Search results for: multilayer dyadic Green’s function

Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Avan Al-Saffar, Eun-Jin Kim

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Both the logistic growth model and the gompertz growth model are used to describe growth processes. Both models driven by perturbations in different cases are investigated using information theory as a useful measure of sustainability and the variability. Specifically, we study the effect of different oscillatory modulations in the system's parameters on the evolution of the system and Probability Density Function (PDF). We show the maintenance of the initial conditions for a long time. We offer Fisher information analysis in positive and/or negative feedback and explain its implications for the sustainability of population dynamics. We also display a finite amplitude solution due to the purely fluctuating growth rate whereas the periodic fluctuations in negative feedback can lead to break down the system's self-regulation with an exponentially growing solution. In the cases tested, the gompertz and logistic systems show similar behaviour in terms of information and sustainability although they develop differently in time.

Keywords: dynamical systems, fisher information, probability density function (pdf), sustainability

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Authors: Kunpeng Wang, Hongchun, Wu, Liangzhi Cao, Chuanqi Zhao

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The distributions of homogeneous neutron flux within a node were expanded into a set of analytic basis functions which satisfy the diffusion equation at any point in a triangular-z node for each energy group, and nodes were coupled with each other with both the zero- and first-order partial neutron current moments across all the interfaces of the triangular prism at the same time. Based this method, a code TABFEN has been developed and applied to solve the neutron diffusion equation in a complicated geometry. In addition, after a series of numerical derivation, one can get the neutron adjoint diffusion equations in matrix form which is the same with the neutron diffusion equation; therefore, it can be solved by TABFEN, and the low-high scan strategy is adopted to improve the efficiency. Four benchmark problems are tested by this method to verify its feasibility, the results show good agreement with the references which demonstrates the efficiency and feasibility of this method.

Keywords: analytic basis function expansion method, arbitrary triangular-z node, adjoint neutron flux, complicated geometry

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Authors: A. Alli-Oluwafuyi, A. Amin, S. M. Fii, S. O. Amusa, A. Imam, N. T. Asogwa, W. I. Abdulmajeed, F. Olaseinde, B. V. Owoyele

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Chronic stress or prolonged glucocorticoid administration impairs higher cognitive functions in rodents and humans. However, the mechanisms are not fully clear. Insulin and receptors are expressed in the brain and are involved in cognition. Insulin resistance accompanies Alzheimer’s disease and associated cognitive decline. The goal of this study was to evaluate the effects of sub-chronic administration of a glucocorticoid, dexamethasone (DEX) on behavior and biochemical changes in prefrontal cortex (PFC). Male Wistar rats were administered DEX (2, 4 & 8 mg/kg, IP) or saline for seven consecutive days and behavior was assessed in the following paradigms: “Y” maze, elevated plus maze, Morris’ water maze and novel object recognition (NOR) tests. Insulin, lactate dehydrogenase (LDH) and Superoxide Dismutase (SOD) activity were evaluated in homogenates of the prefrontal cortex. DEX-treated rats exhibited impaired prefrontal cortex function manifesting as reduced locomotion, impaired novel object exploration and impaired short- and long-term spatial memory compared to normal controls (p < 0.05). These effects were not consistently dose-dependent. These behavioral alterations were accompanied by a decrease in insulin concentration observed in PFC of 4 mg/kg DEX-treated rats compared to control (10μIU/mg vs. 50μIU/mg; p < 0.05) but not 2mg/kg. Furthermore, we report a modification of brain stress markers LDH and SOD (p > 0.05). These results indicate that prolonged activation of GCs disrupt prefrontal cortex function which may be related to insulin impairment. These effects may not be attributable to a non-specific elevation of oxidative stress in the brain. Future studies would evaluate mechanisms of GR-induced insulin loss.

Keywords: dexamethasone, insulin, memory, prefrontal cortex

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

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Authors: Lela Gadrani, Mariam Tsitsagi

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Human is a part of the urban landscape and responsible for it. Urbanization of cities includes the longest phase; thus none of the environment ever undergoes such anthropogenic impact as the area of large cities. The post-Soviet period is very interesting in terms of scientific research. The changes that have occurred in the cities since the collapse of the Soviet Union have not yet been analyzed best to our knowledge. In this context, the aim of this paper is to analyze the changes in the land use of the three large cities of Georgia (Tbilisi, Kutaisi, Batumi). Tbilisi as a capital city, Batumi as a port city, and Kutaisi as a former industrial center. Data used during the research process are conventionally divided into satellite and supporting materials. For this purpose, the largest topographic maps (1:10 000) of all three cities were analyzed, Tbilisi General Plans (1896, 1924), Tbilisi and Kutaisi historical maps. The main emphasis was placed on the classification of Landsat images. In this case, we have classified the images LULC (LandUse / LandCover) of all three cities taken in 1987 and 2016 using the supervised and unsupervised methods. All the procedures were performed in the programs: Arc GIS 10.3.1 and ENVI 5.0. In each classification we have singled out the following classes: built-up area, water bodies, agricultural lands, green cover and bare soil, and calculated the areas occupied by them. In order to check the validity of the obtained results, additionally we used the higher resolution images of CORONA and Sentinel. Ultimately we identified the changes that took place in the land use in the post-Soviet period in the above cities. According to the results, a large wave of changes touched Tbilisi and Batumi, though in different periods. It turned out that in the case of Tbilisi, the area of developed territory has increased by 13.9% compared to the 1987 data, which is certainly happening at the expense of agricultural land and green cover, in particular, the area of agricultural lands has decreased by 4.97%; and the green cover by 5.67%. It should be noted that Batumi has obviously overtaken the country's capital in terms of development. With the unaided eye it is clear that in comparison with other regions of Georgia, everything is different in Batumi. In fact, Batumi is an unofficial summer capital of Georgia. Undoubtedly, Batumi’s development is very important both in economic and social terms. However, there is a danger that in the uneven conditions of urban development, we will eventually get a developed center - Batumi, and multiple underdeveloped peripheries around it. Analysis of the changes in the land use is of utmost importance not only for quantitative evaluation of the changes already implemented, but for future modeling and prognosis of urban development. Raster data containing the classes of land use is an integral part of the city's prognostic models.

Keywords: analysis, geo information system, remote sensing, LULC

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Authors: Filimonova Alexanra

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Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.

Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.

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Authors: Oh Hyeon Jeon, WooYoung Jung

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In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.

Keywords: weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo simulation, permeability coefficient

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Authors: A. Movaghar, R. A. Mahdavinejad

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To analyze the effect of various parameters of fluid on the material properties such as surface and depth defects and/or cracks, it is possible to determine the affection of pressure field on these specifications. Stress tensor analysis is also able to determine the points in which the probability of defection creation is more. Besides, from pressure field, it is possible to analyze the affection of various fluid specifications such as viscosity and density on defect created in the material. In this research, the concerned boundary conditions are analyzed first. Then the solution network and stencil used are mentioned. With the determination of relevant equation on the fluid flow between notch and matrix and their discretion according to the governed boundary conditions, these equations can be solved. Finally, with the variation creations on fluid parameters such as density and viscosity, the affection of these variations can be determined on pressure field. In this direction, the flowchart and solution algorithm with their results as vortex and current function contours for two conditions with most applications in pressing process are introduced and discussed.

Keywords: pressing, notch, matrix, flow function, vortex

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Authors: Sabri Sudirman, Yuan-Hua Hsu, Zwe-Ling Kong

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Male reproductive dysfunction is predominantly due to insulin resistance and hyperglycemia result in inflammation and oxidative stress. Furthermore, nanotechnology provides an alternative approach to improve the bioavailability of natural active food ingredients. Therefore, the aim of this study were to investigate nanoencapsulated triterpenoids from petri-dish cultured Antrodia cinnamomea (PAC) nanoparticles whether it could increase the bioavailability; in addition, the anti-inflammatory and anti-oxidative effects could more effectively ameliorate the reproductive function of diabetic male rats. First, PAC encapsulated in chitosan-silica nanoparticles (Nano-PAC) were prepared by biosilicification method. Scanning electron micrographs confirm the average particle size is about 30 nm, and the encapsulation efficiency is 83.7% by HPLC. Diabetic male Sprague-Dawley rats were induced by high fat diet (40% kcal from fat) and streptozotocin (35 mg/kg). Nano-PAC was administered by oral gavage in three doses (4, 8 and 20 mg/kg) for 6 weeks. Besides, metformin (300 mg/kg) and nanoparticles (Nano) were treated as the positive and negative control respectively. Results indicated that 4 mg/kg Nano-PAC administration for 6 weeks improved hyperglycemia, insulin resistance, and also reduced advanced glycation end products in plasma. In addition, 8 mg/kg Nano-PAC ameliorated morphological of testicular seminiferous tubules, sperm morphology and motility, reactive oxygen species production and mitochondrial membrane potential. Moreover, 20 mg/kg Nano-PAC restored reproductive endocrine system function and increased KiSS-1 level in plasma. In plasma or testis anti-oxidant superoxide dismutase, glutathione peroxidase and catalase were increased whereas malondialdehyde, as well as pro-inflammatory cytokines tumor necrosis factor-α, interleukin-6, and interferon-gamma, decreased. Most importantly, 8 mg/kg Nano-PAC down-regulated the oxidative stress induced c-Jun N-terminal kinase (JNK) signaling pathway. Our study successfully nanoencapsulated PAC to form nanoparticles and low-dose Nano-PAC improved diabetes-induced hyperglycemia, inflammation and oxidative stress to ameliorate the reproductive function of diabetic male rats.

Keywords: Antrodia cinnamomea, diabetes mellitus, male reproduction, nanoparticles

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Authors: Haiping Zhu

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The purpose of this work-in-progress paper is to explore how the Chinese philosophic-religious tradition of Taoism impacts on the consumption behaviour of contemporary Chinese consumers. Although much cultural research has been conducted on Chinese consumption behaviours, most studies have approached the subject from Western perspectives. Examination of the limited literature indicates a gap in the knowledge of the relationship of traditional Chinese Taoism philosophy and Chinese consumption behaviour. To bridge this gap, this study examines Chinese consumption behaviour at a Taoist-related Chinese religious festival - the DuanWu festival - in order to seek some understanding of how the Taoism philosophic-religious tradition influences Chinese consumption behaviour from the point of view of the individuals involved. It focuses attention on their expression of Taoism cultural values, purchasing experience and subsequent consumption behaviours. This study undertook multiple methods for Taoist case study data collection: accompanied shopping with Taoists before DuanWu Festival; participant observations during DuanWu Festival; and in-depth interviews in order to explore Taoists consumption behaviours at the end of the Festival. Specifically, the finding from the Taoist case study corroborates and details the influence of the Taoism doctrine: man–nature orientation, Fenshui, ecological effect, and ecological knowledge, on their attitudes toward green purchasing behaviour. Findings from this Taoist case study - one of a series of three Chinese philosophic religious tradition case studies - contribute to the deeper understanding of contemporary Chinese consumers from a non-Western viewpoint and offer initial insights for global marketers to differentiate consumer needs and develop effective marketing strategies.

Keywords: consumer behaviour, culture values, green purchase behaviour, Taoism

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

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Authors: Seyed Reza Mirdehghan, Mohammad Reza Haeri Yazdi

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In this paper, the stability and the performance of a two-degree-of-freedom robot under an interaction with a unknown environment has been investigated. The time when the robot returns to its initial position after an interaction and the primary resistance of the robot against the impact must be reduced. Thus, the applied torque on the motor will be reduced. The impedance control is an appropriate method for robot control in these conditions. The stability of the robot at interaction moment was transformed to be a robust stability problem. The dynamic of the unknown environment was modeled as a weight function and the stability of the robot under an interaction with the environment has been investigated using the robust control concept. To improve the performance of the system, a force controller has been designed which the normalized impedance after interaction has been reduced. The resistance of the robot has been considered as a normalized cost function and its value was 0.593. The results has showed reduction of resistance of the robot against impact and the reduction of convergence time by lower than one second.

Keywords: impedance control, control system, robots, interaction

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Authors: Magdy Abouzeid, Nancy Abouzeid, Afaf Salem

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Background: The elite child athletes are one who has superior athletic talent. Monofin (a single surface swim fin) swimming already proved to be the most efficient method of swimming for human being. This is a novel descriptive study examining myocardial function indices in prepubertal monofin children. The aim of the present study was to determine the influence of long-term monofin training (LTMT), 36 weeks, 6 times per week, 90 min per unit on Myocardial function adaptation in elite child monofin athletes. Methods: 14 elite monofin children aged 11.95 years (± 1.09 yr) took part for (LTMT). All subjects underwent two-dimension, M-mode, and Doppler echocardiography before and after training to evaluate cardiac dimensions and function; septal and posterior wall thickness. Statistical methods of SPSS, means ± SD and paired t test, % of improvement were used. Findings: There was significant difference (p<0.01) and % improvement for all echocardiography parameter after (LTMT). Inter ventricular septal thickness in diastole and in systole increased by 27.9 % and 42.75 %. Left ventricular end systolic dimension and diastole increased by 16.81 % and 42.7 % respectively. Posterior wall thickness in systole very highly increased by 283.3 % and in diastole increased by 51.78 %. Left ventricular mass in diastole and in systole increased by 44.8 % and 40.1 % respectively. Stroke volume (SV) and resting heart rate (HR) significant changed (sv) 25 %, (HR) 14.7 %. Interpretation: the unique swim fin tool and create propulsion and overcome resistance. Further researches are needed to determine the effects of monofin training on right ventricular in child athletes.

Keywords: prepubertal, monofin training, heart athlete's, elite child athlete, echocardiography

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Authors: Ju-Hong Lee, Ding-Chen Chung

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This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: Nkem Angela Udeani

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Despite the widespread use of synthetic dyes, natural dyes are still exploited and used to enhance its inherent aesthetic qualities as a major material for the beautification of the body. Centuries before the discovery of synthetic dye, natural dyes were the only source of dye open to mankind. Dyes are extracted from plant - leaves, roots, and barks, insect secretions, and minerals. However, research findings have made it clear that of all, plant- leaves, roots, barks or flowers are the most explored and exploited. Henna (Lawsonia innermis) is one of those plants. The experiment has also shown that henna is used in body painting in conjunction with an alkaline (Ammonium Sulphate) as a fixing agent. This of course gives a clue that if colour derived from henna is properly investigated, it may not only be used as body decoration but possibly, may have affinity to fibre substrate. This paper investigates the dyeing potentials - dyeing ability and fastness qualities of henna dye extract on cotton and linen fibres using mordants like ammonium sulphate and other alkalies (hydrosulphate and caustic soda, potash, common salt and alum). Hot and cold water and ethanol solvent were used in the extraction of the dye to investigate the most effective method of extraction, dyeing ability and fastness qualities of these extracts under room temperature. The results of the experiment show that cotton have a high rate of dye intake than linen fibre. On a similar note, the colours obtained depend most on the solvent and or the mordant used. In conclusion, hot water extraction appear more effective. While the colours obtained from ethanol and both cold and hot method of extraction range from light to dark yellow, light green to army green, there are to some extent shades of brown hues.

Keywords: dye, fabrics, henna leaves, potential

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Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

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Authors: Gabriel I. Loaiza Ossa, Carlos A. Cadavid Moreno, Juan C. Arango Parra

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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ= -1/2, as does the family of usual Gaussian distributions. In the present paper, firstly, we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ₁, θ₂; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the inverse q-Gaussian distribution family (q < 3) as the family obtained by replacing the usual exponential function with the Tsallis q-exponential function in the expression for the inverse Gaussian distribution and observe that it supports two possible geometries, the Fisher and the q-Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q-Fisher geometry of the inverse q-Gaussian distribution family, similar to the ones obtained in the case of the inverse Gaussian distribution family.

Keywords: base of changes, information geometry, inverse Gaussian distribution, inverse q-Gaussian distribution, statistical manifolds

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Authors: Sharmin Ferdewsi Rakhi, A. H. M. Mohsinul Reza, Brynley Davies, Jianzhong Wang, Youhong Tang, Jian Qin

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Mass production of microalgae has become a focus of research owing to their promising aspects for sustainable food, biofunctional compounds, and biofuel feedstock. However, low lipid content with optimum algal biomass is still a challenge that must be resolved for commercial use. This research aims to determine the effects of light spectral shift and reactive oxygen species (ROS) on growth and lipid biosynthesis in a green microalga, Chlamydomonas reinhardtii. Aggregation Induced Emission (AIE)-based photosensitisers, CN-TPAQ-PF6 ([C₃₂H₂₃N₄]+) with high ROS productivity, was introduced into the algal culture media separately for effective conversion of the green-yellow-light to the red spectra. The intense photon energy and high-photon flux density in the photosystems and ROS supplementation induced photosynthesis and lipid biogenesis. In comparison to the control, maximum algal growth (0.15 g/l) was achieved at 2 µM CN-TPAQ-PF6 exposure. A significant increase in total lipid accumulation (146.87 mg/g dry biomass) with high proportion of 10-Heptadecanoic acid (C17:1) linolenic acid (C18:2), α-linolenic acid (C18:3) was observed. The elevated level of cellular NADP/NADPH triggered the Acetyl-Co-A production in lipid biogenesis cascade. Furthermore, MTT analysis suggested that this nanomaterial is highly biocompatible on HaCat cell lines with 100% cell viability. This study reveals that the AIE-based approach can strongly impact algal biofactory development for sustainable food, healthy lipids and eco-friendly biofuel.

Keywords: microalgae, photosensitiser, lipid, biomass, aggregation-induced-emission, reactive oxygen species

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Authors: Kiara Lawrence, Nadine Ponnusamy, Clive Greenstone

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One of the major challenges facing society today is food security. The risks to food security have increased significantly due to the evolving urban landscape, globalization, and a rising population. The cultivation of food is essential, particularly during times of crisis, such as a recession, and has long been a necessity for urban populations. In contemporary society, many urban residents are confronted with new challenges, including high levels of unemployment, which compel individuals to adopt alternative survival strategies, such as growing their own food. Recently, rooftop agriculture has made significant contributions to urban and national food security and has been utilized as a tool to mitigate the frequent and damaging disasters that many cities encounter. They have the potential to transform unused spaces into green, productive vegetable plots, while also providing urban residents with the opportunity to enjoy the benefits of gardening. Therefore, this study looks to investigate the evolving themes around rooftop agriculture and food security globally. A bibliometric review analysis was carried out on Scopus and Web of Science using the keywords “rooftop agriculture” OR “rooftop farming” OR “rooftop garden” AND “food security” between 2004 and 2024 to ensure a broader scope was covered around the chosen study. Vosviewer software was then utilized to analyze the extracted data to create network visualization maps based on keyword occurrences, co-author analysis, country analysis. There were only 37 relevant documents within the study parameters. Preliminary results indicate that much research focused on urban agriculture, food supply, green roof, sustainability and climate change. By analysing these aspects of rooftop agriculture and food security, the trends can identify gaps in literature and dictate future applications to assist in food security.

Keywords: food security, rooftop agriculture, rooftop farming, rooftop garden

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Chien-Chun Huang, P. W. Yuan

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Banana is one of the important fruits which constitute a valuable source of energy, vitamins and minerals and an important food component throughout the world. The fruit ripening and maturity standards vary from country to country depending on the expected shelf life of market. During ripening there are changes in appearance, texture and chemical composition of banana. The changes of component of banana during ethylene-induced ripening are categorized as nutritive values and commercial utilization. The objectives of this study were to investigate the changes of chemical composition and physicochemical properties of banana during ethylene-induced ripening. Green bananas were harvested and ripened by ethylene gas at low temperature (15℃) for seven stages. At each stage, banana was sliced and freeze-dried for banana flour preparation. The changes of total starch, resistant starch, chemical compositions, physicochemical properties, activity of amylase, polyphenolic oxidase (PPO) and phenylalanine ammonia lyase (PAL) of banana were analyzed each stage during ripening. The banana starch was isolated and analyzed for gelatinization properties, pasting properties and microscopic appearance each stage of ripening. The results indicated that the highest total starch and resistant starch content of green banana were 76.2% and 34.6%, respectively at the harvest stage. Both total starch and resistant starch content were significantly declined to 25.3% and 8.8%, respectively at the seventh stage. Soluble sugars content of banana increased from 1.21% at harvest stage to 37.72% at seventh stage during ethylene-induced ripening. Swelling power of banana flour decreased with the progress of ripening stage, but solubility increased. These results strongly related with the decreases of starch content of banana flour during ethylene-induced ripening. Both water insoluble and alcohol insoluble solids of banana flour decreased with the progress of ripening stage. Both activity of PPO and PAL increased, but the total free phenolics content decreased, with the increases of ripening stages. As ripening stage extended, the gelatinization enthalpy of banana starch significantly decreased from 15.31 J/g at the harvest stage to 10.55 J/g at the seventh stage. The peak viscosity and setback increased with the progress of ripening stages in the pasting properties of banana starch. The highest final viscosity, 5701 RVU, of banana starch slurry was found at the seventh stage. The scanning electron micrograph of banana starch showed the shapes of banana starch appeared to be round and elongated forms, ranging in 10-50 μm at the harvest stage. As the banana closed to ripe status, some parallel striations were observed on the surface of banana starch granular which could be caused by enzyme reaction during ripening. These results inferred that the highest resistant starch was found in the green banana could be considered as a potential application of healthy foods. The changes of chemical composition and physicochemical properties of banana could be caused by the hydrolysis of enzymes during the ethylene-induced ripening treatment.

Keywords: maturation of banana, appearance, texture, soluble sugars, resistant starch, enzyme activities, physicochemical properties of banana starch

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Authors: Andrea Dragu, Solen Kinayyigit, Valerie Colliere, Karin Karin Philippot, Camelia Bala, Vasile I. Parvulescu

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The production of transportation fuels from biomass has gained a growing attention due to diminishing fossil fuel reserves, rising petroleum prices and increasing concern about global warming. In recent years, renewable hydrocarbons that are completely fungible with fossil fuels have been suggested to be efficiently produced by catalytic deoxygenation of fatty acids and their derivatives viadecarboxylation / decarbonylation. Several triglycerides (tall oil fatty acids) and saturated/unsaturated fatty acids and their corresponding esters were used as feedstocks. Their impact together with the influence of the reaction conditions and the catalyst composition on the nature of the reaction pathways of the deoxygenation of vegetable oils and their derivatives were recently reviewed. Following this state of the art the aim of the present study was the investigation of Pd NPs deposited onto mesoporous carbon supports as active and stable catalysts for the deoxygenation of oleic acid. The catalysts were prepared by the deposition of Pd NPs synthesised following an organometallic route on mesoporous carbons with different characteristics. Experiments were carried out under both batch and flow conditions. They demonstrated that under batch conditions (200 atm; 573K), the extent of the reaction depended, firstly, on the Pd loading and then on the metal dispersion and the oxidation state of palladium, both influenced by the way the support has been treated before the NPs deposition and by the preparation/stabilization methodology of Pd NPs. No aromatic compounds were detected in the reaction products but octadecanol and octadecane were observed in large extents. Under flow conditions (4 atm; 573 K), the conversion of stearic acid was superior to that observed in batch conditions. The product mixture contained over 20% heptadecane. No octadecanol, octadecane, and aromatic compounds were detected. The maxima in performances are obtained after only 0.5 h. After that, the yields in heptadecane suffer from a severe decrease until 3h reaction time. However, at that time, stopping feeding the reactor with oleic acid and flushing the catalyst only with mesitylene recovered the activity and the selectivity of the catalysts. With the complete removal of H2, the analysis revealed the presence of heptadecene in high excess compared to heptadecane (almost 7 to 1), thus suggesting decarbonylation as the main route. ICP-OES measurements indicated no leaching of palladium and simple washing of catalysts with mesitylene allowed recycling without any change in conversion or product distribution. Noteworthy, mesitylene as solvent exhibited no effect in this reaction. In conclusion, this study demonstrates the feasibility of such catalysts for the green production of fuels from biomass.

Keywords: fuels from biomass, green catalyst, Pd nano-particles , recycble catalyst

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Authors: David Bywaters, Paweł Młodkowski

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The paper assesses the roles of resource growth and technology in development for Nigeria, India, and the UK and concludes by assessing the contribution of technological progress in the economic function of exchange on technological progress in the economic function of production. The evidence suggests for Nigeria, India, and the UK that increases in specialisation, as measured by the variable denoted exchtech in this paper, are the most statistically significant explanation of production technology, compared to education and capital per worker. This paper builds on theoretical work by the authors, which shows that reductions in resource use per transaction are a cause of economic growth, as well as increases in resource quantity and improvements in production technology using mathematical programming. That work is briefly reviewed and then extended to include the economic activities of consumption, from stock, production, and exchange to government, investing activities, financing activities, and exchange within and outside one economy to facilitate application to national accounts and other data.

Keywords: economic growth, Nigeria, transactions costs, Ronald Coase

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Authors: Gabriel Woldu, Maria Sassi

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Coffee performs a pivotal role in Ethiopia's GDP, revenue, employment, domestic demand, and export earnings. Ethiopia's coffee production and exports show high variability in the amount of production and export earnings. Despite being the continent's fifth-largest coffee producer, Ethiopia has not developed its ability to shine as a major exporter in the globe's green coffee exports. Ethiopian coffee exports were not stable and had high volume and earnings fluctuations. The main aim of this study was to analyze the dynamics of the export of coffee variation to different importing nations using a first-order Markov Chain model. 14 years of time-series data has been used to examine the direction and structural change in the export of coffee. A compound annual growth rate (CAGR) was used to determine the annual growth rate in the coffee export quantity, value, and per-unit price over the study period. The major export markets for Ethiopian coffee were Germany, Japan, and the USA, which were more stable, while countries such as France, Italy, Belgium, and Saudi Arabia were less stable and had low retention rates for Ethiopian coffee. The study, therefore, recommends that Ethiopia should again revitalize its market to France, Italy, Belgium, and Saudi Arabia, as these countries are the major coffee-consuming countries in the world to boost its export stake to the global coffee markets in the future. In order to further enhance export stability, the Ethiopian Government and other stakeholders in the coffee sector should have to work on reducing the volatility of coffee output and exports in order to improve production and quality efficiency, so that stabilize markets as well as to make the product attractive and price competitive in the importing countries.

Keywords: coffee, CAGR, Markov chain, direction of trade, Ethiopia

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Authors: Ocsana Opris, Ildiko Lung, Maria L. Soran, Alexandra Ciorita, Lucian Copolovici

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The effects assessment of environmental stress factors on both crop and wild plants of nutritional value are a very important research topic. Continuously worldwide consumption of drugs leads to significant environmental pollution, thus generating environmental stress. Understanding the effects of the important drugs on plant composition and ultrastructural modification is still limited, especially at environmentally relevant concentrations. The aim of the present work was to investigate the influence of three non-steroidal anti-inflammatory drugs (NSAIDs) on chlorophylls content, carotenoids content, total polyphenols content, antioxidant capacity, and ultrastructure of orache (Atriplex patula L.) and spinach (Spinacia oleracea L.). All green leafy vegetables selected for this study were grown in controlled conditions and treated with solutions of different concentrations (0.1‒1 mg L⁻¹) of diclofenac, ibuprofen, and naproxen. After eight weeks of exposure of the plants to NSAIDs, the chlorophylls and carotenoids content were analyzed by high-performance liquid chromatography coupled with photodiode array and mass spectrometer detectors, total polyphenols and antioxidant capacity by ultraviolet-visible spectroscopy. Also, the ultrastructural analyses of the vegetables were performed using transmission electron microscopy in order to assess the influence of the selected NSAIDs on cellular organisms, mainly photosynthetic organisms (chloroplasts), energy supply organisms (mitochondria) and nucleus as a cellular metabolism coordinator. In comparison with the control plants, decreases in the content of chlorophylls were observed in the case of the Atriplex patula L. plants treated with ibuprofen (11-34%) and naproxen (25-52%). Also, the chlorophylls content from Spinacia oleracea L. was affected, the lowest decrease (34%) being obtained in the case of the treatment with naproxen (1 mg L⁻¹). Diclofenac (1 mg L⁻¹) affected the total polyphenols content (a decrease of 45%) of Atriplex patula L. and ibuprofen (1 mg L⁻¹) affected the total polyphenols content (a decrease of 20%) of Spinacia oleracea L. The results obtained also indicate a moderate reduction of carotenoids and antioxidant capacity in the treated plants, in comparison with the controls. The investigations by transmission electron microscopy demonstrated that the green leafy vegetables were affected by the selected NSAIDs. Thus, this research contributes to a better understanding of the adverse effects of these drugs on studied plants. Important to mention is that the dietary intake of these drugs contaminated plants, plants with important nutritional value, may also presume a risk to human health, but currently little is known about the fate of the drugs in plants and their effect on or risk to the ecosystem.

Keywords: abiotic stress, green leafy vegetables, pigments content, ultra structure

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: Hamed Reza Heshmat Mohajer, Lan Ding, Mattheos Santamouris

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One of the worst environmental dangers for people who live in cities is the Urban Heat Island (UHI) impact which is anticipated to become stronger in the coming years as a result of climate change. Accordingly, the key aim of this paper is to study the interaction between the urban configuration and mitigation strategies including increasing albedo of the urban environment (reflective material), implementation of Urban Green Infrastructure (UGI) and/or a combination thereof. To analyse the microclimate models of different urban categories in the metropolis of Sydney, this study will assess meteorological parameters using a 3D model simulation tool of computational fluid dynamics (CFD) named ENVI-met. In this study, four main parameters are taken into consideration while assessing the effectiveness of UHI mitigation strategies: ambient air temperature, wind speed/direction, and outdoor thermal comfort. Layouts with present condition simulation studies from the basic model (scenario one) are taken as the benchmark. A base model is used to calculate the relative percentage variations between each scenario. The findings showed that maximum cooling potential across different urban layouts can be decreased by 2.15 °C degrees by combining high-albedo material with flora; besides layouts with open arrangements(OT1) present a highly remarkable improvement in ambient air temperature and outdoor thermal comfort when mitigation technologies applied compare to compact counterparts. Besides all layouts present a higher intensity on the maximum ambient air temperature reduction rather than the minimum ambient air temperature. On the other hand, Scenarios associated with an increase in greeneries are anticipated to have a slight cooling effect, especially on high-rise layouts.

Keywords: sustainable urban development, urban green infrastructure, high-albedo materials, heat island effect

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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