Search results for: MIMO (Multiple Input Multiple Output)

Authors: Ananya Govindarajan

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Tetrahymena thermophila is a single-cell, eukaryotic organism that belongs to the Protozoa Kingdom. Tetrahymena thermophila is often used in signal transduction pathway studies because of its ability to model sensory input and the effects of environmental conditions such as chemicals and temperature. The recently discovered G37 chemorepellent receptor showed increased responsiveness to all chemorepellents. Investigating the mutant G37 Tetrahymena gene in various test solutions, including ferric chloride, ferrous sulfate, hydrogen peroxide, tetrazolium blue, potassium chloride, and dithiothreitol were performed to determine the role of oxidants and reducing agents with the mutant and wild-type cells (CU427) to assess the role of the receptor. Behavioral assays and recordings processed by ImageJ indicated that ferric chloride, hydrogen peroxide, and tetrazolium blue yielded little to no chemorepellent responses from G37 cells (<20% ARs). CU427 cells were over-responsive based on the mean percent of cells (>50% ARs). Reducing agents elicited chemorepellent responses from both G37 and CU427, in addition to potassium chloride. Cell responses were classified as over-responsive (>50% ARs). Dithiothreitol yielded unexpected results as G37 (37.0% ARs) and CU427 (38.1% ARs) had relatively similar responses and were only responsive and not over-responsive to the reducing agent test chemical solution. Ultimately, this indicates that the G37 receptor is more interactive with molecules that are reducing agents or non-oxidant compounds; G37 may be unable to sense and respond to oxidants effectively, further elucidating the pathways of the G37 strain and nature of this receptor. Results also indicate that the CSF most likely contained an oxidant, like ferric chloride. This research can be further applied to neuronal influences and how specific compounds may affect human neurons individually and their excitability as the responses model action potentials and membrane potential.

Keywords: tetrahymena thermophila, signal transduction, chemosensory, oxidant, reducing agent

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Authors: Ali Kadivar, Kaveh Niayesh

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The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

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Authors: Hakim Herbane

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Efforts to achieve sustainability in architecture must prove their effectiveness despite various methods attempted. Biomimicry, which looks to successful natural models to promote sustainability and innovation, faces obstacles in implementing sustainability despite its restorative approach to the relationship between humans and nature. In Nunavik, Inuit communities are exploring a sustainable production system that aligns with their aspirations and meets their demands of human, technological, technical, economic, and ecological factors. Biomimicry holds promise in line with Inuit philosophy, but its failure to implement sustainability requires further investigations to remedy its deficiencies. Our literature review underscores the importance of involving the community in defining sustainability and determining the best methods for its implementation. Additionally, vernacular architecture shows valuable orientations for achieving sustainability. Moreover, reintegrating Inuit communities and their traditional architectural practices, which have successfully balanced their built environment's diverse needs and constraints, could pave the way for a sustainable Inuit-built environment in Nunavik and advance architectural biomimicry principles simultaneously. This research aims at establishing a sustainability monitoring tool for Nordic architectural process by analyzing Inuit vernacular and biomimetic architecture, in addition to the input of stakeholders involved in Inuit architecture production in Nunavik, especially Inuit. The goal is to create a practical tool (an index) to aid in designing sustainable architecture, taking into account environmental, social, and economic perspectives. Furthermore, the study seeks to authenticate strong, sustainable design principles of vernacular and biomimetic architectures. The literature review uncovered challenges and identified new opportunities. The forthcoming discourse will focus on the careful and considerate incorporation of Inuit communities’ perceptions and indigenous building practices into our methodology and the latest findings of our research.

Keywords: sustainability, biomimicry, vernacular architecture, community involvement

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Authors: Zengda Li

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The tectonic evolution of the Beishan orogen, which forms part of the Central Asian Orogenic Belt, remains debated. This study reports the identification of three Triassic granitic plutons representing two distinct stages of magmatism in southern Beishan orogen. Zircon U–Pb dating constrains the early stage as 238–237 Ma and the late stage as 229–227 Ma. The granitoids belong to high-K calc-alkaline and shoshonitic series and exhibit alkalic-calcic and calc-alkalic features, and are weakly peraluminous rocks. Most of these granitoids are highly fractionated I-type and A-type granites. They have relatively high Isr values (0.7049–0.7086) and weak negative εNd(t) values of −1.5 to −2.1, with young Nd model ages of 1.04–0.91 Ga, indicating a crustal contribution. They also show markedly positive zircon εHf(t) values (+3.4 to +11.8) and two-stage Hf model ages of 1.06–0.69 Ga, indicating a mixture of mantle and crustal components. The lithospheric mantle beneath this region incorporating older subducted materials was metasomatized by fluids or melts. Partial melting of the metasomatized lithospheric mantle resulted in underplated magmas, which provided the heat and material input to generate the granitoids. The Middle Triassic granitic plutons show moderate negative Eu anomalies, enrichment of LILEs and depletion in Nb, Ta, and Ti suggesting partial melting of crustal components in response to the underplated mantle-derived magmas, probably linked to lithospheric delamination and asthenospheric upwelling. The Late Triassic granitic plutons show characteristics of post-orogenic granite with strong negative anomalies of Eu, Ba, Nb, Sr, P, and Ti, indicating fractional crystallization and crustal contamination during the emplacement process.

Keywords: Triassic, magmatism, geochronology, petrogenesis, Beishan orogen

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Yoni Elviandri, Vivi Fitriyanti, Agung Surya Wijaya, Suryani Humayyah, Muhammad Alif Azizi

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The massive development of computing power and internet access nowadays is marked by audiovisual games and computers which are known as electronic games, one of the examples is online games. This kind of game can be found everywhere in Indonesia, both in the cities and even the villages. In the present time, online games are becoming a popular games in various layers of the community, one of them does happen to elementary school students. As the online games spread over, the traditional games gradually fade away and even thought as an old-fashioned game. Contrary, traditional games actually have the better and higher educational values such as patience, honesty, integrity and togetherness value which cannot be found in online games which are more to individualist. A brand new set of education tools is necessary to provide a convenience, safe and fun place for children to play around but still contains educational values. One interesting example goes to Cilulaba is an agricultural-based playground. It is a good place for children to play and learn as it was planned to entertain children to play around as well as introducing agriculture to them. One of the games is a 1990’s well-known traditional game which its name is Congklak. Congklak is an agricultural-based traditional game and it also introduces the home garden to the children. Some of the Cilulaba’s aims are to protect the existence of nation’s cultural inheritance through Congklak traditional game, as a tool to introduce the agriculture to the children through the methods of Congklak traditional game and giving explanation related to the advantages of a “healthy home garden” to the children. The expected output from this place is to deliver a good understanding about agriculture to the children and make them begin to love it to make an aesthetic home garden and enhance the optimalisation usage of home garden that will support the availability of various edible plants in productive and health households. The proposed method in this Student Creative Program in Society Service is Participatory Rural Appraisal (PRA) method.

Keywords: Cilubaba, Congklak, traditional game, agricultural-based playground

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Authors: Abeer F. Almarzouki, Christopher A. Brown, Richard J. Brown, Anthony K. P. Jones

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Although relief is commonly assumed to be a direct reflection of pain reduction, it seems to be driven by complex emotional interactions in which pain reduction is only one component. For example, termination of a painful/aversive event may be relieving and rewarding. Accordingly, in this study, whether terminating an aversive negative prediction of pain would be reflected in a greater relief experience was investigated, with a view to separating apart the effects of the manipulation on pain and relief. We use aversive conditioning paradigm to investigate the perception of relief in an aversive (threat) vs. positive context. Participants received positive predictors of a non-painful outcome which were presented within either a congruent positive (non-painful) context or an incongruent threat (painful) context that had been previously conditioned; trials followed by identical laser stimuli on both conditions. Participants were asked to rate the perceived intensity of pain as well as their perception of relief in response to the cue predicting the outcome. Results demonstrated that participants reported more pain in the aversive context compared to the positive context. Conversely, participants reported more relief in the aversive context compares to the neutral context. The rating of relief in the threat context was not correlated with pain reports. The results suggest that relief is not dependant on pain intensity. Consistent with this, relief in the threat context was greater than that in the positive expectancy condition, while the opposite pattern was obtained for the pain ratings. The value of relief in this study is better appreciated in the context of an impending negative threat, which is apparent in the higher pain ratings in the prior negative expectancy compared to the positive expectancy condition. Moreover, the more threatening the context (as manifested by higher unpleasantness/higher state anxiety scores), the more the relief is appreciated. The importance of the study highlights the importance of exploring relief and pain intensity in monitoring separately or evaluating pain-related suffering. The results also illustrate that the perception of painful input may largely be shaped by the context and not necessarily stimulus-related.

Keywords: aversive context, pain, predictions, relief

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Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

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Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to the ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental mesoscale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to those obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, sensitivity analysis, total petroleum hydrocarbons

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Mohammed Alruwaili‬

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Nowadays, renewable energy resources are playing an important role in replacing traditional energy resources such as fossil fuels by integrating solar energy with conventional energy. Concerns about the environment led to an intensive search for a renewable energy source. The Rapid growth of distributed energy resources will have prompted increasing interest in the integrated distributing network in the Kingdom of Saudi Arabia next few years, especially after the adoption of new laws and regulations in this regard. Photovoltaic energy is one of the promising renewable energy sources that has grown rapidly worldwide in the past few years and can be used to produce electrical energy through the photovoltaic process. The main objective of the research is to study the impact of PV in distribution networks based on real data and details. In this research, site survey and computer simulation will be dealt with using the well-known computer program software ETAB to simulate the input of electrical distribution lines with other variable inputs such as the levels of solar radiation and the field study that represent the prevailing conditions and conditions in Diriah, Riyadh region, Saudi Arabia. In addition, the impact of adding distributed generation units (DGs) to the distribution network, including solar photovoltaic (PV), will be studied and assessed for the impact of adding different power capacities. The result has been achieved with less power loss in the loop distribution network from the current condition by more than 69% increase in network power loss. However, the studied network contains 78 buses. It is hoped from this research that the efficiency, performance, quality and reliability by having an enhancement in power loss and voltage profile of the distribution networks in Riyadh City. Simulation results prove that the applied method can illustrate the positive impact of PV in loop distribution generation.

Keywords: renewable energy, smart grid, efficiency, distribution network

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Authors: Vivek Thorat, Suhasini Desai

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The hybrid electric vehicle is widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and low emissions at competitive costs. Retro fitment of hybrid components into a conventional vehicle for achieving better performance is the best solution so far. But retro fitment includes major modifications into a conventional vehicle with a high cost. This paper focuses on the development of a P3x hybrid prototype with rear wheel drive parallel hybrid electric Light Commercial Vehicle (LCV) with minimum and low-cost modifications. This diesel Hybrid LCV is different from another hybrid with regard to the powertrain. The additional powertrain consists of continuous contact helical gear pair followed by chain and sprocket as a coupler for traction motor. Vehicle powertrain which is designed for the intended high-speed application. This work focuses on targeting of design, development, and packaging of this unique parallel diesel-electric vehicle which is based on multimode hybrid advantages. To demonstrate the practical applicability of this transmission with P3x hybrid configuration, one concept prototype vehicle has been build integrating the transmission. The hybrid system makes it easy to retrofit existing vehicle because the changes required into the vehicle chassis are a minimum. The additional system is designed for mainly five modes of operations which are engine only mode, electric-only mode, hybrid power mode, engine charging battery mode and regenerative braking mode. Its driving performance, fuel economy and emissions are measured and results are analyzed over a given drive cycle. Finally, the output results which are achieved by the first vehicle prototype during experimental testing is carried out on a chassis dynamometer using MIDC driving cycle. The results showed that the prototype hybrid vehicle is about 27% faster than the equivalent conventional vehicle. The fuel economy is increased by 20-25% approximately compared to the conventional powertrain.

Keywords: P3x configuration, LCV, hybrid electric vehicle, ROMAX, transmission

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Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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Authors: F. Christie, M. Staber

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Malnutrition is a predictor of poor clinical outcome in the elderly. Up to 60% of hip fracture patients are clinically malnourished on admission. This study assessed the perioperative nutritional state of patients admitted with a proximal femoral fracture and examined if adequate nutritional support was achieved. Methods: Prospective, the observational audit of 30 patients, admitted with a proximal femoral fracture, over a one-month period. We recorded: patient demographics; surgical delay; nutritional state on admission; documentation of Malnutrition Universal Screening Tool (MUST) score; dietician input and daily calorie intake through food charts. The nutritional state was re-assessed weekly and at discharge. The outcome was measured by the length of hospital stay and thirty-day mortality. Results: Mean age 87, M:F 1:2 and all patients were ASA three or four. Five patients (17%) had a prolonged ( >24 hours) fasting period. All patients had a MUST score completed on admission, 27% were underweight and 30% were high risk for malnutrition. Twenty-six patients (87%) were appropriately assessed for dietician referral. Thirteen patients had food charts; on average, hospital meals provided 1500kcal daily. No patient achieved > 75% of the provided calories with 69% of patients achieving 50% or less. Only three patients were started on nutritional supplements. Twenty-three patients (77%) lost weight, averaging 6% weight loss during admission. Mean length of stay (LOS) was 23 days and 30-day mortality 9%. Four patients (13%) gained weight, their mean LOS was 17 days and 30-day mortality 0%. Discussion: Malnutrition in the elderly originates in the community. Following major trauma it’s difficult to reverse nutritional deficits in hospitals. It’s therefore concerning that no high-risk patient achieved their recommended calorie intake. Perioperative optimisation needs to include early nutritional intervention, early anaesthetic review and adjusted anaesthetic techniques to support feeding.

Keywords: trauma, nutrition, neck of femur fracture

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Authors: Sonia Barbouchi, Meriem Samcha

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Scale deposition during water injection into aquifer of oil reservoirs is a serious problem experienced in the oil production industry. One of the primary causes of scale formation and injection well plugging is mixing two waters which are incompatible. Considered individually, the waters may be quite stable at system conditions and present no scale problems. However, once they are mixed, reactions between ions dissolved in the individual waters may form insoluble products. The purpose of this study is to identify the causes of well plugging in a southern Tunisian oilfield, where fresh water has been injected into the producing wells to counteract the salinity of the formation waters and inhibit the deposition of halite. X-ray diffraction (XRD) mineralogical analysis has been carried out on scale samples collected from the blocked well. Two samples collected from both formation water and injected water were analysed using inductively coupled plasma atomic emission spectroscopy, ion chromatography and other standard laboratory techniques. The results of complete waters analysis were the typical input parameters, to determine scaling tendency. Saturation indices values related to CaCO3, CaSO4, BaSO4 and SrSO4 scales were calculated for the water mixtures at different share, under various conditions of temperature, using a computerized scale prediction model. The compatibility study results showed that mixing the two waters tends to increase the probability of barite deposition. XRD analysis confirmed the compatibility study results, since it proved that the analysed deposits consisted predominantly of barite with minor galena. At the studied temperatures conditions, the tendency for barite scale is significantly increasing with the increase of fresh water share in the mixture. The future scale inhibition and removal strategies to be implemented in the concerned oilfield are being derived in a large part from the results of the present study.

Keywords: compatibility study, produced water, scaling, water injection

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Authors: Nicholas Pearce, Eun-jin Kim

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Pathologies of the cardiovascular (CV) system remain a serious and deadly health problem for human society. Computational modelling provides a relatively accessible tool for diagnosis, treatment, and research into CV disorders. However, numerical models of the CV system have largely focused on the function of the ventricles, frequently overlooking the behaviour of the atria. Furthermore, in the study of the pressure-volume relationship of the heart, which is a key diagnosis of cardiac vascular pathologies, previous works often evoke popular yet questionable time-varying elastance (TVE) method that imposes the pressure-volume relationship instead of calculating it consistently. Despite the convenience of the TVE method, there have been various indications of its limitations and the need for checking its validity in different scenarios. A model of the combined left ventricle (LV) and left atrium (LA) is presented, which consistently considers various feedback mechanisms in the heart without having to use the TVE method. Specifically, a synergistic model of the left ventricle is extended and modified to include the function of the LA. The synergy of the original model is preserved by modelling the electro-mechanical and chemical functions of the micro-scale myofiber for the LA and integrating it with the microscale and macro-organ-scale heart dynamics of the left ventricle and CV circulation. The atrioventricular node function is included and forms the conduction pathway for electrical signals between the atria and ventricle. The model reproduces the essential features of LA behaviour, such as the two-phase pressure-volume relationship and the classic figure of eight pressure-volume loops. Using this model, disorders in the internal cardiac electrical signalling are investigated by recreating the mechano-electric feedback (MEF), which is impossible where the time-varying elastance method is used. The effects of AV node block and slow conduction are then investigated in the presence of an atrial arrhythmia. It is found that electrical disorders and arrhythmia in the LA degrade the CV system by reducing the cardiac output, power, and heart rate.

Keywords: cardiovascular system, left atrium, numerical model, MEF

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Authors: Daniel Monsalve, Takafumi Noguchi

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Mycelium-based composites (MBC) are made by growing living mycelium on lignocellulosic fibres to create a porous composite material which can be lightweight, and biodegradable, making them suitable as a sustainable thermal insulation. Thus, they can help to reduce material extraction while improving the energy efficiency of buildings, especially when agricultural by-products are used. However, as MBC are hygroscopic materials, moisture can reduce their thermal insulation efficiency. It is known that surface growth, or “mycelium skin”, can form a natural coating due to the hydrophobic properties in the mycelium cell wall. Therefore, this research aims to biofabricate a homogeneous mycelium skin and measure its influence on the final composite material by testing material properties such as thermal conductivity, vapour permeability and water absorption by partial immersion over 24 hours. In addition, porosity, surface morphology and chemical composition were also analyzed. The white-rot fungi species Pleurotus ostreatus, Ganoderma lucidum, and Trametes versicolor were grown on 10 mm hemp fibres (Cannabis sativa), and three different biofabrication protocols were used during incubation, varying the time and surface treatment, including the addition of pre-colonised sawdust. The results indicate that density can be reduced by colonisation time, which will favourably impact thermal conductivity but will negatively affect vapour and liquid water control. Additionally, different fungi can exhibit different resistance to prolonged water absorption, and due to osmotic sensitivity, mycelium skin may also diminish moisture control. Finally, a collapse in the mycelium network after water immersion was observed through SEM, indicating how the microstructure is affected, which is also dependent on fungi species and the type of skin achieved. These results help to comprehend the differences and limitations of three of the most common species used for MBC fabrication and how precise engineering is needed to effectively control the material output.

Keywords: mycelium, thermal conductivity, vapor permeability, water absorption

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Authors: Man Wai Lei, Charles Mark Zaroff

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Objective: A majority of studies suggest that people with Autism Spectrum Disorder (ASD) have multisensory integration deficits. However, normal and even supranormal multisensory integration abilities have also been reported. Additionally, little of this work has been undertaken utilizing a dimensional conceptualization of ASD; i.e., a broader autism phenotype. Utilizing methodology that controls for common potential confounds, the current study aimed to examine if deficits in multisensory integration are associated with ASD traits in a non-clinical population. The contribution of affective versus non-affective components of sensory hypersensitivity to multisensory integration was also examined. Methods: Participants were 147 undergraduate university students in Macau, a Special Administrative Region of China, of Chinese ethnicity, aged 16 to 21 (Mean age = 19.13; SD = 1.07). Participants completed the Autism-Spectrum Quotient, the Sensory Perception Quotient, and the Adolescent/Adult Sensory Profile, in order to measure ASD traits, non-affective, and affective aspects of sensory/perceptual hypersensitivity, respectively. In order to explore multisensory integration across visual and haptic domains, participants were asked to judge which one of two equally weighted, but different sized cylinders was heavier, as a means of detecting the presence of the size-weight illusion (SWI). Results: ASD trait level was significantly and negatively correlated with susceptibility to the SWI (p < 0.05); this correlation was not associated with either accuracy in weight discrimination or gender. Examining the top decile of the non-normally distributed SWI scores revealed a significant negative association with sensation avoiding, but not other aspects of effective or non-effective sensory hypersensitivity. Conclusion and Implications: Within the normal population, a greater degree of ASD traits is associated with a lower likelihood of multisensory integration; echoing was often found in individuals with a clinical diagnosis of ASD, and providing further evidence for the dimensional nature of this disorder. This tendency appears to be associated with dysphoric emotional reactions to sensory input.

Keywords: Autism Spectrum Disorder, dimensional, multisensory integration, size-weight illusion

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Authors: Emile Niringiyimana, LI Ji Qing, Giovanni Dushimimana, Virginie Umwere

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The development and utilization of renewable energy (RE) can not only effectively reduce carbon dioxide (CO2) emissions, but also became a solution to electricity shortage mitigation in rural areas. Hybrid RE systems are promising ways to provide consistent and continuous power for isolated areas. This work investigated the prospect and cost effectiveness of hybrid system complementarity between a 100kW solar PV system and a small-scale 200kW hydropower station in the South of Rwanda. In order to establish the optimal size of a RE system with adequate sizing of system components, electricity demand, solar radiation, hydrology, climate data are utilized as system input. The average daily solar radiation in Rukarara is 5.6 kWh/m2 and average wind speed is 3.5 m/s. The ideal integrated RE system, according to Homer optimization, consists of 91.21kW PV, 146kW hydropower, 12 x 24V li-ion batteries with a 20kW converter. The method of enhancing such hybrid systems control, sizing and choice of components is to reduce the Net present cost (NPC) of the system, unmet load, the cost of energy and reduction of CO2. The power consumption varies according to dominant source of energy in the system by controlling the energy compensation depending on the generation capacity of each power source. The initial investment of the RE system is $977,689.25, and its operation and maintenance expenses is $142,769.39 over a 25-year period. Although the investment is very high, the targeted profits in future are huge, taking into consideration of high investment in rural electrification structure implementations, tied with an increase of electricity cost and the 5 years payback period. The study outcomes suggest that the standalone hybrid PV-Hydropower system is feasible with zero pollution in Rukara community.

Keywords: HOMER optimization, hybrid power system, renewable energy, NPC and solar pv systems

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Authors: Weihao Wang, Zhulin Zong

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Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

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Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: control, milling, multibody, robotic, simulation

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Jason Clarke, Michaela Porubanova, Angela Mazzoli, Gulsah Kut

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What accounts for our perception that time inexorably passes in one direction, from the past to the future, the so-called arrow of time, given that the laws of physics permit motion in one temporal direction to also happen in the reverse temporal direction? Modern physics says that the reason for time’s unidirectional physical arrow is the relationship between time and entropy, the degree of disorder in the universe, which is evolving from low entropy (high order; thermal disequilibrium) toward high entropy (high disorder; thermal equilibrium), the second law of thermodynamics. Accordingly, our perception of the direction of time, from past to future, is believed to emanate as a result of the natural evolution of entropy from low to high, with low entropy defining our notion of ‘before’ and high entropy defining our notion of ‘after’. Here we explored this proposed relationship between entropy and the perception of time’s arrow. We predicted that if the brain has some mechanism for detecting entropy, whose output feeds into processes involved in constructing our perception of the direction of time, presentation of violations to the expectation that low entropy defines ‘before’ and high entropy defines ‘after’ would alert this mechanism, leading to measurable behavioral effects, namely a disruption in duration perception. To test this hypothesis, participants were shown briefly-presented (1000 ms or 500 ms) computer-generated visual dynamic events: novel 3D shapes that were seen either to evolve from whole figures into parts (low to high entropy condition) or were seen in the reverse direction: parts that coalesced into whole figures (high to low entropy condition). On each trial, participants were instructed to reproduce the duration of their visual experience of the stimulus by pressing and releasing the space bar. To ensure that attention was being deployed to the stimuli, a secondary task was to report the direction of the visual event (forward or reverse motion). Participants completed 60 trials. As predicted, we found that duration reproduction was significantly longer for the high to low entropy condition compared to the low to high entropy condition (p=.03). This preliminary data suggests the presence of a neural mechanism that detects entropy, which is used by other processes to construct our perception of the direction of time or time’s arrow.

Keywords: time perception, entropy, temporal illusions, duration perception

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Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

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Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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Authors: H. M. Zakir Hossain

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Cenozoic mudstone samples, obtained from drilled cored and outcrop in northeastern Bengal Basin of Bangladesh were organic geochemically analyzed to identify vertical variations of organic facies, thermal maturity, hydrocarbon potential and depositional environments. Total organic carbon (TOC) content ranges from 0.11 to 1.56 wt% with an average of 0.43 wt%, indicating a good source rock potential. Total sulphur content is variable with values ranging from ~0.001 to 1.75 wt% with an average of 0.065 wt%. Rock-Eval S1 and S2 yields range from 0.03 to 0.14 mg HC/g rock and 0.01 to 0.66 mg HC/g rock, respectively. The hydrogen index values range from 2.71 to 56.09 mg HC/g TOC. These results revealed that the samples are dominated by type III kerogene. Tmax values of 426 to 453 °C and vitrinite reflectance of 0.51 to 0.66% indicate the organic matter is immature to mature. Saturated hydrocarbon ratios such as pristane, phytane, steranes, and hopanes, indicate mostly terrigenous organic matter with small influence of marine organic matter. Organic matter in the succession was accumulated in three different environmental conditions based on the integration of biomarker proxies. First phase (late Eocene to early Miocene): Deposition occurred entirely in seawater-dominated oxic conditions, with high inputs of land plants organic matter including angiosperms. Second phase (middle to late Miocene): Deposition occurred in freshwater-dominated anoxic conditions, with phytoplanktonic organic matter and a small influence of land plants. Third phase (late Miocene to Pleistocene): Deposition occurred in oxygen-poor freshwater conditions, with abundant input of planktonic organic matter and high influx of angiosperms. The lower part (middle Eocene to early Miocene) of the succession with moderate TOC contents and primarily terrestrial organic matter could have generated some condensates and oils in and around the study area.

Keywords: Bangladesh, geochemistry, hydrocarbon potential, mudstone

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Authors: Samson Abayomi Olasoju, Olufemi Adekunle, Titilope Edun, Johnson Owoseni

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Science offers opportunities for revolutionizing human activities, enriched by input from scientific research and technology. Biotechnology is a major force for development in developing countries such as Nigeria. It is found to contribute to solving human problems like water and food insecurity that impede national development and threaten peace wherever it is applied. This review identified the problems of agricultural biotechnology in Nigeria. On the part of rural farmers, there is a lack of adequate knowledge or awareness of biotechnology despite the fact that they constitute the bulk of Nigerian farmers. On part of the government, the problems include: lack of adequate implementation of government policy on bio-safety and genetically modified products, inadequate funding of education as well as research and development of products related to biotechnology. Other problems include: inadequate infrastructures (including laboratory), poor funding and lack of national strategies needed for development and running of agricultural biotechnology. In spite of all the challenges associated with agricultural biotechnology, its prospects still remain great if Nigeria is to meet with the food needs of the country’s ever increasing population. The introduction of genetically engineered products will lead to the high productivity needed for commercialization and food security. Insect, virus and other related diseases resistant crops and livestock are another viable area of contribution of biotechnology to agricultural production. In conclusion, agricultural biotechnology will not only ensure food security, but, in addition, will ensure that the local farmers utilize appropriate technology needed for large production, leading to the prosperity of the farmers and national economic growth, provided government plays its role of adequate funding and good policy implementation.

Keywords: biosafety, biotechnology, food security, genetic engineering, genetic modification

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Authors: Amizawati Mohd Amir, Ruhanita Maelah, Zaidi Mohd Noor

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As part of the Malaysia Higher Institutions' Strategic Plan in promoting high-quality research and education, the Ministry of Higher Education has introduced various instrument to assess the universities performance. The aims are that university will produce more commercially-oriented research and continue to contribute in producing professional workforce for domestic and foreign needs. Yet the spirit of the success lies in the commitment of university particularly the academic staff to translate the vision into reality. For that reason, the element of fairness and justice in assessing individual academic staff performance is crucial to promote directly linked between university and individual work goals. Focusing on public research universities (RUs) in Malaysia, this study observes at the issue through the practice of university contemporary performance measurement system. Accordingly management control theory has conceptualized that contemporary performance measurement consisting of three dimension namely strategic, comprehensive and dynamic building upon equity theory, the relationships between contemporary performance measurement system and organizational justice and in turn the effect on academic staff work performance are tested based on online survey data administered on 365 academic staff from public RUs, which were analyzed using statistics analysis SPSS and Equation Structure Modeling. The findings validated the presence of strategic, comprehensive and dynamic in the contemporary performance measurement system. The empirical evidence also indicated that contemporary performance measure and procedural justice are significantly associated with work performance but not for distributive justice. Furthermore, procedural justice does mediate the relationship between contemporary performance measurement and academic staff work performance. Evidently, this study provides evidence on the importance of perceptions of justice towards influencing academic staff work performance. This finding may be a fruitful input in the setting up academic staff performance assessment policy.

Keywords: comprehensive, dynamic, distributive justice, contemporary performance measurement system, strategic, procedure justice, work performance

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Authors: Yulna Yulnafatmawita, Syafrimen Yasin, Lusi Maira

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Irrigation source is one of the factors affecting physical properties of rice field. This research was aimed to determine the impact of polluted irrigation wáter on soil physical properties of rice field. The study site was located in Koto Nan IV, Dharmasraya Regency, West Sumatra, Indonesia. The rice field was irrigated with wáter from Momongan river in which people do gold mining. The soil was sampled vertically from the top to 100 cm depth with 20 cm increment of soil profile from 2 year-fallowed rice field, as well as from the top 20 cm of cultivated rice field from the terrace-1 (the highest terrace) to terrace-5 (the lowest terrace) position. Soil samples were analysed in laboratory. For comparison, rice field receiving irrigation wáter from non-polluted source was also sampled at the top 20 cm and anaysed for the physical properties. The result showed that there was a change in soil physical properties of rice field after 9 years of getting irrigation from the river. Based on laboratory analyses, the total suspended solid (TSS) in the tailing reached 10,736 mg/L. The texture of rice field at polluted rice field (PRF) was dominated (>55%) by sand particles at the top 100 cm soil depth, and it tended to linearly decrease (R2=0.65) from the top 20 cm to 100 cm depth. Likewise, the sand particles also linearly decreased (R2=0.83), but clay particles linearly increased (R2=0.74) horizontally as the distance from the wáter input (terrace-1) was fartherst. Compared to nonpolluted rice field (NPRF), percentage of sand was higher, and clay was lower at PRF. This sandy texture of soil in PRF increased soil hydraulic conductivity (up to 19.1 times), soil bulk density (by 38%), and sharply decreased SOM (by 88.5 %), as well as soil total pore (by 22.1%) compared to the NPRF at the top 20 cm soil. The rice field was suggested to be reclaimed before reusing it. Otherwise the soil characteristics requirement, especially soil wáter retention, for rice field could not be fulfilled.

Keywords: gold mine tailing, polluted irrigation, rice field, soil physical properties

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: Mohammed Alharbi, Clare Wood, Vasileios Samaras

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Sustainability leadership is a controversial topic, particularly in the engineering context. The theoretical and practical technical focus of the engineering profession impacts our lives. Technologically, engineers significantly contribute to our modern civilization. Industrial revolutions are among the top engineering accomplishments that have contributed to the flourishing of our life. However, engineers have not always received the credit they deserve; instead, they have been blamed for the advent of various global issues, among them the global warming phenomena that are believed to be a result of the industrial revolutions. Global challenges demand engineers demonstrate more than their technical skills for effective contribution to a sustainable future. As a result, engineering leadership has emerged as a new research field. Sustainable manufacturing is a cornerstone for sustainable development. Investigating the change to more sustainable manufacturing practices is a significant issue for all, and even more in the field of engineering leadership. Engineers dominate the manufacturing industry; however, one of the main criticism of engineers is the lack of leadership skills. The literature on engineering leadership has not highlighted enough the engineers' leadership ability in leading sustainable manufacturing. Since we are at the cusp of a new industrial revolution -Industry 4.0, it is vital to investigate the ability of engineers to lead the industry towards a sustainable future. The primary purpose of this paper is to evaluate engineers' sustainability leadership competencies utilizing The Cambridge University Behavioral Competency Model. However, the practical application of the Cambridge model is limited due to the absence of a reliable measurement tool. Therefore, this study developed a valid and reliable survey instrument tool compatible with the Cambridge model as a secondary objective. More than 300 Saudi engineers from the manufacturing industry responded to an online questionnaire collected through the Qualtrics platform and analyzed using SPSS software. The findings provide a contemporary understanding of engineers' mindset related to sustainability leadership. The output of this research study could be valuable in designing effective engineering leadership programs in academia or industry, particularly for enhancing a sustainable manufacturing environment.

Keywords: engineer, leadership, manufacturing, sustainability

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