Search results for: fuzzy aggregation operator

Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra

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Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.

Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission

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Authors: Madhurima S. Waghmare, Shaleen Singhal

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The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

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Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Marulasiddappa H. B., Pushparajesh Viswanathan

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Day by day, the uses of internal combustion engines (ICE) are deteriorating because of pollution and less fuel availability. In the present scenario, the electric vehicle (EV) plays a major role in the place of an ICE vehicle. The performance of EVs can be improved by the proper selection of electric motors. Initially, EV preferred induction motors for traction purposes, but due to complexity in controlling induction motor, permanent magnet synchronous motor (PMSM) is replacing induction motor in EV due to its advantages. Direct torque control (DTC) is one of the known techniques for PMSM drive in EV to control the torque and speed. However, the presence of torque ripple is the main drawback of this technique. Many control strategies are followed to reduce the torque ripples in PMSM. In this paper, the adaptive neuro-fuzzy inference system (ANFIS) controller technique is proposed to reduce torque ripples and settling time. Here the performance parameters like torque, speed and settling time are compared between conventional proportional-integral (PI) controller with ANFIS controller.

Keywords: direct torque control, electric vehicle, torque ripple, PMSM

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Authors: Vasile Caunii, Andreea D. Serban, Mihaela Ivancia

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The paper presents a new approach in terms of the circular economy of technologies for feeding and aeration of accumulations and water basins for fish farming and aquaculture. Because fish is and will be one of the main foods on the planet, the use of bio-eco-technologies is a priority for all producers. The technologies proposed in the paper want to reduce by a substantial percentage the costs of operation of ponds and water accumulation, using non-polluting technologies with minimal impact on the environment. The paper proposes two innovative, intelligent systems, fully automated that use a common platform, completely eco-friendly. One system is intended to aerate the water of the fish pond, and the second is intended to feed the fish by dispersing an optimal amount of fodder, depending on population size, age and habits. Both systems use a floating platform, regenerative energy sources, are equipped with intelligent and innovative systems, and in addition to fully automated operation, significantly reduce the costs of aerating water accumulations (natural or artificial) and feeding fish. The intelligent system used for feeding, in addition, to reduce operating costs, optimizes the amount of food, thus preventing water pollution and the development of bacteria, microorganisms. The advantages of the systems are: increasing the yield of fish production, these are green installations, with zero pollutant emissions, can be arranged anywhere on the water surface, depending on the user's needs, can operate autonomously or remotely controlled, if there is a component failure, the system provides the operator with accurate data on the issue, significantly reducing maintenance costs, transmit data about the water physical and chemical parameters.

Keywords: bio-eco-technologies, economy, environment, fish

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Authors: Yi Sun, George Ed Rainger, Steve P. Watson

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Background: Beyond the classical roles in haemostasis and thrombosis, platelets are important in the initiation and development of various thrombo-inflammatory diseases. In atherosclerosis and deep vein thrombosis, for example, platelets bridge monocytes with endothelium and form heterotypic aggregates with monocytes in the circulation. This can alter monocyte phenotype by inducing their activation, stimulating adhesion and migration. These interactions involve cell surface receptor-ligand pairs on both cells. This list is likely incomplete as new interactions of importance to platelet biology are continuing to be discovered as illustrated by our discovery of PEAR-1 binding to FcεR1α. Results: We have developed a highly sensitive avidity-based assay to identify novel extracellular interactions among 126 recombinantly-expressed platelet cell surface and secreted proteins involved in platelet aggregation. In this study, we will use this method to identify novel platelet-monocyte interactions. We aim to identify ligands for orphan receptors and novel partners of well-known proteins. Identified interactions will be studied in preliminary functional assays to demonstrate relevance to the inflammatory processes supporting atherogenesis. Conclusions: Platelet-monocyte interactions are essential for the development of thromboinflammatory disease. Up until relatively recently, technologies only allow us to limit our studies on each individual protein interaction at a single time. These studies propose for the first time to study the cell surface platelet-monocyte interactions in a systematic large-scale approach using a reliable screening method we have developed. If successful, this will likely to identify previously unknown ligands for important receptors that will be investigated in details and also provide a list of novel interactions for the field. This should stimulate studies on developing alternative therapeutic strategies to treat vascular inflammatory disorders such as atherosclerosis, DVT and sepsis and other clinically important inflammatory conditions.

Keywords: membrane proteins, large-scale screening, platelets, recombinant expression

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Authors: Kateryna Zharan, Jan C. Bongaerts

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Mining operations are energy intensive, and the share of energy costs in total costs is often quoted in the range of 40 %. Saving on energy costs is, therefore, a key element of any mine operator. With the improving reliability and security of renewable energy (RE) sources, and requirements to reduce carbon dioxide emissions, perspectives for using RE in mining operations emerge. These aspects are stimulating the mining companies to search for ways to substitute fossil energy with RE. Hereby, the main purpose of this study is to present the survey research assessment in matter of finding out the key issues related to the integration of RE into mining activities, based on the mining and renewable energy experts’ opinion. The purpose of the paper is to present the outcomes of a survey conducted among mining and renewable energy experts about the feasibility of RE in mining operations. The survey research has been developed taking into consideration the following categories: first of all, the mining and renewable energy experts were chosen based on the specific criteria. Secondly, they were offered a questionnaire to gather their knowledge and opinions on incentives for mining operators to turn to RE, barriers and challenges to be expected, environmental effects, appropriate business models and the overall impact of RE on mining operations. The outcomes of the survey allow for the identification of factors which favor and disfavor decision-making on the use of RE in mining operations. It concludes with a set of recommendations for further study. One of them relates to a deeper analysis of benefits for mining operators when using RE, and another one suggests that appropriate business models considering economic and environmental issues need to be studied and developed. The results of the paper will be used for developing a hybrid optimized model which might be adopted at mines according to their operation processes as well as economic and environmental perspectives.

Keywords: carbon dioxide emissions, mining industry, photovoltaic, renewable energy, survey research, wind generation

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Authors: Ben Nadler

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Cell adhesion plays a vital role in many cell activities. The motivation to model cell adhesion is to study important biological processes, such as cell spreading, cell aggregation, tissue formation, and cell adhesion, which are very challenging to study by experimental methods alone. This study provides important insight into cell adhesion, which can lead to improve regenerative medicine and tissue formation techniques. In this presentation the biological cells adhesion is mediated by receptors–ligands binding and the diffusivity of the receptor on the cell membrane surface. The ability of receptors to diffuse on the cell membrane surface yields a very unique and complicated adhesion mechanism, which is exclusive to cells. The phospholipid bilayer, which is the main component in the cell membrane, shows fluid-like behavior associated with the molecules’ diffusivity. The biological cell is modeled as a fluid-like membrane with negligible bending stiffness enclosing the cytoplasm fluid. The in-plane mechanical behavior of the cell membrane is assumed to depend only on the area change, which is motivated by the fluidity of the phospholipid bilayer. In addition, the presence of receptors influences on the local mechanical properties of the cell membrane is accounted for by including stress-free area change, which depends on the receptor density. Based on the physical properties of the receptors and ligands the attraction between the receptors and ligands is modeled as a charged-nonpolar which is a noncovalent interaction. Such interaction is a short-range type, which decays fast with distance. The mobility of the receptor on the cell membrane is modeled using the diffusion equation and Fick’s law is used to model the receptor–receptor interactions. The resultant interaction force, which includes receptor–ligand and receptor–receptor interaction, is decomposed into tangential part, which governs the receptor diffusion, and normal part, which governs the cell deformation and adhesion. The formulation of the governing equations and numerical simulations will be presented. Analysis of the adhesion characteristic and properties are discussed. The roles of various thermomechanical properties of the cell, receptors and ligands on the cell adhesion are investigated.

Keywords: cell adhesion, cell membrane, receptor-ligand interaction, receptor diffusion

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Authors: S. L. J. Tan, N. Billa, C. J. Roberts

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Oral delivery of amphotericin B (AmpB) potentially eliminates constraints and side effects associated with intravenous administration, but remains challenging due to the physicochemical properties of the drug such that it results in meagre bioavailability (0.3%). In an advanced formulation, 1) nanostructured lipid carriers (NLC) were formulated as they can accommodate higher levels of cargoes and restrict drug expulsion and 2) a mucoadhesion feature was incorporated so as to impart sluggish transit of the NLC along the gastrointestinal tract and hence, maximize uptake and improve bioavailability of AmpB. The AmpB-loaded NLC formulation was successfully formulated via high shear homogenisation and ultrasonication. A chitosan coating was adsorbed onto the formed NLC. Physical properties of the formulations; particle size, zeta potential, encapsulation efficiency (%EE), aggregation states and mucoadhesion as well as the effect of the variable pH on the integrity of the formulations were examined. The particle size of the freshly prepared AmpB-loaded NLC was 163.1 ± 0.7 nm, with a negative surface charge and remained essentially stable over 120 days. Adsorption of chitosan caused a significant increase in particle size to 348.0 ± 12 nm with the zeta potential change towards positivity. Interestingly, the chitosan-coated AmpB-loaded NLC (ChiAmpB NLC) showed significant decrease in particle size upon storage, suggesting 'anti-Ostwald' ripening effect. AmpB-loaded NLC formulation showed %EE of 94.3 ± 0.02 % and incorporation of chitosan increased the %EE significantly, to 99.3 ± 0.15 %. This suggests that the addition of chitosan renders stability to the NLC formulation, interacting with the anionic segment of the NLC and preventing the drug leakage. AmpB in both NLC and ChiAmpB NLC showed polyaggregation which is the non-toxic conformation. The mucoadhesiveness of the ChiAmpB NLC formulation was observed in both acidic pH (pH 5.8) and near-neutral pH (pH 6.8) conditions as opposed to AmpB-loaded NLC formulation. Hence, the incorporation of chitosan into the NLC formulation did not only impart mucoadhesive property but also protected against the expulsion of AmpB which makes it well-primed as a potential oral delivery system for AmpB.

Keywords: Amphotericin B, mucoadhesion, nanostructured lipid carriers, oral delivery

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Authors: Satya S. N. Narayana, P. Parthiban, T. Niranjan, N. Kannan

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Enterprises adopt methodologies to increase their business performance and to stay competent in the volatile global market. Lean manufacturing is one such manufacturing paradigm which focuses on reduction of cost by elimination of wastes or non-value added activities. With increased awareness about social responsibility and the necessary to meet the terms of the environmental policy, green manufacturing is becoming increasingly important for industries. Large plants have more resources, have started implementing lean and green practices and they are getting good results. Small and medium scale enterprises (SMEs) are facing problems in implementing lean and green concept. This paper aims to identify the key issues for implementation of lean and green concept in Indian SMEs. The key factors identified based on literature review and expert opinions are grouped into different levels by Modified Interpretive Structural Modeling (MISM) to explore the importance among the factors to implement lean and green manufacturing. Finally, Fuzzy Analytic Network Process (FANP) method has been used to determine the extent to which the main principles of lean and green manufacturing have been carried out in the six Indian medium scale manufacturing industries.

Keywords: lean manufacturing, green manufacturing, MISM, FANP

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Authors: Margaret Boone Rappaport, Christopher J. Corbally

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The ancient ape ancestral population from which living great ape and human species evolved had demographic features affecting their evolution. The population was large, had great genetic variability, and natural selection was effective at honing adaptations. The emerging populations of chimpanzees and humans were affected more by founder effects and genetic drift because they were smaller. Natural selection did not disappear, but it was not as strong. Consequences of the 'population crash' and the human effective population size are introduced briefly. The history of the ancient apes is written in the genomes of living humans and great apes. The expansion of the brain began before the human line emerged. Coalescence times for some genes are very old – up to several million years, long before Homo sapiens. The mismatch between gene trees and species trees highlights the anthropoid speciation processes, and gives the human genome history a fuzzy, probabilistic quality. However, it suggests traits that might form a foundation for capacities emerging later. A theoretical model is presented in which the genomes of early ape populations provide the substructure for the emergence of religious capacity later on the human line. The model does not search for religion, but its foundations. It suggests a course by which an evolutionary line that began with prosimians eventually produced a human species with biologically based religious capacity. The model of the sequential emergence of religious capacity relies on cognitive science, neuroscience, paleoneurology, primate field studies, cognitive archaeology, genomics, and population genetics. And, it emphasizes five trait types: (1) Documented, positive selection of sensory capabilities on the human line may have favored survival, but also eventually enriched human religious experience. (2) The bonobo model suggests a possible down-regulation of aggression and increase in tolerance while feeding, as well as paedomorphism – but, in a human species that remains cognitively sharp (unlike the bonobo). The two species emerged from the same ancient ape population, so it is logical to search for shared traits. (3) An up-regulation of emotional sensitivity and compassion seems to have occurred on the human line. This finds support in modern genetic studies. (4) The authors’ published model of morality's emergence in Homo erectus encompasses a cognitively based, decision-making capacity that was hypothetically overtaken, in part, by religious capacity. Together, they produced a strong, variable, biocultural capability to support human sociability. (5) The full flowering of human religious capacity came with the parietal expansion and smaller face (klinorhynchy) found only in Homo sapiens. Details from paleoneurology suggest the stage was set for human theologies. Larger parietal lobes allowed humans to imagine inner spaces, processes, and beings, and, with the frontal lobe, led to the first theologies composed of structured and integrated theories of the relationships between humans and the supernatural. The model leads to the evolution of a small population of African hominins that was ready to emerge with religious capacity when the species Homo sapiens evolved two hundred thousand years ago. By 50-60,000 years ago, when human ancestors left Africa, they were fully enabled.

Keywords: genetic drift, genomics, parietal expansion, religious capacity

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Authors: Masome Moeni, Roya Abedizadeh, Elham Aram, Hamid Sadeghi-Abandansari, Davood Sabour, Robert Menzel, Ali Hassanpour

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Mitochondria- targeting immunogenic cell death inducers (MT-ICD) have been designed to trigger intrinsic apoptosis signalling pathway in malignant cells and revive the antitumour immune system. MT-ICD inducers have considered to be non-specific, which can deteriorate the ability to initiate mitochondria-selective oxidative stress, causing high toxicity. Iron oxide nanoparticles (IONPs) can be an ideal candidate as vehicles for utilizing in immunotherapy due to their biocompatibility, modifiable surface chemistry, magnetic characteristics and multi-functional applications in single platform. These types of NPs can facilitate a real time imaging which can provide an effective strategy to analyse pharmacokinetic parameters of nano-formula, including blood circulation time, targeted and controlled release at tumour microenvironment. To our knowledge, the conjugation of IONPs with MT-ICD and oxaliplatin (a chemotherapeutic agent used for the treatment of colorectal cancer) for immunotherapy have not been investigated. Herein, IONPs were generated via co-precipitation reaction at high temperatures, followed by coating the colloidal suspension with tetraethyl orthosilicate and 3-aminopropyltriethoxysilane to optimize their bio-compatibility, preventing aggregation and maintaining stability at physiological pH, then functionalized with (3-carboxypropyl) triphenyl phosphonium bromide for mitochondrial delivery. Analytical results demonstrated the successful process of IONPs functionalization. In particular, the colloidal particles of doped IONPs exhibited an excellent stability and dispersibility. The resultant particles were also successfully loaded with the oxaliplatin for an active mitochondrial targeting in immunotherapy, resulting in well-maintained super-paramagnetic characteristics and stable structure of the functionalized IONPs with nanoscale particle sizes.

Keywords: Immunotherapy, mitochondria, cancer, iron oxide nanoparticle

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Authors: Hajar Zarei, AliAkbar Zarenejadatashgah, Vuk Uskoković, Hiroshi Watabe

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The reactive oxygen species (ROS) generated by radiation in nuclear diagnostic imaging and radiotherapy could damage the structure of the proteins in noncancerous cells surrounding the tumor. The critical factor in many age-related diseases, such as Alzheimer, Parkinson, or Huntington diseases, is the oxidation of proteins by the ROS as molecular triggers of the given pathologies. Our studies by spectroscopic experiments showed doses close to therapeutic ones (1 to 5 Gy) could lead to changes of secondary and tertiary structures in BSA protein macromolecule as a protein model as well as the aggregation of polypeptide chain but without the fragmentation. For this reason, we investigated the radioprotective effects of natural (vitamin C and E) and synthetic materials (CNPs and FIOMPs) on the structural changes in BSA protein induced by gamma irradiation at a therapeutic dose (3Gy). In the presence of both vitamins and synthetic materials, the spectroscopic studies revealed that irradiated BSA was protected from the structural changes caused by ROS, according to in vitro research. The radioprotective property of CNPs and FIOMPs arises from enzyme mimetic activities (catalase, superoxide dismutase, and peroxidase) and their antioxidant capability against hydroxyl radicals. In the case of FIOMPs, a porous structure also leads to increased ROS recombination with each other in the same radiolytic track and subsequently decreased encounters with BSA. The hydrophilicity of vitamin C resulted in the major scavenging of ROS in the solvent, whereas hydrophobic vitamin E localized on the nonpolar patches of the BSA surface, where it did not only neutralize them thanks to the moderate BSA binding constant but also formed a barrier for diffusing ROS. To the best of our knowledge, there has been a persistent lack of studies investigating the radioactive effect of mentioned materials on proteins. Therefore, the results of our studies can open a new widow for application of these common dietary ingredients and new synthetic NPs in improving the safety of radiotherapy.

Keywords: reactive oxygen species, spectroscopy, bovine serum albumin, gamma radiation, radioprotection

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: Garance Liaboeuf, Alain Le Bot, Ali Daouadji, Antoine Martinet, Mohamed Bouteldja, Nicolas Grignard, Damien Pilet

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As every French road operator, Autoroutes et Tunnel du Mont Blanc (ATMB) conducts annual inspections of its infrastructures. Significant loss of skid resistance has been observed on some sections of his network, sometimes on recent pavements. In the way of making the mechanisms and factors that can lead to this loss of grip more understandable, ATMB has launched a study aimed at identifying the causes and developing solutions to prevent this phenomenon. To quantify the deterioration of different road surfaces subjected to controlled scraping with steel blades of snow removal machines, a field campaign was conducted. These operations are carried out during the winter period according to a strict protocol. In order to correct the skid-resistance values, a control panel is set up. In this way, only the effect of the scraping is taken into account. It allows us to exclude the influence of the environment (temperature, humidity, etc.) and of the surface state on the skid resistance values measured during the different sessions. Skid measurements after eight years of scraping cycles showed a 7% to 13% decrease in microtexture and a 2% to 12% decrease in macrotexture adhesion. These reductions are attributed to the phenomenon of polishing road surfaces by using steel blades. Also, regeneration phenomena occur after a certain number of blades pass. Differences in steel scraper blade resistance appear related to the intrinsic properties of the aggregate used in the pavement formulation and its type. Finally, the results of this campaign will allow the determination of the resistance characteristics of the pavement damage by the steel blade of snow plows. An evolution law of the surface condition as a function of the scraping operations will also be developed from this study.

Keywords: pavement, skid, surface, snow plow

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Authors: Małgorzata Tomczyńska, Joanna Saluk-Bijak

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Background: Graves’ disease is a frequent organ-specific autoimmune thyroid disease, which characterized by the presence of different kind autoantibodies, that, in most cases, act as agonists of the thyrotropin receptor, leading to hyperthyroidism. Role of platelets and lymphocytes can be modulated in the pathophysiology of thyroid autoimmune diseases. Interference in the physiology of platelets can lead to enhanced activity of these cells. Activated platelets can bind to circulating lymphocytes and to affect lymphocyte adhesion. Platelets and lymphocytes can regulate mutual functions. Therefore, the activation of T lymphocytes, as well as blood platelets, is associated with the development of inflammation and oxidative stress within the target tissue. The present study was performed to investigate a platelet-lymphocyte relation by assessing the degree of their mutual aggregation in whole blood of patients with Graves’ disease. Also, the purpose of this study was to examine the impact of platelet interaction on lymphocyte migration capacity. Methods: 30 patients with Graves’ disease were recruited in the study. The matched 30 healthy subjects were served as the control group. Immunophenotyping of lymphocytes was carried out by flow cytometry method. A CytoSelect™ Cell Migration Assay Kit was used to evaluate lymphocyte migration and adhesion to blood platelets. Visual assessment of lymphocyte-platelet aggregate morphology was done using confocal microscope after magnetic cell isolation by Miltenyi Biotec. Results: The migration and functional responses of lymphocytes to blood platelets were greater in the group of Graves’ disease patients compared with healthy controls. The group of Graves’ disease patients exhibited a reduced T lymphocyte and a higher B cell count compared with controls. Based on microscopic analysis, more platelet-lymphocyte aggregates were found in patients than in control. Conclusions: Studies have shown that in Graves' disease, lymphocytes show increased platelet affinity, more strongly migrating toward them, and forming mutual cellular conglomerates. This may be due to the increased activation of blood platelets in this disease.

Keywords: blood platelets, cell migration, Graves’ disease, lymphocytes, lymphocyte-platelet aggregates

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Authors: P. Valsalal, S. Thangalakshmi

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There is a widespread changeover in the electrical power industry universally from old-style monopolistic outline towards a horizontally distributed competitive structure to come across the demand of rising consumption. When the transmission lines of derestricted system are incapable to oblige the entire service needs, the lines are overloaded or congested. The governor between customer and power producer is nominated as Independent System Operator (ISO) to lessen the congestion without obstructing transmission line restrictions. Among the existing approaches for congestion management, the frequently used approaches are reorganizing the generation and load curbing. There is a boundary for reorganizing the generators, and further loads may not be supplemented with the prevailing resources unless more private power producers are added in the system by considerably raising the cost. Hence, congestion is relaxed by appropriate Flexible AC Transmission Systems (FACTS) devices which boost the existing transfer capacity of transmission lines. The FACTs device, namely, Unified Power Flow Controller (UPFC) is preferred, and the correct placement of UPFC is more vital and should be positioned in the highly congested line. Hence, the weak line is identified by using power flow performance index with the new objective function with proposed hybrid Fish – Bee algorithm. Further, the location of UPFC at appropriate line reduces the branch loading and minimizes the voltage deviation. The power transfer capacity of lines is determined with and without UPFC in the identified congested line of IEEE 30 bus structure and the simulated results are compared with prevailing algorithms. It is observed that the transfer capacity of existing line is increased with the presented algorithm and thus alleviating the congestion.

Keywords: available line transfer capability, congestion management, FACTS device, Hybrid Fish-Bee Algorithm, ISO, UPFC

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

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To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

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Authors: Salihah Alghamdi, Surajit Ray

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Space-time data can be observed over irregularly shaped manifolds, which might have complex boundaries or interior gaps. Most of the existing methods do not consider the shape of the data, and as a result, it is difficult to model irregularly shaped data accommodating the complex domain. We used a method that can deal with space-time data that are distributed over non-planner shaped regions. The method is based on partial differential equations and finite element analysis. The model can be estimated using a penalized least squares approach with a regularization term that controls the over-fitting. The model is regularized using two roughness penalties, which consider the spatial and temporal regularities separately. The integrated square of the second derivative of the basis function is used as temporal penalty. While the spatial penalty consists of the integrated square of Laplace operator, which is integrated exclusively over the domain of interest that is determined using finite element technique. In this paper, we applied a spatio-temporal regression model with partial differential equations regularization (ST-PDE) approach to analyze a remote sensing data measuring the greenness of vegetation, measure by an index called enhanced vegetation index (EVI). The EVI data consist of measurements that take values between -1 and 1 reflecting the level of greenness of some region over a period of time. We applied (ST-PDE) approach to irregular shaped region of the EVI data. The approach efficiently accommodates the irregular shaped regions taking into account the complex boundaries rather than smoothing across the boundaries. Furthermore, the approach succeeds in capturing the temporal variation in the data.

Keywords: irregularly shaped domain, partial differential equations, finite element analysis, complex boundray

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Shailendra Natraj, Kristin Paetzold, B. R. Katzy

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The significant role of technology in strategic business decisions has created the need for executives who understand technology and recognize profitable applications to products, services and processes. The role of CTO’s is very complex within technology-based firms, which stretches from the technology aspects to the strategic goal and vision of the firm. Often the roles of CTOs scales from as functional leaders, strategic leaders or supera- functional leaders. In most of the companies the roles are unclear and fuzzy. We in our research are trying to explore each of the orientation and link between leadership types (functional, strategic and super functional) of CTOs, responsibilities, credibility and strategic and conceptual responsibilities. Approach: We conducted a comprehensive literature review with the available databank sources. Results: From the conducted literature review we could identify that most of the research work conducted so far were mainly distributed between roles and responsibilities of CTOs. The available sources pointed were limited to roles of CTOs as functional leaders. Contribution: In our findings based on the literature review, we could identify that apart from the conducted research what so far has not been focused yet are (a) The leadership types (mainly) strategic and super-functional leaders) of CTOs, (b) the responsibilities and credibility of CTOs and (c) the strategic and conceptual responsibilities of CTOs.

Keywords: CTO, chief technology officer, strategy, technology leaders

Procedia PDF Downloads 490

Authors: Albert Alexander Stonier

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Due to the fossil fuel exhaustion and environmental pollution, renewable energy sources especially solar photovoltaic system plays a predominant role in providing energy to the consumers. It has been estimated that by 2050 the renewable energy sources will satisfy 50% of the total energy requirement of the world. In this context, the faults in the conversion process require a special attention which is considered as a major problem. A fault which remains even for a few seconds will cause undesirable effects to the system. The presentation comprises of the analysis, causes, effects and mitigation methods of various faults occurring in the entire solar photovoltaic energy conversion process. In order to overcome the faults in the system, an intelligent based artificial neural networks and fuzzy logic are proposed which can significantly mitigate the faults. Hence the presentation intends to find the problem in renewable energy and provides the possible solution to overcome it with simulation and experimental results. The work performed in a 3kWp solar photovoltaic plant whose results cites the improvement in reliability, availability, power quality and fault tolerant ability.

Keywords: solar photovoltaic, power electronics, power quality, PWM

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Authors: Lynn Louis, Bor Shin Chee, Marion McAfee, Michael Nugent

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This article aims to develop a sustained release formulation of microspheres containing the mTOR inhibitor Everolimus (EVR) using Polyvinyl alcohol (PVA) to enhance the bioavailability of the drug and to overcome poor solubility characteristics of Everolimus. This paper builds on recent work in the manufacture of microspheres using the sessile droplet technique by freezing the polymer-drug solution by suspending the droplets into pre-cooled ethanol vials immersed in liquid nitrogen. The spheres were subjected to 6 freezing cycles and 3 freezing cycles with thawing to obtain proper geometry, prevent aggregation, and achieve physical cross-linking. The prepared microspheres were characterised for surface morphology by SEM, where a 3-D porous structure was observed. The in vitro release studies showed a 62.17% release over 12.5 days, indicating a sustained release due to good encapsulation. This result is comparatively much more than the 49.06% release achieved within 4 hours from the solvent cast Everolimus film as a control with no freeze-thaw cycles performed. The solvent cast films were made in this work for comparison. A prolonged release of Everolimus using a polymer-based drug delivery system is essential to reach optimal therapeutic concentrations in treating SEGA tumours without systemic exposure. These results suggest that the combination of PVA and Everolimus via a rheological synergism enhanced the bioavailability of the hydrophobic drug Everolimus. Physical-chemical characterisation using DSC and FTIR analysis showed compatibility of the drug with the polymer, and the stability of the drug was maintained owing to the high molecular weight of the PVA. The obtained results indicate that the developed PVA/EVR microsphere is highly suitable as a potential drug delivery system with improved bioavailability in treating Subependymal Giant cell astrocytoma (SEGA).

Keywords: drug delivery system, everolimus, freeze-thaw cycles, polyvinyl alcohol

Procedia PDF Downloads 96

Authors: Huseyin A. Yavasoglu, Yusuf Ziya Tengiz, Ali Göksenli

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In this study, an automatic feeding machine for different type and class of bovine animals is designed. Daily nutrition of a bovine consists of grass, corn, straw, silage, oat, wheat and different vitamins and minerals. The amount and mixture amount of each of the nutrition depends on different parameters of the bovine. These parameters are; age, sex, weight and maternity of the bovine, also outside temperature. The problem in a farm is to constitute the correct mixture and amount of nutrition for each animal. Faulty nutrition will cause an insufficient feeding of the animal concluding in an unhealthy bovine. To solve this problem, a new automatic feeding machine is designed. Travelling of the machine is performed by four tires, which is pulled by a tractor. The carrier consists of eight bins, which each of them carries a nutrition type. Capacity of each unit is 250 kg. At the bottom of each chamber is a sensor measuring the weight of the food inside. A funnel is at the bottom of each chamber by which open/close function is controlled by a valve. Each animal will carry a RFID tag including ID on its ear. A receiver on the feeding machine will read this ID and by given previous information by the operator (veterinarian), the system will detect the amount of each nutrition unit which will be given to the selected animal for feeding. In the system, each bin will open its exit gate by the help of the valve under the control of PLC (Programmable Logic Controller). The amount of each nutrition type will be controlled by measuring the open/close time. The exit canals of the bins are collected in a reservoir. To achieve a homogenous nitration, the collected feed will be mixed by a worm gear. Further the mixture will be transported by a help of a funnel to the feeding unit of the animal. The feeding process can be performed in 100 seconds. After feeding of the animal, the tractor pulls the travelling machine to the next animal. By the help of this system animals can be feeded by right amount and mixture of nutrition

Keywords: bovine, feeding, nutrition, transportation, automatic

Procedia PDF Downloads 324

Authors: Victoria I. Michailova, Denitsa B. Momekova, Hristiana A. Velichkova, Evgeni H. Ivanov

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The aim of this work is to design and develop thermo-responsive nanosized drug delivery systems based on poly(N-isopropylacrylamide)-g-poly(ethylene oxide) (PNIPAM-g-PEO) double hydrophilic graft copolymers. The PNIPAM-g-PEO copolymers are able to self-assemble in water into nanoparticles above the LCST of the thermo-responsive PNIPAM backbone and to disassemble and rapidly release the entrapped drugs upon cooling. However, their drug delivery applications are often hindered by their low loading capacity as the drugs to be encapsulated do not dissolve in water. In order to overcome this limitation, here we applied a low-temperature procedure with ethanol as an alternative route to the formation and loading a model hydrophobic drug, Indomethacin (IMC), into PNIPAM-g-PEO nanoparticles. The rationale for this approach was that ethanol dissolves both IMC and the copolymer and its mixing with water may induce micellization of PNIPAM-g-PEO at temperatures lower than the LCST. The influence of the volume fraction of ethanol and the temperature on the aggregation characteristics of PNIPAM-g-PEO copolymers (2.7 mol% PEO) was investigated by means of DLS, TEM and rheological dynamic oscillatory tests. The studies showed rich phase behavior at T < LCST, incl. the formation of highly solvated 500-1000 nm complex structures, 30-70 nm micelles and polymersomes as well as giant polymersomes, as the fraction of added ethanol increased. We believe that the PNIPAM-g-PEO self-assembly is favored due to the different solvation of its constituting blocks in ethanol-water mixtures. The incorporation of IMC led to alteration of the physicochemical and morphological characteristics of the blank nanoparticles. In this case, only monodisperse polymersomes and micelles were observed in the solutions with an average diameter less than 65 nm and substantial drug loading (DLC ~117 – 146 wt%). Indomethacin release from the nanoparticles was responsive to temperature changes, being much faster at a temperature of 42oC compared to that of 37oC under otherwise the same conditions. The results obtained suggest that these PNIPAM-g-PEO nanoparticles could be potential in mild hyper-thermic delivery of nonsteroidal anti-inflammatory drugs.

Keywords: drug delivery, nanoparticles, poly(N-isopropylacryl amide)-g-poly(ethylene oxide), thermo-responsive

Procedia PDF Downloads 263

Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

Procedia PDF Downloads 47

Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

Procedia PDF Downloads 63

Authors: Nebiyou Masebo

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The severities of land degradation in southern Ethiopia has been increasing due to high population density, replacement of an age-old agroforestry (AF) based agricultural system with monocropping. The consequences of these activities combined with climate change have been impaired soil biota, soil organic carbon (SOC), soil glomalin, soil aggregation and aggregate stability. The AF systems could curb these problems due it is an ecologically and economically sustainable. This study was aimed to determine the effect of agroforestry practices (AFPs) on soil glomalin, soil aggregate stability (SAS), and aggregate association with SOC. Soil samples (from two depth level: 0-30 & 30-60 cm) and woody species were collected from homegarden based agroforestry practice (HAFP), cropland based agroforestry practice (ClAFP), woodlot based agroforestry practice (WlAFP) and trees on soil and water conservation based agroforestry practice (TSWAFP) using systematic sampling. In this study, both easily extractable glomalin related soil protein (EEGRSP) and total glomalin related soil protein (TGRSP) were significantly (p<0.05) higher in HAFP compared to others, with decreasing order HAFP>WlAFP>TSWAFP>ClAFP at upper surface but in subsurface in decreasing order: WlAFP>HAFP>TSWAFP>ClAFP. On the other hand, the macroaggregate fraction of AFPs ranged from 22.64-36.51% where the lowest was in ClAFP, while the highest was in HAFP, moreover, the order for subsurface was also the same but SAS decreased with the increasing of soil depths. The micro-aggregate fraction ranged from 15.9–24.56%, where the lowest was in HAFP, but the highest was in ClAFP. Besides, the association of OC with both macro-and micro-aggregates was greatest in HAFP and followed by WlAFP. The findings also showed that both glomalin and SAS were significantly high with woody species diversity and richness. Thus, AFP with good management practice can play role on maintenance of biodiversity, glomalin content and other soil quality parameters with future implications for a stable ecosystem.

Keywords: agroforestry, soil aggregate stability, glomalin, aggregate-associated carbon, HAFP, ClAFP, WlAFP, TSWAFP.

Procedia PDF Downloads 72