Search results for: injury prediction

Authors: R. Rajeswari

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An investigation was carried out to know the SOC stock and its change over time in benchmark soils of different agroclimatic zones of Tamil Nadu. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern. Soil map prepared on 1:50,000 scale from Natural Resources Information System (NRIS) employed under satellite data (IRS-1C/1D-PAN sharpened LISS-III image) was used to estimate SOC stock in different agroclimatic zones of Tamil Nadu. Fifteen benchmark soils were selected in different agroclimatic zones of Tamil Nadu based on their land use and the areal extent to assess SOC level and its change overtime. This revealed that, between eleven years of period (1997 - 2007). SOC buildup was higher in soils under horticulture system, followed by soils under rice cultivation. Among different agroclimatic zones of Tamil Nadu hilly zone have the highest SOC stock, followed by north eastern, southern, western, cauvery delta, north western, and high rainfall zone. Although organic carbon content in the soils of North eastern, southern, western, North western, Cauvery delta were less than high rainfall zone, the SOC stock was high. SOC density was higher in high rainfall and hilly zone than other agroclimatic zones of Tamil Nadu. Among low rainfall regions of Tamil Nadu cauvery delta zone recorded higher SOC density. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern in viz., Periyanaickenpalayam series (western zone), Peelamedu series (southern zone), Vallam series (north eastern zone), Vannappatti series (north western zone) and Padugai series (cauvery delta zone). Padugai series recorded higher TOC, BIO, and HUM, followed by Periyanaickenpalayam series, Peelamedu series, Vallam series, and Vannappatti series. Vannappatti and Padugai series develop high TOC, BIO, and HUM under existing cropping pattern. Periyanaickenpalayam, Peelamedu, and Vallam series develop high TOC, BIO, and HUM under alternate cropping pattern. Among five selected soil series, Periyanaickenpalayam, Peelamedu, and Padugai series recorded 0.75 per cent TOC during 2025 and 2018, 2100 and 2035, 2013 and 2014 under existing and alternate cropping pattern, respectively.

Keywords: agro climatic zones, benchmark soil, land use, soil organic carbon

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Authors: Alexander Chinyere Nwankpa, Nneka Ngozi Nwankpa

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In Nigeria, the Federal government is trying to make sure that everyone has access to enough food that is nutritiously adequate and safe. But in the southwest of Nigeria, notably in Ondo State, the most valuable minerals such as oil and gas, bitumen, kaolin, limestone talc, columbite, tin, gold, coal, and phosphate are abundant. Therefore, some regions of Ondo State are now linked to large quantities of natural radioactivity as a result of the mineral presence. In this work, the baseline radioactivity levels in some of the most important food crops in Ondo State were analyzed, allowing for the prediction of probable radiological health impacts. To this effect, maize (Zea mays), yam (Dioscorea alata) and cassava (Manihot esculenta) tubers were collected from the farmlands in the State because they make up the majority of food's nutritional needs. Ondo State was divided into eight zones in order to provide comprehensive coverage of the research region. At room temperature, the maize (Zea mays), yam (Dioscorea alata), and cassava (Manihot esculenta) samples were dried until they reached a consistent weight. They were pulverized, homogenized, and 250 g packed in a 1-liter Marinelli beaker and kept for 28 days to achieve secular equilibrium. The activity concentrations of Radium-226 (Ra-226), Thorium-232 (Th-232), and Potassium-40 (K-40) were determined in the food samples using Gamma-ray spectrometry. Firstly, the Hyper Pure Germanium detector was calibrated using standard radioactive sources. The gamma counting, which lasted for 36000s for each sample, was carried out in the Centre for Energy Research and Development, Obafemi Awolowo University, Ile-Ife, Nigeria. The mean activity concentration of Ra-226, Th-232 and K-40 for yam were 1.91 ± 0.10 Bq/kg, 2.34 ± 0.21 Bq/kg and 48.84 ± 3.14 Bq/kg, respectively. The content of the radionuclides in maize gave a mean value of 2.83 ± 0.21 Bq/kg for Ra-226, 2.19 ± 0.07 Bq/kg for Th-232 and 41.11 ± 2.16 Bq/kg for K-40. The mean activity concentrations in cassava were 2.52 ± 0.31 Bq/kg for Ra-226, 1.94 ± 0.21 Bq/kg for Th-232 and 45.12 ± 3.31 Bq/kg for K-40. The average committed effective doses in zones 6-8 were 0.55 µSv/y for the consumption of yam, 0.39 µSv/y for maize, and 0.49 µSv/y for cassava. These values are higher than the annual dose guideline of 0.35 µSv/y for the general public. Therefore, the values obtained in this work show that there is radiological contamination of some foodstuffs consumed in some parts of Ondo State. However, we recommend that systematic and appropriate methods also need to be established for the measurement of gamma-emitting radionuclides since these constitute important contributors to the internal exposure of man through ingestion, inhalation, or wound on the body.

Keywords: contamination, environment, radioactivity, radionuclides

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Authors: Carolina S. Monteiro, Eugénia Pinto, Miguel A. Faria, Sara C. Cunha

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Rice (Oryza sativa) production plays a vital role in reducing hunger and poverty and assumes particular importance in low-income and developing countries. Rice is a sensitive plant, and production occurs strictly where suitable temperature and water conditions are found. Climatic changes are likely to affect worldwide, and some models have predicted increased temperatures, variations in atmospheric CO₂ concentrations and modification in precipitation patterns. Therefore, the ongoing climatic changes threaten rice production by increasing biotic and abiotic stress factors, and crops will grow in different environmental conditions in the following years. Around the world, the effects will be regional and can be detrimental or advantageous depending on the region. Mediterranean zones have been identified as possible hot spots, where dramatic temperature changes, modifications of CO₂ levels, and rainfall patterns are predicted. The actual estimated atmospheric CO₂ concentration is around 400 ppm, and it is predicted that it can reach up to 1000–1200 ppm, which can lead to a temperature increase of 2–4 °C. Alongside, rainfall patterns are also expected to change, with more extreme wet/dry episodes taking place. As a result, it could increase the migration of pathogens, and a shift in the occurrence of mycotoxins, concerning their types and concentrations, is expected. Mycotoxigenic spoilage fungi can colonize the crops and be present in all rice food chain supplies, especially Penicillium species, mainly resulting in ochratoxin A (OTA) contamination. In this scenario, the objectives of the present study are evaluating the effect of temperature (20 vs. 25 °C), CO₂ (400 vs. 1000 ppm), and water stress (0.93 vs 0.95 water activity) on growth and OTA production by a Penicillium nordicum strain in vitro on rice-based media and when colonizing layers of raw rice. Results demonstrate the effect of temperature, CO₂ and drought on the OTA production in a rice-based environment, thus contributing to the development of mycotoxins predictive models in climate change scenarios. As a result, improving mycotoxins' surveillance and monitoring systems, whose occurrence can be more frequent due to climatic changes, seems relevant and necessary. The development of prediction models for hazard contaminants presents in foods highly sensitive to climatic changes, such as mycotoxins, in the highly probable new agricultural scenarios is of paramount importance.

Keywords: climate changes, ochratoxin A, penicillium, rice

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Authors: Jithin S. Kumar, Ramesh Kannan Kandasami

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Geomaterials are generally porous in nature due to the presence of discrete particles and interconnected voids. The porosity present in these geomaterials play a critical role in many engineering applications such as CO2 sequestration, well bore strengthening, enhanced oil and hydrocarbon recovery, hydraulic fracturing, and subsurface waste storage. These applications involves solid-fluid interactions, which govern the changes in the porosity which in turn affect the permeability and stiffness of the medium. Injecting fluid into the geomaterials results in permeation which exhibits small or negligible deformation of the soil skeleton followed by cavity expansion/ fingering/ fracturing (different forms of instabilities) due to the large deformation especially when the flow rate is greater than the ability of the medium to permeate the fluid. The complexity of this problem increases as the geomaterial behaves like a solid and fluid under certain conditions. Thus it is important to understand this multiphysics problem where in addition to the permeation, the elastic-plastic deformation of the soil skeleton plays a vital role during fluid injection. The phenomenon of permeation and cavity expansion in porous medium has been studied independently through extensive experimental and analytical/ numerical models. The analytical models generally use Darcy's/ diffusion equations to capture the fluid flow during permeation while elastic-plastic (Mohr-Coulomb and Modified Cam-Clay) models were used to predict the solid deformations. Hitherto, the research generally focused on modelling cavity expansion without considering the effect of injected fluid coming into the medium. Very few studies have considered the effect of injected fluid on the deformation of soil skeleton. However, the porosity changes during the fluid injection and coupled elastic-plastic deformation are not clearly understood. In this study, the phenomenon of permeation and instabilities such as cavity and finger/ fracture formation will be quantified extensively by performing experiments using a novel experimental setup in addition to utilizing image processing techniques. This experimental study will describe the fluid flow and soil deformation characteristics under different boundary conditions. Further, a well refined coupled semi-analytical model will be developed to capture the physics involved in quantifying the deformation behaviour of geomaterial during fluid injection.

Keywords: solid-fluid interaction, permeation, poroelasticity, plasticity, continuum model

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Authors: Shilpi Bora, Abhirup Chatterjee, Debkumar Chakrabarti

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Organizations of all the sectors around the world are increasingly revisiting their workplace strategies with due concern for women working therein. Limited office space and rigid work arrangements contribute to lesser job satisfaction and greater work impoundments for any organization. Flexible workspace strategies are indispensable to accommodate the progressive rise of modular workstations and involvement of women. Today’s generation of employees deserves malleable office environments with employee-friendly job conditions and strategies. The workplace nowadays stands on rapid organizational changes in progressive and flexible work culture. Occupational well-being practices need to keep pace with the rapid changes in office-based work. Working at the office (workspace) with awkward postures or for long periods can cause pain, discomfort, and injury. The world is stirring towards the era of globalization and progress. The 4000 women police personnel constitute less than one per cent of the total police strength of India. Lots of innovative fields are growing fast, and it is important that we should accommodate women in those arenas. The timeworn trends should be set apart to set out for fresh opportunities and possibilities of development and success through more involvement of women in the workplace. The notion of women policing is gaining position throughout the world, and various countries are putting solemn efforts to mainstream women in policing. As the role of women policing in a society is budding, and thus it is also notable that the accessibility of women at general police stations should be considered. Accordingly, the impact of workspace at police station on the employee productivity has been widely deliberated as a crucial contributor to employee satisfaction leading to better functional motivation. Thus the present research aimed to look into the office workstation design of police station with reference to womanhood specific issues to uplift occupational wellbeing of the policewomen. Personal interview and individual responses collected through administering to a subjective assessment questionnaire on thirty women police as well as to have their views on these issues by purposive non-probability sampling of women police personnel of different ranks posted in Guwahati, Assam, India. Scrutiny of the collected data revealed that office design has a substantial impact on the policewomen job satisfaction in the police station. In this study, the workspace was designed in such a way that the set of factors would impact on the individual to ensure increased productivity. Office design such as furniture, noise, temperature, lighting and spatial arrangement were considered. The primary feature which affected the productivity of policewomen was the furniture used in the workspace, which was found to disturb the everyday and overall productivity of policewomen. Therefore, it was recommended to have proper and adequate ergonomics design intervention to improve the office design for better performance. This type of study is today’s need-of-the-hour to empower women and facilitate their inner talent to come up in service of the nation. The office workspace design also finds critical importance at several other occupations also – where office workstation needs further improvement.

Keywords: office workspace design, policewomen, womanhood concerns at workspace, occupational wellbeing

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Authors: Mubarack Ahmed, Gabriele Gradoni, Stephen C. Creagh, Gregor Tanner

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High-frequency cables commonly connect modern devices and sensors. Interestingly, the proportion of electric components is rising fast in an attempt to achieve lighter and greener devices. Modelling the propagation of signals through these cable networks in the presence of parameter uncertainty is a daunting task. In this work, we study the response of high-frequency cable networks using both Transmission Line and Quantum Graph (QG) theories. We have successfully compared the two theories in terms of reflection spectra using measurements on real, lossy cables. We have derived a generalisation of the vertex scattering matrix to include non-uniform networks – networks of cables with different characteristic impedances and propagation constants. The QG model implicitly takes into account the pseudo-chaotic behavior, at the vertices, of the propagating electric signal. We have successfully compared the asymptotic growth of eigenvalues of the Laplacian with the predictions of Weyl law. We investigate the nearest-neighbour level-spacing distribution of the resonances and compare our results with the predictions of Random Matrix Theory (RMT). To achieve this, we will compare our graphs with the generalisation of Wigner distribution for open systems. The problem of scattering from networks of cables can also provide an analogue model for wireless communication in highly reverberant environments. In this context, we provide a preliminary analysis of the statistics of communication capacity for communication across cable networks, whose eventual aim is to enable detailed laboratory testing of information transfer rates using software defined radio. We specialise this analysis in particular for the case of MIMO (Multiple-Input Multiple-Output) protocols. We have successfully validated our QG model with both TL model and laboratory measurements. The growth of Eigenvalues compares well with Weyl’s law and the level-spacing distribution agrees so well RMT predictions. The results we achieved in the MIMO application compares favourably with the prediction of a parallel on-going research (sponsored by NEMF21.)

Keywords: eigenvalues, multiple-input multiple-output, quantum graph, random matrix theory, transmission line

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Authors: Agnieszka A. Malinowska, R. Hejmanowski

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A number of European cities are strongly affected by ground movements caused by anthropogenic activities or post-anthropogenic metamorphosis. Those are mainly water pumping, current mining operation, the collapse of post-mining underground voids or mining-induced earthquakes. These activities lead to large and small-scale ground displacements and a ground ruptures. The ground movements occurring in urban areas could considerably affect stability and safety of structures and infrastructures. The complexity of the ground deformation phenomenon in relation to the structures and infrastructures vulnerability leads to considerable constraints in assessing the threat of those objects. However, the increase of access to the free software and satellite data could pave the way for developing new methods and strategies for environmental risk mitigation and management. Open source geographical information systems (OS GIS), may support data integration, management, and risk analysis. Lately, developed methods based on fuzzy logic and experts methods for buildings and infrastructure damage risk assessment could be integrated into OS GIS. Those methods were verified base on back analysis proving their accuracy. Moreover, those methods could be supported by ground displacement observation. Based on freely available data from European Space Agency and free software, ground deformation could be estimated. The main innovation presented in the paper is the application of open source software (OS GIS) for integration developed models and assessment of the threat of urban areas. Those approaches will be reinforced by analysis of ground movement based on free satellite data. Those data would support the verification of ground movement prediction models. Moreover, satellite data will enable our mapping of ground deformation in urbanized areas. Developed models and methods have been implemented in one of the urban areas hazarded by underground mining activity. Vulnerability maps supported by satellite ground movement observation would mitigate the hazards of land displacements in urban areas close to mines.

Keywords: fuzzy logic, open source geographic information science (OS GIS), risk assessment on urbanized areas, satellite interferometry (InSAR)

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Authors: Ivana Čavlina Tomašević, Višnjica Vučetić, Maja Telišman Prtenjak, Barbara Malečić

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The Split wildfire on the mid-Adriatic Coast in July 2017 is one of the most severe wildfires in Croatian history, given the size and unexpected fire behavior, and it is used in this research as a case study to run the Weather Research and Forecasting Spread Fire (WRF SFIRE) model. This coupled fire-atmosphere model was successfully run for the first time ever for one Croatian wildfire case. Verification of coupled simulations was possible by using the detailed reconstruction of the Split wildfire. Specifically, precise information on ignition time and location, together with mapped fire progressions and spotting within the first 30 hours of the wildfire, was used for both – to initialize simulations and to evaluate the model’s ability to simulate fire’s propagation and final fire scar. The preliminary simulations were obtained using high-resolution vegetation and topography data for the fire area, additionally interpolated to fire grid spacing at 33.3 m. The results demonstrated that the WRF SFIRE model has the ability to work with real data from Croatia and produce adequate results for forecasting fire spread. As the model in its setup has the ability to include and exclude the energy fluxes between the fire and the atmosphere, this was used to investigate possible fire-atmosphere interactions during the Split wildfire. Finally, successfully coupled simulations provided the first numerical evidence that a wildfire from the Adriatic coast region can modify the dynamical structure of the surrounding atmosphere, which agrees with observations from fire grounds. This study has demonstrated that the WRF SFIRE model has the potential for operational application in Croatia with more accurate fire predictions in the future, which could be accomplished by inserting the higher-resolution input data into the model without interpolation. Possible uses for fire management in Croatia include prediction of fire spread and intensity that may vary under changing weather conditions, available fuels and topography, planning effective and safe deployment of ground and aerial firefighting forces, preventing wildland-urban interface fires, effective planning of evacuation routes etc. In addition, the WRF SFIRE model results from this research demonstrated that the model is important for fire weather research and education purposes in order to better understand this hazardous phenomenon that occurs in Croatia.

Keywords: meteorology, agrometeorology, fire weather, wildfires, couple fire-atmosphere model

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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Authors: Christina Largent, Tazley Hobbs

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Objective: A literature review was performed to examine the existing research on COVID-19 lockdown as it relates to ADHD child/adolescent individuals, media use, and impact on educational performance/learning. It was surmised that with the COVID-19 shut-down and transition to remote learning, a less structured learning environment, increased screen time, in addition to potential difficulty accessing school resources would impair ADHD individuals’ performance and learning. A resulting increase in the number of youths diagnosed and treated for ADHD would be expected. As of yet, there has been little to no published data on the incidence of ADHD as it relates to COVID-19 outside of reports from several nonprofit agencies such as CHADD (Children and Adults with Attention-Deficit/Hyperactivity Disorder ), who reported an increased number of calls to their helpline, The New York based Child Mind Institute, who reported an increased number of appointments to discuss medications, and research released from Athenahealth showing an increase in the number of patients receiving new diagnosis of ADHD and new prescriptions for ADHD medications. Methods: A literature search for articles published between 2020 and 2021 from Pubmed, Google Scholar, PsychInfo, was performed. Search phrases and keywords included “covid, adhd, child, impact, remote learning, media, screen”. Results: Studies primarily utilized parental reports, with very few from the perspective of the ADHD individuals themselves. Most findings thus far show that with the COVID-19 quarantine and transition to online learning, ADHD individuals’ experienced decreased ability to keep focused or adhere to the daily routine, as well as increased inattention-related problems, such as careless mistakes or lack of completion in homework, which in turn translated into overall more difficulty with remote learning. To add further injury, one study showed (just on evaluation of two different sites within the US) that school based services for these individuals decreased with the shift to online-learning. Increased screen time, television, social media, and gaming were noted amongst ADHD individuals. One study further differentiated the degree of digital media, identifying individuals with “problematic “ or “non-problematic” use. ADHD children with problematic digital media use suffered from more severe core symptoms of ADHD, negative emotions, executive function deficits, damage to family environment, pressure from life events, and a lower motivation to learn. Conclusions and Future Considerations: Studies found not only was online learning difficult for ADHD individuals but it, in addition to greater use of digital media, was associated with worsening ADHD symptoms impairing schoolwork, in addition to secondary findings of worsening mood and behavior. Currently, data on the number of new ADHD cases, in addition to data on the prescription and usage of stimulants during COVID-19, has not been well documented or studied; this would be well-warranted out of concern for over diagnosing or over-prescribing our youth. It would also be well-worth studying how reversible or long-lasting these negative impacts may be.

Keywords: COVID-19, remote learning, media use, ADHD, child, adolescent

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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Authors: Sandeep Kumar Agrawal, Aditi Bhattacharya, Janvie Manhas, Krushna Bhatt, Yatin Kholakiya, Nupur Khera, Ajoy Roychoudhury, Sudip Sen

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Autologous cultured explants of human oral mucosal epithelial cells (OMEC) are a potential therapeutic modality for limbal stem cell deficiency (LSCD). Injury or inflammation of the ocular surface in the form of burns, chemicals, Stevens Johnson syndrome, ocular cicatricial pemphigoid etc. can lead to destruction and deficiency of limbal stem cells. LSCD manifests in the form of severe ocular surface diseases (OSD) characterized by persistent and recurrent epithelial defects, conjuntivalisation and neovascularisation of the corneal surface, scarring and ultimately opacity and blindness. Most of the cases of OSD are associated with severe dry eye pertaining to diminished mucin and aqueous secretion. Mycophenolate mofetil (MMF) has been shown to upregulate the mucin expression in conjunctival goblet cells in vitro. The aim of this study was to evaluate the effects of MMF on mucin expression in primary cultures of oral mucosal epithelial cells. With institutional ethics committee approval and written informed consent, thirty oral mucosal epithelial tissue samples were obtained from patients undergoing oral surgery for non-malignant conditions. OMEC were grown on human amniotic membrane (HAM, obtained from expecting mothers undergoing elective caesarean section) scaffold for 2 weeks in growth media containing DMEM & Ham’s F12 (1:1) with 10% FBS and growth factors. In vitro dosage of MMF was standardised by MTT assay. Analysis of stem cell markers was done using RT-PCR while mucin mRNA expression was quantified using RT-PCR and q-PCR before and after treating cultured OMEC with graded concentrations of MMF for 24 hours. Protein expression was validated using immunocytochemistry. Morphological studies revealed a confluent sheet of proliferating, stratified oral mucosal epithelial cells growing over the surface of HAM scaffold. The presence of progenitor stem cell markers (p63, p75, β1-Integrin and ABCG2) and cell surface associated mucins (MUC1, MUC15 and MUC16) were elucidated by RT-PCR. The mucin mRNA expression was found to be upregulated in MMF treated primary cultures of OMEC, compared to untreated controls as quantified by q-PCR with β-actin as internal reference gene. Increased MUC1 protein expression was validated by immunocytochemistry on representative samples. Our findings conclude that OMEC have the ability to form a multi-layered confluent sheet on the surface of HAM similar to a cornea, which is important for the reconstruction of the damaged ocular surface. Cultured OMEC has stem cell properties as demonstrated by stem cell markers. MMF can be a novel enhancer of mucin production in OMEC. It has the potential to improve dry eye in patients undergoing OMEC transplantation for bilateral OSD. Further clinical trials are required to establish the role of MMF in patients undergoing OMEC transplantation.

Keywords: limbal stem cell deficiency, mycophenolate mofetil, mucin, ocular surface disease

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Authors: Kouassi Louis Kra

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The nearshore deep-water gravity flow deposits in the Northern steep slope of Dongying depression, Bohai Bay basin, have been acknowledged as important reservoirs in the rift lacustrine basin. These deep strata term as coarse clastic sediment, deposit at the root of the slope have complex depositional processes and involve wide diagenetic events which made high-quality reservoir prediction to be complex. Based on the integrated study of seismic interpretation, sedimentary analysis, petrography, cores samples, wireline logging data, 3D seismic and lithological data, the reservoir formation mechanism deciphered. The Geoframe software was used to analyze 3-D seismic data to interpret the stratigraphy and build a sequence stratigraphic framework. Thin section identification, point counts were performed to assess the reservoir characteristics. The software PetroMod 1D of Schlumberger was utilized for the simulation of burial history. CL and SEM analysis were performed to reveal diagenesis sequences. Backscattered electron (BSE) images were recorded for definition of the textural relationships between diagenetic phases. The result showed that the nearshore steep slope deposits mainly consist of conglomerate, gravel sandstone, pebbly sandstone and fine sandstone interbedded with mudstone. The reservoir is characterized by low-porosity and ultra-low permeability. The diagenesis reactions include compaction, precipitation of calcite, dolomite, kaolinite, quartz cement and dissolution of feldspars and rock fragment. The main types of reservoir space are primary intergranular pores, residual intergranular pores, intergranular dissolved pores, intergranular dissolved pores, and fractures. There are three obvious anomalous high-porosity zones in the reservoir. Overpressure and early hydrocarbon filling are the main reason for abnormal secondary pores development. Sedimentary facies control the formation of high-quality reservoir, oil and gas filling preserves secondary pores from late carbonate cementation.

Keywords: Bohai Bay, Dongying Sag, deep strata, formation mechanism, high-quality reservoir

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Authors: Tatsiana Ihnatovich, Darya Nizheharodava, Mikalai Halabarodzka, Tatsiana Savitskaya, Marina Zafranskaya

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Liver fibrosis is a complex of histological changes resulting from chronic liver disease accompanied by an excessive production and deposition of extracellular matrix components in the hepatic parenchyma. Liver fibrosis is a serious medical and social problem. Hepatic stellate cells (HSCs) make a significant contribution to the extracellular matrix deposition due to liver injury. Mesenchymal stem cells (MSCs) have a pronounced anti-inflammatory, regenerative and immunomodulatory effect; they are able to differentiate into hepatocytes and induce apoptosis of activated HSCs that opens the prospect of their use for preventing the excessive fibro-formation and the development of liver cirrhosis. The aim of the study is to evaluate the effect of MSCs therapy on the expression of fibrogenesis markers genes in liver tissue and HSCs cultures of rats with experimental liver cirrhosis (ELC). Materials and methods: ELC was induced by the common bile duct ligation (CBDL) in female Wistar rats (n = 19) with an average body weight of 250 (220 ÷ 270) g. Animals from the control group (n = 10) were sham-operated. On the 56th day after the CBDL, the rats of the experimental (n = 12) and the control (n = 5) groups received intraportal MSCs in concentration of 1×106 cells/animal (previously obtained from rat’s bone marrow) or saline, respectively. The animals were taken out of the experiment on the 21st day. HSCs were isolated by sequential liver perfusion in situ with following disaggregation, enzymatic treatment and centrifugation of cell suspension on a two-stage density gradient. The expression of collagen type I (Col1a1) and type III (Col3a1), matrix metalloproteinase type 2 (MMP2) and type 9 (MMP9), tissue inhibitor of matrix metalloproteinases type 1 (TIMP1), transforming growth factor β type 1 (TGFβ1) and type 3 (TGFβ3) was determined by real-time polymerase chain reaction. Statistical analysis was performed using Statistica 10.0. Results: In ELC rats compared to sham-operated animals, a significant increase of all studied markers expression was observed. The administration of MSCs led to a significant decrease of all detectable markers in the experimental group compared to rats without cell therapy. In ELC rats, an increased MMP9/TIMP1 ratio after cell therapy was also detected. The infusion of MSCs in the sham-operated animals did not lead to any changes. In the HSCs from ELC animals, the expression of Col1a1 and Col3a1 exceeded the similar parameters of the control group (p <0.05) and statistically decreased after the MSCs administration. The correlation between Col3a1 (Rs = 0.51, p <0.05), TGFβ1 (Rs = 0.6, p <0.01), and TGFβ3 (Rs = 0.75, p <0.001) expression in HSCs cultures and liver tissue has been found. Conclusion: Intraportal administration of MSCs to rats with ELC leads to a decreased Col1a1 and Col3a1, MMP2 and MMP9, TIMP1, TGFβ1 and TGFβ3 expression. The correlation between the expression of Col3a1, TGFβ1 and TGFβ3 in liver tissue and in HSCs cultures indicates the involvement of activated HSCs in the fibrogenesis that allows considering HSCs to be the main cell therapy target in ELC.

Keywords: cell therapy, experimental liver cirrhosis, hepatic stellate cells, mesenchymal stem cells

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Authors: Bhupendra Kumar Poudel, Sadhana Amatya, Tirtha Maiya Shrestha, Bharatmani Pokhrel, Mohan Prasad Amatya

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Background: H. salicifolia is a dense, branched, multipurpose, deciduous, nitrogen fixing, thorny willow-like small to moderate tree, restricted to the Himalaya. Among the two species of Nepal (Hippophae salicifolia and H. tibetana), it has been traditionally used as food additive, anticancer (bark), and treating toothache, tooth inflammation (anti-inflammatory) and radiation injury; while people of Western Nepal have largely undermined its veiled treasure by using it for fuel, wood and soil stabilization only. Therefore, the main objective of this study was to explore biological properties (analgesic, antidiabetic, cytotoxic and anti-inflammatory properties of this plant. Methodology: The transverse section of leaves and stems were viewed under microscope. Extracts obtained from soxhlation subjected to tests for phytochemical and biological studies. Rats (used to study antidiabetic and anti-inflammatory properties) and mice (used to study analgesic, CNS depressant, muscle relaxant and locomotor properties) were assumed to be normally distributed; then ANOVA and post hoc tukey test was used to find significance. The data obtained were analyzed by SPSS 17 and Excel 2007. Results and Conclusion: Pharmacognostical analysis revealed the presence of long stellate trichomes, double layered vascular bundle 5-6 in number and double layered compact sclerenchyma. The preliminary phytochemical screening of the extracts was found to exhibit the positive reaction tests for glycoside, steroid, tannin, flavonoid, saponin, coumarin and reducing sugar. The brine shrimp lethality bioassay tested in 1000, 100 and 10 ppm revealed cytotoxic activity inherent in methanol, water, chloroform and ethyl acetate extracts with LC50 (μg/ml) values of 61.42, 99.77, 292.72 and 277.84 respectively. The cytotoxic activity may be due to presence of tannins in the constituents. Antimicrobial screening of the extracts by cup diffusion method using Staphylococcus aereus, Escherichia coli and Pseudomonas aeruginosa against standard antibiotics (oxacillin, gentamycin and amikacin respectively) portrayed no activity against the microorganisms tested. The methanol extract of the stems and leaves showed various pharmacological properties: and antidiabetic, anti-inflammatory, analgesic [chemical writhing method], CNS depressant, muscle relaxant and locomotor activities in a dose-dependent fashion, indicating the possibility of the presence of different constituents in the stems and leaves responsible for these biological activities. All the effects when analyzed by post hoc tukey test were found to be significant at 95% confidence level. The antidiabetic activity was presumed to be due to flavonoids present in extract. Therefore, it can be concluded that this plant’s secondary metabolites possessed strong antidiabetic, anti-inflammatory and cytotoxic activity which could be isolated for further investigation.

Keywords: Hippophae salicifolia, constituents, antidiabetic, inflammatory, brine shrimp

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Authors: Sontana Mimapan, Phattarawadee Wattanasuntorn, Phanom Saijit

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

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

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Authors: Abdullah Almilaibary, Jeremy Jolley, Mark Hayter

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Background: Despite recent progress in enhancing the accessibility of HIV-related health services worldwide, opportunities to diagnose patients are often missed due to genuine barriers at different levels. The aim of the study is to explore the factors that affect the utilization of HIV testing services by young people aged 17-25 in Saudi Arabia. Methods: A non-experimental descriptive cross-sectional design was used to predict factors that influenced HIV testing among Umm- Al Qura University students aged 17-25 years. A newly developed self-completed online questionnaire was used and the study sample was drawn using a convenience sampling technique. The questionnaire consisted of 52 items divided into three scales: 12 items for HIV/AIDS-related knowledge, 3 items for risk perception, and 37 items for attitudes toward HIV testing. Five experts in the field of HIV/AIDS validated the contents of the questionnaire and agreed that the items included were related to the construct being measured. The reliability of the questionnaire was also assessed using a test/re-test strategy with 27 participants recruited from the population under study. The reliability assessment revealed that the questionnaire was consistent as Cronbach’s Alpha was 0.80 for HIV/ADS knowledge, 0.88 for risk perception and 0.78 for attitudes towards HIV testing. The data were collected between 14th of July and 14th of October 2014. Results: 394 participants completed the questionnaires: 116 (29.4%) male and 278 (70%) female. 50.5% of the participants were aged 20 to 22 years, 34.8% were 17-19 years and 14.7% were aged between 23-25 years; about 93% of the participants were single. Only 20 (6%) participants had previously been tested for HIV. The main reasons for not being tested for HIV were: exposure to HIV was considered unlikely (48%), HIV test was not offered (36%) and unawareness of HIV testing centres (16%). On HIV/AIDS-related knowledge, the male participants scored higher than the females as the mean score for males was (M = 6.4, SD = 2.4) while for females it was (M 5.7, SD 2.5). In terms of risk perception, female participants appeared to have lower levels of risk perception than male participants, with the mean score for males being (M 11.7, SD 2.5) and (M 10.5, SD 2.4) for females. The female participants showed slightly more positive attitudes towards HIV testing than male participants: the mean score for males was (M = 108.14, SD = 17.9) and was (M = 111.32, SD = 17.3) for females. Conclusions: The data reveal that misconceptions about HIV/AIDS in Saudi Arabia are still a challenge. Although the attitudes towards HIV testing were reasonably positive, the utilization of the HIV test was low. Thus, tailoring HIV/AIDS preventive strategies in Saudi Arabia should focus on the needs of young people and other high risk groups in the country.

Keywords: attitude toward hiv testing, hiv testing, hiv/aids related knowledge, risk perception

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Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

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The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: K. Rawojć, J. Miszczyk, A. Możdżeń, A. Panek, J. Swakoń, M. Rydygier

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Due to the mitotic delay, poor mitotic index and disappearance of lymphocytes from peripheral blood circulation, assessing the DNA damage after high dose exposure is less effective. Conventional chromosome aberration analysis or cytokinesis-blocked micronucleus assay do not provide an accurate dose estimation or radiosensitivity prediction in doses higher than 6.0 Gy. For this reason, there is a need to establish reliable methods allowing analysis of biological effects after exposure in high dose range i.e., during particle radiotherapy. Lately, Premature Chromosome Condensation (PCC) has become an important method in high dose biodosimetry and a promising treatment modality to cancer patients. The aim of the study was to evaluate the usefulness of drug-induced PCC scoring procedure in an experimental mode, where 100 G2/M cells were analyzed in different dose ranges. To test the consistency of obtained results, scoring was performed by 3 independent persons in the same mode and following identical scoring criteria. Whole-body exposure was simulated in an in vitro experiment by irradiating whole blood collected from healthy donors with 60 MeV protons and 250 keV X-rays, in the range of 4.0 – 20.0 Gy. Drug-induced PCC assay was performed on human peripheral blood lymphocytes (HPBL) isolated after in vitro exposure. Cells were cultured for 48 hours with PHA. Then to achieve premature condensation, calyculin A was added. After Giemsa staining, chromosome spreads were photographed and manually analyzed by scorers. The dose-effect curves were derived by counting the excess chromosome fragments. The results indicated adequate dose estimates for the whole-body exposure scenario in the high dose range for both studied types of radiation. Moreover, compared results revealed no significant differences between scores, which has an important meaning in reducing the analysis time. These investigations were conducted as a part of an extended examination of 60 MeV protons from AIC-144 isochronous cyclotron, at the Institute of Nuclear Physics in Kraków, Poland (IFJ PAN) by cytogenetic and molecular methods and were partially supported by grant DEC-2013/09/D/NZ7/00324 from the National Science Centre, Poland.

Keywords: cell response to radiation exposure, drug induced premature chromosome condensation, premature chromosome condensation procedure, proton therapy

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Authors: Victor Lopez-Richard, Rafael Schio Wengenroth Silva, Fabian Hartmann

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Memcomputing is a computational paradigm that combines information processing and storage on the same physical platform. Key elements for this topic are devices with an inherent memory, such as memristors, memcapacitors, and meminductors. Despite the widespread emergence of memory effects in various solid systems, a clear understanding of the basic microscopic mechanisms that trigger them is still a puzzling task. We report basic ingredients of the theory of solid-state transport, intrinsic to a wide range of mechanisms, as sufficient conditions for a memristive response that points to the natural emergence of memory. This emergence should be discernible under an adequate set of driving inputs, as highlighted by our theoretical prediction and general common trends can be thus listed that become a rule and not the exception, with contrasting signatures according to symmetry constraints, either built-in or induced by external factors at the microscopic level. Explicit analytical figures of merit for the memory modulation of the conductance are presented, unveiling very concise and accessible correlations between general intrinsic microscopic parameters such as relaxation times, activation energies, and efficiencies (encountered throughout various fields in Physics) with external drives: voltage pulses, temperature, illumination, etc. These building blocks of memory can be extended to a vast universe of materials and devices, with combinations of parallel and independent transport channels, providing an efficient and unified physical explanation for a wide class of resistive memory devices that have emerged in recent years. Its simplicity and practicality have also allowed a direct correlation with reported experimental observations with the potential of pointing out the optimal driving configurations. The main methodological tools used to combine three quantum transport approaches, Drude-like model, Landauer-Buttiker formalism, and field-effect transistor emulators, with the microscopic characterization of nonequilibrium dynamics. Both qualitative and quantitative agreements with available experimental responses are provided for validating the main hypothesis. This analysis also shades light on the basic universality of complex natural impedances of systems out of equilibrium and might help pave the way for new trends in the area of memory formation as well as in its technological applications.

Keywords: memories, memdevices, memristors, nonequilibrium states

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Authors: Tomilola J. Ajayi

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A category of nanovalves system containing the α-cyclodextrin (α-CD) ring on a stalk tethered to the pores of mesoporous silica nanoparticles (MSN) is theoretically and computationally modelled. This functions to control opening and blocking of the MSN pores for efficient targeted drug release system. Modeling of the nanovalves is based on the interaction between α-CD and the stalk (p-anisidine) in relation to pH variation. Conformational analysis was carried out prior to the formation of the inclusion complex, to find the global minimum of both neutral and protonated stalk. B3LYP/6-311G**(d, p) basis set was employed to attain all theoretically possible conformers of the stalk. Six conformers were taken into considerations, and the dihedral angle (θ) around the reference atom (N17) of the p-anisidine stalk was scanned from 0° to 360° at 5° intervals. The most stable conformer was obtained at a dihedral angle of 85.3° and was fully optimized at B3LYP/6-311G**(d, p) level of theory. The most stable conformer obtained from conformational analysis was used as the starting structure to create the inclusion complexes. 9 complexes were formed by moving the neutral guest into the α-CD cavity along the Z-axis in 1 Å stepwise while keeping the distance between dummy atom and OMe oxygen atom on the stalk restricted. The dummy atom and the carbon atoms on α-CD structure were equally restricted for orientation A (see Scheme 1). The generated structures at each step were optimized with B3LYP/6-311G**(d, p) methods to determine their energy minima. Protonation of the nitrogen atom on the stalk occurs at acidic pH, leading to unsatisfactory host-guest interaction in the nanogate; hence there is dethreading. High required interaction energy and conformational change are theoretically established to drive the release of α-CD at a certain pH. The release was found to occur between pH 5-7 which agreed with reported experimental results. In this study, we applied the theoretical model for the prediction of the experimentally observed pH-responsive nanovalves which enables blocking, and opening of mesoporous silica nanoparticles pores for targeted drug release system. Our results show that two major factors are responsible for the cargo release at acidic pH. The higher interaction energy needed for the complex/nanovalve formation to exist after protonation as well as conformational change upon protonation are driving the release due to slight pH change from 5 to 7.

Keywords: nanovalves, nanogate, mesoporous silica nanoparticles, cargo

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Authors: Mustarakh Gelfi, Tiedo Vellinga, Poonam Taneja, Delon Hamonangan

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The development of New Priok/Kalibaru as an expansion terminal of the old port has been being done by IPC (Indonesia Port Cooperation) together with the subsidiary company, Port Developer (PT Pengembangan Pelabuhan Indonesia). As stated in the master plan, from 2 phases that had been proposed, phase I has shown its form and even Container Terminal I has been operated in 2016. It was planned principally, the development will be divided into Phase I (2013-2018) consist of 3 container terminals and 2 product terminals and Phase II (2018-2023) consist of 4 container terminals. In fact, the master plan has to be changed due to some major uncertainties which were escaped in prediction. This study is focused on the design scenario of phase II (2035- onwards) to deal with future uncertainty. The outcome is the robust design of phase II of the Kalibaru Terminal taking into account the future changes. Flexibility has to be a major goal in such a large infrastructure project like New Priok in order to deal and manage future uncertainty. The phasing of project needs to be adapted and re-look frequently before being irrelevant to future challenges. One of the frameworks that have been developed by an expert in port planning is Adaptive Port Planning (APP) with scenario-based planning. The idea behind APP framework is the adaptation that might be needed at any moment as an answer to a challenge. It is a continuous procedure that basically aims to increase the lifespan of waterborne transport infrastructure by increasing flexibility in the planning, contracting and design phases. Other methods used in this study are brainstorming with the port authority, desk study, interview and site visit to the real project. The result of the study is expected to be the insight for the port authority of Tanjung Priok over the future look and how it will impact the design of the port. There will be guidelines to do the design in an uncertain environment as well. Solutions of flexibility can be divided into: 1 - Physical solutions, all the items related hard infrastructure in the projects. The common things in this type of solution are using modularity, standardization, multi-functional, shorter and longer design lifetime, reusability, etc. 2 - Non-physical solutions, usually related to the planning processes, decision making and management of the projects. To conclude, APP framework seems quite robust to deal with the problem of designing phase II of New Priok Project for such a long period.

Keywords: Indonesia port, port's design, port planning, scenario-based planning

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

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Authors: Jean De Dieu Ayabagabo, Paul A.Onjoro, Karubiu P. Migwi, Marie C. Dusingize

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This study investigated the effects of feed on milk yield and quality through feed monitoring and quality assessment, and the consequent enteric methane gas emissions from smallholder dairy farms in drier areas of Rwanda, using the Tier II approach for four seasons in three zones, namely; Mayaga and peripheral Bugesera (MPB), Eastern Savanna and Central Bugesera (ESCB), and Eastern plateau (EP). The study was carried out using 186 dairy cows with a mean live weight of 292 Kg in three communal cowsheds. The milk quality analysis was carried out on 418 samples. Methane emission was estimated using prediction equations. Data collected were subjected to ANOVA. The dry matter intake was lower (p<0.05) in the long dry season (7.24 Kg), with the ESCB zone having the highest value of 9.10 Kg, explained by the practice of crop-livestock integration agriculture in that zone. The Dry matter digestibility varied between seasons and zones, ranging from 52.5 to 56.4% for seasons and from 51.9 to 57.5% for zones. The daily protein supply was higher (p<0.05) in the long rain season with 969 g. The mean daily milk production of lactating cows was 5.6 L with a lower value (p<0.05) during the long dry season (4.76 L), and the MPB zone having the lowest value of 4.65 L. The yearly milk production per cow was 1179 L. The milk fat varied from 3.79 to 5.49% with a seasonal and zone variation. No variation was observed with milk protein. The seasonal daily methane emission varied from 150 g for the long dry season to 174 g for the long rain season (p<0.05). The rain season had the highest methane emission as it is associated with high forage intake. The mean emission factor was 59.4 Kg of methane/year. The present EFs were higher than the default IPPC value of 41 Kg from developing countries in African, the Middle East, and other tropical regions livestock EFs using Tier I approach due to the higher live weight in the current study. The methane emission per unit of milk production was lower in the EP zone (46.8 g/L) due to the feed efficiency observed in that zone. Farmers should use high-quality feeds to increase the milk yield and reduce the methane gas produced per unit of milk. For an accurate assessment of the methane produced from dairy farms, there is a need for the use of the Life Cycle Assessment approach that considers all the sources of emissions.

Keywords: footprint, forage, girinka, tier

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Mariamawit T. Belete

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

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

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Authors: Natalia Kartushina

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Foreign (second) language (L2) learning is highly promoted in modern society. Students are encouraged to study abroad (SA) to achieve the most effective learning outcomes. However, L2 learning has side effects for native language (L1) production, as L1 sounds might show a drift from the L1 norms towards those of the L2, and this, even after a short period of L2 learning. L1 assimilatory drift has been attributed to a strong perceptual association between similar L1 and L2 sounds in the mind of L2 leaners; thus, a change in the production of an L2 target leads to the change in the production of the related L1 sound. However, nowadays, it is quite common that speakers acquire two languages from birth, as, for example, it is the case for many bilingual communities (e.g., Basque and Spanish in the Basque Country). Yet, it remains to be established how FL learning affects native production in individuals who have two native languages, i.e., in simultaneous or very early bilinguals. Does FL learning (here a third language, L3) affect bilinguals’ both languages or only one? What factors determine which of the bilinguals’ languages is more susceptible to change? The current study examines the effects of L3 (English) learning on the production of vowels in the two native languages of simultaneous Spanish-Basque bilingual adolescents enrolled into the Erasmus SA English program. Ten bilingual speakers read five Spanish and Basque consonant-vowel-consonant-vowel words two months before their SA and the next day after their arrival back to Spain. Each word contained the target vowel in the stressed syllable and was repeated five times. Acoustic analyses measuring vowel openness (F1) and backness (F2) were performed. Two possible outcomes were considered. First, we predicted that L3 learning would affect the production of only one language and this would be the language that would be used the most in contact with English during the SA period. This prediction stems from the results of recent studies showing that early bilinguals have separate phonological systems for each of their languages; and that late FL learner (as it is the case of our participants), who tend to use their L1 in language-mixing contexts, have more L2-accented L1 speech. The second possibility stated that L3 learning would affect both of the bilinguals’ languages in line with the studies showing that bilinguals’ L1 and L2 phonologies interact and constantly co-influence each other. The results revealed that speakers who used both languages equally often (balanced users) showed an F1 drift in both languages toward the F1 of the English vowel space. Unbalanced speakers, however, showed a drift only in the less used language. The results are discussed in light of recent studies suggesting that the amount of language use is a strong predictor of the authenticity in speech production with less language use leading to more foreign-accented speech and, eventually, to language attrition.

Keywords: language-contact, multilingualism, phonetic drift, bilinguals' production

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

Abstract:

This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Gautier Viaud, Paul-Henry Cournède

Abstract:

Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

Procedia PDF Downloads 280