Search results for: functional optimization

Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

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Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

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Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

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In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Ammar Boudaka, Maryam Al-Suleimani, Hajar BaOmar, Intisar Al-Lawati, Fahad Zadjali

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Background: Hypertension is increasingly becoming a matter of medical and public health importance. The maintenance of normal blood pressure requires a balance between cardiac output and total peripheral resistance. The endothelium, through the release of vasodilating factors, plays an important role in the control of total peripheral resistance and hence blood pressure homeostasis. Transient Receptor Potential Vanilloid type 4 (TRPV4) is a mechanosensitive non-selective cation channel that is expressed on the endothelium and contributes to endothelium-mediated vasodilation. So far, no data are available about the morphological and functional status of this channel in hypertensive cases. Objectives: This study aimed to investigate whether there is any difference in the morphological and functional features of TRPV4 in the mesenteric artery of normotensive and hypertensive rats. Methods: Functional feature of TRPV4 in four experimental animal groups: young and adult Wistar-Kyoto rats (WKY-Y and WKY-A), young and adult spontaneously hypertensive rats (SHR-Y and SHR-A), was studied by adding 5 µM 4αPDD (TRPV4 agonist) to mesenteric arteries mounted in a four-chamber wire myograph and pre-contracted with 4 µM phenylephrine. The 4αPDD-induced response was investigated in the presence and absence of 1 µM HC067047 (TRPV4 antagonist), 100 µM L-NAME (nitric oxide synthase inhibitor), and endothelium. The morphological distribution of TRPV4 in the wall of rat mesenteric arteries was investigated by immunostaining. Real-time PCR was used in order to investigate mRNA expression level of TRPV4 in the mesenteric arteries of the four groups. The collected data were expressed as mean ± S.E.M. with n equal to the number of animals used (one vessel was taken from each rat). To determine the level of significance, statistical comparisons were performed using the student’s t-test and considered to be significantly different at p<0.05. Results: 4αPDD induced a relaxation response in the mesenteric arterial preparations (WKY-Y: 85.98% ± 4.18; n = 5) that was markedly inhibited by HC067047 (18.30% ± 2.86; n= 5; p<0.05), endothelium removal (19.93% ± 1.50; n = 5; p<0.05) and L-NAME (28.18% ± 3.09; n = 5; p<0.05). The 4αPDD-induced relaxation was significantly lower in SHR-Y compared to WKY-Y (SHR-Y: 70.96% ± 3.65; n = 6, WKY-Y: 85.98% ± 4.18; n = 5-6, p<0.05. Moreover, the 4αPDD-induced response was significantly lower in WKY-A than WKY-Y (WKY-A: 75.58 ± 1.30; n = 5, WKY-Y: 85.98% ± 4.18; n = 5, p<0.05). Immunostaining study showed immunofluorescent signal confined to the endothelial layer of the mesenteric arteries. The expression of TRPV4 mRNA in SHR-Y was significantly lower than in WKY-Y (SHR-Y; 0.67RU ± 0.34; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Furthermore, TRPV4 mRNA expression in WKY-A was lower than its expression in WKY-Y (WKY-A: 0.62RU ± 0.37; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Conclusion: Stimulation of TRPV4, which is expressed on the endothelium of rat mesenteric artery, triggers an endothelium-mediated relaxation response that markedly decreases with hypertension and growing up changes due to downregulation of TRPV4 expression.

Keywords: hypertension, endothelium, mesenteric artery, TRPV4

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Huanhuan Qiang, Sijia Jin

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Population aging has become a global trend, and China has entered an aging society, implementing an active aging system focused on home and community-based care. However, most urban communities where elderly people live face issues such as monotonous planning, unappealing landscapes, and inadequate aging infrastructure, which do not meet the requirements for active aging. Intergenerational friendliness and mutual assistance are key components in China's active aging policy framework. Therefore, residential development should prioritize enhancing intergenerational friendliness. Residential and public spaces are central to community life and well-being, offering new and challenging venues to improve relationships among residents of different ages. They are crucial for developing intergenerational communities with diverse generations and non-blood relationships. This paper takes the Maigaoqiao community in Nanjing, China, as a case study, examining intergenerational interactions in public spaces. Based on Maslow's hierarchy of needs and using time geography analysis, it identifies the spatiotemporal behavior characteristics of intergenerational groups in outdoor activities. Then construct an intergenerational-friendly evaluation system and an IPA quadrant model for public spaces in residential areas. Lastly, it explores optimization strategies for public spaces to promote intergenerational friendly interactions, focusing on five aspects: accessibility, safety, functionality, a sense of belonging, and interactivity.

Keywords: intergenerational friendliness, demand theory, spatiotemporal behavior, IPA analysis, existing residential public space

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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Authors: Debasis Sengupta, Sudipta Das

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The class of life distributions with decreasing mean residual life (DMRL) is well known in the field of reliability modeling. It contains the IFR class of distributions and is contained in the NBUE class of distributions. While upper and lower bounds of the reliability distribution function of aging classes such as IFR, IFRA, NBU, NBUE, and HNBUE have discussed in the literature for a long time, there is no analogous result available for the DMRL class. We obtain the upper and lower bounds for the reliability function of the DMRL class in terms of first order finite moment. The lower bound is obtained by showing that for any fixed time, the minimization of the reliability function over the class of all DMRL distributions with a fixed mean is equivalent to its minimization over a smaller class of distribution with a special form. Optimization over this restricted set can be made algebraically. Likewise, the maximization of the reliability function over the class of all DMRL distributions with a fixed mean turns out to be a parametric optimization problem over the class of DMRL distributions of a special form. The constructive proofs also establish that both the upper and lower bounds are sharp. Further, the DMRL upper bound coincides with the HNBUE upper bound and the lower bound coincides with the IFR lower bound. We also prove that a pair of sharp upper and lower bounds for the reliability function when the distribution is increasing mean residual life (IMRL) with a fixed mean. This result is proved in a similar way. These inequalities fill a long-standing void in the literature of the life distribution modeling.

Keywords: DMRL, IMRL, reliability bounds, hazard functions

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Authors: S. Beekrum, B. Odhav, R. Lalloo, E. A. Amonsou

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Marine microalgae are rich sources of novel and biologically active metabolites; therefore they may be used in the food industry as natural food ingredients and functional foods. They have several biological applications related to health benefits, among others. The aim of the study focused on the screening of phytochemicals from Amphora sp. biomass extracts, and to examine the in vitro antioxidant and antimicrobial potential. Amphora sp. biomass was obtained from CSIR (South Africa) and methanol, hexane and water extracts were prepared. The in vitro antimicrobial effect of extracts were tested against some pathogens (Staphylococcus aureus, Listeria monocytogenes, Bacillus subtilis, Salmonella enteritidis, Escherichia coli, Pseudomonas aeruginosa and Candida albicans), using the disc diffusion assay. Qualitative analyses of phytochemicals were conducted by chemical tests. The present investigation revealed that all extracts showed relatively strong antibacterial activity against most of the tested bacteria. The highest phenolic content was found in the methanolic extract. Results of the DPPH assay showed that the biomass contained strong antioxidant capacity, 79% in the methanolic extract and 85% in the hexane extract. Extracts have displayed effectively reducing power and superoxide anion radical scavenging activity. Results of this study have highlighted potential antioxidant activity in the methanol and hexane extracts. The results of the phytochemical screening showed the presence of terpenoids and sterols with potential applications as food flavorants and functional foods, respectively. The use of Amphora sp. as a natural antioxidant source and a potential source of antibacterial compounds and phytochemicals in the food industry appears promising and should be investigated further.

Keywords: antioxidants, antimicrobial, microalgae, phytochemicals, cymbella

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Authors: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Khenenou Tarek, Mohamed Amine Fares, Djallal Eddine Rahmoun

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The study intends to evaluate the morphological changes in the mesenteric lymph nodes of dromedaries in different rearing systems. we aimed to evaluate the adaptative behavior of the animal’s immune system with environmental variations, and to conduct a comparative analysis on the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued, with two different rearing systems, with different practices and different purposes. The study was conducted using histo-morphometric techniques to analyze the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued. Two groups of dromedaries were used in the study, one group raised in a free-roaming housing system and another group raised in a restricted-roaming housing system. The results revealed that there were significant differences between the two groups in terms of active follicle ratio and size and also the cellular population of functional zones. Animals living and roaming outside the farm barriers were more exposed to pathogens, which leads to the installation of an adaptative process, whereas the animals living under restricted-roaming housing system were not exposed to pathogens. This study indicated that the adaptative behavior of the animal’s immune system with environmental variations is the functional translation of morphological changes. The obtained findings revealed that the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued are directly linked to the rearing system practices

Keywords: adaptative behavior, dromedary, lymph node, morphology, rearing systems

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Authors: Pradipta Risang Ratna Sambawa, Driya Herseta, Mahendra Fajri Nugraha

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In 2020, PT Petrokimia Gresik implemented a program to increase the ROP (Run Of Pile) production rate at the Phosphate Fertilizer 1 plant, causing an increase in scrubbing water consumption in the 100/200 area unit. This increase in water consumption causes a higher discharge of wastewater, which can further cause local flooding, especially during the rainy season. The 100/200 area of the Phosphate Fertilizer 1 plant is close to the warehouse and is often a passing area for trucks transporting raw materials. This causes the pH in the wastewater to become acidic (the worst point is up to pH 1). The problem of flooding and exposure to acidic wastewater in the 100/200 area of Phosphate Fertilizer Plant 1 was then resolved by PT Petrokimia Gresik through wastewater optimization steps called the 3R program (Reduce, Reuse, and Recycle). The 3R (Reduce, reuse, and recycle) program consists of an air consumption reduction program by considering the liquid/gas ratio in scrubbing unit of 100/200 Phosphate Fertilizer 1 plant, creating a wastewater interconnection line so that wastewater from unit 100/200 can be used as scrubbing water in the Phonska 1, Phonska 2, Phonska 3 and unit 300 Phosphate Fertilizer 1 plant and increasing scrubbing effectiveness through scrubbing effectiveness simulations. Through a series of wastewater optimization programs, PT Petrokimia Gresik has succeeded in reducing NaOH consumption for neutralization up to 2,880 kg/day or equivalent in saving up to 314,359.76 dollars/year and reducing process water consumption up to 600 m3/day or equivalent in saving up to 63,739.62 dollars/year.

Keywords: fertilizer, phosphate fertilizer, wastewater, wastewater treatment, water management

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Authors: Hosein Ghahremani, MohammadReza Khoshchehre, Pejman Hakemi

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This study involves numerical simulations of a vertical plate-type photo-bioreactor to investigate the performance of Microalgae Spirulina and Control and optimization of parameters for the digital controller by Taguchi method that MATLAB software and Qualitek-4 has been made. Since the addition of parameters such as temperature, dissolved carbon dioxide, biomass, and ... Some new physical parameters such as light intensity and physiological conditions like photosynthetic efficiency and light inhibitors are involved in biological processes, control is facing many challenges. Not only facilitate the commercial production photo-bioreactor Microalgae as feed for aquaculture and food supplements are efficient systems but also as a possible platform for the production of active molecules such as antibiotics or innovative anti-tumor agents, carbon dioxide removal and removal of heavy metals from wastewater is used. Digital controller is designed for controlling the light bioreactor until Microalgae growth rate and carbon dioxide concentration inside the bioreactor is investigated. The optimal values of the controller parameters of the S/N and ANOVA analysis software Qualitek-4 obtained With Reaction curve, Cohen-Con and Ziegler-Nichols method were compared. The sum of the squared error obtained for each of the control methods mentioned, the Taguchi method as the best method for controlling the light intensity was selected photo-bioreactor. This method compared to control methods listed the higher stability and a shorter interval to be answered.

Keywords: photo-bioreactor, control and optimization, Light intensity, Taguchi method

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: Debajyoti Bose

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Chitosan has received much attention as a functional biopolymer for diverse applications, especially in pharmaceutics and medicine. Chitosan is a positively charged natural biodegradable and biocompatible polymer. It is a linear polysaccharide consisting of β-1,4 linked monomers of glucosamine and N-acetylglucosamine. Chitosan can be mainly obtained from fungal sources during large fermentation process. In this study,three different fungal strains Aspergillus niger NCIM 1045, Aspergillus oryzae NCIM 645 and Mucor indicus MTCC 3318 were used for the production of chitosan. The growth mediums were optimized for maximum fungal production. The produced chitosan was characterized by determining degree of deacetylation. Chitosan possesses one reactive amino at the C-2 position of the glucosamine residue, and these amines confer important functional properties to chitosan which can be exploited for biofabrication to generate various chemically modified derivatives and explore their potential for pharmaceutical field. Chitosan nanoparticles were prepared by ionic cross-linking with tripolyphosphate (TPP). The major effect on encapsulation and release of protein (e.g. enzyme diastase) in chitosan-TPP nanoparticles was investigated in order to control the loading and release efficiency. It was noted that the chitosan loading and releasing efficiency as a nanocapsule, obtained from different fungal sources was almost near to initial enzyme activity(12026 U/ml) with a negligible loss. This signify, chitosan can be used as a polymeric drug as well as active component or protein carrier material in dosage by design due to its appealing properties such as biocompatibility, biodegradability, low toxicity and relatively low production cost from abundant natural sources. Based upon these initial experiments, studies were also carried out on modification of chitosan based nanocapsules incorporated with physiologically important enzymes and nutraceuticals for target delivery.

Keywords: fungi, chitosan, enzyme, nanocapsule

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: S. O. Ayansina, R. A. Oyeyinka, K. K. Bolarinwa

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There is an increasing demand for a functional extension delivery services in Nigeria with a view to meet up with the food and fiber needs of the ever growing population of human and animal respectively. This study was designed to examine farmers’ involvement in public and private extension services in southwestern Nigeria, specifically to explore the farmers’ participation in the two types of organizations involved. It also evaluates the performances of personnel in the organizations. A multi-stage random sampling technique was used to select 30 respondents from each of the three selected organizations in Ogun, Osun and Oyo states in Southwestern Nigeria. Data was collected with interview schedule and analyzed both at descriptive and inferential levels. Kruskal Wallis one-way Analysis of variance was used to test the differences between the participation of beneficiaries who are farmers under the public and private extension services and the level of benefit accrued to them from the various extension organizations involved in the study. Results revealed that private extension organizations were performing better and were more preferred by the beneficiaries. Results of the tested hypotheses as shown by Kruskal Wallis test of difference (x2 = 0.709) S no significant difference between farmers’ participation in the extension services of public and private organizations but however showed significant difference (X2 =12.074) in the benefits achieved by respondents in the two organizations. These include: increased quantity of crop produced, farm income, skill acquisition, and improved education in private extension organizations. Based on this result, it could be inferred that beneficiaries generally preferred private extension organizations because of their effectiveness and vibrancy in programme administration. Public extension is therefore recommended for general overhauling and possibly privatization in order to cater for teeming population of farmers demanding for efficient and functional extension services to better their lots in production, processing and marketing of agricultural produce.

Keywords: public and private involvement, extension services, farmers' participation

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Authors: Wenjuan Lu

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China and Hungary have risen from a friendly and comprehensive cooperative relationship to a comprehensive strategic partnership in recent years, and the economic and trade relations between the two countries have developed smoothly. As an important country along the ‘Belt and Road’, Hungary and China have strong economic complementarities and have unique advantages in carrying China's industrial transfer and economic transformation and development. The construction of the China-Hungary Economic and Trade Cooperation Zone, which was initiated by the ‘Sino-Hungarian Borsod Industrial Zone’ and the ‘Hungarian Central European Trade and Logistics Cooperation Park’ has promoted infrastructure construction, optimized production capacity, promoted industrial restructuring, and formed brand and agglomeration effects. Enhancing the influence of Chinese companies in the European market has also promoted economic development in Hungary and even in Central and Eastern Europe. However, as the China-Hungary Economic and Trade Cooperation Zone is still in its infancy, there are still shortcomings such as small scale, single function, and no prominent platform. In the future, based on the needs of China's cooperation with ‘17+1’ and China-Hungary cooperation, on the basis of appropriately expanding the scale of economic and trade cooperation zones and appropriately increasing the number of economic and trade cooperation zones, it is better to focus on optimizing and adjusting its functions and highlighting different economic and trade cooperation. The differentiated function of the trade zones strengthens the multi-faceted cooperation of economic and trade cooperation zones and highlights its role as a platform for cooperation in information, capital, and services.

Keywords: ‘One Belt, One Road’ Initiative, China-Hungary economic and trade cooperation zone, function optimization, Central and Eastern Europe

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Authors: Xiao-Yin Liu, Liang-Xue Zhou

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Traumatic brain injury (TBI), as a kind of nerve trauma caused by an external force, affects people all over the world and is a global public health problem. Although there are various clinical treatments for brain injury, including surgery, drug therapy, and rehabilitation therapy, the therapeutic effect is very limited. To improve the therapeutic effect of TBI, scaffolds combined with exosomes are a promising but challenging method for TBI repair. In this study, we examined whether a novel 3D-printed collagen/chitosan scaffold/exosomes derived from neural stem cells (NSCs) pretreated with insulin growth factor-1 (IGF-I) scaffolds (3D-CC-INExos) could be used to improve TBI repair and functional recovery after TBI. Our results showed that composite scaffolds of collagen-, chitosan- and exosomes derived from NSCs pretreated with IGF-I (INExos) could continuously release the exosomes for two weeks. In the rat TBI model, 3D-CC-INExos scaffold transplantation significantly improved motor and cognitive function after TBI, as assessed by the Morris water maze test and modified neurological severity scores. In addition, immunofluorescence staining and transmission electron microscopy showed that the recovery of damaged nerve tissue in the injured area was significantly improved by 3D-CC-INExos implantation. In conclusion, our data suggest that 3D-CC-INExos might provide a potential strategy for the treatment of TBI and lay a solid foundation for clinical translation.

Keywords: traumatic brain injury, exosomes, insulin growth factor-1, neural stem cells, collagen, chitosan, 3D printing, neural regeneration, angiogenesis, functional recovery

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Authors: Walter Sebron, Hans Tschürtz, Peter Krebs

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The choice of applicable analysis methods in safety or systems engineering depends on the depth of knowledge about a system, and on the respective lifecycle phase. However, the analysis method chain still shows gaps as it should support system analysis during the lifecycle of a system from a rough concept in pre-project phase until end-of-life. This paper’s goal is to discuss an analysis method, the VISSE Shell Model Analysis (VISMA) method, which aims at closing the gap in the early system lifecycle phases, like the conceptual or pre-project phase, or the project start phase. It was originally developed to aid in the definition of the system boundary of electronic system parts, like e.g. a control unit for a pump motor. Furthermore, it can be also applied to non-electronic system parts. The VISMA method is a graphical sketch-like method that stratifies a system and its parts in inner and outer shells, like the layers of an onion. It analyses a system in a two-step approach, from the innermost to the outermost components followed by the reverse direction. To ensure a complete view of a system and its environment, the VISMA should be performed by (multifunctional) development teams. To introduce the method, a set of rules and guidelines has been defined in order to enable a proper shell build-up. In the first step, the innermost system, named system under consideration (SUC), is selected, which is the focus of the subsequent analysis. Then, its directly adjacent components, responsible for providing input to and receiving output from the SUC, are identified. These components are the content of the first shell around the SUC. Next, the input and output components to the components in the first shell are identified and form the second shell around the first one. Continuing this way, shell by shell is added with its respective parts until the border of the complete system (external border) is reached. Last, two external shells are added to complete the system view, the environment and the use case shell. This system view is also stored for future use. In the second step, the shells are examined in the reverse direction (outside to inside) in order to remove superfluous components or subsystems. Input chains to the SUC, as well as output chains from the SUC are described graphically via arrows, to highlight functional chains through the system. As a result, this method offers a clear and graphical description and overview of a system, its main parts and environment; however, the focus still remains on a specific SUC. It helps to identify the interfaces and interfacing components of the SUC, as well as important external interfaces of the overall system. It supports the identification of the first internal and external hazard causes and causal chains. Additionally, the method promotes a holistic picture and cross-functional understanding of a system, its contributing parts, internal relationships and possible dangers within a multidisciplinary development team.

Keywords: analysis methods, functional safety, hazard identification, system and safety engineering, system boundary definition, system safety

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Authors: Kyung Hwa Hong

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The objective of this study was to evaluate the ability of spent coffee extract to enhance the antioxidant and antimicrobial properties of cotton fabrics. The emergence and spread of infectious diseases has raised a global interest in the antimicrobial substances. The safety of chemical agents, such as antimicrobials and dyes, which may irritate the skin, cause cellular and organ damage, and have adverse environmental impacts during their manufacturing, in relation to the human body has not been established. Nevertheless, there is a growing interest in natural antimicrobials that kill microorganisms or stop their growth without dangerous effects on human health. Spent coffee is the by-product of coffee brewing and amounted to 96,000 tons worldwide in 2015. Coffee components such as caffeine, melanoidins, and chlorogenic acid have been reported to possess multifunctional properties, including antimicrobial, antioxidant, and anti-inflammatory activities. Therefore, the current study examined the possibility of applying spent coffee in functional textile finishing. Spent coffee was extracted with 60% methanol solution, and the major components of the extract were quantified. In addition, cotton fabrics treated with spent coffee extract through a pad-dry-cure process were investigated for antioxidant and antimicrobial activities. The cotton fabrics finished with the spent coffee extract showed an increase in yellowness, which is an unfavorable outcome from the fabric finishing process. However, the cotton fabrics finished with the spent coffee extract exhibited considerable antioxidant activity. In particular, the antioxidant ability significantly increased with increasing concentrations of the spent coffee extract. The finished cotton fabrics showed antimicrobial ability against S. aureus but relatively low antimicrobial ability against K. pneumoniae. Therefore, further investigations are needed to determine the appropriate concentration of spent coffee extract to inhibit the growth of various pathogenic bacteria.

Keywords: spent coffee grounds, cotton, natural finishing agent, antioxidant activity, antimicrobial activity

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Authors: Aliaa M. El-Borai, Ehab A. Beltagy, Eman E. Gadallah, Samy A. ElAssar

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Bioremediation technology is now used for treatment instead of traditional metal removal methods. A strain was isolated from Marsa Alam, Red sea, Egypt showed high resistance to high lead concentration and was identified by the 16S rRNA gene sequencing technique as Halomonas sp. ES015. Medium optimization was carried out using Plackett-Burman design, and the most significant factors were yeast extract, casamino acid and inoculums size. The optimized media obtained by the statistical design raised the removal efficiency from 84% to 99% from initial concentration 250 ppm of lead. Moreover, Box-Behnken experimental design was applied to study the relationship between yeast extract concentration, casamino acid concentration and inoculums size. The optimized medium increased removal efficiency to 97% from initial concentration 500 ppm of lead. Immobilized Halomonas sp. ES015 cells on sponge cubes, using optimized medium in loop bioremediation column, showed relatively constant lead removal efficiency when reused six successive cycles over the range of time interval. Also metal removal efficiency was not affected by flow rate changes. Finally, the results of this research refer to the possibility of lead bioremediation by free or immobilized cells of Halomonas sp. ES015. Also, bioremediation can be done in batch cultures and semicontinuous cultures using column technology.

Keywords: bioremediation, lead, Box–Behnken, Halomonas sp. ES015, loop bioremediation, Plackett-Burman

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Authors: Xi Quan Cheng, Yan Chao Xu, Xu Jiang, Lu Shao, Cher Hon Lau

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A hydrophilic thin-film-composite (TFC) nanofiltration (NF) membrane has been developed through the interfacial polymerization (IP) of amino-functional polyethylene glycol (PEG) and trimesoyl chloride. The selective layer is formed on a polyethersulfone (PES) support that is characterized using FTIR, XPS and SEM, and is dependent on monomer immersion duration, and the concentration of monomers and additives. The higher hydrophilicity alongside the larger pore size of the PEG-based selective layer is the key to a high water flux of 66.0 L m-2 h-1 at 5.0 bar. With mean pore radius of 0.42 nm and narrow pore size distribution, the MgSO4 rejections of the PEG based PA TFC NF membranes can reach up to 80.2 %. The hydrophilic PEG based membranes shows positive charged since the isoelectric points range from pH=8.9 to pH=9.1 and the rejection rates for different salts of the novel membranes are in the order of R(MgCl2)>R(MgSO4)>R(NaCl)>R(Na2SO4). The pore sizes and water permeability of these membranes are tailored by varying the molecular weight and molecular architecture of amino-functional PEG. Due to the unique structure of the selective layer of the PEG based membranes consisting of saturated aliphatic construction unit (CH2-CH2-O), the membranes demonstrate dual resistance to fouling and chlorine. The membranes maintain good salt rejections and high water flux of PEG based membranes after treatment by 2000 ppm NaClO for 24 hours. Interestingly, the PEG based membranes exhibit excellent fouling resistance with a water flux recovery of 90.2 % using BSA as a model molecule. More importantly, the hydrophilic PEG based NF membranes have been exploited to separate several water soluble antibiotics (such as tobramycin, an aminoglycoside antibiotic applied in the treatment of various types of bacterial infections), showing excellent performance in concentration or removal of antibioics.

Keywords: nanofiltration, antibiotic separation, hydrophilic membrane, high flux

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Authors: Carine Kawakami

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In French, as well as in English, there are two types of psychological predicate constructions depending on where the experiencer argument is realized; the first type is in the subject position (e.g. Je regrette d’être venu ici. ‘I regret coming here'), hereinafter called ES construction, and the second type is in the object position (e.g. Cette nouvelle m’a surpris. ‘This new surprised me.'), referred as EO construction. In the previous studies about psychological predicates, the syntactic position of the experiencer argument has been just a matter of its connection with the syntactic or semantic structure of the predicate. So that few attentions have been paid to how two types of realization of experiencer are related to the conceptualization of psychological event and to the function of the sentence describing the psychological event, in the sense of speech act theory. In this research, focusing on the French phenomena limited to the first personal pronoun and the present tense, the ES constructions and the EO constructions will be analyzed from cognitive and functional approach. It will be revealed that, due to the possibility to be used in soliloquy and the high co-occurrence with ça (‘it’), the EO constructions may have expressive function to betray what speaker feels in hic et nunc, like interjection. And in the expressive case, the experiencer is construed as a locus where a feeling appears spontaneously and is construed subjectively (e.g. Ah, ça m’énerve! ‘Oh, it irritates me!'). On the other hand, the ES constructions describe speaker’s mental state in an assertive manner rather than the expressive and spontaneously way. In other words, they describe what speaker feels to the interlocutor (e.g. Je suis énervé. ‘I am irritated.'). As a consequence, when the experiencer argument is realized in the subject position, it is construed objectively and have a participant feature in the sense of cognitive grammar. Finally, it will be concluded that the choice of construction type, at least in French, is correlated to the conceptualization of the psychological event and the discourse feature of its expression.

Keywords: french psychological verb, conceptualization, expressive function, assertive function, experiencer realization

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: H. A. Bentounes, A. Abbad, W. Benstaali

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Using first principles calculations based on the density functional theory and local spin density approximation, we investigate optical properties of GaFeMnN quaternary compound. Results show that optical properties confirm that GaFeMnN can be a good candidate in the design of thin film solar cells in the visible and ultraviolet parts of the spectrum, and a good sensor in the infrared

Keywords: GaN, optical absorption, semi-metallic, dielectric function

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Authors: Parth Mehta, Vedasri Bai Khavala, Prabhu Rajagopal, Tiju Thomas

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There is an increasing need for alternative clean fuels, and hydrogen (H₂) has long been considered a promising solution with a high calorific value (142MJ/kg). However, the storage of H₂ and expensive processes for its generation have hindered its usage. Sodium borohydride (NaBH₄) can potentially be used as an economically viable means of H₂ storage. Thus far, there have been attempts to optimize the life of NaBH₄ (half-life) in aqueous media by stabilizing it with sodium hydroxide (NaOH) for various pH values. Other reports have shown that H₂ yield and reaction kinetics remained constant for all ratios of H₂O to NaBH₄ > 30:1, without any acidic catalysts. Here we highlight the importance of pH and H₂O: NaBH₄ ratio (80:1, 40:1, 20:1 and 10:1 by weight), for NaBH₄ stabilization (half-life reaction time at room temperature) and corrosion minimization of H₂ reactor components. It is interesting to observe that at any particular pH>10 (e.g., pH = 10, 11 and 12), the H₂O: NaBH₄ ratio does not have the expected linear dependence with stability. On the contrary, high stability was observed at the ratio of 10:1 H₂O: NaBH₄ across all pH>10. When the H₂O: NaBH₄ ratio is increased from 10:1 to 20:1 and beyond (till 80:1), constant stability (% degradation) is observed with respect to time. For practical usage (consumption within 6 hours of making NaBH₄ solution), 15% degradation at pH 11 and NaBH₄: H₂O ratio of 10:1 is recommended. Increasing this ratio demands higher NaOH concentration at the same pH, thus requiring a higher concentration or volume of acid (e.g., HCl) for H₂ generation. The reactions are done with tap water to render the results useful from an industrial standpoint. The observed stability regimes are rationalized based on complexes associated with NaBH₄ when solvated in water, which depend sensitively on both pH and NaBH₄: H₂O ratio.

Keywords: hydrogen, sodium borohydride, stability optimization, H₂O:NaBH₄ ratio

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