Search results for: the soil variables

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Developing tailored management strategies to ensure the sustainability of groundwater resource under climate and demographic changes is critical for tropical karst island, where relatively small watershed and highly porous soil nature make this natural resource highly susceptible and thus very sensitive to those changes. In this study, long-term impacts of climate variability on groundwater recharge and discharge at the Oemau spring, Rote Island, Indonesia were investigated. Following calibration and validation of groundwater model using MODFLOW code, groundwater flow was simulated for period of 2020-2090 under HadCM3 global model climate (GCM) scenarios, using input data of weather variables downscaled by Statistical Downscaling Model (SDSM). The reported analysis suggests that the sustainability of groundwater resources will be adversely affected by climate change during dry years. The area is projected to variably experience 2.53-22.80% decrease of spring discharge. A subsequent comprehensive set of management strategies as palliative and adaptive efforts was proposed to be implemented by relevant stakeholders to assist the community dealing with water deficit during the dry years. Three main adaptive strategies, namely socio-cultural, technical, and ecological measures, were proposed by incorporating physical and socio-economic characteristics of the area. This study presents a blueprint for assessing groundwater sustainability under climate change scenarios and developing tailored management strategies to cope with adverse impacts of climate change, which may become fundamental necessities across other tropical karst islands in the future.

Keywords: climate change, groundwater, management strategies, tropical karst island, Rote Island, Indonesia

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Authors: Mohammad Moezzibadi, Isabelle Charpentier, Adrien Wanko, Robert Mosé

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The calibration of hydrodynamic parameters for subsurface constructed wetlands (CWs) is a sensitive process since highly non-linear equations are involved in unsaturated flow modeling. CW systems are engineered systems designed to favour natural treatment processes involving wetland vegetation, soil, and their microbial flora. Their significant efficiency at reducing the ecological impact of urban runoff has been recently proved in the field. Numerical flow modeling in a vertical variably saturated CW is here carried out by implementing the Richards model by means of a mixed hybrid finite element method (MHFEM), particularly well adapted to the simulation of heterogeneous media, and the van Genuchten-Mualem parametrization. For validation purposes, MHFEM results were compared to those of HYDRUS (a software based on a finite element discretization). As van Genuchten-Mualem soil hydrodynamic parameters depend on water content, their estimation is subject to considerable experimental and numerical studies. In particular, the sensitivity analysis performed with respect to the van Genuchten-Mualem parameters reveals a predominant influence of the shape parameters α, n and the saturated conductivity of the filter on the piezometric heads, during saturation and desaturation. Modeling issues arise when the soil reaches oven-dry conditions. A particular attention should also be brought to boundary condition modeling (surface ponding or evaporation) to be able to tackle different sequences of rainfall-runoff events. For proper parameter identification, large field datasets would be needed. As these are usually not available, notably due to the randomness of the storm events, we thus propose a simple, robust and low-cost numerical method for the inverse modeling of the soil hydrodynamic properties. Among the methods, the variational data assimilation technique introduced by Le Dimet and Talagrand is applied. To that end, a variational data assimilation technique is implemented by applying automatic differentiation (AD) to augment computer codes with derivative computations. Note that very little effort is needed to obtain the differentiated code using the on-line Tapenade AD engine. Field data are collected for a three-layered CW located in Strasbourg (Alsace, France) at the water edge of the urban water stream Ostwaldergraben, during several months. Identification experiments are conducted by comparing measured and computed piezometric head by means of the least square objective function. The temporal variability of hydrodynamic parameter is then assessed and analyzed.

Keywords: automatic differentiation, constructed wetland, inverse method, mixed hybrid FEM, sensitivity analysis

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Authors: Gayathri P. Nair

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The focus of this study is to identify whether the board structure has any significant impact on the firm performance and finding out any evidence of being listed in the Fortune 500 list compiled and published by the American business magazine, Fortune and published globally by Time Inc., as the world’s wealthiest companies. The list has been released based on the ranking obtained for the total revenues for the respective fiscal year which has ended on or before March 31st. The study has been conducted on the Indian companies that were listed in the Fortune 500 list for the past 10 years. This study employs a logical regression between the variables, firm performance and board composition as mentioned in the clause 49 of companies act 1956 and 2013. For getting the firm performance, ROA has selected as the key performance metric, as it focuses the management attention on the assets required to run the business. The highlight of the study is that the tools had been applied between public and private sector firms so that, it reveals whether the board composition is helping out to maintain the position in the list. In addition, the findings reveal that apart from independent directors, all other variables have significant impact on firm performance.

Keywords: board structure, Fortune 500 company, firm performance, India

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Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: Faijal Ali, Darga Kumar N., Ravikant Singh, Rajnil Lal

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Fiji has three major landforms such as plains, low mountains, and hills. The low land soils are formed on beach sand. Fiji soils contain high concentration of iron (III), aluminum oxides and hydroxides. The soil possesses reddish or yellowish colour. The characterization of lateritic soils collected from different locations along the national highway in Viti Levu, Fiji Islands. The research has been carried out mainly to understand the physical and strength properties to assess their suitability for the highway and building construction. In this paper, the field tests such as dynamic cone penetrometer test, field vane shear, field density and laboratory tests such as unconfined compression stress, compaction, grain size analysis and Atterberg limits are conducted. The test results are analyzed and presented. From the results, it is revealed that the soils are having more percentage of silt and clay which is more than 80% and 5 to 15% of fine to medium sand is noticed. The dynamic cone penetrometer results up to 3m depth had similar penetration resistance. For the first 1m depth, the rate of penetration is found 300mm per 3 to 4 blows. In all the sites it is further noticed that the rate of penetration at depths beyond 1.5 m is decreasing for the same number of blows as compared to the top soil. From the penetration resistance measured through dynamic cone penetrometer test, the California bearing ratio and allowable bearing capacities are 4 to 5% and 50 to 100 kPa for the top 1m layer and below 1m these values are increasing. The California bearing ratio of these soils for below 1m depth is in the order of 10% to 20%. The safe bearing capacity of these soils below 1m and up to 3m depth is varying from 150 kPa to 250 kPa. The field vane shear was measured within a depth of 1m from the surface and the values were almost similar varying from 60 kPa to 120 kPa. The liquid limit and plastic limits of these soils are in the range of 40 to 60% and 20 to 25%. Overall it is found that the top 1m soil along the national highway in majority places possess a soft to medium stiff behavior with low to medium bearing capacity as well low California bearing ratio values. It is recommended to ascertain these soils behavior in terms of geotechnical parameters before taking up any construction activity.

Keywords: California bearing ratio, dynamic cone penetrometer test, field vane shear, unconfined compression stress.

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Authors: Tomasz Komornicki

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The primary aim of the presentation is to try to model border traffic and, at the same time to explain on which economic variables the intensity of border traffic depended in the long term. For this purpose, long series of traffic data on the Polish borders were used. Models were estimated for three variants of explanatory variables: a) for total arrivals and departures (total movement of Poles and foreigners), b) for arrivals and departures of Poles, and c) for arrivals and departures of foreigners. Each of the defined explanatory variables in the models appeared as the logarithm of the natural number of persons. Data from 1994-2017 were used for modeling (for internal Schengen borders for the years 1994-2007). Information on the number of people arriving in and leaving Poland was collected for a total of 303 border crossings. On the basis of the analyses carried out, it was found that one of the main factors determining border traffic is generally differences in the level of economic development (GDP) and the condition of the economy (level of unemployment) and the degree of border permeability. Also statistically significant for border traffic are differences in the prices of goods (fuels, tobacco, and alcohol products) and services (mainly basic ones, e.g., hairdressing services). Such a relationship exists mainly on the eastern border (border traffic determined largely by differences in the prices of goods) and on the border with Germany (in the first analysed period, border traffic was determined mainly by the prices of goods, later - after Poland's accession to the EU and the Schengen area - also by the prices of services). The models also confirmed differences in the set of factors shaping the volume and structure of border traffic on the Polish borders resulting from general geopolitical conditions, with the year 2007 being an important caesura, after which the classical population mobility factors became visible. The results obtained were additionally related to changes in traffic that occurred as a result of the CPOVID-19 pandemic and as a result of the Russian aggression against Ukraine.

Keywords: border, modal structure, transport, Ukraine

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Authors: Monty Vacura

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Hamilton’s Rule is a universal law of biology expressed in protists, plants and animals. When applied to human populations, this model explains: 1) Origin of religion in society as a biopsychological need naturally selected to increase population size; 2) Instincts of racism expressed through intergroup competition; 3) Simultaneous selection for human cooperation and conflict, love and hate; 4) Places Dawkins’s selfish gene as the r, relationship variable; 5) Flipping the equation variable themes (close relationship to distant relationship, and benefit to threat) the new equation can now be used to identify the offensive and defensive sides of conflict; 6) Connection between sporting events and instinctive social messaging for stimulating offensive and defensive responses; 6) Pathway to reduce human sacrifice through manipulation of variables. This paper discusses the deep psychological influences of Hamilton’s Rule. Suggestions are provided to reduce human deaths via our instinctive sacrificial behavior, by consciously monitoring Hamilton’s Rule variables highlighted throughout our media outlets.

Keywords: psychology, Hamilton’s rule, evolution, human instincts

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Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

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Authors: Tomer Gans-Or, Shmulik Pinkert

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The determination of lateral pile capacity per unit length is a key aspect in geotechnical engineering. Traditional approaches for assessing piles lateral capacity in cohesive soils involve the application of upper-bound and lower-bound plasticity theorems. However, a comprehensive solution encompassing the entire spectrum of soil strength parameters, particularly in frictional soils with or without cohesion, is still lacking. This research introduces an innovative implementation of the slice method limit equilibrium solution for lateral capacity assessment. For any given numerical discretization of the soil's domain around the pile, the lateral capacity evaluation is based on mobilized strength concept. The critical failure geometry is then found by a unique optimization procedure which includes both factor of safety minimization and geometrical optimization. The robustness of this suggested methodology is that the solution is independent of any predefined assumptions. Validation of the solution is accomplished through a comparison with established plasticity solutions for cohesive soils. Furthermore, the study demonstrates the applicability of the limit equilibrium method to address unresolved cases related to frictional and cohesive-frictional soils. Beyond providing capacity values, the method enables the utilization of the mobilized strength concept to generate safety-factor distributions for scenarios representing pre-failure states.

Keywords: lateral pile capacity, slice method, limit equilibrium, mobilized strength

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Authors: Hanen Filali, Mohamed Hachicha

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Treated grey water (TGW) reuse emerged as an alternative resource to meet the growing demand for water for agricultural irrigation and reduce the pressure on limited existing fresh water. However, this reuse needs adapted management in order to avoid environmental and health risks. In this work, the treatment of grey water (GW) was studied from a cyclic treatment system that we designed and implemented in the greenhouse of National Research Institute for Rural Engineering, Water and Forests (INRGREF). This system is composed of three levels for treatment (TGW 1, TGW 2, and TGW 3). Each level includes a sandy soil box. The use of grey water was moderated depending on the chemical and microbiological quality obtained. Different samples of soils and treated grey water were performed and analyzed for 14 irrigation cycles. TGW through cyclic treatment showed physicochemical parameters like pH, electrical conductivity (EC), chemical oxygen demand (COD), biological oxygen demand (BOD5) in the range of 7,35-7,91, 1,69-5,03 dS/m, 102,6-54,2 mgO2/l, and 31,33-15,74 mgO2/l, respectively. Results showed a reduction in the pollutant load with a significant effect on the three treatment levels; however, an increase in salinity was observed during all irrigation cycles. Microbiological results showed good grey water treatment with low health risk on irrigated soil. Treated water quality was below permissible Tunisian standards (NT106.03), and treated water is suitable for non-potable options.

Keywords: treated grey water, irrigation, cyclic treatment, soils, physico-chemical parameters, microbiological parameters

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Authors: Loubna Hamami, Bouchaib Nassereddine

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Due to the evolution of technologies, the need to observe and manage hostile environments, and reduction in size, wireless sensor networks (WSNs) are becoming essential and implicated in the most fields of life. WSNs enable us to change the style of living, working and interacting with the physical environment. The agricultural sector is one of such sectors where WSNs are successfully used to get various benefits. For successful agricultural production, the irrigation system is one of the most important factors, and it plays a tactical role in the process of agriculture domain. However, it is considered as the largest consumer of freshwater. Besides, the scarcity of water, the drought, the waste of the limited available water resources are among the critical issues that touch the almost sectors, notably agricultural services. These facts are leading all governments around the world to rethink about saving water and reducing the volume of water used; this requires the development of irrigation practices in order to have a complete and independent system that is more efficient in the management of irrigation. Consequently, the selection of WSNs in irrigation system has been a benefit for developing the agriculture sector. In this work, we propose a prototype for a complete and intelligent irrigation system based on wireless sensor networks and we present and discuss the design of this prototype. This latter aims at saving water, energy and time. The proposed prototype controls water system for irrigation by monitoring the soil temperature, soil moisture and weather conditions for estimation of water requirements of each plant.

Keywords: precision irrigation, sensor, wireless sensor networks, water resources

Procedia PDF Downloads 138

Authors: Mike Yaw Osei-Atweneboana, John Asiedu Larbi, Edward Jenner Tettevi

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Background: The lymphatic filariasis (LF) control programme has been on-going in Ghana since 2000. This community-wide approach involves the use of ivermectin (IVM) and albendazole (ALB). Soil-transmitted helminth (STH) infections control is augmented within this programme; however, in areas where LF is not prevalent, albendazole alone is administered to school children. The purpose of this study was therefore, to determine the efficacy of albendazole against soils transmitted helminths and the impact of mass drug administration of albendazole and ivermectin on the health status of children of school going age and pregnant women. Material/Methods: This was a twelve months longitudinal study. A total of 412 subjects including school children (between the ages of 2-17 years) and pregnant women were randomly selected from four endemic communities in Kpandai district of the Northern region. Coprological assessment for parasites was based on the Kato–Katz technique in both dry and rainy seasons at baseline, 21 days and 3 months post-treatment. Single-dose albendazole treatment was administered to all patients at baseline. Preserved samples are currently under molecular studies to identify possible single nucleotide polymorphism (SNP) within the beta tubulin gene which is associated with benzimidazole resistance. Results: Of all the parasites found (hookworm, Trichuris trichiura, Hymenolepis nana, and Taenia sp.); hookworm was the most prevalent. In the dry season, the overall STHs prevalence at pre-treatment was 29%, while 9% and 13% prevalence was recorded at 21 days, and three months after treatment respectively. However, in the rainy season, the overall STHs prevalence was 8%, while 4% and 12% was recorded at 21 days and three months respectively after ALB treatment. In general, ALB treatment resulted in an overall hookworm egg count reduction rate of 89% in the dry season and 93% in the rainy season, while the T. trichiura egg count reduction rate was 100% in both seasons. Conclusions: STH infections still remains a significant public health burden in Ghana. Hookworm infection seems to respond poorly or sub-optimally to ALB, raising concerns of possible emergence of resistance which may lead to a major setback for the control and elimination of STH infections, especially hookworm infections.

Keywords: hookworm, sub-optimal response, albendazole, trichuriasis, soil-transmitted helminths

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Adji Achmad Rinaldo Fernandes, Usriatur Rohma

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Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best truncated spline nonparametric path function between linear and quadratic polynomial degrees with 1, 2, and 3 knot points and to determine the significance of estimating the best truncated spline nonparametric path function in the model of the effect of perceived benefits and perceived convenience on behavior to convert waste into economic value through the intention variable of changing people's mindset about waste using the t test statistic at the jackknife resampling stage. The data used in this study are primary data obtained from research grants. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3 knot points. In addition, the significance of the best truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, kuadratic, behavior to turn waste into economic value, jackknife resampling

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Authors: Abdelkader Anouzla, Soukaina Bouaouda, Roukaya Bouyakhsass, Salah Souabi, Abdeslam Taleb

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During storage and under the combined action of rainwater and natural fermentation, these wastes produce over 800.000 m3 of landfill leachates. Due to population growth and changing global economic activities, the amount of waste constantly generated increases, making more significant volumes of leachate. Leachate, when leaching into the soil, can negatively impact soil, surface water, groundwater, and the overall environment and human life. The leachate must first be treated because of its high pollutant load before being released into the environment. This article reviews the different leachate treatments in September 2022 techniques. Different techniques can be used for this purpose, such as biological, physical-chemical, and membrane methods. Young leachate is biodegradable; in contrast, these biological processes lose their effectiveness with leachate aging. They are characterized by high ammonia nitrogen concentrations that inhibit their activity. Most physical-chemical treatments serve as pre-treatment or post-treatment to complement conventional treatment processes or remove specific contaminants. After the introduction, the different types of pollutants present in leachates and their impacts have been made, followed by a discussion highlighting the advantages and disadvantages of the various treatments, whether biological, physicochemical, or membrane. From this work, due to their simplicity and reasonable cost compared to other treatment procedures, biological treatments offer the most suitable alternative to limit the effects produced by the pollutants in landfill leachates.

Keywords: landfill leachate, landfill pollution, impact, wastewater

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Authors: Mamata Mohanty, J. T. Shahu

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The in-situ deep mixing is an effective ground improvement technique which involves columnar inclusion into soft ground to increase its bearing capacity and reduce settlement. The first part of the study presents the results of unconfined compression on cement-admixed clay prepared at different cement content and subjected to varying curing periods. It is found that cement content is a prime factor controlling the strength of the cement-admixed clay. Besides cement content, curing period is important parameter that adds to the strength of cement-admixed clay. Increase in cement content leads to significant increase in Unconfined Compressive Strength (UCS) values especially at cement contents greater than 8%. The second part of the study investigated the bearing capacity of the clay ground improved by a group of end-bearing column using model tests under plain-strain condition. This study mainly focus to examine the effect of cement contents on the ultimate bearing capacity and failure stress of the improved clay ground. The study shows that the bearing capacity of the improved ground increases significantly with increase in cement contents of the soil-cement columns. A considerable increase in the stiffness of the model ground and failure stress was observed with increase in cement contents.

Keywords: bearing capacity, cement content, curing time, unconfined compressive strength, undrained shear strength

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Authors: Jaworski Mariusz, Owczarek Krzysztof, Adamus Mirosława

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Binge eating disorder (BED) is one of the three main eating disorders, beside anorexia and bulimia nervosa. BED is characterized by a loss of control over the quantity of food consumed and the lack of the compensatory behaviors, such as induced vomiting or purging. Studies highlight that certain personality traits may contribute to the severity of symptoms in the ED. The aim of this study is to analyze the relationship between psychological variables (Impulsivity and Urgency) and Nutritional restrictions in BED. The study included two groups. The first group consisted of 35 women with BED aged 18 to 28. The control group - 35 women without ED aged 18 to 28. ED-1 questionnaire was used in a study to assess the severity of impulsivity, urgency and nutritional restrictions. The obtained data were standardized. Statistical analyzes were performed using SPSS 21 software. The severity of impulsivity was higher in patients with BED than the control group. The relation between impulsivity and nutritional restrictions in BED was observed, only taking into consideration the relationship of these variables with the level of urgency. However, if the severity of urgency in this relationship is skipped, the relationship between impulsivity and nutritional restrictions will not occur. Impulsivity has a negative relationship with the level of urgency. This study suggests the need to analyze the interaction between impulsivity and urgency, and their relationship with dietary behavior in BED, especially nutritional restrictions. Analysis of single isolated features may give erroneous results.

Keywords: binge eating disorder, impulsivity, nutritional restrictions, urgency

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Authors: Javad Sarvestan, Zdenek Svoboda

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Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

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Authors: Dhritilekha Deka, Deepak Patwa, Ravi K., Archana M. Nair

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Bioaccumulation of heavy metal contaminants due to intense anthropogenic interference degrades the environment and ecosystem functions. Conventional physicochemical methods involve energy-intensive and costly methodologies. Phytoremediation, on the other hand, provides an efficient nature-based strategy for the reclamation of heavy metal-contaminated sites. However, the slow process and adaptation to high-concentration contaminant sequestration often limit the efficiency of the method. This necessitates natural amendments such as biochar to improve phytoextraction and stabilize the green cover. Biochar is a highly porous structure with high carbon sequestration potential and containing negatively charged functional groups that provide binding sites for the positively charged metals. This study aims to develop and determine the synergy between sugarcane bagasse biochar content and phytoremediation. A 60-day pot experiment using perennial tussock vetiver grass (Chrysopogon zizanioides) was conducted for different biochar contents of 1%, 2%, and 4% for the removal of cadmium and zinc. A concentration of 500 ppm is maintained for the amended and unamended control (CK) samples. The survival rates of the plants, biomass production, and leaf area index were measured for the plant growth characteristics. Results indicate a visible change in the plant growth and the heavy metal concentration with the biochar content. The bioconcentration factor (BCF) in the plant improved significantly for the 4% biochar content by 57% in comparison to the control CK treatment in Cd-treated soils. The Zn soils indicated the highest reduction in the metal concentration by 50% in the 2% amended samples and an increase in the BCF in all the amended samples. The translocation from the rhizosphere to the shoots was low but not dependent on the amendment content and varied for each contaminant type. The root-to-shoot ratio indicates higher values compared to the control samples. The enhanced tolerance capacities can be attributed to the nutrients released by the biochar in the soil. The study reveals the high potential of biochar as a phytoremediation amendment, but its effect is dependent on the soil and heavy metal and accumulator species.

Keywords: phytoextraction, biochar, heavy metals, chrysopogon zizanioides, bioaccumulation factor

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Khatesiree Sripoothon, Usanee Sengpanich, Rattana Sittioum

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The objective of this study is to examine the factors influencing consumer purchasing decisions about healthy food. This model consists of two latent variables: Consumer Perception relating to NCDs and Consumer Perceived Product Value. The study was conducted in the northern provinces of Thailand, which are popular with tourists and have received support from the government for health tourism. A survey was used as the data collection method, and the questionnaire was applied to 385 tourists. An accidental sampling method was used to identify the sample. The statistics of frequency, percentage, mean, and structural equation model were used to analyze the data obtained. Additionally, all factors had a significant positive influence on healthy food purchasing decisions (p<0.01) and were predictive of healthy food purchasing decisions at 46.20 (R2=0.462). Also, these findings seem to underline a supposition that consumer perceptions of NCDs and perceived product value are key variables that strengthens the competitive effects of a healthy-friendly business entrepreneur. Moreover, reduce the country's public health costs for treating patients with the disease of NCDs in Thailand.

Keywords: healthy food, perceived product value, perception of non-communicable diseases, purchasing decisions

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Authors: Rashmi Uchil, A. H. Sequeira

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Post-liberalization era in India has seen an unprecedented growth of mergers, both domestic as well as cross-border deals. Indian organizations have slowly begun appreciating this inorganic method of growth. However, all is not well as is evidenced in the lowering value creation of organizations after mergers. Several studies have identified that organizational culture is one of the key factors that affects the success of mergers. But very few studies have been attempted in this realm in India. The current study attempts to identify the factors in the organizational culture variable that may be unique to India. It also focuses on the difference in the impact of organizational culture on merger of organizations in the manufacturing and service sectors in India. The study uses a mixed research approach. An exploratory research approach is adopted to identify the variables that constitute organizational culture specifically in the Indian scenario. A few hypotheses were developed from the identified variables and tested to arrive at the Grounded Theory. The Grounded Theory approach used in the study, attempts to integrate the variables related to organizational culture. Descriptive approach is used to validate the developed grounded theory with a new empirical data set and thus test the relationship between the organizational culture variables and the success of mergers. Empirical data is captured from merged organizations situated in major cities of India. These organizations represent significant proportions of the total number of organizations which have adopted mergers. The mix of industries included software, banking, manufacturing, pharmaceutical and financial services. Mixed sampling approach was adopted for this study. The first phase of sampling was conducted using the probability method of stratified random sampling. The study further used the non-probability method of judgmental sampling. Adequate sample size was identified for the study which represents the top, middle and junior management levels of the organizations that had adopted mergers. Validity and reliability of the research instrument was ensured with appropriate tests. Statistical tools like regression analysis, correlation analysis and factor analysis were used for data analysis. The results of the study revealed a strong relationship between organizational culture and its impact on the success of mergers. The study also revealed that the results were unique to the extent that they highlighted a marked difference in the manner of internalization of change of organizational culture after merger by the organizations in the manufacturing sector. Further, the study reveals that the organizations in the service sector internalized the changes at a slower rate. The study also portrays the industries in the manufacturing sector as more proactive and can contribute to a change in the perception of the said organizations.

Keywords: manufacturing industries, mergers, organizational culture, service industries

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Authors: Olivier Mesly

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This article examines the likelihood of deception on the part of borrowers wishing to obtain credit from institutional or private lenders. In our first study, we identify five explanatory variables that account for nearly forty percent of the propensity to act deceitfully: a poor credit history, debt, risky behavior, and to a much lesser degree, irrational behavior and disconnection from the bundle of needs, goals, and preferences. For the second study, we remodeled the initial questionnaire to adapt it to the needs of institutional bankers and borrowers, especially those that engage in money on-line peer-to-peer lending, a growing business fueled by the COVID pandemic. We find that the three key psychological variables that help to indirectly predict the likelihood of deceitful behaviors and possible default on loan reimbursement, i.e., risky behaviors, ir-rationality, and dis-connection, interact with each other to form a loop. This study presents two benefits: first, we provide evidence that it is to some degree possible to tighten control over lending practices. Second, we offer a pragmatic tool: a questionnaire, that lenders can use or adapt to gauge potential borrowers’ deceit, notably by combining their results with standard hard-data measures of risk.

Keywords: bundle of needs, default, debt, deception, risk, peer-to-peer lending

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Authors: Amanuel Bekuma, Rebecca Swift, Sarah Jackson, Ben Biddulph

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Economic loss to frost damage is increasing over the past years in the Western Australian Wheatbelt. Agronomic, genetic, and climatic works have still found a weak correlation between temperature and frost damage. One possibility that has not been explored within the Australian cropping system is whether ice nucleation active bacteria (INB) either present in situ on crop residue or introduced by rainfall could be responsible for the increased sensitivity of cereal plants to frost at different stages of development. This study investigated upper and lower leaf canopy, stubble, and soil as a potential site of ice nucleation activity (INA) and tracked the changes in INA during the plant development. We found that older leaves of wheat are the primary sites of ice nucleation (-4.7 to -6.3°C) followed by stubble (-5.7 to -6.7°C) which increases the risk of frost damage during heading and flowering (the most susceptible stages). However, healthy and green upper canopy leaves (flag and flag-2) and the soil have lower INA (< -11°C) during the frost-sensitive stage of wheat. We anticipate the higher INA on the stubble and older leaves to be due to the presence of biologically active ice-nucleating bacteria (INB), known to cause frost injury to sensitive plants at -5°C. Stubble retained or applied during the growing season further exacerbates additional frost risk by potentially increasing the INB load. The implications of the result for stubble and frost risk management in a frost-prone landscape will be discussed.

Keywords: frost, ice-nucleation-activity, stubble, wheat

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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Authors: Masoud Sheidaei, Fahimeh Koohdar

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Date palms are economically important tree plants with high nutrition and medicinal values. More than 400 date palm cultivars are cultivated in many regions of Iran, but no report is available on landscape genetics and species distribution modeling of these trees from the country. Therefore, the present study provides a detailed insight into the genetic diversity and structure of date palm populations in Iran and investigates the effects of geographical and climatic variables on the structuring of genetic diversity in them. We used different computational methods in the study like, spatial principal components analysis (sPCA), redundancy analysis (RDA), latent factor mixed model (LFMM), and Maxent and Dismo models of species distribution modeling. We used a combination of different molecular markers for this study. The results showed that both global and local spatial features play an important role in the genetic structuring of date palms, and the genetic regions associated with local adaptation and climatic variables were identified. The effects of climatic change on the distribution of these taxa and the genetic regions adaptive to these changes will be discussed.

Keywords: adaptive genetic regions, genetic diversity, isolation by distance, populations divergence

Procedia PDF Downloads 93