Search results for: energy conversion efficiency

Authors: Gautier Viaud, Paul-Henry Cournède

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

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

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Authors: Nafsi K. Ashraf, C. V. Vipin, V. Anantha Subramanian

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This paper reports the design of a waterjet propulsion system for an amphibious vehicle based on circulation distribution over the camber line for the sections of the impeller and stator. In contrast with the conventional waterjet design, the inlet duct is straight for water entry parallel and in line with the nozzle exit. The extended nozzle after the stator bowl makes the flow more axial further improving thrust delivery. Waterjet works on the principle of volume flow rate through the system and unlike the propeller, it is an internal flow system. The major difference between the propeller and the waterjet occurs at the flow passing the actuator. Though a ducted propeller could constitute the equivalent of waterjet propulsion, in a realistic situation, the nozzle area for the Waterjet would be proportionately larger to the inlet area and propeller disc area. Moreover, the flow rate through impeller disk is controlled by nozzle area. For these reasons the waterjet design is based on pump systems rather than propellers and therefore it is important to bring out the characteristics of the flow from this point of view. The analysis is carried out using computational fluid dynamics. Design of waterjet propulsion is carried out adapting the axial flow pump design and performance analysis was done with three-dimensional computational fluid dynamics (CFD) code. With the varying environmental conditions as well as with the necessity of high discharge and low head along with the space confinement for the given amphibious vehicle, an axial pump design is suitable. The major problem of inlet velocity distribution is the large variation of velocity in the circumferential direction which gives rise to heavy blade loading that varies with time. The cavitation criteria have also been taken into account as per the hydrodynamic pump design. Generally, waterjet propulsion system can be parted into the inlet, the pump, the nozzle and the steering device. The pump further comprises an impeller and a stator. Analytical and numerical approaches such as RANSE solver has been undertaken to understand the performance of designed waterjet propulsion system. Unlike in case of propellers the analysis was based on head flow curve with efficiency and power curves. The modeling of the impeller is performed using rigid body motion approach. The realizable k-ϵ model has been used for turbulence modeling. The appropriate boundary conditions are applied for the domain, domain size and grid dependence studies are carried out.

Keywords: amphibious vehicle, CFD, impeller design, waterjet propulsion

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Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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Authors: Chanya Inprasit, Ching-Liang Hsieh, Yi-Wen Lin

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Obesity (OB) is a hazardous global health problem that has been increasing in prevalence, more severely in last decade. It is the mainly resultant from the imbalance between food consumption and energy expenditure, which is concordant with a modern lifestyle, implying an increase in calories with poorer quality of food intake accompanied by a decrease in physical activities. Obesity does not concern the appearance only but is also a major factor contributing to poor physiology, psychology, society and economic issues. Moreover, OB induces low-grade inflammation in the body through the regulatory effect it enacts on the adipocyte function. Various alternative treatments were investigated for body weight control, including Acupoint Catgut Embedding (ACE). ACE is the implantation of absorbable catgut sutures at specific acupoints, displaying durable and potent stimulation and thereby reducing the treatment frequency. Our study utilized a mouse model to exclude any psychological factors of OB and ACE treatment. High-fat diet and body weight were measured once a week before subjects in ACE and Sham group received the ACE treatment or placebo treatment. We hypothesized that ACE can control body weight through the interaction of the TRPV1 pathways, as TRPV1 accordingly responds to inflammatory factors. The results of body weight variation show a significant decrease in body weight in ACE group compared with the baseline of control and Sham group. Meanwhile, converse results were explored in TRPV1 knockout mice, where a significant maintenance of normal body weight throughout the experiment period was observed. There was no significant difference in food consumption of each group. These finding indicated that TRPV1 pathways and its associated pathways may be involved in the maintenance of body weight, which can be controlled by ACE treatment of genetic manipulation.

Keywords: acupoint catgut embedding, obesity, hypothalamus, TRPV1

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Authors: Maria Korman, Carmit Gal, Ella Gabitov, Avi Karni

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The main question addressed in this study was whether the time-of-day wherein training is afforded is a significant factor for motor skill ('how-to', procedural knowledge) acquisition and consolidation into long term memory in the healthy elderly population. Twenty-nine older adults (60-75 years) practiced an explicitly instructed 5-element key-press sequence by repeatedly generating the sequence ‘as fast and accurately as possible’. Contribution of three parameters to acquisition, 24h post-training consolidation, and 1-week retention gains in motor sequence speed was assessed: (a) time of training (morning vs. evening group) (b) sleep quality (actigraphy) and (c) chronotype. All study participants were moderately morning type, according to the Morningness-Eveningness Questionnaire score. All participants had sleep patterns typical of age, with average sleep efficiency of ~ 82%, and approximately 6 hours of sleep. Speed of motor sequence performance in both groups improved to a similar extent during training session. Nevertheless, evening group expressed small but significant overnight consolidation phase gains, while morning group showed only maintenance of performance level attained at the end of training. By 1-week retention test, both groups showed similar performance levels with no significant gains or losses with respect to 24h test. Changes in the tapping patterns at 24h and 1-week post-training were assessed based on normalized Pearson correlation coefficients using the Fisher’s z-transformation in reference to the tapping pattern attained at the end of the training. Significant differences between the groups were found: the evening group showed larger changes in tapping patterns across the consolidation and retention windows. Our results show that morning-oriented older adults effectively acquired, consolidated, and maintained a new sequence of finger movements, following both morning and evening practice sessions. However, time-of-training affected the time-course of skill evolution in terms of performance speed, as well as the re-organization of tapping patterns during the consolidation period. These results are in line with the notion that motor training preceding a sleep interval may be beneficial for the long-term memory in the elderly. Evening training should be considered an appropriate time window for motor skill learning in older adults, even in individuals with morning chronotype.

Keywords: time-of-day, elderly, motor learning, memory consolidation, chronotype

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Authors: Seok-Tae Yoon, Jae-Yeong Choi, Gyu-Mok Jeon, Yong-Jin Cho, Jong-Chun Park

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Conventional submarines obtain propulsive force by using an electric propulsion system consisting of a diesel generator, battery, motor, and propeller. In the underwater, the submarine uses the electric power stored in the battery. After that, when a certain amount of electric power is consumed, the submarine floats near the sea water surface and recharges the electric power by using the diesel generator. The voyage carried out while charging the power is called a snorkel, and the high-temperature exhaust gas from the diesel generator forms a heat distribution on the sea water surface. The heat distribution is detected by weapon system equipped with thermo-detector and that is the main cause of reducing the survivability of the submarine. In this paper, an experimental study was carried out to establish optimal operating conditions of a submarine for reduction of infrared signature radiated from the sea water surface. For this, a hot gas generating system and a round acrylic water tank with adjustable water level were made. The control variables of the experiment were set as the mass flow rate, the temperature difference between the water and the hot gas in the water tank, and the water level difference between the air outlet and the water surface. The experimental instrumentation used a thermocouple of T-type to measure the released air temperature on the surface of the water, and a thermography system to measure the thermal energy distribution on the water surface. As a result of the experiment study, we analyzed the correlation between the final released temperature of the exhaust pipe exit in a submarine and the depth of the snorkel, and presented reasonable operating conditions for the infrared signature reduction of submarine.

Keywords: experiment study, flow rate, infrared signature, snorkeling, thermography

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Authors: O. I. H. Dimitry, N. A. Mansour, A. L. G. Saad

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Natural sodium montmorillonite (NaMMT), Cloisite Na⁺ and two organophilic montmorillonites (OMMTs), Cloisites 20A and 15A were used. Polycaprolactone (PCL)/MMT composites containing 1, 3, 5, and 10 wt% of Cloisite Na⁺ and PCL/OMMT nanocomposites containing 5 and 10 wt% of Cloisites 20A and 15A were prepared via solution intercalation technique to study the influence of organic modifier loading on particle dispersion of PCL/ NaMMT composites. Thermal stabilities of the obtained composites were characterized by thermal analysis using the thermogravimetric analyzer (TGA) which showed that in the presence of nitrogen flow the incorporation of 5 and 10 wt% of filler brings some decrease in PCL thermal stability in the sequence: Cloisite Na+>Cloisite 15A > Cloisite 20A, while in the presence of air flow these fillers scarcely influenced the thermoxidative stability of PCL by slightly accelerating the process. The interaction between PCL and silicate layers was studied by Fourier transform infrared (FTIR) spectroscopy which confirmed moderate interactions between nanometric silicate layers and PCL segments. The electrical conductivity (σ) which describes the ionic mobility of the systems was studied as a function of temperature and showed that σ of PCL was enhanced on increasing the modifier loading at filler content of 5 wt%, especially at higher temperatures in the sequence: Cloisite Na⁺<Cloisite 20A<Cloisite 15A, and was then decreased to some extent with a further increase to 10 wt%. The activation energy E_σ obtained from the dependency of σ on temperature using Arrhenius equation was found to be lowest for the nanocomposite containing 5 wt% of Cloisite 15A. The dispersed behavior of clay in PCL matrix was evaluated by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses which revealed partial intercalated structures in PCL/NaMMT composites and semi-intercalated/semi-exfoliated structures in PCL/OMMT nanocomposites containing 5 wt% of Cloisite 20A or Cloisite 15A.

Keywords: electrical conductivity, montmorillonite, nanocomposite, organoclay, polycaprolactone

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Authors: Martin Mundo-Molina

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In Mexico, there are many small rural communities with serious water supply deficiencies. In Chiapas, Mexico, there are 19,972 poor rural communities, 15,712 of which have fewer than 100 inhabitants. The lack of a constant water supply is most severe in the highlands of Chiapas where the population is made up mainly of indigenous groups. The communities are on mountainous terrain with a widely dispersed population. These characteristics combine to make the provision of public utilities, such as water, electricity and sewerage, difficult with conventional means. The introduction of alternative, low-cost technologies represents means of supplying water such as through fog and rain catchment with zero greenhouse emissions. In this paper is presented the rainwater harvesting system (RWS) constructed in Yalentay, Chiapas Mexico. The RWS is able to store 1.2 M liters of water to provide drinking water to small rural indigenous communities of 500 people in the drought stage. Inside the system of rainwater harvesting there isn't photosynthesis in order to conserve water for long periods. The natural filters of the system of rainwater harvesting guarantee the drinking water for using to the community. The combination of potability and low cost makes rain collection a viable alternative for rural areas, weather permitting. The Mexican Institute of Water Technology and Chiapas University constructed a rainwater harvesting system in Yalentay Chiapas, it consists of four parts: 1. Roof of aluminum, for collecting rainwater, 2. Underground-cistern, divided in two tanks, 3. Filters, to improve the water quality and 4. The system of rainwater harvesting dignified the lives of people in Yalentay, saves energy, prevents the emission of greenhouse gases into the atmosphere, conserves natural resources such as water and air.

Keywords: appropriate technologies, climate change, greenhouse gases, rainwater harvesting

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Authors: Kirti Tewari, Rahul Dev

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Solar water heating is a thermodynamic process of heating water using sunlight with the help of solar water heater. Thus, solar water heater is a device used to harness solar energy. In this paper, a modified solar water heating system (MSWHS) has been proposed over flat plate collector (FPC) and Evacuated tube collector (ETC). The modifications include selection of materials other than glass, and glass wool which are conventionally used for fabricating FPC and ETC. Some modifications in design have also been proposed. Its collector is made of double layer of semi-cylindrical acrylic tubes and fibre reinforced plastic (FRP) insulation base. Water tank is made of double layer of acrylic sheet except base and north wall. FRP is used in base and north wall of the water tank. A concept of equivalent thickness has been utilised for calculating the dimensions of collector plate, acrylic tube and tank. A thermal model for the proposed design of MSWHS is developed and simulation is carried out on MATLAB for the capacity of 200L MSWHS having collector area of 1.6 m2, length of acrylic tubes of 2m at an inclination angle 25° which is taken nearly equal to the latitude of the given location. Latitude of Allahabad is 24.45° N. The results show that the maximum temperature of water in tank and tube has been found to be 71.2°C and 73.3°C at 17:00hr and 16:00hr respectively in March for the climatic data of Allahabad. Theoretical performance analysis has been carried out by varying number of tubes of collector, the tank capacity and climatic data for given months of winter and summer.

Keywords: acrylic, fibre reinforced plastic, solar water heating, thermal model, conventional water heaters

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Authors: Monu Verma, Hyunook Kim

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Heavy metals and organic dyes are the major sources of water pollution. Herein, a trifunctional β−cyclodextrin−ethylenediaminetetraacetic acid−chitosan (β−CD−EDTA−CS) polymer was synthesized using an easy and simple chemical route by the reaction of activated β−CD with CS through EDTA as a cross-linker (amidation reaction) for the removal of inorganic and organic pollutants from aqueous solution under different parameters such as pH, time effect, initial concentration, reusability, etc. The synthesized adsorbent was characterized using powder X-ray diffraction, Fourier transform infrared spectroscopy, field scanning electron microscopy, energy dispersive spectroscopy, Brunauer-Emmett-Teller (BET), thermogravimetric analyzer techniques to investigate their structural, functional, morphological, elemental compositions, surface area, and thermal properties, respectively. Two types of heavy metals, i.e., mercury (Hg²⁺) and cadmium (Cd²⁺), and three organic dyes, i.e., methylene blue (MB), crystal violet (CV), and safranin O (SO), were chosen as inorganic and organic pollutants, respectively, to study the adsorption capacity of β-CD-EDTA-CS in aqueous solution. The β-CD-EDTA-CS shows a monolayer adsorption capacity of 346.30 ± 14.0 and 202.90 ± 13.90 mg g−¹ for Hg²⁺ and Cd²⁺, respectively, and a heterogeneous adsorption capacity of 107.20 ± 5.70, 77.40 ± 5.30 and 55.30 ± 3.60 mg g−¹ for MB, CV and SO, respectively. Kinetics results followed pseudo-second order (PSO) kinetics behavior for both metal ions and dyes, and higher rate constants values (0.00161–0.00368 g mg−¹ min−¹) for dyes confirmed the cavitation of organic dyes (physisorption). In addition, we have also demonstrated the performance of β-CD-EDTA-CS for the four heavy metals, Hg²⁺, Cd²⁺, Ni²⁺, and Cu²⁺, and three dyes MB, CV, and SO in secondary treated wastewater. The findings of this study indicate that β-CD-EDTA-CS is simple and easy to synthesize and can be used in wastewater treatment.

Keywords: adsorption isotherms, adsorption mechanism, amino-β-cyclodextrin, heavy metal ions, organic dyes

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Authors: Tim Dunne, Jiaxiang Ren, Lei Zhao, Peng Cheng, Yi Song, Yu Liu, Wenhan Yue, Xiongwen Yang

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Two decades of the Shale Revolution has transforming transformed the global energy market, in part by the adaption of multi-stage dissolvable frac plugs. Magnesium has been favored for the bulk of plugs, requiring development of materials to suit specific field requirements. Herein, the mechanical and dissolution results from equal channel angular pressing (ECAP) of two cast dissolvable magnesium alloy are described. ECAP was selected as a route to increase the mechanical properties of two formulations of dissolvable magnesium, as solutionizing failed. In this study, 1” square cross section samples cast Mg alloys formulations containing rare earth were processed at temperatures ranging from 200 to 350 °C, at a rate of 0.005”/s, with a backpressure from 0 to 70 MPa, in a brass, or brass + graphite sheet. Generally, the yield and ultimate tensile strength (UTS) doubled for all. For formulation DM-2, the yield increased from 100 MPa to 250 MPa; UTS from 175 MPa to 325 MPa, but the strain fell from 2 to 1%. Formulation DM-3 yield increased from 75 MPa to 200 MPa, UTS from 150 MPa to 275 MPa, with strain increasing from 1 to 3%. Meanwhile, ECAP has also been found to reduce the dissolution rate significantly. A microstructural analysis showed grain refinement of the alloy and the movement of secondary phases away from the grain boundary. It is believed that reconfiguration of the grain boundary phases increased the mechanical properties and decreased the dissolution rate. ECAP processing of dissolvable high rare earth content magnesium is possible despite the brittleness of the material. ECAP is a possible processing route to increase mechanical properties for dissolvable aluminum alloys that do not extrude.

Keywords: equal channel angular processing, dissolvable magnesium, frac plug, mechanical properties

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Authors: Numfon Rakkhumkaew, Takeru Kawasaki, Makoto Fujie, Takashi Yamada

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Chlorella viruses or chloroviruses contain a gene that encodes a function for chitin synthesis, which is expressed early in viral infection to produce chitin polysaccharide, a polymer of β-1, 4-linked GlcNAc, on the outside of Chlorella cell wall. Interestingly, chlorovirus system is an eco-friendly system which converses CO2 and solar energy from the environment into useful materials. However, infected Chlorella cells are lysed at the final stage of viral infection, and this phenomenon is caused the breaking down of polysaccharide. To postpone the lysing period and prolong the synthesis of chitin polysaccharide on cells, the slow growing virus incorporated with aphidicolin treatment, an inhibitor of DNA synthesis, was investigated. In this study, a total of 25 virus isolates from water samples in Japan region were analyzed for CHS (the gene for CH synthase) gene by PCR (polymerase chain reaction). The accumulation and appearance of chitin polysaccharide on infected cells were detected by biotinylated chitin-binding proteins WGA (wheat germ agglutinin)-biotin for chitin in conjunction with avidin-Cy 2 or Cy 3 and investigated by fluorescence microscopy, observed as green or yellow fluorescence over the cell surface. Among all chlorovirus isolates, cells infected with CNF1 revealed the accumulation of chitin over the cell surface within 30 min p.i. and continued to accumulate on cells until 4 h p.i. before cell lyses which was 1.6 times longer accumulation period than cells infected with CVK2 (prototype virus). Furthermore, addition of aphidicolin could extend the chitin accumulation on cells infected with CNF1 until 8 h p.i. before cell lyses. Whereas, CVK2-infected cells treated with aphidicolin could prolong the chitin synthesis only for 6 h p.i. before cell lyses. Therefore, chitin synthesis by Chlorella-virus system could be prolonged by using slow-growing viral isolates and with aphidicolin.

Keywords: chitin, chlorovirus, Chlorella virus, aphidicolin

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Authors: Sunday Paul Bako, Augustine Uwanekwu Ezealor, Yahuza Tanimu

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In a study to evaluate the response of indigenous ruderal plants to the metal deposition regime imposed by anthropogenic modification in the Southern Guinea Savanna of north Western Nigeria during the dry and wet seasons, herbaceous plants and samples of soils were collected in three 5m by 5m quadrats laid around the environs of the Kaduna Refinery and Petrochemical Company and the banks of River Kaduna. Heavy metal concentration (Cd, Ni, Cr, Cu, Fe, Mn and Zn) in soil and plant samples was determined using Energy Dispersive X-ray Fluorescence. Concentrations of heavy metals in soils were generally observed to be higher during the wet season in both locations although the differences were not statistically significant (P > 0.05). Concentrations of Cd, Zn, Cr, Cu and Ni in all the plants observed were found to be below levels described as phytotoxic to plants. However, above ‘normal’ concentrations of Cr was observed in most of the plant species sampled. The concentrations of Cr, Cu, Ni and Zn in soils around the KRPC and RKB were found to be above the acceptable limits. Although no hyper accumulator plant species was encountered in this study, twenty (20) plant species were identified to have high bioconcentration (BCF > 1.0) of Cd and Cu, which indicated tolerance of these plants to excessive or phytotoxic concentrations of these metals. In addition, they generally produce high above ground biomass, due to rapid vegetative growth. These are likely species for phytoextraction. Elevated concentration of metals in both soil and plant materials may cause a decrease in biodiversity due to direct toxicity. There are also risks to humans and other animals due to bioaccumulation across the food chain. There are further possibilities of further evaluating and genetically improving metal tolerance traits in some of these plant species in relation to their potential use in phytoremediation programmes in metal polluted sites.

Keywords: bioprospecting, phytoremediation, heavy metals, Nigeria

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Authors: Tiziana Biasutti, Daniela Rigamonti, Lorenzo Palmiotti, Adelaide Nespoli, Paolo Bettini

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Aerospace industry is based on the continuous development of new technologies and solutions that allows constant improvement of the systems. Shape Memory Alloys are smart materials that can be used as dampers due to their pseudoelastic effect. The purpose of the research was to design a passive damper in Nitinol, manufactured by Selective Laser Melting, for space applications to reduce vibration between different structural parts in space structures. The powder is NiTi (50.2 at.% of Ni). The structure manufactured by additive technology allows us to eliminate the presence of joint and moving parts and to have a compact solution with high structural strength. The designed dampers had single or double cell structures with three different internal angles (30°, 45° and 60°). This particular shape has damping properties also without the pseudoelastic effect. For this reason, the geometries were reproduced in different materials, SS316L and Ti6Al4V, to test the geometry loss factor. The mechanical performances of these specimens were compared to the ones of NiTi structures, pointing out good damping properties of the designed structure and the highest performances of the NiTi pseudoelastic effect. The NiTi damper was mechanically characterized by static and dynamic tests and with DSC and microscope observations. The experimental results were verified with numerical models and with some scaled steel specimens in which optical fibers were embedded. The realized structure presented good mechanical and damping properties. It was observed that the loss factor and the dissipated energy increased with the angles of the cells.

Keywords: additive manufacturing, damper, nitinol, pseudo elastic effect, selective laser melting, shape memory alloys

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: S. Al-Fadala, J. Chakkamalayath, S. Al-Bahar, A. Al-Aibani, S. Ahmed

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Globally, the use of pozzolan in blended cement is gaining great interest due to the desirable effect of pozzolan from the environmental and energy conservation standpoint and the technical benefits they provide to the performance of cement. The deterioration of concrete structures in the marine environment and extreme climates demand the use of pozzolana cement in concrete construction in the Gulf region. Also, natural sources of cement clinker materials are limited in the Gulf region, and cement industry imports the raw materials for the production of Portland cement, resulting in an increase in the greenhouse gas effect due to the CO₂ emissions generated from transportation. Even though the Gulf region has vast deposits of natural pozzolana, it is not explored properly for the production of high performance concrete. Hence, an optimum use of regionally available natural pozzolana for the production of blended cement can result in sustainable construction. This paper investigates the effect of incorporating natural pozzolan sourced from the Gulf region on the performance of blended cement in terms of heat evolution and strength development. For this purpose, a locally produced Ordinary Portland Cement (OPC) and pozzolan-incorporated blended cements containing different amounts of natural pozzolan (volcanic ash) were prepared on laboratory scale. The strength development and heat evolution were measured and quantified. Promising results of strength development were obtained for blends with the percentages of Volcanic Ash (VA) replacement varying from 10 to 30%. Results showed that the heat of hydration decreased with increase in percentage of replacement of OPC with VA, indicating increased retardation in hydration due to the addition of VA. This property could be used in mass concreting in which a reduction in heat of hydration is required to reduce cracking in concrete, especially in hot weather concreting.

Keywords: blended cement, hot weather, hydration, volcanic ash

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Authors: Bishal Saha, Musah Ahmed Rufai Muhyedeen, Jubeyer Hossain Joy, Muhammad Muhitur Rahman, Mohammad Shahedur Rahman, Md Arif Hasan, Syed Masiur Rahman

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Greenhouse gas (GHG) emission is one of the critical problems of today’s world. Many countries have been taking many short- and long-term plans to reduce climate change mitigation. However, the potential of behavioral changes in addressing this problem is promising, as reported by many researchers. This paper presents a comprehensive literature review that focuses on ways to influence people’s behavior in their homes, workplace, and transportation to mitigate the emission directly or indirectly. This study will investigate different theories pertinent to planned behavior and the key elements for modifying behavior like biophilia, reinforcement to use optimum energy and recyclable products, proper application of greenhouse tax, modern technology, and sustainable design adaptation, transportation sharing, social and community norms, proper education and information, and financial incentives. There is a number of challenges associated with behavioral changes. Behavioral interventions have different actions varied by their type and need to combine various policy tools and great social marketing. Many interventions can reduce GHG emissions without any compromise with household well-being. This study will develop a landscape of prevailing theories of environmental psychology by identifying and reviewing the key themes and findings of this field of study. It will support especially the developing countries to reduce GHG emissions without significant capital investment. It is also expected that the behavioral changes will lead to the successful adoption of climate-friendly policies easily. This study will also generate new research questions and directions.

Keywords: behavioral changes, climate change mitigation, environmental psychology, greenhouse gas emission

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Authors: Rasha Ahmadi

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Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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Authors: Elena Listo, Miguel Marchamalo

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This research studies the soil properties located in the watershed of Jabillo River in the Guanacaste province, Costa Rica. The soils are classified as Alfisols (T. Haplustalfs), in the flatter parts with grazing as Fluventic Haplustalfs or as a consequence of bad drainage as F. Epiaqualfs. The objective of this project is to define the status of the soil, to use remote sensing as a tool for analyzing the evolution of land use and determining the water balance of the watershed in order to improve the efficiency of the water collecting systems. Soil samples were analyzed from trial pits taken from secondary forests, degraded pastures, mature teak plantation, and regrowth -Tectona grandis L. F.- species developed favorably in the area. Furthermore, to complete the study, infiltration measurements were taken with an artificial rainfall simulator, as well as studies of soil compaction with a penetrometer, in points strategically selected from the different land uses. Regarding remote sensing, nearly 40 data samples were collected per plot of land. The source of radiation is reflected sunlight from the beam and the underside of leaves, bare soil, streams, roads and logs, and soil samples. Infiltration reached high levels. The majority of data came from the secondary forest and mature planting due to a high proportion of organic matter, relatively low bulk density, and high hydraulic conductivity. Teak regrowth had a low rate of infiltration because the studies made regarding the soil compaction showed a partial compaction over 50 cm. The secondary forest presented a compaction layer from 15 cm to 30 cm deep, and the degraded pasture, as a result of grazing, in the first 15 cm. In this area, the alfisols soils have high content of iron oxides, a fact that causes a higher reflectivity close to the infrared region of the electromagnetic spectrum (around 700mm), as a result of clay texture. Specifically in the teak plantation where the reflectivity reaches values of 90 %, this is due to the high content of clay in relation to others. In conclusion, the protective function of secondary forests is reaffirmed with regards to erosion and high rate of infiltration. In humid climates and permeable soils, the decrease of runoff is less, however, the percolation increases. The remote sensing indicates that being clay soils, they retain moisture in a better way and it means a low reflectivity despite being fine texture.

Keywords: alfisols, Costa Rica, infiltration, remote sensing

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Authors: Samuel Ahamefula Mba

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Fluid turbulence is a complex and nonlinear phenomenon that occurs in various natural and industrial processes. Understanding turbulence remains a challenging task due to its intricate nature. One approach to gain insights into turbulence is through the study of entropy, which quantifies the disorder or randomness of a system. This research presents a numerical investigation of entropy signatures in fluid turbulence. The work is to develop a numerical framework to describe and analyse fluid turbulence in terms of entropy. This decomposes the turbulent flow field into different scales, ranging from large energy-containing eddies to small dissipative structures, thus establishing a correlation between entropy and other turbulence statistics. This entropy-based framework provides a powerful tool for understanding the underlying mechanisms driving turbulence and its impact on various phenomena. This work necessitates the derivation of the Poisson equation for pressure transformation of Navier-Stokes equation and using Chebyshev-Finite Difference techniques to effectively resolve it. To carry out the mathematical analysis, consider bounded domains with smooth solutions and non-periodic boundary conditions. To address this, a hybrid computational approach combining direct numerical simulation (DNS) and Large Eddy Simulation with Wall Models (LES-WM) is utilized to perform extensive simulations of turbulent flows. The potential impact ranges from industrial process optimization and improved prediction of weather patterns.

Keywords: turbulence, Navier-Stokes equation, Poisson pressure equation, numerical investigation, Chebyshev-finite difference, hybrid computational approach, large Eddy simulation with wall models, direct numerical simulation

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Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

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Authors: Mir Md. Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soil and water pollution caused by extensive mining practices can adversely affect environmental components, such as humans, animals, and plants. Despite a generally positive contribution to society, mining practices have become a serious threat to biological systems. As metals do not degrade completely, they require immobilization, toxicity reduction, or removal. A greenhouse experiment was conducted to evaluate the effects of lime and N100 (11-amino-1-hydroxyundecylidene) chelate amendment on the growth and phytoextraction potential of the willow variety Klara (S. viminalis × S. schwerinii × S. dasyclados) grown in soils heavily contaminated with copper (Cu). The plants were irrigated with tap or processed water (mine wastewater). The sequential extraction technique and inductively coupled plasma-mass spectrometry (ICP-MS) tool were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The results suggest that the combined effects of the contaminated soil and processed water inhibited growth parameter values. In contrast, the accumulation of Cu in the plant tissues was increased compared to the control. When the soil was supplemented with lime and N100; growth parameter and resistance capacity were significantly higher compared to unamended soil treatments, especially in the contaminated soil treatments. The combined lime- and N100-amended soil treatment produced higher growth rate of biomass, resistance capacity and phytoextraction efficiency levels relative to either the lime-amended or the N100-amended soil treatments. This study provides practical evidence of the efficient chelate-assisted phytoextraction capability of Klara and highlights its potential as a viable and inexpensive novel approach for in-situ remediation of Cu-contaminated soils and mine wastewaters. Abandoned agricultural, industrial and mining sites can also be utilized by a Salix afforestation program without conflict with the production of food crops. This kind of program may create opportunities for bioenergy production and economic development, but contamination levels should be examined before bioenergy products are used.

Keywords: copper, Klara, lime, N100, phytoextraction

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Authors: Nihel Dib, Redouane Bachir, Ghezlane Berrahou, Chaima Zoulikha Tabet Zatla, Sumeya Bedrane, Ginessa Blanco Montilla, Jose Juan Calvino Gamez

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In recent decades, the world’s population has rapidly increased annually, resulting in the consumption of huge amounts of conventional non-renewable petroleum-based resources at an alarming rate. The scarcity of such resources will shut down the corresponding industries and consequently have negative effects on the well-being of humanity. Accordingly, to combat the forthcoming crises and to serve the ever-growing demands, seeking potentially sustainable resources such as geothermal, wind, solar, and biomass has become an active field of study. Currently, lignocellulosic biomass, one of the world’s most plentiful resources, is acknowledged as a cost-effective material that has drawn great interest from many researchers since it has substantial energy potential as well as containing useful C5 and C6 sugars. These C5 and C6 sugars are the key reactants for the production of the valuable 16-platform chemicals such as 5-hydroxymethyl furfural, furfural, levulinic acid, succinic acid, and fumaric acid, all of which are crucial intermediates for synthesizing high-value bio-based chemicals and polymers. Succinic acid (SA) has been predicted to make a significant contribution to the global bio-based economy soon since it serves as a C4 building block that is used in a wide spectrum of industries, including biopolymers, solvents, and pharmaceuticals. In the present work, we modify the HDL MgAl with Zr to try to create acid sites on the supports and deposit gold by deposition precipitation with urea with a low gold content (0.25%). The catalyst was used to produce succinic acid by selective oxidation of furfuraldehyde with hydrogen peroxide under mild reaction conditions.

Keywords: hydrotalcite, catalysis, gold, biomass, furfural, oxidation

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Authors: Ayodele A. Otaiku

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Purpose: Nigeria has become the largest importer of rice in Africa and second in the world, 2015. Investigate interactions of organic rice farming on soil quality and health from bio-waste converted to biofertilizer and its environmental impact on rice crop. Methodology: Bio-wastes, poultry waste, organic agriculture wastes, wood ash mixed with microbial inoculant organisms called OBD-Plus microbes (broad spectrum) composted in anaerobic digester to OBD-biofertilizer (2010 - 2012) uses microbes to build humus and other stable carbons. Two field experiments were carried out at Badeggi, Niger state in 2011 and 2012 to evaluate the response of lowland rice production using biofertilizer. The experimental field was laid out in a strip-plot design with five treatments and three replications and at twenty-one day old seedlings of FARO 44 and FARO 52 rice varieties were transplanted. Plots without fertiliser application served as control. Findings: The highest rice grain yield increase of 4.4 t/ha over the control in 2012 against the Nigeria average of lowland rice grain yields of 1.5 t/ha. The utilization of OBD-Biofertilizer can decrease the use of chemical nitrogen fertilizer, prevent the depletion of soil organic matter and reduce environmental pollution. Increasing the floodwater productivity and optimizing the recycling of nutrients cum grazer populations and disease by biocontrols microbes present in the OBD-Biofertilizer. Organic matter in the soil improves by 58% and C/N 15 (2011) and 13.35 (2012). Implications: OBD- Biofertilizer produce plant growth hormones such as indole acetic acid (IAA), glomalin related soil protein and extracellular enzymes as phosphatases that promote soil health and quality. Conclusion: Microorganisms can enhance nutrients use efficiency by increasing root surface area e.g., mycorrhizal, fungi, promoting other beneficial symbioses of the host plant and microbial interactions resulting to increase in soil organic matter. By 2030, climate change is projected to depress cereal production in Africa by 2 to 3 percent. Improved seeds and increased fertilizer use should more than compensate, but this factor will still weigh heavily on efforts to make progress.

Keywords: OBD-plus microbial consortia, OBD-biofertilizer, rice production, soil quality, sustainable agriculture

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Authors: Omer Zvi Shaked

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Intimate Partner Violence (IPV) is a widespread social problem. Since the 1970's, and due to political changes resulting from the feminist movement, western society has been changing its attitude towards the phenomenon and has been taking an active approach to reduce its magnitude. Enterprises in the form of legislation, awareness and prevention campaigns, women's shelters, and community intervention programs became more prevalent as years progressed. Although many initiatives were found to be productive, the effectiveness of one, however, remained questionable throughout the years: intervention programs for men's intimate violence. Surveys outline two main intervention models for men's intimate violence. The first is the Duluth model, which argued that men are socialized to be dominant - while women are socialized to be subordinate - and men are therefore required by social imperative to enforce, physically if necessary, their dominance. The Duluth model became the chief authorized intervention program, and some states in the US even regulated it as the standard criminal justice program for men's intimate violence. However, meta-analysis findings demonstrated that based on a partner's reports, Duluth treatment completers have 44% recidivism rate, and between 40% and 85% dropout range. The second model is the Cognitive-Behavioral Model (CBT), which is a highly accepted intervention worldwide. The model argues that cognitive misrepresentations of intimate situations precede violent behaviors frequently when anger predisposition exists. Since anger dysregulation mediates between one's cognitive schemes and violent response, anger regulation became the chief purpose of the intervention. Yet, a meta-analysis found only a 56% risk reduction for CBT interventions. It is, therefore, crucial to understand the background behind the domination of both the Duluth model and CBT interventions. This presentation will discuss the ways in which theoretical conceptualizations of men's intimate violence, as well as ideologies, had contributed to the above-mentioned interventions' wide acceptance, despite known lack of scientific and evidential support. First, the presentation will review the prominent interventions for male intimate violence, the Duluth model, and CBT. Second, the presentation will review the prominent theoretical models explaining men's intimate violence: The Patriarchal model, the Abusive Personality model, and the Post-Traumatic Stress model. Third, the presentation will discuss the interrelation between theory and practice, and the nature of affinity between research and practice regarding men's intimate violence. Finally, the presentation will set new directions for further research, aiming to improve intervention's efficiency with men's intimate violence and advance social work practice in the field.

Keywords: intimate partner violence, theory and practice relationship, Duluth, CBT, abusive personality, post-traumatic stress

Procedia PDF Downloads 116

Authors: M. M. Tawfik, Ezzat M. Abd El Lateef, B. B. Mekki, Amany A. Bahr, Magda H. Mohamed, Gehan S. Bakhoom

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The rapid increase in the world’s population coupled by decrease the arable land per capita has resulted into an increased demand for food which has in turn led to the production of large amounts of agricultural wastes, both at the farmer, municipality and city levels. Agricultural wastes can be a valuable resource for improving food security. Unfortunately, agricultural wastes are likely to cause pollution to the environment or even harm to human health. This calls for increased public awareness on the benefits and potential hazards of agricultural wastes, especially in developing countries. Agricultural wastes (residual stalks, straw, leaves, roots, husks, shells etcetera) and animal waste (manures) are widely available, renewable and virtually free, hence they can be an important resource. They can be converted into heat, steam, charcoal, methanol, ethanol, bio diesel as well as raw materials (animal feed, composting, energy and biogas construction etcetera). agricultural wastes are likely to cause pollution to the environment or even harm to human health, if it is not used in a sustainable manner. Organic wastes could be considered an important source of biofertilizer for enhancing food security in the small holder farming communities that would not afford use of expensive inorganic fertilizers. Moreover, these organic wastes contain high levels of nitrogen, phosphorus, potassium, and organic matter important for improving nutrient status of soils in urban agriculture. Organic compost leading to improved crop yields and its nutritional values as compared with inorganic fertilization. This paper briefly reviews how agricultural wastes can be used to enhance food security and conserve the environment.

Keywords: agricultural waste, organic compost, environment, valuable resources

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Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

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Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

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Authors: Masoud Irannezhad, Sirpa Rasmus, Saghar Ahmadian, Deliang Chen, Bjorn Klove

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Variability and changes in thermal conditions play a crucial role in functioning of human society, particularly over cold climate regions like Finland. Accordingly, the frost-free season (FFS) parameters in terms of start (FFSS), end (FFSE) and length (FFSL) have substantial effects not only on natural environment (e.g. flora and fauna), but also on human requirements (e.g. agriculture, forestry and energy generation). Applying the 0°C threshold of minimum temperature (Tmin), the FFS was defined as the period between the last spring frost as FFSS and the first fall frost as FFSE. For this study, gridded (10 x 10 km2) daily minimum temperature datasets throughout Finland during 1961-2011 was used to investigate recent spatio-temporal variations and trends in frost-free season (FFS) parameters and their relationships with the well-known large-scale climate teleconnections (CTs). The FFS in Finland naturally increases from north (~60 days) to south (~190 days), in association with earlier FFSS (~24 April) and later FFSE (~30 October). Statistically significant (p<0.05) trends in FFSL were all positive (increasing) ranged between 0 and 13.5 (days/decade) and mainly observed in the east, upper west, centre and upper north of Finland. Such lengthening trends in FFS were attributable to both earlier FFSS and later FFSE mostly over central and upper northern Finland, while only to later FFSE in eastern and upper western parts. Variations in both FFSL and FFSS were significantly associated with the Polar (POL) pattern over northern Finland, while with the East Atlantic (EA) pattern over eastern and upper western areas. However, the POL and Scandinavia (SCA) patterns were most influential CTs for FFSE variability over northern Finland.

Keywords: climate teleconnections, Finland, frost-free season, trend analysis

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Authors: Anupama Sahoo, Bongyong Lee, Katia Boniface, Julien Seneschal, Sanjaya K. Sahoo, Tatsuya Seki, Chunyan Wang, Soumen Das, Xianlin Han, Michael Steppie, Sudipta Seal, Alain Taieb, Ranjan J. Perera

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Vitiligo is a common, chronic skin disorder characterized by loss of epidermal melanocytes and progressive depigmentation. Vitiligo has a complex immune, genetic, environmental, and biochemical etiology, but the exact molecular mechanisms of vitiligo development and progression, particularly those related to metabolic control, are poorly understood. Here we characterized the human vitiligo cell line PIG3V and the normal human melanocytes, HEM-l by RNA-sequencing, targeted metabolomics, and shotgun lipidomics. Melanocyte-enriched miR-211, a known metabolic switch in non-pigmented melanoma cells, was severely downregulated in vitiligo cell line PIG3V and skin biopsies from vitiligo patients, while its novel predicted targets transcriptional co-activator PGC1-α (PPARGC1A), ribonucleotide reductase regulatory subunit M2 (RRM2), and serine-threonine protein kinase TAO1 (TAOK1) were reciprocally upregulated. miR-211 binds to PGC1-α 3’UTR locus and represses it. Although mitochondrial numbers were constant, mitochondrial complexes I, II, and IV and respiratory responses were defective in vitiligo cells. Nanoparticle-coated miR-211 partially augmented the oxygen consumption rate in PIG3V cells. The lower oxygen consumption rate, changes in lipid and metabolite profiles, and increased reactive oxygen species production observed in vitiligo cells appear to be partly due to abnormal regulation of miR-211 and its target genes. These genes represent potential biomarkers and therapeutic targets in human vitiligo.

Keywords: metabolism, microRNA, mitochondria, vitiligo

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 47