Search results for: finger vein recognition

Authors: Venugopal Kummamuru

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Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.

Keywords: corporate governance, corporate responsibility, direct selling, network marketing

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Authors: Mohamed Hefnawy, Abdulrahman Al-Majed, Aymen Al-Suwailem

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Enantioseparation of drugs with multiple stereogenic centers is challenging. This study objectives to evaluate the efficiency of different mobilized and/or immobilized polysaccharide-based chiral stationary phases to separate enantiomers of some drugs containing multiple stereogenic centers namely indenolol, nadolol, labetalol. The critical mobile phase variables (composition of organic solvents, acid/base ratios) were carefully studied to compare the retention time and elution order of all isomers. Different chromatographic parameters such as capacity factor (k), selectivity (α) and resolution (Rs) were calculated. Experimental conditions and the possible chiral recognition mechanisms have been discussed.

Keywords: HPLC, polysaccharide columns, enantio-resolution, indenolol, nadolol, labetalol

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Authors: Rachael Collins, George Lafford

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We report a case of a generally fit and a well 54-year-old gentleman who presented with a two-day history of worsening left-sided otorrhea, headache, neck stiffness, vomiting and pyrexia on the background of a seven-week history of OE. His condition progressed dramatically as he developed symptoms consistent with acute complete cervical cord syndrome with radiological evidence of skull base osteomyelitis, parapharyngeal, retropharyngeal and paravertebral abscesses and sigmoid sinus thrombus. Ultimately he made a significant, although not complete, recovery. This case is unique in demonstrating how OE can develop into a potentially life-threatening condition. It emphasizes the importance of early diagnosis and treatment of OE, the recognition of ‘red flag’ symptoms and highlights the importance of a multi-disciplinary team (MDT) approach when managing complex complications of OE.

Keywords: ENT, neurology, otology, MDT

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Authors: Ioanna Taouki, Marie Lallier, David Soto

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Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Jithin S. Kumar, Ramesh Kannan Kandasami

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Geomaterials are generally porous in nature due to the presence of discrete particles and interconnected voids. The porosity present in these geomaterials play a critical role in many engineering applications such as CO2 sequestration, well bore strengthening, enhanced oil and hydrocarbon recovery, hydraulic fracturing, and subsurface waste storage. These applications involves solid-fluid interactions, which govern the changes in the porosity which in turn affect the permeability and stiffness of the medium. Injecting fluid into the geomaterials results in permeation which exhibits small or negligible deformation of the soil skeleton followed by cavity expansion/ fingering/ fracturing (different forms of instabilities) due to the large deformation especially when the flow rate is greater than the ability of the medium to permeate the fluid. The complexity of this problem increases as the geomaterial behaves like a solid and fluid under certain conditions. Thus it is important to understand this multiphysics problem where in addition to the permeation, the elastic-plastic deformation of the soil skeleton plays a vital role during fluid injection. The phenomenon of permeation and cavity expansion in porous medium has been studied independently through extensive experimental and analytical/ numerical models. The analytical models generally use Darcy's/ diffusion equations to capture the fluid flow during permeation while elastic-plastic (Mohr-Coulomb and Modified Cam-Clay) models were used to predict the solid deformations. Hitherto, the research generally focused on modelling cavity expansion without considering the effect of injected fluid coming into the medium. Very few studies have considered the effect of injected fluid on the deformation of soil skeleton. However, the porosity changes during the fluid injection and coupled elastic-plastic deformation are not clearly understood. In this study, the phenomenon of permeation and instabilities such as cavity and finger/ fracture formation will be quantified extensively by performing experiments using a novel experimental setup in addition to utilizing image processing techniques. This experimental study will describe the fluid flow and soil deformation characteristics under different boundary conditions. Further, a well refined coupled semi-analytical model will be developed to capture the physics involved in quantifying the deformation behaviour of geomaterial during fluid injection.

Keywords: solid-fluid interaction, permeation, poroelasticity, plasticity, continuum model

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Authors: Mitesh Rathod, Jungho Ahn, Noo Li Jeon, Junghoon Lee

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Endothelial cells respond to cues from both biochemical as well as micro mechanical environment. Significant effort has been directed to understand the effects of biochemical signaling, however, relatively little is known about regulation of endothelial cell biology by the micro mechanical environment. Numerous studies have been performed to understand how physical forces regulate endothelial cell behavior. In this regard, past studies have majorly focused on exploring how fluid shear stress governs endothelial cell behavior. Parallel plate flow chambers and rectangular microchannels are routinely employed for applying fluid shear force on endothelial cells. However, these studies fall short in mimicking the in vivo like micro environment from topological aspects. Few studies have only used circular microchannels to replicate in vivo like condition. Seldom efforts have been directed to elucidate the combined effect of topology, substrate rigidity and fluid shear stress on endothelial cell response. In this regard, we demonstrate a facile fabrication process to develop a hybrid polydimethylsiloxane microfluidic platform to study endothelial cell biology. On a single chip microchannels with different cross sections i.e., circular, rectangular and square have been fabricated. In addition, our fabrication approach allows variation in the substrate rigidity along the channel length. Two different variants of polydimethylsiloxane, namely Sylgard 184 and Sylgard 527, were utilized to achieve the variation in rigidity. Moreover, our approach also enables in creating Y bifurcation circular microchannels. Our microfluidic platform thus facilitates for conducting studies pertaining to endothelial cell morphology with respect to change in topology, substrate rigidity and fluid flow on a single chip. The hybrid platform was tested by culturing Human Umbilical Vein Endothelial Cells in circular microchannels with varying substrate rigidity, and exposed to fluid shear stress of 12 dynes/cm² and static conditions. Results indicate the cell area response to flow induced shear stress was governed by the underlying substrate mechanics.

Keywords: hybrid, microfluidic platform, PDMS, shear flow, substrate rigidity

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Authors: Chantell Gouws, Lourens Millard, Anne Naude, Jan-Wessel Meyer, Brandon Stuwart Shaw, Ina Shaw

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Background: Millions of South African youths participate in team sports, with netball and rugby being two of the largest worldwide. This increased participation and professionalism have resulted in an increase in the number of musculoskeletal injuries. Objective: This study examined the extent to which sport coaching knowledge translates to the injuries and prevention of injuries in adolescents participating in netball and rugby. Methods: Thirty-four South African sports coaches participated in the study. Eighteen netball coaches and 16 rugby coaches with varying levels of coaching experience were selected to participate. An adapted version of Nash and Sproule’s questionnaire was used to investigate the coaches’ knowledge with regards to sport-specific common injuries, injury prevention, fitness/conditioning, individual technique development, training programs, mental training, and preparation of players. The analysis of data was carried out using a number of different techniques outlined by Nash and Sproule (2012). These techniques were determined by the type of data. Descriptive data was used to provide statistical analysis. Quantitative data was used to determine the educational framework and knowledge of sports coaches on injury prevention. Numerical data was obtained through questions on sports injuries, as well as coaches’ sports knowledge levels. Participants’ knowledge was measured using a standardized scoring system. Results: For the 0-4 years of netball coaching experience, 76.4% of the coaches had knowledge and experience and 33.3% appropriate first aid knowledge, while for the 9-12 years and 13-16 years, 100% of the coaches had knowledge and experience and first aid knowledge. For the 0-4 years in rugby coaching experience, 59.1% had knowledge and experience and 71% the appropriate first aid knowledge; for the 17-20 years, 100% had knowledge and experience and first aid, while for higher or equal to 25 years, 45.5% had knowledge and experience. In netball, 90% of injuries consisted of ankle injuries, followed by 70% for knee, 50% for shoulder, 20% for lower leg, and 15% for finger injuries. In rugby, 81% of the injuries occurred at the knee, followed by 50% for the shoulder, 40% for the ankle, 31% for the head and neck, and 25% for hamstring injuries. Six hours of training resulted in a 13% chance of injuries in netball and a 32% chance in rugby. For 10 hours of training, the injury prevalence was 10% in netball and 17% in rugby, while 15 hours resulted in an injury incidence of 58% in netball players and a 25% chance in rugby players. Conclusion: This study highlights the need for coaches to improve their knowledge in relation to injuries and injury prevention, along with factors that act as a preventative measure and promotes players’ well-being.

Keywords: musculoskeletal injury, sport coaching, sport trauma

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Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

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Authors: Pavana Basavakumar, Devadas Bhat

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Diabetes is a disease which often goes undiagnosed until its secondary effects are noticed. Early detection of the disease is necessary to avoid serious consequences which could lead to the death of the patient. Conventional invasive tests for screening of diabetes are mostly painful, time consuming and expensive. There’s also a risk of infection involved, therefore it is very essential to develop non-invasive methods to screen and estimate the level of blood glucose. Extensive research is going on with this perspective, involving various techniques that explore optical, electrical, chemical and thermal properties of the human body that directly or indirectly depend on the blood glucose concentration. Thus, non-invasive blood glucose monitoring has grown into a vast field of research. In this project, an attempt was made to device a prototype for screening of diabetes by measuring electrical impedance of the skin and building a model to predict a patient’s condition based on the measured impedance. The prototype developed, passes a negligible amount of constant current (0.5mA) across a subject’s index finger through tetra polar silver electrodes and measures output voltage across a wide range of frequencies (10 KHz – 4 MHz). The measured voltage is proportional to the impedance of the skin. The impedance was acquired in real-time for further analysis. Study was conducted on over 75 subjects with permission from the institutional ethics committee, along with impedance, subject’s blood glucose values were also noted, using conventional method. Nonlinear regression analysis was performed on the features extracted from the impedance data to obtain a model that predicts blood glucose values for a given set of features. When the predicted data was depicted on Clarke’s Error Grid, only 58% of the values predicted were clinically acceptable. Since the objective of the project was to screen diabetes and not actual estimation of blood glucose, the data was classified into three classes ‘NORMAL FASTING’,’NORMAL POSTPRANDIAL’ and ‘HIGH’ using linear Support Vector Machine (SVM). Classification accuracy obtained was 91.4%. The developed prototype was economical, fast and pain free. Thus, it can be used for mass screening of diabetes.

Keywords: Clarke’s error grid, electrical impedance of skin, linear SVM, nonlinear regression, non-invasive blood glucose monitoring, screening device for diabetes

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Authors: Fatemeh Zeinali Sehrig

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This study aimed to evaluate the expression of miR-299-3p, DNMT1, DNMT3A, and DNMT3B in breast cancer samples and investigate their diagnostic significance. Using the GSE40525 and GSE45666, the miR-299-3p expression level was studied in breast cancer tissues. Also, the expression levels of DNMT1, DNMT3A, and DNMT3B were investigated by analyzing GSE61725, GSE86374, and GSE37751 datasets. The target genes were studied in terms of biological processes of molecular functions and cellular components. Consistent with the in silico results, miR-299-3p expression was substantially decreased in breast cancer tissues, and the expression levels of DNMT1, DNMT3A, and DNMT3B were considerably upregulated in breast cancer samples. It was found that the expression levels of miR-299-3p and DNMT1, DNMT3A, and DNMT3B could be valuable diagnostic tools for detecting breast cancer. Also, miR-299-3p downregulation may play a role in DNMT1, DNMT3A, and DNMT3B upregulation in breast cancer.

Keywords: breast cancer, miR-299-3p, DNMTs, GEO database

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis

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Authors: Carmen Noheda

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This text provides a reflection on the way of thinking about the study of the history of music by examining the production of historiography in Spain at the turn of the century. Based on concepts developed by the historical theorist Jörn Rüsen, the article focuses on the following aspects: the theoretical artifacts that structure the interpretation of the limits of writing the history of music, the narrative patterns used to give meaning to the discourse of history, and the orientation context that functions as a source of criteria of significance for both interpretation and representation. This analysis intends to show that historical music theory is not only a means to abstractly explore the complex questions connected to the production of historical knowledge, but also a tool for obtaining concrete images about the intellectual practice of professional musicologists. Writing about the historiography of contemporary Spanish music is a task that requires both a knowledge of the history that is being written and investigated, as well as a familiarity with current theoretical trends and methodologies that allow for the recognition and definition of the different tendencies that have arisen in recent decades. With the objective of carrying out these premises, this project takes as its point of departure the 'immediate historiography' in relation to Spanish music at the beginning of the 21st century. The hesitation that Spanish musicology has shown in opening itself to new anthropological and sociological approaches, along with its rigidity in the face of the multiple shifts in dynamic forms of thinking about history, have produced a standstill whose consequences can be seen in the delayed reception of the historiographical revolutions that have emerged in the last century. Methodologically, this essay is underpinned by Rüsen’s notion of the disciplinary matrix, which is an important contribution to the understanding of historiography. Combined with his parallel conception of differing paradigms of historiography, it is useful for analyzing the present-day forms of thinking about the history of music. Following these theories, the article will in the first place address the characteristics and identification of present historiographical currents in Spanish musicology to thereby carry out an analysis based on the theories of Rüsen. Finally, it will establish some considerations for the future of musical historiography, whose atrophy has not only fostered the maintenance of an ingrained positivist tradition, but has also implied, in the case of Spain, an absence of methodological schools and an insufficient participation in international theoretical debates. An update of fundamental concepts has become necessary in order to understand that thinking historically about music demands that we remember that subjects are always linked by reciprocal interdependencies that structure and define what it is possible to create. In this sense, the fundamental aim of this research departs from the recognition that the history of music is embedded in the conditions that make it conceivable, communicable and comprehensible within a society.

Keywords: historiography, Jörn Rüssen, Spanish musicology, theory of history of music

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Authors: Katsumi Hirata

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To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position

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Authors: Mark Omu

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Education has remained the greatest fulcrum on which the developmental aspirations of societies and the world over is Anchored. This has been the case from the antiquity. As a result of recognition of this fact, education occupies a crucial and centripetal position at different epochs of societal formation and transformation. This paper recognized the all-embracing role of education to society and it utilized the literary research and review of literature to espouse on the role of alternative sources of financing education. This position was borne out of the dwindling resources available to education. Especially to finance teaching, learning, research and retraining of staffers. This paper found among other things that alternative funding of education is possible and it can be achieved through selling of its research products like entrepreneurial skills, collaborative ventures in public private partnership, philanthropic of endowments, etc. These are capable of bridging the financial gap currently bedevilling the educational sectors.

Keywords: alternative sources, funding, tertiary, education, society, partnership, Nigeria

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Authors: Fernando Cabo Aseguinolaza, Víctor Bouzas Blanco, Alberto Martí Ezpeleta

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Santiago de Compostela became a stable object of literary representation during the period between 1840 and 1915, approximately. This study offers a partial cartographical look at this process, suggesting that a cultural space like Compostela’s becoming an object of literary representation paralleled the first stages of its becoming a tourist destination. We use maps as a method of analysis to show the interaction between a corpus of novels and the emerging tradition of tourist guides on Compostela during the selected period. Often, the novels constitute ways to present a city to the outside, marking it for the gaze of others, as guidebooks do. That leads us to examine the ways of constructing and rendering communicable the local in other contexts. For that matter, we should also acknowledge the fact that a good number of the narratives in the corpus evoke the representation of the city through the figure of one who comes from elsewhere: a traveler, a student or a professor. The guidebooks coincide in this with the emerging fiction, of which the mimesis of a city is a key characteristic. The local cannot define itself except through a process of symbolic negotiation, in which recognition and self-recognition play important roles. Cartography shows some of the forms that these processes of symbolic representation take through the treatment of space. The research uses GIS to find significant models of representation. We used the program ArcGIS for the mapping, defining the databases starting from an adapted version of the methodology applied by Barbara Piatti and Lorenz Hurni’s team at the University of Zurich. First, we designed maps that emphasize the peripheral position of Compostela from a historical and institutional perspective using elements found in the texts of our corpus (novels and tourist guides). Second, other maps delve into the parallels between recurring techniques in the fictional texts and characteristic devices of the guidebooks (sketching itineraries and the selection of zones and indexicalization), like a foreigner’s visit guided by someone who knows the city or the description of one’s first entrance into the city’s premises. Last, we offer a cartography that demonstrates the connection between the best known of the novels in our corpus (Alejandro Pérez Lugín’s 1915 novel La casa de la Troya) and the first attempt to create package tourist tours with Galicia as a destination, in a joint venture of Galician and British business owners, in the years immediately preceding the Great War. Literary cartography becomes a crucial instrument for digging deeply into the methods of cultural production of places. Through maps, the interaction between discursive forms seemingly so far removed from each other as novels and tourist guides becomes obvious and suggests the need to go deeper into a complex process through which a city like Compostela becomes visible on the contemporary cultural horizon.

Keywords: compostela, literary geography, literary cartography, tourism

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Nuruddin Mohammod Zahangir, Syed Tanvir Ahmady, Firoz Ahmed, Mainul Kabir, Tamjid Mohammad Najmus Sakib Khan, Nazmul Hossain, Niaz Ahmed, Madhava Janardhan Naik

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The management of combined Coronary Artery Disease and Peripheral Vascular Disease is a challenge and brings with it numerous clinical dilemmas.The 56 year old gentleman presented to our department with significant triple vessel disease with occluded lower end of aorta just before bifurcation and bilateral superficial femoral arteries. Operation was done on 11.03.14. The The Left Internal Mammary Artery (LIMA) and the Right Internal Mammary Artery (RIMA) were harvested in skeletonized manner. The free RIMA was then anastomosed with LIMA to make LIMA-RIMA Y. Cardio Pulmonary Bypass was then established and coronary artery bypass grafts performed. LIMA was anastomosed to the Left Anterior Descending artery. RIMA was anastomosed to Posterior Descending Artery, 1st and 2nd Obtuse Marginal arteries in a sequential manner. Abdomen was opened by midline incision. The infrarenal aorta exposed and was found to be severely diseased. A Vascular Clamp was applied infrarenally, aortotomy done and limited endarterectomy performed. An end-to-side anastomosis was done with upper end of PTFE synthetic Y-graft (14/7 mm) to the infarenal Aorta and the Clamp released. Good flow noted in both limbs of the graft. Patient was then slowly weaned off from Cardio Pulmonary Bypass without difficulty. The distal two limbs of the Y graft were passed to the groin through retroperitoneal tunnels and anastomosed end-to-side with the common femoral arteries. Saphenous vein was interposed between common femoral and popliteal arteries bilaterally through subfascial tunnels in both thigh. On 12th postoperative day he was discharged from hospital in good general condition. Follow up after 3 months of operation the patient is doing good and free of chest pain and claudication pain.

Keywords: total arterial, coronary revascularization, aorto-bifemoral bypass, bifemoro-bipopliteal bypass

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Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

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Authors: Leila Safazadeh, Brad Berron

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Self-assembled monolayers have tremendous impact in interfacial science, due to the unique opportunity they offer to tailor surface properties. Low-density self-assembled monolayers are an emerging class of monolayers where the environment-interfacing portion of the adsorbate has a greater level of conformational freedom when compared to traditional monolayer chemistries. This greater range of motion and increased spacing between surface-bound molecules offers new opportunities in tailoring adsorption phenomena in sensing systems. In particular, we expect low-density surfaces to offer a unique opportunity to intercalate surface bound ligands into the secondary structure of protiens and other macromolecules. Additionally, as many conventional sensing surfaces are built upon gold surfaces (SPR or QCM), these surfaces must be compatible with gold substrates. Here, we present the first stable method of generating low-density self assembled monolayer surfaces on gold for the analysis of their interactions with protein targets. Our approach is based on the 2:1 addition of thiol-yne chemistry to develop new classes of y-shaped adsorbates on gold, where the environment-interfacing group is spaced laterally from neighboring chemical groups. This technique involves an initial deposition of a crystalline monolayer of 1,10 decanedithiol on the gold substrate, followed by grafting of a low-packed monolayer on through a photoinitiated thiol-yne reaction in presence of light. Orthogonality of the thiol-yne chemistry (commonly referred to as a click chemistry) allows for preparation of low-density monolayers with variety of functional groups. To date, carboxyl, amine, alcohol, and alkyl terminated monolayers have been prepared using this core technology. Results from surface characterization techniques such as FTIR, contact angle goniometry and electrochemical impedance spectroscopy confirm the proposed low chain-chain interactions of the environment interfacing groups. Reductive desorption measurements suggest a higher stability for the click-LDMs compared to traditional SAMs, along with the equivalent packing density at the substrate interface, which confirms the proposed stability of the monolayer-gold interface. In addition, contact angle measurements change in the presence of an applied potential, supporting our description of a surface structure which allows the alkyl chains to freely orient themselves in response to different environments. We are studying the differences in protein adsorption phenomena between well packed and our loosely packed surfaces, and we expect this data will be ready to present at the GRC meeting. This work aims to contribute biotechnology science in the following manner: Molecularly imprinted polymers are a promising recognition mode with several advantages over natural antibodies in the recognition of small molecules. However, because of their bulk polymer structure, they are poorly suited for the rapid diffusion desired for recognition of proteins and other macromolecules. Molecularly imprinted monolayers are an emerging class of materials where the surface is imprinted, and there is not a bulk material to impede mass transfer. Further, the short distance between the binding site and the signal transduction material improves many modes of detection. My dissertation project is to develop a new chemistry for protein-imprinted self-assembled monolayers on gold, for incorporation into SPR sensors. Our unique contribution is the spatial imprinting of not only physical cues (seen in current imprinted monolayer techniques), but to also incorporate complementary chemical cues. This is accomplished through a photo-click grafting of preassembled ligands around a protein template. This conference is important for my development as a graduate student to broaden my appreciation of the sensor development beyond surface chemistry.

Keywords: low-density self-assembled monolayers, thiol-yne click reaction, molecular imprinting

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Samane Eftekhari Ranjbar

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Diabetes mellitus, a metabolic disorder characterized by elevated blood glucose levels, ranks among the leading causes of adult mortality. This study investigates the impact of an eight-week high-intensity interval training (HIIT) program combined with sodium nitrite supplementation on TNF- α, MURF1, and PI3K in a type 2 diabetes rodent model. Elevated TNF-α levels have been associated with insulin resistance, while MURF1 and PI3K play roles in muscle atrophy and insulin signaling pathways, respectively. In this experimental study, 15 eight-week-old rats from the Sara Laboratory Center in Tabriz were assigned to one of five groups: healthy control, diabetic control, diabetic with sodium nitrite supplementation, diabetic with eight weeks of intermittent exercise, and diabetic with eight weeks of interval training plus sodium nitrite supplementation. The HIIT protocol was designed to span eight weeks, with five weekly sessions at specified intensities and durations. Sodium nitrite, known for its vasodilatory and cytoprotective properties, was administered via injection. The findings revealed that the HIIT program and sodium nitrite supplementation influenced the examined biomarkers. ANOVA test outcomes indicated statistically significant differences in TNF- α (P=0.001), MURF1 (P=0.001), and PI3K (P=0.001) concentrations among the various groups. The healthy control group exhibited substantially decreased TNF- α, and MURF1 levels, as well as elevated PI3K levels compared to the diabetic control group. The exercise group, in conjunction with sodium nitrite supplementation, demonstrated a significant rise in PI3K levels (P=0.001) and a decline in TNF- α levels (P=0.018) relative to the diabetic control group. These results suggest that the combined intervention may help improve insulin sensitivity and reduce inflammation. However, MURF1 levels, which are related to muscle atrophy, showed no significant difference (P=0.24). In conclusion, in type 2 diabetic rats, an eight-week high-intensity interval training program with sodium nitrite supplementation does not affect MURF1 levels but does influence PI3K and TNF- α levels. This combination may hold potential for improving insulin sensitivity and reducing inflammation in type 2 diabetes patients, warranting further investigation and potential translation to human clinical trials.

Keywords: high-intensity interval training, sodium nitrate supplementation, type 2 diabetes, tumor necrosis factor-alpha, phosphatidylinositol-3-kinase, muscle RING-finger protein-1

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Authors: Roman Matejka, Vaclav Prochazka, Tibor Izak, Jana Stepanovska, Martina Travnickova, Alexander Kromka

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Cell-based impedance spectroscopy is suitable method for electrical monitoring of cell activity especially on substrates that cannot be easily inspected by optical microscope (without fluorescent markers) like decellularized tissues, nano-fibrous scaffold etc. Special sensor for this measurement was developed. This sensor consists of corning glass substrate with gold interdigitated electrodes covered with diamond layer. This diamond layer provides biocompatible non-conductive surface for cells. Also, a special PPFC flow cultivation chamber was developed. This chamber is able to fix sensor in place. The spring contacts are connecting sensor pads with external measuring device. Construction allows real-time live cell imaging. Combining with perfusion system allows medium circulation and generating shear stress stimulation. Experimental evaluation consist of several setups, including pure sensor without any coating and also collagen and fibrin coating was done. The Adipose derived stem cells (ASC) and Human umbilical vein endothelial cells (HUVEC) were seeded onto sensor in cultivation chamber. Then the chamber was installed into microscope system for live-cell imaging. The impedance measurement was utilized by vector impedance analyzer. The measured range was from 10 Hz to 40 kHz. These impedance measurements were correlated with live-cell microscopic imaging and immunofluorescent staining. Data analysis of measured signals showed response to cell adhesion of substrates, their proliferation and also change after shear stress stimulation which are important parameters during cultivation. Further experiments plan to use decellularized tissue as scaffold fixed on sensor. This kind of impedance sensor can provide feedback about cell culture conditions on opaque surfaces and scaffolds that can be used in tissue engineering in development artificial prostheses. This work was supported by the Ministry of Health, grants No. 15-29153A and 15-33018A.

Keywords: bio-impedance measuring, bioreactor, cell cultivation, diamond layer, gold interdigitated electrodes, tissue engineering

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Yaron Covo, Tamar Kofman, Shira Palti

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Over the recent decades, debates about the engagement of fans in football governance have focused on the club level and national level, emphasizing the significance of fans’ involvement in increasing the connection of clubs with the community, and in safeguarding the transparency, accountability, and clubs’ financial stability. This paper will offer a different conceptual justification for providing fans with access to decision-making processes in football. First, it will suggest that the participation of fans is necessary for addressing discriminatory practices against women in football stadiums. Second, it will argue that fans’ involvement in football governance is important not only at the club and national level but also at the global level, relying on the principles of Global Administrative Law. In contemporary men’s football, female fans face different forms of discrimination. Iranian women are still prohibited from attending football games at the domestic level; In Saudi Arabia, female fans are only permitted to enter designated family areas; Qatar – the host of the 2022 FIFA world cup – requires women to attend matches wearing modest clothing. Similarly, in Turkey, Lebanon, UAE, and Algeria, women face cultural barriers when attending men’s football games. In other countries, female fans suffer from subtle discrimination, including micro-aggressions, misogyny, sexism, and noninstitutionalized exclusion. Despite the vital role of fans in world football and the importance of football for many women’s lives, little has been done to address this problem. While FIFA recognizes that these discriminatory practices contradict its statutes, this recognition fails to materialize into meaningful change. This paper will argue that FIFA’s omission stems from two interrelated characteristics of world football: (1) the ultra-masculine nature of the game; (2) the insufficient recognition of fans’ significance. While fans have been given a voice in various football bodies on the domestic level, FIFA has yet to allow the representation of fans as stakeholders in world football governance. Since fans are a more heterogeneous group than players, the voices of those fans who do not fit the ultra-masculine model are not heard. Thus, by focusing mainly on male players, FIFA reproduces the hegemonic masculinity that feeds back into fan dynamics and marginalizes female fans. To rectify this problem, we will call on FIFA to provide fans and female fans in particular, with voice mechanisms and access to decision-making processes. In addition to its impact on the formation of fans’ identities, such a move will allow fans to demand better enforcement of existing anti-discrimination norms and new regulations to address their needs. The literature has yet to address the relationship between fans’ gender discrimination and global football governance. Building on Global Administrative Law scholarship and feminist theories, this paper will aim to fill this gap.

Keywords: fans, FIFA, football governance, gender discrimination, global administrative law, human rights

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Reut Lanyado, David Mendlovic

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Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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