Search results for: non-linear regression models

Authors: Jack Nash, Chris Simpson, Holly Hurn, Ronel Terblanche, Alan Mistlin

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There is an increasing incidence of mild traumatic brain injury (mTBI) cases throughout sport and with this, a growing interest from governing bodies to ensure these are managed appropriately and player welfare is prioritised. The Berlin consensus statement on concussion in sport recommends a multidisciplinary approach when managing those patients who do not have full resolution of mTBI symptoms. There are as of yet no standardised guideline to follow in the treatment of complex cases mTBI in athletes. The aim of this project was to analyse the outcomes, both clinical and vocational, of all patients admitted to the mild Traumatic Brain Injury (mTBI) service at the UK’s Defence Military Rehabilitation Centre Headley Court between 1st June 2008 and 1st February 2017, as a result of a sport induced injury, and evaluate potential predictive indicators of outcome. Patients were identified from a database maintained by the mTBI service. Clinical and occupational outcomes were ascertained from medical and occupational employment records, recorded prospectively, at time of discharge from the mTBI service. Outcomes were graded based on the vocational independence scale (VIS) and clinical documentation at discharge. Predictive indicators including referral time, age at time of injury, previous mental health diagnosis and a financial claim in place at time of entry to service were assessed using logistic regression. 45 Patients were treated for sport-related mTBI during this time frame. Clinically 96% of patients had full resolution of their mTBI symptoms after input from the mTBI service. 51% of patients returned to work at their previous vocational level, 4% had ongoing mTBI symptoms, 22% had ongoing physical rehabilitation needs, 11% required mental health input and 11% required further vestibular rehabilitation. Neither age, time to referral, pre-existing mental health condition nor compensation seeking had a significant impact on either vocational or clinical outcome in this population. The vast majority of patients reviewed in the mTBI clinic had persistent symptoms which could not be managed in primary care. A consultant-led, multidisciplinary approach to the diagnosis and management of mTBI has resulted in excellent clinical outcomes in these complex cases. High levels of symptom resolution suggest that this referral and treatment pathway is successful and is a model which could be replicated in other organisations with consultant led input. Further understanding of both predictive and individual factors would allow clinicians to focus treatments on those who are most likely to develop long-term complications following mTBI. A consultant-led, multidisciplinary service ensures a large number of patients will have complete resolution of mTBI symptoms after sport-related mTBI. Further research is now required to ascertain the key predictive indicators of outcome following sport-related mTBI.

Keywords: brain injury, concussion, neurology, rehabilitation, sports injury

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Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

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Authors: Pius Borona, Cheikh Mbow, Issa Ouedraogo

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In the Sahel, climate variability has been associated with a complex web of direct and indirect impacts. This natural phenomenon has been an impediment to agro-pastoral communities who experience uncertainty while involving in farming activities which is also their key source of livelihood. In this scenario, the role of climate variability in influencing the performance, quantity and quality of staple cereals yields, vital for food and nutrition security has been a topic of importance. This response of crops and subsequent yield variability is also a subject of immense debate due to the complexity of crop development at different stages. This complexity is further compounded by influence of slowly changing non-climatic factors. With these challenges in mind, the present paper initially explores the occurrence of climate variability at an inter annual and inter decadal level in South Burkina Faso. This is evidenced by variation of the total annual rainfall and the number of rainy days among other climatic descriptors. Further, it is shown how district-scale cereal yields in the study area including maize, sorghum and millet casually associate variably to the inter-annual variation of selected climate variables. Statistical models show that the three cereals widely depict sensitivity to the length of the growing period and total dry days in the growing season. Maize yields on the other hand relate strongly to the rainfall amount variation (R2=51.8%) showing high moisture dependence during critical growth stages. Our conclusions emphasize on adoption of efficient water utilization platforms especially those that have evidently increased yields and strengthening of forecasts dissemination.

Keywords: climate variability, cereal yields, seasonality, rain fed farming, Burkina Faso, rainfall

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Authors: Marija Vitanovа, Igor Gjorgjiev, Viktor Hristovski, Vlado Micov

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Evaluation of stability is very important in the process of definition of optimal structural measures for maintenance of bridge structures and their strengthening. To define optimal measures for their repair and strengthening, it is necessary to evaluate their static and seismic stability. Presented in this paper are methodologies for evaluation of the seismic stability of existing reinforced concrete bridges designed without consideration of seismic effects and checking of structural justification of newly designed bridge structures. All bridges are located in the territory of the Republic of North Macedonia. A total of 26 existing bridges of different structural systems have been analyzed. Visual inspection has been carried out for all bridges, along with the definition of three main damage categories according to which structures have been categorized in respect to the need for their repair and strengthening. Investigations involving testing the quality of the built-in materials have been carried out, and dynamic tests pointing to the dynamic characteristics of the structures have been conducted by use of non-destructive methods of ambient vibration measurements. The conclusions drawn from the performed measurements and tests have been used for the development of accurate mathematical models that have been analyzed for static and dynamic loads. Based on the geometrical characteristics of the cross-sections and the physical characteristics of the built-in materials, interaction diagrams have been constructed. These diagrams along with the obtained section quantities under seismic effects, have been used to obtain the bearing capacity of the cross-sections. The results obtained from the conducted analyses point to the need for the repair of certain structural parts of the bridge structures. They indicate that the stability of the superstructure elements is not critical during a seismic effect, unlike the elements of the sub-structure, whose strengthening is necessary.

Keywords: existing bridges, newly designed bridges, reinforced concrete bridges, stability assessment

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Authors: Aritra Majumdar

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While organizations strive to expand their new customer base, retaining existing relationships is a key aspect of improving overall profitability and also showcasing how successful an organization is in holding on to its customers. It is an experimentally proven fact that the lion’s share of profit always comes from existing customers. Hence seamless management of renewal journeys across different channels goes a long way in improving trust in the brand. From a quality assurance standpoint, time travel testing provides an approach to both business and technology teams to enhance the customer experience when they look to extend their partnership with the organization for a defined phase of time. This whitepaper will focus on key pillars of time travel testing: time travel planning, time travel data preparation, and enterprise automation. Along with that, it will call out some of the best practices and common accelerator implementation ideas which are generic across verticals like healthcare, insurance, etc. In this abstract document, a high-level snapshot of these pillars will be provided. Time Travel Planning: The first step of setting up a time travel testing roadmap is appropriate planning. Planning will include identifying the impacted systems that need to be time traveled backward or forward depending on the business requirement, aligning time travel with other releases, frequency of time travel testing, preparedness for handling renewal issues in production after time travel testing is done and most importantly planning for test automation testing during time travel testing. Time Travel Data Preparation: One of the most complex areas in time travel testing is test data coverage. Aligning test data to cover required customer segments and narrowing it down to multiple offer sequencing based on defined parameters are keys for successful time travel testing. Another aspect is the availability of sufficient data for similar combinations to support activities like defect retesting, regression testing, post-production testing (if required), etc. This section will talk about the necessary steps for suitable data coverage and sufficient data availability from a time travel testing perspective. Enterprise Automation: Time travel testing is never restricted to a single application. The workflow needs to be validated in the downstream applications to ensure consistency across the board. Along with that, the correctness of offers across different digital channels needs to be checked in order to ensure a smooth customer experience. This section will talk about the focus areas of enterprise automation and how automation testing can be leveraged to improve the overall quality without compromising on the project schedule. Along with the above-mentioned items, the white paper will elaborate on the best practices that need to be followed during time travel testing and some ideas pertaining to accelerator implementation. To sum it up, this paper will be written based on the real-time experience author had on time travel testing. While actual customer names and program-related details will not be disclosed, the paper will highlight the key learnings which will help other teams to implement time travel testing successfully.

Keywords: time travel planning, time travel data preparation, enterprise automation, best practices, accelerator implementation ideas

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Authors: Anatoliy A. Alabugin, Nikolay K. Topuzov, Sergei V. Aliukov

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It is well known, that while we do a quantitative evaluation of the quality control of some economic processes (in particular, resource saving) with help innovation factors, there are three groups of problems: high uncertainty of indicators of the quality management, their considerable ambiguity, and high costs to provide a large-scale research. These problems are defined by the use of contradictory objectives of enhancing of the quality control in accordance with innovation factors and preservation of economic stability of the enterprise. The most acutely, such factors are felt in the countries lagging behind developed economies of the world according to criteria of innovativeness and effectiveness of management of the resource saving. In our opinion, the following two methods for reconciling of the above-mentioned objectives and reducing of conflictness of the problems are to solve this task most effectively: 1) the use of paradigms and concepts of evolutionary improvement of quality of resource-saving management in the cycle "from the project of an innovative product (technology) - to its commercialization and update parameters of customer value"; 2) the application of the so-called integrative-cyclical approach which consistent with complexity and type of the concept, to studies allowing to get quantitative assessment of the stages of achieving of the consistency of these objectives (from baseline of imbalance, their compromise to achievement of positive synergies). For implementation, the following mathematical tools are included in the integrative-cyclical approach: index-factor analysis (to identify the most relevant factors); regression analysis of relationship between the quality control and the factors; the use of results of the analysis in the model of fuzzy sets (to adjust the feature space); method of non-parametric statistics (for a decision on the completion or repetition of the cycle in the approach in depending on the focus and the closeness of the connection of indicator ranks of disbalance of purposes). The repetition is performed after partial substitution of technical and technological factors ("hard") by management factors ("soft") in accordance with our proposed methodology. Testing of the proposed approach has shown that in comparison with the world practice there are opportunities to improve the quality of resource-saving management using innovation factors. We believe that the implementation of this promising research, to provide consistent management decisions for reducing the severity of the above-mentioned contradictions and increasing the validity of the choice of resource-development strategies in terms of parameters of quality management and sustainability of enterprise, is perspective. Our existing experience in the field of quality resource-saving management and the achieved level of scientific competence of the authors allow us to hope that the use of the integrative-cyclical approach to the study and evaluation of the resulting and factor indicators will help raise the level of resource-saving characteristics up to the value existing in the developed economies of post-industrial type.

Keywords: integrative-cyclical approach, quality control, evaluation, innovation factors. economic sustainability, innovation cycle of management, disbalance of goals of development

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Authors: Catherine Mangan, Beth Anderson

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There has been a significant drive to use online or hybrid learning in Higher Education (HE) over recent years. HEs with a virtual presence offer their communities a range of benefits, including the potential for greater inclusivity, diversity, and collaboration; more flexible learning packages; and more engaging, dynamic content. Institutions can also experience significant challenges when seeking to extend learning spaces in this way, as can learners themselves. For example, staff members’ and learners’ digital literacy varies (as do their perceptions of technologies in use), and there can be confusion about optimal approaches to implementation. Furthermore, the speed with which HE institutions have needed to shift to fully online or hybrid models, owing to the COVID19 pandemic, has highlighted the significant barriers to successful implementation. HE environments have been shown to predict a range of organisational, academic, and experiential outcomes, both positive and negative. Much research has focused on the social aspect of virtual platforms, as well as the nature and effectiveness of the technologies themselves. There remains, however, a relative paucity of synthesised knowledge on the psychology of learners’ relationships with their institutions; specifically, how individual difference and interpersonal factors predict students’ ability and willingness to engage with novel virtual learning spaces. Accordingly, extending learning spaces remains challenging for institutions, and wholly remote courses, in particular, can experience high attrition rates. Focusing on the last five years, this pragmatic review summarises evidence from the psychological and pedagogical literature. In particular, the review highlights the importance of addressing the psychological and relational complexities of students’ shift from offline to online engagement. In doing so, it identifies considerations for HE institutions looking to deliver in this way.

Keywords: higher education, individual differences, interpersonal relationships, online learning, virtual environment

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Authors: Ahmad Ammar, Umar Khan Khattak, Muhammad Majid

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Empirically based lumped hydrologic models have an extensive track record of use for various watershed managements and flood related studies. This study focuses on the impacts of LULC change for 10 year period on the discharge in watershed using lumped model HEC-HMS. The Indus above Tarbela region acts as a source of the main flood events in the middle and lower portions of Indus because of the amount of rainfall and topographic setting of the region. The discharge pattern of the region is influenced by the LULC associated with it. In this study the Landsat TM images were used to do LULC analysis of the watershed. Satellite daily precipitation TRMM data was used as input rainfall. The input variables for model building in HEC-HMS were then calculated based on the GIS data collected and pre-processed in HEC-GeoHMS. SCS-CN was used as transform model, SCS unit hydrograph method was used as loss model and Muskingum was used as routing model. For discharge simulation years 2000 and 2010 were taken. HEC-HMS was calibrated for the year 2000 and then validated for 2010.The performance of the model was assessed through calibration and validation process and resulted R2=0.92 during calibration and validation. Relative Bias for the years 2000 was -9% and for2010 was -14%. The result shows that in 10 years the impact of LULC change on discharge has been negligible in the study area overall. One reason is that, the proportion of built-up area in the watershed, which is the main causative factor of change in discharge, is less than 1% of the total area. However, locally, the impact of development was found significant in built up area of Mansehra city. The analysis was done on Mansehra city sub-watershed with an area of about 16 km2 and has more than 13% built up area in 2010. The results showed that with an increase of 40% built-up area in the city from 2000 to 2010 the discharge values increased about 33 percent, indicating the impact of LULC change on discharge value.

Keywords: LULC change, HEC-HMS, Indus Above Tarbela, SCS-CN

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Authors: Florian Billing, Soren Segan, Meike Jakobi, Elsa Arefaine, Aliki Jerch, Xin Xiong, Matthias Becker, Thomas Joos, Burkhard Schlosshauer, Ulrich Rothbauer, Nicole Schneiderhan-Marra, Hanna Hartmann, Christopher Shipp

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The immune response plays a major role in implant biocompatibility, but an understanding of how to design biomaterials for specific immune responses is yet to be achieved. We aimed to better understand how changing certain material properties can drive immune responses. To this end, we tested immune response to experimental implant coatings that vary in specific characteristics. A layer-by-layer approach was employed to vary surface charge and wettability. Human-based in vitro models (THP-1 macrophages and primary peripheral blood mononuclear cells (PBMCS)) were used to assess immune responses using multiplex cytokine analysis, flow cytometry (CD molecule expression) and microscopy (cell morphology). We observed dramatic differences in immune response due to specific alterations in coating properties. For example altering the surface charge of coating A from anionic to cationic resulted in the substantial elevation of the pro-inflammatory molecules IL-1beta, IL-6, TNF-alpha and MIP-1beta, while the pro-wound healing factor VEGF was significantly down-regulated. We also observed changes in cell surface marker expression in relation to altered coating properties, such as CD16 on NK Cells and HLA-DR on monocytes. We furthermore observed changes in the morphology of THP-1 macrophages following cultivation on different coatings. A correlation between these morphological changes and the cytokine expression profile is ongoing. Targeted changes in biomaterial properties can produce vast differences in immune response. The properties of the coatings examined here may, therefore, be a method to direct specific biological responses in order to improve implant biocompatibility.

Keywords: biomaterials, coatings, immune system, implants

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Authors: Savas Yildiz

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The article assesses the performance of international aid donors to determine the sub-national distribution of their aid projects dependent on recipient countries’ governance. The present paper extends the scope from a cross-country perspective to a more detailed analysis by looking at the effects of institutional qualities on the sub-national distribution of foreign aid. The analysis examines geo-referenced aid project in 37 countries and 404 regions at the first administrative division level in Sub-Saharan Africa from the World Bank (WB) and the African Development Bank (ADB) that were approved between the years 2000 and 2011. To measure the influence of institutional qualities on the distribution of aid the following measures are used: control of corruption, government effectiveness, regulatory quality and rule of law from the World Governance Indicators (WGI) and the corruption perception index from Transparency International. Furthermore, to assess the importance of ethnic heterogeneity on the sub-national distribution of aid projects, the study also includes interaction terms measuring ethnic fragmentation. The regression results indicate a general skew of aid projects towards regions which hold capital cities, however, being incumbent presidents’ birth region does not increase the allocation of aid projects significantly. Nevertheless, with increasing quality of institutions aid projects are less skewed towards capital regions and the previously estimated coefficients loose significance in most cases. Higher ethnic fragmentation also seems to impede the possibility to allocate aid projects mainly in capital city regions and presidents’ birth places. Additionally, to assess the performance of the WB based on its own proclaimed goal to aim the poor in a country, the study also includes sub-national wealth data from the Demographic and Health Surveys (DSH), and finds that, even with better institutional qualities, regions with a larger share from the richest quintile receive significantly more aid than regions with a larger share of poor people. With increasing ethnic diversity, the allocation of aid projects towards regions where the richest citizens reside diminishes, but still remains high and significant. However, regions with a larger share of poor people still do not receive significantly more aid. This might imply that the sub-national distribution of aid projects increases in general with higher ethnic fragmentation, independent of the diverse regional needs. The results provide evidence that institutional qualities matter to undermine the influence of incumbent presidents on the allocation of aid projects towards their birth regions and capital regions. Moreover, even for countries with better institutional qualities the WB and the ADB do not seem to be able to aim the poor in a country with their aid projects. Even, if one considers need-based variables, such as infant mortality and child mortality rates, aid projects do not seem to be allocated in districts with a larger share of people in need. Therefore, the study provides further evidence using more detailed information on the sub-national distribution of aid projects that aid is not being allocated effectively towards regions with a larger share of poor people to alleviate poverty in recipient countries directly. Institutions do not have any significant influence on the sub-national distribution of aid towards the poor.

Keywords: aid allocation, georeferenced data, institutions, spatial analysis

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Authors: Lavinia Flueckiger, Roselind Lieb, Andrea H. Meyer, Cornelia Witthauer, Jutta Mata

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Objective: Health behaviors tend to show a high variability over time within the same person. However, most existing research can only assess a snapshot of a person’s behavior and not capture this natural daily variability. Two intensive longitudinal studies examine the variability in health behavior over one academic year and their implications for other aspects of daily life such as affect and academic performance. Can already a single day of increased physical activity, snacking, or improved sleep have beneficial effects? Methods: In two intensive longitudinal studies with up to 65 assessment days over an entire academic year, university students (Study 1: N = 292; Study 2: N = 304) reported sleep quality, physical activity, snacking, positive and negative affect, and learning goal achievement. Results: Multilevel structural equation models showed that on days on which participants reported better sleep quality or more physical activity than usual, they also reported increased positive affect, decreased negative affect, and better learning goal achievement. Higher day-to-day snacking was only associated with increased positive affect. Both, increased day-to-day sleep quality and physical activity were indirectly associated with better learning goal achievement through changes in positive and negative affect; results for snacking were mixed. Importantly, day-to-day sleep quality was a stronger predictor for affect and learning goal achievement than physical activity or snacking. Conclusion: One day of better sleep or more physical activity than usual is associated with improved affect and academic performance. These findings have important implications for low-threshold interventions targeting the improvement of daily functioning.

Keywords: sleep quality, physical activity, snacking, affect, academic performance, multilevel structural equation model

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Barham J. Nareeman, Ilham I. Mohammed

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Excavations in urban developed area are generally supported by deep excavation walls such as; diaphragm wall, bored piles, soldier piles and sheet piles. In some cases, these walls may be braced by internal braces or tie back anchors. Tie back anchors are by far the predominant method for wall support, the large working space inside the excavation provided by a tieback anchor system has a significant construction advantage. This paper aims to analyze a deep excavation bracing system of contiguous pile wall braced by pre-stressed tie back anchors, which is a part of a huge residential building project, located in Turkey/Gaziantep province. The contiguous pile wall will be constructed with a length of 270 m that consists of 285 piles, each having a diameter of 80 cm, and a center to center spacing of 95 cm. The deformation analysis was carried out by a finite element analysis tool using PLAXIS. In the analysis, beam element method together with an elastic perfect plastic soil model and Soil Hardening Model was used to design the contiguous pile wall, the tieback anchor system, and the soil. The two soil clusters which are limestone and a filled soil were modelled with both Hardening soil and Mohr Coulomb models. According to the basic design, both soil clusters are modelled as drained condition. The simulation results show that the maximum horizontal movement of the walls and the maximum settlement of the ground are convenient with 300 individual case histories which are ranging between 1.2mm and 2.3mm for walls, and 15mm and 6.5mm for the settlements. It was concluded that tied-back contiguous pile wall can be satisfactorily modelled using Hardening soil model.

Keywords: deep excavation, finite element, pre-stressed tie back anchors, contiguous pile wall, PLAXIS, horizontal deflection, ground settlement

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Authors: A. Aboubakr, E. Fehling, S. A. Mourad, M. Omar

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Wind energy is one of the most effective renewable sources especially offshore wind energy although offshore wind technology is more costly to produce. It is well known that offshore wind energy can potentially be very cheap once infrastructure and researches improve. Laterally, the trend is to construct offshore wind energy to generate the electricity form wind. This leads to intensive research in order to improve the infrastructures. Offshore wind energy is the construction of wind farms in bodies of water to generate electricity from wind. The most important part in offshore wind turbine structure is the foundation and its connection with the wind tower. This is the main difference between onshore and offshore structures. Grouted connection between the foundation and the wind tower is the most important part of the building process when constructing wind offshore turbines. Most attention should be paid to the actual grout connection as this transfers the loads safely from tower to foundations and the soil also. In this paper, finite element analyses have been carried out for studying the behaviour of offshore grouted connection for wind turbine structures. ATENA program have been used for non-linear analysis simulation of the real structural behavior thus demonstrating the crushing, cracking, contact between the two materials and steel yielding. A calibration of the material used in the simulation has been carried out assuring an accurate model of the used material by ATENA program. This calibration was performed by comparing the results from the ATENA program with experimental results to validate the material properties used in ATENA program. Three simple patch test models with different properties have been performed. The research is concluded with a result that the calibration showing a good agreement between the ATENA program material behaviors and the experimental results.

Keywords: grouted connection, 3D modeling, finite element analysis, offshore wind energy turbines, stresses

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Authors: Pontus Backstrom

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In the educational literature on peer effects, attention has been brought to the fact that the mechanisms creating peer effects are still to a large extent hidden in obscurity. The hypothesis in this study is that the Frame Factor Theory can be used to explain these mechanisms. At heart of the theory is the concept of “time needed” for students to learn a certain curricula unit. The relations between class-aggregated time needed and the actual time available, steers and hinders the actions possible for the teacher. Further, the theory predicts that the timing and pacing of the teachers’ instruction is governed by a “criterion steering group” (CSG), namely the pupils in the 10th-25th percentile of the aptitude distribution in class. The class composition hereby set the possibilities and limitations for instruction, creating peer effects on individual outcomes. To test if the theory can be applied to the issue of peer effects, the study employs multilevel structural equation modelling (M-SEM) on Swedish TIMSS 2015-data (Trends in International Mathematics and Science Study; students N=4090, teachers N=200). Using confirmatory factor analysis (CFA) in the SEM-framework in MPLUS, latent variables are specified according to the theory, such as “limitations of instruction” from TIMSS survey items. The results indicate a good model fit to data of the measurement model. Research is still in progress, but preliminary results from initial M-SEM-models verify a strong relation between the mean level of the CSG and the latent variable of limitations on instruction, a variable which in turn have a great impact on individual students’ test results. Further analysis is required, but so far the analysis indicates a confirmation of the predictions derived from the frame factor theory and reveals that one of the important mechanisms creating peer effects in student outcomes is the effect the class composition has upon the teachers’ instruction in class.

Keywords: compositional effects, frame factor theory, peer effects, structural equation modelling

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Safia Hasan Varachhia, Neela Badrie, Marsha Singh

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Genetic modification of food is an innovative technology that offers a host of benefits and advantages to consumers. Consumer attitudes towards GM food and GM technologies can be identified a major determinant in conditioning market force and encouraging policy makers and regulators to recognize the significance of consumer influence on the market. This study aimed to investigate and evaluate the extent of consumer awareness, knowledge, perception and acceptance of GM foods and its associated health risks and benefit in Trinidad and Tobago, West Indies. The specific objectives of this study were to (determine consumer awareness to GM foods, ascertain their perspectives on health and safety risks and ethical issues associated with GM foods and determine whether labeling of GM foods and ingredients will influence consumers’ willingness to purchase GM foods. A survey comprising of a questionnaire consisting of 40 questions, both open-ended and close-ended was administered to 240 shoppers in small, medium and large-scale supermarkets throughout Trinidad between April-May, 2015 using convenience sampling. This survey investigated consumer awareness, knowledge, perception and acceptance of GM foods and its associated health risks/benefits. The data was analyzed using SPSS 19.0 and Minitab 16.0. One-way ANOVA investigated the effects categories of supermarkets and knowledge scores on shoppers’ awareness, knowledge, perception and acceptance of GM foods. Linear Regression tested whether demographic variables (category of supermarket, age of consumer, level of were useful predictors of consumer’s knowledge of GM foods). More than half of respondents (64.3%) were aware of GM foods and GM technologies, 28.3% of consumers indicated the presence of GM foods in local supermarkets and 47.1% claimed to be knowledgeable of GM foods. Furthermore, significant associations (P < 0.05) were observed between demographic variables (age, income, and education), and consumer knowledge of GM foods. Also, significant differences (P < 0.05) were observed between demographic variables (education, gender, and income) and consumer knowledge of GM foods. In addition, age, education, gender and income (P < 0.05) were useful predictors of consumer knowledge of GM foods. There was a contradiction as whilst 35% of consumers considered GM foods safe for consumption, 70% of consumers were wary of the unknown health risks of GM foods. About two-thirds of respondents (67.5%) considered the creation of GM foods morally wrong and unethical. Regarding GM food labeling preferences, 88% of consumers preferred mandatory labeling of GM foods and 67% of consumers specified that any food product containing a trace of GM food ingredients required mandatory GM labeling. Also, despite the declaration of GM food ingredients on food labels and the reassurance of its safety for consumption by food safety and regulatory institutions, the majority of consumers (76.1%) still preferred conventionally produced foods over GM foods. The study revealed the need to inform shoppers of the presence of GM foods and technologies, present the scientific evidence as to the benefits and risks and the need for a policy on labeling so that informed choices could be taken.

Keywords: genetically modified foods, income, labeling consumer awareness, ingredients, morality and ethics, policy

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Authors: Paramvir Singh

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The locomotion of aquatic organisms has long fascinated biologists and engineers alike, with fish fins serving as a prime example of nature's remarkable adaptations for efficient underwater propulsion. This paper presents a comprehensive study focused on the hydrodynamic analysis of fish fin kinematics, employing an innovative approach that combines machine learning and image processing techniques. Through high-speed videography and advanced computational tools, we gain insights into the complex and dynamic motion of the fins of a Tilapia (Oreochromis Niloticus) fish. This study was initially done by experimentally capturing videos of the various motions of a Tilapia in a custom-made setup. Using deep learning and image processing on the videos, the motion of the Caudal and Pectoral fin was extracted. This motion included the fin configuration (i.e., the angle of deviation from the mean position) with respect to time. Numerical investigations for the flapping fins are then performed using a Computational Fluid Dynamics (CFD) solver. 3D models of the fins were created, mimicking the real-life geometry of the fins. Thrust Characteristics of separate fins (i.e., Caudal and Pectoral separately) and when the fins are together were studied. The relationship and the phase between caudal and pectoral fin motion were also discussed. The key objectives include mathematical modeling of the motion of a flapping fin at different naturally occurring frequencies and amplitudes. The interactions between both fins (caudal and pectoral) were also an area of keen interest. This work aims to improve on research that has been done in the past on similar topics. Also, these results can help in the better and more efficient design of the propulsion systems for biomimetic underwater vehicles that are used to study aquatic ecosystems, explore uncharted or challenging underwater regions, do ocean bed modeling, etc.

Keywords: biomimetics, fish fin kinematics, image processing, fish tracking, underwater vehicles

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Authors: Ladda Thiamwong, Renata Komalasari

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Falls are the leading cause of disability and hospitalization in low-income older adults. Fear of falling is present in 20% to 85 % of older adults and has been identified as an independent risk factor of fall risk, activity restriction, and loss of independence. About 12% of American older adults have subjective cognitive decline. Cognitive impairment is also an established factor of fall risk. However, it is unclear whether measures of fear of falling and subjective cognitive decline have the greatest association with fall risk in low-income older adults. The aim of this study was to evaluate the association between fear of falling, subjective cognitive decline-functional performance (SCD-FP), and fall risk using simple screening tools. In this cross-section study, we collected data from community-dwelling older adults 60 years or older in low-income settings in Central Florida, and 86 participants were included in the data analysis. Fear of falling was assessed by the Short Fall Efficacy Scale- International (Short FES-I) with seven items. Subjective cognitive decline-functional performance (SCD-FP) was assessed by a self-reported experience of worsening or more frequent confusion or memory loss in the past 12 months and its functional implications. Fall risk was evaluated by the Centers for Disease Control and Prevention (CDC)'s Stay Independent checklist with 12 items. The majority of participants were female, and more than half of the participants were African American. More than half of the participants had a higher school degree or higher, and less than 20% had no financial problems. Less than 30% of the participants perceived their general health as very good- excellent. More than half of the participants lived alone, and less than 15% lived with a partner or spouse. About 60% of the participants had hypertension, 40% had diabetes, 16% had cancer, and 50% had arthritis. About 30% of the participants had difficulty walking up ten steps without resting, more than 40% felt unsteady when walking, and 30% had been advised to use a cane or walker to get around safely. Regression analysis showed that fall risk was associated with fear of falling ( = .524, p <.001) and subjective cognitive decline-functional performance ( = .465, p =.027). The structure coefficient showed that fear of falling (rs2 = .922) was a stronger predictor of fall risk than subjective cognitive decline-functional performance (rs2= .200). Fear of falling and subjective cognitive decline-functional performance are growing public health issues, and addressing those issues is a public priority. Proactive screening for fear of falling and subjective cognitive decline-functional performance is critical in fall prevention. A combination of all three self-reported tools (Short FES-I, SCD-FP, and CDC's Stay Independent checklist) takes less than 5 minutes to complete. Primary care providers or public health professionals should consider including these tools to screen fear of falling and subjective cognitive decline-functional performance as part of fall risk assessment, especially in low-income settings. Thus, encouraging older adults and healthcare professionals to discuss fear of falling, subjective cognitive decline, and fall risk during routine medical office visits.

Keywords: falls, fall risk, fear of falling, cognition, subjective cognitive decline, low-income, older adults, community, screening, nursing, primary care

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Authors: Rajkumar Ghosh

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Urban flooding is a common occurrence throughout Asia. Almost every city is vulnerable to urban floods in some fashion, and city people are particularly vulnerable. Pluvial and fluvial flooding are the most prominent causes of urban flooding in the Gomti Nagar region of Lucknow, Uttar Pradesh, India. The pluvial flooding is regarded to be less damaging because it is caused by heavy rainfall, Seasonal rainfall fluctuations, water flows off concrete infrastructures, blockages of the drainage system, and insufficient drainage capacity or low infiltration capacity. However, this study considers pluvial flooding in Lucknow to be a significant source of cumulative damage over time, and the risks of such events are increasing as a result of changes in ageing infrastructure, hazard exposure, rapid urbanization, massive water logging and global warming. As a result, urban flooding has emerged as a critical field of study. The popularity of analytical approaches to project the spatial extent of flood dangers has skyrocketed. To address future urban flood resilience, more effort is needed to enhance both hydrodynamic models and analytical tools to simulate risks under present and forecast conditions. Proper urban planning with drainage system and ample space for high infiltration capacity are required to reduce urban flooding. A better India with no urban flooding is a pipe dream that can be realized by putting household rooftop rainwater collection systems in every structure. According to the current study, domestic RTRWHs are strongly recommended as an alternative source of water, as well as to prevent surface runoff and urban floods in this region of Lucknow, urban areas of India.

Keywords: rooftop rainwater harvesting, urban flood, pluvial flooding, fluvial flooding

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Authors: Matthew Armitt

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The revolutionary school of architectural teaching – VKhUTEAMAS (1923-1926) was a new approach for a new society bringing architectural education to the masses and masses to the growing industrial production. The school's pedagogical contribution of the 1920s made it an important school of the modernist movement, engaging pedagogy as a mode of experimentation. The teachers and students saw design education not just as a process of knowledge transfer but as a vehicle for design innovation developing an approach without precedent. This process of teaching and learning served as a vehicle for venturing into the unknown through a discipline of architectural teaching called “Space” developed by the Soviet architect Nikolai Ladovskii (1881-1941). The creation of “Space” was paramount not only for its innovative pedagogy but also as an experimental laboratory for developing new architectural language. This paper discusses whether the historical teaching of “Space” can function in the construction of the modern teaching identity today to promote value, richness, quality, and diversity inherent in architectural design education. The history of “Space” teaching remains unknown within academic circles and separate from the current architectural teaching debate. Using VKhUTEMAS and the teaching of “Space” as a pedagogical lens and drawing upon research carried out in the Russian Federation, America, Canada, Germany, and the UK, this paper discusses how historically different models of teaching and learning can intersect through examining historical based educational research by exploring different design studio initiatives; pedagogical methodologies; teaching and learning theories and problem-based projects. There are strong arguments and desire for pedagogical change and this paper will promote new historical and educational research to widen the current academic debate by exposing new approaches to architectural teaching today.

Keywords: VKhUTEMAS, discipline space, modernist pedagogy, teaching identity

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Authors: F. Sahnoune

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The study focuses on the analysis of the Algerian greenhouse gase emissions. In Algeria, as in other countries, the issue of greenhouse gas (GHG) emissions and climate change is the subject of great concern. As climate change is a global problem and taking into consideration the principle of 'common but differentiated responsibilities' as mentioned in the Rio Declaration in 1992, Algeria has initiated a broad program of voluntary reduction of GHG emissions and climate change adaptation. Thus although the contribution of Algeria on global warming is minimal (less than 0.5% of global GHG emissions), the country is, because its geographical position and climatic characteristics, very vulnerable and should integrate mitigation and adaptation into its development policy. Even a small rise in temperature would lead to various socio-economic problems that hinder the development of the country. The models predict that rainfall events are less frequent but more intense, while droughts are more common and longer. The decrease of water resources, declining agricultural yields, encroaching desert, the challenge of planning and the energy consumption for air conditioning are only the initial impacts to which Algeria must find answers supportable economically and socially. The study examines to what extent, Algeria can significantly reduce greenhouse gas emissions. We present an analysis of the current situation, trends in CO2 emissions, footprint of Algeria, national climate plan and especially what will be the impact on GHG emissions of the new strategy for promoting renewable energy adopted in 2011 and expects to produce 40% of electricity needs from solar energy. The results show that in 2012 the GHG emissions totaled 153 MT CO2 eq and growing at a rate of over 3%. The Introduction of solar energy in electricity production and implementation of energy efficiency allow to reduce by 2030 more than 300 MT CO2 eq. Avenues of consideration relating to a combination of policies and improved technologies that are able to reduce CO2 emissions and mitigate the impacts caused by climate change in the medium term will also be presented.

Keywords: climate change, co2 mitigation, greenhouse gases, renewable energy, sustainable development

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Authors: Joanna Fidelus-Orzechowska, Dominika Wronska-Walach, Jaroslaw Cebulski

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Mountain areas are very often exposed to numerous transformations connected with the development of tourist infrastructure. In mountain areas in Poland ski tourism is very popular, so agricultural areas are often transformed into tourist areas. The construction of new ski runs can change the direction and rate of slope development. The main aim of this research was to determine geomorphological and hydrological changes within slopes caused by ski run constructions. The study was conducted in the Remiaszów catchment in the Inner Polish Carpathians (southern Poland). The mean elevation of the catchment is 859 m a.s.l. and the maximum is 946 m a.s.l. The surface area of the catchment is 1.16 km2, of which 16.8% is the area of the two studied ski runs. The studied ski runs were constructed in 2014 and 2015. In order to determine the relief transformations connected with new ski run construction high resolution LIDAR data was analyzed. The general relief changes in the studied catchment were determined on the basis of ALS (Airborne Laser Scanning ) data obtained before (2013) and after (2016) ski run construction. Based on the two sets of ALS data a digital elevation models of differences (DoDs) was created, which made it possible to determine the quantitative relief changes in the entire studied catchment. Additionally, cross and longitudinal profiles were calculated within slopes where new ski runs were built. Detailed data on relief changes within selected test surfaces was obtained based on TLS (Terrestrial Laser Scanning). Hydrological changes within the analyzed catchment were determined based on the convergence and divergence index. The study shows that the construction of the new ski runs caused significant geomorphological and hydrological changes in the entire studied catchment. However, the most important changes were identified within the ski slopes. After the construction of ski runs the entire catchment area lowered about 0.02 m. Hydrological changes in the studied catchment mainly led to the interruption of surface runoff pathways and changes in runoff direction and geometry.

Keywords: hydrological changes, mountain areas, relief transformations, ski run construction

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Authors: Rui Calejo Rodrigues

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Building Refurbishing and Maintenance is a major area of knowledge ultimately dispensed to user/occupant criteria. The optimization of the service life of a building needs a special background to be assessed as it is one of those concepts that needs proficiency to be implemented. ISO 15686-2 Buildings and constructed assets - Service life planning: Part 2, Service life prediction procedures, states a factorial method based on deterministic data for building components life span. Major consequences result on a deterministic approach because users/occupants are not sensible to understand the end of components life span and so simply act on deterministic periods and so costly and resources consuming solutions do not meet global targets of planet sustainability. The estimation of 2 thousand million conventional buildings in the world, if submitted to a probabilistic method for service life planning rather than a deterministic one provide an immense amount of resources savings. Since 1989 the research team nowadays stating for CEES–Center for Building in Service Studies developed a methodology based on Montecarlo method for probabilistic approach regarding life span of building components, cost and service life care time spans. The research question of this deals with the importance of probabilistic approach of buildings life planning compared with deterministic methods. It is presented the mathematic model developed for buildings probabilistic lifespan approach and experimental data is obtained to be compared with deterministic data. Assuming that buildings lifecycle depends a lot on component replacement this methodology allows to conclude on the global impact of fixed replacements methodologies such as those on result of deterministic models usage. Major conclusions based on conventional buildings estimate are presented and evaluated under a sustainable perspective.

Keywords: building components life cycle, building maintenance, building sustainability, Montecarlo Simulation

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Authors: Tahar Tayachi, Ahlam Alrehaili

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Purpose: The purpose of this paper is to investigate the relationship between the corporate board characteristics and the dividend policy among firms on the Saudi Stock Exchange. Design/Methodology/Approach: This paper uses a sample of 103 nonfinancial firms over a time period of 4 years from 2015 to 2018. To investigate how corporate governance mechanisms such as board independence, the board size, frequency of meetings, and free cash flow impact dividends, the study uses Logit and Tobit models. Findings: This paper finds that board size, board independence, and frequency of board meetings have no influence on a firm’s decision to pay dividends, while board size has a significantly positive impact on the levels of cash dividends paid to investors. This study also finds that the level of free cash flows has a positively significant influence on both the decision to pay dividends and the magnitude of dividend payouts. Research Limitations/Implications: This paper attempts to study the effectiveness of dividend policy among some firms on the Saudi Stock Exchange. Practical Implications: The findings reveal that board characteristics, which represent one of the crucial mechanisms of corporate governance, were found to be complementary to corporate laws and regulations imposed on the Saudi market in 2015. The findings also imply that capital market authorities should revise their corporate regulations and ensure that protection laws are adequate and strong enough to protect the interests of all shareholders. Originality/Value: This paper is among the few studies focusing on dividend policy in Saudi Arabia. Finally, these findings suggest that the improvements in corporate laws in Saudi Arabia led to such an outcome, and it has become prevalent in dividend policy decisions and behaviors of Saudi firms.

Keywords: agency theory, Tobit, corporate governance, dividend payout, Logit

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Authors: Ulugbek Azimov, Nearchos Stylianidis, Nobuyuki Kawahara, Eiji Tomita

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A chemical kinetics and computational fluid-dynamics (CFD) analysis was performed to evaluate the combustion of syngas derived from biomass and coke-oven solid feedstock in a micro-pilot ignited supercharged dual-fuel engine under lean conditions. For this analysis, a new reduced syngas chemical kinetics mechanism was constructed and validated by comparing the ignition delay and laminar flame speed data with those obtained from experiments and other detail chemical kinetics mechanisms available in the literature. The reaction sensitivity analysis was conducted for ignition delay at elevated pressures in order to identify important chemical reactions that govern the combustion process. The chemical kinetics of NOx formation was analyzed for H2/CO/CO2/CH4 syngas mixtures by using counter flow burner and premixed laminar flame speed reactor models. The new mechanism showed a very good agreement with experimental measurements and accurately reproduced the effect of pressure, temperature and equivalence ratio on NOx formation. In order to identify the species important for NOx formation, a sensitivity analysis was conducted for pressures 4 bar, 10 bar and 16 bar and preheat temperature 300 K. The results show that the NOx formation is driven mostly by hydrogen based species while other species, such as N2, CO2 and CH4, have also important effects on combustion. Finally, the new mechanism was used in a multidimensional CFD simulation to predict the combustion of syngas in a micro-pilot-ignited supercharged dual-fuel engine and results were compared with experiments. The mechanism showed the closest prediction of the in-cylinder pressure and the rate of heat release (ROHR).

Keywords: syngas, chemical kinetics mechanism, internal combustion engine, NOx formation

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Authors: Dipendra Kumar Yadav, Nabaraj Paudel, Anjana Yadav

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Background: Low Birth weight (LBW) is defined as the weight at birth less than 2500 grams, irrespective of the period of their gestation. LBW is an important indicator of general health status of population and is considered as the single most important predictors of infant mortality especially of deaths within the first month of life that is birth weight determines the chances of newborn survival. Objective of this study was to identify the maternal risk factors associated with low birth weight neonates. Materials and Methods: A hospital based case-control study was conducted in maternity ward of Manipal Teaching Hospital, Pokhara, Nepal from 23 September 2014 to 12 November 2014. During study period 59 cases were obtained and twice number of control group were selected with frequency matching of the mother`s age with ± 3 years and total controls were 118. Interview schedule was used for data collection along with record review. Data were entered in Epi-data program and analysis was done with help of SPSS software program. Results: From bivariate logistic regression analysis, eighteen variables were found significantly associated with LBW and these were place of residence, family monthly income, education, previous still birth, previous LBW, history of STD, history of vaginal bleeding, anemia, ANC visits, less than four ANC visits, de-worming status, counseling during pregnancy, CVD, physical workload, stress, extra meal during pregnancy, smoking and alcohol consumption status. However after adjusting confounding variables, only six variables were found significantly associated with LBW. Mothers who had family monthly income up to ten thousand rupees were 4.83 times more likely to deliver LBW with CI (1.5-40.645) and p value 0.014 compared to mothers whose family income NRs.20,001-60,000. Mothers who had previous still birth were 2.01 times more likely to deliver LBW with CI (0.69-5.87) and p value 0.02 compared to mothers who did not has previous still birth. Mothers who had previous LBW were 5.472 times more likely to deliver LBW with CI (1.2-24.93) and p value 0.028 compared to mothers who did not has previous LBW. Mothers who had anemia during pregnancy were 3.36 times more likely to deliver LBW with CI (0.77-14.57) and p value 0.014 compared to mothers who did not has anemia. Mothers who delivered female newborn were 2.96 times more likely to have LBW with 95% CI (1.27-7.28) and p value 0.01 compared to mothers who deliver male newborn. Mothers who did not get extra meal during pregnancy were 6.04 times more likely to deliver LBW with CI (1.11-32.7) and p value 0.037 compared to mothers who getting the extra meal during pregnancy. Mothers who consumed alcohol during pregnancy were 4.83 times more likely to deliver LBW with CI (1.57-14.83) and p value 0.006 compared to mothers who did not consumed alcohol during pregnancy. Conclusions: To reduce low birth weight baby through economic empowerment of family and individual women. Prevention and control of anemia during pregnancy is one of the another strategy to control the LBW baby and mothers should take full dose of iron supplements with screening of haemoglobin level. Extra nutritional food should be provided to women during pregnancy. Health promotion program will be focused on avoidance of alcohol and strengthen of health services that leads increasing use of maternity services.

Keywords: low birth weight, case-control, risk factors, hospital based study

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Authors: T. Aragaw, P. Gari

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In spite of social, political, and economic marginalization, women are still considered as the backbone of Ethiopia, one of the least developed countries in the world. The general purpose of this study was to assess factors that affect participation of women in politics, social and economic decisions at Kelem-Wollega Administrative Zone of Oromia Regional State, Ethiopia. Data used in this paper is mainly primary, and a few secondary data were incorporated. Respondents were selected using a systematic random sampling method and were placed questionnaires containing open-ended and closed-ended. Focus group discussion was also used for the study subjects in two offices. According to the information collected from the KWAZ Development and Social Service Office, a total of 18,473 tax-paying employees are present in the Zone, which is 14% of the total population of the Zone. Among the total number of employees in the Zone, 2,617 have been recruited for this study based on the criteria stated. This showed 1.8% of them were comprised of several churches and religious owned integrated development projects in the KWAZ. The 2,103 (80.34%) study participants responded personally, and they completed and returned the questionnaire to the researchers. The study revealed that in public institutions existed in KWAZ, the majority of women were having an educational status of diploma and lower, practicing lower non-decision making and leadership positions. Conclusion: Major barriers hindering women include: Socio-cultural attitudes, lack of necessary experience, education, the burden of domestic responsibilities, and lack of role models of women leaders in the Zone. Empowerment of women via social organizations, critical involvement of the government, and Affirmative action for women is critical. Further research is needed on the scope and challenges in implementing the strategies.

Keywords: women, affirmative action, leadership, empowerment, Ethiopia

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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Authors: Young-Taeg Kim, Gwang Ho Seo, Hyungju Oh, Ho Kyung Ha, Kuk Jin Kim

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Kim et al., hypothesized an increase in volume transport in the Korea Strait based on the concurrent increase in water temperature and mean sea level observed by the Korea Hydrographic and Oceanographic Agency (KHOA) in the vicinity of the Korea Strait from 2000 to 2009. Since then, to our best knowledge, no definitive studies have been reported on the increase in volume transport through the Korea Strait, but the observed water temperature (2000-2021) and sea level (1989-2021) in the Korea Strait and East Sea have been found to be increasing. In particular, the rapid increase rate in the mean sea level rise (2.55~3.53 mm/y) in these areas cannot be explained by only steric effect due to the increased water temperature. It is more reasonable interpretation that the sea level rise is due to an increase in the volume transport of warm and salty currents. If the increase in the volume transport is explained by the geostrophic equation without considering the sea level rise in the Korea Strait, the current velocity should increase. However, up to now, there are no reports of an increase in current velocity from direct observations using ADCP (e.g., observations of Camellia) or from various numerical models. Therefore, the increase in volume transport cannot be explained by the geostrophic equation. Another possible explanation for the increase in the volume transport is the effect of wind. Although Korea is dominated by monsoon, it is affected by winds according to El Niño and La Niña, which have a cycle of about 3 to 4 years. During El Niño (La Niña), northerly winds (southerly winds) prevail in Korea. Consequently, it is inferred that the transported volume in the Korea Strait slowly increases interannually. However, in this study, it was difficult to find a clear correlation between annually-averaged mean sea level and El Niño (or La Niña) during 1989-2021. This is probably due to the interactions of the PDO (Pacific Decadal Oscillation) and AO (Arctic Oscillation) along with the ENSO (El niño-Southern Oscillation). However, it is clear that the interannual variability of winds is affecting the volume transport in the Korean Strait. On the other hand, the effect of global sea level rise on the volume transport in the Korea Strait is small compared to the interannual variability of the volume transport, but it seems to play a constant role.

Keywords: mean sea level, volume transport, El nino, La nina

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