Search results for: evaluation of digital evidence

Authors: Elena Listo Ubeda, Miguel Marchamalo Sacristan

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The demand for water doubles every twenty years, at a rate which is twice as fast as the world´s population growth. Despite it´s great importance, water is one of the most degraded natural resources in the world, mainly because of the reduction of natural vegetation coverage, population growth, contamination and changes in the soil use which reduces its capacity to collect water. This situation is especially serious in Central America, as reflected in the Human Development reports. The objective of this project is to assist in the improvement of water production and quality in Central America. In order to do these two watersheds in Costa Rica were selected as experiments: that of the Virilla-Durazno River, located in the extreme north east of the central valley which has an Atlantic influence; and that of the Jabillo River, which flows directly into the Pacific. The Virilla river watershed is located over andisols, and that of the Jabillo River is over alfisols, and both are of great importance for water supply to the Greater Metropolitan Area and the future tourist resorts respectively, as well as for the production of agriculture, livestock and hydroelectricity. The hydrological reaction in different soil-cover complexes, varying from the secondary forest to natural vegetation and degraded pasture, was analyzed according to the evaluation of the properties of the soil, infiltration, soil compaction, as well as the effects of the soil cover complex on erosion, calculated by the C factor of the Revised Universal Soil Loss Equation (RUSLE). A water balance was defined for each watershed, in which the volume of water that enters and leaves were estimated, as well as the evapotranspiration, runoff, and infiltration. Two future scenarios, representing the implementation of reforestation and deforestation plans, were proposed, and were analyzed for the effects of the soil cover complex on the water balance in each case. The results obtained show an increase of the ground water recharge in the humid forest areas, and an extension of the study of the dry areas is proposed since the ground water recharge here is diminishing. These results are of great significance for the planning, design of Payment Schemes for Environmental Services and the improvement of the existing water supply systems. In Central America spatial planning is a priority, as are the watersheds, in order to assess the water resource socially and economically, and securing its availability for the future.

Keywords: Costa Rica, infiltration, soil, water

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Authors: Florim Grajcevci, Flamur Grajcevci, Fatos Tahiri, Hamdi Kurteshi

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The territory of Kosova is actually included in one of the most seismic-prone regions in Europe. Therefore, the earthquakes are not so rare in Kosova; and when they occurred, the consequences have been rather destructive. The importance of assessing the seismic resistance of existing masonry structures has drawn strong and growing interest in the recent years. Engineering included those of Vulnerability, Loss of Buildings and Risk assessment, are also of a particular interest. This is due to the fact that this rapidly developing field is related to great impact of earthquakes on the socioeconomic life in seismic-prone areas, as Kosova and Prishtina are, too. Such work paper for Prishtina city may serve as a real basis for possible interventions in historic buildings as are museums, mosques, old residential buildings, in order to adequately strengthen and/or repair them, by reducing the seismic risk within acceptable limits. The procedures of the vulnerability assessment of building structures have concentrated on structural system, capacity, and the shape of layout and response parameters. These parameters will provide expected performance of the very important existing building structures on the vulnerability and the overall behavior during the earthquake excitations. The structural systems of existing historical buildings in Pristina, Kosovo, are dominantly unreinforced brick or stone masonry with very high risk potential from the expected earthquakes in the region. Therefore, statistical analysis based on the observed damage-deformation, cracks, deflections and critical building elements, would provide more reliable and accurate results for the regional assessments. The analytical technique was used to develop a preliminary evaluation methodology for assessing seismic vulnerability of the respective structures. One of the main objectives is also to identify the buildings that are highly vulnerable to damage caused from inadequate seismic performance-response. Hence, the damage scores obtained from the derived vulnerability functions will be used to categorize the evaluated buildings as “stabile”, “intermediate”, and “unstable”. The vulnerability functions are generated based on the basic damage inducing parameters, namely number of stories (S), lateral stiffness (LS), capacity curve of total building structure (CCBS), interstory drift (IS) and overhang ratio (OR).

Keywords: vulnerability, ductility, seismic microzone, ductility, energy efficiency

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Authors: M. Turmanauli, T. Todua, O. Gvaberidze, R. Javakhadze, N. Chkhaidze, N. Khatiashvili

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Background: Mining process has the significant influence on human health and quality of life. In recent years the events in Georgia were reflected on the industry working process, especially minimal requirements of labor safety, hygiene standards of workplace and the regime of work and rest are not observed. This situation is often caused by the lack of responsibility, awareness, and knowledge both of workers and employers. The control of working conditions and its protection has been worsened in many of industries. Materials and Methods: For evaluation of the current situation the prospective epidemiological study by face to face interview method was conducted at Georgian “Manganese Zestafoni Ferroalloy Plant” in 2011-2013. 65.7% of employees (1428 bulletin) were surveyed and the incidence rates of temporary disability days were studied. Results: The average length of a temporary disability single accident was studied taking into consideration as sex groups as well as the whole cohort. According to the classes of harmfulness the following results were received: Class 2.0-10.3%; 3.1-12.4%; 3.2-35.1%; 3.3-12.1%; 3.4-17.6%; 4.0-12.5%. Among the employees 47.5% and 83.1% were tobacco and alcohol consumers respectively. According to the age groups and years of work on the base of previous experience ≥50 ages and ≥21 years of work data prevalence respectively. The obtained data revealed increased morbidity rate according to age and years of work. It was found that the bone and articulate system and connective tissue diseases, aggravation of chronic respiratory diseases, ischemic heart diseases, hypertension and cerebral blood discirculation were the leading among the other diseases. High prevalence of morbidity observed in the workplace with not satisfactory labor conditions from the hygienic point of view. Conclusion: According to received data the causes of morbidity are the followings: unsafety labor conditions; incomplete of preventive medical examinations (preliminary and periodic); lack of access to appropriate health care services; derangement of gathering, recording, and analysis of morbidity data. This epidemiological study was conducted at the JSC “Manganese Ferro Alloy Plant” according to State program “ Prevention of Occupational Diseases” (Program code is 35 03 02 05).

Keywords: occupational health, mining process, morbidity level, cerebral blood discirculation

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Tamam Albelwi, Robert Rogers, Hans-Peter Kubis

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Background: Exercise is widely acknowledged as a highly important health behavior, which reduces risks related to lifestyle diseases like type 2 diabetes, cardiovascular disease. However, exercise adherence is low in high-risk groups and sedentary lifestyle is more the norm than the exception. Expressed reasons for exercise participation are often based on delayed outcomes related to health threats and benefits but also enjoyment. Whether exercise is perceived as rewarding is well established in animal literature but the evidence is sparse in humans. Additionally, the question how stable any reward is perceived with time delays is an important question influencing decision-making (in favor or against a behavior). For the modality exercise, this has not been examined before. We, therefore, investigated the discounting of pre-established self-selected exercise compared with established rewards of food and money with a computer-based discounting paradigm. We hypothesized that exercise will be discounted like an established reward (food and money); however, we expect that the discounting rate is similar to a consumable reward like food. Additionally, we expected that individuals’ characteristics like preferred intensity, physical activity and body characteristics are associated with discount rates. Methods: 71 participants took part in four sessions. The sessions were designed to let participants select their preferred exercise intensity on a treadmill. Participants were asked to adjust their speed for optimizing pleasantness over an exercise period of up to 30 minutes, heart rate and pleasantness rating was measured. In further sessions, the established exercise intensity was modified and tested on perceptual validity. In the last exercise session rates of perceived exertion was measured on the preferred intensity level. Furthermore, participants filled in questionnaires related to physical activity, mood, craving, and impulsivity and answered choice questions on a bespoke computer task to establish discounting rates of their preferred exercise (kex), their favorite food (kfood) and a value-matching amount of money (kmoney). Results: Participants self-selected preferred speed was 5.5±2.24 km/h, at a heart rate of 120.7±23.5, and perceived exertion scale of 10.13±2.06. This shows that participants preferred a light exercise intensity with low to moderate cardiovascular strain based on perceived pleasantness. Computer assessment of discounting rates revealed that exercise was quickly discounted like a consumable reward, no significant difference between kfood and kex (kfood =0.322±0.263; kex=0.223±0.203). However, kmoney (kmoney=0.080±0.02) was significantly lower than the rates of exercise and food. Moreover, significant associations were found between preferred speed and kex (r=-0.302) and between physical activity levels and preferred speed (r=0.324). Outcomes show that participants perceived and discounted self-selected exercise like an established reward (food and money) but was discounted more like consumable rewards. Moreover, exercise discounting was quicker in individuals who preferred lower speeds, being less physically active. This may show that in a choice conflict between exercise and food the delay of exercise (because of distance) might disadvantage exercise as the chosen behavior particular in sedentary people. Conclusion: exercise can be perceived as a reward and is discounted quickly in time like food. Pleasant exercise experience is connected to low to moderate cardiovascular and perceptual strain.

Keywords: delay discounting, exercise, temporal discounting, time perspective

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Authors: Faheemah N. Mustafaa, Tamarie Macon, Tabbye Chavous

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A major concern of university leaders worldwide is how to create environments where students from diverse racial/ethnic, national, and cultural backgrounds can thrive. Over the past decade or so in the United States, African American women have done exceedingly well in terms of college enrollment, academic performance, and completion. However, the relative academic successes of African American women in higher education has in some ways overshadowed social challenges many Black women continue to encounter on college campuses in the United States. Within predominantly White institutions (PWIs) in particular, there is consistent evidence that many Black students experience racially hostile climates. However, research studies on racial climates within PWIs have mostly focused on cross-sectional comparisons of minority and majority group experiences, and few studies have examined campus racial climate in relation to short- and longer-term well-being. One longitudinal study reported that African American women’s psychological well-being was positively related to their comfort in cross-racial interactions (a concept closely related to campus climate). Thus, our primary research question was: Do African American women’s perceptions of campus climate (tension and positive association) during their freshman year predict their reports of psychological distress and well-being (self-acceptance) during their sophomore year? Participants were part of a longitudinal survey examining African American college students’ academic identity development, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields. The final subsample included 134 self-identified African American/Black women enrolled in PWIs. Accounting for background characteristics (mother’s education, family income, interracial contact, and prior levels of outcomes), we employed hierarchical regression to examine relationships between campus racial climate during freshman year and psychological adjustment one year later. Both regression models significantly predicted African American women’s psychological outcomes (for distress, F(7,91)= 4.34, p < .001; and for self-acceptance, F(7,90)= 4.92, p < .001). Although none of the controls were significant predictors, perceptions of racial tension on campus were associated with both distress and self-acceptance. More perceptions of tension were related to African American women’s greater psychological distress the following year (B= 0.22, p= .01). Additionally, racial tension predicted later self-acceptance in the expected direction: Higher first-year reports of racial tension were related to less positive attitudes toward the self during the sophomore year (B= -0.16, p= .04). However, perceptions that it was normative for Black and White students to socialize on campus (or positive association scores) were unrelated to psychological distress or self-acceptance. Findings highlight the relevance of examining multiple facets of campus racial climate in relation to psychological adjustment, with possible emphasis on the import of racial tension on African American women’s psychological adjustment. Results suggest that negative dimensions of campus racial climate may have lingering effects on psychological well-being, over and above more positive aspects of climate. Thus, programs targeted toward improving student relations on campus should consider addressing cross-racial tensions.

Keywords: higher education, psychological adjustment, university climate, university students

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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

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Authors: Soheila Sadeghi

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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

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Authors: A. Mohammad Abdul Motalib Momin, B. Sheikh Mohammad Adil Uddin, C. Md Mamunur Rashid, D. Sheikh Arman Mahbub, E. Mohammad Sazzad Rahman, F. Abdullah Faruque

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The present study was designed to investigate the antioxidant and cytotoxicity potential of methanol and pet ether extracts of the Lagenaria siceraria (LM, LP), Cucumis sativus (CSM, CSP), Cucurbita maxima (CMM, CMP) plants. For the phytochemical screening, crude extract was tested for the presence of different chemical groups. In Lagenaria siceraria the following groups were identified: alkaloids, steroids, glycosides and saponins for methanol extract and alkaloids, steroids, glycosides, tannins and saponins are for pet ether extract. Glycosides, steroids, alkaloids, saponins and tannins are present in the methanol extract of Cucumis sativus; the pet ether extract has the alkaloids, steroids and saponins. Glycosides, steroids, alkaloids, saponins and tannins are present in both the methanolic and pet ether extract of Cucurbita maxima. In vitro antioxidant activity of the extracts were performed using DPPH radical scavenging, nitric oxide (NO) scavenging, total antioxidant capacity, total phenol content, total flavonoid content, and Cupric Reducing Antioxidant Capacity assays. The most prominent antioxidant activity was observed with the CSM in the DPPH free radical scavenging test with an IC50 value of 1667.23±11.00271 μg/ml as opposed to that of standard ascorbic acid (IC50 value of 15.707± 1.181 μg/ml.) In total antioxidant capacity method, CMP showed the highest activity (427.81±11.4 mg ascorbic acid/g). The total phenolic and flavonoids content were determined by Folin-Ciocalteu Reagent and aluminium chloride colorimetric method, respectively. The highest total phenols and total flavonoids content were found in CMM and LP with the value of 79.06±16.06 mg gallic acid/g & 119.0±1.41 mg quercetin/g, respectively. In nitric oxide (NO) scavenging the most prominent antioxidant activity was observed in CMM with an IC50 value of 8.119± 0.0036 μg/ml. The Cupric reducing capacity of the extracts was strong and dose dependent manner and CSM showed lowest reducing capacity. The cytotoxicity was determined by Brine shrimp lethality test and among these extracts most potent cytotoxicity was shown by CMM with LC50 value 16.98 µg/ml. The obtained results indicate that the investigated plants could be potential sources of natural antioxidants and can be used for various types of diseases.

Keywords: antioxidant, cytotoxicity, methanol, petroleum ether

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Authors: Rebecca-Lee Kuhnert, Ron Rapee

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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

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Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: Noreen Pulte

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Prior to the 'Back to Sleep' Campaign in 1992, 1 of every 300 infants seen by Advanced Practice Providers had plagiocephaly. Insufficient attention is given to plagiocephaly and brachycephaly diagnoses in practice and pediatric education. In this talk, Nurse Practitioners and Pediatric Providers will be able to: (1) identify red flags associated with head shape abnormalities, (2) learn techniques they can teach parents to prevent head shape abnormalities, and (3) differentiate between plagiocephaly, brachycephaly, and craniosynostosis. The presenter is a Primary Care Pediatric Nurse Practitioner at Ann & Robert H. Lurie Children's Hospital of Chicago and the primary provider for its head shape abnormality clinics. She will help participants translate key information obtained from birth history, review of systems, and developmental history to understand risk factors for head shape abnormalities and progression of deformities. Synostotic and non-synostotic head shapes will be explained to help participants differentiate plagiocephaly and brachycephaly from synostotic head shapes. This knowledge is critical for the prompt referral of infants with craniosynostosis for surgical evaluation and correction. Rapid referral for craniosynostosis can possibly direct the patient to a minimally invasive surgical procedure versus a craniectomy. As for plagiocephaly and brachycephaly, this timely referral can also aid in a physical therapy referral if necessitated, which treats torticollis and aids in improving head shape. A well-timed referral to a head shape clinic can possibly eliminate the need for a helmet and/or minimize the time in a helmet. Practitioners will learn the importance of obtaining head measurements using calipers. The presenter will explain head calculations and how the calculations are interpreted to determine the severity of the head shape abnormalities. Severity defines the treatment plan. Participants will learn when to refer patients to a head shape abnormality clinic and techniques they should teach parents to perform while waiting for the referral appointment. The purpose, mechanics, and logistics of helmet therapy, including optimal time to initiate helmet therapy, recommended helmet wear-time, and tips for helmet therapy compliance, will be described. Case scenarios will be incorporated into the presenter's presentation to support learning. The salient points of the case studies will be explained and discussed. Practitioners will be able to immediately translate the knowledge and skills gained in this presentation into their clinical practice.

Keywords: plagiocephaly, brachycephaly, craniosynostosis, red flags

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: Franco Primo Soffietti, Diego Fernando Turello, Federico Pinto

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Shear waves that propagate through the ground impose deformations that must be taken into account in the design and assessment of buried longitudinal structures such as tunnels, pipelines, and piles. Conventional engineering approaches for seismic evaluation often rely on a Euler-Bernoulli beam models supported by a Winkler foundation. This approach, however, falls short in capturing the distortions induced when the structure is subjected to shear waves. To overcome these limitations, in the present work an analytical solution is proposed considering a Timoshenko beam and including transverse and rotational springs. The present research proposes ground springs derived as closed-form analytical solutions of the equations of elasticity including the seismic wavelength. These proposed springs extend the applicability of previous plane-strain models. By considering variations in displacements along the longitudinal direction, the presented approach ensures the springs do not approach zero at low frequencies. This characteristic makes them suitable for assessing pseudo-static cases, which typically govern structural forces in kinematic interaction analyses. The results obtained, validated against existing literature and a 3D Finite Element model, reveal several key insights: i) the cutoff frequency significantly influences transverse and rotational springs; ii) neglecting displacement variations along the structure axis (i.e., assuming plane-strain deformation) results in unrealistically low transverse springs, particularly for wavelengths shorter than the structure length; iii) disregarding lateral displacement components in rotational springs and neglecting variations along the structure axis leads to inaccurately low spring values, misrepresenting interaction phenomena; iv) transverse springs exhibit a notable drop in resonance frequency, followed by increasing damping as frequency rises; v) rotational springs show minor frequency-dependent variations, with radiation damping occurring beyond resonance frequencies, starting from negative values. This comprehensive analysis sheds light on the complex behavior of embedded longitudinal structures when subjected to shear waves and provides valuable insights for the seismic assessment.

Keywords: shear waves, Timoshenko beams, Winkler springs, sol-structure interaction

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Authors: Maryam Hajrezaie, Mahmood Ameen Abdulla, Nazia Abdul Majid, Hapipa Mohd Ali, Pouya Hassandarvish, Maryam Zahedi Fard

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Background: Colon cancer is one of the most prevalent cancers in the world and is the third leading cause of death among cancers in both males and females. The incidence of colon cancer is ranked fourth among all cancers but varies in different parts of the world. Cancer chemoprevention is defined as the use of natural or synthetic compounds capable of inducing biological mechanisms necessary to preserve genomic fidelity. Andrographolide is the major labdane diterpenoidal constituent of the plant Andrographis paniculata (family Acanthaceae), used extensively in the traditional medicine. Extracts of the plant and their constituents are reported to exhibit a wide spectrum of biological activities of therapeutic importance. Laboratory animal model studies have provided evidence that Andrographolide play a role in inhibiting the risk of certain cancers. Objective: Our aim was to evaluate the chemopreventive efficacy of the Andrographolide in the AOM induced rat model. Methods: To evaluate inhibitory properties of andrographolide on colonic aberrant crypt foci (ACF), five groups of 7-week-old male rats were used. Group 1 (control group) were fed with 10% Tween 20 once a day, Group 2 (cancer control) rats were intra-peritoneally injected with 15 mg/kg Azoxymethan, Gropu 3 (drug control) rats were injected with 15 mg/kg azoxymethan and 5-Flourouracil, Group 4 and 5 (experimental groups) were fed with 10 and 20 mg/kg andrographolide each once a day. After 1 week, the treatment group rats received subcutaneous injections of azoxymethane, 15 mg/kg body weight, once weekly for 2 weeks. Control rats were continued on Tween 20 feeding once a day and experimental groups 10 and 20 mg/kg andrographolide feeding once a day for 8 weeks. All rats were sacrificed 8 weeks after the azoxymethane treatment. Colons were evaluated grossly and histopathologically for ACF. Results: Administration of 10 mg/kg and 20 mg/kg andrographolide were found to be effectively chemoprotective, as evidenced microscopily and biochemically. Andrographolide suppressed total colonic ACF formation up to 40% to 60%, respectively, when compared with control group. Pre-treatment with andrographolide, significantly reduced the impact of AOM toxicity on plasma protein and urea levels as well as on plasma aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH) and gamma-glutamyl transpeptidase (GGT) activities. Grossly, colorectal specimens revealed that andrographolide treatments decreased the mean score of number of crypts in AOM-treated rats. Importantly, rats fed andrographolide showed 75% inhibition of foci containing four or more aberrant crypts. The results also showed a significant increase in glutathione (GSH), superoxide dismutase (SOD), nitric oxide (NO), and Prostaglandin E2 (PGE2) activities and a decrease in malondialdehyde (MDA) level. Histologically all treatment groups showed a significant decrease of dysplasia as compared to control group. Immunohistochemical staining showed up-regulation of Hsp70 and down-regulation of Bax proteins. Conclusion: The current study demonstrated that Andrographolide reduce the number of ACF. According to these data, Andrographolide might be a promising chemoprotective activity, in a model of AOM-induced in ACF.

Keywords: chemopreventive, andrographolide, colon cancer, aberrant crypt foci (ACF)

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Authors: Soheila Sadeghi

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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

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Authors: Sana Fatima, Paul Sadler, Jon Cooper, David Mendel, Ayesha Jameel

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Background: Neurodiversity refers to intrinsic differences between human minds and encompasses dyspraxia, dyslexia, attention deficit hyperactivity disorder, dyscalculia, autism spectrum disorder, and Tourette syndrome. There is increasing recognition of neurodiversity in relation to disability/diversity in medical education and the associated impact on training, career progression, and personal and professional wellbeing. In addition, documented and anecdotal evidence suggests that medical educators and training providers in all four nations (UK) are increasingly concerned about understanding neurodiversity and identifying and providing support for neurodivergent trainees. Summary of Work: A national Neurodiversity Task and Finish group were established to survey Health Education England local office Professional Support teams about insights into infrastructure, training for educators, triggers for assessment, resources, and intervention protocols. This group drew from educational leadership, professional and personal neurodiverse expertise, occupational medicine, employer human resource, and trainees. An online, exploratory survey was conducted to gather insights from supervisors and trainers across England using the Professional Support Units' platform. Summary of Results: This survey highlighted marked heterogeneity in the identification, assessment, and approaches to support and management of neurodivergent trainees and highlighted a 'deficit' approach to neurodiversity. It also demonstrated a paucity of educational and protocol resources for educators and supervisors in supporting neurodivergent trainees. Discussions and Conclusions: In phase one, we focused on faculty development. An educational repository for all supervising trainees using a thematic approach was formalised. This was guided by our survey findings specific for neurodiversity and took a triple 'A' approach: awareness, assessment, and action. This is further supported by video material incorporating stories in training as well as mobile workshops for trainers for more immersive learning. The subtle theme from both the survey and Task and finish group suggested a move away from deficit-focused methods toward a positive holistic, interdisciplinary approach within a biopsychosocial framework. Contributions: 1. Faculty Knowledge and basic understanding of neurodiversity are key to supporting trainees with known or underlying Neurodiverse conditions. This is further complicated by challenges around non-disclosure, varied presentations, stigma, and intersectionality. 2. There is national (and international) inconsistency in the approach to how trainees are managed once a neurodiverse condition is suspected or diagnosed. 3. A carefully constituted and focussed Task and Finish group can rapidly identify national inconsistencies in neurodiversity and implement rapid educational interventions. 4. Nuanced findings from surveys and discussion can reframe the approach to neurodiversity; from a medical model to a more comprehensive, asset-based, biopsychosocial model of support, fostering a cultural shift, accepting 'diversity' in all its manifestations, visible and hidden.

Keywords: neurodiversity, professional support, human considerations, workplace wellbeing

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Adnan Celik

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Entrepreneurs are people who attempt to do a business and do not hesitate to do so. They are involved in the production of economic goods and services through factors of production. They also find the financial resources necessary for production and the markets where the production will be evaluated. After all, they create economic values. The main function of the entrepreneur in contemporary societies is to realize innovations. From this point, the power of the modern entrepreneur is based on her/his capacity to innovate and transform his innovations into tangible commercial products. In this context, the concept of an entrepreneur is used to mean the person or persons who constantly innovate. Successful entrepreneurs take on the role of the locomotive in the development of their countries. They support economic development with their activities. In addition to production and marketing activities, it also has important contributions to employment. Along with the development of the country, they also try to make the income distribution more balanced. Especially developed country entrepreneurs intensely perform the following functions; “to produce new goods and services or to increase the quality and quality of known goods and services; ability to develop and apply new production methods; establishing new organizations in the industry; reach new markets; to find new sources from which raw materials and similar materials can be obtained”. Entrepreneurs who fully implement business functions are easier to achieve economic efficiency. Thus, they provide great advantages to the business and the national economy. Successful entrepreneurs are people who make money by creating economic values. These revenues are; on the one hand, it is distributed to individuals in the business as wages, premiums, or dividends; It is also used in the growth of companies. Thus, employees, managers, entrepreneurs and the whole country can benefit greatly. In the least developed countries, the guiding effect of traditional value patterns on individuals' attitudes and behaviors varies depending on the socio-economic characteristics of individuals. It is normal for an entrepreneur with a low level of education, who was brought up in a traditional structure, to behave in accordance with traditional value patterns. In fact, this is the primary problem of all countries in the development effort. The solution to this problem will be possible by giving the necessary importance to the social dimension as well as the technical dimension of development. This study mainly focuses on the importance of entrepreneurship for the national economy. This issue has been handled separately in terms of developed and least developed countries. As a result of the study, entrepreneurship suggestions were made, especially to least developed countries, with the goal of national economy and development.

Keywords: entrepreneur, entrepreneurship, national economy, entrepreneurship in developed and least developed countries

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Jaspreet Kaur, Parminder Nain, Vipin Saini, Sumitra Dahiya

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Elaeocarpus sphaericus has been traditionally used in the Indian traditional medicine system for the treatment of stress, anxiety, depression, palpitation, epilepsy, migraine and lack of concentration. The study was investigated to evaluate the neurological potential such as anxiolytic, muscle relaxant and sedative activity of methanolic extract of Elaeocarpus sphaericus stem bark (MEESSB) in mice. Preliminary phytochemical screening and acute oral toxicity of MEESSB was carried out by using standard methods. The anxiety was induced by employing Elevated Plus-Maze (EPM), Light and Dark Test (LDT), Open Field Test (OFT) and Social Interaction test (SIT). The motor coordination and sedative effect was also observed by using actophotometer, rota-rod apparatus and ketamine-induced sleeping time, respectively. Animals were treated with different doses of MEESSB (i.e.100, 200, 400 and 800 mg/kg orally) and diazepam (2 mg/kg i.p) for 21 days. Brain neurotransmitters like dopamine, serotonin and nor-epinephrine level were estimated by validated methods. Preliminary phytochemical analysis of the extract revealed the presence of tannins, phytosterols, steroids and alkaloids. In the acute toxicity studies, MEESSB was found to be non-toxic and with no mortality. In anxiolytic studies, the different doses of MEESSB showed a significant (p<0.05) effect on EPM and LDT. In OFT and SIT, a significant (p<0.05) increase in ambulation, rearing and social interaction time was observed. In the case of motor coordination activity, the MEESSB does not cause any significant effect on the latency to fall off from the rotarod bar as compared to the control group. Moreover, no significant effects on ketamine-induced sleep latency and total sleeping time induced by ketamine were observed. Results of neurotransmitter estimation revealed the increased concentration of dopamine, whereas the level of serotonin and nor-epinephrine was found to be decreased in the mice brain, with MEESSB at dose 800 mg/kg only. The study has validated the folkloric use of the plant as an anxiolytic in Indian traditional medicine while also suggesting potential usefulness in the treatment of stress and anxiety without causing sedation.

Keywords: anxiolytic, behavior experiments, brain neurotransmitters, elaeocarpus sphaericus

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Authors: Aurora Sheehy, Caitlin Prince

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Within current orthodox medical protocols, trauma and mental health issues are deemed to reside within the realm of cognitive or psychological therapists and are marginalised in these areas, in part due to limited drugs option available, mostly manipulating neurotransmitters or sedating patients to reduce symptoms. By contrast, this research presents examples from the clinical practice of how trauma can be assessed and treated physiologically. Adverse Childhood Experiences (ACEs) are a tally of different types of abuse and neglect. It has been used as a measurable and reliable predictor of the likelihood of the development of autoimmune disease. It is a direct way to demonstrate reliably the health impact of traumatic life experiences. A second assessment tool is Allostatic Load, which refers to the cumulative effects that chronic stress has on mental and physical health. It records the decline of an individual’s physiological capacity to cope with their experience. It uses a specific grouping of serum testing and physical measures. It includes an assessment of neuroendocrine, cardiovascular, immune and metabolic systems. Allostatic load demonstrates the health impact that trauma has throughout the body. It forms part of an initial intake assessment in clinical practice and could also be used in research to evaluate treatment. Examining medicinal plants for their physiological, neurological and somatic effects through the lens of Polyvagal theory offers new opportunities for trauma treatments. In situations where Polyvagal theory recommends activities and exercises to enable parasympathetic activation, many herbs that affect Effector Memory T (TEM) cells also enact these responses. Traditional or Indigenous European herbs show the potential to support the polyvagal tone, through multiple mechanisms. As the ventral vagal nerve reaches almost every major organ, plants that have actions on these tissues can be understood via their polyvagal actions, such as monoterpenes as agents to improve respiratory vagal tone, cyanogenic glycosides to reset polyvagal tone, volatile oils rich in phenyl methyl esters improve both sympathetic and parasympathetic tone, bitters activate gut function and can strongly promote parasympathetic regulation. Auricular Acupuncture uses a system of somatotopic mapping of the auricular surface overlaid with an image of an inverted foetus with each body organ and system featured. Given that the concha of the auricle is the only place on the body where the Vagus Nerve neurons reach the surface of the skin, several investigators have evaluated non-invasive, transcutaneous electrical nerve stimulation (TENS) at auricular points. Drawn from an interdisciplinary evidence base and developed through clinical practice, these assessment and treatment tools are examples of practitioners in the field innovating out of necessity for the best outcomes for patients. This paper draws on case studies to direct future research.

Keywords: polyvagal, auricular acupuncture, trauma, herbs

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Authors: Dina Magnaye

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In the Philippines, the performance of the agricultural sector is gauged through crop productivity and returns from farm production rather than the biodiversity in the agricultural ecosystem. Agricultural development hinges on the overall goal of increasing productivity through intensive agriculture, monoculture system, utilization of high yielding varieties in plants, and genetic upgrading in animals. This merits an analysis of the role of agro-biodiversity in terms of increasing productivity, food security and economic returns from community-based pro-biodiversity enterprises. These enterprises conserve biodiversity while equitably sharing production income in the utilization of biological resources. The study aims to determine how community-based pro-biodiversity enterprises become instrumental in local climate change adaptation and agro-biodiversity conservation as input to local green economic development planning. It also involves an assessment of the role of agrobiodiversity in terms of increasing productivity, food security and economic returns from community-based pro-biodiversity enterprises. The perceptions of the local community members both in urban and upland rural areas on community-based pro-biodiversity enterprises were evaluated. These served as a basis in developing a planning modality that can be mainstreamed in the management of local green economic enterprises to benefit the environment, provide local income opportunities, conserve species diversity, and sustain environment-friendly farming systems and practices. The interviews conducted with organic farmer-owners, entrepreneur-organic farmers, and organic farm workers revealed that pro-biodiversity enterprise such as organic farming involved the cyclic use of natural resources within the carrying capacity of a farm; recognition of the value of tradition and culture especially in the upland rural area; enhancement of socio-economic capacity; conservation of ecosystems in harmony with nature; and climate change mitigation. The suggested planning modality for community-based pro-biodiversity enterprises for a green economy encompasses four (4) phases to include community resource or capital asset profiling; stakeholder vision development; strategy formulation for sustained enterprises; and monitoring and evaluation.

Keywords: agro-biodiversity, agro-biodiversity conservation, local green economy, organic farming, pro-biodiversity enterprise

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Authors: H. C. Chen, S. W. C. Chan, K. Cheng, A. Vathsala, H. K. Sran, H. He

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Background: End-stage renal disease (ESRD) is the last stage of chronic kidney disease. The numbers of patients with ESRD have increased worldwide due to the growing number of aging, diabetes and hypertension populations. Patients with ESRD suffer from physical illness and psychological distress due to complex treatment regimens, which often affect the patients’ social and psychological functioning. As a result, the patients may fail to perform daily self-care and self-management, and consequently experience worsening conditions. Aims: The study aims to examine the effectiveness of a self-efficacy psychoeducational programme on primary outcome (self-efficacy) and secondary outcomes (psychological wellbeing, treatment adherence, and quality of life) in patients with ESRD and haemodialysis in Singapore. Methodology: A randomised controlled, two-group pretest and repeated posttests design will be carried out. A total of 154 participants (n=154) will be recruited. The participants in the control group will receive a routine treatment. The participants in the intervention group will receive a self-efficacy psychoeducational programme in addition to the routine treatment. The programme is a two-session of educational intervention in a week. A booklet, two consecutive sessions of face-to-face individual education, and an abdominal breathing exercise are adopted in the programme. Outcome measurements include Dialysis Specific Self-efficacy Scale, Kidney Disease Quality of Life- 36 Hospital Anxiety and Depression Scale, Renal Adherence Attitudes Questionnaire and Renal Adherence Behaviour Questionnaire. The questionnaires will be used to measure at baseline, 1- and 3- and 6-month follow-up periods. Process evaluation will be conducted with a semi-structured face to face interview. Quantitative data will be analysed using SPSS21.0 software. Qualitative data will be analysed by content analysis. Significance of the study: This study will identify a clinically useful and potentially effective approach to help patients with end-stage renal disease and haemodialysis by enhancing their self-efficacy in self-care behaviour, and therefore improving their psychological well-being, treatment adherence and quality of life. This study will provide information to develop clinical guidelines to improve patients’ disease self-management and to enhance health-related outcomes and it will help reducing disease burden.

Keywords: end-stage renal disease (ESRD), haemodialysis, psychoeducation, self-efficacy

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Authors: Rafia S. Al-lamki, Jun Wang, Simon Pacey, Jordan Pober, John R. Bradley

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Tumor necrosis factor alpha (TNF), signaling through TNFR2, may act an autocrine growth factor for renal tubular epithelial cells. Clear cell renal carcinomas (ccRCC) contain cancer stem cells (CSCs) that give rise to progeny which form the bulk of the tumor. CSCs are rarely in cell cycle and, as non-proliferating cells, resist most chemotherapeutic agents. Thus, recurrence after chemotherapy may result from the survival of CSCs. Therapeutic targeting of both CSCs and the more differentiated bulk tumor populations may provide a more effective strategy for treatment of RCC. In this study, we hypothesized that TNFR2 signaling will induce CSCs in ccRCC to enter cell cycle so that treatment with ligands that engage TNFR2 will render CSCs susceptible to chemotherapy. To test this hypothesis, we have utilized wild-type TNF (wtTNF) or specific muteins selective for TNFR1 (R1TNF) or TNFR2 (R2TNF) to treat either short-term organ cultures of ccRCC and adjacent normal kidney (NK) tissue or cultures of CD133+ cells isolated from ccRCC and adjacent NK, hereafter referred to as stem cell-like cells (SCLCs). The effect of cyclophosphamide (CP), currently an effective anticancer agent, was tested on CD133+SCLCs from ccRCC and NK before and after R2TNF treatment. Responses to TNF were assessed by flow cytometry (FACS), immunofluorescence, and quantitative real-time PCR, TUNEL, and cell viability assays. Cytotoxic effect of CP was analyzed by Annexin V and propidium iodide staining with FACS. In addition, we assessed the effect of TNF on isolated SCLCs differentiation using a three-dimensional (3D) culture system. Clinical samples of ccRCC contain a greater number SCLCs compared to NK and the number of SCSC increases with higher tumor grade. Isolated SCLCs show expression of stemness markers (oct4, Nanog, Sox2, Lin28) but not differentiation markers (cytokeratin, CD31, CD45, and EpCAM). In ccRCC organ cultures, wtTNF and R2TNF increase CD133 and TNFR2 expression and promote cell cycle entry whereas wtTNF and R1TNF increase TNFR1 expression and promote cell death of SCLCs. Similar findings are observed in SCLCs isolated from NK but the effect was greater in SCLCs isolated from ccRCC. Application of CP distinctly triggered apoptotic and necrotic cell death in SLCSs pre-treatment with R2TNF as compared to CP treatment alone, with SCLCs from ccRCC more sensitive to CP compared to SLCS from NK. Furthermore, TNF promotes differentiation of SCLCs to an epithelial phenotype in 3D cultures, confirmed by cytokeratin expression and loss of stemness markers Nanog and Sox2. The differentiated cells show positive expression of TNF and TNFR2. These findings provide evidence that selective engagement of TNFR2 drive CSCs to cell proliferation/differentiation, and targeting of cycling cells with TNFR2 agonist in combination with anti-cancer agents may be a potential therapy for RCC.

Keywords: cancer stem cells, ccRCC, cell cycle, cell death, TNF, TNFR1, TNFR2, CD133

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Authors: Flavien Marteau, Pedro Affonso Nóbrega, Pascal Biwole, Nicolas Autrusson, Iona De Bievre, Christian Beauger

Abstract:

Effective water management is essential for the optimal performance of fuel cells. For this reason, many vehicle systems use a membrane humidifier, a passive device that humidifies the air before the cathode inlet. Although they offer good performance, humidifiers are voluminous, costly, and fragile, hence the desire to find an alternative. Direct water injection could be an option, although this method lacks maturity. It consists of injecting liquid water as a spray in the dry heated air coming out from the compressor. This work focuses on the evaluation of direct water injection and its performance compared to the membrane humidifier selected as a reference. Two architectures were experimentally tested to humidify an industrial 2 kW short stack made up of 20 cells of 150 cm² each. For the reference architecture, the inlet air is humidified with a commercial membrane humidifier. For the direct water injection architecture, a pneumatic nozzle was selected to generate a fine spray in the air flow with a Sauter mean diameter of about 20 μm. Initial performance was compared over the entire range of current based on polarisation curves. Then, the influence of various parameters impacting water management was studied, such as the temperature, the gas stoichiometry, and the water injection flow rate. The experimental results obtained confirm the possibility of humidifying the fuel cell using direct water injection. This study, however shows the limits of this humidification method, the mean cell voltage being significantly lower in some operating conditions with direct water injection than with the membrane humidifier. The voltage drop reaches 30 mV per cell (4 %) at 1 A/cm² (1,8 bara, 80 °C) and increases in more demanding humidification conditions. It is noteworthy that the heat of compression available is not enough to evaporate all the injected liquid water in the case of DWI, resulting in a mix of liquid and vapour water entering the fuel cell, whereas only vapour is present with the humidifier. Variation of the injection flow rate shows that part of the injected water is useless for humidification and seems to cross channels without reaching the membrane. The stack was successfully humidified thanks to direct water injection. Nevertheless, our work shows that its implementation requires substantial adaptations and may reduce the fuel cell stack performance when compared to conventional membrane humidifiers, but opportunities for optimisation have been identified.

Keywords: cathode humidification, direct water injection, membrane humidifier, proton exchange membrane fuel cell

Procedia PDF Downloads 29

Authors: Abdallah M. Fayed

Abstract:

The study area is located in south Darb El Arbaieen, western desert of Egypt. It occupies the area between latitudes 22° 00/ and 22° 30/ North and Longitudes 29° 30/ and 30° 00/ East, from southern border of Egypt to the area north Bir Kuraiym and from the area East of East Owienat to the area west Tushka district, its area about 2750 Km2. The famous features; southern part of Darb El Arbaieen road, G Baraqat El Scab El Qarra, Bir Dibis, Bir El Shab and Bir Kuraiym, Interpretation of soil stratification shows layers that are related to Quaternary and Upper-Lower Cretaceous eras. It is dissected by a series of NE-SW striking faults. The regional groundwater flow direction is in SW-NE direction with a hydraulic gradient is 1m / 2km. Mathematical model program has been applied for evaluation of groundwater potentials in the main Aquifer –Nubian Sandstone- in the area of study and Remote sensing technique is considered powerful, accurate and saving time in this respect. These techniques are widely used for illustrating and analysis different phenomenon such as the new development in the desert (land reclamation), residential development (new communities), urbanization, etc. The major issues concerning water development objective of this work is to determine the new development areas in western desert of Egypt during the period from 2003 to 2015 using remote sensing technique, the impacts of the present and future development have been evaluated by using the two-dimensional numerical groundwater flow Simulation Package (visual modflow 4.2). The package was used to construct and calibrate a numerical model that can be used to simulate the response of the aquifer in the study area under implementing different management alternatives in the form of changes in piezometric levels and salinity. Total period of simulation is 100 years. After steady state calibration, two different scenarios are simulated for groundwater development. 21 production wells are installed at the study area and used in the model, with the total discharge for the two scenarios were 105000 m3/d, 210000 m3/d. The drawdown was 11.8 m and 23.7 m for the two scenarios in the end of 100 year. Contour maps for water heads and drawdown and hydrographs for piezometric head are represented. The drawdown was less than the half of the saturated thickness (the safe yield case).

Keywords: remote sensing, management of aquifer systems, simulation modeling, western desert, South Darb El Arbaieen

Procedia PDF Downloads 391