the virus genetic sequence, and a variant is a viral genome that may contain one or more mutations. Critical mutations may cause the virus to be more transmissible, with high disease severity, and more vulnerable to diagnostics, therapeutics, and vaccines. Thus, variants carrying such mutations may increase the risk to human health and are considered variants of concern (VOC). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - the contagious in humans, positive-sense single-stranded RNA virus that caused coronavirus disease 2019 (COVID-19) - has been studied thoroughly, and several variants were revealed across the world with their corresponding mutations. SARS-CoV-2 has four structural proteins, known as the S (spike), E (envelope), M (membrane), and N (nucleocapsid) proteins, but prior study and vaccines development focused on genetic mutations in the S protein due to its vital role in allowing the virus to attach and fuse with the membrane of a host cell. Specifically, subunit S1 catalyzes attachment, whereas subunit S2 mediates fusion. In this perspective, we studied all charged amino acid mutations of the SARS-CoV-2 viral spike protein S1 when bound to Antibody CC12.1 in a crystal structure and assessed the effect of different mutations. We generated all missense mutants of SARS-CoV-2 protein amino acids (AAs) within the SARS-CoV-2:CC12.1 complex model. To generate the family of mutants in each complex, we mutated every charged amino acid with all other charged amino acids (Lysine (K), Arginine (R), Glutamic Acid (E), and Aspartic Acid (D)) and studied the new binding of the complex after each mutation. We applied Poisson-Boltzmann electrostatic calculations feeding into free energy calculations to determine the effect of each mutation on binding. After analyzing our data, we identified charged amino acids keys for binding. Furthermore, we validated those findings against published experimental genetic data. Our results are the first to propose in silico potential life-threatening mutations of SARS-CoV-2 beyond the present mutations found in the five common variants found worldwide.

Keywords: SARS-CoV-2, variant, ionic amino acid, protein-protein interactions, missense mutation, AESOP

Procedia PDF Downloads 113

Authors: Geun-Yeon Kim, S. P. Praveen Kumar, Kwon-Hee Lee

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A steering knuckle arm is the component that connects the steering system and suspension system. The structural performances such as stiffness, strength, and durability are considered in its design process. The former study suggested the lightweight design of a knuckle arm considering the structural performances and using the metamodel-based optimization. The six shape design variables were defined, and the optimum design was calculated by applying the kriging interpolation method. The finite element method was utilized to predict the structural responses. The suggested knuckle was made of the aluminum Al6082, and its weight was reduced about 60% in comparison with the base steel knuckle, satisfying the design requirements. Then, we investigated its manufacturability by performing foraging analysis. The forging was done as hot process, and the product was made through two-step forging. As a final step of its developing process, the durability is investigated by using the flexible dynamic analysis software, LS-DYNA and the pre and post processor, eta/VPG. Generally, a car make does not provide all the information with the part manufacturer. Thus, the part manufacturer has a limit in predicting the durability performance with the unit of full car. The eta/VPG has the libraries of suspension, tire, and road, which are commonly used parts. That makes a full car modeling. First, the full car is modeled by referencing the following information; Overall Length: 3,595mm, Overall Width: 1,595mm, CVW (Curve Vehicle Weight): 910kg, Front Suspension: MacPherson Strut, Rear Suspension: Torsion Beam Axle, Tire: 235/65R17. Second, the road is selected as the cobblestone. The road condition of the cobblestone is almost 10 times more severe than that of usual paved road. Third, the dynamic finite element analysis using the LS-DYNA is performed to predict the durability performance of the suggested knuckle arm. The life of the suggested knuckle arm is calculated as 350,000km, which satisfies the design requirement set up by the part manufacturer. In this study, the overall design process of a knuckle arm is suggested, and it can be seen that the developed knuckle arm satisfies the design requirement of the durability with the unit of full car. The VPG analysis is successfully performed even though it does not an exact prediction since the full car model is very rough one. Thus, this approach can be used effectively when the detail to full car is not given.

Keywords: knuckle arm, structural optimization, Metamodel, forging, durability, VPG (Virtual Proving Ground)

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Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

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Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

Procedia PDF Downloads 210

Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Mohd Ayyub Khan, Nadeem Akhtar

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Due to recent advances in wireless communication technologies and hand-held devices, there is a huge demand for video-based applications such as video surveillance, video conferencing, remote surgery, Digital Video Broadcast (DVB), IPTV, online learning courses, YouTube, WhatsApp, Instagram, Facebook, Interactive Video Games. However, the raw videos posses very high bandwidth which makes the compression a must before its transmission over the wireless channels. The High Efficiency Video Codec (HEVC) (also called H.265) is latest state-of-the-art video coding standard developed by the Joint effort of ITU-T and ISO/IEC teams. HEVC is targeted for high resolution videos such as 4K or 8K resolutions that can fulfil the recent demands for video services. The compression ratio achieved by the HEVC is twice as compared to its predecessor H.264/AVC for same quality level. The compression efficiency is generally increased by removing more correlation between the frames/pixels using complex techniques such as extensive intra and inter prediction techniques. As more correlation is removed, the chances of interdependency among coded bits increases. Thus, bit errors may have large effect on the reconstructed video. Sometimes even single bit error can lead to catastrophic failure of the reconstructed video. In this paper, we study the performance of HEVC bitstream over additive white Gaussian noise (AWGN) channel. Moreover, HEVC over Quadrature Amplitude Modulation (QAM) combined with forward error correction (FEC) schemes are also explored over the noisy channel. The video will be encoded using HEVC, and the coded bitstream is channel coded to provide some redundancies. The channel coded bitstream is then modulated using QAM and transmitted over AWGN channel. At the receiver, the symbols are demodulated and channel decoded to obtain the video bitstream. The bitstream is then used to reconstruct the video using HEVC decoder. It is observed that as the signal to noise ratio of channel is decreased the quality of the reconstructed video decreases drastically. Using proper FEC codes, the quality of the video can be restored up to certain extent. Thus, the performance analysis of HEVC presented in this paper may assist in designing the optimized code rate of FEC such that the quality of the reconstructed video is maximized over wireless channels.

Keywords: AWGN, forward error correction, HEVC, video coding, QAM

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Authors: Rakesh Tiwary, D. M. Diwakar, Sandhya Mahapatro

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Agro-forestry offers huge opportunities for diversification of agriculture in middle Gangetic Basin of India, particularly in the state of Bihar as the region is identified with traditional & stagnant agriculture, low productivity, high population pressure, rural poverty and lack of agro- industrial development. The region is endowed with favourable agro-climatic, soil & drainage conditions; interestingly, there has been an age old tradition of agro-forestry in the state. However, due to demographic pressures, declining land holdings and other socio- economic factors, agro forestry practices have declined in recent decades. The government of Bihar has initiated a special program for expansion of agro-forestry based on modern practices with an aim to raise income level of farmers, make available raw material for wood based industries and increase green cover in the state. The Agro-forestry Schemes – Poplar & Other Species are the key components of the program being implemented by Department of Environment & Forest, Govt. of Bihar. The paper is based on fieldwork based evaluation study on experiences of implementation of the agro-forestry schemes. Understanding adoption patterns, identification of key motives for practising agro-forestry, experiences of farmers well analysing the barriers in expansion constituted the major themes of the research study. This paper is based on primary as well as secondary data. The primary data consists of beneficiary household survey, Focus Group Discussions among beneficiary communities, dialogue and multi stakeholder meetings and field visit to the sites. The secondary data information was collected and analysed from official records, policy documents and reports. Primary data was collected from about 500 beneficiary households of Muzaffarpur & Saharsa- two populous, large and agriculture dominated districts of middle Gangetic basin of North Bihar. Survey also covers 100 households of non-beneficiaries. Probability Proportionate to Size method was used to determine the number of samples to be covered in different blocks of two districts. Qualitative tools were also implemented to have better insights about key research questions. Present paper discusses socio-economic background of farmers practising agro-forestry; the adoption patterns of agro- forestry (choice of plants, methods of plantation and others); and motivation behind adoption of agro-forestry and the comparative benefits of agro-forestry (vis-a-vis traditional agriculture). Experience of beneficiary farmers with agro-forestry based on government programs & promotional campaigns (in terms of awareness, ease of access, knowhow and others) have been covered in the paper. Different aspects of survival of plants have been closely examined. Non beneficiaries but potential adopters were also interviewed to understand barriers of adoption of agro- forestry. Paper provides policy recommendations and interventions required for effective expansion of the agro- forestry and realisation of its future prospects for agricultural diversification in the region.

Keywords: agro-forestry adoption patterns, farmers’ motivations & experiences, Indian middle Gangetic plains, strategies for expansion

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Authors: Ahmed Abdulrahman, Jalal Foroozesh

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CO₂ based enhanced oil recovery (EOR) techniques have gained massive attention from major oil firms since they resolve the industry's two main concerns of CO₂ contribution to the greenhouse effect and the declined oil production. Carbonated water injection (CWI) is a promising EOR technique that promotes safe and economic CO₂ storage; moreover, it mitigates the pitfalls of CO₂ injection, which include low sweep efficiency, early CO₂ breakthrough, and the risk of CO₂ leakage in fractured formations. One of the main challenges that hinder the wide adoption of this EOR technique is the complexity of accurate modeling of the kinetics of CO₂ mass transfer. The mechanisms of CO₂ mass transfer during CWI include the slow and gradual cross-phase CO₂ diffusion from carbonated water (CW) to the oil phase and the CO₂ dispersion (within phase diffusion and mechanical mixing), which affects the oil physical properties and the spatial spreading of CO₂ inside the reservoir. A 2D non-equilibrium compositional simulator has been developed using a fully implicit finite difference approximation. The material balance term (k) was added to the governing equation to account for the slow cross-phase diffusion of CO₂ from CW to the oil within the gird cell. Also, longitudinal and transverse dispersion coefficients have been added to account for CO₂ spatial distribution inside the oil phase. The CO₂-oil diffusion coefficient was calculated using the Sigmund correlation, while a scale-dependent dispersivity was used to calculate CO₂ mechanical mixing. It was found that the CO₂-oil diffusion mechanism has a minor impact on oil recovery, but it tends to increase the amount of CO₂ stored inside the formation and slightly alters the residual oil properties. On the other hand, the mechanical mixing mechanism has a huge impact on CO₂ spatial spreading (accurate prediction of CO₂ production) and the noticeable change in oil physical properties tends to increase the recovery factor. A sensitivity analysis has been done to investigate the effect of formation heterogeneity (porosity, permeability) and injection rate, it was found that the formation heterogeneity tends to increase CO₂ dispersion coefficients, and a low injection rate should be implemented during CWI.

Keywords: CO₂ mass transfer, carbonated water injection, CO₂ dispersion, CO₂ diffusion, cross phase CO₂ diffusion, within phase CO2 diffusion, CO₂ mechanical mixing, non-equilibrium simulation

Procedia PDF Downloads 176

Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

Procedia PDF Downloads 79

Authors: Adnan A. Kadi, Nasser S. Al-Shakliah, Haitham Al-Rabiah

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Zorifertinib is a novel, potent, oral, a small molecule used to treat non-small cell lung cancer (NSCLC). zorifertinib is an Epidermal Growth Factor Receptor (EGFR) inhibitor and has good blood–brain barrier permeability for (NSCLC) patients with EGFR mutations. zorifertinibis currently at phase II/III clinical trials. The current research reports the characterization and identification of in vitro, in vivo and reactive intermediates of zorifertinib. Prediction of susceptible sites of metabolism and reactivity pathways (cyanide and GSH) of zorifertinib were performed by the Xenosite web predictor tool. In-vitro metabolites of zorifertinib were performed by incubation with rat liver microsomes (RLMs) and isolated perfused rat liver hepatocytes. Extraction of zorifertinib and it's in vitro metabolites from the incubation mixtures were done by protein precipitation. In vivo metabolism was done by giving a single oral dose of zorifertinib(10 mg/Kg) to Sprague Dawely rats in metabolic cages by using oral gavage. Urine was gathered and filtered at specific time intervals (0, 6, 12, 18, 24, 48, 72,96and 120 hr) from zorifertinib dosing. A similar volume of ACN was added to each collected urine sample. Both layers (organic and aqueous) were injected into liquid chromatography ion trap mass spectrometry(LC-IT-MS) to detect vivozorifertinib metabolites. N-methyl piperizine ring and quinazoline group of zorifertinib undergoe metabolism forming iminium and electro deficient conjugated system respectively, which are very reactive toward nucleophilic macromolecules. Incubation of zorifertinib with RLMs in the presence of 1.0 mM KCN and 1.0 Mm glutathione were made to check reactive metabolites as it is often responsible for toxicities associated with this drug. For in vitro metabolites there were nine in vitro phase I metabolites, four in vitro phase II metabolites, eleven reactive metabolites(three cyano adducts, five GSH conjugates metabolites, and three methoxy metabolites of zorifertinib were detected by LC-IT-MS. For in vivo metabolites, there were eight in vivo phase I, tenin vivo phase II metabolitesofzorifertinib were detected by LC-IT-MS. In vitro and in vivo phase I metabolic pathways wereN- demthylation, O-demethylation, hydroxylation, reduction, defluorination, and dechlorination. In vivo phase II metabolic reaction was direct conjugation of zorifertinib with glucuronic acid and sulphate.

Keywords: in vivo metabolites, in vitro metabolites, cyano adducts, GSH conjugate

Procedia PDF Downloads 198

Authors: Janet Modu, Jean-Francois Georgin, Laurent Briancon, Eric Antoinet

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The current practice during the repowering phase of wind turbines is deconstruction of existing foundations and construction of new foundations to accept larger wind loads or once the foundations have reached the end of their service lives. The ongoing research project FUI25 FEDRE (Fondations d’Eoliennes Durables et REpowering) therefore serves to propose scalable wind turbine foundation designs to allow reuse of the existing foundations. To undertake this research, numerical models and laboratory-scale models are currently being utilized and implemented in the GEOMAS laboratory at INSA Lyon following instrumentation of a reference wind turbine situated in the Northern part of France. Sensors placed within both the foundation and the underlying soil monitor the evolution of stresses from the foundation’s early age to stresses during service. The results from the instrumentation form the basis of validation for both the laboratory and numerical works conducted throughout the project duration. The study currently focuses on the effect of coupled mechanisms (Thermal-Hydro-Mechanical-Chemical) that induce stress during the early age of the reinforced concrete foundation, and scale factor considerations in the replication of the reference wind turbine foundation at laboratory-scale. Using THMC 3D models on COMSOL Multi-physics software, the numerical analysis performed on both the laboratory-scale and the full-scale foundations simulate the thermal deformation, hydration, shrinkage (desiccation and autogenous) and creep so as to predict the initial damage caused by internal processes during concrete setting and hardening. Results show a prominent effect of early age properties on the damage potential in full-scale wind turbine foundations. However, a prediction of the damage potential at laboratory scale shows significant differences in early age stresses in comparison to the full-scale model depending on the spatial position in the foundation. In addition to the well-known size effect phenomenon, these differences may contribute to inaccuracies encountered when predicting ultimate deformations of the on-site foundation using laboratory scale models.

Keywords: cement hydration, early age behavior, reinforced concrete, shrinkage, THMC 3D models, wind turbines

Procedia PDF Downloads 175

Authors: Mohammad Borhani, Ahmad Jamshidzaei, Mehdi Koohsari

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The study of climate has captivated human interest throughout history. In response to this fascination, individuals historically organized their daily activities in alignment with prevailing climatic conditions and seasonal variations. Understanding the elements and specific climatic parameters of each region, such as precipitation, which directly impacts human life, is essential because, in recent years, there has been a significant increase in heavy rainfall in various parts of the world attributed to the effects of climate change. Climate prediction models suggest a future scenario characterized by an increase in severe precipitation events and related floods on a global scale. This is a result of human-induced greenhouse gas emissions causing changes in the natural precipitation patterns. The Intergovernmental Panel on Climate Change reported global warming in 2001. The average global temperature has shown an increasing trend since 1861. In the 20th century, this increase has been between (0/2 ± 0/6) °C. The present study focused on examining the trend of monthly, seasonal, and annual precipitation in Sistan and Baluchestan provinces. The study employed data obtained from 13 precipitation measurement stations managed by the Iran Water Resources Management Company, encompassing daily precipitation records spanning the period from 1997 to 2016. The results indicated that the total monthly precipitation at the studied stations in Sistan and Baluchestan province follows a sinusoidal trend. The highest intense precipitation was observed in January, February, and March, while the lowest occurred in September, October, and then November. The investigation of the trend of seasonal precipitation in this province showed that precipitation follows an upward trend in the autumn season, reaching its peak in winter, and then shows a decreasing trend in spring and summer. Also, the examination of average precipitation indicated that the highest yearly precipitation occurred in 1997 and then in 2004, while the lowest annual precipitation took place between 1999 and 2001. The analysis of the annual precipitation trend demonstrates a decrease in precipitation from 1997 to 2016 in Sistan and Baluchestan province.

Keywords: climate change, extreme precipitation, greenhouse gas, trend analysis

Procedia PDF Downloads 66

Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

Procedia PDF Downloads 302

Authors: Oscar Norman Nekesa, Yoshitaka Kajita

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Tom Mboya Street is a vital urban corridor within the spectrum of Nairobi city, it experiences high volumes of pedestrian and vehicular traffic. Despite past intervention measures to lessen this catastrophe, rates have remained high. This highlights significant safety concerns that need urgent attention. This study investigates the correlation and pedestrian accident predictability with significant independent variables using multiple linear regression to model to develop effective mobility management strategies for accident mitigation. The methodology involves collecting and analyzing data on pedestrian accidents and various related independent variables. Data sources include the National Transport and Safety Authority (NTSA), Kenya National Bureau of Statistics, and Nairobi City County records, covering five years. This study aims to investigate that traffic volumes (pedestrian and vehicle), Vehicular speed, human factors, illegal parking, policy issues, urban-land use, built environment, traffic signals conditions, inadequate lighting, and insufficient traffic control measures significantly have predictability with the rate of pedestrian accidents. Explanatory variables related to road design and geometry are significant in predictor models for the Tom Mboya Road link but less influential in junction along the 5 km stretch road models. The most impactful variable across all models was vehicular traffic flow. The study recommends infrastructural improvements, enhanced enforcement, and public awareness campaigns to reduce accidents and improve urban mobility. These insights can inform policy-making and urban planning to enhance pedestrian safety along the dense packed Tom Mboya Street and similar urban settings. The findings will inform evidence-based interventions to enhance pedestrian safety and improve urban mobility.

Keywords: multiple linear regression, urban mobility, traffic management, Nairobi, Tom Mboya street, infrastructure conditions., pedestrian safety, correlation and prediction

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Authors: Tanveer Ahmed Choudhury

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Background: Bangladesh is one of the largest deltas in the world, with high population density and high rates of poverty and illiteracy. 80% of the country is on low-lying floodplains, leaving the country one of the most vulnerable to the adverse effects of climate change: sea level rise, cyclones and storms, salinity intrusion, rising temperatures and heavy monsoon downpours. Such climatic events already limit Economic Development in the country. Although Bangladesh has had little responsibility in contributing to global climatic change, it is vulnerable to both its direct and indirect impacts. Real threats include reduced agricultural production, worsening food security, increased incidence of flooding and drought, spreading disease and an increased risk of conflict over scarce land and water resources. Currently, 8.3 million Bangladeshis live in cyclone high risk areas. However, by 2050 this is expected to grow to 20.3 million people, if proper adaptive actions are not taken. Under a high emissions scenario, an additional 7.6 million people will be exposed to very high salinity by 2050 compared to current levels. It is also projected that, an average of 7.2 million people will be affected by flooding due to sea level rise every year between 2070-2100 and If global emissions decrease rapidly and adaptation interventions are taken, the population affected by flooding could be limited to only about 14,000 people. To combat the climate change adverse effects, Bangladesh government has initiated many adaptive measures specially in infrastructure and renewable energy sector. Government is investing huge money and initiated many projects which have been proved very success full. Objectives: The objective of this paper is to describe some successful measures initiated by Bangladesh government in its effort to make the country a Climate Resilient. Methodology: Review of operation plan and activities of different relevant Ministries of Bangladesh government. Result: The following initiative projects, programs and activities are considered as best practices for Climate Change adaptation successes for Bangladesh: 1. The Infrastructure Development Company Limited (IDCOL); 2. Climate Change and Health Promotion Unit (CCHPU); 3. The Climate Change Trust Fund (CCTF); 4. Community Climate Change Project (CCCP); 5. Health, Population, Nutrition Sector Development Program (HPNSDP, 2011-2016)- "Climate Change and Environmental Issues"; 6. Ministry of Health and Family Welfare, Bangladesh and WHO Collaboration; - National Adaptation Plan. -"Building adaptation to climate change in health in least developed countries through resilient WASH". 7. COP-21 “Climate and health country profile -2015 Bangladesh. Conclusion: Due to a vast coastline, low-lying land and abundance of rivers, Bangladesh is highly vulnerable to climate change. Having extensive experience with facing natural disasters, Bangladesh has developed a successful adaptation program, which led to a significant reduction in casualties from extreme weather events. In a low income country setting, Bangladesh had successfully adapted various projects and initiatives to combat future Climate Change challenges.

Keywords: climate, change, success, Bangladesh

Procedia PDF Downloads 249

Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

Procedia PDF Downloads 92