Search results for: activity learning

Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Devendra Sillu, Shekhar Agnihotri

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The 'nano-biocatalyst' utilizes an ordered assembling of enzyme on to nanomaterial carriers to catalyze desirable biochemical kinetics and substrate selectivity. The current study describes an inter-disciplinary approach for converting agriculture waste, sugarcane bagasse into D-glucose exploiting halloysite nanotubes (HNTs) decorated cellulase enzyme as nano-biocatalytic system. Cellulase was successfully immobilized on HNTs employing polydopamine as an eco-friendly crosslinker while iron oxide nanoparticles were attached to facilitate magnetic recovery of material. The characterization studies (UV-Vis, TEM, SEM, and XRD) displayed the characteristic features of both cellulase and magnetic HNTs in the resulting nanocomposite. Various factors (i.e., working pH, temp., crosslinker conc., enzyme conc.) which may influence the activity of biocatalytic system were investigated. The experimental design was performed using Response Surface Methodology (RSM) for process optimization. Analyses data demonstrated that the nanobiocatalysts retained 80.30% activity even at elevated temperature (55°C) and excellent storage stabilities after 10 days. The repeated usage of system revealed a remarkable consistent relative activity over several cycles. The immobilized cellulase was employed to decompose agro-waste and the maximum decomposition rate of 67.2 % was achieved. Conclusively, magnetic HNTs can serve as a potential support for enzyme immobilization with long term usage, good efficacy, reusability and easy recovery from solution.

Keywords: halloysite nanotubes, enzyme immobilization, cellulase, response surface methodology, magnetic recovery

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Authors: B. Benalioua, I. Benyamina, M. Mansour, A. Bentouami, B. Boury

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The objective of this study is based on the synthesis of a new photocatalyst based on TiO2 and its application in the photo-degradation of an acid dye under the visible light. The material obtained was characterized by XRD, BET and UV- vis DRS. The photocatalytic efficiency of the Zn -Fe TiO2 treated at 500°C was tested on the Indigo Carmine under the irradiation of visible light and compared with that of the commercial titanium oxide TiO2-P25 (Degussa). The XRD characterization of the material Zn-Fe-TiO2 (500°C) revealed the presence of the anatase phase and the absence of the Rutile phase in comparison of the TiO2 P25 diffractogram. Characterization by UV-visible diffuse reflection material showed that the Fe-Zn-TiO2 exhibits redshift (move visible) relative to commercial titanium oxide TiO2-P25, this property promises a photocatalytic activity of Zn -Fe- TiO2 under visible light. Indeed, the efficiency of photocatalytic Fe-Zn-TiO2 as a visible light is shown by a complete discoloration of indigo carmine solution of 16 mg/L after 40 minutes, whereas with the P25-TiO2 discoloration is achieved after 90 minutes.

Keywords: POA, heterogeneous photocatalysis, TiO2, doping

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Authors: Michael Lousis

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The systematic identification of the most conspicuous and significant errors made by learners during three-years of testing of their progress in learning Arithmetic are presented in this article. How these errors have changed over three-years of school instruction of Arithmetic also is shown. The sample is comprised of two hundred (200) English students and one hundred and fifty (150) Greek students. These students were purposefully selected according to their participation in each testing session in the development of the three-year Kassel Project in England and Greece, in both domains simultaneously in Arithmetic and Algebra. The data sample includes six test-scripts corresponding to three testing sessions in both Arithmetic and Algebra respectively.

Keywords: arithmetic, errors, Kassel Project, progress of learning

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Authors: Milad Abbasi

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Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

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Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Laurence C. Hanes, Robert J. Stone

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Video games have reached a point of huge commercial success as well as wide familiarity with audiences both young and old. Much attention and research have also been directed towards serious games and their potential learning affordances. It is little surprise that the field of virtual heritage has taken a keen interest in using serious games to present cultural heritage information to users, with applications ranging from museums and cultural heritage institutions, to academia and research, to schools and education. Many researchers have already documented their efforts to develop and distribute virtual heritage serious games. Although attempts have been made to create classifications of the different types of virtual heritage games (somewhat akin to the idea of game genres), no formal taxonomy has yet been produced to define the different types of cultural heritage and historical information that can be presented through these games at a content level, and how the information can be manifested within the game. This study proposes such a taxonomy. First the informational content is categorized as heritage or historical, then further divided into tangible, intangible, natural, and analytical. Next, the characteristics of the manifestation within the game are covered. The means of manifestation, level of demonstration, tone, and focus are all defined and explained. Finally, the potential learning outcomes of the content are discussed. A demonstration of the taxonomy is then given by describing the informational content and corresponding manifestations within several examples of virtual heritage serious games as well as commercial games. It is anticipated that this taxonomy will help designers of virtual heritage serious games to think about and clearly define the information they are presenting through their games, and how they are presenting it. Another result of the taxonomy is that it will enable us to frame cultural heritage and historical information presented in commercial games with a critical lens, especially where there may not be explicit learning objectives. Finally, the results will also enable us to identify shared informational content and learning objectives between any virtual heritage serious and/or commercial games.

Keywords: informational content, serious games, taxonomy, virtual heritage

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Authors: B. Chandar, M. K. Ramasamy, P. Madasamy

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The discovery and development of newer antibiotics are limited with the increase in resistance of such multi-drug resistant bacteria creating the need for alternative new therapeutic agents. The recently discovered New Delhi Metallo-betalactamase-1 (NDM-1), which confers antibiotic resistance to most of the currently available β-lactams, except colistin and tigecycline, is a global concern. Several antibacterial drugs approved are natural products or their semisynthetic derivatives, but plant extracts remain to be explored to find molecules that are effective against NDM-1 bacteria. Therefore, it is necessary to explore the possibility of finding new and effective antibacterial compounds against NDM-1 bacteria. In the present study, we have screened a diverse set South Indian plant species, and report most plant species as a potential source for antimicrobial compounds against NDM-1 bacteria. Ethanol extracts from the leaves of taxonomically diverse South Indian medicinal plants were screened for antibacterial activity against NDM-1 E. coli using streak plate method. Among the plant screened against NDM-1 E. coli, the ethanol extracts from many plant extracts showed minimum bactericidal concentration between 5 and 15 mg /ml and MIC between 2.54 and 5.12 mg/ml. These extracts also showed a potent synergistic effect when combined with antibiotics colistin and tetracycline. Combretum albidum that was effective was taken for further analysis. At 5mg/L concentration, these extracts inhibited the NDM-1 enzyme in vitro, and residual activity for Combretum albidum was 33.09%. Treatment of NDM-1 E. coli with the extracts disrupted the cell wall integrity and caused 89.7% cell death. The plant extract of Combretum albidum that was effective was subjected to fractionation and the fraction was further subjected to HPLC, LC-MS for identification of antibacterial compound.

Keywords: antibacterial activity, combretum albidum, Escherichia coli, NDM-1

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Authors: Siriporn Okonogi, Pimpak Phumat, Sakornrat Khongkhunthian

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Piper betle has been extensively reported for various pharmacological effects including antimicrobial activity. 4-Allylpyrocatechol (AC) is a principle active compound found in P. betle. However, AC has a problem of solubility in water. The aims of the present study were to prepare AC loaded polymeric micelles for enhancing its water solubility and to evaluate its anti-biofilm activity against oral phathogenic bacteria. AC was loaded in polymeric micelles (PM) of Pluronic F127 by using thin film hydration method to obtain AC loaded PM (PMAC). The results revealed that AC in the form of PMAC possessed high water solubility. PMAC particles were characterized using a transmission electron microscope and photon correlation spectroscopy. Determination of entrapment efficiency (EE) and loading capacity (LC) of PMAC was done by using high-performance liquid chromatography. The highest EE (86.33 ± 14.27 %) and LC (19.25 ± 3.18 %) of PMAC were found when the weight ratio of polymer to AC was 4 to 1. At this ratio, the particles showed spherical in shape with the size of 38.83 ± 1.36 nm and polydispersity index of 0.28 ± 0.10. Zeta potential of the particles is negative with the value of 16.43 ± 0.55 mV. Crystal violet assay and confocal microscopy were applied to evaluate the effects of PMAC on Streptococcus mutans biofilms using chlorhexidine (CHX) as a positive control. PMAC contained 1.5 mg/mL AC could potentially inhibit (102.01 ± 9.18%) and significantly eradicate (85.05 ± 2.03 %) these biofilms (p < 0.05). Comparison with CHX, PMAC showed slightly similar biofilm inhibition but significantly stronger biofilm eradication (p < 0.05) than CHX. It is concluded that PMAC can enhance water solubility and anti-biofilm activity of AC.

Keywords: pluronic, polymeric micelles, solubility, 4-allylpyrocathecol, Streptococcus mutans, anti-biofilm

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Authors: Salima Tabti, Chaima Maouche, Tinhinene Louaileche, Amel Djedouani, Ismail Warad

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Novel Schiff base ligand HL has been synthesized by condensation of aromatic amine and DHA. It was characterized by UV-Vis, FT-IR, SM, NMR (1H, 13C) and also by single-crystal X-ray diffraction. The crystal structure shows that compound crystallized in a triclinic system in P-1 space group and with a two unit per cell (Z = 2).The asymmetric unit, contains one independent molecules, the conformation is determined by an intermolecular N-H…O hydrogen bond with an S(6) ring motif. The molecule have an (E) conformation about the C=N bond. The dihedral angles between the phenyl and pyran ring planes is 89.37 (1), the two plans are approximately perpendicular. The catecholase activity of is situ copper complexes of this ligand has been investigated against catechol. The progress of the oxidation reactions was closely monitored over time following the strong peak of catechol using UV-Vis. Oxidation rates were determined from the initial slope of absorbance. time plots, then analyzed by Michaelis-Menten equations. Catechol oxidation reactions were realized using different concentrations of copper acetate and ligand (L/Cu: 1/1, 1/2, 2/1). The results show that all complexes were able to catalyze the oxidation of catechol. Acetate complexes have the highest activity. Catalysis is a branch of chemical kinetics that, more generally, studies the influence of all physical or chemical factors determining reaction rates. It solves a lot of problems in the chemistry reaction process, especially for a green, economic and less polluting chemistry. For this reason, the search for new catalysts for known organic reactions, occupies a very advanced place in the themes proposed by the chemists.

Keywords: dehydroacetic acid, catechol, copper, catecholase activity, x-ray

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Fitri Ayu, Nadia, Tanti, Putri, Fatkhan, Pasid Harlisa, Suparmi

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Acne is a skin abnormal conditions experienced by many teens, this is caused by various factors such as the climate is hot, humid and excessive sun exposure can aggravate acne because it will lead to excess oil production. Flavonoids form complex compounds against extracellular proteins that disrupt the integrity of bacterial cell membrane in a way denature bacterial cell proteins and bacterial cell membrane damage. This study aimed to test the antibacterial activity of corn silk extract with a concentration of 10 %, 20 %, 30 %, 40 %, 50 %, 60 %, 70 %, 80 %, 90 % and 100 % in vitro by measuring the inhibition of the growth of bacteria Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermis then compared with the standard antibiotic clindamycin. Extracts tested by Disk Diffusion Method, in which the blank disc soaked with their respective corn silk extract concentration for 15-30 minutes and then the medium of bacteria that have been planted with Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermis in the given disk that already contains extracts with various concentration. Incubated for 24 hours and then measured the growth inhibition zone Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermidis. Corn silk contains flavonoids, is shown by the test of flavonoids in corn silk extract by using a tube heating and without heating. Flavonoid in corn silk potentially as anti acne by inhibiting the growth of bacteria that cause acne. Corn silk extract concentration which has the highest antibacterial activity is then performed in a cream formulation and evaluation test of physical and chemical properties of the resulting cream preparation.

Keywords: antibacterial, flavonoid, corn silk, acne

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Authors: Hanane Boutaj, Abdelilah Meddich, Said Wahbi, Zainab El Alaoui-Talibi, Allal Douira, Abdelkarim Filali-Maltouf, Cherkaoui El Modafar

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The present work aims to investigate the effect of arbuscular mycorrhizal fungi (AMF) in improving the olive tree resistance to Verticillium wilt caused by Verticillium dahliae. Inoculated plants with a mycorrhizal autochthonous consortium 'Rhizolive consortium' and pure strain 'Glomus irregulare' were infected after three months with V. dahliae. The improving of olive tree resistance was determined through disease severity, incidence, and defoliation. On the other hand, the defense mechanisms of olive plants were evaluated through lignin content, phenylalanine ammonia lyase (PAL) activity, and polyphenol content. The results revealed that both AMF significantly (p < 0.05) reduced disease development and the rate of defoliation in infected olive plants. Moreover, the contents of lignin were boosted after mycorrhizal inoculation in both the roots and the stems of olive plants, which remained significantly (p < 0.001) higher after the 90th days of V. dahliae inoculation. PAL activity was increased after V. dahliae inoculation in the stems of 'Rhizolive consortium' treatment that were 17 times higher than those in the roots of olive plants. The polyphenol content in the stems was about twice higher than those in the roots. The reduction of disease severity was accompanied by increased levels of lignin content, PAL activity, and polyphenol content, particularly in the stems of olive plants, indicating the strengthening of the olive plant immune system against V. dahliae.

Keywords: olive tree, Mycorrhizal autochthonous consortium, Glomus irregulare, Verticillium dahliae, defense mechanisms

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Nancy M. El-Baz, Laila Ziko, Rania Siam, Wael Mamdouh

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Cancer is one of the most devastating diseases, and has over than 10 million new cases annually worldwide. Despite the effectiveness of chemotherapeutic agents, their systemic toxicity and non-selective anticancer actions represent the main obstacles facing cancer curability. Due to the effective enhanced permeability and retention (EPR) effect of nanomaterials, nanoparticles (NPs) have been used as drug nanocarriers providing targeted cancer drug delivery systems. In addition, several inorganic nanoparticles such as silver (AgNPs) nanoparticles demonstrated a potent anticancer activity against different cancers. The present study aimed at formulating core-shell inorganic NPs-based combinatorial therapy based on combining the anticancer activity of AgNPs along with doxorubicin (DOX) and evaluating their cytotoxicity on MCF-7 breast cancer cells. These inorganic NPs-based combinatorial therapies were designed to (i) Target and kill cancer cells with high selectivity, (ii) Have an improved efficacy/toxicity balance, and (iii) Have an enhanced therapeutic index when compared to the original non-modified DOX with much lower dosage The in-vitro cytotoxicity studies demonstrated that the NPs-based combinatorial therapy achieved the same efficacy of non-modified DOX on breast cancer cell line, but with 96% reduced dose. Such reduction in DOX dose revealed that the combination between DOX and NPs possess a synergic anticancer activity against breast cancer. We believe that this is the first report on a synergic anticancer effect at very low dose of DOX against MCF-7 cells. Future studies on NPs-based combinatorial therapy may aid in formulating novel and significantly more effective cancer therapeutics.

Keywords: nanoparticles-based combinatorial therapy, silver nanoparticles, doxorubicin, breast cancer

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Authors: A. Abdenbi, B. Dennai, B. Touati, M. Bouaaza, A. Saad

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The essential oils of many plants have become popular in recent years and their bioactive principles have recently won several industry sectors, however their use as antibacterial and anti fungal agents has been reported. This study focuses on the physico chemical and phyto chemical with a study of the antimicrobial activity of essential oils of aromatic and medicinal plant of southwest Algeria, this essential oil was obtained by hydro-distillation of aerial parts of Cotula cinerea, belonging to the Asteraceae family, it is very extensive in the spring season in a region called Kenadza road, located 12km from Bechar. Variable anti fungal activity of the essential oil of Cotula cinerea (yield 2%) were revealed about four fungal strains, the minimum inhibitory concentrations of essential oils were determined by the method of dilution in agar. Significant fungal sensitivity of Penicillium sp with an inhibition of 32.3 mm area.

Keywords: Cotula cinerea, essential oil, physico- chemical analysis and phyto- chemical, anti fungal power

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: M. Abdel-Hamid, P. Saporito, R. V. Mateiu, A. Osman, E. Romeih, H. Jenssen

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Camel milk whey (CMW) was hydrolyzed with papain from Carica papaya and fractionated by size exclusion chromatography (SEC). The antibacterial and anti-biofilm activity of the CMW, Camel milk whey hydrolysate (CMWH) and the obtained SEC-fractions was assessed against Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus (MRSA). SEC-F2 (fraction 2) exhibited antibacterial effectiveness against MRSA and P. aeruginosa with the minimum inhibitory concentration of 0.31 and 0.156 mg/ml, respectively. Furthermore, SEC-F2 significantly decreased biofilm biomass by 71% and 83 % for MRSA and P. aeruginosa in a crystal violet microplate assay. Scanning electron microscopy showed that the SEC-F2 caused changes in the treated bacterial cells. Additionally, LC/MS analysis was used to characterize the peptides of SEC-F2. Two major peptides were detected in SEC-F2 having masses of 414.05 Da and 456.06 Da. In conclusion, this study has demonstrated that hydrolysis of CMW with papain generates small and extremely potent antibacterial and anti-biofilm peptides against both MRSA and P. aeruginosa.

Keywords: camel milk, whey proteins, antibacterial peptide, anti-biofilm

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Authors: D. Shehu, Z. Alias

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Glutathione S-transferases (GSTs) are family of enzymes that function in the detoxification of variety of electrophilic substrates. In the present work, we report a novel zeta-like GST (designated as KKSG9) from the biphenyl/polychlorobiphenyl degrading organism Acidovorax sp. KKS102. KKSG9 possessed low sequence similarity but similar biochemical properties to zeta class GSTs. The gene for KKSG9 was cloned, purified and biochemically characterized. Functional analysis showed that the enzyme exhibits wider substrate specificity compared to most zeta class GSTs by reacting with 1-chloro-2,4-dinitrobenzene (CDNB), p-nitrobenzyl chloride (NBC), ethacrynic acid (EA), hydrogen peroxide, and cumene hydroperoxide (CuOOH). The enzyme also displayed dehalogenation function against dichloroacetate (a common substrate for zeta class GSTs) in addition to permethrin, and dieldrin. The functional role of Tyr12 was also investigated by site-directed mutagenesis. The mutant (Y12C) displayed low catalytic activity and dehalogenation function against all the substrates when compared with the wild type. Kinetic analysis using NBC and GSH as substrates showed that the mutant (Y12C) displayed a higher affinity for NBC when compared with the wild type, however, no significant change in GSH affinity was observed. These findings suggest that the presence of tyrosine residue in the motif might represent an evolutionary trend toward improving the catalytic activity of the enzyme. The enzyme as well could be useful in the bioremediation of various types of organochlorine pollutants.

Keywords: Acidovorax sp. KKS102, bioremediation, glutathione s-transferase, site-directed mutagenesis, zeta

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Authors: Richard I. Licayan, Aisle Janne B. Dagpin, Romeo M. Del Rosario, Nenita D. Palmes

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Hiptage benghalensis, Antigonon leptopus, Macroptillium atropurpureum, and Dioscorea bulbifera L. are herbal weeds that have been used by traditional healers in rural communities in the Philippines as medicine. In this study, the basic pharmacological components of the crude secondary metabolites extracted from the four herbal weeds and their in vitro antioxidant properties was investigated to provide baseline data for the possible development of these metabolites in pharmaceutical products. Qualitative screening of the secondary metabolites showed that alkaloids, tannins, saponins, steroids, and flavonoids were present in their leaf extracts. All of the plant extracts showed varied antioxidant activity. The greatest DPPH radical scavenging activity was observed in H. begnhalensis (84.64%), followed by A. leptopus (68.21%), M. atropurpureum (26.62%), and D. bulbifera L. (19.04%). The FRAP assay revealed that H. benghalensis had the highest antioxidant activity (8.32 mg/g) while ABTS assay showed that M. atropurpureum had the strongest scavenging ability of free radicals (0.0842 mg Trolox/g). The total flavonoid content (TFC) analysis showed that D. bulbifera L. had the highest TFC (420.35 mg quercetin per gram-dried material). The total phenolic content (TPC) of the four herbal weeds showed large variations, between 26.56±0.160 and 55.91±0.087 mg GAE/g dried material. The plant leaf extracts arranged in increasing values of TPC are H. benghalensis (26.565) < A. leptopus (37.29) < D. bulbifera L. (46.81) < M. atropurpureum (55.91). The obtained results may support their use in herbal medicine and as baseline data for the development of new drugs and standardized phytomedicines.

Keywords: antioxidant properties, total flavonoids, total phenolics, creeping herbal weeds

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Authors: Tatjana Kadifkova Panovska, Svetlana Kulevanova, Blagica Jovanova

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Biological systems possess the ability to neutralize the excess of reactive oxygen species (ROS) and to protect cells from destructive alterations. However, many pathological conditions (cardiovascular diseases, autoimmune disorders, cancer) are associated with inflammatory processes that generate an excessive amount of reactive oxygen species (ROS) that shift the balance between endogenous antioxidant systems and free oxygen radicals in favor of the latter, leading to oxidative stress. Therefore, an additional source of natural compounds with antioxidant properties that will reduce the amount of ROS in cells is much needed despite their broad utilization; many plant species remain largely unexplored. Therefore, the purpose of the present study is to investigate the antioxidant activity of twenty-five selected medicinal and aromatic plant species. The antioxidant activity of the ethanol extracts was evaluated with in vitro assays: 2,2’-diphenyl-1-pycryl-hydrazyl (DPPH), ferric reducing antioxidant power (FRAP), non-site-specific- (NSSOH) and site-specific hydroxyl radical-2-deoxy-D-ribose degradation (SSOH) assays. The Folin-Ciocalteu method and AlCl3 method were performed to determine total phenolic content (TPC) and total flavonoid content (TFC). All examined plant extracts manifested antioxidant activity to a different extent. Cinnamomum verum J.Presl bark and Ocimum basilicum L. Herba demonstrated strong radical scavenging activity and reducing power with the DPPH and FRAP assay, respectively. Additionally, significant hydroxyl scavenging potential and metal chelating properties were observed using the NSSOH and SSOH assays. Furthermore, significant variations were determined in the total polyphenolic content (TPC) and total flavonoid content (TFC), with Cinnamomum verum and Ocimum basilicum showing the highest amount of total polyphenols. The considerably strong radical scavenging activity, hydroxyl scavenging potential and reducing power for the species mentioned above suggest of a presence of highly bioactive phytochemical compounds, predominantly polyphenols. Since flavonoids are the most abundant group of polyphenols that possess a large number of available reactive OH groups in their structure, it is considered that they are the main contributors to the radical scavenging properties of the examined plant extracts. This observation is supported by the positive correlation between the radical scavenging activity and the total polyphenolic and flavonoid content obtained in the current research. The observations from the current research nominate Cinnamomum verum bark and Ocimum basilicum herba as potential sources of bioactive compounds that could be utilized as antioxidative additives in the food and pharmaceutical industries. Moreover, the present study will help the researchers as basic data for future research in exploiting the hidden potential of these important plants that have not been explored so far.

Keywords: ethanol extracts, radical scavenging activity, reducing power, total polyphenols.

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Authors: Farah El Mohtadi, Richard d'Arcy, Nicola Tirelli

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Since 40 years, poly (ethylene glycol) (PEG) has been the gold standard in biomaterials and drug delivery, because of its combination of chemical and biological inertness. However, the possibility of its breakdown under oxidative conditions and the demonstrated development of anti-PEG antibodies highlight the necessity to develop carriers based on materials with increased stability in a challenging biological environment. Here, we describe the synthesis of polysulfide via anionic ring-opening polymerization. In vitro, the synthesized polymer was characterized by low toxicity and a level of complement activation (in human plasma) and macrophage uptake slightly lower than PEG and poly (2‐methyl-2‐oxazoline) (PMOX), of a similar size. Importantly, and differently from PEG, on activated macrophages, the synthesized polymer showed a strong and dose-dependent ROS scavenging activity, which resulted in the corresponding reduction of cytokine production. Therefore, the results from these studies show that polysulfide is highly biocompatible and are potential candidates to be used as an alternative to PEG for various applications in nanomedicine.

Keywords: PEG, low toxicity, ROS scavenging, biocompatible

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Authors: Weerachit Pulsawas, Thirasak Rirksomboon

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Due to its abundance from catalytic reforming and thermal cracking of naphtha, toluene could become more value-added compound if it is converted into xylenes, particularly p-xylene, via toluene methylation. Attractively, toluene methylation with methanol is an alternative route to produce xylenes in the absence of other hydrocarbon by-products for which appropriate catalyst would be utilized. In this study, HZSM-5 catalysts with Si/Al molar ratio of 100 were synthesized via hydrothermal treatment and modified by either chemical liquid deposition using tetraethyl-orthosilicate or dealumination with steam. The modified catalysts were characterized by several techniques and tested for their catalytic activity in a continuous down-flow fixed bed reactor. Various operating conditions including WHSV’s of 5 to 20 h-1, reaction temperatures of 400 to 500 °C, and toluene-to-methanol molar ratios (T/M) of 1 to 4 were investigated for attaining possible highest p-xylene selectivity. As a result, the catalytic activity of parent HZSM-5 with temperature of 400 °C, T/M of 4 and WHSV of 24 h-1 showed 65.36% in p-xylene selectivity and 11.90% in toluene conversion as demonstrated for 4 h on stream.

Keywords: toluene methylaion, HZSM-5, silylation, dealumination

Procedia PDF Downloads 184

Authors: Ting Gao, Mingyue He

Abstract:

Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

Procedia PDF Downloads 81

Authors: Christiana Ene Ogwuche, Joseph Amupitan, George Ndukwe, Rachael Ayo

Abstract:

Maesobotrya barteri (Baill), belonging to the family Euphorbiaceae, is a medicinal plant growing widely in tropical Africa. The Aerial plant parts of Maesobotrya barteri (Baill) were collected fresh from Orokam, Ogbadibo local Government of Benue State, Nigeria in July 2013. Taxonomical identification was done by Mallam Musa Abdullahi at the Herbarium unit of Biological Sciences Department, ABU, Zaria, Nigeria. Pulverized aerial parts of Maesobotrya barteri (960g) was exhaustively extracted successively using petroleum ether, chloroform, ethyl acetate and methanol and concentrated in the rotary evaporator at 40°C. The Petroleum ether extract had the second highest activity against test microbes from preliminary crude microbial screenings. The Petroleum ether extract was subjected to phytochemical studies, antimicrobial analysis and column chromatography (CC). The column chromatography yielded fraction PE, which was further purified using preparative thin layer chromatography to give PE1. The structure of the isolated compound was established using 1-D NMR and 2-D NMR spectroscopic analysis and by direct comparison with data reported in literature was confirmed to be a mixture, an isomer of Betulinic acid and Oleanolic acid, both with the molecular weight (C₃₀H₄₈O₃). The bioactivity of this compound was carried out using some clinical pathogens and the activity compared with standard drugs, and this was found to be comparable with the standard drug.

Keywords: Maesobotrya barteri, medicinal plant, bioactivity, petroleum spirit extract, butellinic acid, oleanilic acid

Procedia PDF Downloads 180

Authors: Sriraman Kothuri, Komal Teja Mattupalli

Abstract:

In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

Procedia PDF Downloads 390

Authors: Alaa M. Badr Eldin, Mayar M. Shahen, Mohammed S. Sedeek, Marwa I. Ezzat, Sawsan M. ElSonbaty, Muhammed A. Saad, Manal S. Afifi, Omar M. Sabry

Abstract:

Using HPLC-MS/MS technique, 133 polyphenolic compounds were identified in the methanol extract of pomegranate rind (Punica granatum L.). In-vitro cytotoxic activity against breast cancer cell line MCF-7 was investigated, with an IC50 of 54 ug/ml. In-silico molecular docking using ellagic acid, gallagic acid, and Punicalagin as model compounds identified in pomegranate rind extract confirmed the intriguing anti-estrogenic action of the key polyphenolic components in pomegranate rind extract. Surprisingly, taxol showed low activity compared to pomegranate compounds as ERα antagonist and ERβ agonist. Pomegranate rind extract enhanced apoptosis of breast cancer cells through upregulation of the caspase-3 expression and downregulation of NF-κB transcription factor.

Keywords: HPLC-MS/MS, pomegranate rind, cytotoxicity, MCF-7, ER, caspase-3, NF-kB

Procedia PDF Downloads 106

Authors: Albin Wallace

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Part of the provision within educational institutions is the design, commissioning and implementation of ICT facilities to improve teaching and learning. Inevitably, these facilities focus largely on Internet Protocol (IP) based provisions including access to the World Wide Web, email, interactive software and hardware tools. Educators should be committed to the use of ICT to improve learning and teaching as well as to issues relating to the Internet and educational disadvantage, especially with respect to access and exclusion concerns. In this paper I examine some recent research into the issue of inequality and use of the Internet during which I discuss the causes and consequences of exclusion in the context of social inequality, digital literacy and digital inequality, also touching on issues of global inequality.

Keywords: inequality, internet, education, design

Procedia PDF Downloads 475