Search results for: activity recognition

Authors: Mohamed E. Abdelrahamn, Mahmoud Aly Hassan, Mohamed Sarhan

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Subacromial impingement syndrome (SIS) is a common shoulder disorder. Patients often complain from a decrease in electromyography (EMG) activity of the rotator cuff muscles especially the supraspinatus muscle during glenohumeral elevation. Objective: The purpose of the study is to assess the effect of applying 50% of maximum voluntary contraction of hand grip strength on the EMG activity of the shoulder muscles in patients with SIS. Methods: Thirty male and female patients participated in this study. Their ages ranged from 25 to 40 years. EMG activity of supraspinatus muscle and middle deltoid muscle was assessed without and with applying 50% of maximum voluntary contraction (MVC). Results: A significant difference was found for both supraspinatus and middle deltoid muscles, indicating that the gripping resulted in increasing muscle activity. Conclusion: Applying 50% MVC of hand grip strength could increase the supraspinatus and middle deltoid muscles activity in patients of SIS. This might be useful in the development and monitoring of shoulder rehabilitation strategies.

Keywords: electromyography, supraspinatus muscle, deltoid muscle, subacromial impingement syndrome

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Authors: Reem I. Altamimi, Geoff D. Skinner

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Extended periods engaged in sedentary behavior increases the risk of becoming overweight and/or obese which is linked to other health problems. Adding technology to the term ‘active living’ permits its inclusion in promoting and facilitating habitual physical activity. Technology can either act as a barrier to, or facilitate this lifestyle, depending on the chosen technology. Physical Activity Monitoring Technologies (PAMTs) are a popular example of such technologies. Different contemporary PAMTs have been evaluated based on customer reviews; however, there is a lack of published experimental research into the efficacy of PAMTs. This research aims to investigate the reliability of four PAMTs: two wristbands (Fitbit Flex and Jawbone UP), a waist-clip (Fitbit One), and a mobile application (iPhone Health Application) for recording a specific distance walked on a treadmill (1.5km) at constant speed. Physical activity tracking technologies are varied in their recordings, even while performing the same activity. This research demonstrates that Jawbone UP band recorded the most accurate distance compared to Fitbit One, Fitbit Flex, and iPhone Health Application.

Keywords: Fitbit, jawbone up, mobile tracking applications, physical activity tracking technologies

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Authors: Srinivasarao Kondaparla, Utsab Debnath, Awakash Soni, Vasantha Rao Dola, Manish Sinha, Kumkum Kumkum Srivastava, Sunil K. Puri, Seturam B. Katti

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In a focused exploration, we have designed synthesized and biologically evaluated chiral conjugated new chloroquine (CQ) analogs with substituted piperazines as antimalarial agents. In vitro as well as in vivo studies revealed that compound 7c showed potent activity [for in vitro IC₅₀= 56.98nM (3D7), 97.76nM (K1); for in vivo (up to at the dose of 12.5 mg/kg); SI = 3510] as a new lead of antimalarial agent. Other compounds 6b, 6d, 7d, 7h, 8c, 8d, 9a, and 9c are also showing moderate activity against CQ-sensitive (3D7) strain and superior activity against resistant (K1) strain of P. falciparum. Furthermore, we have carried out docking and 3D-QSAR studies of all in-house data sets (168 molecules) of chiral CQ analogs to explain the structure activity relationships (SAR). Our new findings specified the significance of H-bond interaction with the side chain of heme for biological activity. In addition, the 3D-QSAR study against 3D7 strain indicated the favorable and unfavorable sites of CQ analogs for incorporating steric, hydrophobic and electropositive groups to improve the antimalarial activity.

Keywords: piperazines, CQ-sensitive strain-3D7, in-vitro and in-vivo assay, docking, 3D-QSAR

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Authors: Yong Geun Yun, Jong Hui kim, Sang Ho Baik

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This study was carried out to develop a fermented dandelion (Tarazacum officinale) beverage using lactic acid bacteria with cinnamoyl esterase (CE) activity isolated from human feces. Lactic acid bacteria were screened based on bacterial survival ability in dandelion extract and CE activity. Dandelion extract fermented by Lactobacillus acidophilus F-46 (LA-F46) maintained approximately 105-106 log CFU/mL over an 8 days period. After fermented dandelion beverage (FDB) with LA-46 for 8 days at 37oC the pH was decreased from pH 7.0 to 3.5. Antioxidant activity by using DPPH radical scavenging activity of the prepared FDB was significantly increased compared to that of non-fermented dandelion beverage (NFDB). Moreover, CE activity was significantly enhanced during fermentation and showed the approximately 4.3 times increased concentration of caffeic acid up to 9.91 mg/100 mL after 8 days of incubation compared to NFDB. Therefore, it concluded that dandelion can be a good source for preparing a functional beverage and fermentation by LA-F46 enhanced the food functionality with enhanced caffeic acids.

Keywords: cinnamoyl esterase, dandelion, fermented beverage, lactic acid bacteria

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Authors: Mohamed M. Bumadian, D. James Gilmour

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Three bacterial species were isolated from the River Wye (Derbyshire, England) and identified using 16S rRNA gene sequencing as Serratia proteamaculans, Aeromonas hydrophila and Klebsiella pneumoniae. Respiration rates of the strains were measured in order to determine the metabolic activity under salt stress. The highest respiration rates of all three strains were found at 0.17 M and 0.5 M NaCl and then the respiration rate decreased with increasing concentrations of NaCl. In addition, the effect of increasing concentrations of NaCl on malate dehydrogenase activity was determined using cell-free extracts of the three strains. Malate dehydrogenase activity was stimulated at NaCl concentrations up to 0.5 M, and a small level of activity remained even at 3.5 M NaCl. The pH optimum of the malate dehydrogenase in cell-free extracts of all strains was higher than pH 7.5.

Keywords: fresh water, halotolerant pathogenic bacteria, 16S rRNA gene, cell-free extracts, respiration rates, malate dehydrogenase

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Authors: I. Tulay Cagatay

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Blue-green microalgae cyanobacteria, which are important photosynthetic organisms of aquatic ecosystems, are the primary sources of many bioactive compounds such as proteins, carbohydrates, lipids, vitamins and enzymes that can be used as antimicrobial and antiviral agents. Some of these organisms are nowadays used directly in the food, cosmetic and pharmaceutical industry, or in aquaculture and biotechnological approaches like biofuel or drug therapy. Finding the effective, environmental friendly chemotropic and antimicrobial agents to control fish pathogens are crucial in a country like Turkey which has a production capacity of about 240 thousand tons of cultured fish and has 2377 production farms and which is the second biggest producer in Europe. In our study, we tested the antimicrobial activity of cyanobacterium spp. against some fish pathogens Aeromonas hydrophila and Yersinia ruckeri that are important pathogens for rainbow trout farms. Agar disk diffusion test method was used for studying antimicrobial activity on pathogens. Both tested microorganisms have shown antimicrobial activity positively as the inhibition zones were 0.45 mm and 0.40 mm respectively.

Keywords: fish pathogen, cyanobacteria, antimicrobial activity, trout

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Authors: T. Ould Bellahcen, A. Amiri, I. Touam, F. Hmimid, A. El Amrani, M. Cherki

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The antioxidant activity of three extracts (water, lipidic and ethanolic) prepared from the microalgae Spirulina platensis isolated from Moroccan lake, using 2, 2 diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-azino-bis ethylbenzthiazoline-6-sulfonic acid (ABTS) radical assay, was studied and compared. The obtained results revealed that the IC₅₀ found using DPPH were lower than that of ABTS for all extracts from these planktonic blue-green algae. The high levels of phenolic and flavonoid content were found in the ethanolic extract 0,33 ± 0,01 mg GAE/g dw and 0,21 ± 0,01 mg quercetin/g dw respectively. In addition, using DPPH, the highest activity with IC₅₀ = 0,449 ± 0,083 mg/ml, was found for the ethanolic extract, followed by that of lipidic extract (IC₅₀ = 0,491 ± 0,059 mg/ml). The lowest activity was for the aqueous extract (IC₅₀ = 4,148 ± 0,132 mg/ml). For ABTS, the highest activity was observed for the lipidic extract with IC₅₀ = 0,740 ± 0,012 mg/ml, while, the aqueous extract recorded the lowest activity (IC₅₀ = 6,914 ± 0, 0067 mg/ml). A moderate activity was showed for the ethanolic extract (IC₅₀ = 5,852 ± 0, 0171 mg/ml). It can be concluded from this first study that Spirulina platensis extracts show an interesting antioxidant and antiradicals properties suggesting that this alga could be used as a potential source of antioxidants. A qualitative and quantitative analysis of polyphenol and flavonoids in the extracts using HPLC is in progress so as to study the correlation between the antioxidant activity and chemical composition.

Keywords: Spirulina platensis, antioxidant, DPPH, ABTS

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: M. P. Casiraghi, C. M. Quintella, P. Almeida

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Paraffinic oils were submitted to microbial action. The microorganisms consisted of bacteria of the genera Pseudomonas sp and Bacillus lincheniforms. The alterations in interfacial tension were determined using a tensometer and applying the hanging drop technique at room temperature (299 K ±275 K). The alteration in the constitution of the paraffins was evaluated by means of gas chromatography. The microbial activity was observed to reduce interfacial tension by 54 to 78%, as well as consuming the paraffins C19 to C29 and producing paraffins C36 to C44. The LIFirr technique made it possible to determine the microbial action quickly.

Keywords: paraffins, biosurfactants, LIFirr, microbial activity

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Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Sarekha Woranuch, Rangrong Yoksan

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Chitosan is a derivative of chitin, which is a second most naturally abundant polysaccharide found in crab shells, shrimp shells, and squid pens. The applications of chitosan in pharmaceutical, cosmetics, food and packaging industries have been reported owing to its general recognition as safe, excellent biodegradability and biocompatibility, as well as ability to form films, membranes, gels, beads, fibers and particles. Nevertheless, chitosan is an amino polysaccharide consisting of strong inter- and intramolecular hydrogen bonds which limit its solubility in neutral pH water resulting in restricted utilization. Chemical modification is an alternative way to impede hydrogen bond formation. The objective of the present research is to improve water solubility and antioxidant activity of chitosan by grafting with ferulic acid. Ferulic acid was grafted onto chitosan at the C-2 position via a carbodiimide-mediated coupling reaction. Different mole ratios of chitosan to ferulic acid (i.e. 1.0:0.0, 1.0:0.5, 1.0:1.0, 1.0:1.5, 1.0:2.0, and 1.0:2.5) and various reaction temperatures (i.e. 40, 60, and 80 °C) were used. The reaction was performed at different times (i.e. 1.5, 3.0, 4.5, and 6.0 h). The obtained ferulic acid-grafted chitosan was characterized by FTIR and 1H NMR technique. The influences of ferulic acid on crystallinity, solubility and radical scavenging activity of chitosan were also investigated. Ferulic acid grafted chitosan was successfully synthesized as confirmed from (i) the appearance of FTIR absorption band at 1517 cm-1 belonging to C=C aromatic ring of ferulic acid and the increased C–H stretching band intensity and (ii) the appearance of proton signals at δ = 6.31-7.67 ppm ascribing to methine protons of ferulic acid. The condition in which the reaction temperature of 60°C, reaction time of 3 h and the mole ratio of chitosan to ferulic acid of 1:1 gave the highest ferulic acid substitution degree, i.e. 0.37. The resulting ferulic acid grafted chitosan was soluble in water (1.3 mg/mL) due to its reduced crystallinity as compared with chitosan and also exhibited 90% greater radical scavenging activity than chitosan. The result suggested the utilization of ferulic acid grafted chitosan as an antioxidant material.

Keywords: antioxidant property, chitosan, ferulic acid, grafting

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Authors: N. Saki, S. Nalbantoglu, M. Akin, G. Arabaci

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Walnut has a great range of phenolic profile and it is used in Asia and Africa for treatment of many diseases and cancer. Phenolic compounds play a number of crucial roles in complex metabolism of plants and of also fruit trees. Consumption of certain phenolics in the food is considered beneficial for human nutrition. Phenolic compounds known as anti-radical inactivators with their high antioxidant activities and these activities play an important role in inhibition of multi-metal corrosion. Many common corrosion inhibitors that are still in use today are health hazards. Therefore, there is still an increased attention directed towards the development of environmentally compatible, nonpolluting corrosion inhibitors. The present study reports the total phenols content, antioxidant potentials and tyrosinase inhibitory activity of the walnut (Juglans regia L.) produced in Turkey. The anti-tyrosinase activity was investigated for walnut at 2 h extraction time and all extracts exhibited tyrosinase activity. The results of this study suggested that walnut can be used as an excellent, easily accessible source of natural antioxidant.

Keywords: antioxidant activity, Juglans Regia, total phenols, tyrosinase activity

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Authors: L. Mallesha, P. Mallu, B. Veeresh

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In the present study, 2, 6-diflurobenzohydrazide and 4-fluorophenylisothiocyanate were used as the starting materials to synthesize 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3, 4-diamine. Further, compound 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3,4-diamine reacted with fluoro substituted benzaldehydes to yield a series of Schiff bases. All the final compounds were characterized using IR, 1H NMR, 13C NMR, MS and elemental analyses. New compounds were evaluated for their antiproliferative effect using the MTT assay method against four human cancer cell lines (K562, COLO-205, MDA-MB231, and IMR-32) for the time period of 24 h. Among the series, few compounds showed good activity on all cell lines, whereas the other compounds in the series exhibited moderate activity.

Keywords: Schiff bases, MTT assay, antiproliferative activity, human cancer cell lines, 1, 2, 4-triazoles

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Authors: Mekhaldi Abdelkader, Bouzned Ahcen, Djibaoui Rachid, Hamoum Hakim

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This study presents an attempt to evaluate the antioxidant and antimicrobial activity of methanolic extract and essential oils prepared from the leaves of sage (Salvia officinalis L.). The content of polyphenols in the methanolic extract of the leaves from Salvia officinalis extract was determined by spectrophoto- metrically, calculated as gallic acid and catechin equivalent. Antioxidant activity was evaluated by free radical scavenging activity using 2,2-diphenylpicryl-1-picrylhydrazyl (DPPH) assay. The plant essential oil and methanol extract were also subjected to screenings for the evaluation of their antioxidant activities using 2, 2-diphenyl-1-picrylhydrazyl (DPPH) test. While the plant essential oil showed only weak antioxidant activities, its methanol extract was considerably active in DPPH (IC50= 37.29µg/ml) test. Appreciable total phenolic content (31.25mg/g) was also detected for the plant methanol extract as gallic acid equivalent in the Folin–Ciocalteu test. The plant was also screened for its antimicrobial activity and good to moderate inhibitions were recorded for its essential oil and methanol extract against most of the tested microorganisms. The present investigation revealed that this plant has rich source of antioxidant properties. It is for this reason that sage has found increasing application in food formulations.

Keywords: antibacterial activity, antioxidant activity, flavonoid, polyphenol, salvia officinalis

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Reza Shakoori

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This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.

Keywords: Arabic, chain code normalization, OCR systems, image processing

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Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor

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Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.

Keywords: additive parameter, angular softmax, speaker verification, PLDA

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Authors: Belgheis Ebrahimi, Jun Lu

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In recent years, there has been a growing recognition of the potential of marine-based functional foods and combination therapies in promoting a healthy lifestyle and exploring their effectiveness in preventing or treating diseases. The combination of marine bioactive compounds or extracts offers synergistic or enhancement effects through various mechanisms, including multi-target actions, improved bioavailability, enhanced bioactivity, and mitigation of potential adverse effects. Both the green-lipped mussel (GLM) and fucoidan derived from brown seaweed are rich in bioactivities. These two, mussel and fucoidan, have not been previously formulated together. This study aims to combine GLM oil from Perna canaliculus with low molecular weight fucoidan (LMWF) extracted from Undaria pinnatifida to investigate the unique mixture’s anti-inflammatory and antioxidant properties. The cytotoxicity of individual compounds and combinations was assessed using the MTT assay in (THP-1 and RAW264.7) cell lines. The anti-inflammatory activity of mussel-fucoidan was evaluated by treating LPS-stimulated human monocyte and macrophage (THP1-1) cells. Subsequently, the inflammatory cytokines released into the supernatant of these cell lines were quantified via ELISA. Antioxidant activity was determined by using the free radical scavenging assay (DPPH). DPPH assay demonstrated that the radical scavenging activity of the combinations, particularly at concentrations exceeding 1 mg/ml, showed a significantly higher percentage of inhibition when compared to the individual component. This suggests an enhancement effect when the two compounds are combined, leading to increased antioxidant activity. In terms of immunomodulatory activity, the individual compounds exhibited distinct behaviors. GLM oil displayed a higher ability to suppress the cytokine TNF- compared to LMWF. Interestingly, the LMWF fraction, when used individually, did not demonstrate TNF- suppression. However, when combined with GLM, the TNF- suppression (anti-inflammatory) activity of the combination was better than GLM or LWMF alone. This observation underscores the potential for enhancement interactions between the two components in terms of anti-inflammatory properties. This study revealed that each individual compound, LMWF, and GLM, possesses unique and notable bioactivity. The combination of these two individual compounds results in an enhancement effect, where the bioactivity of each is enhanced, creating a superior combination. This suggests that the combination of LMWF and GLM has the potential to offer a more potent and multifaceted therapeutic effect, particularly in the context of antioxidant and anti-inflammatory activities. These findings hold promise for the development of novel therapeutic interventions or supplements that harness the enhancement effects.

Keywords: combination, enhancement effect, perna canaliculus, undaria pinnatifida

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Authors: Renee P. Baang, Romeo M. del Rosario, Nenita D. Palmes

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The crude methanol extracts of five indigenous vegetables namely, Amarathus tricolor, Basella rubra L, Chochurus olitorius L., Ipomea batatas, and Momordica chuchinensis L., were examined for their phytochemical profile and antioxidant activity using 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical. The values for DPPH radical scavenging activity ranged from 7.6-89.53% with B. rubra and I. batatas having the lowest and highest values, respectively. The total flavonoid content of all five indigenous vegetables ranged from 74.65-277.3 mg quercetin equivalent per gram of dried vegetable material while the total phenolic content ranged from 1.93-6.15 mg gallic acid equivalent per gram dried material. Phytochemical screening revealed the presence of steroids, flavonoids, saponins, tannins, carbohydrates and reducing sugars, which may also be associated with the antioxidant activity shown by these indigenous vegetables.

Keywords: antioxidant, DPPH radical scavenging activity, Philippine İndigenous vegetables, phytochemical screening

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Authors: Han Xue, Zhang Lanyue

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In order to seek more effective feature extraction technology, feature extraction method based on MFCC combined with vector hydrophone is exposed in the paper. The sound pressure signal and particle velocity signal of two kinds of ships are extracted by using MFCC and its evolution form, and the extracted features are fused by using fisher-ratio and correlated distance criterion. The features are then identified by BP neural network. The results showed that MFCC, First-Order Differential MFCC and Second-Order Differential MFCC features can be used as effective features for recognition of underwater targets, and the fusion feature can improve the recognition rate. Moreover, the results also showed that the recognition rate of the particle velocity signal is higher than that of the sound pressure signal, and it reflects the superiority of vector signal processing.

Keywords: vector information, MFCC, differential MFCC, fusion feature, BP neural network

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Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

Abstract:

Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

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Authors: Keerthie Dissanayake, Chandrika Jayasinghe, Priyani Wanigasekara, Jayampathy Dissanayake, Ajith Sominanda

Abstract:

The routine use of Disease Activity Score-28 (DAS28) to assess the disease activity in rheumatoid arthritis (RA) is limited due to its dependency on laboratory investigations and the complex calculations involved. In contrast, the clinical disease activity index (CDAI) is simple to calculate, which makes the "treat to target" strategy for the management of RA more practical. We aimed to assess the validity of CDAI compared to DAS28 in RA patients in Sri Lanka. A total of 103 newly diagnosed RA patients were recruited, and their disease activity was calculated using DAS 28 and CDAI during the first visit to the clinic (0 months) and re-assessed at 4 and 9 months of the follow-up visits. The validity of the CDAI, compared to DAS 28, was evaluated. Patients had a female preponderance (6:1) and a short symptom duration (mean = 6.33 months). The construct validity of CDAI, as assessed by Cronbach's α test, was 0.868. Convergent validity was assessed by correlation and Kappa statistics. Strong positive correlations were observed between CDAI and DAS 28 at the baseline (0 months), 4, and 9 months of evaluation (Spearman's r = 0.9357, 0.9354, 0.9106, respectively). Moderate-good inter-rater agreements between the DAS-28 and CDAI were observed (Weighted kappa of 0.660, 0.519, and 0.741 at 0, 4, and 9 months respectively). Discriminant validity, as assessed by ROC curves at 0, 4th, and 9th months of the evaluation, showed the area under the curve (AUC) of 0.958, 0.985, and 0.914, respectively. The suggested cut-off points for different CDAI disease activity categories according to ROC curves were ≤ 2 (Remission), >2 to ≤ 5 (low), >5 to ≤ 18 (moderate), > 18 (high). These findings indicate that the CDAI has good concordance with DAS 28 in assessing the disease activity in RA patients in this study sample.

Keywords: rheumatoid arthritis, CDAI, disease activity, Sri Lanka, validation

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Authors: Jitpisute Chunthorng-Orn, Thana Juckmeta, Onmanee Prajuabjinda, Arunporn Itharat

Abstract:

Inflammation and oxidative stress work together to produce symptoms in cancer patients. The whole part of it is used as a preparation to treat cancer patients in Khampramong temple which has been a place of treatment and palliative care for cancer patients since 2005. Thus, the objective of this study was to investigate anti-inflammatory and antioxidant activities of Heliotropium indicum extracts. Dried plant materials were extracted in a similar manner to those practiced by the Khampramong Temple i.e. maceration in 95% ethanol and boiling in water. For anti-inflammation activity, both extracts were tested for suppression of nitric oxide (NO) production in LPS-induced RAW 264.7 cells. They were also tested for antioxidant activity by DPPH radical scavenging assay. This study found that the ethanolic extract of Heliotropium indicum exhibited higher inhibitory activity of NO release than Indomethacin as a positive control (IC50 value of 24.17±2.12 and 34.67±6.23 μg/mL, respectively). For DPPH radical scavenging assay, the ethanolic extract also exhibited antioxidant activity but less than BHT as a antioxidant compound (EC50 values = 28.91±4.26 and 13.08±0.29 μg/mL, respectively). In contrast, its water extract had no inhibitory activity on NO release (IC50 > 100 μg/mL) and no inhibitory activity on DPPH radicals (EC50 values > 100 μg/mL). The results showed correlation between anti-inflammation and antioxidant activity and these results also support using this plant to treat cancer patients.

Keywords: Heliotropium indicum, RAW 264.7, DPPH, Khampramong Temple

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Authors: Desta Gebretekle Shiferaw, Balakrishna Kalluraya

Abstract:

Oxadiazoles and their derivatives with thioether functionalities represent a new and exciting class of physiologically active heterocyclic compounds. Several molecules with these moieties play a vital role in pharmaceuticals because of their diverse biological activities. This paper describes a new class of 1,3,4- oxadiazole-2-thioethers with acetophenone, coumarin, and N-phenyl acetamide residues (S-alkylation), with the hope that the addition of various biologically active molecules will have a synergistic effect on anticancer activity. The structure of the synthesized title compounds was determined by the combined methods of IR, proton-NMR, carbon-13-NMR, and mass spectrometry. Further, all the newly prepared molecules were assessed against their antioxidant activity. Furthermore, four compounds were assessed for their molecular docking interactions and cytotoxicity activity. The synthesized derivatives have shown moderate antioxidant activity compared to the standard BHA. The IC50 of the tilted molecules (11b, 11c, 13b, and 14b) observed for in vitro anti-cancer activities were 11.20, 15.73, 59.61, and 27.66 g/ml at 72-hour treatment time against the A549 cell lines, respectively. The tested compounds' biological evaluation showed that 11b is the most effective molecule in the series.

Keywords: antioxidant activity, cytotoxicity activity, molecular docking, 1, 3, 4-Oxadiazole-2 thioether derivatives

Procedia PDF Downloads 67