Search results for: computational experiment

Authors: W. Hamaidia, T. Zebbiche

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This paper presents the design of axisymmetric supersonic nozzles, in order to accelerate a supersonic flow to the desired Mach number and that having a small weight, in the same time gives a high thrust. The concerned nozzle gives a parallel and uniform flow at the exit section. The nozzle is divided into subsonic and supersonic regions. The supersonic portion is independent to the upstream conditions of the sonic line. The subsonic portion is used to give a sonic flow at the throat. In this case, nozzle gives a uniform and parallel flow at the exit section. It’s named by minimum length Nozzle. The study is done at high temperature, lower than the dissociation threshold of the molecules, in order to improve the aerodynamic performances. Our aim consists of improving the performances both by the increase of exit Mach number and the thrust coefficient and by reduction of the nozzle's mass. The variation of the specific heats with the temperature is considered. The design is made by the Method of Characteristics. The finite differences method with predictor-corrector algorithm is used to make the numerical resolution of the obtained nonlinear algebraic equations. The application is for air. All the obtained results depend on three parameters which are exit Mach number, the stagnation temperature, the chosen mesh in characteristics. A numerical simulation of nozzle through Computational Fluid Dynamics-FASTRAN was done to determine and to confirm the necessary design parameters.

Keywords: flux supersonic flow, axisymmetric minimum length nozzle, high temperature, method of characteristics, calorically imperfect gas, finite difference method, trust coefficient, mass of the nozzle, specific heat at constant pressure, air, error

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Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

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Authors: Driss Cherqaoui, Nouhaila Ait Lahcen, Ismail Hdoufane, Mehdi Oubahmane, Wissal Liman, Christelle Delaite, Mohammed M. Alanazi

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The Ebola virus is a highly contagious and deadly pathogen that causes Ebola virus disease. The Ebola virus glycoprotein (EBOV-GP) is a key factor in viral entry into host cells, making it a critical target for therapeutic intervention. Using a combination of computational approaches, this study focuses on the identification of natural compounds that could serve as potent inhibitors of EBOV-GP. The 3D structure of EBOV-GP was selected, with missing residues modeled, and this structure was minimized and equilibrated. Two large natural compound databases, COCONUT and NPASS, were chosen and filtered based on toxicity risks and Lipinski’s Rule of Five to ensure drug-likeness. Following this, a pharmacophore model, built from 22 reported active inhibitors, was employed to refine the selection of compounds with a focus on structural relevance to known Ebola inhibitors. The filtered compounds were subjected to virtual screening via molecular docking, which identified ten promising candidates (five from each database) with strong binding affinities to EBOV-GP. These compounds were then validated through molecular dynamics simulations to evaluate their binding stability and interactions with the target. The top three compounds from each database were further analyzed using ADMET profiling, confirming their favorable pharmacokinetic properties, stability, and safety. These results suggest that the selected compounds have the potential to inhibit EBOV-GP, offering new avenues for antiviral drug development against the Ebola virus.

Keywords: EBOV-GP, Ebola virus glycoprotein, high-throughput drug screening, molecular docking, molecular dynamics, natural compounds, pharmacophore modeling, virtual screening

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: T. Ewetumo, K. D. Adedayo, Festus Ben

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Knowledge of the thermal properties of foods is of fundamental importance in the food industry to establish the design of processing equipment. However, for tropical fruit juice, there is very little information in literature, seriously hampering processing procedures. This research work describes the development of an instrument for automated thermal conductivity and thermal diffusivity measurement of tropical fruit juice using a transient thermal probe technique based on line heat principle. The system consists of two thermocouple sensors, constant current source, heater, thermocouple amplifier, microcontroller, microSD card shield and intelligent liquid crystal. A fixed distance of 6.50mm was maintained between the two probes. When heat is applied, the temperature rise at the heater probe measured with time at time interval of 4s for 240s. The measuring element conforms as closely as possible to an infinite line source of heat in an infinite fluid. Under these conditions, thermal conductivity and thermal diffusivity are simultaneously measured, with thermal conductivity determined from the slope of a plot of the temperature rise of the heating element against the logarithm of time while thermal diffusivity was determined from the time it took the sample to attain a peak temperature and the time duration over a fixed diffusivity distance. A constant current source was designed to apply a power input of 16.33W/m to the probe throughout the experiment. The thermal probe was interfaced with a digital display and data logger by using an application program written in C++. Calibration of the instrument was done by determining the thermal properties of distilled water. Error due to convection was avoided by adding 1.5% agar to the water. The instrument has been used for measurement of thermal properties of banana, orange and watermelon. Thermal conductivity values of 0.593, 0.598, 0.586 W/m^o C and thermal diffusivity values of 1.053 ×〖10〗^(-7), 1.086 ×〖10〗^(-7), and 0.959 ×〖10〗^(-7) 〖m/s〗^2 were obtained for banana, orange and water melon respectively. Measured values were stored in a microSD card. The instrument performed very well as it measured the thermal conductivity and thermal diffusivity of the tropical fruit juice samples with statistical analysis (ANOVA) showing no significant difference (p>0.05) between the literature standards and estimated averages of each sample investigated with the developed instrument.

Keywords: thermal conductivity, thermal diffusivity, tropical fruit juice, diffusion equation

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Authors: Xiaobo Wang, Zhen-Yu Chen

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Higher plasma total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) are independent risk factors of cardiovascular disease while high-density lipoprotein cholesterol (HDL-C) is protective. Vitamin D is well-known for its regulatory role in calcium homeostasis. Its potential important role in cardiovascular disease has recently attracted much attention. This study was conducted to investigate effects of different dosage of calcitriol on plasma lipoprotein profile and the underlying mechanism. Sixty male Syrian Golden hamsters were randomly divided into 6 groups: no-cholesterol control (NCD), high-cholesterol control (HCD), groups with calcitriol supplementation at 10/20/40/80ng/kg body weight (CA, CB, CC, CD), respectively. Calcitriol in medium-chain triacylglycerol (MCT) oil was delivered to four experimental groups via oral gavage every other day, while NCD and HCD received MCT oil in the equivalent amount. NCD hamsters were fed with non-cholesterol diet while other five groups were maintained on diet containing 0.2% cholesterol to induce a hypercholesterolemic condition. The treatment lasts for 6 weeks followed by sample collection after hamsters sacrificed. Four experimental groups experienced a reduction in average food intake around 11% compared to HCD with slight decrease in body weight (not exceeding 10%). This reduction reflects on the deceased relative weights of testis, epididymal and perirenal adipose tissue in a dose-dependent manner. Plasma calcitriol levels were measured and was corresponding to oral gavage. At the end of week 6, lipoprotein profiles were improved with calcitriol supplementation with TC, non-HDL-C and plasma triglyceride (TG) decreased in a dose-dependent manner (TC: r=0.373, p=0.009, non-HDL-C: r=0.479, p=0.001, TG: r=0.405, p=0.004). Since HDL-C of four experiment groups showed no significant difference compared to HCD, the ratio of nHDL-C to HDL-C and HDL-C to TC had been restored in a dose-dependent manner. For hamsters receiving the highest level of calcitriol (80ng/kg) showed a reduction of TC by 11.5%, nHDL-C by 24.1% and TG by 31.25%. Little difference was found among six groups on the acetylcholine-induced endothelium-dependent relaxation or contraction of thoracic aorta. To summarize, calcitriol supplementation in hamster at maximum 80ng/kg body weight for 6 weeks lead to an overall improvement in plasma lipoprotein profile with decreased TC and TG level. The molecular mechanism of its effects is under investigation.

Keywords: cholesterol, vitamin D, calcitriol, hamster

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Authors: Ali Kadivar, Kaveh Niayesh

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This work simulates the voltage drop and resistance of the explosion of copper wires of diameters 25, 40, and 100 µm surrounded by 1 bar nitrogen exposed to a 150 A current and before plasma formation. The absorption of electrical energy in an exploding wire is greatly diminished when the plasma is formed. This study shows the importance of considering radiation and heat conductivity in the accuracy of the circuit simulations. The radiation of the dense plasma formed on the wire surface is modeled with the Net Emission Coefficient (NEC) and is mixed with heat conductivity through PLASIMO® software. A time-transient code for analyzing wire explosions driven by a slow current rise rate is developed. It solves a circuit equation coupled with one-dimensional (1D) equations for the copper electrical conductivity as a function of its physical state and Net Emission Coefficient (NEC) radiation. At first, an initial voltage drop over the copper wire, current, and temperature distribution at the time of expansion is derived. The experiments have demonstrated that wires remain rather uniform lengthwise during the explosion and can be simulated utilizing 1D simulations. Data from the first stage are then used as the initial conditions of the second stage, in which a simplified 1D model for high-Mach-number flows is adopted to describe the expansion of the core. The current was carried by the vaporized wire material before it was dispersed in nitrogen by the shock wave. In the third stage, using a three-dimensional model of the test bench, the streamer threshold is estimated. Electrical breakdown voltage is calculated without solving a full-blown plasma model by integrating Townsend growth coefficients (TdGC) along electric field lines. BOLSIG⁺ and LAPLACE databases are used to calculate the TdGC at different mixture ratios of nitrogen/copper vapor. The simulations show both radiation and heat conductivity should be considered for an adequate description of wire resistance, and gaseous discharges start at lower voltages than expected due to ultraviolet radiation and the exploding shocks, which may have ionized the nitrogen.

Keywords: exploding wire, Townsend breakdown mechanism, streamer, metal vapor, shock waves

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Authors: Ahmed M. Eed, Adam H. Burgoyne

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Jojoba (Simmondsia chinensis (Link) Schneider), is a desert shrub which tolerates saline, alkyle soils and drought. The seeds contain a characteristic liquid wax of economic importance in industry as a machine lubricant and cosmetics. A major problem in seed propagation is that jojoba is a dioecious plant whose sex is not easily determined prior to flowering (3-4 years from germination). To overcome this phenomenon, asexual propagation using vegetative methods such as cutting can be used. This research was conducted to find out the effect of different Plant Growth Regulators (PGRs) and rooting media on Jojoba rhizogenesis. An experiment was carried out in a Factorial Completely Randomized Design (FCRD) with three replications, each with sixty cuttings per replication in fiberglass house of Natural Jojoba Corporation at Yemen. The different rooting media used were peat moss + perlite + vermiculite (1:1:1), peat moss + perlite (1:1) and peat moss + sand (1:1). Plant materials used were semi-hard wood cuttings of jojoba plants with length of 15 cm. The cuttings were collected in the month of June during 2012 and 2013 from the sub-terminal growth of the mother plants of Amman farm and introduced to Yemen. They were wounded, treated with Indole butyric acid (IBA), α-naphthalene acetic acid (NAA) or Indole-3-acetic acid (IAA) all @ 4000 ppm (part per million) and cultured on different rooting media under intermittent mist propagation conditions. IBA gave significantly higher percentage of rooting (66.23%) compared to NAA and IAA in all media used. However, the lowest percentage of rooting (5.33%) was recorded with IAA in the medium consisting of peat moss and sand (1:1). No significant difference was observed at all types of PGRs used with rooting media in respect of root length. Maximum number of roots was noticed in medium consisting of peat moss, perlite and vermiculite (1:1:1); peat moss and perlite (1:1) and peat moss and sand (1:1) using IBA, NAA and IBA, respectively. The interaction among rooting media was statistically significant with respect to rooting percentage character. Similarly, the interactions among PGRs were significant in terms of rooting percentage and also root length characters. The results demonstrated suitability of propagation of jojoba plants by semi-hard wood cuttings.

Keywords: cutting, IBA, Jojoba, propagation, rhizogenesis

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Authors: Sofia Sehli, Zainab El Ouafi, Casey Eddington, Soumaya Jbara, Kasambula Arthur Shem, Islam El Jaddaoui, Ayorinde Afolayan, Olaitan I. Awe, Allissa Dillman, Hassan Ghazal

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The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually.

Keywords: metagenomics, shotgun metagenomic sequence analysis, COVID-19, pipeline, bioinformatics

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Authors: Jae-Hyun Choi, Sung-Soo Bae, Sangyoung Yoon, Hong-Ku Yun, Jiyoung Kwahk

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This study was conducted to investigate the effect of ocular dominance on recognition performance using a single-lens smart display designed for cycling. A total of 36 bicycle riders who have been cycling consistently were recruited and participated in the experiment. The participants were asked to perform tasks riding a bicycle on a stationary stand for safety reasons. Independent variables of interest include ocular dominance, bike usage, age group, and information layout. Recognition time (i.e., the time required to identify specific information measured with an eye-tracker), error rate (i.e. false answer or failure to identify the information in 5 seconds), and user preference scores were measured and statistical tests were conducted to identify significant results. Recognition time and error ratio showed significant difference by ocular dominance factor, while the preference score did not. Recognition time was faster when the single-lens see-through display on the dominant eye (average 1.12sec) than on the non-dominant eye (average 1.38sec). Error ratio of the information recognition task was significantly lower when the see-through display was worn on the dominant eye (average 4.86%) than on the non-dominant eye (average 14.04%). The interaction effect of ocular dominance and age group was significant with respect to recognition time and error ratio. The recognition time of the users in their 40s was significantly longer than the other age groups when the display was placed on the non-dominant eye, while no difference was observed on the dominant eye. Error ratio also showed the same pattern. Although no difference was observed for the main effect of ocular dominance and bike usage, the interaction effect between the two variables was significant with respect to preference score. Preference score of daily bike users was higher when the display was placed on the dominant eye, whereas participants who use bikes for leisure purposes showed the opposite preference patterns. It was found more effective and efficient to wear a see-through display on the dominant eye than on the non-dominant eye, although user preference was not affected by ocular dominance. It is recommended to wear a see-through display on the dominant eye since it is safer by helping the user recognize the presented information faster and more accurately, even if the user may not notice the difference.

Keywords: eye tracking, information recognition, ocular dominance, smart headware, wearable device

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Authors: Edgar Willy Rimarachin Valderrama, Eduardo Rojas Parra

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Thermal energy from solar radiation is widely present in power plants, food drying, chemical reactors, heating and cooling systems, water treatment processes, hydrogen production, and others. In the case of power plants, one of the technologies available to transform solar energy into thermal energy is by solar rotary kilns where a bed of granular matter is heated through concentrated radiation obtained from an arrangement of heliostats. Numerical modeling is a useful approach to study the behavior of granular beds in solar rotary kilns. This technique, once validated with small-scale experiments, can be used to simulate large-scale processes for industrial applications. This study gives a comprehensive classification of numerical models used to simulate the movement and heat transfer for beds of granular media within solar rotary furnaces. In general, there exist three categories of models: 1) continuum, 2) discrete, and 3) multiphysics modeling. The continuum modeling considers zero-dimensional, one-dimensional and fluid-like models. On the other hand, the discrete element models compute the movement of each particle of the bed individually. In this kind of modeling, the heat transfer acts during contacts, which can occur by solid-solid and solid-gas-solid conduction. Finally, the multiphysics approach considers discrete elements to simulate grains and a continuous modeling to simulate the fluid around particles. This classification allows to compare the advantages and disadvantages for each kind of model in terms of accuracy, computational cost and implementation.

Keywords: granular beds, numerical models, rotary kilns, solar thermal applications

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Authors: Reham Hajomer, Ikram Elsiddig, Amna Hamad

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Lepidium sativum (Garden Cress) belonging to Brassicaceae family is an annual herb locally known as El-rshad. In Ayurveda it is an important medicinal plant, traditionally used for the treatment of jaundice, liver problems, spleen diseases, gastrointestinal disorders, menstrual problems, fracture, arthritis, inflammatory conditions and for treatment of hypothyroidism. Hypothyroidism is a condition in which the thyroid gland does not produce enough thyroid hormones (Triiodithyronine T3 and Thyroxine T4) which are commonly caused by iodine deficiency. It’s divided into primary and secondary hypothyroidism, the primary caused by failure of thyroid function and secondary due to the failure of adequate thyroid-stimulating hormone (TSH) secretion from the pituitary gland or thyroid -releasing hormone (TRH) from the hypothalamus. The disease is most common in women over age 60. The objective regarding this study is to know whether Lepidium sativum would affect the level of thyroid hormones. The extract was prepared with 96% ethanol using Soxhlet apparatus. The anti-hypothyroidism activity was tested by using thirty male Wistar rats weighing (100-140 g) were used in the experiment. They were grouping into five groups, Group 1: Normal group= Administered only distilled water. Then 10 mg/kg Propylthiouracil was added to the drinking water of all other groups to induce hypothyroidism. Group 2: Negative control without any treatment; Group 3: Test group= treated with oral administration of 500mg/kg extract; Group 4: treated with oral administration of 250mg/kg of the extract; Group 5: Standard group (positive control) = treated with intraperitoneal Levothyroxine. All rats were incubated for 20 days at animal house with room temperature of proper ventilation provided with standard diet. The result show that the Lepidium sativum extract was found to increases the T3 and T4 in the propylthiouracil induced rats with values (0.29 ng/dl T3 and 0.57 U T4) for the 500mg/kg and (0.27 ng/dl T3 and 0.517 U T4) for the 250mg/kg in comparison with standard with values (0.241 ng/dl T3 and 0.516 U T4) so that Lepidium sativum can be stimulatory to thyroid function and possess significant anti-hypothyroidism effect with p-values ranges from (0.000006*-0.893472). In conclusion, from results obtained, Lepidium sativum plant extract was found to posses anti-hypothyroidism effects so its act as an agent that stimulates thyroid hormone secretion.

Keywords: anti-hypothyroidism, extract, lepidium, sativum

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Authors: Joel F. Campbell, Bing Lin, Michael Obland, Susan Kooi, Tai-Fang Fan, Byron Meadows, Edward Browell, Wayne Erxleben, Doug McGregor, Jeremy Dobler, Sandip Pal, Christopher O'Dell, Ken Davis

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The Active Sensing of CO₂ Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center instrument funded by NASA’s Science Mission Directorate that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO₂ ) mixing ratios in support of the NASA ASCENDS mission. The ACES instrument, an Intensity-Modulated Continuous-Wave (IM-CW) lidar, was designed for high-altitude aircraft operations and can be directly applied to space instrumentation to meet the ASCENDS mission requirements. The ACES design demonstrates advanced technologies critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. The Atmospheric Carbon and Transport – America (ACT-America) is an Earth Venture Suborbital -2 (EVS-2) mission sponsored by the Earth Science Division of NASA’s Science Mission Directorate. A major objective is to enhance knowledge of the sources/sinks and transport of atmospheric CO₂ through the application of remote and in situ airborne measurements of CO₂ and other atmospheric properties on spatial and temporal scales. ACT-America consists of five campaigns to measure regional carbon and evaluate transport under various meteorological conditions in three regional areas of the Continental United States. Regional CO₂ distributions of the lower atmosphere were observed from the C-130 aircraft by the Harris Corp. Multi-Frequency Fiber Laser Lidar (MFLL) and the ACES lidar. The airborne lidars provide unique data that complement the more traditional in situ sensors. This presentation shows the applications of CO₂ lidars in support of these science needs.

Keywords: CO₂ measurement, IMCW, CW lidar, laser spectroscopy

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Authors: Oxana Lukoshus

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The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

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Authors: Dhritilekha Deka, Deepak Patwa, Ravi K., Archana M. Nair

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Bioaccumulation of heavy metal contaminants due to intense anthropogenic interference degrades the environment and ecosystem functions. Conventional physicochemical methods involve energy-intensive and costly methodologies. Phytoremediation, on the other hand, provides an efficient nature-based strategy for the reclamation of heavy metal-contaminated sites. However, the slow process and adaptation to high-concentration contaminant sequestration often limit the efficiency of the method. This necessitates natural amendments such as biochar to improve phytoextraction and stabilize the green cover. Biochar is a highly porous structure with high carbon sequestration potential and containing negatively charged functional groups that provide binding sites for the positively charged metals. This study aims to develop and determine the synergy between sugarcane bagasse biochar content and phytoremediation. A 60-day pot experiment using perennial tussock vetiver grass (Chrysopogon zizanioides) was conducted for different biochar contents of 1%, 2%, and 4% for the removal of cadmium and zinc. A concentration of 500 ppm is maintained for the amended and unamended control (CK) samples. The survival rates of the plants, biomass production, and leaf area index were measured for the plant growth characteristics. Results indicate a visible change in the plant growth and the heavy metal concentration with the biochar content. The bioconcentration factor (BCF) in the plant improved significantly for the 4% biochar content by 57% in comparison to the control CK treatment in Cd-treated soils. The Zn soils indicated the highest reduction in the metal concentration by 50% in the 2% amended samples and an increase in the BCF in all the amended samples. The translocation from the rhizosphere to the shoots was low but not dependent on the amendment content and varied for each contaminant type. The root-to-shoot ratio indicates higher values compared to the control samples. The enhanced tolerance capacities can be attributed to the nutrients released by the biochar in the soil. The study reveals the high potential of biochar as a phytoremediation amendment, but its effect is dependent on the soil and heavy metal and accumulator species.

Keywords: phytoextraction, biochar, heavy metals, chrysopogon zizanioides, bioaccumulation factor

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Authors: Shazia Naheed Akhter, Rekha Kumari

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An estimated 70 million population are exposed to arsenic poisoning in India in recent times. Arsenic contamination in the groundwater has caused serious health hazards among the exposed population. In Bihar, the first district was Bhojpur, where arsenic causing health issues were reported in 2002. Presently, there are 18 districts that are reported arsenic poisoning in the groundwater. The exposed population is firstly diseased with various symptoms such as skin manifestations, loss of appetite, constipation, hormonal disorders, etc. The long duration exposure has led to cause infertility in the male subjects. The present study thus aims to develop the antidote against arsenic-induced male reproductive toxicity in animal models. The study was carried out on Charles Foster Rats after the approval from Institutional Animal Ethics Committee. A total of n=18 rats (12 weeks old) of an average weight of 160 ± 20 g were used for the study. The study group included n=6 control and n= 12 treated with sodium arsenite orally at the dose of 8mg/Kg b.w daily for 40 days. The n= 6 animals were dissected and the rest n=6 was administered orally with Curcuma longa rhizome ethanolic extract at the dose of 600mg/Kg b.w per day for 40 days. At the end of the entire experiment, all the animals were dissected out and their reproductive organs were taken out, especially epididymis for sperm counts, sperm motility, sperm mortality, sperm morphology. The blood samples were collected for the hormonal assay (testosterone and luteinizing hormone), as well as for hematological and biochemical analysis. The study showed a high magnitude of degeneration in the reproductive organs of the rats in the arsenic-treated group. There were degenerative fluctuations in the sperm counts, sperm motility, sperm mortality, sperm morphology and in the hormonal parameters, as well as in the hematological and biochemical parameters in the arsenic-treated rats. But, after the administration of Curcuma longa, there was significant amelioration in all these parameters. Therefore, the present study shows that Curcuma longa plays a vital role to combat arsenic-induced male reproductive toxicity.

Keywords: sodium arsenite, Charles foster rats, ethanolic rhizome extract of curcuma longa, male reproductive toxicity, amelioration

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of the living tissues to the mechanical loads is necessary for a wide range of developing fields such as, designing of prosthetics and optimized surgery operations. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically growth and remodeling is one of the main sources. Extracting body organs from medical imaging, does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is the gravity since an organ grows under its influence from its birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. In this paper, we have implemented a computational framework based on fixed-point iteration to determine the residual stresses due to growth. Using nonlinear continuum mechanics and the concept of fictitious configuration we find the unknown stress-free reference configuration which is necessary for mechanical analysis. To illustrate the method, we apply it to a finite element model of healthy human face whose geometry has been extracted from medical images. We have computed the distribution of residual stress in facial tissues, which can overcome the effect of gravity and cause that tissues remain firm. Tissue wrinkles caused by aging could be a consequence of decreasing residual stress and not counteracting the gravity. Considering these stresses has important application in maxillofacial surgery. It helps the surgeons to predict the changes after surgical operations and their consequences.

Keywords: growth, soft tissue, residual stress, finite element method

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: battery state estimation, hybrid electric vehicle, hybrid energy storage, state of charge, state of health

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Authors: Mouna Baassi, Mohamed Moussaoui, Hatim Soufi, Sanchaita RajkhowaI, Ashwani Sharma, Subrata Sinha, Said Belaaouad

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Human Immunodeficiency Virus type 1 protease (HIV-1 PR) is one of the most challenging targets of antiretroviral therapy used in the treatment of AIDS-infected people. The performance of protease inhibitors (PIs) is limited by the development of protease mutations that can promote resistance to the treatment. The current study was carried out using statistics and bioinformatics tools. A series of thirty-three compounds with known enzymatic inhibitory activities against HIV-1 protease was used in this paper to build a mathematical model relating the structure to the biological activity. These compounds were designed by software; their descriptors were computed using various tools, such as Gaussian, Chem3D, ChemSketch and MarvinSketch. Computational methods generated the best model based on its statistical parameters. The model’s applicability domain (AD) was elaborated. Furthermore, one compound has been proposed as efficient against HIV-1 protease with comparable biological activity to the existing ones; this drug candidate was evaluated using ADMET properties and Lipinski’s rule. Molecular Docking performed on Wild Type and Mutant Type HIV-1 proteases allowed the investigation of the interaction types displayed between the proteases and the ligands, Darunavir (DRV) and the new drug (ND). Molecular dynamics simulation was also used in order to investigate the complexes’ stability, allowing a comparative study of the performance of both ligands (DRV & ND). Our study suggested that the new molecule showed comparable results to that of Darunavir and may be used for further experimental studies. Our study may also be used as a pipeline to search and design new potential inhibitors of HIV-1 proteases.

Keywords: QSAR, ADMET properties, molecular docking, molecular dynamics simulation.

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Authors: Kiran Nawaz, Ahmad Ali Shahid, Sehrish Iftikhar, Waheed Anwar, Muhammad Nasir Subhani

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Chili (Solanum annum L.) attacks by many fungal pathogens, including members of Oomycetes which are responsible for root rot in different chili growing areas of the world. Oomycetes pathogens cause economic losses in different regions of the Pakistan. Most of the plant tissues, including roots, crowns, fruit, and leaves, are vulnerable to Phytophthora capsici. It is very difficult to manage the Phytophthora root rot of chili as many commercial varieties are tremendously vulnerable to P. capsici. The causal agent of the disease was isolated on corn meal agar (CMA) and identified on a morphological basis by using available taxonomic keys. The pathogen was also confirmed on the molecular basis through internal transcribed spacer region and with other molecular markers.The Blastn results showed 100% homology with already reported sequences of P. capsici in NCBI database. Most of the farmers have conventionally relied on foliar fungicide applications to control Phytophthora root rot in spite of their incomplete effectiveness. In this study, in vitro plate assay, seed soaking and foliar applications of 6 fungicides were evaluated against root rot of chili. In vitro assay revealed that significant inhibition of linear growth was obtained with Triflumizole at 7.0%, followed by Thiophanate methyl (8.9%), Etridiazole (6.0%), Propamocarb (5.9%) and 7.5% with Mefenoxam and Iprodione for P. capsici. The promising treatments of in vitro plate bioassay were evaluated in pot experiments under controlled conditions in the greenhouse. All fungicides were applied after at 6-day intervals. Results of pot experiment showed that all treatments considerably inhibited the percentage of P. capsici root rot incidence. In addition, application of seed soaking with all six fungicides combined with the foliar spray of the same components showed the significant reduction in root rot incidence. The combine treatments of all fungicides as in vitro bioassay, seed soaking followed by foliar spray is considered non-harmful control methods which have advantages and limitation. Hence, these applications proved effective and harmless for the management of soil-borne plant pathogens.

Keywords: blastn, bioassay, corn meal agar(CMA), oomycetes

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Authors: Waheed Ahmad Safi, Shunichi Nakamura

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Concrete filled steel I-girder (CFIG) bridge was proposed and the bending and shear strength was confirmed by experiments. The area surrounded by the upper and lower flanges and the web is filled with concrete in CFIG, which is used to the intermediate support of a continuous girder. Three-dimensional finite element models were established to simulate the bending and shear behaviors of CFIG and to clarify the load transfer mechanism. Steel plates and filled concrete were modeled as a three-dimensional 8-node solid element and steel reinforcement bars as a three-dimensional 2-node truss element. The elements were mostly divided into the 50 x 50 mm mesh size. The non-linear stress-strain relation is assumed for concrete in compression including the softening effect after the peak, and the stress increases linearly for concrete in tension until concrete cracking but then decreases due to tension stiffening effect. The stress-strain relation for steel plates was tri-linear and that for reinforcements was bi-linear. The concrete and the steel plates were rigidly connected. The developed FEM model was applied to simulate and analysis the bending behaviors of the CFIG specimens. The vertical displacements and the strains of steel plates and the filled concrete obtained by FEM agreed very well with the test results until the yield load. The specimens collapsed when the upper flange buckled or the concrete spalled off. These phenomena cannot be properly analyzed by FEM, which produces a small discrepancy at the ultimate states. The FEM model was also applied to simulate and analysis the shear tests of the CFIG specimens. The vertical displacements and strains of steel and concrete calculated by FEM model agreed well with the test results. A truss action was confirmed by the FEM and the experiment, clarifying that shear forces were mainly resisted by the tension strut of the steel plate and the compression strut of the filled concrete acting in the diagonal direction. A trail design with the CFIG was carried out for a four-span continuous highway bridge and the design method was established. Construction cost was estimated about 12% lower than that of a conventional steel I-section girder.

Keywords: concrete filled steel I-girder, bending strength, FEM, limit states design, steel I-girder, shear strength

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Authors: H. Shamoradifar, B. Teimuri, P. Parvaresh, S. Mohammadi

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One of the main characteristics of Heavy Water Moderated Reactors is their high production of plutonium. This article demonstrates the possibility of reduction of plutonium and other actinides in Heavy Water Research Reactor. Among the many ways for reducing plutonium production in a heavy water reactor, in this research, changing the fuel from natural Uranium fuel to Thorium-Uranium mixed fuel was focused. The main fissile nucleus in Thorium-Uranium fuels is U-233 which would be produced after neutron absorption by Th-232, so the Thorium-Uranium fuels have some known advantages compared to the Uranium fuels. Due to this fact, four Thorium-Uranium fuels with different compositions ratios were chosen in our simulations; a) 10% UO₂-90% THO₂ (enriched= 20%); b) 15% UO₂-85% THO₂ (enriched= 10%); c) 30% UO₂-70% THO₂ (enriched= 5%); d) 35% UO₂-65% THO₂ (enriched= 3.7%). The natural Uranium Oxide (UO₂) is considered as the reference fuel, in other words all of the calculated data are compared with the related data from Uranium fuel. Neutronic parameters were calculated and used as the comparison parameters. All calculations were performed by Monte Carol (MCNPX2.6) steady state reaction rate calculation linked to a deterministic depletion calculation (CINDER90). The obtained computational data showed that Thorium-Uranium fuels with four different fissile compositions ratios can satisfy the safety and operating requirements for Heavy Water Research Reactor. Furthermore, Thorium-Uranium fuels have a very good proliferation resistance and consume less fissile material than uranium fuels at the same reactor operation time. Using mixed Thorium-Uranium fuels reduced the long-lived α emitter, high radiotoxic wastes and the radio toxicity level of spent fuel.

Keywords: Heavy Water Reactor, Burn up, Minor Actinides, Neutronic Calculation

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Authors: Debarati Bhaumik, Diptish Dey

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Multilevel models, increasingly deployed in industries such as insurance, food production, and entertainment within functions such as marketing and supply chain management, need to be transparent and ethical. Applications usually result in binary classification within groups or hierarchies based on a set of input features. Using open-source datasets, we demonstrate that popular explainability methods, such as SHAP and LIME, consistently underperform inaccuracy when interpreting these models. They fail to predict the order of feature importance, the magnitudes, and occasionally even the nature of the feature contribution (negative versus positive contribution to the outcome). Besides accuracy, the computational intractability of SHAP for binomial classification is a cause of concern. For transparent and ethical applications of these hierarchical statistical models, sound audit frameworks need to be developed. In this paper, we propose an audit framework for technical assessment of multilevel regression models focusing on three aspects: (i) model assumptions & statistical properties, (ii) model transparency using different explainability methods, and (iii) discrimination assessment. To this end, we undertake a quantitative approach and compare intrinsic model methods with SHAP and LIME. The framework comprises a shortlist of KPIs, such as PoCE (Percentage of Correct Explanations) and MDG (Mean Discriminatory Gap) per feature, for each of these three aspects. A traffic light risk assessment method is furthermore coupled to these KPIs. The audit framework will assist regulatory bodies in performing conformity assessments of AI systems using multilevel binomial classification models at businesses. It will also benefit businesses deploying multilevel models to be future-proof and aligned with the European Commission’s proposed Regulation on Artificial Intelligence.

Keywords: audit, multilevel model, model transparency, model explainability, discrimination, ethics

Procedia PDF Downloads 88

Authors: Qianqian He, Naian Liu, Xiaodong Xie, Linhe Zhang, Yang Zhang, Weidong Yan

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In the wild, the vegetation layer with exceptionally complex fuel composition and heterogeneous spatial distribution strongly affects the rate of fire spread (ROS) and fire intensity. Clarifying the influence of fuel bed structure on fire spread behavior is of great significance to wildland fire management and prediction. The packing ratio is one of the key physical parameters describing the property of the fuel bed. There is a threshold value of the packing ratio for ROS, but little is known about the controlling mechanism. In this study, to address this deficiency, a series of fire spread experiments were performed across a discrete fuel bed composed of some regularly arranged laser-cut cardboards, with constant wind speed and different packing ratios (0.0125-0.0375). The experiment aims to explore the relative importance of the internal and surface heat transfer with packing ratio. The dependence of the measured ROS on the packing ratio was almost consistent with the previous researches. The data of the radiative and total heat fluxes show that the internal heat transfer and surface heat transfer are both enhanced with increasing packing ratio (referred to as ‘Stage 1’). The trend agrees well with the variation of the flame length. The results extracted from the video show that the flame length markedly increases with increasing packing ratio in Stage 1. Combustion intensity is suggested to be increased, which, in turn, enhances the heat radiation. The heat flux data shows that the surface heat transfer appears to be more important than the internal heat transfer (fuel preheating inside the fuel bed) in Stage 1. On the contrary, the internal heat transfer dominates the fuel preheating mechanism when the packing ratio further increases (referred to as ‘Stage 2’) because the surface heat flux keeps almost stable with the packing ratio in Stage 2. As for the heat convection, the flow velocity was measured using Pitot tubes both inside and on the upper surface of the fuel bed during the fire spread. Based on the gas velocity distribution ahead of the flame front, it is found that the airflow inside the fuel bed is restricted in Stage 2, which can reduce the internal heat convection in theory. However, the analysis indicates not the influence of inside flow on convection and combustion, but the decreased internal radiation of per unit fuel is responsible for the decrease of ROS.

Keywords: discrete fuel bed, fire spread, packing ratio, wildfire

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Authors: Daniel Panario, Daniel Santana de Freitas, Brett Stevens

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Almost Perfect Nonlinear (APN) permutations with optimal resistance against differential cryptanalysis can be found in several domains. The permutation used in the standard for symmetric cryptography (the AES), for example, is based on a special kind of inversion in GF(28). Although very close to APN (2-uniform), this permutation still contains one number 4 in its differential spectrum, which means that, rigorously, it must be classified as 4-uniform. This fact motivates the search for fully APN permutations in other domains of definition. The extremely high complexity associated to this kind of problem precludes an exhaustive search for an APN permutation with 256 elements to be performed without the support of a suitable mathematical structure. On the other hand, in principle, there is nothing to indicate which mathematically structured domains can effectively help the search, and it is necessary to test several domains. In this work, the search for APN permutations in rings ℤ2×ℤ2k is investigated. After a full, exhaustive search with k=2 and k=3, all possible APN permutations in those rings were recorded, together with their differential profiles. Some very promising heuristics in these cases were collected so that, when used as a basis to prune backtracking for the same search in ℤ2×ℤ8 (search space with size 16! ≅244), just a few tenths of a second were enough to produce an APN permutation in a single CPU. Those heuristics were empirically extrapolated so that they could be applied to a backtracking search for APNs over ℤ2×ℤ16 (search space with size 32! ≅2117). The best permutations found in this search were further refined through Simulated Annealing, with a definition of neighbors suitable to this domain. The best result produced with this scheme was a 3-uniform permutation over ℤ2×ℤ16 with only 24 values equal to 3 in the differential spectrum (all the other 968 values were less than or equal 2, as it should be the case for an APN permutation). Although far from being fully APN, this result is technically better than a 4-uniform permutation and demanded only a few seconds in a single CPU. This is a strong indication that the use of mathematically structured domains, like the rings described in this work, together with heuristics based on smaller cases, can lead to dramatic cuts in the computational resources involved in the complexity of the search for APN permutations in extremely large domains.

Keywords: APN permutations, heuristic searches, symmetric cryptography, S-box design

Procedia PDF Downloads 154

Authors: Dimitra Marini, Konstantinos Bakogiannis, Spyros Polychronopoulos, Georgios Kouroupetroglou

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Archaemusicology cannot entirely depend on the study of the excavated ancient musical instruments as most of the time their condition is not ideal (i.e., missing/eroded parts) and moreover, because of the concern damaging the originals during the experiments. Researchers, in order to overcome the above obstacles, build replicas. This technique is still the most popular one, although it is rather expensive and time-consuming. Throughout the last decades, the development of physical modeling techniques has provided tools that enable the study of musical instruments through their digitally simulated models. This is not only a more cost and time-efficient technique but also provides additional flexibility as the user can easily modify parameters such as their geometrical features and materials. This paper thoroughly describes the steps to create a physical model of a woodwind ancient Greek instrument, Plagiaulos. This instrument could be considered as the ancestor of the modern flute due to the common geometry and air-jet excitation mechanism. Plagiaulos is comprised of a single resonator with an open end and a number of tone holes. The combination of closed and open tone holes produces the pitch variations. In this work, the effects of all the instrument’s components are described by means of physics and then simulated based on digital waveguides. The synthesized sound of the proposed model complies with the theory, highlighting its validity. Further, the synthesized sound of the model simulating the Plagiaulos of Koile (2nd century BCE) was compared with its replica build in our laboratory by following the scientific methodologies of archeomusicology. The aforementioned results verify that robust dynamic digital tools can be introduced in the field of computational, experimental archaemusicology.

Keywords: archaeomusicology, digital waveguides, musical acoustics, physical modeling

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Authors: Md. Kausar Alam, Ramin Motamed

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The damaging effects of liquefaction-induced ground movements have been frequently observed in past earthquakes, such as the 2010-2011 Canterbury Earthquake Sequence (CES) in New Zealand and the 2011 Tohoku earthquake in Japan. To reduce the consequences of soil liquefaction at shallow depths, various ground improvement techniques have been utilized in engineering practice, among which this research is focused on experimentally evaluating the press-in sheet piling technique. The press-in sheet pile technique eliminates the vibration, hammering, and noise pollution associated with dynamic sheet pile installation methods. Unfortunately, there are limited experimental studies on the press-in sheet piling technique for liquefaction mitigation using 1g shake table tests in which all the controlling mechanisms of liquefaction-induced foundation settlement, including sand ejecta, can be realistically reproduced. In this study, a series of moderate scale 1g shake table experiments were conducted at the University of Nevada, Reno, to evaluate the performance of this technique in liquefiable soil layers. First, a 1/5 size model was developed based on a recent UC San Diego shaking table experiment. The scaled model has a density of 50% for the top crust, 40% for the intermediate liquefiable layer, and 85% for the bottom dense layer. Second, a shallow foundation is seated atop an unsaturated sandy soil crust. Third, in a series of tests, a sheet pile with variable embedment depth is inserted into the liquefiable soil using the press-in technique surrounding the shallow foundations. The scaled models are subjected to harmonic input motions with amplitude and dominant frequency properly scaled based on the large-scale shake table test. This study assesses the performance of the press-in sheet piling technique in terms of reductions in the foundation movements (settlement and tilt) and generated excess pore water pressures. In addition, this paper discusses the cost-effectiveness and carbon footprint features of the studied mitigation measures.

Keywords: excess pore water pressure, foundation settlement, press-in sheet pile, soil liquefaction

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Authors: Fu Jia

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The effects of soil-structure interaction (SSI) are often studied using axial-symmetric three-dimensional (3D) models to avoid the high computational cost of the more realistic, fully 3D models, which require 2-3 orders of magnitude more computer time and storage. This paper analyzes the error and presents correction factors for system frequency, system damping, and peak amplitude of structural response computed by axisymmetric models, embedded in uniform or layered half-space. The results are compared with those for fully 3D rectangular foundations of different aspect ratios. Correction factors are presented for a range of the model parameters, such as fixed-base frequency, structure mass, height and length-to-width ratio, foundation embedment, soil-layer stiffness and thickness. It is shown that the errors are larger for stiffer, taller and heavier structures, deeper foundations and deeper soil layer. For example, for a stiff structure like Millikan Library (NS response; length-to-width ratio 1), the error is 6.5% in system frequency, 49% in system damping and 180% in peak amplitude. Analysis of a case study shows that the NEHRP-2015 provisions for reduction of base shear force due to SSI effects may be unsafe for some structures and need revision. The presented correction factor diagrams can be used in practical design and other applications.

Keywords: 3D soil-structure interaction, correction factors for axisymmetric models, length-to-width ratio, NEHRP-2015 provisions for reduction of base shear force, rectangular embedded foundations, SSI system frequency, SSI system damping

Procedia PDF Downloads 259

Authors: Matthias Walluch, José Alberto Rodríguez, Christopher Giehl, Gunther Arnold, Daniela Ehgartner

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Dynamic mechanical analysis (DMA) is a powerful method to characterize viscoelastic properties and phase transitions for a wide range of materials. It is often used to characterize polymers and their temperature-dependent behavior, including thermal transitions like the glass transition temperature Tg, via determination of storage and loss moduli in tension (Young’s modulus, E) and shear or torsion (shear modulus, G) or other testing modes. While production and application temperatures for polymers are often limited to several hundred degrees, material properties of glasses usually require characterization at temperatures exceeding 600 °C. This contribution highlights a high temperature setup for rotational and oscillatory rheometry as well as for DMA in different modes. The implemented standard convection oven enables the characterization of glass in different loading modes at temperatures up to 950 °C. Three-point bending, tension and torsional measurements on different glasses, with E and G moduli as a function of frequency and temperature, are presented. Additional tests include superimposing several frequencies in a single temperature sweep (“multiwave”). This type of test results in a considerable reduction of the experiment time and allows to evaluate structural changes of the material and their frequency dependence. Furthermore, DMA in torsion and tension was performed to determine the complex Poisson’s ratio as a function of frequency and temperature within a single test definition. Tests were performed in a frequency range from 0.1 to 10 Hz and temperatures up to the glass transition. While variations in the frequency did not reveal significant changes of the complex Poisson’s ratio of the glass, a monotonic increase of this parameter was observed when increasing the temperature. This contribution outlines the possibilities of DMA in bending, tension and torsion for an extended temperature range. It allows the precise mechanical characterization of material behavior from room temperature up to the glass transition and the softening temperature interval. Compared to other thermo-analytical methods, like Dynamic Scanning Calorimetry (DSC) where mechanical stress is neglected, the frequency-dependence links measurement results (e.g. relaxation times) to real applications

Keywords: dynamic mechanical analysis, oscillatory rheometry, Poisson's ratio, solid glass, viscoelasticity

Procedia PDF Downloads 78