Search results for: temporal resolution

Authors: A. Cittadino, P. Gantes, C. Coviella, M. Casset, A. Sanchez Caro

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Three currently active landfills receive the waste from Buenos Aires city and the Great Buenos Aires suburbs. One of the first landfills to receive solid waste from this area was located in Villa Dominico, some 7 km south from Buenos Aires City. With an area of some 750 ha, including riparian habitats, divided into 14 cells, it received solid wastes from June 1979 through February 2004. In December 2010, a biological monitoring program was set up by CEAMSE and Universidad Nacional de Lujan, still operational to date. The aim of the monitoring program is to assess the state of several biological groups within the landfill and to follow their dynamics overtime in order to identify if any, early signs of damage the landfill activities might have over the biota present. Bird and rodent populations, aquatic and terrestrial invertebrates’ populations, cells vegetation coverage, and surrounding areas vegetation coverage and main composition are followed by quarterly samplings. Bird species richness and abundance were estimated by observation over walk transects on each environment. A total of 74 different species of birds were identified. Species richness and diversity were high for both riparian surrounding areas and within the landfill. Several grassland -typical of the 'Pampa'- bird species were found within the landfill, as well as some migratory and endangered bird species. Sherman and Tomahawk traps are set overnight for small mammal sampling. Rodent populations are just above detection limits, and the few specimens captured belong mainly to species common to rural areas, instead of city-dwelling species. The two marsupial species present in the region were captured on occasions. Aquatic macroinvertebrates were sampled on a watercourse upstream and downstream the outlet of the landfill’s wastewater treatment plant and are used to follow water quality using biological indices. Water quality ranged between weak and severe pollution; benthic invertebrates sampled before and after the landfill, show no significant differences in water quality using the IBMWP index. Insect biota from yellow sticky cards and pitfall traps showed over 90 different morphospecies, with Shannon diversity index running from 1.9 to 3.9, strongly affected by the season. An easy-to-perform non-expert demandant method was used to assess vegetation coverage. Two scales of determination are utilized: field observation (1 m resolution), and Google Earth images (that allow for a better than 5 m resolution). Over the eight year period of the study, vegetation coverage over the landfill cells run from a low 83% to 100% on different cells, with an average between 95 to 99% for the entire landfill depending on seasonality. Surrounding area vegetation showed almost 100% coverage during the entire period, with an average density from 2 to 6 species per sq meter and no signs of leachate damaged vegetation.

Keywords: biological indicators, biota monitoring, landfill species diversity, waste management

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Authors: M. Yasin Al-Arif, Mohammad Faisol Soleh

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The Indonesia’s Constitution in Article 18b explained that the state recognizes and respects indigenous peoples and their traditional rights that are guaranteed by the law. Despite already guaranteed its existence; in practice such indigenous law is often considered contrary to positive law by legal experts. It is because of legal positivism paradigm which requires the written law as the main reference for the settlement of legal disputes. Carok’s culture is one of the indigenous cultures of Madura to resolve legal disputes that still thrives until today. Carok’s culture is in outside the legal process, and through a fight between the disputing parties until one dies. On the other hand, the legal positivism does not give place to accommodate Carok as indigenous dispute settlement, until it must be solved through trial. This way of settlement has not been successfully satisfying the indigenous people, thus although it has been done through its verdict in the trial, but Carok still be used by them. From the explanation above, Carok’s culture must be accommodated as the main settlement process and legal process of law as the alternative to the effectiveness of dispute resolution in Madura Indonesia.

Keywords: carok, dispute settlement, legal positivism, madura’s culture

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Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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Authors: Osamu Komori, Shinto Eguchi, Hiroshi Okamura, Momoko Ichinokawa

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The long time-series data on population assessments are essential for global ecosystem assessment because the temporal change of biomass in such a database reflects the status of global ecosystem properly. However, the available assessment data usually have limited sample sizes and the ratio of populations with low abundance of biomass (collapsed) to those with high abundance (non-collapsed) is highly imbalanced. To allow for the imbalance and uncertainty involved in the ecological data, we propose a binary regression model with mixed effects for inferring ecosystem status through an asymmetric logistic model. In the estimation equation, we observe that the weights for the non-collapsed populations are relatively reduced, which in turn puts more importance on the small number of observations of collapsed populations. Moreover, we extend the asymmetric logistic regression model using propensity score to allow for the sample biases observed in the labeled and unlabeled datasets. It robustified the estimation procedure and improved the model fitting.

Keywords: double robust estimation, ecological binary data, mixed effect logistic regression model, propensity score

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Authors: Sancho-Esper Franco, Rodríguez Sánchez Carla, Sánchez Carolina, Orús-Sanclemente Carlos

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Water scarcity is a reality that affects many regions of the world and is aggravated by climate change and population growth. Saving water has become an urgent need to ensure the sustainability of the planet and the survival of many communities, where youth and social networks play a key role in promoting responsible practices and adopting habits that contribute to environmental preservation. This study analyzes the persuasion capacity of messages designed to promote pro-environmental behaviors among youth. Specifically, it studies how the efficacy (effectiveness) of the response (personal response efficacy/effectiveness) and the perception of distance from the source of the message influence the water-saving behavior of the audience. To do so, two communication frameworks are combined. First, the Construal Level Theory, which is based on the concept of "psychological distance", that is, people, objects or events can be perceived as psychologically near or far, and this subjective distance (i.e., social, temporal, or spatial) determines their attitudes, emotions, and actions. This perceived distance can be social, temporal, or spatial. This research focuses on studying the spatial distance and social distance generated by cultural differences between influencers and their audience to understand how cultural distance can influence the persuasiveness of a message. Research on the effects of psychological distance between influencers-followers in the pro-environmental field is very limited, being relevant because people could learn specific behaviors suggested by opinion leaders such as influencers in social networks. Second, different approaches to behavioral change suggest that the perceived efficacy of a behavior can explain individual pro-environmental actions. People will be more likely to adopt a new behavior if they perceive that they are capable of performing it (efficacy belief) and that their behavior will effectively contribute to solving that problem (personal response efficacy). It is also important to study the different actors (social and individual) that are perceived as responsible for addressing environmental problems. Specifically, we analyze to what extent the belief individual’s water-saving actions are effective in solving the problem can influence water-saving behavior since this individual effectiveness increases people's sense of obligation and responsibility with the problem. However, in this regard, empirical evidence presents mixed results. Our study addresses the call for experimental studies manipulating different subtypes of response effectiveness to generate robust causal evidence. Based on all the above, this research analyzes whether cultural distance (local vs. international influencer) and the perception of effectiveness of behavior (personal response efficacy) (personal/individual vs. collective) affect the actual behavior and the intention to conserve water of social network users. An experiment of 2 (local influencer vs. international influencer) x 2 (effectiveness of individual vs. collective response) is designed and estimated. The results show that a message from a local influencer appealing to individual responsibility exerts greater influence on intention and actual water-saving behavior, given the cultural closeness between influencer-follower, and the appeal to individual responsibility increases the feeling of obligation to participate in pro-environmental actions. These results offer important implications for social marketing campaigns that seek to promote water conservation.

Keywords: social marketing, influencer, message framing, experiment, personal response efficacy, water saving

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Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

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We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Majid Afkhami, Maryam Ehsanpour

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The present study provides information about the nature of adverse effects on fish and the ecological impact that polycyclic aromatic hydrocarbons (PAHs) pollutant are having in the northern coast of Hormuz Strait. The glucose and cholesterol levels were higher in fish from the St3 than in Walton's mudskipper from other stations however St3 samples had lowest total proteins levels. There was a significant positive correlation between glucose and cholesterol with PAHs concentrations in sediment and tissue samples (P<0.05). However, total proteins had adverse significant correlation with PAHs concentrations (P>0.05). The adverse correlation was seen between length and body weight of fish samples with PAHs concentrations. According to the results of this study, the monitoring of contaminants bioaccumulation in the northern part of Hormuz Strait is necessary, because this will give an indication of the temporal and spatial extent of the process, as well as an assessment of the potential impact on aquatic organisms health.

Keywords: PAHs, blood metabolic factors, Periophthalmus waltoni, Hormuz Strait

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Authors: Annabelle Onyefulu-Kingston

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One of the major purposes of AI today is to evaluate and analyze millions of micro and macro data in order to determine what is relevant in a particular case and proffer it in an adequate manner. Microdata, as far as it relates to AI in international arbitration, is the millions of key issues specifically mentioned by either one or both parties or by their counsels, arbitrators, or arbitral tribunals in arbitral proceedings. This can be qualifications of expert witness and admissibility of evidence, amongst others. Macro data, on the other hand, refers to data derived from the resolution of the dispute and, consequently, the final and binding award. A notable example of this includes the rationale of the award and specific and general damages awarded, amongst others. This paper aims to critically evaluate and analyze the possibility of technological inclusion in international arbitration. This research will be imploring the qualitative method by evaluating existing literature on the consequence of applying AI to both micro and macro data in international arbitration, and how this can be of assistance to parties, counsels, and arbitrators.

Keywords: AI-based technologies, algorithms, arbitrators, international arbitration

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Authors: Igor Izosimov

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This work is devoted to applications of the Time-resolved laser-induced luminescence (TRLIF) spectroscopy and time-resolved laser-induced chemiluminescence spectroscopy for detection of lanthanides and actinides. Results of the experiments on Eu, Sm, U, and Pu detection in solutions are presented. The limit of uranyl detection (LOD) in urine in our TRLIF experiments was up to 5 pg/ml. In blood plasma LOD was 0.1 ng/ml and after mineralization was up to 8pg/ml – 10pg/ml. In pure solution, the limit of detection of europium was 0.005ng/ml and samarium, 0.07ng/ml. After addition urine, the limit of detection of europium was 0.015 ng/ml and samarium, 0.2 ng/ml. Pu, Np, and some U compounds do not produce direct luminescence in solutions, but when excited by laser radiation, they can induce chemiluminescence of some chemiluminogen (luminol in our experiments). It is shown that multi-photon scheme of chemiluminescence excitation makes chemiluminescence not only a highly sensitive but also a highly selective tool for the detection of lanthanides/actinides in solutions.

Keywords: actinides/lanthanides detection, laser spectroscopy with time resolution, luminescence/chemiluminescence, solutions

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Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

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Authors: Khusboo Agrawal, S. Saraf

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Quercetin, a flavonol provides a cellular protection against UV induced oxidative damages due to its excellent free radical scavenging activity and direct pro-apoptopic effect on tumor cells. However, its topical use is limited due to its unfavorable physicochemical properties. The present study was aimed to evaluate the potential of mesoporous silica nanoparticles as topical carrier system for quercetin delivery. Complexes of quercetin with mesoporous silica was prepared with different weight ratios and characterized by thermo gravimetric analysis, X-ray diffraction, high resolution TEM, FT-IR spectroscopy, zeta potential measurements and differential scanning calorimetry The protective effect of this vehicle on UV-induced degradation of the quercetin was investigated revealing a certain positive influence of the inclusion on the photostability over time. Epidermal accumulation and transdermal permeation of this molecule were ex vivo evaluated by using Franz diffusion cells. The immobilization of Quercetin in mesoporous silica nanoparticles (MSNs) increased the stability without undermining the antioxidant efficacy.

Keywords: cancer, MSNs, quercetin, topical delivery

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Authors: Seyed Mahdi Rafiaei

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In this investigation, red emitting Eu³⁺ doped YVO₄ nano-phosphors have been synthesized via the facile combustion method using isobutyl nitrite and urea fuels, individually. Field-emission scanning electron microscope (FE-SEM) images, high resolution transmission electron microscope (TEM) images and X-ray diffraction (XRD) spectra reveal that the mentioned fuels can be used successfully to synthesis YVO₄: Eu³⁺ nano-particles. Interestingly, the fuels have a large effect on the size and morphology of nano-phosphors as well as luminescence properties. Noteworthy the use of isobutyl nitrite provides an average particle size of 65 nm, while the employment of urea, results in the formation of larger particles and also provides higher photoluminescence emission intensity. The improved luminescence performance is attributed to the condition of chemical reaction via the combustion synthesis and the size of synthesized phosphors.

Keywords: phosphors, combustion, fuels, luminescence, nanostructure

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Authors: Sachin Jain, Daniel Perez-Astudillo, Dunia A. Bachour, Antonio P. Sanfilippo

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The future of solar energy in Qatar is evolving steadily. Hence, high-quality spatial solar radiation data is of the uttermost requirement for any planning and commissioning of solar technology. Generally, two types of solar radiation data are available: satellite data and ground observations. Satellite solar radiation data is developed by the physical and statistical model. Ground data is collected by solar radiation measurement stations. The ground data is of high quality. However, they are limited to distributed point locations with the high cost of installation and maintenance for the ground stations. On the other hand, satellite solar radiation data is continuous and available throughout geographical locations, but they are relatively less accurate than ground data. To utilize the advantage of both data, a product has been developed here which provides spatial continuity and higher accuracy than any of the data alone. The popular satellite databases: National Solar radiation Data Base, NSRDB (PSM V3 model, spatial resolution: 4 km) is chosen here for merging with ground-measured solar radiation measurement in Qatar. The spatial distribution of ground solar radiation measurement stations is comprehensive in Qatar, with a network of 13 ground stations. The monthly average of the daily total Global Horizontal Irradiation (GHI) component from ground and satellite data is used for error analysis. The normalized root means square error (NRMSE) values of 3.31%, 6.53%, and 6.63% for October, November, and December 2019 were observed respectively when comparing in-situ and NSRDB data. The method is based on the Empirical Bayesian Kriging Regression Prediction model available in ArcGIS, ESRI. The workflow of the algorithm is based on the combination of regression and kriging methods. A regression model (OLS, ordinary least square) is fitted between the ground and NSBRD data points. A semi-variogram is fitted into the experimental semi-variogram obtained from the residuals. The kriging residuals obtained after fitting the semi-variogram model were added to NSRBD data predicted values obtained from the regression model to obtain the final predicted values. The NRMSE values obtained after merging are respectively 1.84%, 1.28%, and 1.81% for October, November, and December 2019. One more explanatory variable, that is the ground elevation, has been incorporated in the regression and kriging methods to reduce the error and to provide higher spatial resolution (30 m). The final GHI maps have been created after merging, and NRMSE values of 1.24%, 1.28%, and 1.28% have been observed for October, November, and December 2019, respectively. The proposed merging method has proven as a highly accurate method. An additional method is also proposed here to generate calibrated maps by using regression and kriging model and further to use the calibrated model to generate solar radiation maps from the explanatory variable only when not enough historical ground data is available for long-term analysis. The NRMSE values obtained after the comparison of the calibrated maps with ground data are 5.60% and 5.31% for November and December 2019 month respectively.

Keywords: global horizontal irradiation, GIS, empirical bayesian kriging regression prediction, NSRDB

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from McRae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-worls, resilience to damage

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Authors: M. Arabghahestani, A. Darwish Ahmad, N. K. Akafuah

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In this work, small-scale experiments of fire whirl were conducted to study the spinning fire phenomenon and to gain comprehensive understandings of fire tornadoes and the factors that affect their behavior. High speed imaging was used to track the flames at both temporal and spatial scales. This allowed us to better understand the role of the near-ground height in creating a boundary layer flow profile that, in turn contributes to formation of vortices around the fire, and consequent fire whirls. Based on the results obtained from these observations, we were able to spot the differences in the fuel burning rate of the fire itself as a function of a newly defined specific non-dimensional near-ground height. Based on our observations, there is a cutoff non-dimensional height, beyond which a normal fire can be turned into a fire whirl. Additionally, the results showed that the fire burning rate decreases by moving the fire to a height higher than the ground level. These effects were justified by the interactions between vortices formed by, the back pressure and the boundary layer velocity profile, and the vortices generated by the fire itself.

Keywords: boundary layer profile, fire whirls, near-ground height, vortex interactions

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Authors: Thusitha B. Abeysekara, M. A. Nihal Chandrathilake

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The aim of this research is to examine the legal mechanism of resolving maritime disputes by arbitration, and it would be a reference point on the analysis of USA approaches. In doing so, the research aims to analyse the relevant legal principles in the context of current maritime arbitration practices in selected jurisdictions. The research also aims to analyse the advantages and applicability of arbitration in maritime dispute settlements over the litigation and further approaches the role of specialist maritime arbitration institutes in the USA and the position of international merchant organizations in maritime arbitration. Further, research values the legislative aspects of maritime arbitration. The study would evaluate the contemporary issues in maritime arbitration practices in the USA and further analyses the statistical information on maritime arbitration. Finally, the research made remarks to often parallel consequence in USA legal systems in maritime arbitration and despite the fundamental divergences of the applicable principles and practices of maritime arbitration. The research finally suggests the doctrine should reshape with equitable remedies and international maritime arbitration practices with its institutional impact rather than using as statutory rules related maritime arbitration.

Keywords: arbitration, international shipping, maritime dispute, New York convention

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Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

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FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

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Authors: Ahmed Nour El Islam Ayad, Wafa Krika, Abdelghani Ayad, Moulay Larab, Houari Boudjella, Farid Benhamida

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The purpose of this study is to evaluate the magnetic emission of underground electric cable of high voltage, because these power lines generate electromagnetic interaction with other objects near to it. The aim of this work shows a numerical simulation of the magnetic field of buried 400 kV line in three cases: permanent and transient states of short circuit and the last case with the presence of the harmonics at different positions as a function of time variation, with finite element resolution using Comsol Multiphysics software. The results obtained showed that the amplitude and distribution of the magnetic flux density change in the transient state and the presence of harmonics. The results of this work calculate the magnetic field generated by the underground lines in order to evaluate and know their impact on ecology and health.

Keywords: underground, electric power cables, cables crossing, harmonic, emission

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Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

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Authors: Kanchan Negi

Abstract:

Background: Modern work culture has driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and well-being (including happiness) in a sample of working women. Method: Primary data of 360 currently married women working in the education, health, banking and IT sector in Delhi, India, were analysed. Logistic regression was used to estimate physical and psychological well-being and happiness across work characteristics. Results: Relative to 35–40 hours/week, working longer related to poor well-being (ß=0.75, 95% CI 0.12 to 1.39). Compared with not working weekends, working most or all weekends is related to poor physical (ß=0.34, 95% CI 0.08 to 0.61) and psychological well-being (ß=0.50, 95% CI 0.20 to 0.79). Rigid work patterns (ß=0.17, 95% CI −0.09 to 0.42) are also related to poor well-being. Conclusion: Decreased well-being and unhappiness are significantly linked to strenuous and rigid work patterns, suggesting that modern work culture may contribute to poor well-being. Flexible timings, compensatory holidays, work-from-home, and daycare facilities for young ones must be welcomed by companies to ease the dual burden of homemakers and career makers.

Keywords: happiness, well-being, work pattern, working women

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Authors: Abdulazeez Balogun Shittu

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This study investigates the role of self-overestimation and underestimation of others in fueling religious conflicts in Nigeria. Using a mixed-methods approach, this research examines how exaggerated self-perceptions and diminished views of others contribute to intergroup tensions, stereotypes, and violence. The findings reveal that self-overestimation and underestimation of others are significant predictors of religious conflict, mediated by factors such as intergroup bias, social identity, cultural narratives and lack of interfaith dialogue. The study also identifies the consequences of these biases, including Escalated sectarian violence, social cohesion erosion and polarized communities. To mitigate these effects, the research recommends interfaith education and dialogue initiatives, inclusive governance and policy frameworks and pluralistic media representation. This study contributes to the understanding of psychological and social dynamics driving religious conflict in Nigeria, informing evidence-based policies and interventions to promote peaceful coexistence.

Keywords: conflict resolution, intergroup relations, Nigeria, Religious conflict, self-overestimation, social psychology, underestimation of others

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Riyadh Alsultani, Ali Majdi

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It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

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Authors: Reshma Raskar-Phule, Makarand Landge, Saurabh Singh, Vijay Singh, Jash Saparia, Shivam Tripathi

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For any construction project, slope calculations are necessary in order to evaluate constructability on the site, such as the slope of parking lots, sidewalks, and ramps, the slope of sanitary sewer lines, slope of roads and highways. When slopes and grades are to be determined, designers are concerned with establishing proper slopes and grades for their projects to assess cut and fill volume calculations and determine inverts of pipes. There are several established instruments commonly used to determine slopes, such as Dumpy level, Abney level or Hand Level, Inclinometer, Tacheometer, Henry method, etc., and surveyors are very familiar with the use of these instruments to calculate slopes. However, they have some other drawbacks which cannot be neglected while major surveying works. Firstly, it requires expert surveyors and skilled staff. The accessibility, visibility, and accommodation to remote hilly terrain with these instruments and surveying teams are difficult. Also, determination of gentle slopes in case of road and sewer drainage constructions in congested urban places with these instruments is not easy. This paper aims to develop a method that requires minimum field work, minimum instruments, no high-end technology or instruments or software, and low cost. It requires basic and handy surveying accessories like a plane table with a fixed weighing machine, standard weights, alidade, tripod, and ranging rods should be able to determine the terrain slope in congested areas as well as in remote hilly terrain. Also, being simple and easy to understand and perform the people of that local rural area can be easily trained for the proposed method. The idea for the proposed method is based on the principle of resolution of weight components. When any object of standard weight ‘W’ is placed on an inclined surface with a weighing machine below it, then its cosine component of weight is presently measured by that weighing machine. The slope can be determined from the relation between the true or actual weight and the apparent weight. A proper procedure is to be followed, which includes site location, centering and sighting work, fixing the whole set at the identified station, and finally taking the readings. A set of experiments for slope determination, mild and moderate slopes, are carried out by the proposed method and by the theodolite instrument in a controlled environment, on the college campus, and uncontrolled environment actual site. The slopes determined by the proposed method were compared with those determined by the established instruments. For example, it was observed that for the same distances for mild slope, the difference in the slope obtained by the proposed method and by the established method ranges from 4’ for a distance of 8m to 2o15’20” for a distance of 16m for an uncontrolled environment. Thus, for mild slopes, the proposed method is suitable for a distance of 8m to 10m. The correlation between the proposed method and the established method shows a good correlation of 0.91 to 0.99 for various combinations, mild and moderate slope, with the controlled and uncontrolled environment.

Keywords: surveying, plane table, weight component, slope determination, hilly terrain, construction

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Authors: Huiwu Yu, Xiangyou Li, Xiaoyan Zeng

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Porous spheres have been widely used in many fields due to their attractive features. In this work, an approach for fabricating porous spheres of nanoparticles was presented, in which the nanoparticles were welded together to form micro spheres by simply irradiating the nanoparticles in liquid medium by a picosecond laser. As an example, anatase titanium dioxide was chosen as a typical material on account of its metastability. The structure and morphologies of the products were characterised by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman, and high-resolution transmission electron microscopy (HRTEM), respectively. The results showed that, anatase titanium dioxide micro spheres (2-10 μm) with macroporous (10-100 nm) were prepared from nano-anatase titanium dioxide nanoparticles (10-100 nm). The formation process of polycrystalline anatase titanium dioxide microspheres was investigated with different liquid mediums and the input laser fluences. Thus, this facile laser irradiation approach might provide a way for the fabrication of porous microspheres without phase-transition.

Keywords: titanium dioxide, porous microspheres, picosecond laser, nano-welding

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Authors: Nawaf Alotaibi, Andy Evans, Alison Heppenstall, Nick Malleson

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Throughout the last two decades, motor vehicle theft (MVT) has accounted for the largest proportion of property crime incidents in Saudi Arabia (SA). However, to date, few studies have investigated SA’s MVT problem. Those that have are primarily focused on the characteristics of car thieves, and most have overlooked any spatial-temporal distribution of MVT incidents and the characteristics of victims. This paper represents the first step in understanding this problem by reviewing the existing MVT studies contextualised within the theoretical frameworks developed in environmental criminology theories – originating in the West – and exploring to what extent they are relevant to the SA context. To achieve this, the paper has identified a range of key features in SA that are different from typical Western contexts, that could limit the appropriateness and capability of applying existing environmental criminology theories. Furthermore, despite these Western studies reviewed so far having introduced a number of explanatory variables for MVT rates, a range of significant elements are apparently absent in the current literature and this requires further analysis. For example, almost no attempts have been made to quantify the associations between the locations of vehicle theft, recovery of stolen vehicles, joyriding and traffic volume.

Keywords: environmental criminology theories, motor vehicle theft, Saudi Arabia, spatial analysis

Procedia PDF Downloads 298