Search results for: spatial rainfall prediction

Authors: Oskar Sekowski

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Current global warming causes changes in the traditional zones of viticulture worldwide. During 20th century, the average global air temperature increased by 0.89˚C. The models of climate change indicate that viticulture, currently concentrating in narrow geographic niches, may move towards the poles, to higher geographic latitudes. Global warming may cause changes in traditional viticulture regions. Therefore, there is a need to estimate the climatic conditions and climate change in areas that are not traditionally associated with viticulture, e.g., Poland. The primary objective of this paper is to prepare methodology to evaluate the climatic and meteorological potential for viticulture in Poland based on a case study. Moreover, the additional aim is to evaluate the climatic potential of a mesoregion where a university vineyard is located. The daily data of temperature, precipitation, insolation, and wind speed (1988-2018) from the meteorological station located in Łazy, southern Poland, was used to evaluate 15 climatological parameters and indices connected with viticulture. The next steps of the methodology are based on Geographic Information System methods. The topographical factors such as a slope gradient and slope exposure were created using Digital Elevation Models. The spatial distribution of climatological elements was interpolated by ordinary kriging. The values of each factor and indices were also ranked and classified. The viticultural potential was determined by integrating two suitability maps, i.e., the topographical and climatic ones, and by calculating the average for each pixel. Data analysis shows significant changes in heat accumulation indices that are driven by increases in maximum temperature, mostly increasing number of days with Tmax > 30˚C. The climatic conditions of this mesoregion are sufficient for vitis vinifera viticulture. The values of indicators and insolation are similar to those in the known wine regions located on similar geographical latitudes in Europe. The smallest threat to viticulture in study area is the occurrence of hail and the highest occurrence of frost in the winter. This research provides the basis for evaluating general suitability and climatologic potential for viticulture in Poland. To characterize the climatic potential for viticulture, it is necessary to assess the suitability of all climatological and topographical factors that can influence viticulture. The methodology used in this case study shows places where there is a possibility to create vineyards. It may also be helpful for wine-makers to select grape varieties.

Keywords: climatologic potential, climatic classification, Poland, viticulture

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Authors: N. Pritchard

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Within architectural education, students arrive fore-armed with; their life-experience; knowledge gained from subject-based learning; their brains and more specifically their imaginations. The learning-by-doing that they embark on in studio-based/project-based learning calls for supervision that allows the student to proactively undertake research and experimentation with design solution possibilities. The degree to which this supervision includes direction is subject to debate and differing opinion. It can be argued that if the student is to learn-by-doing, then design decision making within the design process needs to be instigated and owned by the student so that they have the ability to personally reflect on and evaluate those decisions. Within this premise lies the problem that the student's endeavours can become unstructured and unfocused as they work their way into a new and complex activity. A resultant weakness can be that the design activity is compartmented and not holistic or comprehensive, and therefore, the student's reflections are consequently impoverished in terms of providing a positive, informative feedback loop. The construct proffered in this paper is that a supportive 'armature' or 'Heuristic-Framework' can be developed that facilitates a holistic approach and reflective learning. The normal explorations of architectural design comprise: Analysing the site and context, reviewing building precedents, assimilating the briefing information. However, the student can still be compromised by 'not knowing what they need to know'. The long-serving triad 'Firmness, Commodity and Delight' provides a broad-brush framework of considerations to explore and integrate into good design. If this were further atomised in subdivision formed from the disparate aspects of architectural design that need to be considered within the design process, then the student could sieve through the facts more methodically and reflectively in terms of considering their interrelationship conflict and alliances. The words facts and sieve hold the acronym of the aspects that form the Heuristic-Framework: Function, Aesthetics, Context, Tectonics, Spatial, Servicing, Infrastructure, Environmental, Value and Ecological issues. The Heuristic could be used as a Hermeneutic Model with each aspect of design being focused on and considered in abstraction and then considered in its relation to other aspect and the design proposal as a whole. Importantly, the heuristic could be used as a method for gathering information and enhancing the design brief. The more poetic, mysterious, intuitive, unconscious processes should still be able to occur for the student. The Heuristic-Framework should not be seen as comprehensive prescriptive formulaic or inhibiting to the wide exploration of possibilities and solutions within the architectural design process.

Keywords: atomistic, hermeneutic, holistic, approach architectural design studio education

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Victorita Radulescu

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Introduction: The optimum exploitation of agricultural land in the presence of an aquifer polluted by the surface sources requires close monitoring of groundwater level in both periods of intense irrigation and in absence of the irrigations, in times of drought. Currently in Romania, in the south part of the country, the Baragan area, many agricultural lands are confronted with the risk of groundwater pollution in the absence of systematic irrigation, correlated with the climate changes. Basic Methods: The non-steady flow of the groundwater from an aquifer can be described by the Bousinesq’s partial differential equation. The finite element method was used, applied to the porous media needed for the water mass balance equation. By the proper structure of the initial and boundary conditions may be modeled the flow in drainage or injection systems of wells, according to the period of irrigation or prolonged drought. The boundary conditions consist of the groundwater levels required at margins of the analyzed area, in conformity to the reality of the pollutant emissaries, following the method of the double steps. Major Findings/Results: The drainage condition is equivalent to operating regimes on the two or three rows of wells, negative, as to assure the pollutant transport, modeled with the variable flow in groups of two adjacent nodes. In order to obtain the level of the water table, in accordance with the real constraints, are needed, for example, to be restricted its top level below of an imposed value, required in each node. The objective function consists of a sum of the absolute values of differences of the infiltration flow rates, increased by a large penalty factor when there are positive values of pollutant. In these conditions, a balanced structure of the pollutant concentration is maintained in the groundwater. The spatial coordinates represent the modified parameters during the process of optimization and the drainage flows through wells. Conclusions: The presented calculation scheme was applied to an area having a cross-section of 50 km between two emissaries with various levels of altitude and different values of pollution. The input data were correlated with the measurements made in-situ, such as the level of the bedrock, the grain size of the field, the slope, etc. This method of calculation can also be extended to determine the variation of the groundwater in the aquifer following the flood wave propagation in envoys.

Keywords: environmental protection, infiltrations, numerical modeling, pollutant transport through soils

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Authors: Shima Nabinejad, Holger Schüttrumpf

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Farmers who are living in flood-prone areas such as coasts are exposed to storm surges increased due to climate change. Crop cultivation is the most important economic activity of farmers, and in the time of flooding, agricultural lands are subject to inundation. Additionally, overflow saline water causes more severe damage outcomes than riverine flooding. Agricultural crops are more vulnerable to salinity than other land uses for which the economic damages may continue for a number of years even after flooding and affect farmers’ decision-making for the following year. Therefore, it is essential to assess what extent the agricultural areas are flooded and how much the associated flood damage to each individual farmer is. To address these questions, we integrated farmers’ decision-making at farm-scale with flood risk management. The integrated model includes identification of hazard scenarios, failure analysis of structural measures, derivation of hydraulic parameters for the inundated areas and analysis of the economic damages experienced by each farmer. The present study has two aims; firstly, it attempts to investigate the flooded cropland and potential crop damages for the whole area. Secondly, it compares them among farmers’ field for three flood scenarios, which differ in breach locations of the flood protection structure. To achieve its goal, the spatial distribution of fields and cultivated crops of farmers were fed into the flood risk model, and a 100-year storm surge hydrograph was selected as the flood event. The study area was Pellworm Island that is located in the German Wadden Sea National Park and surrounded by North Sea. Due to high salt content in seawater of North Sea, crops cultivated in the agricultural areas of Pellworm Island are 100% destroyed by storm surges which were taken into account in developing of depth-damage curve for analysis of consequences. As a result, inundated croplands and economic damages to crops were estimated in the whole Island which was further compared for six selected farmers under three flood scenarios. The results demonstrate the significance and the flexibility of the proposed model in flood risk assessment of flood-prone areas by integrating flood risk management and decision-making.

Keywords: crop damages, flood risk analysis, individual farmer, inundated cropland, Pellworm Island, storm surges

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Authors: E. Menga, S. Hernandez

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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Yu-Fong Lin

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The main purpose of this study is to explore the impact of different lighting arrangements that create different visual environments in a 3C retail store on the perception, psychology, and shopping tendencies of consumers of different genders. In recent years, the ‘emotional shopping’ model has been widely accepted in the consumer market; in addition to the emotional meaning and value of a product, the in-store ‘shopping atmosphere’ has also been increasingly regarded as significant. The lighting serves as an important environmental stimulus that influences the atmosphere of a store. Altering the lighting can change the color, the shape, and the atmosphere of a space. A successful retail lighting design can not only attract consumers’ attention and generate their interest in various goods, but it can also affect consumers’ shopping approach, behavior, and desires. 3C electronic products have become mainstream in the current consumer market. Consumers of different genders may demonstrate different behaviors and preferences within a 3C store environment. This study tests the impact of a combination of lighting contrasts and color temperatures in a 3C retail store on the visual perception and psychological reactions of consumers of different genders. The research design employs an experimental method to collect data from subjects and then uses statistical analysis adhering to a 2 x 2 x 2 factorial design to identify the influences of different lighting environments. This study utilizes virtual reality technology as the primary method by which to create four virtual store lighting environments. The four lighting conditions are as follows: high contrast/cool tone, high contrast/warm tone, low contrast/cool tone, and low contrast/warm tone. Differences in the virtual lighting and the environment are used to test subjects’ visual perceptions, emotional reactions, store satisfaction, approach-avoidance intentions, and spatial atmosphere preferences. The findings of our preliminary test indicate that female subjects have a higher pleasure response than male subjects in a 3C retail store. Based on the findings of our preliminary test, the researchers modified the contents of the questionnaires and the virtual 3C retail environment with different lighting conditions in order to conduct the final experiment. The results will provide information about the effects of retail lighting on the environmental psychology and the psychological reactions of consumers of different genders in a 3C retail store lighting environment. These results will enable useful practical guidelines about creating 3C retail store lighting and atmosphere for retailers and interior designers to be established.

Keywords: 3C retail store, environmental stimuli, lighting, virtual reality

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

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Authors: Christian Ihwiwhu, Nnamdi Obioha, Udeme John, Edward Bobade, Oghenerunor Bekibele, Adedeji Awujoola, Ibi-Ada Itotoi

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Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have a drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study aims to evaluate selected reservoirs in Ovhor Field, Niger Delta, Nigeria, with the objective of optimising production from the field by targeting undeveloped oil reserves, bypassed pay, and gaining an improved understanding of the selected reservoirs to increase the company’s reservoir limits. The task at the Ovhor field is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (sedimentology and stratigraphy) interpretation, use of results from quantitative interpretation, and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model has been constructed in such a way as to capture heterogeneities and the various compartments in the field to aid the proper simulation of fluid flow in the field for future production prediction, proper history matching and design of good trajectories to adequately target undeveloped oil in the field. Reservoir property models (porosity, permeability, and net-to-gross) have been constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captures the heterogeneities expected in the studied reservoirs. At least, two scenarios have been modelled for most of the studied reservoirs to capture the range of uncertainties we are dealing with. The total original oil in-place volume for the four reservoirs studied is 157 MMstb. The cumulative oil and gas production from the selected reservoirs are 67.64 MMstb and 9.76 Bscf respectively, with current production rate of about 7035 bopd and 4.38 MMscf/d (as at 31/08/2019). Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities include side-tracking and re-perforation of existing wells. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. New wells have/are being drilled now to test the results of our studies, and the results are very confirmatory and satisfying.

Keywords: facies, flow baffle, bypassed pay, heterogeneities, history matching, reservoir limit

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Authors: Sikhou Drame, Arfang Diamanka

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In Senegal, the fishing sector plays an important role in socio-economic development. However, he is going through enormous difficulties, caused by the scarcity of fish on the Senegalese coast, the overexploitation of fishery resources. Based on this observation, the authorities are betting on the development of aquaculture. It is in this context that the exploration of fish from the highly consumed Sparidae family remains a good solution. Indeed, the Sparidae family has good characteristics for farming at sea. However, parasites can proliferate and destroy the efforts made to cultivate fish in confined areas. the knowledge of these parasites in particular the monogeneans, very specific to the sparidae fishes will allow to better know the bio-ecology of the fishes. Better know the main parasitic monogeneans of the genus Lamellodiscus of sparidae fish of the genus Pagrus harvested in Senegal. It will first be a question of identifying from the observation of the morpho-anatomical characters, Monogeneans of the genus Lamellodiscus, branchial parasites collected from three species of host: Pagrus caeruleostictus , Pagrus auriga and Pagrus africanus. Then to evaluate the spatial and temporary distribution of parasitic indices on two Dakar landing sites (Soumbédioune and Yarakh) and finally to determine their specificity. The fish examined were purchased directly from the landing sites in Dakar and then transported to the laboratory where they were identified, then dissected. The gills were examined under a magnifying glass and the monogeneans were harvested, fixed in 70% ethanol and then mounted between slide and coverslip. The identification of the parasites is based on the observation of the morpho-anatomical characters and on the measurements of the sclerified organs of the haptor and the male copulatory organ. In total out of the 90 individuals examined: Pagrus auriga (30), Pagrus africanus (30) and Pagrus caeruleostictus (30), 6 species of monogeneans of the genus Lamellodiscus (Monogenea, Diplectanidae) are obtained: L. sarculus, L. sigillatus, L.vicinus, L. rastellus, L. africanus n.sp and L. yarakhensis n.sp. Our results show that specimens of small sizes [15-20[cm are the most infested. The values of infestation intensity and abundance are higher in fish from Yarakh and also during the cold season. it is the species Pagrus caeruleostictus which records the highest parasitic loads in the two localities. the majority of the parasites identified have a strict or oioxene specificity. It appears from this study that fish of the genus Pagrus are highly parasitized by monogeneans of the genus Lamellodiscus with a general prevalence of 87.78%. Each infested fish has an average of 30 monogeneans of the genus Lamellodiscus.

Keywords: monogeneans, Lamellodiscus, Dakar coast, genus Pagrus

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Authors: Meenakshi Pappu

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The terms like liveability, Sustainable Development Goals and pandemic have been widely analysed in proving sustainable cities and community living in growing urban areas by 2030. The pandemic has made us all ruminate about how we look into different fast-growing cities which vary in geographical location, climatic zones, terrains, land use and varying cultural backgrounds & traditions belong to the mother soil. India has taken up huge steps to move towards achieving UN-SDGs. Smart city missions have played a vital role in moving towards SDG. Visakhapatnam city is the executive capital in the state of Andhra Pradesh. Located on the Eastern Ghats in South India, it is surrounded by a mountain range on three sides and the Indian Ocean on one side. This unique geographical location and fast urbanization in the last two decades, has put up immense pressure on the natural environment and recourses. It's observed that a lot of investigation to address the existing and proposed land-use, spatial, natural resources, air quality, environmental challenges, and a range of socio-economic, economic challenges were identified during the assessment phase. The citizen concerns with quality and quantity of access to water, sewerage, energy, transportation (public & private) and safety for the public were found out through surveying. Urban infrastructure plays a major part in city building. These cities are occupied by people who come for a better living. This paper aims to provide off-center way of approach to citizens-oriented community habits by addressing SDG 11: Sustainable cities & community by enkindling a characteristic framework of amalgamating 1.eco-design principal, 2. three factors of liveability and 3. a local traditional planning solution. Aiming towards a sustainable development utilized with the focus on the quality of the life and experience of the people who live in urban areas integrating life with soil & water. Building strong social agenda that includes affordable housing for all levels of households, secure and place for good quality public realm for the local people with activity in green corridor, open meeting space & adding recreational places for advantage..

Keywords: livability, eco-design, smart city mission, sustainable

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

Procedia PDF Downloads 77

Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Ahmed A. El-Gindy, Elham S. El-Nashar, Abdallah Nafaa, Sameh El-Kafrawy

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The generation of energy from marine energy became one of the most preferable resources since it is a clean source and friendly to environment. Egypt has long shores along Mediterranean with important cities that need energy resources with significant wave energy. No detailed studies have been done on wave energy distribution in the Egyptian waters. The objective of this paper is to assess the energy wave power available in the Egyptian waters for the choice of the most suitable devices to be used in this area. This paper deals the characteristics and power of the offshore waves in the Egyptian waters. Since the field observations of waves are not frequent and need much technical work, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data in Mediterranean, with a grid size 0.75 degree, which is a relatively course grid, are considered in the present study for preliminary assessment of sea waves characteristics and power. The used data covers the period from 2012 to 2014. The data used are significant wave height (swh), mean wave period (mwp) and wave direction taken at six hourly intervals, at seven chosen stations, and at grid points covering the Egyptian waters. The wave power (wp) formula was used to calculate energy flux. Descriptive statistical analysis including monthly means and standard deviations of the swh, mwp, and wp. The percentiles of wave heights and their corresponding power are done, as a tool of choice of the best technology suitable for the site. The surfer is used to show spatial distributions of wp. The analysis of data at chosen 7 stations determined the potential of wp off important Egyptian cities. Offshore of Al Saloum and Marsa Matruh, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and October (1.49-1.69) ± (1.45-1.74) kw/m. In front of Alexandria and Rashid, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and September (1.29-2.01) ± (1.31-1.83) kw/m. In front of Damietta and Port Said, the highest wp occurred in February (14.29-17.61) ± (21.61-27.10) kw/m and the lowest occurred in June (0.94-0.96) ± (0.71-0.72) kw/m. In winter, the probabilities of waves higher than 0.8 m in percentage were, at Al Saloum and Marsa Matruh (76.56-80.33) ± (11.62-12.05), at Alexandria and Rashid (73.67-74.79) ± (16.21-18.59) and at Damietta and Port Said (66.28-68.69) ± (17.88-17.90). In spring, the percentiles were, at Al Saloum and Marsa Matruh, (48.17-50.92) ± (5.79-6.56), at Alexandria and Rashid, (39.38-43.59) ± (9.06-9.34) and at Damietta and Port Said, (31.59-33.61) ± (10.72-11.25). In summer, the probabilities were, at Al Saloum and Marsa Matruh (57.70-66.67) ± (4.87-6.83), at Alexandria and Rashid (59.96-65.13) ± (9.14-9.35) and at Damietta and Port Said (46.38-49.28) ± (10.89-11.47). In autumn, the probabilities were, at Al Saloum and Marsa Matruh (58.75-59.56) ± (2.55-5.84), at Alexandria and Rashid (47.78-52.13) ± (3.11-7.08) and at Damietta and Port Said (41.16-42.52) ± (7.52-8.34).

Keywords: distribution of sea waves energy, Egyptian Mediterranean waters, waves characteristics, waves power

Procedia PDF Downloads 174

Authors: Titilope F. Onaolapo, Christiana A. Breed, Maya Pasgaard, Kristine E. Jensen, Peta Brom

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In the face of fast-growing urbanization in most of the world's developing countries, there is a need to understand and address the risk and consequences involved in the indiscriminate use of urban green space. Tshwane city in South Africa has the potential to become one of the world's top biodiversity cities as South Africa is ranked one of the mega countries in biodiversity conservation, and Tshwane metropolitan municipality is the city with the wealthiest biodiversity with grassland biomes. In this study, we focus on the potentials and challenges of urban green transitioning from the Global South perspective with Tshwane city as the case study. We also address the issue of management conflicts that have resulted in informal and illegal activities in and around green spaces, with consequences such as land degradation, loss of livelihoods and biodiversity, and socio-ecological imbalances. A desk study review of eight policy frameworks related to green urban planning and development was done based on four GI principles: multifunctionality, connectivity, interdisciplinary and social inclusion. We interviewed 15 key informants in related departments in the city and administered 200 survey questionnaires among residents. We also had several workshops the other researchers and experts on biodiversity and ecosystem. We found out there is no specific document dedicated to green space management, and where green infrastructure was mentioned, it was focused on as an approach to climate mitigation and adaptation. Also, residents perceive green and open spaces as extra land that could be developed at will. We demonstrated the use of collaborative learning approaches in ecological and development research and the tying research to the existing frameworks, programs, and strategies. Based on this understanding. We outlined the need to incorporate principles of green infrastructure in policy frameworks on spatial planning and environmental development. Furthermore, we develop a model for co-management of green infrastructures by stakeholders, such as residents, developers, policymakers, and decision-makers, to maximize benefits. Our collaborative, interdisciplinary projects pursue SDG multifunctionality of goals 11 and 15 by simultaneously addressing issues around Sustainable Cities and Communities, Climate Action, Life on Land, and Strong Institutions, and halt and reverse land degradation and biodiversity.

Keywords: governance, green infrastructure, South Africa, sustainable development, urban planning, Tshwane

Procedia PDF Downloads 103

Authors: Sandra Smart-Akande, Chaminda Hewage, Imtiaz Khan, Thanuja Mallikarachchi

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According to UK police-recorded data, there has been a substantial increase in knife-related crime and youth violence in the UK since 2014 particularly in the London boroughs. These crime rates are disproportionally distributed across London with the majority of these crimes occurring in the highly deprived areas of London and among young people aged 11 to 24 with large discrepancies across ethnicity, age, gender and borough of residence. Comprehensive studies and literature have identified risk factors associated with a knife carrying among youth to be Adverse Childhood Experience (ACEs), poor mental health, school or social exclusion, drug dealing, drug using, victim of violent crime, bullying, peer pressure or gang involvement, just to mention a few. ACEs are potentially traumatic events that occur in childhood, this can be experiences or stressful events in the early life of a child and can lead to an increased risk of damaging health or social outcomes in the latter life of the individual. Research has shown that children or youths involved in youth violence have had childhood experience characterised by disproportionate adverse childhood experiences and substantial literature link ACEs to be associated with criminal or delinquent behavior. ACEs are commonly grouped by researchers into: Abuse (Physical, Verbal, Sexual), Neglect (Physical, Emotional) and Household adversities (Mental Illness, Incarcerated relative, Domestic violence, Parental Separation or Bereavement). To the author's best knowledge, no study to date has investigated how household mental health (mental health of a parent or mental health of a child) and domestic violence (domestic violence on a parent or domestic violence on a child) is related to knife homicides across the local authorities areas of London. This study seeks to address the gap by examining a large sample of data from the London Metropolitan Police Force and Characteristics of Children in Need data from the UK Department for Education. The aim of this review is to identify and synthesise evidence from data and a range of literature to identify the relationship between adverse childhood experiences and youth violence in the UK. Understanding the link between ACEs and future outcomes can support preventative action.

Keywords: adverse childhood experiences, domestic violence, mental health, youth violence, prediction analysis, London knife crime

Procedia PDF Downloads 103

Authors: Anjali Sadanand, R. V. Nagarajan

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Architecture morphs with advances in technology and the roof, wall, and floor as basic elements of a building, follow in redefining themselves over time. Their contribution is bound by time and held by design principles that deal with function, sturdiness, and beauty. Architecture engages with people to give joy through its form, material, design structure, and spatial qualities. This paper attempts to re-interpret John Ruskin’s “Seven lamps of Architecture” in the context of the architecture of the modern and present period. The paper focuses on the “wall” as an element of study in this context. Four of Ruskin’s seven lamps will be discussed, namely beauty, truth, life, and memory, through examples of architecture ranging from modernism to contemporary architecture of today. The study will focus on the relevance of Ruskin’s principles to the “wall” in specific, in buildings of different materials and over a range of typologies from all parts of the world. Two examples will be analyzed for each lamp. It will be shown that in each case, there is relevance to the significance of Ruskin’s lamps in modern and contemporary architecture. Nature to which Ruskin alludes to for his lamp of “beauty” is found in the different expressions of interpretation used by Corbusier in his Villa Stein façade based on proportion found in nature and in the direct expression of Toyo Ito in his translation of an understanding of the structure of trees into his façade design of the showroom for a Japanese bag boutique. “Truth” is shown in Mies van der Rohe’s Crown Hall building with its clarity of material and structure and Studio Mumbai’s Palmyra House, which celebrates the use of natural materials and local craftsmanship. “Life” is reviewed with a sustainable house in Kerala by Ashrams Ravi and Alvar Aalto’s summer house, which illustrate walls as repositories of intellectual thought and craft. “Memory” is discussed with Charles Correa’s Jawahar Kala Kendra and Venturi’s Vana Venturi house and discloses facades as text in the context of its materiality and iconography. Beauty is reviewed in Villa Stein and Toyo Ito’s Branded Retail building in Tokyo. The paper thus concludes that Ruskin’s Lamps can be interpreted in today’s context and add richness to meaning to the understanding of architecture.

Keywords: beauty, design, facade, modernism

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Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

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Low-molecular-weight organogelators form gels by self-assembly into the crystalline network which immobilizes the organic solvent. For single bisamide organogelator systems, the effect of the molecular structure on the molecular interaction and their self-assembly behavior has been explored. The spatial arrangement of bisamide molecules in the gel-state is driven by a combination of hydrogen bonding and Van der Waals interactions. The hydrogen-bonding pattern between the amide groups of bisamide molecules is regulated by the number of methylene spacers; the even number of methylene spacers between two amide groups, in even-spaced bisamides, leads to the antiparallel position of amide groups within a molecule. An even-spaced bisamide molecule with antiparallel amide groups can make two pairs of hydrogen bonding with the molecules on the same plane. The odd-spaced bisamide with a parallel directionality of amide groups can form four independent hydrogen bonds with four other bisamide molecules on different planes. The arrangement of bisamide molecules in the crystalline state and the interaction of these molecules depends on the molecular structure, particularly the parity of the spacer length between the amide groups in the bisamide molecule. In this study, the directionality of amide groups has been exploited as a structural characteristic to affect the arrangement of molecules in the crystalline state and produce different binary bisamide gelators with different degrees of crystallinities. Single odd- and even-spaced single bisamides were synthesized and blended to produce binary bisamide organogelators to be characterized in order to understand the effect of the different directionality of amide groups on the molecular interaction in the crystalline state. The pattern of molecular interactions between these blended molecules, mixing or phase separation, has been monitored via differential scanning calorimetry (DSC) and crystallography techniques; X-ray powder diffraction (XRD) and Small-angle X-ray scattering (SAXS). The formation of lamellar structures for odd- and even-spaced bisamide gelators was confirmed by using SAXS and XRD techniques. DSC results have shown that binary bisamide organogelators with different parity of methylene spacers (odd-even binary blends) have a higher tendency for phase separation compared to the binary bisamides with the same parity (odd-odd or even-even binary blends). Phase separation in binary odd-even bisamides was confirmed by the presence of individual (100) reflections of odd and even lamellar structures. The structural characteristic of bisamide organogelators, the parity of spacer length in binary systems, is a promising tool to control the arrangement of molecules and their crystalline structure.

Keywords: binary bisamide organogelators, crystalline structure, phase separation, self-assembly behavior

Procedia PDF Downloads 173

Authors: Ahmed Elaksher

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Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.

Keywords: UAV, photogrammetry, SfM, DEM

Procedia PDF Downloads 273

Authors: Emílie Kučerová, Tereza Veverková, Marina Morozovová, Eva Kudová, Jitka Viktorová

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The blood-brain barrier (BBB) is a key element regulating the transport of substances between the blood and the central nervous system (CNS). The BBB protects the CNS from potentially harmful substances and maintains a suitable environment for nervous activity in the CNS, but at the same time, it represents a significant obstacle to the entry of drugs into the CNS. Pharmacoresistant epilepsy is a form of epilepsy that cannot be suppressed using two (or more) appropriately chosen antiepileptic drugs. In many cases, pharmacoresistant epilepsy is characterized by an increased concentration of efflux pumps on the luminal sides of the endothelial cells that form the BBB and an increased number of drug-metabolizing enzymes in the BBB cells, thereby preventing the effective transport of antiepileptic drugs into the CNS. Currently, a number of scientific groups are focusing on the preparation and improvement of BBB models in vitro in order to study cell interactions or transport mechanisms. However, in pathological conditions such as pharmacoresistant epilepsy, there are changes in BBB structure, and current BBB models are insufficient for related research. Our goal is to develop a suitable BBB model for pharmacoresistant epilepsy in vitro and use it to test the transfer of potential antiepileptic drugs. This model is created by co-culturing immortalized human cerebral microvascular endothelial cells, human vascular pericytes and immortalized human astrocytes. The BBB in vitro is cultivated in the form of a 2D transwell model and the integrity of the barrier is verified by measuring transendothelial electrical resistance (TEER). From the current results, a contact cell arrangement with the cultivation of endothelial cells on the upper side of the insert and the co-cultivation of astrocytes and pericytes on the lower side of the insert is selected as the most promising for BBB model cultivation. The pharmacoresistance of the BBB model is achieved by long-term cultivation of endothelial cells in an increasing concentration of selected antiepileptic drugs, which should lead to increased production of efflux pumps and drug-metabolizing enzymes. The pharmacoresistant BBB model in vitro will be further used for the screening of substances that could act both as antiepileptics and at the same time as inhibitors of efflux pumps in endothelial cells. This project was supported by the Technology Agency of the Czech Republic (TACR), Personalized Medicine: Translational research towards biomedical applications, No. TN02000109 and by the Academy of Sciences of the Czech Republic (AS CR) – grant RVO 61388963.

Keywords: antiepileptic drugs, blood-brain barrier, efflux transporters, pharmacoresistance

Procedia PDF Downloads 48

Authors: Esmat Kamel

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This paper aims to shed light on the extent to which the Agadir Association agreement has fostered inter regional trade between the E.U_26 and the Agadir_4 countries; once that we control for the evolution of Agadir agreement’s exports to the rest of the world. The next valid question will be regarding any remarkable variation in the spatial/sectoral structure of exports, and to what extent has it been induced by the Agadir agreement itself and precisely after the adoption of rules of origin and the PANEURO diagonal cumulative scheme? The paper’s empirical dataset covering a timeframe from [2000 -2009] was designed to account for sector specific export and intermediate flows and the bilateral structured gravity model was custom tailored to capture sector and regime specific rules of origin and the Poisson Pseudo Maximum Likelihood Estimator was used to calculate the gravity equation. The methodological approach of this work is considered to be a threefold one which starts first by conducting a ‘Hierarchal Cluster Analysis’ to classify final export flows showing a certain degree of linkage between each other. The analysis resulted in three main sectoral clusters of exports between Agadir_4 and E.U_26: cluster 1 for Petrochemical related sectors, cluster 2 durable goods and finally cluster 3 for heavy duty machinery and spare parts sectors. Second step continues by taking export flows resulting from the 3 clusters to be subject to treatment with diagonal Rules of origin through ‘The Double Differences Approach’, versus an equally comparable untreated control group. Third step is to verify results through a robustness check applied by ‘Propensity Score Matching’ to validate that the same sectoral final export and intermediate flows increased when rules of origin were relaxed. Through all the previous analysis, a remarkable and partial significance of the interaction term combining both treatment effects and time for the coefficients of 13 out of the 17 covered sectors turned out to be partially significant and it further asserted that treatment with diagonal rules of origin contributed in increasing Agadir’s_4 final and intermediate exports to the E.U._26 on average by 335% and in changing Agadir_4 exports structure and composition to the E.U._26 countries.

Keywords: agadir association agreement, structured gravity model, hierarchal cluster analysis, double differences estimation, propensity score matching, diagonal and relaxed rules of origin

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Authors: Claudia García-García, Catalina B. García-García, Román Salmerón-Gómez

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Much economic-environmental research includes the analysis of possible interactions by using Moderated Regression Analysis (MRA), which is a specific application of multiple linear regression analysis. This methodology allows analyzing how the effect of one of the independent variables is moderated by a second independent variable by adding a cross-product term between them as an additional explanatory variable. Due to the very specification of the methodology, the moderated factor is often highly correlated with the constitutive terms. Thus, great multicollinearity problems arise. The appearance of strong multicollinearity in a model has important consequences. Inflated variances of the estimators may appear, there is a tendency to consider non-significant regressors that they probably are together with a very high coefficient of determination, incorrect signs of our coefficients may appear and also the high sensibility of the results to small changes in the dataset. Finally, the high relationship among explanatory variables implies difficulties in fixing the individual effects of each one on the model under study. These consequences shifted to the moderated analysis may imply that it is not worth including an interaction term that may be distorting the model. Thus, it is important to manage the problem with some methodology that allows for obtaining reliable results. After a review of those works that applied the MRA among the ten top journals of the field, it is clear that multicollinearity is mostly disregarded. Less than 15% of the reviewed works take into account potential multicollinearity problems. To overcome the issue, this work studies the possible application of recent methodologies to MRA. Particularly, the raised regression is analyzed. This methodology mitigates collinearity from a geometrical point of view: the collinearity problem arises because the variables under study are very close geometrically, so by separating both variables, the problem can be mitigated. Raise regression maintains the available information and modifies the problematic variables instead of deleting variables, for example. Furthermore, the global characteristics of the initial model are also maintained (sum of squared residuals, estimated variance, coefficient of determination, global significance test and prediction). The proposal is implemented to data from countries of the European Union during the last year available regarding greenhouse gas emissions, per capita GDP and a dummy variable that represents the topography of the country. The use of a dummy variable as the moderator is a special variant of MRA, sometimes called “subgroup regression analysis.” The main conclusion of this work is that applying new techniques to the field can improve in a substantial way the results of the analysis. Particularly, the use of raised regression mitigates great multicollinearity problems, so the researcher is able to rely on the interaction term when interpreting the results of a particular study.

Keywords: multicollinearity, MRA, interaction, raise

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Authors: Jianuo Sun, Jinghan Wang, Sirui Zhang, Chenhan Xu, Hongxia Hao, Hong Zhou

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In recent years, the diversification and industrialization of drug-related crimes have posed significant threats to public health and safety globally. The widespread and increasingly younger demographics of drug users and the persistence of drug-impaired driving incidents underscore the urgency of this issue. Drug detection, a specialized forensic activity, is pivotal in identifying and analyzing substances involved in drug crimes. It relies on pharmacological and chemical knowledge and employs analytical chemistry and modern detection techniques. However, current drug detection methods are limited by their inability to perform semi-quantitative, real-time field analyses. They require extensive, complex laboratory-based preprocessing, expensive equipment, and specialized personnel and are hindered by long processing times. This study introduces an alternative approach using nucleic acid aptamers and Aggregation-Induced Emission (AIE) technology. Nucleic acid aptamers, selected artificially for their specific binding to target molecules and stable spatial structures, represent a new generation of biosensors following antibodies. Rapid advancements in AIE technology, particularly in tetraphenyl ethene-based luminous, offer simplicity in synthesis and versatility in modifications, making them ideal for fluorescence analysis. This work successfully synthesized, isolated, and purified an AIE molecule and constructed a probe comprising the AIE molecule, nucleic acid aptamers, and exonuclease for cocaine detection. The probe demonstrated significant relative fluorescence intensity changes and selectivity towards cocaine over other drugs. Using 4-Butoxytriethylammonium Bromide Tetraphenylethene (TPE-TTA) as the fluorescent probe, the aptamer as the recognition unit, and Exo I as an auxiliary, the system achieved rapid detection of cocaine within 5 mins in aqueous and urine, with detection limits of 1.0 and 5.0 µmol/L respectively. The probe-maintained stability and interference resistance in urine, enabling quantitative cocaine detection within a certain concentration range. This fluorescent sensor significantly reduces sample preprocessing time, offers a basis for rapid onsite cocaine detection, and promises potential for miniaturized testing setups.

Keywords: drug detection, aggregation-induced emission (AIE), nucleic acid aptamer, exonuclease, cocaine

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Authors: Virendra Nath, Vipin Kumar

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Background: TypeII Diabetes mellitus is a foremost health problem worldwide, predisposing to increased mortality and morbidity. Undesirable effects of the current medications have prompted the researcher to develop more potential drug(s) against the disease. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptors family and take part in a vital role in the regulation of metabolic equilibrium. They can induce or repress genes associated with adipogenesis, lipid, and glucose metabolism. Aims: Investigation of PPARα/γ agonistic hits were screened by hierarchical virtual screening followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) analysis using approved PPAR α/γ dual agonist. Methods: The PPARα/γ agonistic activity of compounds was searched by using Maestro through structure-based virtual screening and molecular dynamics (MD) simulation application. Virtual screening of nuclear-receptor ligands was done, and the binding modes with protein-ligand interactions of newer entity(s) were investigated. Further, binding energy prediction, Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit along with the structural comparative analysis of approved PPARα/γ agonists with screened hit was done for knowledge-based SAR. Results and Discussion: The silicone chip-based approach recognized the most capable nine hits and had better predictive binding energy as compared to the reference drug compound (Tesaglitazar). In this study, the key amino acid residues of binding pockets of both targets PPARα/γ were acknowledged as essential and were found to be associated in the key interactions with the most potential dual hit (ChemDiv-3269-0443). Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit and found root mean square deviation (RMSD) stabile around 2Å and 2.1Å, respectively. Frequency distribution data also revealed that the key residues of both proteins showed maximum contacts with a potent hit during the MD simulation of 20 nanoseconds (ns). The knowledge-based SAR studies of PPARα/γ agonists were studied using 2D structures of approved drugs like aleglitazar, tesaglitazar, etc. for successful designing and synthesis of compounds PPARγ agonistic candidates with anti-hyperlipidimic potential.

Keywords: computational, diabetes, PPAR, simulation

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Authors: Xue Ma, Yang Fu, Dangyuan Lei

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Passive daytime radiative cooling is an emerging technology which has attracted worldwide attention in recent years due to its huge potential in cooling buildings without the use of electricity. Various coating materials with different optical properties have been developed to improve the daytime radiative cooling performance. However, commercial cooling coatings comprising functional fillers with optical bandgaps within the solar spectral range suffers from severe intrinsic absorption, limiting their cooling performance. Fortunately, it has recently been demonstrated that introducing fluorescent materials into polymeric coatings can covert the absorbed sunlight to fluorescent emissions and hence increase the effective solar reflectance and cooling performance. In this paper, we experimentally investigate the key factors for fluorescence-assisted radiative cooling with TiO2-based white coatings. The surrounding TiO2 nanoparticles, which enable spatial and temporal light confinement through multiple Mie scattering, lead to Purcell enhancement of phosphors in the coating. Photoluminescence lifetimes of two phosphors (BaMgAl10O17:Eu2+ and (Sr, Ba)SiO4:Eu2+) exhibit significant reduction of ~61% and ~23%, indicating Purcell factors of 2.6 and 1.3, respectively. Moreover, smaller Stokes shifts of the phosphors are preferred to further diminish solar absorption. Field test of fluorescent cooling coatings demonstrate an improvement of ~4% solar reflectance for the BaMgAl10O17:Eu2+-based fluorescent cooling coating. However, to maximize solar reflectance, a white appearance is introduced based on multiple Mie scattering by the broad size distribution of fillers, which is visually pressurized and aesthetically bored. Besides, most colored pigments absorb visible light significantly and convert it to non-radiative thermal energy, offsetting the cooling effect. Therefore, current colored cooling coatings are facing the compromise between color saturation and cooling effect. To solve this problem, we introduced colored fluorescent materials into white coating based on SiO2 microspheres as a top layer, covering a white cooling coating based on TiO2. Compared with the colored pigments, fluorescent materials could re-emit the absorbed light, reducing the solar absorption introduced by coloration. Our work investigated the scattering properties of SiO2 dielectric spheres with different diameters and detailly discussed their impact on the PL properties of phosphors, paving the way for colored fluorescent-assisted cooling coting to application and industrialization.

Keywords: solar reflection, infrared emissivity, mie scattering, photoluminescent emission, radiative cooling

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

Abstract:

This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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