Search results for: genome scale metabolic model

Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Angelina Anani, Ignacio Ortiz Flores, Haitao Li

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The use of underground mining methods have increased significantly over the past decades. This increase has also been spared on by several mines transitioning from surface to underground mining. However, determining the transition depth can be a challenging task, especially when coupled with production schedule optimization. Several researchers have simplified the problem by excluding operational features relevant to production schedule optimization. Our research objective is to investigate the extent to which operational features of transition mines accounted for affect the optimal production schedule. We also provide a framework for factors to consider in production schedule optimization for transition mines. An integrated mixed-integer linear programming (MILP) model is developed that maximizes the NPV as a function of production schedule and transition depth. A case study is performed to validate the model, with a comparative sensitivity analysis to obtain operational insights.

Keywords: underground mining, transition mines, mixed-integer linear programming, production schedule

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Authors: Shyh-Ming Chern, Hung-Chi Tu

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One way to utilize biomass is to thermochemically convert it into gases and chemicals. For conversion of biomass, glucose is a particularly popular model compound for cellulose, or more generally for biomass. The present study takes a different approach by employing lactic acid as the model compound for cellulose. Since lactic acid and glucose have identical elemental composition, they are expected to produce similar results as they go through the conversion process. In the current study, lactic acid was thermochemically converted to assess its reactivity and reaction mechanism in subcritical and supercritical water, by using a 16-ml autoclave reactor. The major operating parameters investigated include: The reaction temperature, from 673 to 873 K, the reaction pressure, 10 and 25 MPa, the dosage of oxidizing agent, 0 and 0.5 chemical oxygen demand, and the concentration of lactic acid in the feed, 0.5 and 1.0 M. Gaseous products from the conversion were generally found to be comparable to those derived from the conversion of glucose.

Keywords: lactic acid, subcritical water, supercritical water, thermochemical conversion

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Authors: Mustafa Jahanara

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The purpose of the research was to study the relationship between self-esteem, self-Efficacy with psychological distress in the high school teachers. A total of 245 teachers (92 male and 153 female) in the high school of Kabul and Mazar-e-Sharif from Afghanistan completed inventories General Self-Efficacy, Rosenberg Self-Esteem Scale, and General Health Questionnaire-12 and that assessed their Self-Efficacy, self-esteem with psychological distress. Correlational analysis showed that self-efficacy and self-esteem were significantly and positively correlated with each other. The results of the study indicated that psychological distress is negatively related to self-esteem, and self-efficacy. However, the findings suggest that self-esteem, and self-efficacy could influence on mental health.

Keywords: high school teachers, self-esteem, self-efficacy, psychological distress

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Authors: Salma Akter, Mohammad M. Haque, Lawrence Akwetey

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An empirical research design will analyze different factors/predictors children use to influence their parents in the family buying decision process in the unexplored area of British Bangladeshi children in the United Kingdom. The proposed conceptual model of factors- buying decision making process will be tested by the Structure Equation Model. A structured Questionnaire and secondary sources will employ to collect data and analyse and measure the validity by Statistical tools (SPSS) and Microsoft Excel. The Contemporary research aims to use the deductive approach developing the research questions and testing the hypothesis to identify the impact of different strategies British Bangladeshi children used to influence their parents in the family buying decision which was overlooked in the previous research.

Keywords: British Bangladeshi children, buying decision process, children influence, influential factors

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Authors: Amina Ramdani, Abdelkader Kadeche, Zoubida Taleb, Safia Taleb

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The aim of this present study is to evaluate the adsorption capacity of a dye, Malachite green, on a local Algerian montmorillonite clay mineral (raw, purified and Cr-pillared). Various parameters influencing the dye adsorption process ie contact time, adsorbent dose, initial concentration of dye, pH of the solution and temperature. Cr pillared clay has been obtained with a better surface character than purified and natural clay. An increase in basal spacing from 12.45 Å (Mont-Na) to 22.88 Å (Mont-PLCr), surface area from 67 m2 /g (Mont-Na) to 102 m2 /g (Mont-PLCr). The experimental results show that the dye adsorption kinetic were fast: 5 min for Cr-pillared clay mineral, and 30 min for raw and purified clay mineral (RC and Mont-Na). The removal efficiency on Mont-PLCr (98.64%) is greater than that of Mont-Na (86.20%) and RC (82.09%). The acidity and basicity of the medium considerably affect the adsorption of the dye. It attained its maximum at pH 4.8. The equilibrium and kinetic data were found to fit well the Langmuir model and the pseudo-second-order model.

Keywords: Dye removal, pillared clay, isotherm, kinetic

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Authors: George N. Prodromidis, Frank A. Coutelieris

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Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.

Keywords: biogas, exergy, efficiency, optimization

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Authors: Cynthia Briggs, Kimberly Gerardi

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Over the past six years, the authors have been working together on World Language Collaborations in the Middle School French Program at St. Luke's School in New Canaan, Connecticut, USA. Author 2 brings design expertise to the projects, and both teachers have utilized the fabrication lab, emerging technologies, and collaboration with students. Each year, author 1 proposes a project scope, and her students are challenged to design and engineer a signature project. Both partners have improved the iterative process to ensure deeper learning and sustained student inquiry. The projects range from a 1:32 scale model of the Eiffel Tower that was CNC routed to a fully functional jukebox that plays francophone music, lights up, and can hold up to one thousand songs powered by Raspberry Pi. The most recent project is a Fragrance Marketplace, culminating with a pop-up store for the entire community to discover. Each student will learn the history of fragrance and the chemistry behind making essential oils. Students then create a unique brand, marketing strategy, and concept for their signature fragrance. They are further tasked to use the industrial design process (bottling, packaging, and creating a brand name) to finalize their product for the public Marketplace. Sometimes, these dynamic projects require maintenance and updates. For example, our wall-mounted, three-foot francophone clock is constantly changing. The most recent iteration uses Chat GPT to program the Arduino to reconcile the real-time clock shield and keep perfect time as each hour passes. The lights, motors, and sounds from the clock are authentic to each region, represented with laser-cut embellishments. Inspired by Michel Parmigiani, the history of Swiss watch-making, and the precision of time instruments, we aim for perfection with each passing minute. The authors aim to share exemplary work that is possible with students of all ages. We implemented the reverse engineering process to focus on student outcomes to refine our collaborative process. The products that our students create are prime examples of how the design engineering process is applicable across disciplines. The authors firmly believe that the past and present of World cultures inspire innovation.

Keywords: collaboration, design thinking, emerging technologies, world language

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Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh

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This paper presents a new method to design nonlinear feedback linearization controller for polymer electrolyte membrane fuel cells (PEMFCs). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEM fuel cells. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEM fuel cell system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA_II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: nonlinear dynamic model, polymer electrolyte membrane fuel cells, feedback linearization, optimal control, NSGA_II

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Authors: Xu Tao, Yilun Xu, Dingwei Xiang, Yaofei Sun

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The practice of urban planning and construction based on the concept of the “low carbon eco-city” has been universally accepted by the academic community in response to urban issues such as population, resources, environment, and social development. Based on this, the current article first analyzes the concepts of low carbon eco-city, then builds a complex adaptive system (CAS) theory based on Chinese traditional philosophical thinking, and analyzes the adaptive relationship between material and non-material elements. A three-dimensional evaluation model of natural ecology, economic low carbon, and social harmony was constructed. Finally, the construction of a low carbon eco-city index system in Hexi Newtown of Nanjing was used as an example to verify the effectiveness of the research results; this paradigm provides a new way to achieve a low carbon eco-city system.

Keywords: complex adaptive system, low carbon ecology, index system, model

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: control, identification, robot, co-manipulation, sensor-less

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Authors: Xiaojie Cheng, Ulrike Frank, Feng Zhao, Karin Pritsch

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Ragweed (Ambrosia artemisiifolia) is an invasive weed that has become an increasing global problem. In addition to affecting land use and crop yields, ragweed has a strong impact on human health as it produces highly allergenic pollen. Global warming will result in an earlier and longer pollen season enhanced pollen production and an increase in pollen allergenicity with a negative effect on atopic patients. The aims of this study were to investigate the effects of increasing temperature, the future climate scenario in the Munich area, southern Germany, predicted on the basis of RCP8.5 until the end of 2050s, or/and NO₂, a major air pollutant, 1) on the vegetative and reproductive characteristics of ragweed plants, 2) on the total allergenicity of ragweed pollen, 3) on the total pollen proteomic patterns. Ragweed plants were cultivated for the whole plant vegetation period under controlled conditions either under ambient climate conditions or 4°C higher temperatures with or without additional NO₂. Higher temperature resulted in bigger plant sizes, longer male inflorescences, and longer pollen seasons. The total allergenic potential of the pollen was accessed by dot blot using serum from ragweed pollen sensitized patients. The comparative immunoblot analysis revealed that the in vivo fumigation of ragweed plants with elevated NO₂-concentrations significantly increased the allergenic potential of the pollen, and in combination with increased temperature, the allergenic potential was even higher. On the other hand, label-free protein quantification by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed. The results showed that more proteins were significantly up- and down-regulated under higher temperatures with/without elevated NO₂ conditions. Most of the highly expressed proteins were participating intensively in the metabolic process, the cellular process, and the stress defense process. These findings suggest that rising temperature and elevated NO₂ are important environmental factors for higher abiotic stress activities, catalytic activities, and thus higher allergenic potential observed in pollen proteins.

Keywords: climate change, NO₂, pollen proteome, ragweed, temperature

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Authors: Raymond C. Hawkins II, Catherine A. Hawkins

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The System Contextual Integrated Model (SCIM), developed as a trans-theoretical framework for selecting measures for psychotherapy process and outcome, is reformulated for behavioral health applications. The SCIM “healing cycle” is an allostatic hedonic affective-cognitive right-hemisphere–left-hemisphere coordinated process involving positive alliesthesia that mitigates traumatic pain and generates psychological flexibility. The SCIM “trauma cycle” is an allostatic overload alliesthesia opponent process with long-lasting pathology sequelae. The social ecological context moderates the “healing cycle” and the “trauma cycle.” Repeated evocation of the “healing cycle” in a therapeutic relationship can gradually relieve trauma sequelae. The SCIM is applied to pain, obese binge eating, and substance use disorders.

Keywords: allostasis, alliesthesia, opponent process, behavioral health, assessment

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Authors: Maor Farid, Oleg Gendelman

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Equivalent mechanical model of liquid sloshing in partially-filled cylindrical vessel is treated in the cases of free oscillations and of horizontal base excitation. The model is designed to cover both the linear and essentially nonlinear sloshing regimes. The latter fluid behaviour might involve hydraulic impacts interacting with the inner walls of the tank. These impulsive interactions are often modeled by high-power potential and dissipation functions. For the sake of analytical description, we use the traditional approach by modeling the impacts with velocity-dependent restitution coefficient. This modelling is similar to vibro-impact nonlinear energy sink (VI NES) which was recently explored for its vibration mitigation performances and nonlinear response regimes. Steady-state periodic regimes and chaotic strongly modulated responses (CSMR) are detected. Those dynamical regimes were described by the system's slow motion on the slow invariant manifold (SIM). There is a good agreement between the analytical results and numerical simulations. Subsequently, Finite-Element (FE) method is used to determine and verify the model parameters and to identify dominant dynamical regimes, natural modes and frequencies. The tank failure modes are identified and critical locations are identified. Mathematical relation is found between degrees-of-freedom (DOFs) motion and the mechanical stress applied in the tank critical section. This is the prior attempt to take under consideration large-amplitude nonlinear sloshing and tank structure elasticity effects for design, regulation definition and resistance analysis purposes. Both linear (tuned mass damper, TMD) and nonlinear (nonlinear energy sink, NES) passive energy absorbers contribution to the overall system mitigation is firstly examined, in terms of both stress reduction and time for vibration decay.

Keywords: nonlinear energy sink (NES), reduced-order modelling, liquid sloshing, vibration mitigation, vibro-impact dynamics

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Authors: M. H. Korayem, Sh. Ameri, N. Yousefi Lademakhi

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To ensure the stability of closed-loop nonlinear model predictive control (NMPC) within a finite horizon, there is a need for appropriate design terminal ingredients, which can be a time-consuming and challenging effort. Otherwise, in order to ensure the stability of the control system, it is necessary to consider an infinite predictive horizon. Increasing the prediction horizon increases computational demand and slows down the implementation of the method. In this study, a new technique has been proposed to ensure system stability without terminal ingredients. This technique has been employed in the design of the NMPC algorithm, leading to a reduction in the computational complexity of designing terminal ingredients and computational burden. The studied system is a wheeled mobile robot (WMR) subjected to non-holonomic constraints. Simulation has been investigated for two problems: trajectory tracking and adjustment mode.

Keywords: wheeled mobile robot, nonlinear model predictive control, stability, without terminal ingredients

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Authors: Bruno R. Mendes, Francisco J. Caldeira, Rita S. Luís

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Population ageing is directly correlated to an increase in medicine consumption. Beyond the latter and the polymedicated profile of elderly, it is possible to see a need for pharmacotherapeutic monitoring due to cognitive and physical impairment. In this sense, the tracking, organization and administration of medicines become a daily challenge and the pill-box dispenser system a solution. The pill-box dispenser (system) consists in a small compartmentalized container to unit dose organization, which means a container able to correlate the patient’s prescribed dose regimen and the time schedule of intake. In many European countries, this system is part of pharmacist’s role in clinical pharmacy. Despite this simple solution, therapy compliance is only possible if the patient adheres to the system, so it is important to establish a qualitative and quantitative analysis on the perception of the patient on the benefits and risks of the pill-box dispenser as well as the identification of the ideal system. The analysis was conducted through an observational study, based on the application of a standardized questionnaire structured with the numerical scale of Likert (5 levels) and previously validated on the population. The study was performed during a limited period of time and under a randomized sample of 188 participants. The questionnaire consisted of 22 questions: 6 background measures and 16 specific measures. The standards for the final comparative analysis were obtained through the state-of-the-art on the subject. The study carried out using the Likert scale afforded a degree of agreement and discordance between measures (Sample vs. Standard) of 56,25% and 43,75%, respectively. It was concluded that the pill-box dispenser has greater acceptance among a younger population, that was not the initial target of the system. However, this allows us to guarantee a high adherence in the future. Additionally, it was noted that the cost associated with this service is not a limiting factor for its use. The pill-box dispenser system, as currently implemented, demonstrates an important weakness regarding the quality and effectiveness of the medicines, which is not understood by the patient, revealing a significant lack of literacy when it concerns with medicine area. The characteristics of an ideal system remain unchanged, which means that the size, appearance and availability of information in the pill-box continue to be indispensable elements for the compliance with the system. The pill-box dispenser remains unsuitable regarding container size and the type of treatment to which it applies. Despite that, it might be a future standard for clinical pharmacy, allowing a differentiation of the pharmacist role, as well as a wider range of applications to other age groups and treatments.

Keywords: clinical pharmacy, medicines, patient safety, pill-box dispenser

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Authors: Eric Lacoste

Abstract:

Laboratory animals are currently widely used as a model of human pathologies in dermatology such as atopic dermatitis (AD). These models provide a better understanding of the pathophysiology of this complex and multifactorial disease, the discovery of potential new therapeutic targets and the testing of the efficacy of new therapeutics. However, confirmation of the correct development of AD is mainly based on histology from skin biopsies requiring invasive surgery or euthanasia of the animals, plus slicing and staining protocols. However, there are currently accessible imaging technologies such as Optical Coherence Tomography (OCT), which allows non-invasive visualization of the main histological structures of the skin (like stratum corneum, epidermis, and dermis) and assessment of the dynamics of the pathology or efficacy of new treatments. Briefly, female immunocompetent hairless mice (SKH1 strain) were sensitized and challenged topically on back and ears for about 4 weeks. Back skin and ears thickness were measured using calliper at 3 occasions per week in complement to a macroscopic evaluation of atopic dermatitis lesions on back: erythema, scaling and excoriations scoring. In addition, OCT was performed on the back and ears of animals. OCT allows a virtual in-depth section (tomography) of the imaged organ to be made using a laser, a camera and image processing software allowing fast, non-contact and non-denaturing acquisitions of the explored tissues. To perform the imaging sessions, the animals were anesthetized with isoflurane, placed on a support under the OCT for a total examination time of 5 to 10 minutes. The results show a good correlation of the OCT technique with classical HES histology for skin lesions structures such as hyperkeratosis, epidermal hyperplasia, and dermis thickness. This OCT imaging technique can, therefore, be used in live animals at different times for longitudinal evaluation by repeated measurements of lesions in the same animals, in addition to the classical histological evaluation. Furthermore, this original imaging technique speeds up research protocols, reduces the number of animals and refines the use of the laboratory animal.

Keywords: atopic dermatitis, mouse model, oxzolone model, histology, imaging

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Authors: J. Nyenhuis, J. Drelich

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This research study was designed to determine if food crops could be bio-fortified with micro-nutrients by growing sprouts on mineral fortified fiber mats. Diets high in processed foods have been found to lack essential micro-nutrients for optimum human development and overall health. Some micro-nutrients such as copper (Cu) have been found to enhance the inflammatory response through its oxidative functions, thereby having a role in cardiovascular disease (CVD), metabolic syndrome (MetS), diabetes and related complications. Recycled cellulose fibers and clay saturated with micro-nutrient ions can be converted to a novel mineral-metal hybrid material in which the fiber mat becomes a carrier of essential micro-nutrients. The reduction of ionic to metallic copper was accomplished using hydrogen at temperatures ranging from 400o to 600oC. Copper particles with diameters ranging from ~1 to 400-500 nm reside on the recycled fibers that make up the mats. Seeds purchased from a commercial, organic supplier were germinated on the specially engineered cellulose fiber mats that incorporated w10 wt% clay fillers saturated with either copper particles or ionic copper. After the appearance of the first leaves, the sprouts were dehydrated and analyzed for Cu content. Nutrient analysis showed 1.5 to 1.6 increase in Cu of the sprouts grown on the fiber mats with copper particles, and 2.3 to 2.5 increase on mats with ionic copper as compared to the control samples. The antibacterial properties of materials saturated with copper ions at room temperature and at temperatures up to 400°C have been verified with halo method tests against Escherichia Coli in previous studies. E. coli is a known pathogenic risk in sprout production. Copper exhibits excellent antibacterial properties when tested on S. aureus, a pathogenic gram-positive bacterium. This has also been confirmed for the fiber-copper hybrid material in this study. This study illustrates the potential for the use of engineered mats as a viable way to increase the micro-nutrient composition of locally-grown food crops and the need for additional research to determine the uptake, nutritional implications and risks of micro-nutrient bio-fortification.

Keywords: bio-fortification, copper nutrient analysis, micro-nutrient uptake, sprouts and mineral-fortified mats

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Authors: Paul E. Jose

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A new self-report measure named the General Emotion Regulation Measure (GERM) assesses four key goals for experiencing broad valenced groups of emotions: 1) trying to experience positive emotions (e.g., joy, pride, liking a person); 2) trying to avoid experiencing positive emotions; 3) trying to experience negative emotions (e.g., anger, anxiety, contempt); and 4) trying to avoid experiencing negative emotions. Although individual differences in GERM motives have been identified, evidence of validity with common mood outcomes is lacking. In the present study, whether GERM motives predict self-reported subjective happiness and depressive symptoms (CES-D) was tested with a community sample of 833 young adults. It was predicted that the GERM motive of trying to experience positive emotions would positively predict subjective happiness, and analogously trying to experience negative emotions would predict depressive symptoms. An initial path model was constructed in which the four GERM motives predicted both subjective happiness and depressive symptoms. The fully saturated model included three non-significant paths, which were subsequently pruned, and a good fitting model was obtained (CFI = 1.00; RMR = .007). Two GERM motives significantly predicted subjective happiness: 1) trying to experience positive emotions ( = .38, p < .001) and 2) trying to avoid experiencing positive emotions ( = -.48, p <.001). Thus, individuals who reported high levels of trying to experience positive emotions reported high levels of happiness, and individuals who reported low levels of trying to avoid experiencing positive emotions also reported high levels of happiness. Three GERM motives significantly predicted depressive symptoms: 1) trying to avoid experiencing positive emotions ( = .20, p <.001); 2) trying to experience negative emotions ( = .15, p <.001); and 3) trying to experience positive emotions (= -.07, p <.001). In agreement with predictions, trying to experience positive emotions was positively associated with subjective happiness and trying to experience negative emotions was positively associated with depressive symptoms. In essence, these two valenced mood states seem to be sustained by trying to experience similarly valenced emotions. However, the three other significant paths in the model indicated that emotional motives play a complicated role in supporting both positive and negative mood states. For subjective happiness, the GERM motive of not trying to avoid positive emotions, i.e., not avoiding happiness, was also a strong predictor of happiness. Thus, people who report being the happiest are those individuals who not only strive to experience positive emotions but also are not ambivalent about them. The pattern for depressive symptoms was more nuanced. Individuals who reported higher depressive symptoms also reported higher levels of avoiding positive emotions and trying to experience negative emotions. The strongest predictor for depressed mood was avoiding positive emotions, which would suggest that happiness aversion or fear of happiness is an important motive for dysphoric people. Future work should determine whether these patterns of association are similar among clinically depressed people, and longitudinal data are needed to determine temporal relationships between motives and mood states.

Keywords: emotions motives, depression, subjective happiness, path model

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Authors: Adriana-Gabriela Plaiasu, Catalin Marian Ducu

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The interest in the unique properties associated with materials having structures on a nanometer scale has been increasing at an exponential rate in last decade. Among the functional mineral compounds such as perovskite (CaTiO3), rutile (TiO2), CaF2, spinel (MgAl2O4), wurtzite (ZnS), zincite (ZnO) and the cupric oxide (CuO) has been used in numerous applications such as catalysis, semiconductors, batteries, gas sensors, biosensors, field transistors and medicine. The Solar Physical Vapor Deposition (SPVD) presented in the paper as elaboration method is an original process to prepare nanopowders working under concentrated sunlight in 2kW solar furnaces. The influence of the synthesis parameters on the chemical and microstructural characteristics of zinc and manganese oxides synthesized nanophases has been systematically studied using XRD, TEM and SEM.

Keywords: characterization, morphological, nano-oxides, structural

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Authors: Jing Yuan, Hongwei Yang

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This paper aims to understand U.S. middle school students’ mathematics achievements by examining relevant student and school-level predictors. Through a variance component analysis, the study first identifies evidence supporting the use of multilevel modeling. Then, a multilevel analysis is performed under Bayesian statistical inference where prior information is incorporated into the modeling process. During the analysis, independent variables are entered sequentially in the order of theoretical importance to create a hierarchy of models. By evaluating each model using Bayesian fit indices, a best-fit and most parsimonious model is selected where Bayesian statistical inference is performed for the purpose of result interpretation and discussion. The primary dataset for Bayesian modeling is derived from the Program for International Student Assessment (PISA) in 2012 with a secondary PISA dataset from 2003 analyzed under the traditional ordinary least squares method to provide the information needed to specify informative priors for a subset of the model parameters. The dependent variable is a composite measure of mathematics literacy, calculated from an exploratory factor analysis of all five PISA 2012 mathematics achievement plausible values for which multiple evidences are found supporting data unidimensionality. The independent variables include demographics variables and content-specific variables: mathematics efficacy, teacher-student ratio, proportion of girls in the school, etc. Finally, the entire analysis is performed using the MCMCpack and MCMCglmm packages in R.

Keywords: Bayesian multilevel modeling, mathematics education, PISA, multilevel

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Authors: Zerarka Hizia, Akchiche Mustapha, Prunier Florent

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The landslide of Ain El Hammam (AEH) is characterized by a complex geology and a high hydrogeology hazard. AEH's perpetual reactivation compels us to look closely at its triggers and to better understand the mechanisms of its evolution in mass and in depth. This study builds a numerical model to simulate the influencing factors such as precipitation, non-saturation, and pore pressure fluctuations, using Plaxis software. For a finer analysis of instabilities, we use Hill's criterion, based on the sign of the second order work, which is the most appropriate material stability criterion for non-associated elastoplastic materials. The results of this type of calculation allow us, in theory, to predict the shape and position of the slip surface(s) which are liable to ground movements of the slope, before reaching the rupture given by the plastic limit of Mohr Coulomb. To validate the numerical model, an analysis of inclinometer measures is performed to confirm the direction of movement and kinematic of the sliding mechanism of AEH’s slope.

Keywords: landslide, second order work, precipitation, inclinometers

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Authors: Taha Ahmed Husain

Abstract:

The dynamic characteristics such as speed and torque as well as voltages and currents of pwm brushless DC motor inverter are analyzed with a MATLAB model. The contribution of external load torque and friction torque is monitored. The switching function technique is adopted for the current control of the embedded three phase inverter that drives the brushless DC motor.In switching functions the power conversions circuits can be modeled according to their functions rather than circuit topologies. Therefore, it can achieve simplification of the overall power conversion functions. The trapezoidal type (back emf) is used in the model as ithas lower switching loss compared with sinusoidal type (back emf). Results show reliable time analysis for speed, torque, phase and line voltages and currents and the effect of current commutation is clearly observed.

Keywords: BLDC motor, brushless dc motors, pwm inverter, DC motor control, trapezoidal back emf, ripple torque in brushless DC motor

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Authors: Jesus David Argueta Moreno, Justa Rufina Martel, Edith Gabriela Carrasco

Abstract:

The Central American Coffee small, medium, and large corporations search for excellence, sustainability, and continuous improvement, triggers in a still unknown scale the Local expansion, crusading, and franchising strategies towards a more suitable commercial opportunity, where the dynamics of the Central American business displacement can be explained through the markets permeability traits. By considering the previously mentioned, the present study aims to evaluate the franchising potentialities offered by Central American Coffee business scenario, in order to explain dynamics of the business demography phenomena and its relevance on the Central American competitiveness landscape.

Keywords: competitiveness, franchising, business demography, Central American Coffee

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Authors: Kunthida Kulprateepunya, Napat Boontiam, Bunthita Phuasa, Chatsuda Kankayant, Bantoeng Polsawat, Sumran Poontong

Abstract:

Frailty is the thin line between good health and illness. The syndrome is more common in the elderly who transition from strong to weak. (Vulnerability). Fragility can prevent and promote healthy recovery before it goes into disability. This research and development aim to analyze the situation analysis of frailty of the elderly, develop a program, and evaluate the effect of a health promotion program to prevent and solve the problem of frailty among the elderly. The research consisted of 3 phases: 1) analysis of the frailty situation, 2) development of a model, 3) evaluation of the effectiveness of the model. Samples were 328, 122 elderlies using the multi-stage random sampling method. The research instrument was a frailty questionnaire use of the five symptoms, the main characteristics were muscle weakness, slow walking, low physical activity. Fatigue and unintentional weight loss, criteria frailty use more than or equal to three or more symptoms are frailty. Data were analyzed by descriptive and t-test dependent test statistics. The findings showed three parts. First, frailty in the elderly was 23.05 percentage and 56.70% pre-frailty. Second, it was development of a health promotion program to prevent and solve the problem of frailty the elderly with a combination of Nine-Square Exercise, Elastic Band Exercise, Elastic Coconut Shell. Third, evaluation of the effectiveness of the model by comparison of the elderly's get up and go test, the average time before using the program was 14.42 and after using the program was 8.57. It was statistically significant at the .05 level. In conclusion, the findings can used to develop guidelines to promote the health of the frailty elderly.

Keywords: elderly, fragile, nine-square exercise, elastic coconut shell

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Authors: Nisha Singh, Munish Puri, Collin Barrow, Deepak Tuli, Anshu S. Mathur

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The biological conversion of lignocellulosic biomass to ethanol is a promising strategy to solve the present global crisis of exhausting fossil fuels. The existing bioethanol production technologies have cost constraints due to the involvement of mandate pretreatment and extensive enzyme production steps. A unique process configuration known as consolidated bioprocessing (CBP) is believed to be a potential cost-effective process due to its efficient integration of enzyme production, saccharification, and fermentation into one step. Due to several favorable reasons like single step conversion, no need of adding exogenous enzymes and facilitated product recovery, CBP has gained the attention of researchers worldwide. However, there are several technical and economic barriers which need to be overcome for making consolidated bioprocessing a commercially viable process. Finding a natural candidate CBP organism is critically important and thermophilic anaerobes are preferred microorganisms. The thermophilic anaerobes that can represent CBP mainly belong to genus Clostridium, Caldicellulosiruptor, Thermoanaerobacter, Thermoanaero bacterium, and Geobacillus etc. Amongst them, Clostridium thermocellum has received increased attention as a high utility CBP candidate due to its highest growth rate on crystalline cellulose, the presence of highly efficient cellulosome system and ability to produce ethanol directly from cellulose. Recently with the availability of genetic and molecular tools aiding the metabolic engineering of Clostridium thermocellum have further facilitated the viability of commercial CBP process. With this view, we have specifically screened cellulolytic and xylanolytic thermophilic anaerobic ethanol producing bacteria, from unexplored hot spring/s in India. One of the isolates is a potential CBP organism identified as a new strain of Clostridium thermocellum. This strain has shown superior avicel and xylan degradation under unoptimized conditions compared to reported wild type strains of Clostridium thermocellum and produced more than 50 mM ethanol in 72 hours from 1 % avicel at 60°C. Besides, this strain shows good ethanol tolerance and growth on both hexose and pentose sugars. Hence, with further optimization this new strain could be developed as a potential CBP microbe.

Keywords: Clostridium thermocellum, consolidated bioprocessing, ethanol, thermophilic anaerobes

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Authors: El Andari Chifaa, Bouaziz Rached

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The central focus of this paper was to check whether the Okun’s law in Tunisia is valid or not. For this purpose, we have used quarterly time series data during the period 1990Q1-2014Q1. Firstly, we applied the error correction model instead of the difference version of Okun's Law, the Engle-Granger and Johansen test are employed to find out long run association between unemployment, production, and how error correction mechanism (ECM) is used for short run dynamic. Secondly, we used the gap version of Okun’s law where the estimation is done from three band pass filters which are mathematical tools used in macro-economic and especially in business cycles theory. The finding of the study indicates that the inverse relationship between unemployment and output is verified in the short and long term, and the Okun's law holds for the Tunisian economy, but with an Okun’s coefficient lower than required. Therefore, our empirical results have important implications for structural and cyclical policymakers in Tunisia to promote economic growth in a context of lower unemployment growth.

Keywords: Okun’s law, validity, unit root, cointegration, error correction model, bandpass filters

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Authors: Cláudia Alcoforado, Anabela Ribeiro

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This paper is part of an ongoing PhD thesis. It seeks to develop a model to identify the spatial failures of the public transportation supply. In the construction of the model, it also seeks to detect the social needs arising from the disadvantage in transport. The case study is carried out for the Brazilian city of Recife. Currently, Recife has a population density of 7,039.64 inhabitants per km². Unfortunately, only 46.9% of urban households on public roads have adequate urbanization. Allied to this reality, the trend of the occupation of the poorest population is that of the peripheries, a fact that has been consolidated in Brazil and Latin America, thus burdening the families' income, since the greater the distances covered for the basic activities and consequently also the transport costs. In this way, there have been great impacts caused by the supply of public transportation to locations with low demand or lack of urban infrastructure. The model under construction uses methods such as Currie’s Gap Assessment associated with the London’s Public Transport Access Level, and the Public Transport Accessibility Index developed by Saghapour. It is intended to present the stage of the thesis with the spatial/need gaps of the neighborhoods of Recife already detected. The benefits of the geographic information system are used in this paper. It should be noted that gaps are determined from the transport supply indices. In this case, considering the presence of walking catchment areas. Still in relation to the detection of gaps, the relevant demand index is also determined. This, in turn, is calculated through indicators that reflect social needs. With the use of the smaller Brazilian geographical unit, the census sector, the model with the inclusion of population density in the study areas should present more consolidated results. Based on the results achieved, an analysis of transportation disadvantage will be carried out as a factor of social exclusion in the study area. It is anticipated that the results obtained up to the present moment, already indicate a strong trend of public transportation in areas of higher income classes, leading to the understanding that the most disadvantaged population migrates to those neighborhoods in search of employment.

Keywords: gap assessment, public transport supply, social exclusion, spatial gaps

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

Abstract:

In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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