Search results for: object detection and tracking

Authors: Golayeh Yousefi, Mehdi Homaee, Ali Akbar Norouzi

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Ongoing monitoring of soil contamination by heavy metals is critical for ecosystem stability and environmental protection, and food security. The conventional methods of determining these soil contaminants are time-consuming and costly. Spectroscopy in the visible near-infrared (VNIR) - short wave infrared (SWIR) region is a rapid, non-destructive, noninvasive, and cost-effective method for assessment of soil heavy metals concentration by studying the spectral properties of soil constituents. The aim of this study is to derive spectral bands and important ranges that are sensitive to heavy metals and can be used to estimate the concentration of these soil contaminants. In other words, the change in the spectral properties of spectrally active constituents of soil can lead to the accurate identification and estimation of the concentration of these compounds in soil. For this purpose, 325 soil samples were collected, and their spectral reflectance curves were evaluated at a range of 350-2500 nm. After spectral preprocessing operations, the partial least-squares regression (PLSR) model was fitted on spectral data to predict the concentration of Cu and Ni. Based on the results, the spectral range of Cu- sensitive spectra were 480, 580-610, 1370, 1425, 1850, 1920, 2145, and 2200 nm, and Ni-sensitive ranges were 543, 655, 761, 1003, 1271, 1415, 1903, 2199 nm. Finally, the results of this study indicated that the spectral data contains a lot of information that can be applied to identify the soil properties, such as the concentration of heavy metals, with more detail.

Keywords: heavy metals, spectroscopy, spectral bands, PLS regression

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Authors: Yao Xing, Hong Ling Liu, Wei Dong Yu

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With the increase of global population, it is of importance for the safe water supply, while, the water-monitoring method with the capability of rapidness, low-cost, green and robustness remains unsolved. In this paper, gold nanoclusters-wool keratin is added into copper ions measured by fluorescent method in order to probe copper ions in aqueous solution. The fluorescent results show that gold nanoclusters-wool keratin exhibits high stability of pHs, while it is sensitive to temperature and time. Based on Gauss fitting method, the results exhibit that the slope of gold nanoclusters-wool keratin with pH resolution under acidic condition is higher compared to it under alkaline solutions. Besides, gold nanoclusters-wool keratin added into copper ions shows a fluorescence turn-off response transferring from red to blue under UV light, leading to the dramatically decreased fluorescent intensity of gold nanoclusters-wool keratin solution located at 690 nm. Moreover, the limited concentration of copper ions tested by gold nanoclusters-wool keratin system is around 1 µmol/L, which meets the need of detection standards. The fitting slope of Stern-Volmer plot at low concentration of copper ions is larger than it at high concentrations, which indicates that aggregated gold nanoclusters are from small amounts to large numbers with the increasing concentration of copper ions. It is expected to provide novel method and materials for copper ions testing with low cost, high efficiency, and easy operability.

Keywords: gold nanoclusters, copper ions, wool keratin, fluorescence

Procedia PDF Downloads 252

Authors: Temesgen Geremew

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ZnS/glass and CdS/glass single layers and ZnS/CdS and CdS/ZnS heterojunction thin films were deposited by the chemical bath deposition method using zinc acetate and cadmium acetate as the metal ion sources and thioacetamide as a nonmetallic ion source in acidic medium. Na2EDTA was used as a complexing agent to control the free cation concentration. +e single layer and heterojunction thin films were characterized with X-ray diffraction (XRD), a scanning electron microscope (SEM), energy dispersive X-ray (EDX), and a UV-VIS spectrometer. +e XRD patterns of the CdS/glass thin film deposited on the soda lime glass substrate crystalized in the cubic structure with a single peak along the (111) plane. +e ZnS/CdS heterojunction and ZnS/glass single layer thin films were crystalized in the hexagonal ZnS structure. +e CdS/ZnS heterojunction thin film is nearly amorphous.The optical analysis results confirmed single band gap values of 2.75 eV and 2.5 eV for ZnS/CdS and CdS/ZnS heterojunction thin films, respectively. +e CdS/glass and CdS/ZnS thin films have more imaginary dielectric components than the real part. The optical conductivity of the single layer and heterojunction films is in the order of 1015 1/s. +e optical study also confirmed refractive index values between 2 and 2.7 for ZnS/glass, ZnS/CdS, and CdS/ZnS thin films for incident photon energies between 1.2 eV and 3.8 eV. +e surface morphology studies revealed compacted spherical grains covering the substrate surfaces with few cracks on ZnS/glass, ZnS/CdS, and CdS/glass and voids on CdS/ZnS thin films. +e EDX result confirmed nearly 1 :1 metallic to nonmetallic ion ratio in the single-layered thin films and the dominance of Zn ion over Cd ion in both ZnS/CdS and CdS/ZnS heterojunction thin films.

Keywords: SERS, sensor, Hg2+, water detection, polythiophene

Procedia PDF Downloads 65

Authors: Abdulrahman Fahim M. Alsulami

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This paper is dedicated to a detailed investigation of the interaction between the agreement on trade-related aspects of intellectual property rights (TRIPS) and bilateral investment treaties (BITs) in the regulation of health-related intellectual property rights in Australia and the Kingdom of Saudi Arabia. The chosen research object is complex and requires a thorough examination of a set of factors influencing the problem under investigation. At the moment, to the author’s best knowledge’ there is no academic research that would conceptualize and critically compare the regulation of health-related intellectual property rights in these two countries. While there is a substantial amount of information in the literature on certain aspects of the problem, the existing knowledge about certain aspects of the health-related regulatory frameworks in Australia and Saudi Arabia barely explains in detail the specifics of the ways in which the TRIPS agreement interacts with (BITs) in the regulation of health-related intellectual property rights. Therefore, this paper will address an evident research gap by studying an intriguing yet under-researched problem. The paper comprises five subsections. The first subsection provides an overview of the investment climate in Saudi Arabia and Australia with an emphasis on the health care industry. It will cover political, economic, and social factors influencing the investment climate in these countries, the systems of intellectual property rights protection, recent patterns relevant to the investment climate’s development, and key characteristics of the investment climate in the health care industry. The second subsection analyses BITs in Saudi Arabia and Australia in light of the countries’ responsibilities under the TRIPS Agreement. The third subsection provides a critical examination of the interaction between the TRIPS Agreement and BITs in Saudi Arabia on the basis of data collected and analyzed in previous subsections. It will investigate key discrepancies concerning the regulation of health-related intellectual property rights in Saudi Arabia and Australia from the position of BITs’ interaction with the TRIPS Agreement and explore the existing procedures for clarifying priorities between them in regulating health-related intellectual property rights. The fourth subsection of the paper provides recommendations concerning the transformation of BITS into a TRIPS+ dimension in regulating health-related intellectual property rights in Saudi Arabia and Australia. The final subsection provides a summary of differences between the Australian and Saudi BITs from the perspective of the regulation of health-related intellectual property rights under the TRIPS agreement and bilateral investment treaties.

Keywords: Australia, bilateral investment treaties, IP law, public health sector, Saudi Arabia

Procedia PDF Downloads 144

Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

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The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

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Authors: Ava Zarif Sanayei, Mustafa Farjad-Fard, Mohammad-Reza Mohammadian-Behbahani, Leyli Ebrahimi, Sedigheh Sina

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The fabrication and testing of a low-cost air-filled ion chamber for X-ray dosimetry is studied. The chamber is made of a metal cylinder, a central wire, a BC517 Darlington transistor, a 9V DC battery, and a voltmeter in order to have a cost-effective means to measure the dose. The output current of the dosimeter is amplified by the transistor and then fed to the large internal resistance of the voltmeter, producing a readable voltage signal. The dose-response linearity of the ion chamber is evaluated for different exposure scenarios by the X-ray tube. kVp values 70, 90, and 120, and mAs up to 20 are considered. In all experiments, a solid-state dosimeter (Solidose 400, Elimpex Medizintechnik) is used as a reference device for chamber calibration. Each case of exposure is repeated three times, the voltmeter and Solidose readings are recorded, and the mean and standard deviation values are calculated. Then, the calibration curve, derived by plotting voltmeter readings against Solidose readings, provided a linear fit result for all tube kVps of 70, 90, and 120. A 99, 98, and 100% linear relationship, respectively, for kVp values 70, 90, and 120 are demonstrated. The study shows the feasibility of achieving acceptable dose measurements with a simplified setup. Further enhancements to the proposed setup include solutions for limiting the leakage current, optimizing chamber dimensions, utilizing electronic microcontrollers for dedicated data readout, and minimizing the impact of stray electromagnetic fields on the system.

Keywords: dosimetry, ion chamber, radiation detection, X-ray

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

Procedia PDF Downloads 250

Authors: L. Malic, X. Zhang, D. Brassard, L. Clime, J. Daoud, C. Luebbert, V. Barrere, A. Boutin, S. Bidawid, N. Corneau, J. Farber, T. Veres

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The incidence of infections caused by foodborne pathogens such as Listeria monocytogenes (L. monocytogenes) poses a great potential threat to public health and safety. These issues are further exacerbated by legal repercussions due to “zero tolerance” food safety standards adopted in developed countries. Unfortunately, a large number of related disease outbreaks are caused by pathogens present in extremely low counts currently undetectable by available techniques. The development of highly sensitive and rapid detection of foodborne pathogens is therefore crucial, and requires robust and efficient pre-analytical sample preparation. Immunomagnetic separation is a popular approach to sample preparation. Microfluidic chips combined with external magnets have emerged as viable high throughput methods. However, external magnets alone are not suitable for the capture of nanoparticles, as very strong magnetic fields are required. Devices that incorporate externally applied magnetic field and microstructures of a soft magnetic material have thus been used for local field amplification. Unfortunately, very complex and costly fabrication processes used for integration of soft magnetic materials in the reported proof-of-concept devices would prohibit their use as disposable tools for food and water safety or diagnostic applications. We present a sample preparation magnetic microfluidic device implemented in low-cost thermoplastic polymers using fabrication techniques suitable for mass-production. The developed magnetic capture chip (M-chip) was employed for rapid capture and release of L. monocytogenes conjugated to immunomagnetic nanoparticles (IMNs) in buffer and beef filtrate. The M-chip relies on a dense array of Nickel-coated high-aspect ratio pillars for capture with controlled magnetic field distribution and a microfluidic channel network for sample delivery, waste, wash and recovery. The developed Nickel-coating process and passivation allows generation of switchable local perturbations within the uniform magnetic field generated with a pair of permanent magnets placed at the opposite edges of the chip. This leads to strong and reversible trapping force, wherein high local magnetic field gradients allow efficient capture of IMNs conjugated to L. monocytogenes flowing through the microfluidic chamber. The experimental optimization of the M-chip was performed using commercially available magnetic microparticles and fabricated silica-coated iron-oxide nanoparticles. The fabricated nanoparticles were optimized to achieve the desired magnetic moment and surface functionalization was tailored to allow efficient capture antibody immobilization. The integration, validation and further optimization of the capture and release protocol is demonstrated using both, dead and live L. monocytogenes through fluorescence microscopy and plate- culture method. The capture efficiency of the chip was found to vary as function of listeria to nanoparticle concentration ratio. The maximum capture efficiency of 30% was obtained and the 24-hour plate-culture method allowed the detection of initial sample concentration of only 16 cfu/ml. The device was also very efficient in concentrating the sample from a 10 ml initial volume. Specifically, 280% concentration efficiency was achieved in 17 minutes only, demonstrating the suitability of the system for food safety applications. In addition, flexible design and low-cost fabrication process will allow rapid sample preparation for applications beyond food and water safety, including point-of-care diagnosis.

Keywords: array of pillars, bacteria isolation, immunomagnetic sample preparation, polymer microfluidic device

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Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: camera calibration, ice detection, ice load measurements, image processing

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Authors: Emine Zeytinli

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Ottoman carpets were depicted in Renaissance painting while they were exported commercially. The carpets were highly demanded and used by the middle and upper classes of Western European countries. The motifs, designs, patterns, and ornamentation of these carpets were decorative objects of luxury for Western European residences as well as paintings. Oriental carpets found their way into European market already from the medieval times to the present century. They were considered as luxury items first, however, demanded by middle classes in Europe and North America within the nineteenth century. This century brought unprecedented changes in production and consumption in the world. Expanding industries created quick urbanization, changed the city life and new types of goods dominated the entire century. Increases in income allowed Europeans to spend on luxury items, consumers taste changed in number of ways including furniture and decoration. Use of a carpet in the orient lifestyle often considered as an art object with Western aesthetic sensibility. A carpet with an oriental character, an essential part of home decoration, was highly appreciated for floor, table covering and wall hanging. Turkish carpets with distinctive classical style, patterns, and colours were changed for the tastes of European consumers. This paper attempts to analyse how the taste and preferences of European and American consumers increased their buying of oriental objects namely carpets. The production of local hand woven carpet industry developed, carpet factories were set up and special weaving schools were opened in some major waving centres, and carpet weaving became one of the main manufacturing and export commodity of the empire. All of these attempts increased the reputation and market share in international market. The industry flourished, commercially operated carpet looms, sales revenues and export increased unprecedentedly. British and Ottoman archival documents, parliamentary papers and travel notes were used to analysed above mention effect on how the foreign demand changed designs of carpets and the business itself, how the production in households moved to the commercial premises and a flourished the industry.

Keywords: consumption patterns, carpet weaving, ottoman oriental carpets, commercialisation

Procedia PDF Downloads 138

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

Procedia PDF Downloads 331

Authors: M. R. Mogarekar, Shraddha V. More, Pankaj Kumar

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Gastroenteritis, the third leading killer of children in India today is responsible for 13% of all deaths in children <5 years of age and kills an estimated 300,000 children in India each year. We decided to investigate parameters which can help in early disease detection and prompt treatment. Serum paraoxonase is calcium dependent esterase which is widely distributed among tissues such as liver, kidney, and intestine and is located in the chromosomal region 7q21.3 22.1. Studies show the presence of excessive reactive oxygen metabolites and antioxidant imbalance in the gastrointestinal tract leading to oxidative stress in gastroenteritis. To our knowledge, this is the first ever study done. The objective of present study is to investigate the role of paraoxonase 1 (PON 1) status i.e arylesterase and lactonase activities and Q192R polymorphism and conjugated dienes, in gastroenteritis of paediatric population. The study and control group consists of 40 paediatric patients with and without gastroenteritis. Paraoxonase arylesterase and lactonase activities were assessed and phenotyping was determined. Conjugated dienes were also assessed. PON 1 arylesterase activities in cases (61.494±13.220) and controls (70.942±15.385) and lactonase activities in cases (15.702±1.036) and controls (17.434±1.176) were significantly decreased (p<0.05). There is no significant difference of phenotypic distribution in cases and controls. Conjugated dienes were found significantly increased in patients (0.086±0.024) than the control group (0.064±0.019) (p<0.05). Paraoxonase 1 activities (arylesterase and lactonase) and conjugated dienes may be useful in risk assessment and management in gastroenteritis in paediatric population.

Keywords: paraoxonase 1 polymorphism, arylesterase, lactonase, conjugated dienes, p-nitrophenylacetate, DHC

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Authors: Hahido Samaras

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In many cases, especially with the pandemic playing a major role in fast-tracking the growth of the digital industry, online learning has become a necessity or even a standard educational model nowadays, reliably overcoming barriers such as location, time and cost and frequently combined with a face-to-face format (e.g., in blended learning). This being the case, it is evident that students in many parts of the world, as well as their parents, will increasingly need to become aware of the pros and cons of online versus traditional courses. This fast-growing mode of learning, accelerated during the years of the pandemic, presents an abundance of exciting options especially matched for a large number of secondary school students in remote places of the world where access to stimulating educational settings and opportunities for a variety of learning alternatives are scarce, adding advantages such as flexibility, affordability, engagement, flow and personalization of the learning experience. However, online learning can also present several challenges, such as a lack of student motivation and social interactions in natural settings, digital literacy, and technical issues, to name a few. Therefore, educational researchers will need to conduct further studies focusing on the benefits and weaknesses of online learning vs. traditional learning, while instructional designers propose ways of enhancing student motivation and engagement in virtual environments. Similarly, teachers will be required to become more and more technology-capable, at the same time developing their knowledge about their students’ particular characteristics and needs so as to match them with the affordances the technology offers. And, of course, schools, education programs, and policymakers will have to invest in powerful tools and advanced courses for online instruction. By developing digital courses that incorporate intentional opportunities for community-building and interaction in the learning environment, as well as taking care to include built-in design principles and strategies that align learning outcomes with learning assignments, activities, and assessment practices, rewarding academic experiences can derive for all students. This paper raises various issues regarding the effectiveness of online learning on students by reviewing a large number of research studies related to the usefulness and impact of online learning following the COVID-19-induced digital education shift. It also discusses what students, teachers, decision-makers, and parents have reported about this mode of learning to date. Best practices are proposed for parties involved in the development of online learning materials, particularly for secondary school students, as there is a need for educators and developers to be increasingly concerned about the impact of virtual learning environments on student learning and wellbeing.

Keywords: blended learning, online learning, secondary schools, virtual environments

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Authors: Naira Hakobyan, Shant Bagratyan

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This paper explores the phenomenon of management of innovations from the standpoint of work motivation. The main purpose of the theoretical research is to reveal the role of management of innovations to overcome the destructive work motivation and anomie. Systematization of the theoretical approaches and the literary sources indicates connections between destructive forms of work motivation and anomie. These connections allow an understanding of the role of innovations dedicated to decrease the motivational destructiveness of the employees. It is important to note that, in general, the presence of destructive motivation among employees can lead to work anomie. At the same time, issues related to the influence of destructive motivation on innovative processes in the management of an organization are not sufficiently studied. Exploring the factors leading to destructive work motivation and anomie manages toolkit and innovative ways of solution of the motivational destructiveness. The relevance of this scientific issue is that motivational destructiveness and work anomie are widespread phenomena in modern society. It means that previous forms of management become unusable and the way to introduce the innovations seems unclear for the employees. Investigation of the phenomenon of management of innovations is carried out in the following logical sequence: firstly, the issues of destructive work motivation and leadership are considered, and then the key points of work anomie are presented. Finally, there are explored the modern trends in the management of innovations aimed at overcoming motivational destructiveness and work anomie. The issue of management of innovations is explored by two levels: external-social and internal-organizational levels. Considering the phenomenon of management of innovations, the motivational role of the innovations is emphasized. The object of the research is the phenomenon of management of innovations in the context of overcoming motivational and anomic destructiveness. The paper presents the results of the theoretical analysis of the main factors of destructive motivation and work anomie among employees: an excessive dependence of employees on the manager, ignorance of one’s own work functions or unreasonable change by the manager, prevalence of formalism in assessing work comparing with the content and quality of work, lack of adaptive interaction among employees and low self-esteem of work activity. The paper theoretically proves that unclearly formulated innovative strategies for the development of the organization, lack of feedback from the manager to employees regarding the discussion of innovative technologies, non-compliance of working conditions with declared norms and standards, and formalism in management of innovations lead to destructiveness in a management system. The results of the research can be useful for managers, sociologists, economists, and psychologists.

Keywords: management of innovations, destructive motivation, work anomie, leadership, workaholism

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

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Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

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Authors: Candra Irawan, David Yudianto, Ahsanu Nadiyya, Dewi Anna Br Sitepu, Hanafi, Erna Styani

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Jelly drink was produced from a combination of both natural and synthetic materials, such as acesulfame potassium (acesulfame-K) as synthetic sweetener material. Acesulfame-K content in jelly drink could be determined by High-Performance Liquid Chromatography (HPLC), but this method needed validation due to having a change on the reagent addition step which skips the carrez addition and comparison of mix mobile phase (potassium dihydrogen phosphate and acetonitrile) with ratio from 75:25 to 90:10 to be more efficient and cheap. This study was conducted to evaluate the performance of determination method for acesulfame-K content in the jelly drink by HPLC. The method referred to Deutsches Institut fur Normung European Standard International Organization for Standardization (DIN EN ISO):12856 (1999) about Foodstuffs, Determination of acesulfame-K, aspartame and saccharin. The result of the correlation coefficient value (r) on the linearity test was 0.9987 at concentration range 5-100 mg/L. Detection limit value was 0.9153 ppm, while the quantitation limit value was 1.1932 ppm. The recovery (%) value on accuracy test for sample concentration by spiking 100 mg/L was 102-105%. Relative Standard Deviation (RSD) value for precision and homogenization tests were 2.815% and 4.978%, respectively. Meanwhile, the comparative and stability tests were tstat (0.136) < ttable (2.101) and |µ1-µ2| (1.502) ≤ 0.3×CV Horwitz. Obstinacy test value was tstat < ttable. It can be concluded that the HPLC  method for the determination of acesulfame-K in jelly drink product by HPLC has been valid and can be used for analysis with good performance.

Keywords: acesulfame-K, jelly drink, HPLC, validation

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Authors: Hankyu Lee, Seoung Bum Kim

Abstract:

The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

Abstract:

Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

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Authors: Ki-Yeo Kim

Abstract:

Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: Jaime R. Silva, Gabriel E. Reyes, Marianne Krause

Abstract:

Background: The two-polarity model of the depressive personality argues that experience is organized around two axes: interpersonal relatedness and self-definition. Differential emphasis on one of these poles defines three types of depressive experience: Anaclitic, Introjective or Mixed pattern. On the one hand, Anaclitic pattern has been conceptually related with exaggerated biological stress sensitivity. On the other hand, the Introjective pattern was linked with anhedonic symptomatology. The general aim of the study was to find empirical support for this relationship. Methods: 101 non-clinical individuals participated in two experimental sessions. During the first session, the biological stress reactivity (cortisol concentration in saliva) and the subjective stress perceived (self-reported) during the Trier Social Stress Test (TSST), were investigated. In the second session, a visual discrimination task with a specific reward system, to study the reinforcement sensitivity (anhedonia), was performed. Results: Results evidenced that participants with Introjective depressive symptoms showed a higher interpersonal sensitivity and a diminished sensitivity to reinforcement. In addition, results also indicated that such a group has a poor psychological detection of its exacerbated reactivity to stress, which is the opposite pattern evidenced amongst the Anaclitic group. Conclusions: In perspective, these results empirically support the two-polarity of the depressive personality model. Clinical implications are discussed.

Keywords: depression, interpersonal stress, personality, trier social stress test

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Authors: R. C. Law, Shirley Kang, T. Y. Hin, M. Z. Abdullah

Abstract:

LED technology has been evolving aggressively in recent years from incandescent bulb during older days to as small as chip scale package. It will continue to stay bright in future. As such, there is tremendous pressure to stay competitive in the market by optimizing products to next level of performance and reliability with the shortest time to market. This changes the conventional way of product design and development to virtual prototyping by means of Computer Aided Engineering (CAE). It comprises of the deployment of Finite Element Method (FEM) and Computational Fluid Dynamic (CFD). FEM accelerates the investigation for early detection of failures such as crack, improve the thermal performance of system and enhance solder joint reliability. CFD helps to simulate the flow pattern of molding material as a function of different temperature, molding parameters settings to evaluate failures like voids and displacement. This paper will briefly discuss the procedures and applications of FEM in thermal stress, solder joint reliability and CFD of compression molding in LED CSP. Integration of virtual prototyping in product development had greatly reduced the time to market. Many successful achievements with minimized number of evaluation iterations required in the scope of material, process setting, and package architecture variant have been materialized with this approach.

Keywords: LED, chip scale packaging (CSP), computational fluid dynamic (CFD), virtual prototyping

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Authors: Liaqat Ali, Khalid Farooq, Shafieullah Khan, Nasir Orakzai, Qudratullah

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Objectives: To determine the risk factors for high resistance of ciprofloxacin in complicated urinary tract infections. Materials and Methods: It is an analytical study that was conducted in the department of Urology (Team ‘C’) at Institute of Kidney Diseases Hayatabad Peshawar from 1st June 2012 till 31st December 2012. Total numbers of 100 patients with complicated UTI was selected in the study. Multivariate analysis and linear regression were performed for the detection of risk factors. All the data was recorded on structured Proforma and was analyzed on SPSS version 17. Results: The mean age of the patient was 55.6 years (Range 3-82 years). 62 patients were male while 38 patients were female. 66 isolates of E-Coli were found sensitive to ciprofloxacin while 34 isolates were found Resistant for ciprofloxacin. Using multivariate analysis and linear regression, an increasing age above 50 (p=0.002) History of urinary catheterization especially for bladder outflow obstruction (p=0.001) and previous multiple use of ciprofloxacin (p=0.001) and poor brand of ciprofloxacin were found to be independent risk factors for high resistance of ciprofloxacin. Conclusion: UTI is common illness across the globe with increasing trend of antimicrobial resistance for ciprofloxacin against E Coli in complicated UTI. The risk factors for emerging resistance are increasing age, urinary catheterization and multiple use and poor brand of ciprofloxacin.

Keywords: urinary tract infection, ciprofloxacin, urethral catheterization, antimicrobial resistance

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Authors: Anxuan Xie, Chun-Chan Yu

Abstract:

Survey evidence provides support that auditors can gain professional knowledge not only from client firms but also from teammates they work with. Furthermore, given that knowledge is accumulated in nature, along with the reality that auditors today must work in an environment of increased diversity, whether the attributes of teammates will influence the effects of knowledge sharing and accumulation and ultimately influence an audit partner’s audit quality should be interesting research issues. We test whether the gender of co-signers will moderate the effect of a lead partner’s cooperative experiences on financial restatements. Furthermore, if the answer is “yes”, we further investigate the underlying reasons. We use data from Taiwan because, according to Taiwan’s law, engagement partners, who are basically two certificate public accountants from the same audit firm, are required to disclose (i.e., sign) their names in the audit report of public companies since 1983. Therefore, we can trace each engagement partner’s historic direct cooperative (co-signing) records and get large-sample data. We find that the benefits of knowledge sharing manifest primarily via co-signing audit reports with audit partners of different gender from the lead engagement partners, supporting the argument that in an audit setting, accumulated gender-diverse working relationship is positively associated with knowledge sharing, and therefore improve lead engagements’ audit quality. This study contributes to the extant literature in the following ways. First, we provide evidence that in the auditing setting, the experiences accumulated from cooperating with teammates of a different gender from the lead partner can improve audit quality. Given that most studies find evidence of negative effects of surface-level diversity on team performance, the results of this study support the prior literature that the association between diversity and knowledge sharing actually hinges on the context (e.g., organizational culture, task complexity) and “bridge” (a pre-existing commonality among team members that can smooth the process of diversity toward favorable results) among diversity team members. Second, this study also provides practical insights with respect to the audit firms’ policy of knowledge sharing and deployment of engagement partners. For example, for audit firms that appreciate the merits of knowledge sharing, the deployment of auditors of different gender within an audit team can help auditors accumulate audit-related knowledge, which will further benefit the future performance of those audit firms. Moreover, nowadays, client firms also attach importance to the diversity of their engagement partners. As their policy goals, lawmakers and regulators also continue to promote a gender-diverse working environment. The findings of this study indicate that for audit firms, gender diversity will not be just a means to cater to those groups. Third, for audit committees or other stakeholders, they can evaluate the quality of existing (or potential) lead partners by tracking their co-signing experiences, especially whether they have gender-diverse co-signing experiences.

Keywords: co-signing experiences, audit quality, knowledge sharing, gender diversity

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Authors: Sarim Ahmad

Abstract:

The Single Cell Gel Electrophoresis Assay (SCGE, known as comet assay) is a potential, uncomplicated, sensitive and state-of-the-art technique for quantitating DNA damage at individual cell level and repair from in vivo and in vitro samples of eukaryotic cells and some prokaryotic cells, being popular in its widespread use in various areas including human biomonitoring, genotoxicology, ecological monitoring and as a tool for research into DNA damage or repair in different cell types in response to a range of DNA damaging agents, cancer risk and therapy. The method involves the encapsulation of cells in a low-melting-point agarose suspension, lysis of the cells in neutral or alkaline (pH > 13) conditions, and electrophoresis of the suspended lysed cells, resulting in structures resembling comets as observed by fluorescence microscopy; the intensity of the comet tail relative to the head reflects the number of DNA breaks. The likely basis for this is that loops containing a break lose their supercoiling and become free to extend towards the anode. This is followed by visual analysis with staining of DNA and calculating fluorescence to determine the extent of DNA damage. This can be performed by manual scoring or automatically by imaging software. The assay can, therefore, predict an individual’s tumor sensitivity to radiation and various chemotherapeutic drugs and further assess the oxidative stress within tumors and to detect the extent of DNA damage in various cancerous and precancerous lesions of oral cavity.

Keywords: comet assay, single cell gel electrophoresis, DNA damage, early detection test

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Authors: David Sudre

Abstract:

Sport in cinema, like sport in society, has been mainly concerned with men and masculinity. Whether in the boxing ring, on the basketball playgrounds, or on the soccer fields, these films have mostly focused on the trials and tribulations of male athletes, for whom women have very generally played secondary, often devalued and devaluing roles, such as that of the loving and indispensable woman to the victorious athlete, that of the dangerous femme fatale, or that of the woman as a sexual object. For more than a century, this film genre has, on the contrary, symbolized the dominant values of patriotism, heroism and contributed at the same time to build an ideal of hegemonic masculinity. With the exception of films such as The Grand National (1944) and Million Dollar Baby (2004), the most commercially successful films tell the story of men's adventures in sports. Today, thanks in part to the struggles of the feminist movement and subsequent societal advances, we are seeing an increase in the number of women in increasingly prominent roles in sports films. Indeed, there seems to be a general shift in popular cinema toward women playing major characters in big-budget productions that have also achieved critical and commercial success. However, if, at first sight, the increase in the number of roles given to women suggests an evolution and a more positive image of them on the screen, it will be necessary to see how their representation is really characterized when they are young and occupy major roles in this type of film. In order to answer this question, we will rely on the results of research conducted on a corpus of 28 sports films in which a young woman plays the main role in the story. All of these productions are fictional (not documentary), mostly American, and distributed by major film studios. The chosen sports teen movies are among the biggest commercial successes of the genre and aim to make the maximum profit and occupy the most dominant positions within the "commercial pole" of the cinematic field. Therefore, this research will allow us, although a change has taken place in the last decades in the number of main roles granted to sportswomen, to decode the sociological subtext of these popular sports films for teenagers. The aim is to reveal how these sports films convey a conservative ideology that participates, on the one hand, in the maintenance of patriarchy and, on the other hand, in the dissemination of stereotyped, negative, and regressive images of young women athletes.

Keywords: cinema, sport, gender, youth, representations, inequality, stereotypes

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Authors: Seyyed Mohammad Amin Mousavi Sagharchi, Alireza Mahmoudi Nasab, Tim Bakker

Abstract:

Introduction: Mycobacterium tuberculosis (MTB) is the most intelligent bacterium that existed in the world to our best knowledge. This bacterium can cause tuberculosis (TB) which is responsible for its spread speed and murder of millions of people around the world. MTB has the practical function to escape from anti-tuberculosis drugs (AT), for this purpose, it handles some mutations in the main genes and creates new patterns for inhibited genes. Method and materials: Researchers have their best tries to safely isolate MTB from the sputum specimens of 35 patients in some hospitals in the Tehran province and detect MTB by culture on Löwenstein-Jensen (LJ) medium and microscopic examination. DNA was extracted from the established bacterial colony by enzymatic extraction method. It was amplified by the polymerase chain reaction (PCR) method, reverse hybridization, and evaluation for detection of resistance genes; generally, researchers apply GenoType MTBDRplus assay. Results: Investigations of results declare us that 21 of the isolated specimens (about 60%) have mutation in rpoB gene, which resisted to rifampicin (most prevalence), and 8 of them (about 22.8%) have mutation in katG or inhA genes which resisted to isoniazid. Also, 4 of them (about 11.4%) don't have any mutation, and 2 of them (about 5.7%) have mutation in every three genes, which makes them resistant to the two drugs mentioned above. Conclusion: Rifampicin and isoniazid are two essential AT that using in the first line of treatment. Resistance in rpoB, and katG, and inhA genes related to mentioned drugs lead to ineffective treatment.

Keywords: mycobacterium tuberculosis, tuberculosis, drug resistance, isoniazid, rifampicin

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