Search results for: Autism spectrum disorder

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 380

Authors: Sayyed Yaghoub Zolfegharifar, Khairul Anuar Kassim, Hossein Khoramrooz, Khodayar Farhadiasl, Sadegh Jahan

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Iran is one of the world's seismically active countries so that it experiences many small to medium earthquakes annually and a large earthquake every ten years. Due to seism tectonic conditions and special geographical and climatic position, Iran has the potential to create numerous severe earthquakes. Therefore, seismicity studies and seismic zonation of seismic zones of the country are necessary. In this article, the effect of local site conditions on the characteristics of seismic design in Rahmormoz will be examined. After analyzing the seismic hazard for Rahmormoz through deterministic and statistical methods and preparing the necessary geotechnical models based on available data, the ground response will be analyzed for different parts of the city based on four inputs and acceleration level estimated for bedrock through the equivalent linear method and by means of Deep Soil program. Finally, through the analysis of the obtained results, the seismic profiles of the ground surface for different parts of the city will be presented.

Keywords: seismic microzonation, ground response, resonance spectrum, period, site conditions

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Authors: L. Chetibi, D. Hamana, T. O. Busko, M. P. Kulish, S. Achour

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TiO2 nanostructures have attracted much attention due to their optical, dielectric and photocatalytic properties as well as applications including optical coating, photocatalysis and photoelectrochemical solar cells. This work aims to prepare TiO2 nanofibers (NFs) on titanium substrate (Ti) by in situ oxidation of Ti foils in a mixture solution of concentrated H2O2 and NaOH followed by proton exchange and calcinations. Scanning Electron microscopy (SEM) revealed an obvious network of TiO2 nanofibers. The photoluminescence (PL) spectra of these nanostructures revealed a broad intense band in the visible light range with a reduced near edge band emission. The PL bands in the visible region, mainly, results from surface oxygen vacancies and others defects. After irradiation with Ti+ ions (the irradiation energy was E = 140 keV with doses of 1013 ions/cm2), the intensity of the PL spectrum decreased as a consequence of the radiation treatment. The irradiation with Ti+ leads to a reduction of defects and generation of non irradiative defects near to the level of the conduction band as evidenced by the PL results. On the other hand, reducing the surface defects on TiO2 nanostructures may improve photocatalytic and optoelectronic properties of this nanostructure.

Keywords: TiO2, nanofibers, photoluminescence, irradiation

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Authors: Sang-Wook Han, Zhenlan Jin, In-Hui Hwang, Chang-In Park

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We examined structural and electrical properties of uniformly-oriented VO₂/ZnO nanostructures. VO₂ was deposited on ZnO templates by using a direct current-sputtering deposition. Scanning electron microscope and transmission electron microscope measurements indicated that b-oriented VO₂ were uniformly crystallized on ZnO templates with different lengths. VO₂/ZnO formed nanorods on ZnO nanorods with length longer than 250 nm. X-ray absorption fine structure at V K edge of VO₂/ZnO showed M1 and R phases of VO₂ at 30 and 100 ℃, respectively, suggesting structural phase transition between temperatures. Temperature-dependent resistance measurements of VO₂/ZnO nanostructures revealed metal-to-insulator transition at 65 ℃ and 55 ℃ during heating and cooling, respectively, regardless of ZnO length. The bond lengths of V-O and V-V pairs in VO₂/ZnO nanorods were somewhat distorted, and a substantial amount of structural disorder existed in the atomic pairs, compared to those of VO₂ films without ZnO. Resistance from VO₂/ZnO nanorods revealed a sharp MIT near 65 ℃ during heating and a hysteresis behavior. The resistance results suggest that microchannel for charge carriers exist nearly room temperature during cooling. VO₂/ZnO nanorods are quite stable and reproducible so that they can be widely used for practical applications to electronic devices, gas sensors, and ultra-fast switches, as examples.

Keywords: metal-to-insulator transition, VO₂, ZnO, XAFS, structural-phase transition

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Authors: Abdelmadjid Mammeri, Fatima Zohra Mahi, Luca Varani, H. Marinchoi

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We propose an analytical model for the admittance and the noise calculations of the InGaAs transistor and diode. The development of the small-signal admittance takes into account the longitudinal and transverse electric fields through a pseudo two-dimensional approximation of the Poisson equation. The frequency-dependent of the small-signal admittance response is determined by the total currents and the potentials matrix relation between the gate and the drain terminals. The noise is evaluated by using the real part of the transistor/diode admittance under a small-signal perturbation. The analytical results show that the admittance spectrum exhibits a series of resonant peaks corresponding to the excitation of plasma waves. The appearance of the resonance is discussed and analyzed as functions of the channel length and the temperature. The model can be used, on one hand; to control the appearance of the plasma resonances, and on other hand; can give significant information about the noise frequency dependence in the InGaAs transistor and diode.

Keywords: InGaAs transistors, InGaAs diode, admittance, resonant peaks, plasma waves, analytical model

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Authors: Bhavini Pandya

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This paper considers Hη: T2 → T2 the Perturbed Cerbelli-Giona map. That is a family of 2-dimensional nonlinear area-preserving transformations on the torus T2=[0,1]×[0,1]= ℝ2/ ℤ2. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments which define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated, and compared with the distribution of periodic points of the system.

Keywords: feed forward, gradient descent, neural network, integral equation

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Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Zerrin Erginkaya, Gözde Konuray

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Microbial degradation of foods is defined as a decrease of food safety due to microorganism activity. Organic acids, sulfur dioxide, sulfide, nitrate, nitrite, dimethyl dicarbonate and several preservative gases have been used as chemical preservatives in foods as well as natural preservatives which are indigenous in foods. It is determined that usage of herbal preservatives such as blueberry, dried grape, prune, garlic, mustard, spices inhibited several microorganisms. Moreover, it is determined that animal origin preservatives such as whey, honey, lysosomes of duck egg and chicken egg, chitosan have antimicrobial effect. Other than indigenous antimicrobials in foods, antimicrobial agents produced by microorganisms could be used as natural preservatives. The antimicrobial feature of preservatives depends on the antimicrobial spectrum, chemical and physical features of material, concentration, mode of action, components of food, process conditions, and pH and storage temperature. In this review, studies about antimicrobial components which are indigenous in food (such as herbal and animal origin antimicrobial agents), antimicrobial materials synthesized by microorganisms, and their usage as an antimicrobial agent to preserve foods are discussed.

Keywords: animal origin preservatives, antimicrobial, chemical preservatives, herbal preservatives

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Authors: Sergio A. Bernal-Chavez, Sergio Alcalá-Alcalá, Doris A. Cerecedo-Mercado, Adriana Ganem-Rondero

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The prevalence of people with chronic wounds has increased dramatically by many factors including smoking, obesity and chronic diseases, such as diabetes, that can slow the healing process and increase the risk of becoming chronic. Because of this situation, the improvement of chronic wound treatments is a necessity, which has led to the scientific community to focus on improving the effectiveness of current therapies and the development of new treatments. The wound formation is a physiological complex process, which is characterized by an inflammatory stage with the presence of proinflammatory cells that create a proteolytic microenvironment during the healing process, which includes the degradation of important growth factors and cytokines. This decrease of growth factors and cytokines provides an interesting strategy for wound healing if they are administered externally. The use of nanometric drug delivery systems, such as polymer nanoparticles (NP), also offers an interesting alternative around dermal systems. An interesting strategy would be to propose a formulation based on a thermosensitive hydrogel loaded with polymeric nanoparticles that allows the inclusion and application of a platelet lysate (PL) on damaged skin, with the aim of promoting wound healing. In this work, NP were prepared by a double emulsion-solvent evaporation technique, using polylactic-co-glycolic acid (PLGA) as biodegradable polymer. Firstly, an aqueous solution of PL was emulsified into a PLGA organic solution, previously prepared in dichloromethane (DCM). Then, this disperse system (W/O) was poured into a polyvinyl alcohol (PVA) solution to get the double emulsion (W/O/W), finally the DCM was evaporated by magnetic stirring resulting in the NP formation containing PL. Once the NP were obtained, these systems were characterized by morphology, particle size, Z-potential, encapsulation efficiency (%EE), physical stability, infrared spectrum, calorimetric studies (DSC) and in vitro release profile. The optimized nanoparticles were included in a thermosensitive gel formulation of Pluronic® F-127. The gel was prepared by the cold method at 4 °C and 20% of polymer concentration. Viscosity, sol-gel phase transition, time of no flow solid-gel at wound temperature, changes in particle size by temperature-effect using dynamic light scattering (DLS), occlusive effect, gel degradation, infrared spectrum and micellar point by DSC were evaluated in all gel formulations. PLGA NP of 267 ± 10.5 nm and Z-potential of -29.1 ± 1 mV were obtained. TEM micrographs verified the size of NP and evidenced their spherical shape. The %EE for the system was around 99%. Thermograms and in infrared spectra mark the presence of PL in NP. The systems did not show significant changes in the parameters mentioned above, during the stability studies. Regarding the gel formulation, the transition sol-gel occurred at 28 °C with a time of no flow solid-gel of 7 min at 33°C (common wound temperature). Calorimetric, DLS and infrared studies corroborated the physical properties of a thermosensitive gel, such as the micellar point. In conclusion, the thermosensitive gel described in this work, contains therapeutic amounts of PL and fulfills the technological properties to be used in damaged skin, with potential application in wound healing and tissue regeneration.

Keywords: growth factors, polymeric nanoparticles, thermosensitive hydrogels, tissue regeneration

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Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

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Authors: Mosaab A. Omar, Mohammad Saleh Al-Aboody, Mohmed A. Rizk, Shimaa M. Elsayed, Ahmed ElSify, Naoaki Yokoyama, Ikuo Igarashi

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Enoxacin is a broad-spectrum 6-fluoronaphthyridinone antibacterial agent (fluoroquinolones) structurally related to nalidixic acid used mainly in the treatment of urinary tract infections and gonorrhea. Also, it has been shown recently that it may have cancer inhibiting effect. The primary antibabesial effect of Enoxacin is due to inhibition of DNA gyrase subunit A, and DNA topoisomerase. In the present study, enoxacin was tested as a potent inhibitor against the in vitro growth of bovine and equine Piroplasms. The in vitro growth of five Babesia species that were tested was significantly inhibited (P<0.05) by micromolar concentrations of enoxacin (IC50 values= 13.5, 7.2, 7.5, and 24.2 µM for Babesia bovis, Babesia bigemina, Babesia caballi, and Theileria equi, respectively). Enoxacin IC50 values for Babesia and Theileria parasites were satisfactory as the drug is a potent antibacterial drug with minimum side effects. Therefore, enoxacin might be used for the treatment of Babesiosis and Theileriosis especially in case of mixed infections with bacterial diseases or in the case of animal sensitivity against diminazin toxicity.

Keywords: enoxacin, Babesia, Theileria, IC50 and dimenazin

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Authors: Shao-Hsuan Chien, Ju-Hui Fu

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Parkinson’s disease (PD) is a degenerative disorder of the central nervous system that is characterized by progressive loss of dopaminergic neurons in the substantia nigra pars compacta and motor impairment. Aggregation of α-synuclein in neuronal cells plays a key role in this disease. At present, therapeutics for PD provides moderate symptomatic benefit but is not able to delay the development of this disease. Current efforts for the treatment of PD are to identify new drugs that show slow or arrest progressive course of PD by interfering with a disease-specific pathogenetic process in PD patients. Maackiain is a bioactive compound isolated from the roots of the Chinese herb Sophora flavescens. The purpose of the present study was to assess the potential for maackiain to ameliorate PD in Caenorhabditis elegans models. Our data reveal that maackiain prevents α-synuclein accumulation in the transgenic Caenorhabditis elegans model and also improves dopaminergic neuron degeneration, food-sensing behavior, and life-span in 6-hydroxydopamine-induced Caenorhabditis elegans model, thus indicating its potential as a candidate antiparkinsonian drug.

Keywords: maackiain, Parkinson’s disease, dopaminergic neurons, α-Synuclein

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Authors: Dahi Ghareab Abdelsalam Ibrahim

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Calibration of step heights with high accuracy is needed for many applications in the industry. In general, step height consists of three bands: pass band, transition band (roll-off), and stop band. Abdelsalam used a convolution of the transfer functions of both Chebyshev type 2 and elliptic filters with WFF of the Fresnel transform in the frequency domain for producing a steeper roll-off with the removal of ripples in the pass band- and stop-bands. In this paper, we used a new method based on the Hamming window: band-pass filter for calibration of step heights in terms of perfect adjustment of pass-band, roll-off, and stop-band. The method is applied to calibrate a nominal step height of 40 cm. The step height is measured first by asynchronous dual-wavelength phase-shift interferometry. The measured step height is then calibrated by the simulation of the Hamming window: band-pass filter. The spectrum of the simulated band-pass filter is simulated at N = 881 and f0 = 0.24. We can conclude that the proposed method can calibrate any step height by adjusting only two factors which are N and f0.

Keywords: optical metrology, step heights, hamming window, band-pass filter

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Authors: Mohamed Noureldin, Jinkoo Kim

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In this study, a genetic algorithm was used to find out the optimum locations of the slit dampers satisfying a target displacement. A seismic retrofit scheme for a building structure was presented using steel plate slit dampers. A cyclic loading test was used to verify the energy dissipation capacity of the slit damper. The seismic retrofit of the model structure using the slit dampers was compared with the retrofit with enlarging shear walls. The capacity spectrum method was used to propose a simple damper distribution scheme proportional to the inter-story drifts. The validity of the simple story-wise damper distribution procedure was verified by comparing the results of the genetic algorithm. It was observed that the proposed simple damper distribution pattern was in a good agreement with the optimum distribution obtained from the genetic algorithm. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03032809).

Keywords: slit dampers, seismic retrofit, genetic algorithm, optimum design

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Authors: Simran Sharda

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There is increasing evidence that leads psychologists today to believe that the attachment formed between a mother and child plays a much more profound role in later-life outcomes than previously expected. Particularly, the fact that a link may exist between maternal attachment and the development in addition to the severity of social anxiety in middle childhood seems to be gaining ground. This research will examine and address a myriad of major issues related to the impact of mother-child attachment: behaviors of children with different levels of secure attachment, various aspects of anxiety in relation to attachment security as well as other styles of mother-child attachments, especially avoidant attachment and over-attachment. This analysis serves to compile previous literature on the subject and touch light upon a logical extension of the research. Moreover, researchers have identified links between attachment and the externalization of problem behaviors: these behaviors may later manifest as social anxiety as well as increased severity and likelihood of PTSD diagnosis (an anxiety disorder). Furthermore, secure attachment has been linked to increased health benefits, cognitive skills, emotive socialization, and developmental psychopathology.

Keywords: child development, anxiety, cognition, developmental psychopathology, mother-child relationships, maternal, cognitive development

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Authors: Sukrit Ghorai

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Proof of controlling crack width is a basic condition for securing suitable performance in serviceability limit state. The cracking in concrete can occur at any time from the casting of time to the years after the concrete has been set in place. Most codes struggle with offering procedure for crack width calculation. There is lack in availability of design charts for designers to compute crack width with ease. The focus of the study is to utilize design charts and parametric equations in calculating crack width with minimum error. The paper contains a simplified procedure to calculate crack width for reinforced concrete (RC) sections subjected to bending with axial tensile force following the guidelines of Euro code [DS EN-1992-1-1 & DS EN-1992-1-2]. Numerical examples demonstrate the application of the suggested procedure. Comparison with parallel analytical tools support the validity of result and show the percentage deviation of crack width in both the procedures. The technique is simple, user-friendly and ready to evolve for a greater spectrum of section sizes and materials.

Keywords: concrete structures, crack width calculation, serviceability limit state, structural design, bridge engineering

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Authors: Tony K. Joseph, Balasubramanian Vathilingam, Stephane Morin

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Currently, the refiners around the world are more focused on improving the yield of light olefins (propylene and ethylene) as both of them are very prominent raw materials to produce wide spectrum of polymeric materials such as polyethylene and polypropylene. Henceforth, it is desirable to increase the yield of light olefins via selective cracking of heavy oil fractions. In this study, zeolite grown on SiC was used as the catalyst to do model cracking reaction of n-heptane. The catalytic cracking of n-heptane was performed in a fixed bed reactor (12 mm i.d.) at three different temperatures (425, 450 and 475 °C) and at atmospheric pressure. A carrier gas (N₂) was mixed with n-heptane with ratio of 90:10 (N₂:n-heptane), and the gaseous mixture was introduced into the fixed bed reactor. Various flow rate of reactants was tested to increase the yield of ethylene and propylene. For the comparison purpose, commercial zeolite was also tested in addition to Zeolite on SiC. The products were analyzed using an Agilent gas chromatograph (GC-9860) equipped with flame ionization detector (FID). The GC is connected online with the reactor and all the cracking tests were successfully reproduced. The entire catalytic evaluation results will be presented during the conference.

Keywords: cracking, catalyst, evaluation, ethylene, heptane, propylene

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Authors: Lyudmila V. Ignatova, Yelena V. Brazhnikova, Togzhan D. Mukasheva, Ramza Zh. Berzhanova, Anel A. Omirbekova

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Endophytic microorganisms are presented in plants of different families growing in the foothills and piedmont plains of Trans-Ili Alatau. It was found that the maximum number of endophytic micromycetes is typical to the Fabaceae family. The number of microscopic fungi in the roots reached (145.9±5.9)×103 CFU/g of plant tissue; yeasts - (79.8±3.5)×102 CFU/g of plant tissue. Basically, endophytic microscopic fungi are typical for underground parts of plants. In contrast, yeasts more infected aboveground parts of plants. Small amount of micromycetes is typical to inflorescence and fruits. Antagonistic activity of selected micromycetes against Fusarium graminearum, Cladosporium sp., Phytophtora infestans and Botrytis cinerea phytopathogens was detected. Strains with a broad, narrow and limited range of action were identified. For further investigations Rh2 and T7 strains were selected, they are characterized by a broad spectrum of fungicidal activity and they formed the large inhibition zones against phytopathogens. Active antagonists are attributed to the Rhodotorula mucilaginosa and Beauveria bassiana species.

Keywords: endophytic micromycetes, fungicidal activity, prevalence, plants

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Authors: Avantika Vats, Kushal Thakur

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This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: Shelly Sharma, Pooja Chadha

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Humans are exposed to pesticides and insecticides either directly or indirectly. Exposure to these pesticides may lead to acute toxicity to mammals and non-target organisms. Chlorpyrifos (CPF) is a broad spectrum organophosphate pesticide widely used in various countries of the world. The aim of the present study was to assess the toxicity associated with chlorpyrifos exposure and possible mitigating effect of cow urine against genotoxic and toxic effects in rat brain induced by chlorpyrifos. For this purpose LD50 was determined and rats were orally administered with 1/8th of LD50 (19mg/kg b.wt). Brain samples were taken after 24hrs, 48hrs and 72hrs of treatment. A significant increase in the % tail DNA was observed along with the increase in MDA levels of brain tissues in chlorpyrifos treated groups as compared to control. Cow urine treated groups show decrease in DNA damage and MDA levels as compared to CPF treated group. The study indicates that cow urine has ameliorative potential against neurotoxicity and genotoxicity induced by CPF. Cow urine is considered rich in vitamin A, E and volatile fatty acids which provide antioxidant potential to it. Thus, it can be used as a genoprotective agent.

Keywords: comet assay, brain, cow urine, genotoxicity, toxicity

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Authors: Zian Cheak Tiu, Harith Ahmad, Sulaiman Wadi Harun

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A simple multi-wavelength passively Q-switched Erbium-doped fiber laser (EDFL) is demonstrated using low cost multi-walled carbon nanotubes (MWCNTs) based saturable absorber (SA), which is prepared using polyvinyl alcohol (PVA) as a host polymer. The multi-wavelength operation is achieved based on nonlinear polarization rotation (NPR) effect by incorporating 50 m long photonic crystal fiber (PCF) in the ring cavity. The EDFL produces a stable multi-wavelength comb spectrum for more than 14 lines with a fixed spacing of 0.48 nm. The laser also demonstrates a stable pulse train with the repetition rate increases from 14.9 kHz to 25.4 kHz as the pump power increases from the threshold power of 69.0 mW to the maximum pump power of 133.8 mW. The minimum pulse width of 4.4 µs was obtained at the maximum pump power of 133.8 mW while the highest energy of 0.74 nJ was obtained at pump power of 69.0 mW.

Keywords: multi-wavelength Q-switched, multi-walled carbon nanotube, photonic crystal fiber

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Derick Shi-Chen Ou, Liang-Yu Chen

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Background: Acupuncture, a potential alternative, and complementary therapy revealed insufficient evidence in depression treatment. The efficacy of acupuncture treatment was still uncertainty. To evaluate the effect of acupuncture in treating depression, the randomized controlled trials (RCTs) were examined. Methods: RCTs of the acupuncture therapy in treating major depression were searched from MEDLINE from 2007 to 2017. Keywords used for searching strategy included acupuncture, acupoint, and major depressive disorder. Results: Among the nine RCTs, four studies demonstrated great improvement in acupuncture treatment and five studies revealed the effectiveness of acupuncture intervention in medication. General trends suggest that acupuncture treatment is as effective as antidepressants with minimal side effects. Conclusion: Despite the promising results from the RCTs, there are still a variety of limitations, including small sample size, imprecise enrollment criteria, difficulties with blinding, randomization, short duration of study and lack of longitudinal follow-up. Therefore, the evidence that acupuncture as an alternative therapy for depression is inconclusive. More rigorously designed RCTs should be conducted in the future.

Keywords: acupuncture, major depressive disorders, randomized clinical trials, antidepressants

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Authors: Varsha Rainson

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Artificial intelligence (AI) has great potential and can be used as a powerful tool of application in various domains and sectors. But with the application of AI, there comes a wide spectrum of concerns around bias, accountability, transparency, and privacy. Hence, there is a need for responsible AI, which can uphold ethical and accountable practices to ensure that things are transparent and fair. The paper is a combination of AI and cultural heritage preservation, with a greater focus on India because of the rich cultural legacy that it holds. India’s cultural heritage in itself contributes to its identity and the economy. In this paper, along with discussing the impact culture holds on the Indian economy, we will discuss the threats that the cultural heritage is exposed to due to pollution, climate change and urbanization. Furthermore, the paper reviews some of the exciting applications of AI in cultural heritage preservation, such as 3-D scanning, photogrammetry, and other techniques which have led to the reconstruction of cultural artifacts and sites. The paper eventually moves into the potential risks and challenges that AI poses in cultural heritage preservation. These include ethical, legal, and social issues which are to be addressed by organizations and government authorities. Overall, the paper strongly argues the need for responsible AI and the important role it can play in preserving India’s cultural heritage while holding importance to value and diversity.

Keywords: responsible AI, cultural heritage, artificial intelligence, biases, transparency

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Authors: Azeez O. Ganiyu

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Climate change is expected to lead to substantial changes in rainfall patterns in southwest Nigeria, and this may have substantial consequence for forest management and for conservation outcomes throughout the region. We examine three different forest types across an environmental spectrum from semi-arid to humid subtropical and consider their response to water shortages and other environmental stresses; we also explore the potential consequence for conservation and timber production by considering impacts on forest structure and limiting stand density. Analysis of a series of scenarios provides the basis for a critique of existing management practices and suggests practical alternatives to develop resilient forests with minimal diminution of production and environmental services. We specifically discuss practical silviculture interventions that are feasible at the landscape-scale, that are economically viable, and that have the potential to enhance resilience of forest stands. We also discuss incentives to encourage adoption of these approaches by private forest owners. We draw on these case studies in southwestern Nigeria to offer generic principle to assist forest researchers and managers faced with similar challenges elsewhere.

Keywords: climate change, forest, future, silviculture, Nigeria

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Authors: Victoria Yu. Garnova, Vladimir G. Merzlikin, Sergey V. Khudyakov, Valeriy A. Tovstonog, Svyatoslav V. Cheranev

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Long-term scientific forecasts confirm that diesel engines still will be the basis of the transport and stationary power in the near future. This is explained by their high efficiency and profitability compared to other types of heat engines. In the automotive industry carried basic researches are aimed at creating a new generation of diesel engines with reduced exhaust emissions (with stable performance) determining the minimum impact on the environment. The application of thermal barrier coatings (TBCs) and especially their modifications based on semitransparent ceramic materials allows solving this problem. For such researches, the preliminary stage of testing of physical characteristics materials and coatings especially with semitransparent properties the authors proposed experimental operating innovative radiative-and-convective cycling simulator. This setup contains original radiation sources (imitator) with tunable spectrum for modeling integral flux up to several MW/m2.

Keywords: environment saving, radiative and convective cycling simulator, semitransparent ceramic coatings, imitator radiant energy

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Authors: Henrik L. Funke, Lars Ulke-Winter, Sandra Gelbrich, Lothar Kroll

Abstract:

This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Keywords: concrete design, fibre reinforced concrete, genetic algorithms, GEP-FC

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Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Courret Gilles, Pidoux Damien

Abstract:

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: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

Abstract:

Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 336