Search results for: protein structure classification

Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Behrang Dadfar, Hossein Bidhendi, Jimmy Susetyo, John Paul Abbatangelo

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Finding structural demand under various conditions that a structure may experience during its service life is an important step towards structural life-cycle analysis. In this paper, structural demand for the precast concrete tunnel lining (PCTL) segments of Toronto’s 60-year-old subway tunnels is investigated. Numerical modelling was conducted using FLAC3D, a finite difference-based software capable of simulating ground-structure interaction and ground material’s flow in three dimensions. The specific structural details of the segmental tunnel lining, such as the convex shape of the PCTL segments at radial joints and the PCTL segment pockets, were considered in the numerical modelling. Also, the model was developed in a way to accommodate the flexibility required for the simulation of various deterioration scenarios, shapes, and patterns that have been observed over more than 20 years. The soil behavior was simulated by using plastic-hardening constitutive model of FLAC3D. The effect of the depth of the tunnel, the coefficient of lateral earth pressure as well as the patterns of deterioration of the segments were studied. The structural capacity under various deterioration patterns and the existing loading conditions was evaluated using axial-flexural interaction curves that were developed for each deterioration pattern. The results were used to provide recommendations for the next phase of tunnel lining rehabilitation program.

Keywords: precast concrete tunnel lining, ground-structure interaction, numerical modelling, deterioration, tunnels

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Authors: Y. Benmalem , A. Abbad, W. Benstaali, T. Lantri

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Density functional theory is used to investigate the.the structural, electronic, and magnetic properties of the cubic anti-perovskites InNNi3 and ZnNNi3. The structure of antiperovskite also called (perovskite-inverse) identical to the perovskite structure of the general formula ABX3, where A is a main group (III–V) element or a metallic element, B is carbon or nitrogen, and X is a transition metal, displays a wide range of interesting physical properties, such as giant magnetoresistance. Elastic and electronic properties were determined using generalized gradient approximation (GGA), and local spin density approximation (LSDA) approaches, ), as implemented in the Wien2k computer package. The results show that the two compounds are strong ductile and satisfy the Born-Huang criteria, so they are mechanically stable at normal conditions. Electronic properties show that the two compounds studied are metallic and non-magnetic. The studies of these compounds have confirmed the effectiveness of the two approximations and the ground-state properties are in good agreement with experimental data and theoretical results available.

Keywords: anti-perovskites, elastic anisotropy, electronic band structure, first-principles calculations

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Authors: K. Petcharaporn

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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Authors: O. B. Oriolowo, O. J. John

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Empirical findings have shown insects to be nutritious and good source of food for man. However, human food preferences are not only determined by nutritional values of food consumed but, more importantly, by sociology and economic pressure. This study examined the interrelation between science and sociology in sustaining the acceptance of entomophagy among college students to combat food insecurity. A twenty items five Likert scale, College Students Entomophagy Questionnaire (CSEQ), was used to elucidate information from the respondents. The reliability coefficient was obtained to be 0.91 using Spearman-Brown Prophecy formula. Three research questions and three hypotheses were raised. Also, quantitative nutritional analysis of few insects and some established conventional protein sources were undertaking in order to compare their nutritional status. The data collected were analyzed using descriptive statistics of percentages and inferential statistics of correlation and Analysis of Variance (ANOVA). The results obtained showed that entomophagy has cultural heritage among different tribes in Nigeria and is an acceptable practice; it cuts across every social stratum and is practiced among both major religions. Moreover, insects compared favourably in term of nutrient contents when compared with the conventional animal protein sources analyzed. However, there is a gradual decline in the practice of entomophagy among students, which may be attributed to the influence of western civilization. This study, therefore, recommended an intensification of research and enlightenment of people on the usefulness of entomophagy so as to preserve its cultural heritage as well as boost human food security.

Keywords: entomophagy, food security, malnutrition, poverty alleviation, sociology

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Authors: A. Abbas Khalaf, L. Issazadeh, Z. Arif Abdullah, J. Hassanpour

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In order to evaluate the growth and yield properties of two Sorghum-Sudangrass hybrids under different irrigation levels, an investigation was done in the experiment site of Collage of Agriculture, University of Duhok, Kurdistan region of Iraq (36°5´38^⸗ N, 42°52´02^⸗ E) in the years 2015-16. The experiment was conducted under Randomized Complete Block Design (RCBD) with three replications, which main factor was irrigation treatments (I₁₀₀, I₇₅ and I₅₀) according to evaporation pan class A and type of Sorghum-Sudangrass hybrids (KH12SU9001, G₁) and (KH12SU9002, G₂) were factors of subplots. The parameters studied were: plant height (cm), number of green leaves per plant; leaf area (m²/m²), stem thickness (mm), percent of protein, fresh and dry biomass (ton.ha^-1) and also crop water productivity. The results of variance analysis showed that KH12SU9001 variety had more amount of leaf area, percent of protein, fresh and dry biomass yield in comparison to KH12SU9002 variety. By comparing effects of irrigation levels on vegetative growth and yield properties, results showed that amount of plant height, fresh and dry biomass weight was decreased by decreasing irrigation level from full irrigation regime to 5 _o% of irrigation level. Also, results of crop water productivity (CWP) indicated that improvement in quantity of irrigation would impact fresh and dry biomass yield significantly. Full irrigation regime was recorded the highest level of CWP (1.28-1.29 kg.m^-3).

Keywords: deficit irrigation, growth, sorghum-sudangrass hybrid, yield

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Authors: T. I. Mbata, M. J. Ikenebomeh

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Background: The study was aim at formulating a complementary foods based on maize and bambara groundnut with a view of reducing malnutrition in low income families. Protein-energy malnutrition is a major health challenge attributed to the inappropriate complementary feeding practices, low nutritional quality of traditional complementary foods and high cost of quality protein-based complementary foods. Methods: The blends 70% maize, 30% bambara groundnut were evaluated for proximate analyses, minerals, amino acids profile, and antinutritional factors, using proprietary formula (‘Nutrend’) as standard. Antinutritional factors, amino acids, microbiological properties and sensory attributes were determined using standard methods. Results; For Protein, the results were 15.0% for roasted bambara groundnut maize germinated flour (RBMGF), 13.80% for cooked bambara groundnut maize germinated flour (CBMGF), 15.18% for soaked bambara groundnut maize germinated flour (SBMGF); values for maize flour and nutrend had 10.4% and 23.21% respectively. With respect to energy value, RBMGF, CBMGF, SBMGF, maize flour and nutrend had 494.9, 327.58, 356.49, 366.8 and 467.2 kcal respectively. The percentages of total essential amino acids in the composition of the blends were 36.9%, 40.7% and 38.9% for CBMGF, SBMGF and RBMGF, respectively, non-essential amino acids contents were 63.1%, 59.3% and 61.1% for CBMGF, SBMGF and RBMGF respectively. The mineral content, that is, calcium, potassium, magnesium and sodium, of formulated samples were higher than those obtained for maize flour and Nutrend. The antinutrient composition of RBMGF and CBMGF were lower than of SBMGF. The rats fed with the control diet exhibited better growth performance such as feed intake (1527 g) and body weight gain (93.8 g). For the microbial status, microflora gradually changed from gram negative enteric bacteria, molds, lactic acid bacteria and yeast to be dominated by gram positive lactic acid bacteria (LAB) and yeasts. Yeasts and LAB growth counts in the complementary food varied between 4.44 and 7.36 log cfu/ml. LAB number increased from 5.40 to 7.36 log cfu/ml during fermentation. Yeasts increased from 4.44 to 5.60 log cfu/ml. Organoleptic evaluation revealed that the foods were well accepted. Conclusion: Based on the findings the application of bambara groundnut fortification to traditional foods can promote the nutritional quality of African maize - based traditional foods with acceptable rheological and cooking qualities.

Keywords: bambara groundnut, maize, fortification, complementary food

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Authors: Abdelkader Hocine, Abdelhakim Maizia

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The exponential growth of reinforced fibers composite materials use has prompted researchers to step up their work on the prediction of their reliability. Owing to differences between the properties of the materials used for the composite, the manufacturing processes, the load combinations and types of environment, the prediction of the reliability of composite materials has become a primary task. Through failure criteria, TSAI-WU and the maximum stress, the reliability of multilayer tubular structures under pressure is the subject of this paper, where the failure probability of is estimated by the method of Monte Carlo.

Keywords: composite, design, monte carlo, tubular structure, reliability

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Authors: Agbugui M. O., Inobeme A.

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Fish constitutes a vital component of human diets due to their rich nutritional compositions. They serve as a remarkable source of proteins, vitamins, and fatty acids, which are indispensable for the effective growth and development of humans. The need to explore the nutritional compositions of various species of fish in different water bodies becomes paramount. Presently, consumer concern is not just on food's nutritional value but also on the safety level. Environmental contamination by heavy metals has become an issue of pressing concern in recent times. Heavy metals, due to their ubiquitous nature, are found in various water bodies as they are released from various anthropogenic activities. This work investigated the proximate compositions, mineral contents, and heavy metals concentrations of four different species of fish (P. annectens, L. niloticus, G. niloticus, and H. niloticus) collected from the lower Niger at Agenebode using standard procedures. The highest protein contents were in Gymnarchus niloticus (37.32%), while the least was in Heterotis niloticus (20.41%). Protopterus annectens had the highest carbohydrate content (34.55%), while Heterotis niloticus had the least (12.24%). The highest lipid content (14.41%) was in Gymnarchus niloticus. The highest concentration of potassium was 21.00 ppm. The concentrations of heavy metals in ppm ranged from 0.01 – 1.4 (Cd), 0.07 – 2.89 (Pb), 0.02 – 16.4 (Hg), 0.88 – 5.1 (Cu) and 1.2 – 8.23 (Zn). The concentrations of Hg, Cd and Pb in some of the samples investigated were higher than the permissible limits based on international standards. There is a pressing need for further study focusing on various species of animals and plants in the area due to the alarming contents of these metals; remedial measures could also be ensured for safety.

Keywords: trace metals, nutritional value, human health, crude protein, lipid content

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Authors: Polo G. Yohn Edison, Rocha F. Pedricto

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This work presents a study about a retaining structure designed for the duplication of the rail FEPASA on the 74th km between Santos and São Paulo. This structure, an anchored retaining wall, was instrumented in the anchors heads with strain gauges in order to monitor its loads. The load measurements occurred during the performance test, locking and also after the works were concluded. A decrease on anchors loads is noticed at the moment immediately after the locking, during construction and after the works finished. It was observed that a loss of load in the anchors occurred to a maximum of 54%.

Keywords: instrumentation, strain gauges, retaining wall, anchors

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Authors: Guoyu Wang, Meilian Zhang, Chunhui LI, Bing Ren

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In recent decades, a variety of floating structures have played a crucial role in ocean and marine engineering, such as ships, offshore platforms, floating breakwaters, fish farms, floating airports, etc. It is common for floating structures to suffer from loadings under waves, and the responses of the structures mounted in marine environments have a significant relation to the wave impacts. The interaction between surface waves and floating structures is one of the important issues in ship or marine structure design to increase performance and efficiency. With the progress of computational fluid dynamics, a number of numerical models based on the NS equations in the time domain have been developed to explore the above problem, such as the finite difference method or the finite volume method. Those traditional numerical simulation techniques for moving bodies are grid-based, which may encounter some difficulties when treating a large free surface deformation and a moving boundary. In these models, the moving structures in a Lagrangian formulation need to be appropriately described in grids, and the special treatment of the moving boundary is inevitable. Nevertheless, in the mesh-based models, the movement of the grid near the structure or the communication between the moving Lagrangian structure and Eulerian meshes will increase the algorithm complexity. Fortunately, these challenges can be avoided by the meshless particle methods. In the present study, a moving particle semi-implicit model is explored for the numerical simulation of fluid–structure interaction with surface flows, especially for coupling of fluid and moving rigid body. The equivalent momentum transfer method is proposed and derived for the coupling of fluid and rigid moving body. The structure is discretized into a group of solid particles, which are assumed as fluid particles involved in solving the NS equation altogether with the surrounding fluid particles. The momentum conservation is ensured by the transfer from those fluid particles to the corresponding solid particles. Then, the position of the solid particles is updated to keep the initial shape of the structure. Using the proposed method, the motions of a free-floating body in regular waves are numerically studied. The wave surface evaluation and the dynamic response of the floating body are presented. There is good agreement when the numerical results, such as the sway, heave, and roll of the floating body, are compared with the experimental and other numerical data. It is demonstrated that the presented MPS model is effective for the numerical simulation of fluid-structure interaction.

Keywords: floating body, fluid structure interaction, MPS, particle method, waves

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

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In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: Zahara Abdulhussan Al-Awadai

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Currently, serious games play a significant role in education, sparking an increasing interest in using games for purposes beyond mere entertainment. In this research, we investigate the main requirements and aspects of designing and developing effective serious games for learning and developing a conceptual model to describe the structure of serious games with a focus on both aspects of serious games. The main contributions of this approach are to facilitate the design and development of serious games in a flexible and easy-to-use way and also to support the cooperative work between the multidisciplinary developer team.

Keywords: game development, game design, requirements, serious games, serious game model.

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Authors: Alaa Hamed Habib

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The Coronavirus disease 2019 (COVID-19) is a viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated with systemic inflammation. Inflammation is an important process that follows infection and facilitates the repair of damaged tissue. Polyunsaturated fatty acids play an important role in the inflammatory process. These lipids can target transcription factors to modulate gene expression and protein function. Here, we evaluated whether differences in basal levels of different types of biomarkers can be detected in freshly frozen plasma samples from patients with and without COVID19. Fatty acid methyl ester (FAME) analysis showed a decrease in arachidic acid and myristic acid, but an increase in caprylic acid, palmitic acid, and eicosenoic acid in the plasma of COVID-19 patients compared to non-COVID19 patients. Multiple chemokines, including IP-10, MCP-1, and MIP-1 beta, were increased in the COVID-19 group compared to the non-COVID-19 group. Similarly, cytokines including IL-1 alpha and IL-8, and cell adhesion and inflammatory response markers including ICAM-1 and E-selectin were greater in the plasma of COVID-19 patients compared to non-COVID-19 patients. A baseline signature of specific polyunsaturated fatty acids, cytokines, and chemokines present in the plasma after COVID-19 viral infection may serve as biomarkers that can be useful in various applications, including determination of the severity of infection, an indication of disease prognosis and consideration for therapeutic options.

Keywords: MARKS, COVID 19, UEVS NON COVIDS, kidneys, nanoparticles

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Authors: Wooseok Song, Sunjung Park, Jongkwon Lee, Jaye Koo

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The objective of this paper is to observe the effects of injection conditions on flame structures in gas-centered swirl coaxial injector. Gaseous oxygen and liquid kerosene were used as propellants. For different injection conditions, two types of injector, which only differ in the diameter of the tangential inlet, were used in this study. In addition, oxidizer injection pressure was varied to control the combustion chamber pressure in different types of injector. In order to analyze the combustion instability intensity, the dynamic pressure was measured in both the combustion chamber and propellants lines. With the increase in differential pressure between the propellant injection pressure and the combustion chamber pressure, the combustion instability intensity increased. In addition, the flame structure was recorded using a high-speed camera to detect CH* chemiluminescence intensity. With the change in the injection conditions in the gas-centered swirl coaxial injector, the flame structure changed.

Keywords: liquid rocket engine, flame structure, combustion instability, dynamic pressure

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Esra Sengul, R. G. Aktas, M. E. Sitar, H. Isan

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Hepatocellular carcinoma (HCC) is a hepatocellular tumor commonly found on the surface of the chronic liver. HepG2 is the most commonly used cell type in HCC studies. The main proteins remaining in the blood serum after separation of plasma fibrinogen are albumin and globulin. The fact that the albumin showed hepatocellular damage and reflect the synthesis capacity of the liver was the main reason for our use. Alpha-Fetoprotein (AFP) is an albumin-like structural embryonic globulin found in the embryonic cortex, cord blood, and fetal liver. It has been used as a marker in the follow-up of tumor growth in various malign tumors and in the efficacy of surgical-medical treatments, so it is a good protein to look at with albumins. We have seen the morphological changes of dimethyl sulfoxide (DMSO) on HepG2 and decided to investigate its biochemical effects. We examined the effects of DMSO, which is used in cell cultures, on albumin, AFP and total protein at low doses. Material Method: Cell Culture: Medium was prepared in cell culture using Dulbecco's Modified Eagle Media (DMEM), Fetal Bovine Serum Dulbecco's (FBS), Phosphate Buffered Saline and trypsin maintained at -20 ° C. Fixation of Cells: HepG2 cells, which have been appropriately developed at the end of the first week, were fixed with acetone. We stored our cells in PBS at + 4 ° C until the fixation was completed. Area Calculation: The areas of the cells are calculated in the ImageJ (IJ). Microscope examination: The examination was performed with a Zeiss Inverted Microscope. Daytime photographs were taken at 40x, 100x 200x and 400x. Biochemical Tests: Protein (Total): Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Albumin: Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Alpha-fetoprotein: Serum sample was analyzed by ECLIA method. Results: When liver cancer cells were cultured in medium with 1% DMSO for 4 weeks, a significant difference was observed when compared with the control group. As a result, we have seen that DMSO can be used as an important agent in the treatment of liver cancer. Cell areas were reduced in the DMSO group compared to the control group and the confluency ratio increased. The ability to form spheroids was also significantly higher in the DMSO group. Alpha-fetoprotein was lower than the values of an ordinary liver cancer patient and the total protein amount increased to the reference range of the normal individual. Because the albumin sample was below the specimen value, the numerical results could not be obtained on biochemical examinations. We interpret all these results as making DMSO a caretaking aid. Since each one was not enough alone we used 3 parameters and the results were positive when we refer to the values of a normal healthy individual in parallel. We hope to extend the study further by adding new parameters and genetic analyzes, by increasing the number of samples, and by using DMSO as an adjunct agent in the treatment of liver cancer.

Keywords: hepatocellular carcinoma, HepG2, dimethyl sulfoxide, cell culture, ELISA

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Authors: K. Petcharaporn, N. Prathengjit

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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Authors: Nairy Kechichian

Abstract:

The original Leclerc Bridge is a covered wooden bridge that is considered a Quebec heritage structure with an index of 60, making it a very important provincial bridge from a historical point of view. It was constructed in 1927 and is in the rural area of Abitibi-Temiscamingue. It is a “town Québécois” type of structure, which is generally rare but common for covered bridges in Abitibi-Temiscamingue. This type of structure is composed of two trusses on both sides formed with diagonals, internal bracings, uprights and top and bottom chords to allow the transmission of loads. This structure is mostly known for its solidity, lightweightness, and ease of construction. It is a single-span bridge with a length of 25.3 meters and allows the passage of one vehicle at a time with a 4.22-meter driving lane. The structure is composed of 2 trusses located at each end of the deck, two gabion foundations at both ends, uprights and top and bottom chords. WSP (Williams Sale Partnership) Canada inc. was mandated by the Transport Minister of Quebec in 2019 to increase the capacity of the bridge from 5 tons to 30.6 tons and rehabilitate it, as it has deteriorated quite significantly over the years. The bridge was damaged due to material deterioration over time, exposure to humidity, high load effects and insect infestation. To allow the passage of 3 axle trucks, as well as to keep the integrity of this heritage structure, the final design chosen to rehabilitate the bridge involved adding a new deck independent from the roof structure of the bridge. Essentially, new steel beams support the deck loads and the desired vehicle loads. The roof of the bridge is linked to the steel deck for lateral support, but it is isolated from the wooden deck. The roof is preserved for aesthetic reasons and remains intact as it is a heritage piece. Due to strict traffic management obstacles, an efficient construction method was put into place, which consisted of building a temporary bridge and moving the existing roof onto it to allow the circulation of vehicles on one side of the temporary bridge while providing a working space for the repairs of the roof on the other side to take place simultaneously. In parallel, this method allowed the demolition and reconstruction of the existing foundation, building a new steel deck, and transporting back the roof on the new bridge. One of the main criteria for the rehabilitation of the wooden bridge was to preserve, as much as possible, the existing patrimonial architectural design of the bridge. The project was completed successfully by the end of 2021.

Keywords: covered bridge, wood-steel, short span, town Québécois structure

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Hafiza Javaria Ashraf, Xinghong Wang, Zhanghong Shi, Youming Hou

Abstract:

Insect’s innate immunity depends on a variety of defense responses for the recognition of invading pathogens. Pathogen recognition involves particular proteins known as pattern recognition receptors (PRRs). These PRRs interact with pathogen-associated molecular patterns (PAMPs) present on the surface of pathogens to distinguish between self and non-self. C-type lectins (CTLs) belong to a superfamily of PPRs which involved in insect immunity and defense mechanism. Rhynchophorus ferrugineus Olivier is a devastating pest of Palm cultivations in China. Although studies on R. ferrugineus immune mechanism and host defense have conducted, however, the role of CTL in immune responses of R. ferrugineus remains elusive. Here, we report RfCTL, which is a secreted protein containing a single-CRD domain. The open reading frame (ORF) of CTL is 226 bp, which encodes a putative protein of 168 amino acids. Transcript expression analysis revealed that RfCTL highly expressed in immune-related tissues, i.e., hemolymph and fat body. The abundance of RfCTL in the gut and fat body dramatically increased upon Staphylococcus aureus and Escherichia coli bacterial challenges, suggesting a role in defense against gram-positive and gram-negative bacterial infection. Taken together, we inferred that RfCTL might be involved in the immune defense of R. ferrugineus and established a solid foundation for future studies on R. ferrugineus CTL domain proteins for better understanding of insect immunity.

Keywords: biological invasion, c-type lectin, insect immunity, Rhynchophorus ferrugineus Oliver

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Authors: T. Garba, Y. Y. Sabo A. Babanyara, K. G. Ilellah, A. K. Mutari

Abstract:

This study used the Normalized Difference Vegetation Index (NDVI) and maps compiled from the classification of Landsat TM and Landsat ETM images of 1986 and 1999 respectively and Nigeria sat 1 images of 2007 to quantify changes in land use and land cover in selected areas of Nigeria covering 143,609 hectares that are threatened by the encroaching Sahara desert. The results of this investigation revealed a decrease in natural vegetation over the three time slices (1986, 1999 and 2007) which was characterised by an increase in high positive pixel values from 0.04 in 1986 to 0.22 and 0.32 in 1999 and 2007 respectively and, a decrease in natural vegetation from 74,411.60ha in 1986 to 28,591.93ha and 21,819.19ha in 1999 and 2007 respectively. The same results also revealed a periodic trend in which there was progressive increase in the cultivated area from 60,191.87ha in 1986 to 104,376.07ha in 1999 and a terminal decrease to 88,868.31ha in 2007. These findings point to expansion of vegetated and cultivated areas in in the initial period between 1988 and 1996 and reversal of these increases in the terminal period between 1988 and 1996. The study also revealed progressive expansion of built-up areas from 1, 681.68ha in 1986 to 2,661.82ha in 1999 and to 3,765.35ha in 2007. These results argue for the urgent need to protect and conserve the depleting natural vegetation by adopting sustainable human resource use practices i.e. intensive farming in order to minimize persistent depletion of natural vegetation.

Keywords: changes, classification, desertification, vegetation changes

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

Abstract:

In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Jaruwan Duangchuen, Siwalak Pathaveerat

Abstract:

Coconut (Cocos nucifera) belongs to the family Arecaceae. Coconut juice and meat are consumed as food and dessert in several regions of the world. Coconut juice contains low proteins, and arginine is the main amino acid content. Coconut meat is the endosperm of coconut that has nutritional value. It composes of carbohydrate, protein and fat. The objective of this study is utilization of by-products from the virgin coconut oil extraction process by using the skimmed coconut milk as a powder. The skimmed coconut milk was separated from the coconut milk in virgin coconut oil extraction process that consists approximately of protein 6.4%, carbohydrate 7.2%, dietary fiber 0.27 %, sugar 6.27%, fat 3.6 % and moisture content of 86.93%. This skimmed coconut milk can be made to powder for value - added product by using spray drying. The factors effect to the yield and properties of dry skimmed coconut milk in spraying process are inlet, outlet air temperature and the maltodextrin concentration. The percentage of maltodextrin content (15, 20%), outlet air temperature (80 ºC, 85 ºC, 90 ºC) and inlet air temperature (190 ºC, 200 ºC, 210 ºC) were conducted to the skimmed coconut milk spray drying process. The spray dryer was kept air flow rate (0.2698 m3 /s). The result that shown 2.22 -3.23% of moisture content, solubility, bulk density (0.4-0.67g/mL), solubility, wettability (4.04 -19.25 min) for solubility in the water, color, particle size were analyzed for the powder samples. The maximum yield (18.00%) of spray dried coconut milk powder was obtained at 210 °C of temperature, 80°C of outlet temperature and 20% maltodextrin for 27.27 second for drying time. For the amino analysis shown that the high amino acids are Glutamine (16.28%), Arginine (10.32%) and Glycerin (9.59%) by using HPLP method (UV detector).

Keywords: skimmed coconut milk, spray drying, virgin coconut oil process (VCO), maltodextrin

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Authors: Nikita Katyal, Shaurya Uppal

Abstract:

This paper tackles the significant challenge of accurately classifying customers within a retailer’s customer base. Accurate classification is essential for developing targeted marketing strategies that effectively engage this important demographic. To address this issue, we propose a method that utilizes Large Language Models (LLMs). By employing LLMs, we analyze the metadata associated with product purchases derived from historical data to identify key product categories that act as distinguishing factors. These categories, such as baby food, eldercare products, or family-sized packages, offer valuable insights into the likely household composition of customers, including families with babies, families with kids/teenagers, families with pets, households caring for elders, or mixed households. We segment high-confidence customers into distinct categories by integrating historical purchase behavior with LLM-powered product classification. This paper asserts that life stage segmentation can significantly enhance e-commerce businesses’ ability to target the appropriate customers with tailored products and campaigns, thereby augmenting sales and improving customer retention. Additionally, the paper details the data sources, model architecture, and evaluation metrics employed for the segmentation task.

Keywords: LLMs, segmentation, product tags, fine-tuning, target segments, marketing communication

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Authors: Ghibeche Abderrahmane

Abstract:

To examine whether genes associated with cellular defense against oxidative stress are associated with insulin sensitivity, patients with type 2 diabetes (n=7) and age-matched (n=5) and young (n=9) control subjects underwent a euglycemic-hyperinsulinemic clamp for 120 min. Muscle samples were obtained before and after the clamp and analyzed for heat shock protein (HSP)72 and heme oxygenase (HO)-1 mRNA, intramuscular triglyceride content, and the maximal activities of β-hyroxyacyl-CoA dehydrogenase (β-HAD) and citrate synthase (CS). Basal expression of both HSP72 and HO-1 mRNA were lower (P < 0.05) by 33 and 55%, respectively, when comparing diabetic patients with age-matched and young control subjects, with no differences between the latter groups. Both basal HSP72 (r = 0.75, P < 0.001) and HO-1 (r = 0.50,P < 0.05) mRNA expression correlated with the glucose infusion rate during the clamp. Significant correlations were also observed between HSP72 mRNA and both β-HAD (r = 0.61, P < 0.01) and CS (r = 0.65, P < 0.01). HSP72 mRNA was induced (P < 0.05) by the clamp in all groups. Although HO-1 mRNA was unaffected by the clamp in both the young and age-matched control subjects, it was increased (P < 0.05) ∼70-fold in the diabetic patients after the clamp. These data demonstrate that genes involved in providing cellular protection against oxidative stress are defective in patients with type 2 diabetes and correlate with insulin-stimulated glucose disposal and markers of muscle oxidative capacity. The data provide new evidence that the pathogenesis of type 2 diabetes involves perturbations to the antioxidant defense mechanism within skeletal muscle.

Keywords: euglycemic-hyperinsulinemic, HSP72, mRNA, diabete

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Authors: Hyungoo Kang, Jinkoo Kim

Abstract:

This study investigated the determination of the optimal location and friction force of friction dampers to effectively reduce the seismic response of a reinforced concrete structure designed without considering seismic load. To this end, the genetic algorithm process was applied and the results were compared with those obtained by simplified methods such as distribution of dampers based on the story shear or the inter-story drift ratio. The seismic performance of the model structure with optimally positioned friction dampers was evaluated by nonlinear static and dynamic analyses. The analysis results showed that compared with the system without friction dampers, the maximum roof displacement and the inter-story drift ratio were reduced by about 30% and 40%, respectively. After installation of the dampers about 70% of the earthquake input energy was dissipated by the dampers and the energy dissipated in the structural elements was reduced by about 50%. In comparison with the simplified methods of installation, the genetic algorithm provided more efficient solutions for seismic retrofit of the model structure.

Keywords: friction dampers, genetic algorithm, optimal design, RC buildings

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Authors: Irma Gabriela Lopez-Moreno, Elva Perez-Luque, Herlinda Aguilar-Zavala

Abstract:

Introduction: Type 2 Diabetes Mellitus (T2DM) is characterized by combination of insulin resistance and deterioration of insulin secretion. Sfrp5 is a protein that antagonizes Wnt5a proteins by preventing it from reaching its receptor and activating the Wnt/β-catenin signaling pathway, this pathway is one of the most important regulators of adipogenesis. Although metformin decreases glucose levels its mechanisms of action are not fully known but it has been implicated in the inhibition of the Wnt/β-catenin signaling pathway. Objective: The objective was evaluating the effects of metformin on serum levels of Sfrp5 in patients with T2DM treated and not treated with metformin. Methods: Two groups of patients were selected: one group of T2DM patients treated with metformin (n = 35) and another group of subjects with recent diagnosis of T2DM untreated (n = 35) with a mean age of 48 ± 9 years. In these subjects anthropometric measures were taken as weight, height, waist and hip circumference, were calculated the percentage of body fat, visceral fat and muscle mass. In addition, were measured glucose levels, lipid profile, adiponectin and Sfrp5. Results: Sfrp5 were higher in metformin-treated patients compared to the untreated group (19.9 vs 13.6 ng/mL p < 0.001), a negative correlation was found between Sfrp5 levels and total cholesterol levels (r= -0.25, p = 0.03) and percentage of visceral fat (r = -0.26, p = 0.03) and a positive correlation with HDL cholesterol levels (r = 0.31, p = 0.01) and adiponectin (r=0.65, p = < 0.001). Conclusions: The findings show that metformin consumption increased levels of Sfrp5, which may lead to a decrease in the activation of the WNT/β-catenin pathway impacting on adipogenesis.

Keywords: adiponectin, diabetes, metformin, Sfrp5

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

Abstract:

We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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