Search results for: sensory processing disorders

Authors: Qingsheng Qi, Cuijuan Gao, Carol Sze Ki Lin

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Food waste can be defined as a by-product of food processing by industries and consumers, which has not been recycled or used for other purposes. Stringent waste regulations worldwide are pushing local companies and sectors towards higher sustainability standards. The development of novel strategies for food waste re-use is economically and environmentally sound, as it solves a waste management issue and represents an inexpensive nutrient source for biotechnological processes. For example, Yarrowia lipolytica is a yeast which can utilize hydrophobic substrates, such as fatty acids, lipids, and alkanes and simple carbon sources, such as glucose and glycerol, which can all be found in food waste. This broad substrate range makes Y. lipolytica a promising candidate for the degradation and valorisation of food waste, and for the production of organic acids, such as citric and α-ketoglutaric acids. Current research conducted in our group demonstrated that Y. lipolytica was shown to be able to produce succinic acid. In this talk, we will focus on the application of genetically modified yeast Y. lipolytica for fermentative succinic acid production with an aim to increase productivity and yield.

Keywords: food waste, succinic acid, Yarrowia lipolytica, bioplastic

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: Tarantino E., Disciglio G., Gagliardi A., Gatta G., Tarantino A.

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Fertilizer is a critical input for improving production and increasing crop yields. Consecutive experimental trials during six years (from 2010-2015) were carried out in Apulia region (south-eastern Italy) on seven crops grown in cylinder pots. The aim was to determinate the effects of chemical and organic fertilizer on marketable yield and other parameters of processing tomato (Lycopersicum esculentum L., cv Docet), lettuce (Lactuca sativa L., cv Canasta), cauliflower (Brassica oleracea L., cv Casper), pepper (Capsicum annum L., cv Akron), fennel (Foeniculum vulgare L., cv Tarquinia), eggplant (Solanum melongena L. cv Primato F1) and chard (Beta vulgaris L., Argentata). At harvest the quail-quantitative yield characteristics of each crop were determined. All of the experimental data were subjected to analysis of variance (ANOVA). Results showed that the yields for all of these crops were greater under the chemical system than the organic system whereas quite variable results were generally observed for the other characteristics of the yield.

Keywords: fertilizers, herbaceous crops, yield characteristics, succession

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

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Authors: Angsumalin Puntho

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Disruptive technology has had a great influence on our everyday lives and the existence of an organization. Geologists in the public sector need to keep up with digital technology and be able to work and collaborate in a more effective manner. The result from SWOT and 7S McKinsey analyses suggest that there are inadequate IT personnel, no individual digital literacy development plan, and a misunderstanding of management policies. The Office of Civil Service Commission develops digital literacy skills that civil servants and government officers should possess in order to work effectively; it consists of nine dimensions, including computer skills, internet skills, cyber security awareness, word processing, spreadsheets, presentation programs, online collaboration, graphics editors and cyber security practices; and six steps of digital literacy development including self-assessment, individual development plan, self-learning, certified test, learning reflection, and practices. Geologists can use digital literacy as a learning tool to develop themselves for better career opportunities.

Keywords: disruptive technology, digital technology, digital literacy, computer skills

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Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

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Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

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Authors: Leyli Khavari, Javad Yousefian

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The aim of this study was to investigate the effect of physical biorhythm cycle on health-related fitness factors. For this purpose, 120 athlete and non-athlete male and female students were selected randomly and based on the level of physical activity divided into athletic and non-athletic groups. The exact date of birth and also when the subjects were in the positive, negative and critical physical biorhythm cycle was determined by calculation software biorhythm. The physical fitness factors tests, including Queens College Step Test, AAHPERD sit-ups; Wells stretch test and hand dynamometer. Students in three stages in positive, negative and critical physical cycle were tested. Data processing using SPSS software and statistical tests ANOVA with repeated measures and student t test was used for dependent. The results of this study showed that changes in physical fitness and physical biorhythm were not affected by changes in the 23-day physical cycle.

Keywords: AAHPERD test, biorhythm, physical cycle, Queens College Step Test

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Abdelhadi Adel, Kadri Ouahab

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This paper proposes an improved approach based on MAS Architecture and Heuristic Algorithm for systematic maintenance to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

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Authors: H. Maachou, A. Chagnes, G. Cote

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The present work reports the properties of chitosan/hydroxyapatite (Cs/HA: 100/00, 70/30 and 30/70) composite microspheres obtained by emulsification processing route. The morphology of chitosane microspheres was observed by a scanning electron microscope (SEM) which shows an aggregate of spherical microspheres with a particle size, determined by optical microscope, ranged from 4 to 10 µm. Thereafter, a biomimetic approach was used to study the in vitro biomineralization of these composites. It concerns the composites immersion in simulated body fluid (SBF) for different times. The deposited calcium phosphate was studied using X-ray diffraction analysis (XRD), FTIR spectroscopy and ICP analysis of phosphorus. In fact, the mineral formed on Cs/HA microspheres was a mixture of carbonated HA and β-TCP as showed by FTIR peaks at 1419,5 and 871,8 cm-1 and XRD peak at 29,5°. This formation was induced by the presence of HA in chitosan microspheres. These results are confirmed by SEM micrographs which chow the Ca-P crystals growth in form of cauliflowers. So, these materials are of great interest for bone regeneration applications due to their ability to nucleate calcium phosphates in presence of simulated body fluid (SBF).

Keywords: hydroxyapatite, chitosan, microsphere, composite, bone regeneration

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Authors: Frantisek Bozek, Pavel Budinsky, Ignac Hoza, Alexandr Bozek, Magdalena Naplavova

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A cleaner production project was implemented in a bakery. The project is based on the substitution of the best available technique for an obsolete leaven production technology. The new technology enables production of durable, high-quality leavens. Moreover, 25% of flour as the original raw material can be replaced by pastry from the previous day production which has not been sold. That pastry was previously disposed in a waste incineration plant. Besides the environmental benefits resulting from less waste, lower consumption of energy, reduction of sewage waters quantity and floury dustiness there are also significant economic benefits. Payback period of investment was calculated with help of static method of financial analysis about 2.6 years, using dynamic method 3.5 years and an internal rate of return more than 29%. The supposed annual average profit after taxation in the second year of operation was incompliance with the real profit.

Keywords: bakery, best available technology, cleaner production, costs, economic benefit, efficiency, energy, environmental benefit, investment, savings

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Authors: Ramim Tanver Rahman, Muhammad Mahbub Sobhan, M. A. Alim

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This study reports on processing of biscuits using skinned, treated and dried cassava flour. Five samples of biscuits S2, S3, S4, S5, and S6 containing 8, 16, 24, 32, and 40% cassava flour with wheat flour and a control sample (S1) containing no cassava flour were processed. The weights of all the biscuit samples were higher than that of control biscuit. The biscuit containing cassava flour was lower width than the control biscuit. The spread ratio of biscuits with 16% cassava flour was higher than other combinations of cassava flour. No remarkable changes in moisture content, peroxide value, fatty acid value, texture, and flavor were observed up to 4 months of storage in ambient conditions (27° to 35°C). A decreasing trend in color, flavor, texture and overall acceptability was observed with the increased incorporation of cassava flour. The sample S1 (no cassava flour) secured the highest overall acceptability and sample S6 (40% cassava flour) obtained the lowest overall acceptability. It is recommended that good quality cassava flour fortified biscuits may be processed in industrial-scale substituting the wheat flour by cassava flour up to 24% levels.

Keywords: cassava flour, wheat flour, shelf life, spread ratio, storage, biscuit

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Authors: Najmeh Hoseini

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Strokerecovery happens through neuroplasticity, which is highly influenced by the environment, including neuro-rehabilitation. Transcranial direct current stimulation (tDCS) may enhance recovery by modulating neuroplasticity. With tDCS, weak direct currents are applied noninvasively to modify excitability in the cortical areas under its electrodes. Combined with functional activities, this may facilitate motor recovery in neurologic disorders such as stroke. The purpose of this case study was to examine the effect of tDCS combined with 30 minutes of traditional physical therapy (PT)on arm function following a stroke. A 29-year-old male with chronic stroke involving the left middle cerebral artery territory went through the treatment protocol. Design The design included 5 weeks of treatment: 1 week of traditional PT, 2 weeks of sham tDCS combined with traditional PT, and 2 weeks of tDCS combined with traditional PT. PT included functional electrical stimulation (FES) of wrist extensors followed by task-specific functional training. Dual hemispheric tDCS with 1 mA intensity was applied on the sensorimotor cortices for the first 20 min of the treatment combined with FES. Assessments before and after each treatment block included Modified Ashworth Scale, ChedokeMcmaster Arm and Hand inventory, Action Research Arm Test (ARAT), and the Box and Blocks Test. Results showed reduced spasticity in elbow and wrist flexors only after tDCS combination weeks (+1 to 0). The patient demonstrated clinically meaningful improvements in gross motor and fine motor control over the duration of the study; however, components of the ARAT that require fine motor control improved the greatest during the experimental block. Average time improvement compared to baseline was26.29 s for tDCS combination weeks, 18.48 s for sham tDCS, and 6.83 for PT standard of care weeks. Combining dual hemispheric tDCS with the standard of care PT demonstrated improvements in hand dexterity greater than PT alone in this patient case.

Keywords: tDCS, stroke, case study, physical therapy

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: A. Hamma, A. Pegoretti

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The paper focuses on the evaluation of mechanical performances and viscoelastic behaviour of starch-grafted-PP reinforced with kenaf fibres. Investigations were carried out on composites prepared by melt compounding and compression molding. Two aspects have been taken into account, the effects of various fibres loading rates (10, 20 and 30 wt.%) and the fibres aspect ratios (L/D=30 and 160). Good fibres/matrix interaction has been evidenced by SEM observations. However, processing induced variation of fibre length quantified by optical microscopy observations. Tensile modulus and ultimate properties, hardness and tensile impact stress, were found to remarkably increase with fibre loading. Moreover, short term tensile creep tests have proven that kenaf fibres improved considerably the creep stability. Modelling of creep behaviour by a four parameter Burger model was successfully used. An empirical equation involving Halpin-Tsai semi empirical model was also used to predict the elastic modulus of composites.

Keywords: mechanical properties, creep, fibres, thermoplastic composites, starch-grafted-PP

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Authors: Tuyuan Cheng

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As we age, many things become more difficult. Among the abilities are the linguistic and cognitive ones. Competing theories have shown that these two functions could diminish together or that one is selectively affected by the other. In other words, some proposes aging affects sentence production in the same way it affects sentence comprehension and other cognitive functions, while some argues it does not.To address this question, the current investigation is conducted into the critical aspect of sentences as well as cognitive abilities – the syntactic complexity and the number of perspective shifts being contained in the elicited production. Healthy non-pathological aging is often characterized by a cognitive and neural decline in a number of cognitive abilities. Although the language is assumed to be of the more stable domain, a variety of findings in the cognitive aging literature would suggest otherwise. Older adults often show deficits in language production and multiple aspects of comprehension. Nevertheless, while some age differences likely reflect cognitive decline, others might reflect changes in communicative goals, and some even display cognitive advantages. In the domain of language processing, research efforts have been made in tests that probed a variety of communicative abilities. In general, there exists a distinction: Comprehension seems to be selectively unaffected, while production does not. The current study raises a novel question and investigates whether aging affects the production of relative clauses (RCs) under the cognitive factor of perspective shifts. Based on Perspective Hypothesis (MacWhinney, 2000, 2005), our cognitive processes build upon a fundamental system of perspective-taking, and language provides a series of cues to facilitate the construction and shifting of perspectives. These cues include a wide variety of constructions, including RCs structures. In this regard, linguistic complexity can be determined by the number of perspective shifts, and the processing difficulties of RCs can be interpreted within the theory of perspective shifting. Two experiments were conducted to study language production under controlled conditions. In Experiment 1, older healthy participants were tested on standard measures of cognitive aging, including MMSE (Mini-Mental State Examination), ToMI-2 (a simplified Theory of Mind Inventory-2), and a perspective-shifting comprehension task programmed with E-Prime. The results were analyzed to examine if/how they are correlated with aging people’s subsequent production data. In Experiment 2, the production profile of differing RCs, SRC vs. ORC, were collected with healthy aging participants who perform a picture elicitation task. Variable containing 0, 1, or 2 perspective shifts were juxtaposed respectively to the pictures and counterbalanced presented for elicitation. In parallel, a controlled group of young adults were recruited to examine the linguistic and cognitive abilities in question. The results lead us to the discussion whetheraging affects RCs production in a manner determined by its semantic structure or the number of perspective shifts it contains or the status of participants’ mental understanding. The major findingsare: (1) Elders’ production on Chinese RCtypes did not display intrinsic difficulty asymmetry. (2) RC types (the linguistic structural features) and the cognitiveperspective shifts jointly play important roles in the elders’ RCproduction. (3) The production of RC may defy the aging in the case offlexibly preserved cognitive ability.

Keywords: cognition aging, perspective hypothesis, perspective shift, relative clauses, sentence complexity

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Authors: Bernice Jeanne Lottering, Yi-Wen Lin

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Introduction: Chronic pain has a definitive lack of objective parameters in the measurement and treatment efficacy of diseases such as Fibromyalgia (FM). Persistent widespread pain and generalized tenderness are the characteristic symptoms affecting a large majority of the global population, particularly females. This disease has indicated a refractory tendency to conventional treatment ventures, largely resultant from a lack of etiological and pathogenic understanding of the disease development. Emerging evidence indicates that the central nervous system (CNS) plays a critical role in the amplification of pain signals and the neurotransmitters associated therewith. Various stimuli have been found to activate the channels existent on nociceptor terminals, thereby actuating nociceptive impulses along the pain pathways. The transient receptor potential vanalloid 1 (TRPV1) channel functions as a molecular integrator for numerous sensory inputs, such as nociception, and was explored in the current study. Current intervention approaches face a multitude challenges, ranging from effective therapeutic interventions to the limitation of pathognomonic criteria resultant from incomplete understanding and partial evidence on the mechanisms of action of FM. It remains unclear whether electroacupuncture (EA) plays an integral role in the functioning of the TRPV1 pathway, and whether or not it can reduce the chronic pain induced by FM. Aims: The aim of this study was to explore the mechanisms underlying the activation and modulation of the TRPV1 channel pathway in a cold stress model of FM applied to a murine model. Furthermore, the effect of EA in the treatment of mechanical and thermal pain, as expressed in FM was also to be investigated. Methods: 18 C57BL/6 wild type and 6 TRPV1 knockout (KO) mice, aged 8-12 weeks, were exposed to an intermittent cold stress-induced fibromyalgia-like pain model, with or without EA treatment at ZusanLi ST36 (2Hz/20min) on day 3 to 5. Von Frey and Hargreaves behaviour tests were implemented in order to analyze the mechanical and thermal pain thresholds on day 0, 3 and 5 in control group (C), FM group (FM), FM mice with EA treated group (FM + EA) and FM in KO group. Results: An increase in mechanical and thermal hyperalgesia was observed in the FM, EA and KO groups when compared to the control group. This initial increase was reduced in the EA group, which directs focus at the treatment efficacy of EA in nociceptive sensitization, and the analgesic effect EA has attenuating FM associated pain. Discussion: An increase in the nociceptive sensitization was observed through higher withdrawal thresholds in the von Frey mechanical test and the Hargreaves thermal test. TRPV1 function in mice has been scientifically associated with these nociceptive conduits, and the increased behaviour test results suggest that TRPV1 upregulation is central to the FM induced hyperalgesia. This data was supported by the decrease in sensitivity observed in results of the TRPV1 KO group. Moreover, the treatment of EA showed a decrease in this FM induced nociceptive sensitization, suggesting TRPV1 upregulation and overexpression can be attenuated by EA at bilateral ST36. This evidence compellingly implies that the analgesic effect of EA is associated with TRPV1 downregulation.

Keywords: fibromyalgia, electroacupuncture, TRPV1, nociception

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Authors: Miroslav Popelka, Jakub Nozicka

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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

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Authors: Muna F. Al-Sammaraie

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The aim of this research is to present a multi spectral image enhancement methods used to achieve highly real digital image populates only a small portion of the available range of digital values. Also, a quantitative measure of image enhancement is presented. This measure is related with concepts of the Webers Low of the human visual system. For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. This study involves changing the original values so that more of the available range is used; then increases the contrast between features and their backgrounds. It consists of reading the binary image on the basis of pixels taking them byte-wise and displaying it, calculating the statistics of an image, automatically enhancing the color of the image based on statistics calculation using algorithms and working with RGB color bands. Finally, the enhanced image is displayed along with image histogram. A number of experimental results illustrated the performance of these algorithms. Particularly the quantitative measure has helped to select optimal processing parameters: the best parameters and transform.

Keywords: image enhancement, multi-spectral, RGB, histogram

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: G. Cunningham, E. Cantor, X. Wu, F. Shen, G. Jiang, S. Philips, C. Bales, Y. Xiao, T. R. Cummins, J. C. Fehrenbacher, B. P. Schneider

Abstract:

Background: Taxane-induced peripheral neuropathy (TIPN) is the most devastating survivorship issue for patients receiving therapy. Dose reductions due to TIPN in the curative setting lead to inferior outcomes for African American patients, as prior research has shown that this group is more susceptible to developing severe neuropathy. The mechanistic underpinnings of TIPN, however, have not been entirely elucidated. While it would be appealing to use primary tissue to study the development of TIPN, procuring nerves from patients is not realistically feasible, as nerve biopsies are painful and may result in permanent damage. Therefore, our laboratory has investigated paclitaxel-induced neuronal morphological and molecular changes using an ex vivo model of human-induced pluripotent stem cell (iPSC)-derived neurons. Methods: iPSCs are undifferentiated and endlessly dividing cells that can be generated from a patient’s somatic cells, such as peripheral blood mononuclear cells (PBMCs). We successfully reprogrammed PBMCs into iPSCs using the Erythroid Progenitor Reprograming Kit (STEMCell Technologiesᵀᴹ); pluripotency was verified by flow cytometry analysis. iPSCs were then induced into neurons using a differentiation protocol that bypasses the neural progenitor stage and uses selected small-molecule modulators of key signaling pathways (SMAD, Notch, FGFR1 inhibition, and Wnt activation). Results: Flow cytometry analysis revealed expression of core pluripotency transcription factors Nanog, Oct3/4 and Sox2 in iPSCs overlaps with commercially purchased pluripotent cell line UCSD064i-20-2. Trilineage differentiation of iPSCs was confirmed with immunofluorescent imaging with germ-layer-specific markers; Sox17 and ExoA2 for ectoderm, Nestin, and Pax6 for mesoderm, and Ncam and Brachyury for endoderm. Sensory neuron markers, β-III tubulin, and Peripherin were applied to stain the cells for the maturity of iPSC-derived neurons. Patch-clamp electrophysiology and calcitonin gene-related peptide (CGRP) release data supported the functionality of the induced neurons and provided insight into the timing for which downstream assays could be performed (week 4 post-induction). We have also performed a cell viability assay and fluorescence-activated cell sorting (FACS) using four cell-surface markers (CD184, CD44, CD15, and CD24) to select a neuronal population. At least 70% of the cells were viable in the isolated neuron population. Conclusion: We have found that these iPSC-derived neurons recapitulate mature neuronal phenotypes and demonstrate functionality. Thus, this represents a patient-derived ex vivo neuronal model to investigate the molecular mechanisms of clinical TIPN.

Keywords: chemotherapy, iPSC-derived neurons, peripheral neuropathy, taxane, paclitaxel

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Authors: Yu Liang, Wei Wei

Abstract:

Spatial representation of numbers and numerical magnitude are important for preschoolers’ mathematical ability. Mental number line, a typical index to measure numbers spatial representation, and numerical comparison are both related to arithmetic obviously. However, they seem to rely on different mechanisms and probably influence arithmetic through different mechanisms. In line with this idea, preschool children were trained with two tasks to investigate which one is more important for approximate arithmetic. The training of numerical processing and number line estimation were proved to be effective. They both improved the ability of approximate arithmetic. When the difficulty of approximate arithmetic was taken into account, the performance in number line training group was not significantly different among three levels. However, two harder levels achieved significance in numerical comparison training group. Thus, comparing spatial representation ability, symbolic approximation arithmetic relies more on numerical magnitude. Educational implications of the study were discussed.

Keywords: approximate arithmetic, mental number line, numerical magnitude, preschooler

Procedia PDF Downloads 254

Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

Abstract:

This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

Procedia PDF Downloads 335

Authors: Birgul Hizlar, Sibel Karakaya

Abstract:

Nowadays, consumers are more and more aware of the benefits beyond basic nutrition provided by food and food compounds. Between these, carotenoids have been demonstrated to exhibit multiple health benefits (for example, some types of cancer, cardiovascular diseases, eye disorders, among others). However, carotenoid bioaccessibility and bioavailability is generally rather low due to their specific localization in plant tissue and lipophilic nature. This situation is worldwide issue, since both developed and developing countries have their interest and benefits in increasing the uptake of carotenoids from the human diet. Recently, a new class of foods designed to improve the bioaccessibility/bioavailability of orally administered bioactive compounds is introduced: excipient foods. Excipient foods are specially designed foods which are prepared depending on the physicochemical properties of target bioactive compounds and increasing the bioavailability or bioaccessibility of bioactive compound. In this study, effects of food matrix (greating, boiling and mashing) and different excipient foods (olive oil, lemon juice, whey curd and dried artichoke leaf powder) on bioaccessibility of β-carotene in carrot were investigated by means of simulating in vitro gastrointestinal (GI) digestion. β-carotene contents of grated, boiled and mashed (after boiling process) carrots were 79.28, 147.63 and 151.19 μg/g respectively. No significant differences among boiled and mashed samples indicated that mashing process had no effect on the release of β-carotene from the food matrix (p > 0.05). On the contrary, mashing causes significant increase in the β-carotene bioaccessibility (p < 0.05). The highest β-carotene content was found in the mashed carrots incorporated with olive oil and lemon juice (C2). However, no significant differences between that sample and C1 (mashed carrot with lemon juice, olive oil, dried artichoke leaf powder), C3 (mashed carrot with addition of olive oil, lemon juice, whey curd) and). Similarly, the highest β-carotene bioaccessibility (50.26%) was found mashed C3 sample (p < 0.05). The increase in the bioaccessibility was approximately 5 fold and 50 fold when compared to grated and mashed samples containing olive oil, lemon juice and whey curd. The results demonstrate that both, food matrix and excipient foods, are able to increase the bioaccessibility of β-carotene.

Keywords: bioaccessibility, carotenoids, carrot, β-carotene

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Authors: Abdessalam Hijab, Hafida Boulekbache, Eric Henry

Abstract:

The objective of this article is to explain the use of geographic information system (GIS) and information and communication technologies (ICTs) in the real-time processing and analysis of data on the status of an urban sanitation network by integrating professional actors in sanitation for sustainable management in urban areas. Indeed, it is a smart geo-collaboration based on the complementarity of ICTs and GIS. This multi-actor reflection was built with the objective of contributing to the development of complementary solutions to the existing technologies to better protect the urban environment, with the help of a checklist with the spatial reference "E-Géo-LD" dedicated to the "professional/professional" actors in sanitation, for intelligent monitoring of liquid sanitation networks in urban areas. In addition, this research provides a good understanding and assimilation of liquid sanitation schemes in the "Lamkansa" sampling area of the city of Casablanca, and spatially evaluates these schemes. Downstream, it represents a guide to assess the environmental impacts of the liquid sanitation scheme.

Keywords: ICT, GIS, spatial checklist, liquid sanitation, environment

Procedia PDF Downloads 237