Search results for: functional vision

Authors: Amin Asgarian, Ghyslaine McClure

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Proper seismic evaluation of Non-Structural Components (NSCs) mandates an accurate estimation of floor seismic demands (i.e. acceleration and displacement demands). Most of the current international codes incorporate empirical equations to calculate equivalent static seismic force for which NSCs and their anchorage system must be designed. These equations, in general, are functions of component mass and peak seismic acceleration to which NSCs are subjected to during the earthquake. However, recent studies have shown that these recommendations are suffered from several shortcomings such as neglecting the higher mode effect, tuning effect, NSCs damping effect, etc. which cause underestimation of the component seismic acceleration demand. This work is aimed to circumvent the aforementioned shortcomings of code provisions as well as improving them by proposing a simplified, practical, and yet accurate approach to generate acceleration Floor Design Spectra (FDS) directly from corresponding Uniform Hazard Spectra (UHS) (i.e. design spectra for structural components). A database of 27 Reinforced Concrete (RC) buildings in which Ambient Vibration Measurements (AVM) have been conducted. The database comprises 12 low-rise, 10 medium-rise, and 5 high-rise buildings all located in Montréal, Canada and designated as post-disaster buildings or emergency shelters. The buildings are subjected to a set of 20 compatible seismic records and Floor Response Spectra (FRS) in terms of pseudo acceleration are derived using the proposed approach for every floor of the building in both horizontal directions considering 4 different damping ratios of NSCs (i.e. 2, 5, 10, and 20% viscous damping). Several effective parameters on NSCs response are evaluated statistically. These parameters comprise NSCs damping ratios, tuning of NSCs natural period with one of the natural periods of supporting structure, higher modes of supporting structures, and location of NSCs. The entire spectral region is divided into three distinct segments namely short-period, fundamental period, and long period region. The derived roof floor response spectra for NSCs with 5% damping are compared with the 5% damping UHS and procedure are proposed to generate roof FDS for NSCs with 5% damping directly from 5% damped UHS in each spectral region. The generated FDS is a powerful, practical, and accurate tool for seismic design and assessment of acceleration-sensitive NSCs particularly in existing post-critical buildings which have to remain functional even after the earthquake and cannot tolerate any damage to NSCs.

Keywords: earthquake engineering, operational and functional components (OFCs), operational modal analysis (OMA), seismic assessment and design

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Authors: I. Benkaddour, Y. Benkaddour, A. Benk Addour

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The structural, elastic, Thermal, electronic, and magnetic properties of intermetallic RMn₂Ge₂ (R= Ca, Y, Nd) are investigated by density functional theory (DFT), using the full potential –linearised augmented plane wave method (FP-LAPW). In this approach, the local-density approximation (LDA) is used for the exchange-correlation (XC) potential. The equilibrium lattice constant and magnetic moment agree well with the experiment. The density of states shows that these phases are conductors, with contribution predominantly from the R and Mn d states. We have determined the elastic constants C₁₁, C₁₂, C₁₃, C₄₄, C₃₃, andC₆₆ at ambient conditions in, which have not been established neither experimentally nor theoretically. Thermal properties, including the relative expansion coefficients and the heat capacity, have been estimated using a quasi-harmonic Debye model.

Keywords: RMn₂Ge₂, intermetallic, first-principles, density of states, mechanical properties

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: M. A. Ghebouli, A. Bouhemadou, H. Choutri, L. Louaila

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Some physical properties of the cubic perovskites CsXF3 (X = Sr, Ca, and Hg) have been investigated using pseudopotential plane–wave (PP-PW) method based on the density functional theory (DFT). The calculated lattice constants within GGA (PBE) and LDA (CA-PZ) agree reasonably with the available experiment data. The elastic constants and their pressure derivatives are predicted using the static finite strain technique. We derived the bulk and shear moduli, Young’s modulus, Poisson’s ratio and Lamé’s constants for ideal polycrystalline aggregates. The analysis of B/G ratio indicates that CsXF3 (X = Ca, Sr, and Hg) are ductile materials. The thermal effect on the volume, bulk modulus, heat capacities CV, CP, and Debye temperature was predicted.

Keywords: perovskite, PP-PW method, elastic constants, electronic band structure

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Authors: Mohamad Chour

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Nowadays, a record number of households are headed by single fathers in most of the European societies. Our research aims to explore how French single fathers experience the domestic sphere, a traditionally feminized field while accomplishing their role of fathers. We adopt a gender role and a parenting role construction theoretical perspectives. Indeed, the interior domestic sphere has been traditionally considered as related to the role of the mother. Moreover, according to the masculine domination theory of Bourdieu, men avoid caregiving and domestic practices that are economically and culturally undervalued. Hence, mothers are considered as more likely to handle the expressive dimension of duties whereas fathers’ role is represented as instrumental, functional and independent. Long interviews have been conducted with twenty French single fathers in order to investigate how the absence of the mother affects the practices of fatherhood. We combined the long interviews with projective techniques method in order to better understand their conception of the family and their family values. Seeking a qualitative diversity, our respondents are from various ages (between 30 and 60); they are coming from different regions in France; living in rural, semi-rural and urban areas. Based on the analysis of 427 pages of data, we identify three main categories of single fathers depending on their strategies to copy and/or delegate the role of the mother. 1) Nurturing fathers completely assume the role of the absent mother as well as her functions. Their discourse is characterized by abnegation and sacrifices reflecting a nurturing role. 2) Juggling fathers are those who take charge of a part of the household duties and delegate the other part to the market or to 'feminine resources' for lacking skills or time. 3) Resistant fathers are the very few respondents who refuse to assume any activities related to the domestic sphere that they perceive as feminine. For lacking competences and even for ideological reasons, they have tendency to delegate all the tasks that were assumed by their ex-spouses. Generally, the majority of fathers seem to experience the domestic sphere differently, and their domestic involvement has been underestimated and even misunderstood. Household duties such as cooking and housekeeping in addition to the nurturing role are experienced by many of the respondents as constructing elements of their fatherhood. Our respondents do not seem to accomplish house holding duties in a functional way. The domestic sphere is managed by those fathers with a strong dimension of abnegation. Thus, our research contributes to illustrating the evolution of gender roles and shows how being simultaneously 'a father and a mother' seems to be an emerging social norm in a French and European cultural context.

Keywords: fathering, gender roles, gender studies, identity construction, single fathers

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Authors: Lara Marie Pangan Lo, Soo Im Chung, Yao Cheng Zhang, Xingyue Jin, Mi Young Kang

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Being the world’s most consumed grain crop, rice (Oryza sativa L.) demands’ have increase and this prompted the development of new rice cultivars with high bio-functional properties than the commonly used white rice. Ordinary rice variety is already known to be a potential source for a number of nutritional as well as bioactive compounds. To further enhance the rice’s nutritive values, germination is done in addition to making it more tasty and palatable when cooked. Pigmented rice, on the other hand, has become increasingly popular in the recent years for their greater antioxidant potential and other nutraceutical properties which can help alleviate the occurrence of the increasing incidence of metabolic diseases. Combining these two (2) parameters, this research study is sought to quantitatively determine the pre-germinated and germinated quantities of the major bioactive compounds of South Korea’s newly developed purplish pigmented rice grain cultivar Superjami (SJ) and red pigmented rice grain Superhongmi (SH) and compare them against the non-pigmented Normal Brown (NB) rice variety. Powdered rice grain cultivars were subjected to 72-hour germination period and the quantities of GABA, γ-oryzanol, ferulic acid, tocopherol and tocotrienol homologues were compared against their pre-germinated condition using γ- amino butyric acid (GABA) analysis and High Performance Liquid Chromatography (HPLC). Results revealed the effectiveness of germination in enhancing the bioactive components in all rice samples. GABA contents in germinated rice cultivars increased by more than 10-fold following the order: SJ >SH >NB. In addition, purple rice variety (SJ) has higher total γ-oryzanol and ferulic acid contents which increased by > 2-fold after germination followed by the red cultivar SH then the control, NB. Germinated varieties also possess higher total tocotrienol content than their pre-germinated state. As for the total tocopherol content, SJ has higher quantity, but the red-pigmented SH (0.16 mg/kg) is shown to have lower total tocopherol content than the control rice NB (0.86 mg/kg). However, all tocopherol and tocotrienol homologues were present only in small amounts ( < 3.0 mg/kg) in all pre-germinated and germinated samples. In general, all of the analyzed pigmented rice cultivars were found to possess higher bioactive compounds than the control NB rice variety. Also, regardless of their strain, germinated rice samples have higher bioactive compounds than their pre-germinated counterparts. This only shows the effectiveness of germinating rice in enhancing bioactive constituents. Overall, these results suggest the potential of the pigmented rice varieties as natural source of nutraceuticals in bio-functional food development.

Keywords: bioactive compounds, germinated rice, superhongmi, superjami

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Authors: Ivana Lončarević, Biljana Pajin, Radovan Omorjan, Aleksandra Torbica, Danica Zarić, Jovana Maksimović

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Soybean seeds are the main source of lecithin in confectionery industry in Serbia and elsewhere. The extensive production of sunflower and rapeseed oil opens the possibility of using lecithin from these sources, as an alternative. Also, the development of functional foods dictates the use of edible fats with no undesirable trans fatty acids, obtained by fractionation and transesterification instead of common hydrogenation process. Crystallization properties of nontrans vegetable fat with the addition of soybean, sunflower and rapeseed lecithin were investigated in this paper. NMR technique was used for measuring the solid fat content (SFC) of fats at different temperatures, as well as for crystallization rate under static conditions. Also, the possibility of applying Gompertz function to define kinetics of crystallization was investigated.

Keywords: non-trans fat, lecithin, fatty acids, SFC

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Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Aaron Liggett

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This research focuses on the visionary proposal made by the Olmsted Brothers Landscape Architecture firm in the 1920s for a network of interconnected parkways in Los Angeles. Their envisioned parkways aimed to address environmental and cultural strains by providing green space for recreation, wildlife habitat, and stormwater management while serving as multimodal transportation routes. Although the parkways were never constructed, through an evidence-based approach, this research presents a framework for evaluating the potential functionality and success of the parkways by modeling and visualizing their quantitative and qualitative landscape performance and benefits. Historical documents and innovative digital modeling tools produce detailed analysis, modeling, and visualization of the parkway designs. A set of 1928 construction documents are used to analyze and interpret the design intent of the parkways. Grading plans are digitized in CAD and modeled in Sketchup to produce 3D visualizations of the parkway. Drainage plans are digitized to model stormwater performance. Planting plans are analyzed to model urban forestry and biodiversity. The EPA's Storm Water Management Model (SWMM) predicts runoff quantity and quality. The USDA Forests Service tools evaluate carbon sequestration and air quality. Spatial and overlay analysis techniques are employed to assess urban connectivity and the spatial impacts of the parkway designs. The study reveals how the integration of blue infrastructure, green infrastructure, and transportation infrastructure within the parkway design creates a multifunctional landscape capable of offering alternative spatial and temporal uses. The analysis demonstrates the potential for multiple functional, ecological, aesthetic, and social benefits to be derived from the proposed parkways. The analysis of the Olmsted Brothers' proposed Los Angeles parkways, which predated contemporary ecological design and resiliency practices, demonstrates the potential for providing multiple functional, ecological, aesthetic, and social benefits within urban designs. The findings highlight the importance of integrated blue, green, and transportation infrastructure in creating a multifunctional landscape that simultaneously serves multiple purposes. The research contributes new methods for modeling and visualizing landscape performance benefits, providing insights and techniques for informing future designs and sustainable development strategies.

Keywords: landscape architecture, ecological urban design, greenway, landscape performance

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Mohammad Asadpour, Maryam Sadeghi, Mahmoud Jafari

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The transformation of carbon dioxide into fuels and commodity chemicals is considered one of the most attractive methods to meet energy demands and reduce atmospheric CO₂ levels. Cobalt complexes have previously shown high faradaic efficiency in the reduction of CO₂ to CO. In this study, a nanostructure, referred to as a porphyrin-like buckyball, is simulated and analyzed for its electrical properties. The investigation aims to understand the unique characteristics of this material and its potential applications in electronic devices. Through computational simulations and analysis, the electrocatalytic reduction of CO₂ to CO by Cobalt-porphyrin-like buckyball is explored. The findings of this study offer valuable insights into the electrocatalytic properties of this predicted structure, paving the way for further research and development in the field of nanotechnology.

Keywords: porphyrin-like buckyball, DFT, nanomaterials, CO₂ to CO

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Wali Ullah, Muhammad Nishat

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The study investigates the extent to which the so called Nelson-Siegel model (DNS) and its extended version that accounts for time varying volatility (DNS-EGARCH) can optimally fit the yield curve and predict its future path in the context of an emerging economy. For the in-sample fit, both models fit the curve remarkably well even in the emerging markets. However, the DNS-EGARCH model fits the curve slightly better than the DNS. Moreover, both specifications of yield curve that are based on the Nelson-Siegel functional form outperform the benchmark VAR forecasts at all forecast horizons. The DNS-EGARCH comes with more precise forecasts than the DNS for the 6- and 12-month ahead forecasts, while the two have almost similar performance in terms of RMSE for the very short forecast horizons.

Keywords: yield curve, forecasting, emerging markets, Kalman filter, EGARCH

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Authors: I. Cerrillo, A. Carrillo-Vico, M. A. Ortega, B. Escudero-López, N. Álvarez-Sánchez, F. Martín, M. S. Fernández-Pachón

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Melatonin is a bioactive compound involved in multiple biological activities such as glucose tolerance, circadian rhythm regulation, antioxidant defense or immune system action. In elderly subjects the intake of foods and drinks rich in melatonin is very important due to its endogenous level decreases with age. Alcoholic fermentation is a process carried out in fruits, vegetables and legumes to obtain new products with improved bioactive compounds profile in relation to original substrates. Alcoholic fermentation process carried out by Saccharomycetaceae var. Pichia kluyveri induces an important synthesis of melatonin in orange juice. A novel beverage derived of fermented orange juice could be a promising source of this bioactive compound. The aim of the present study was to determine whether the acute intake of fermented orange juice increase the levels of urinary 6-sulfatoxymelatonin in healthy humans. Nine healthy volunteers (7 women and 2 men), aged between 20 and 25 years old and BMI of 21.1  2.4 kg/m2, were recruited. On the study day, participants ingested 500 mL of fermented orange juice. The first urine collection was made before fermented orange juice consumption (basal). The rest of urine collections were made in the following time intervals after fermented orange juice consumption: 0-2, 2-5, 5-10, 10- 15 and 15-24 hours. During the experimental period only the consumption of water was allowed. At lunch time a meal was provided (60 g of white bread, two slices of ham, a slice of cheese, 125 g of sweetened natural yoghurt and water). The subjects repeated the protocol with orange juice following a 2-wk washout period between both types of beverages. The levels of 6-sulfatoxymelatonin (6-SMT) were measured in urine recollected at different time points using the Melatonin-Sulfate Urine ELISA (IBL International GMBH, Hamburg, Germany). Levels of 6-SMT were corrected to those of creatinine for each sample. A significant (p < 0.05) increase in urinary 6-SMT levels was observed between 2-5 hours after fermented orange juice ingestion with respect to basal values (increase of 67,8 %). The consumption of orange juice did not induce any significant change in urinary 6-SMT levels. In addition, urinary 6-SMT levels obtained between 2-5 hours after fermented orange juice ingestion (115,6 ng/mg) were significantly different (p < 0.05) from those of orange juice (42,4 ng/mg). The enhancement of urinary 6-SMT after the ingestion of 500 mL of fermented orange juice in healthy humans compared to orange juice could be an important advantage of this novel product as an excellent source of melatonin. Fermented orange juice could be a new functional food, and its consumption could exert a potentially positive effect on health in both the maintenance of health status and the prevention of chronic diseases.

Keywords: fermented orange juice, functional beverage, healthy human, melatonin

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Authors: Saleh Hayat

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Efficiency, productivity and sustainability are important factors for structure and the application of processes in green building. Various previous studies have addressed efficiency, productivity and sustainability separately. This research study aims to investigate the implications of these three factors taking together. Frequency analysis and the ranking techniques are carried out to explore the connection between these factors. The interconnection matrix has been developed and functional grouping is made based upon data from expert opinion and field professionals. The existence of a relationship, the type of relationship and the scaled impact have been drawn. Additionally, a system diagram has been developed to show the variable correlation. The results of expert opinion show that efficiency, productivity and sustainability have a stronger impact on green buildings.

Keywords: efficiency, green building, productivity, sustainability

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Authors: Courret Gilles, Pidoux Damien

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Considering that sunshine is the ultimate reference in lighting, we have examined the spectral correlation between a series of electric light sources and sunlight. As the latter is marked by fluctuations, we have taken two spectra of reference: on the one hand, the CIE daylight standard illuminant, and on the other hand, the global illumination by the clear sky with the sun at 30° above the horizon. We determined the coefficients of correlation between the spectra filtered by the sensitivity of the CIE standard observer for photopic vision. We also calculated the luminous efficiency of the radiation in order to compare the ideal energy performances as well as the CIE color indexes Ra, Ra14, and Rf, since the choice of a light source requires a trade-off between color rendering and luminous efficiency. The benchmarking includes the most commonly used bulbs, various white LED (Lighting Emitting Diode) of warm white or cold white types, incandescent halogen as well as two HID lamps (High-Intensity Discharge) and two plasma lamps of different types, a solar simulator and a new version of the sulfur lamp. The latter obtains the best correlation, whether in comparison with the solar spectrum or that of the standard illuminant.

Keywords: electric light sources, plasma lamp, daylighting, sunlight, spectral correlation

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Authors: Lucky Farha, Martha L. Hall

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The current adaptive clothing brands are limited in numbers and specific categories. This study explores clothing challenges for children with Down syndrome and factors that influence their perception of adaptive clothing brands. Another aim of this study was to explore brands' challenges in the adaptive business and factors that influence their perceptions towards the adaptive market. In order to determine the market barriers affecting adaptive target market needs, the researcher applied Technology Acceptance Model. After interviewing and surveying parents/caregivers having children with Down syndrome and current adaptive brands, the results found education as the significant gap in the adaptive clothing market yet to be overcome. Based on the finding, several recommendations were suggested to improve the current barriers in the adaptive clothing market.

Keywords: adaptive fashion, disability, functional clothing, clothing needs assessment, down syndrome, clothing challenge

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Authors: Jacob Lewis Watts, Adam F. A. Pellegrini

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Prairies, grasslands, and forests cover an expansive portion of the world’s surface and contribute significantly to Earth’s carbon cycle. The largest driver of carbon dynamics in some of these ecosystems is fire. As the global climate changes, most fire-dominated ecosystems will experience increased fire frequency and intensity, leading to increased carbon flux into the atmosphere and soil nutrient depletion. The plant communities associated with different fire regimes are important for reassimilation of carbon lost during fire and soil recovery. More frequent fires promote conservative plant functional traits aboveground; however, belowground fine root traits are poorly explored and arguably more important drivers of ecosystem function as the primary interface between the soil and plant. The root economic spectrum (RES) hypothesis describes single-dimensional covariation between important fine-root traits along a range of plant strategies from acquisitive to conservative – parallel to the well-established leaf economic spectrum (LES). However, because of the paucity of root trait data, the complex nature of the rhizosphere, and the phylogenetic conservatism of root traits, it is unknown whether the RES hypothesis accurately describes plant nutrient and water acquisition strategies. This project utilizesplants grown in common garden conditions in the Cambridge University Botanic Garden and a meta-analysis of long-term fire manipulation experiments to examine the belowground physiological traits of fire-adapted and non-fire-adapted herbaceous species to 1) test the RES hypothesis and 2) describe the effect of fire regimes on fine root functional traits – which in turn affect carbon and nutrient cycling. A suite of morphological, chemical, and biological root traits (e.g. root diameter, specific root length, percent N, percent mycorrhizal colonization, etc.) of 50 herbaceous species were measuredand tested for phylogenetic conservatism and RES dimensionality. Fire-adapted and non-fire-adapted plants traits were compared using phylogenetic PCA techniques. Preliminary evidence suggests that phylogenetic conservatism may weaken the single-dimensionality of the RES, suggesting that there may not be a single way that plants optimize nutrient and water acquisition and storage in the complex rhizosphere; additionally, fire-adapted species are expected to be more conservative than non-fire-adapted species, which may be indicative of slower carbon cycling with increasing fire frequency and intensity.

Keywords: climate change, fire regimes, root economic spectrum, fine roots

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Authors: Redouane Tlemsani, Abdelkader Benyettou

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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization. The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, computer vision

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Authors: Budimir S. Sudimac, Andjela N. Dubljevic

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The aim of thisresearch paper is to consider possibilities for improving the street lighting on the E75 highway, which passes through Serbia, using renewable sources of energy. In this paper, we analyzed the possibilities for installing sound barriers along the highway and integrating photovoltaic (PV) modules, which would generate electrical energy to power the lighting on the section of the highway running through Belgrade. The main aim of this paper is to analyze, show and promote innovative, hybrid, multi-functional solar technology using PV modules as an element of sound barriers in urban areas. The paper seeks to show the hybridity of using sustainable technologies in solving environmental issues. This structure solves the problem of noise in populated areas and provides the electricity from renewable source.

Keywords: noise, PV modules, solar energy, sound barriers

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Authors: Mohammadreza Biabani, Mohammad Azadfallah

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A facile and robust strategy is required to fabricate films with high special optical properties for application in the field of anti-counterfeit marking. Nanocellulose, derived from bioresources, is a renewable material with broad application prospects. In this paper, a method for grafting the eco-friendly Berberine cationic dye on cellulose nanofiber is proposed. A functional modification was carried out by in-situ polymerization along with a grafting approach with acrylic acid(AA) in order to develop cationic dyeability of the cellulose nanofiber (CNF). The Berberine grafting on nanocellulose was significantly influenced by the reaction time and temperature during the dyeing process. The dyed CNF-films exhibited appropriate characteristics like appearance, color strength, and fastness for anti-counterfeiting application.

Keywords: Cellulose nanofiber, Berberine, Grafting, anti-counterfeiting, film

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Weikang Gong, Chunhua Li

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Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

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Authors: Aydin Homay, Mario de Sousa, Martin wollschlaeger

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Axiomatic design is a system design methodology that systematically analyses the transformation of customer needs into functional requirements, design parameters, and process variables. This approach aims to create high-quality product or system designs by adhering to specific design principles or axioms, namely, the independence and information axiom. The application of axiomatic design in the design of industrial control and automation software systems could be challenging due to the high flexibility exposed by the software system and the coupling enforced by the hardware part. This paper aims to present how to use axiomatic design for designing industrial control and automation software systems and how to satisfy the independence axiom within these tightly coupled systems.

Keywords: axiomatic design, decoupling, uncoupling, automation

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Authors: Khaleel Saleh Al-Rababah

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Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: Yatin Wadhawan, Clifford Neuman, Anas Al Majali

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In this paper, we evaluate the resilience of the smart grid system in the presence of multiple cyber-physical attacks on its distinct functional components. We discuss attack-defense scenarios and their effect on smart grid resilience. Through contingency simulations in the Network and PowerWorld Simulator, we analyze multiple cyber-physical attacks that propagate from the cyber domain to power systems and discuss how such attacks destabilize the underlying power grid. The analysis of such simulations helps system administrators develop more resilient systems and improves the response of the system in the presence of cyber-physical attacks.

Keywords: smart grid, gas pipeline, cyber- physical attack, security, resilience

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Authors: Putri Alya Ramadhani

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This research analysed how women writers represent their beauty in a platform called Magdalene. With the vision “Supporting diversity, empowering minds,” Magdalene is a new media that seeks to represent women's voices rarely heard in mainstream media. This research elaborates further on how women writers, through their writing, use their body politic to subvert patriarchal values. This research used a qualitative method with an explorative design by using text analysis based on the representation theory of Stuart Hall and in-dept-interview with Women Writers in Magdalene. The result illustrated that women writers represent their beauty in Magdalene to subvert body and beauty-representation in mainstream discourse. Furthermore, the authors have identified an identity negotiation as tension from inevitable oppression and power towards and from women’s bodies. In addition, Women Writers showed the power of their bodies through the redefinition of beauty practices and self. Hence, they subvert body dichotomy to redefine body values in society. In conclusion, this study shows various representations of beauty and body that are underrepresented in the mainstream media through the innovative new medium, Magdalena.

Keywords: women writers, beauty-representation, body politic, new media, identity negotiation

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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