Search results for: point mutations

Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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Authors: Yan-Wen Wang, Chu-Yang Chou, Jen-Cheng Wang, Min-Sheng Liao, Hsuan-Hsiang Hsu, Cheng-Ying Chou, Chen-Kang Huang, Kun-Chang Kuo, Joe-Air Jiang

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Performance-related parameters of high concentration photovoltaic (HCPV) modules (e.g. current and voltage) are required when estimating the maximum power point using numerical and approximation methods. The maximum power point on the characteristic curve for a photovoltaic module varies when temperature or solar radiation is different. It is also difficult to estimate the output performance and maximum power point (MPP) due to the special characteristics of HCPV modules. Based on the p-n junction semiconductor theory, a brand new and simple method is presented in this study to directly evaluate the MPP of HCPV modules. The MPP of HCPV modules can be determined from an irradiated I-V characteristic curve, because there is a non-linear relationship between the temperature of a solar cell and solar radiation. Numerical simulations and field tests are conducted to examine the characteristics of HCPV modules during maximum output power tracking. The performance of the presented method is evaluated by examining the dependence of temperature and irradiation intensity on the MPP characteristics of HCPV modules. These results show that the presented method allows HCPV modules to achieve their maximum power and perform power tracking under various operation conditions. A 0.1% error is found between the estimated and the real maximum power point.

Keywords: energy performance, high concentrated photovoltaic, maximum power point, p-n junction semiconductor

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Authors: Young-Su Ryu, Su-Hyun Jung, Myoung-Jin Kim, Hyoung-Kyu Song

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In this paper, improved performance scheme for joint transmission is proposed in downlink (DL) coordinated multi-point(CoMP) in case of constraint transmission power. This scheme is that serving transmission point (TP) request a joint transmission to inter-TP and selects one pre-coding technique according to channel state information(CSI) from user equipment(UE). The simulation results show that the bit error rate(BER) and throughput performances of the proposed scheme provide high spectral efficiency and reliable data at the cell edge.

Keywords: CoMP, joint transmission, minimum mean square error, zero-forcing, zero-forcing dirty paper coding

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Authors: Hemant Kumar Pathak

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In 1994, Matthews (S.G. Matthews, Partial metric topology, in: Proc. 8th Summer Conference on General Topology and Applications, in: Ann. New York Acad. Sci., vol. 728, 1994, pp. 183-197) introduced the concept of a partial metric as a part of the study of denotational semantics of data flow networks. He gave a modified version of the Banach contraction principle, more suitable in this context. In fact, (complete) partial metric spaces constitute a suitable framework to model several distinguished examples of the theory of computation and also to model metric spaces via domain theory. In this paper, we introduce the concept of almost partial Hausdorff metric. We prove a fixed point theorem for multi-valued mappings on partial metric space using the concept of almost partial Hausdorff metric and prove an analogous to the well-known Nadler’s fixed point theorem. In the sequel, we derive a homotopy result as an application of our main result.

Keywords: fixed point, partial metric space, homotopy, physical sciences

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Authors: Yutong Wan, John N. Wood

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Introduction: SCN9A encoded Nav1.7 is an ideal therapeutic target with minimal side effects for the pharmaceutical industry because SCN9A variants can cause both human gains of function pain-related mutations and loss of function pain-free mutations. This study reviews the clinical effectiveness of existing Nav1.7 inhibitors, which theoretically should be powerful analgesics. Methods: A systematic review is conducted on the effectiveness of current Nav1.7 blockers undergoing clinical trials. Studies were mainly extracted from PubMed, U.S. National Library of Medicine Clinical Trials, World Health Organization International Clinical Trials Registry, ISRCTN registry platform, and Integrated Research Approval System by NHS. Only studies with full text available and those conducted using double-blinded, placebo controlled, and randomised designs and reporting at least one analgesic measurement were included. Results: Overall, 61 trials were screened, and eight studies covering PF 05089771 (Pfizer), TV 45070 (Teva & Xenon), and BIIB074 (Biogen) met the inclusion criteria. Most studies were excluded because results were not published. All three compounds demonstrated insignificant analgesic effects, and the comparison between PF 05089771 and pregabalin/ibuprofen showed that PF 05089771 was a much weaker analgesic. All three drug candidates only have mild side effects, indicating the potentials for further investigation of Nav1.7 antagonists. Discussion: The failure of current Nav1.7 small molecule inhibitors might attribute to ignorance of the key role of endogenous systems in Nav1.7 null mutants, the lack of selectivity and blocking potency, and central impermeability. The synergistic combination of analgesic drugs, a recent UCL patent, combining a small dose of Nav1.7 blockers and opioids or enkephalinase inhibitors dramatically enhanced the analgesic effects. Conclusion: The current clinical testing Nav1.7 blockers are generally disappointing. However, the newer generation of Nav1.7 targeting analgesics has overcome the major constraints of its predecessors.

Keywords: chronic pain, Nav1.7 blockers, SCN9A, systematic review

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Authors: Ramdan B. A. Koad, Ahmed F. Zobaa

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Since the output characteristics of Photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum Power Point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a Maximum Power Point Tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), and Particle Swarm Optimization (PSO) algorithm for (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods.

Keywords: photovoltaic systems, maximum power point tracking, perturb and observe method, incremental conductance, methods and practical swarm optimization algorithm

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Authors: Enemeri George Uweiyohowo

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Improved achievement with respect to output control of photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident to its low carbon emission and efficiency. Power failure or outage from commercial providers, in general, does not promote development to public and private sector, these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost-effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with MPPT from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0∘N, with a corresponding tilt angle of 36∘, 26∘ and 16∘. Preliminary results include regression analysis (normal probability plot) showing the maximum power point in the system as well the best tilt angle for maximum power point tracking.

Keywords: poly-crystalline PV panels, information technology (IT), maximum power point tracking (MPPT), pulse width modulation (PWM)

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Authors: Norhashidah Hj Mohd Ali, Teng Wai Ping

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In this paper, the formulation of a new group explicit method with a fourth order accuracy is described in solving the two-dimensional Helmholtz equation. The formulation is based on the nine-point fourth-order compact finite difference approximation formula. The complexity analysis of the developed scheme is also presented. Several numerical experiments were conducted to test the feasibility of the developed scheme. Comparisons with other existing schemes will be reported and discussed. Preliminary results indicate that this method is a viable alternative high accuracy solver to the Helmholtz equation.

Keywords: explicit group method, finite difference, Helmholtz equation, five-point formula, nine-point formula

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Authors: Gagandeep Singh Digra, Pawan Kumar, Mandeep Kaur Sidhu

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INTRODUCTION: Chronic Progressive External Ophthalmoplegia (CPEO), also known as Progressive External Ophthalmoplegia (PEO), is a type of eye disorder characterized by a loss of the muscle functions involved in eye and eyelid movement. CPEO can be caused by mutations in mitochondrial DNA. It typically manifests in young adults with bilateral and progressive ptosis as the most common presentation but can also present with difficulty swallowing (dysphagia) and general weakness of the skeletal muscles (myopathy), particularly in the neck, arms, or legs. CASE PRESENTATION: This is a case discussion of 3 cousins who presented to our clinic. A 23-year-old male with past surgical history (PSH) of ptosis repair 2 years ago presented with a chief complaint of nasal intonation for 1.5 years associated with difficulty swallowing. The patient also complained of nasal regurgitation of liquids. He denied any headaches, fever, seizures, weakness of arms or legs, urinary complaints or changes in bowel habits. Physical Examination was positive for facial muscle weakness, including an inability to lift eyebrows (Frontalis), inability to close eyes tightly (Orbicularis Oculi), corneal reflex absent bilaterally, difficulty clenching jaw (Masseter muscle), difficulty smiling (Zygomaticus major), inability to elevate upper lip (Zygomaticus minor). Another cousin of the first patient, a 25-year-old male with no past medical history, presented with complaints of nasal intonation for 2 years associated with difficulty swallowing. He denied a history of nasal regurgitation, headaches, fever, seizures, weakness, urinary complaints or changes in bowel habits. Physical Examination showed facial muscle weakness of the Frontalis muscle, Orbicularis Oculi muscle, Masseter Muscle, Zygomaticus Major, Zygomaticus Minor and absent corneal reflexes. A 28-year-old male, a cousin of the first two patients, presented with chief complaints of ptosis and nasal intonation for the last 8 years. He also complained of difficulty swallowing and nasal regurgitation of liquids. His physical examination showed facial muscle weakness, including frontalis muscle (inability to lift eyebrows), Orbicularis Oculi (inability to close eyes tightly), absent corneal reflexes bilaterally, Zygomaticus Major (difficulty smiling), and Zygomaticus Minor (inability to elevate upper lip). MRI brain and visual field of all the patients were normal. Differential diagnoses, including Grave’s disease, Myasthenia Gravis and Glioma, were ruled out. Due to financial reasons, muscle biopsy could not be pursued. Pedigree analysis revealed only males were affected, likely due to maternal inheritance, so the clinical diagnosis of CPEO was made. The patients underwent symptomatic management, including ptosis surgical correction for the third patient. CONCLUSION: Chronic Progressive External Ophthalmoplegia (CPEO), a rare case entity, occurs in young adults as a manifestation of mitochondrial myopathy. There are three modes of transmission- maternal transmission associated with mitochondrial point mutations, autosomal recessive, and autosomal dominant. CPEO can sometimes be difficult to diagnose, especially in asymmetric presentation. Therefore, it is crucial to keep it in differential diagnosis to avoid delay in diagnosis.

Keywords: neurology, chronic, progressive, ophthalmoplegia

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Authors: Cumhur Cansever, Selcuk Er

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There is an increasing cooperation and interaction between the military logistic systems and civil organizations operating in today's market. While the scope and functions of civilian logistics have different characteristics, military logistics tries to import some applications that are conducted by private sectors successfully. Also, at this point, the determination of the optimal point of integration and interaction between civilian and military logistics has emerged as a key issue. In this study, the mutual effects between military and civilian logistics and their most common integration areas, (Supply Chain Management (SCM), Integrated Logistics Support (ILS) and Outsourcing) will be examined with risk analysis and determination of basic skills evaluation methods for determining the optimum point in the integration.

Keywords: core competency, integrated logistics support, outsourcing, supply chain management

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: Li Yin, Xiaoqin Wang

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Background and purpose: Cancer diagnosis is part of a complex stochastic process, in which patients' personal and social characteristics influence the choice of diagnosing methods, diagnosing methods, in turn, influence the initial assessment of cancer stage, the initial assessment, in turn, influences the choice of treating methods, and treating methods in turn influence cancer outcomes such as cancer survival. To evaluate diagnosing methods, one needs to estimate and test the causal effect of a regime of cancer diagnosis and treatments. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to estimate and test these causal effects via point effects. The purpose of the work is to estimate and test causal effects under various regimes of cancer diagnosis and treatments via point effects. Challenges and solutions: The cancer stage has influences from earlier diagnosis as well as on subsequent treatments. As a consequence, it is highly difficult to estimate and test the causal effects via standard parameters, that is, the conditional survival given all stationary covariates, diagnosing methods, cancer stage and prognosis factors, treating methods. Instead of standard parameters, we use the point effects of cancer diagnosis and treatments to estimate and test causal effects under various regimes of cancer diagnosis and treatments. We are able to use familiar methods in the framework of single-point causal inference to accomplish the task. Achievements: we have applied this method to stomach cancer survival from a clinical study in Sweden. We have studied causal effects under various regimes, including the optimal regime of diagnosis and treatments and the effect moderation of the causal effect by age and gender.

Keywords: cancer diagnosis, causal effect, point effect, G-formula, sequential causal effect

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Authors: Sakshi Yadav, Sushila Shekhawat

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This study addresses different types of points of view as seen in nature documentary films with the help of three eco documentaries, and it would be significant in understanding the role of the narrative point of view as a tool for showing and telling in documentaries. Narrative analysis of a film forms an essential aspect of the discourse of scholarship in film studies. Narration is the chain of events occurring in time and space. The notion of narrative provides the idea of coherence and wholeness to the story. There are various components that the narration carries, one of which is the perspective or point of view. The narrator plays the role of a mediator between the film and the audience; thus, his perspective influences the way the audience interprets the film. Feature films have been analyzed through narrative points of view; however, this research intends to conduct it from the angle of a nature documentary film. The study will examine narrative viewpoints unique to nature documentary films using three ecological documentary films-The Cove (2009), Tale of a forest (2012), and Before the flood (2016). This research will apply the framework of narrative theory and will investigate the impact of the different types of narrative points of view, as each portrays the human-nature relationship from a different standpoint, and it will also study the effect that the narrative point of view has on the mode of these eco documentaries.

Keywords: ecodocumentary, narrative, human-nature relationship, point of view

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Authors: Sinethemba Yakobi, Lindiwe Zuma, Ofentse Pooe

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Gonococcal infections present a notable public health issue, and the major approach for treatment involves using β-lactam antibiotics that specifically target penicillin-binding protein 2 (PBP2) in Neisseria gonorrhoeae. This study examines the influence of flavonoids, namely rutin, on the structural changes of PBP2 in both penicillin-resistant (FA6140) and penicillin-susceptible (FA19) strains. The research clarifies the structural effects of particular mutations, such as inserting an aspartate residue at position 345 (Asp-345a) in the PBP2 protein. The strain FA6140, which is resistant to penicillin, shows specific changes that lead to a decrease in penicillin binding. These mutations, namely P551S and F504L, significantly impact the pace at which acylation occurs and the stability of the strain under high temperatures. Molecular docking analyses investigate the antibacterial activities of rutin and other phytocompounds, emphasizing its exceptional binding affinity and potential as an inhibitor of PBP2. Quercetin and protocatechuic acid have encouraging antibacterial effectiveness, with quercetin displaying characteristics similar to those of drugs. Molecular dynamics simulations offer a detailed comprehension of the interactions between flavonoids and PBP2, highlighting rutin's exceptional antioxidant effects and strong affinity for the substrate binding site. The study's wider ramifications pertain to the pressing requirement for antiviral treatments in the context of the ongoing COVID-19 epidemic. Flavonoids have a strong affinity for binding to PBP2, indicating their potential as inhibitors to impair cell wall formation in N. gonorrhoeae. Ultimately, this study provides extensive knowledge on the interactions between proteins and ligands, the dynamics of the structure, and the ability of flavonoids to combat penicillin-resistant N. gonorrhoeae bacteria. The verified simulation outcomes establish a basis for creating potent inhibitors and medicinal therapies to combat infectious illnesses.

Keywords: phytochemicals, penicillin-binding protein 2, gonococcal infection, ligand-protein interaction, binding energy, neisseria gonorrhoeae FA19, neisseria gonorrhoeae FA6140, flavonoids

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Authors: Ozlem Oral, Emre Taskin, Aysel Yuce, Serap Dokmeci, Devrim Gozuacik

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Autophagy is an evolutionary conserved lysosome-dependent catabolic pathway, responsible for the degradation of long-lived proteins, abnormal aggregates and damaged organelles which cannot be degraded by the ubiquitin-proteasome system. Lysosomes degrade the substrates through the activity of lysosomal hydrolases and lysosomal membrane-bound proteins. Mutations in the coding region of these proteins cause malfunctional lysosomes, which contributes to the pathogenesis of lysosomal storage diseases. Gaucher disease is a lysosomal storage disease resulting from the mutation of a lysosomal membrane-associated glycoprotein called glucocerebrosidase and its cofactor saposin C. The disease leads to intracellular accumulation of glucosylceramide and other glycolipids. Because of the essential role of lysosomes in autophagic degradation, Gaucher disease may directly be linked to this pathway. In this study, we investigated the expression of autophagy and/or lysosome-related genes and proteins in fibroblast cells isolated from patients with different mutations. We carried out confocal microscopy analysis and examined autophagic flux by utilizing the differential pH sensitivities of RFP and GFP in mRFP-GFP-LC3 probe. We also evaluated lysosomal pH by active lysosome staining and lysosomal enzyme activity. Beside lysosomes, we also performed proteasomal activity and cell death analysis in patient samples. Our data showed significant attenuation in the expression of key autophagy-related genes and accumulation of their proteins in mutant cells. We found decreased the ability of autophagosomes to fuse with lysosomes, associated with elevated lysosomal pH and reduced lysosomal enzyme activity. Proteasomal degradation and cell death analysis showed reduced proteolytic activity of the proteasome, which consequently leads to increased susceptibility to cell death. Our data indicate that the major degradation pathways are affected by multifunctional lysosomes in mutant patient cells and may underlie in the mechanism of clinical severity of Gaucher patients. (This project is supported by TUBITAK-3501-National Young Researchers Career Development Program, Project No: 112T130).

Keywords: autophagy, Gaucher's disease, glucocerebrosidase, mutant fibroblasts

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Authors: Yahya Jahangiri, Ali Almasi

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Currently capitalism is one of the most important economic issues discussed by great scholars around the world. But Islamic approach, regarding this issue may differ both western and eastern views. A greatest scholar in Islamic economy ‘especially in Shia’ is Martyr Muhammad Baqir Al-Sadr. He wrote “Our economy” (Iqtisaduna) to present an economic point of view according to the Islamic teachings. In this regard firstly we will mention three approaches which are common in Muslim scullers about the economic science and then the main approach which is Sadr's view is described here. His claim explains that Islam and capitalism are in conflict with each other. And finally he explains the relationship between Islam and economy and he suggests the Islamic point of view in economy and its foundations as a solution for economic problems which we face today.

Keywords: Islam, economic science, capitalism, Martyr Sadr

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Authors: Nwadike Emmanuel Chinagoron, Achebe Chukwunonso, Ezeliora Chukwuemeka Daniel, Azaka Onyemazuwa Andrew

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In this research work, the process of biodiesel production in a pilot plant was studied using cow tallow as raw material, methanol as the solvent and potassium hydroxide as catalysts. The biodiesel quality was determined by characterization. The tallow used in the production had a molecular weight of 860g. Its oil had a density value of 0.8g/ml, iodine value of 63.45, viscosity at 300C was 9.83pas, acid value was 1.96, free fatty acid (FFA) of 0.98%, saponification value of 82.75mleq/kg, specific gravity of 0.898, flash point of 1100C, cloud point of 950C and Calorific value also called Higher Heating Value (HHV) of 38.365MJ/Kg. The produced biodiesel had a density of 0.82g/ml, iodine value of 126.9, viscosity of 4.32pas at 300C, acid value of 0.561, FFA of 0.2805%, saponification value of 137.45 mleq/kg.Flash point, cloud point and centane number of the biodiesel produced are 1390C, 980C and 57.5 respectively, with fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 10%, 2.8%, 5%, 5%, 20%, and 37.2% respectively. The biodiesel higher heating values (calorific values) when estimated from viscosity, density and flash points were 41.4MJ/Kg, 63.8MJ/Kg, and 34.6MJ/Kg respectively. The biodiesel was blended with conventional diesel. The blend B-10 had values of 1320C and 960C for flash and cloud points, with Calorific value (or HHV) of 34.6 MJ/Kg (when estimated from its Flash point) and fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 5%, 2.1%,10%, 5%, 15%, and 62.9% respectively.

Keywords: biodiesel, characterization, cow-tallow, cetane rating

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Authors: Jiwoo Park, Junseok Yoon, Jeong Kim, Beomsoo Kang

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Multi-Point Stretch Forming (MPSF) process is suitable for flexible manufacturing, and it has several advantages including that it could be applied to various forming such as sheet metal forming, single curved surface forming and double curved one. In this study, a systematic numerical simulation was carried out for atypical double curved surface forming using the multiple die stretch forming process. In this simulation, urethane pads were defined based on hyper-elastic material model as a cushion for the smooth forming surface. The deformation behaviour on elastic recovery was also investigated to consider the exact result after the last forming process, and then the experiment was also carried out to confirm the formability of this forming process. By comparing the simulation and experiment results, the suitability of the multiple die stretch forming process for the atypical double curved surface was verified. Consequently, it is confirmed that the multi-point stretch forming process has the capability and feasibility of being used to manufacture the double curved surfaces of sheet metal.

Keywords: multi-point stretch forming, double curved surface, numerical simulation, manufacturing

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Authors: Mohammad Farid

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In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area.

Keywords: generalized mixed equilibrium problem, fixed-point problem, nonexpansive semigroup, variational inequality problem, iterative algorithms, hybrid extragradient method

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Mohammad H. Ahmadi, Vahid Haghighatdoost

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Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.

Keywords: meeting point, trip plans, road networks, spatial databases

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Authors: S. Al Dandachli, F. Perales, Y. Monerie, F. Jamin, M. S. El Youssoufi, C. Pelissou

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The goal of this research is to study the fracture process and mechanical behavior of concrete under I–II mixed-mode stress, which is essential for ensuring the safety of concrete structures. For this purpose, two-dimensional simulations of three-point bending tests under variable load and geometry on notched cement paste samples of composite samples (cement paste/siliceous aggregate) are modeled by employing Cohesive Zone Models (CZMs). As a result of experimental validation of these tests, the CZM model demonstrates its capacity to predict fracture propagation at the local scale.

Keywords: cement paste, interface, cohesive zone model, fracture, three-point flexural test bending

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Authors: Adel Bouchakhchoukha, Hakim Akeb

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In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

Keywords: team orienteering problem, vehicle routing, beam search, local search

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Authors: Debamitra Chakravorty, Pratap K. Parida

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Cold-adapted proteases enhance wash performance in low-temperature laundry resulting in a reduction in energy consumption and wear of textiles and are also used in the dehairing process in leather industries. Unfortunately, the possible drawbacks of using cold-adapted proteases are their instability at higher temperatures. Therefore, proteases with broad temperature stability are required. Unfortunately, wild-type cold-adapted proteases exhibit instability at higher temperatures and thus have low shelf lives. Therefore, attempts to engineer cold-adapted proteases by protein engineering were made previously by directed evolution and random mutagenesis. The lacuna is the time, capital, and labour involved to obtain these variants are very demanding and challenging. Therefore, rational engineering for cold stability without compromising an enzyme's optimum pH and temperature for activity is the current requirement. In this work, mutations were rationally designed with the aid of high throughput computational methodology of network analysis, evolutionary conservation scores, and molecular dynamics simulations for Savinase from Bacillus lentus with the intention of rendering the mutants cold stable without affecting their temperature and pH optimum for activity. Further, an attempt was made to incorporate a mutation in the most stable mutant rationally obtained by this method to introduce oxidative stability in the mutant. Such enzymes are desired in detergents with bleaching agents. In silico analysis by performing 300 ns molecular dynamics simulations at 5 different temperatures revealed that these three mutants were found to be better in cold stability compared to the wild type Savinase from Bacillus lentus. Conclusively, this work shows that cold adaptation without losing optimum temperature and pH stability and additionally stability from oxidative damage can be rationally designed by in silico enzyme engineering. The key findings of this work were first, the in silico data of H5 (cold stable savinase) used as a control in this work, corroborated with its reported wet lab temperature stability data. Secondly, three cold stable mutants of Savinase from Bacillus lentus were rationally identified. Lastly, a mutation which will stabilize savinase against oxidative damage was additionally identified.

Keywords: cold stability, molecular dynamics simulations, protein engineering, rational design

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Authors: Z. W. Zhong, C. Xu, W. K. Choi

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To build a thin fan-out wafer-level package, the package had to be ground to a thin level. In this work, the influence of the grinding processes on the strength of the fan-out wafer-level packages was investigated. After different grinding processes, all specimens were placed on a three-point-bending fixture installed on a universal tester for three-point-bending testing, and the strength of the fan-out wafer-level packages was measured. The experiments revealed that the average flexure strength increased with the decreasing surface roughness height of the fan-out wafer-level package tested. The grinding processes had a significant influence on the strength of the fan-out wafer-level packages investigated.

Keywords: FOWLP strength, surface roughness, three-point bending, grinding

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Authors: Wu Liching

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Aim This case aims to discuss the pathogenesis, clinical manifestations and medical treatment of strokes caused by mitochondrial gene mutations. Methods Diagnosis of ischemic stroke caused by mitochondrial gene defect by means of "next-generation sequencing mitochondrial DNA gene variation detection", imaging examination, neurological examination, and medical history; this study took samples from the neurology ward of a medical center in northern Taiwan cases diagnosed with acute cerebral infarction as the research objects. Result This case is a 49-year-old married woman with a rare disease, mitochondrial gene mutation inducing ischemic stroke. She has severe hearing impairment and needs to use hearing aids, and has a history of diabetes. During the patient’s hospitalization, the blood test showed that serum Lactate: 7.72 mmol/L, Lactate (CSF) 5.9 mmol/L. Through the collection of relevant medical history, neurological evaluation showed changes in consciousness and cognition, slow response in language expression, and brain magnetic resonance imaging examination showed subacute bilateral temporal lobe infarction, which was an atypical type of stroke. The lineage DNA gene has m.3243A>G known pathogenic mutation point, and its heteroplasmic level is 24.6%. This pathogenic point is located in MITOMAP and recorded as Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes (MELAS) , Leigh Syndrome and other disease-related pathogenic loci, this mutation is located in ClinVar and recorded as Pathogenic (dbSNP: rs199474657), so it is diagnosed as a case of stroke caused by a rare disease mitochondrial gene mutation. After medical treatment, there was no more seizure during hospitalization. After interventional rehabilitation, the patient's limb weakness, poor language function, and cognitive impairment have all improved significantly. Conclusion Mitochondrial disorders can also be associated with abnormalities in psychological, neurological, cerebral cortical function, and autonomic functions, as well as problems with internal medical diseases. Therefore, the differential diagnoses cover a wide range and are not easy to be diagnosed. After neurological evaluation, medical history collection, imaging and rare disease serological examination, atypical ischemic stroke caused by rare mitochondrial gene mutation was diagnosed. We hope that through this case, the diagnosis of rare disease mitochondrial gene variation leading to cerebral infarction will be more familiar to clinical medical staff, and this case report may help to improve the clinical diagnosis and treatment for patients with similar clinical symptoms in the future.

Keywords: acute stroke, MELAS, lactic acidosis, mitochondrial disorders

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Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

Abstract:

The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

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Authors: Mehdi Ameur, Ahmed Essadki, Tamou Nasser

Abstract:

The purpose of this paper is the evaluation of photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturbing and observing (P&O), incremental conductance (INC) and fuzzy logic controller (FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: fuzzy logic controller, FLC, hill climbing, HC, incremental conductance (INC), perturb and observe (P&O), maximum power point, MPP, maximum power point tracking, MPPT

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Authors: Rindra Rantoson, Hichem Nouira, Nabil Anwer, Charyar Mehdi-Souzani

Abstract:

Multiple measurements by means of various data acquisition systems are generally required to measure the shape of freeform workpieces for accuracy, reliability and holisticity. The obtained data are aligned and fused into a common coordinate system within a registration technique involving coarse and fine registrations. Standardized iterative methods have been established for fine registration such as Iterative Closest Points (ICP) and its variants. For coarse registration, no conventional method has been adopted yet despite a significant number of techniques which have been developed in the literature to supply an automatic rough matching between data sets. Two main issues are addressed in this paper: the coarse registration and the fine registration. For coarse registration, two novel automated methods based on the exploitation of discrete curvatures are presented: an enhanced Hough Transformation (HT) and an improved Ransac Transformation. The use of curvature features in both methods aims to reduce computational cost. For fine registration, a new variant of ICP method is proposed in order to reduce registration error using curvature parameters. A specific distance considering the curvature similarity has been combined with Euclidean distance to define the distance criterion used for correspondences searching. Additionally, the objective function has been improved by combining the point-to-point (P-P) minimization and the point-to-plane (P-Pl) minimization with automatic weights. These ones are determined from the preliminary calculated curvature features at each point of the workpiece surface. The algorithms are applied on simulated and real data performed by a computer tomography (CT) system. The obtained results reveal the benefit of the proposed novel curvature-based registration methods.

Keywords: discrete curvature, RANSAC transformation, hough transformation, coarse registration, ICP variant, point-to-point and point-to-plane minimization combination, computer tomography

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Authors: Dhanuj M. Gandikota

Abstract:

Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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