Search results for: microscopic object detection and tracking

Authors: Laure Wiest, Barbara Giroud, Azziz Assoumani, Francois Lestremau, Emmanuelle Vulliet

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Due to their production at high tonnages and their extensive use, surfactants are contaminants among those determined at the highest concentrations in wastewater. However, analytical methods and data regarding their occurrence in river water are scarce and concern only a few families, mainly anionic surfactants. The objective of this study was to develop an analytical method to extract and analyze a wide variety of surfactants in a minimum of steps, with a sensitivity compatible with the detection of ultra-traces in surface waters. 27 substances, from 12 families of surfactants, anionic, cationic and non-ionic were selected for method optimization. Different retention mechanisms for the extraction by solid phase extraction (SPE) were tested and compared in order to improve their detection by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The best results were finally obtained with a C18 grafted silica LC column and a polymer cartridge with hydrophilic lipophilic balance (HLB), and the method developed allows the extraction of the three types of surfactants with satisfactory recoveries. The final analytical method comprised only one extraction and two LC injections. It was validated and applied for the quantification of surfactants in 36 river samples. The method's limits of quantification (LQ), intra- and inter-day precision and accuracy were evaluated, and good performances were obtained for the 27 substances. As these compounds have many areas of application, contaminations of instrument and method blanks were observed and considered for the determination of LQ. Nevertheless, with LQ between 15 and 485 ng/L, and accuracy of over 80%, this method was suitable for monitoring surfactants in surface waters. Application on French river samples revealed the presence of anionic, cationic and non-ionic surfactants with median concentrations ranging from 24 ng/L for octylphenol ethoxylates (OPEO) to 4.6 µg/L for linear alkylbenzenesulfonates (LAS). The analytical method developed in this work will therefore be useful for future monitoring of surfactants in waters. Moreover, this method, which shows good performances for anionic, non-ionic and cationic surfactants, may be easily adapted to other surfactants.

Keywords: anionic surfactant, cationic surfactant, LC-MS/MS, non-ionic surfactant, SPE, surface water

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Authors: Rudra Prasad Khanal

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Introduction: Non-communicable disease, such as cancer, has spread all over the world for some last decades. However, every nation has experienced a burden from the development of technology. In the context of Nepal, 10 to 15 thousand new cancer incidences are being registered in different hospitals for treatment. Since the date of starting nuclear medicine at Bir Hospital in 1998, cancer patients have been getting treatment regularly. According to the data of the population-based cancer registry, approximately 60% of the population having a middle-class income is being affected by cancer in Nepal. Methods and Materials: The study is aimed to find out the particular place where the population density of new cancer incidence is highest in Nepal and to inform the concerned regulatory body that is working on cancer screening and early detection for the proper treatment from the beginning. In order to identify the areas with the highest population density of new cancer incidence, all the data of cancer patients were collected from five different renowned hospitals and also from the population-based cancer registry center and then analyzed the data. The history of cancer patients was studied from 2003 to 2020, but here the data are analyzed from 2015 to 2020 only to find the latest trend in cancer incidence. Results: In the five major hospitals in Nepal, the total new cancer incidence was 61783 from 2015 to 2020. Out of those, 34617 were female, and 27176 were male. This research shows that female cancer patients were more every year. In the male, lung cancer patients more than cancer of other organs, but in females, the number of breast cancer patients was greatest. The age-adjusted mortality rate for males in Kathmandu valley was 36.3, and for females was 27.0 per 100,000 population. The cancer incidence and mortality rate were slightly lesser in other districts of Nepal. This rate increased with the increase in the age of people. Over 60 years, cancer incidence and mortality rates have been found to increase rapidly. Conclusion: This research supports conducting the program of cancer screening and early detection at Kathmandu valley with high priority and then Morang, Rukum, SSDM, etc., to control cancer.

Keywords: cancer incidence, research scholar, Tribhuvan University, Bhaktapur Cancer Hospital, Nepal

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Authors: B. Samuel Raj, Solomon R. D. Jebakumar

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Microbial fuel cells (MFCs) are an emerging and promising method for achieving sustainable energy since they can remove contaminated organic matter and simultaneously generate electricity. Our approach was driven in three different ways like Bacterial fuel cell, Soil Microbial fuel cell (Soil MFC) and Plant Microbial fuel cell (Plant MFC). Bacterial MFC: Sulphate reducing bacteria (SRB) were isolated and identified as the efficient electricigens which is able to produce ±2.5V (689mW/m2) and it has sustainable activity for 120 days. Experimental data with different MFC revealed that high electricity production harvested continuously for 90 days 1.45V (381mW/m2), 1.98V (456mW/m2) respectively. Biofilm formation was confirmed on the surface of the anode by high content screening (HCS) and scanning electron Microscopic analysis (SEM). Soil MFC: Soil MFC was constructed with low cost and standard Mudwatt soil MFC was purchased from keegotech (USA). Vermicompost soil (V1) produce high energy (± 3.5V for ± 400 days) compared to Agricultural soil (A1) (± 2V for ± 150 days). Biofilm formation was confirmed by HCS and SEM analysis. This finding provides a method for extracting energy from organic matter, but also suggests a strategy for promoting the bioremediation of organic contaminants in subsurface environments. Our Soil MFC were able to run successfully a 3.5V fan and three LED continuously for 150 days. Plant MFC: Amaranthus candatus (P1) and Triticum aestivium (P2) were used in Plant MFC to confirm the electricity production from plant associated microbes, four uniform size of Plant MFC were constructed and checked for energy production. P2 produce high energy (± 3.2V for 40 days) with harvesting interval of two times and P1 produces moderate energy without harvesting interval (±1.5V for 24 days). P2 is able run 3.5V fan continuously for 10days whereas P1 needs optimization of growth conditions to produce high energy.

Keywords: microbial fuel cell, biofilm, soil microbial fuel cell, plant microbial fuel cell

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Authors: Yanto Budisusanto, Aulia Rachmawati

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Land navigation technology that is being developed is Google Street View to provide 360° street views, enabling the user to know the road conditions physically with the photo display. For climbers, especially beginners, detail information of climbing terrain is needed so climbers can prepare supplies and strategies before climbing. Therefore, we built a mountaineer guide application named Mountain Photo Sphere. This application displays a 360̊ panoramic view of mountain hiking trail and important points along the hiking path and its surrounding conditions. By combining panoramic photos 360̊ and tracking paths from coordinate data, a virtual tour will be formed. It is built using Java language and Android Studio. The hiking trail map composed by Google Maps API (Gaining access to google maps), Google GEO API (Gaining access to google maps), and OpenStreetMap API (Getting map files to be accessed offline on the Application). This application can be accessed offline so that climbers can use the application during climbing activities.

Keywords: google street view, panoramic photo 360°, mountain hiking, mountain photo sphere

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

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Authors: Eldar Mammadov, Konul Mammadova, Aytaj Ilyaszada

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Background: According to many studies, it is known that H. pylori transform into the coccoid form, which cannot be cultured and has poor metabolic activity.In this study, we succeeded in preserving the spiral shape of H.pylori for a long time by preparing a biphase transport medium with a hard bottom (Muller Hinton with 7% HRBC (horse red blood cells) agar 5ml) and liquid top part (BH (brain heart) broth + HS (horse serum)+7% HRBC+antibiotics (Vancomycin 5 mg, Trimethoprim lactate 25 mg, Polymyxin B 1250 I.U.)) in cell culture flasks with filter caps. For comparison, we also used a BH broth medium with 7% HRBC used for the transport of H.pylori. Methods: Rapid urease test positive 7 biopsy specimens were also inoculated into biphasic and BH broth medium with 7% HRBC, then put in CO2 Gaspak packages and sent to the laboratory. Then both mediums were kept in the thermostat at 37 °C for 1 day. After microscopic, PCR and urease test diagnosis, they were transferred to Columbia Agar with 7% HRBC. Incubated at 37°C for 5-7 days, cultures were examined for colony characteristics and bacterial morphology. E-test antimicrobial susceptibility test was performed. Results: There were 3 growths from biphasic transport medium passed to Columbia agar with 7% HRBC and only 1 growth from BH broth medium with 7% HRBC. It was also observed that after the first 3 days in BH broth medium with 7%, H.pylori passed into coccoid form and its biochemical activity weakened, while its spiral shape did not change for 2-3 weeks in the biphase transport medium. Conclusions: By using the biphase transport medium we have prepared; we can culture the bacterium by preventing H.pylori from spiraling into the coccoid form. In our opinion, this may result in the wide use of culture method for diagnosis of H.pylori, study of antibiotic susceptibility and molecular genetic analysis.

Keywords: clinical trial, H.pylori, coccoid form, transport medium

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Authors: Santu Dey, Arindam Bhattacharyya

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The object of the present paper is to study a quarter-symmetric metric connection in a Lorentzian α-Sasakian manifold. We study some curvature properties of Lorentzian α-Sasakian manifold with respect to quarter-symmetric metric connection. We investigate quasi-projectively at, Φ-symmetric, Φ-projectively at Lorentzian α-Sasakian manifolds with respect to quarter-symmetric metric connection. We also discuss Lorentzian α-Sasakian manifold admitting quartersymmetric metric connection satisfying P.S = 0, where P denote the projective curvature tensor with respect to quarter-symmetric metric connection.

Keywords: quarter-symmetric metric connection, Lorentzian alpha-Sasakian manifold, quasi-projectively flat Lorentzian alpha-Sasakian manifold, phi-symmetric manifold

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Authors: Muhammad Ilham Agus Salim

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This study aims to reconstruct the discourse of human rights which focused on the issue of freedom of religion/belief (FORB) in Indonesia. This topic always has an appeal considering the development of Islam, both as a phenomenon of religion as well as social and political phenomenon, always in touch with human rights issues. For the majority, Islam is involved in human rights discourse needs to be viewed as a natural thing as it also occurs in the majority group in other countries. The natural state is increasingly gaining affirmation when also considering the doctrine of Islam which is also related to human rights. So the involvement of Islamic parties to human rights talks in Indonesia is not as excessive when considering the sociological position and character of Islamic doctrine. But because of who made the object of conversation, namely human rights and particularly freedom of religion or belief again, not something that is taken for granted, then the diversity within Islam itself impossible can be avoided. In this study the diversity of views presented in the trial which categorically can be grouped into two views, namely: inclusive and exclusive.

Keywords: Islam doctrine, Islamic parties, human rights, freedom of religion

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Authors: Brwa Abdulrahman Abubaker

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Recently, there has been a lot of interest in the difficult task of applying reinforcement learning to autonomous mobile robots. Conventional reinforcement learning (TRL) techniques have many drawbacks, such as lengthy computation times, intricate control frameworks, a great deal of trial and error searching, and sluggish convergence. In this paper, a modified Spiking Neural Network (SNN) is used to offer a distinct method for autonomous mobile robot learning and control in unexpected surroundings. As a learning algorithm, the suggested model combines dopamine modulation with spike-timing-dependent plasticity (STDP). In order to create more computationally efficient, biologically inspired control systems that are adaptable to changing settings, this work uses the effective and physiologically credible Izhikevich neuron model. This study is primarily focused on creating an algorithm for target tracking in the presence of obstacles. Results show that the SNN trained with three obstacles yielded an impressive 96% success rate for our proposal, with collisions happening in about 4% of the 214 simulated seconds.

Keywords: spiking neural network, spike-timing-dependent plasticity, dopamine modulation, reinforcement learning

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Authors: Samir El-Gendy, Doaa Zaghloul

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The current study dealt with the gross and microscopic anatomy of the integument of male ostrich in addition to the histological features of different areas of skin by light and SEM. The ostrich skin is characterized by prominent feather follicles and bristles. The number of feather follicles was determined per cm2 in different regions. The integument of ostrich had many modifications which appeared as callosities and scales, nail and toe pads. They were sternal, pubic and Achilles tendon callosities. The vacuolated epidermal cells were seen mainly in the skin of legs and to a lesser extent in the skin of back and Achilles areas. Higher lipogenic potential was expressed by epidermis from glabrous areas of ostrich skin. The dermal papillae were found in the skin of feathered area of neck and back and this was not a common finding in bird's skin which may give resistance against shearing forces in these regions of ostrich skin. The thickness of the keratin layer of ostrich varied, being thick and characteristically loose in the skin at legs, very thin and wavy at neck, while at Achilles skin area, scale and toe pad were thick and more compact, with the thickest very dense and wavy keratin layer at the nail. The dermis consisted of superficial layer of dense irregular connective tissue characterized by presence of many vacuoles of different sizes just under the basal lamina of the epithelium of epidermis and deep layer of dense regular connective tissue. This result suggested presence of fat droplets in this layer which may be to overcome the lack of good barrier of cutaneous water loss in epidermis.

Keywords: ostrich, light microscopy, scanning electron microscopy, integument, skin modifications

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Authors: Sameen Tariq, Saira Bano, Sayyada Ghufrana Nadeem

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The Ocean, which covers over 70% of the world's surface, is wealthy in biodiversity as well as a rich wellspring of microorganisms with huge potential. The oceanic climate is home to an expansive scope of plants, creatures, and microorganisms. Marine microbial networks, which incorporate microscopic organisms, infections, and different microorganisms, enjoy different benefits in biotechnological processes. Samples were collected from marine environments, including soil and water samples, to cultivate the uncultured marine organisms by using Zobell’s medium, Sabouraud’s dextrose agar, and casein media for this purpose. Following isolation, we conduct microscopy and biochemical tests, including gelatin, starch, glucose, casein, catalase, and carbohydrate hydrolysis for further identification. The results show that more gram-positive and gram-negative bacteria. The isolation process of marine organisms is essential for understanding their ecological roles, unraveling their biological secrets, and harnessing their potential for various applications. Marine organisms exhibit remarkable adaptations to thrive in the diverse and challenging marine environment, offering vast potential for scientific, medical, and industrial applications. The isolation process plays a crucial role in unlocking the secrets of marine organisms, understanding their biological functions, and harnessing their valuable properties. They offer a rich source of bioactive compounds with pharmaceutical potential, including antibiotics, anticancer agents, and novel therapeutics. This study is an attempt to explore the diversity and dynamics related to marine microflora and their role in biofilm formation.

Keywords: marine microorganisms, ecosystem, fungi, biofilm, gram-positive, gram-negative

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Hatane Semuel, Foedjiawati, Michelle Sunur

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This study took the research object of fifteen legal travel agencies in Surabaya. The respondents are taken through purposive sampling of a number of 100 employees out of Fifteen travel agencies which are varied in its division. Service orientation is constructed based on several dimensions; such as, service leadership practices, service encounter practices, human resources management practices, and service system practices. Service skills are constructed with dimensions; namely: technical skills, interpersonal skills, and problem-solving skill. While employee performance is constructed with dimensions; namely: quantity of work, quality of work, timeliness of work and organization of work. The results show that there is a direct positive influence on employee performance service orientation. Additionally, service orientation influences indirectly positive on employee performance through the service skills. Therefore, the total effect of service orientation on employee performance is proven stronger.

Keywords: employee performance, service orientation, service skills, travel agencies

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Authors: A. T. Siacara, A. T. Beck, M. M. Futai

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This paper shows how accurately and efficiently reliability analyses of geotechnical installations can be performed by directly coupling geotechnical software with a reliability solver. An earth slope is used as the study object. The limit equilibrium method of Morgenstern-Price is used to calculate factors of safety and find the critical slip surface. The deterministic software package Seep/W and Slope/W is coupled with the StRAnD reliability software. Reliability indexes of critical probabilistic surfaces are evaluated by the first-order reliability methods (FORM). By means of sensitivity analysis, the effective cohesion (c') is found to be the most relevant uncertain geotechnical parameter for slope equilibrium. The slope was tested using different geometries, taking into account unsaturated soil properties. Finally, a critical slip surface, identified in terms of minimum factor of safety, is shown here not to be the critical surface in terms of reliability index.

Keywords: slope, unsaturated, reliability, safety, seepage

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Authors: Saeid Gharechelou, Ryutaro Tateishi

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Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid damage monitoring, 2015-Nepal earthquake

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Authors: Ahmed M. Alavi

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India is the motherland of countless beliefs and religious traditions. Hinduism is one of the oldest traditions of India and owns the treasure of numerous organic and inorganic gods. Hinduism was unfamiliar of the manifestation of divine powers in its early accounts. The conceptualization of the divine powers is still debatable query among the experts of the area. This study examines the unseen memoirs of the Hindu god concept and answers the dubious question ‘how Hindu gods subjected to manifestation? Comparing the attitude of the Hindu and Asiatic tantric traditions; these study hypotheses the clear role of tantric Bhakti movements which originated in 3rd to 5th century BC in south India as the key of the conceptualization. The study concludes exploring the vital role of Bhakti movement in rifting the Indian Hindu community to three major fans of manifested gods; the Shaivism, Vishnavism and Saktism and spreading the new trend all over the sub-continent.

Keywords: Bhakti movement, concept of manifestation of divine object, Hindu god concept, Tantrism

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Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

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Authors: Abida Haddouche, Ahmed Chrif Toubal

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The Neogene basin of the Eastern Mitidja, object of the study area, represents potential water resources and especially groundwater reserves. This water is an important economic; this resource is highly sensitive which need protection and preservation. Unfortunately, these waters are exposed to various forms of pollution, whether from urban, agricultural, industrial or merely accidental. This pollution is a permanent risk of limiting resource. In this context, the work aims to evaluate the intrinsic vulnerability of the aquifer to protect and preserve the quality of this resource. It will focus on the disposal of water and land managers a cartographic document accessible to locate the areas where the water has a high vulnerability. Vulnerability mapping of the Easter Mitidja quaternary aquifer is performed by applying three methods (DRASTIC, DRIST, and GOD). Comparison and validation results show that the DRASTIC method is the most suitable method for aquifer vulnerability of the study area.

Keywords: Aquifer of Mitidja, DRASTIC method, geographic information system (GIS), vulnerability mapping

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Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

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Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

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Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Mohamed F. Sadek, Safaa M. Hassan, Safwat S. Gabr

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Several alteration zones hosting gold mineralization are wide spreading in the South Eastern Desert of Egypt where gold has been mined from many localities since the time of the Pharaohs. The Sukkari is the only mine currently producing gold in the Eastern Desert of Egypt. Therefore, it is necessary to conduct more detailed studies on these locations using modern exploratory methods. The remote sensing plays an important role in lithological mapping and detection of associated hydrothermal mineralization particularly the exploration of gold mineralization. This study is focused on three localities in South Eastern Desert of Egypt, namely Beida, Defiet and Hoteib-Eiqat aiming to detect the gold-bearing hydrothermal alteration zones using the integrated data of remote sensing, field study and mineralogical investigation. Generally, these areas are dominated by Precambrian basement rocks including metamorphic and magmatic assemblages. They comprise ophiolitic serpentinite-talc carbonate, island-arc metavolcanics which were intruded by syn to late orogenic mafic and felsic intrusions mainly gabbro, granodiorite and monzogranite. The processed data of Advanced Spaceborne Thermal Emission and Reflection (ASTER) and Landsat-8 images are used in the present study to map the gold bearing-hydrothermal alteration zones. Band rationing and principal component analysis techniques are used to discriminate the different lithologic units exposed in the studied three areas. Field study and mineralogical investigation have been used to verify the remote sensing data. This study concluded that, the integrated remote sensing data with geological, field and mineralogical investigations are very effective in lithological discrimination, detailed geological mapping and detection of the gold-bearing hydrothermal alteration zones. More detailed exploration for gold mineralization with the help of remote sensing techniques is recommended to evaluate its potentiality in the study areas.

Keywords: pan-african, Egypt, landsat-8; ASTER, gold, alteration zones

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Authors: B. G. Patel, A. K. Desai, S. G. Shah

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The main of objective of this paper is to develop new measurement technique without touching the object. DIC is advance measurement technique use to measure displacement of particle with very high accuracy. This powerful innovative technique which is used to correlate two image segments to determine the similarity between them. For this study, nine geometrically similar beam specimens of different sizes with (steel fibers and glass fibers) and without fibers were tested under three-point bending in a closed loop servo-controlled machine with crack mouth opening displacement control with a rate of opening of 0.0005 mm/sec. Digital images were captured before loading (unreformed state) and at different instances of loading and were analyzed using correlation techniques to compute the surface displacements, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It was seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Keywords: Digital Image Correlation, fibres, self compacting concrete, size effect

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Authors: Guenther Schuh, Michael Riesener, Jan Kantelberg

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Due to the fugacity of markets and the reduction of product lifecycles, manufacturing companies from high-wage countries are nowadays faced with the challenge to place more innovative products within even shorter development time on the market. At the same time, volatile customer requirements have to be satisfied in order to successfully differentiate from market competitors. One potential approach to address the explained challenges is provided by agile values and principles. These agile values and principles already proofed their success within software development projects in the form of management frameworks like Scrum or concrete procedure models such as Extreme Programming or Crystal Clear. Those models lead to significant improvements regarding quality, costs and development time and are therefore used within most software development projects. Motivated by the success within the software industry, manufacturing companies have tried to transfer agile mechanisms of action to the development of hardware products ever since. Though first empirical studies show similar effects in the agile development of hardware products, no comprehensive procedure model for the design of development iterations has been developed for hardware development yet due to different constraints of the domains. For this reason, this paper focusses on the design of agile product development processes by transferring mechanisms of action used in agile software development towards product development. This is conducted by decomposing the individual systems 'product development' and 'agile software development' into relevant elements and symbiotically composing the elements of both systems in respect of the design of agile product development processes afterwards. In a first step, existing product development processes are described following existing approaches of the system theory. By analyzing existing case studies from industrial companies as well as academic approaches, characteristic objectives, activities and artefacts are identified within a target-, action- and object-system. In partial model two, mechanisms of action are derived from existing procedure models of agile software development. These mechanisms of action are classified in a superior strategy level, in a system level comprising characteristic, domain-independent activities and their cause-effect relationships as well as in an activity-based element level. Within partial model three, the influence of the identified agile mechanism of action towards the characteristic system elements of product development processes is analyzed. For this reason, target-, action- and object-system of the product development are compared with the strategy-, system- and element-level of agile mechanism of action by using the graph theory. Furthermore, the necessity of existence of activities within iteration can be determined by defining activity-specific degrees of freedom. Based on this analysis, agile product development processes are designed in form of different types of iterations within a last step. By defining iteration-differentiating characteristics and their interdependencies, a logic for the configuration of activities, their form of execution as well as relevant artefacts for the specific iteration is developed. Furthermore, characteristic types of iteration for the agile product development are identified.

Keywords: activity-based process model, agile mechanisms of action, agile product development, degrees of freedom

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: Murat Colak, Berkay Cakir Saridogan

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Since the dawn of modern corporations, almost every single employee has been working in the same loop, which contains three basic steps: going to work, providing the needs for the work, and getting back home. Only a small amount of people were able to break that standard and live outside the box. As the 2019 pandemic hit the Earth and most companies shut down their physical offices, that loop had to change for everyone. This means that the old management styles had to be significantly re-arranged to the "work from home" type of business methods. The methods include online conferences and meetings, time and task tracking using algorithms, globalization of the work, and, most importantly, remote working. After the global epidemic started, even the tech giants were concerned. Now, it can be seen those technology companies have an incredible step-up in their shares compared to the other companies because they know how to manage such situations even better than every other industry. This study aims to take the old traditional management styles in big companies and compare them with the post-covid methods (2019-2022). As a result of this comparison made using the annual reports and shared statistics, this study aims to explain why the winners of this crisis are the technology companies.

Keywords: Covid-19, technology companies, business models, remote work

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Authors: Rahul Pal

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In India, construction industry plays a vital role in the development of infrastructures. It is one of the most hazardous industries. Construction workers are a group that is particularly vulnerable to health risks because they have few legal protection. India has the world’s highest accident rate among construction workers. This study aimed to investigate the prevalence of occupation injury among construction workers and to find out the factors responsible for such injuries. Methodology: A cross-sectional study using a semi-structured questionnaire among 305 construction workers in Bhubaneswar city. In this study, it was found that the overall prevalence of injury was 43.28% in the previous one year period. Majority of the construction workers were less experience in the construction work. Factors responsible for injuries are fall of the object followed by striking, and majority of the workers reported their injuries to have occurred in the summer season. And most of the construction workers are not using personal protective equipment (PPE). Conclusion: Given the occupational injuries, the majority of the construction workers are injured in this study; there is a need to address this issue to ensure necessary step for the safety and well-being of construction workers.

Keywords: construction, construction workers, occupational injuries, personal protective equipment

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Yousef Reda

Abstract:

Pancreatic cancer has an overall dismal prognosis. CT, MRI and Endoscopic Ultrasound are most often used to establish the diagnosis. We present a case of a patient found on abdominal CT and MRI to have an 8 mm cystic lesion within the head of the pancreas which was thought to be a benign intraductal papillary mucinous neoplasm (IPMN). Further evaluation by EUS demonstrated a 1 cm predominantly solid mass that was proven to be an adenocarcinoma by EUS-guided FNA. The patient underwent a Whipple procedure. The final pathology confirmed a 1 cm pT1 N0 pancreatic ductal adenocarcinoma. Case: A 63-year-old male presented with left upper quadrant pain and an abdominal CT demonstrated an 8 mm lesion within the head of the pancreas that was thought to represent a side branch IPMN. An MRI also showed similar findings. Four months later due to ongoing symptoms an EUS was performed to re-evaluate the pancreatic lesion. EUS revealed a predominantly solid hypoechoic, homogeneous mass measuring 12 mm x 9 mm. EUS-guided FNA was performed and was positive for adenocarcinoma. The patient underwent a Whipple procedure that confirmed it to be a ductal adenocarcinoma, pT1N0. The solid mass was noted to be adjacent to a cystic dilation with no papillary architecture and scant epithelium. The differential diagnosis resided between cystic degeneration of a primary pancreatic adenocarcinoma versus malignant degeneration within a side-branch IPMN. Discussion: The reported sensitivity of CT for pancreatic cancer is approximately 90%. For pancreatic tumors, less than 3 cm the sensitivity of CT is reduced ranging from 67-77%. MRI does not significantly improve overall detection rates compared to CT. EUS, however is superior to CT in the detection of pancreatic cancer, in particular among lesions smaller than 3 cm. EUS also outperforms CT and MRI in distinguishing neoplastic from non-neoplastic cysts. In this case, both MRI and CT failed to detect a small pancreatic adenocarcinoma. The addition of EUS and FNA to abdominal imaging can increase overall accuracy for the diagnosis of neoplastic pancreatic lesions. It may be prudent that when small lesions although appearing as a benign IPMN should further be evaluated by EUS as this would lead to potentially identifying earlier stage pancreatic cancers and improve survival in a disease which has a dismal prognosis.

Keywords: IPMN, MRI, EUS, CT

Procedia PDF Downloads 257