Search results for: biomarker detection

Authors: Tshegofatso Rambau, Tonderai Muchenje

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Zero-day attacks (ZDA) are increasing day by day; there are many vulnerabilities in systems and software that date back decades. Companies keep discovering vulnerabilities in their systems and software and work to release patches and updates. A zero-day vulnerability is a software fault that is not widely known and is unknown to the vendor; attackers work very quickly to exploit these vulnerabilities. These are major security threats with a high success rate because businesses lack the essential safeguards to detect and prevent them. This study focuses on the factors and techniques that can help us detect zero-day attacks. There are various methods and techniques for detecting vulnerabilities. Various companies like edges can offer penetration testing and smart vulnerability management solutions. We will undertake literature studies on zero-day attacks and detection methods, as well as modeling approaches and simulations, as part of the study process.

Keywords: zero-day attacks, exploitation, vulnerabilities

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Authors: Sundus Ayyaz, Saad Rehman, Usman Qamar

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Software Architecture is the basic structure of software that states the development and advancement of a software system. Software architecture is also considered as a significant tool for the construction of high quality software systems. A clean design leads to the control, value and beauty of software resulting in its longer life while a bad design is the cause of architectural erosion where a software evolution completely fails. This paper discusses the occurrence of software architecture erosion and presents a set of methods for the detection, declaration and prevention of architecture erosion. The causes and symptoms of architecture erosion are observed with the examples of prescriptive and descriptive architectures and the practices used to stop this erosion are also discussed by considering different types of software erosion and their affects. Consequently finding and devising the most suitable approach for fighting software architecture erosion and in some way reducing its affect is evaluated and tested on different scenarios.

Keywords: software architecture, architecture erosion, prescriptive architecture, descriptive architecture

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Authors: R. Sanchez-Salcedo, N. H. Voelcker

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Currently, low breast milk production in women is one of the leading health complications in infants. Recently, It has been demonstrated that exclusive breastfeeding, especially up to a minimum of 6 months, significantly reduces respiratory and gastrointestinal infections, which are the main causes of death in infants. However, the current data shows that a high percentage of women stop breastfeeding their children because they perceive an inadequate supply of milk, and only 45% of children are breastfeeding under 6 months. It is, therefore, clear the necessity to design and develop a biosensor that is sensitive and selective enough to identify and validate a panel of milk biomarkers that allow the early diagnosis of this condition. In this context, electrochemical biosensors could be a powerful tool for assessing all the requirements in terms of reliability, selectivity, sensitivity, cost efficiency and potential for multiplex detection. Moreover, they are suitable for the development of POC devices and wearable sensors. In this work, we report the development of two types of sensing platforms towards several biomarkers, including miRNAs and hormones present in breast milk and dysregulated in this pathological condition. The first type of sensing platform consists of an enzymatic sensor for the detection of lactose, one of the main components in milk. In this design, we used gold surface as an electrochemical transducer due to the several advantages, such as the variety of strategies available for its rapid and efficient functionalization with bioreceptors or capture molecules. For the second type of sensing platform, nanoporous silicon film (pSi) was chosen as the electrode material for the design of DNA sensors and aptasensors targeting miRNAs and hormones, respectively. pSi matrix offers a large superficial area with an abundance of active sites for the immobilization of bioreceptors and tunable characteristics, which increase the selectivity and specificity, making it an ideal alternative material. The analytical performance of the designed biosensors was not only characterized in buffer but also validated in minimally treated breastmilk samples. We have demonstrated the potential of an electrochemical transducer on pSi and gold surface for monitoring clinically relevant biomarkers associated with the heightened risk of low milk production in women. This approach, in which the nanofabrication techniques and the functionalization methods were optimized to increase the efficacy of the biosensor highly provided a foundation for further research and development of targeted diagnosis strategies.

Keywords: biosensors, electrochemistry, early diagnosis, clinical markers, miRNAs

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Authors: Kangkang Wu, Kaizhi Wang, Zhijun Yuan

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This paper deals with a mini radar system aimed at detecting small targets at the low latitude. The radar operates at Ku-band in the frequency modulated continuous wave (FMCW) mode with two receiving channels. The radar system has the characteristics of compactness, mobility, and low power consumption. This paper focuses on the implementation of the radar system, and the Block least mean square (Block LMS) algorithm is applied to minimize the fortuitous distortion. It is validated from a series of experiments that the track of the unmanned aerial vehicle (UAV) can be easily distinguished with the radar system.

Keywords: unmanned aerial vehicle (UAV), interference, Block Least Mean Square (Block LMS) Algorithm, Frequency Modulated Continuous Wave (FMCW)

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Authors: Prabhakar Sathujoda

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Vibration analysis of a misaligned rotor coupling bearing system has been carried out while decelerating through its critical speed. The finite element method (FEM) is used to model the rotor system and simulate flexural vibrations. A flexible coupling with a frictionless joint is considered in the present work. The continuous wavelet transform is used to extract the misalignment features from the simulated time response. Subcritical speeds at one-half, one-third, and one-fourth the critical speed have appeared in the wavelet transformed vibration response of a misaligned rotor coupling bearing system. These features are also verified through a parametric study.

Keywords: Continuous Wavelet Transform, Flexible Coupling, Rotor System, Sub Critical Speed

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Authors: Desouky Abd El Haleem, Sahar Zaki

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This work was conducted to develop a one-step multiplex PCR system for rapid, sensitive, and specific detection of three different bacterial pathogens, Escherichia coli, Pseudomonas aeruginosa, and Salmonella spp, directly in wastewater without prior isolation on selective media. As a molecular confirmatory test after isolation of the pathogens by classical microbiological methods, PCR-RFLP of their amplified 16S rDNA genes was performed. It was observed that the developed protocols have significance impact in the ability to detect sensitively, rapidly and specifically the three pathogens directly in water within short-time, represents a considerable advancement over more time-consuming and less-sensitive methods for identification and characterization of these kinds of pathogens.

Keywords: multiplex PCR, bacterial pathogens, Escherichia coli, Pseudomonas aeruginosa, Salmonella spp.

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Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

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Authors: Srinivas Bathini, Duraichelvan Raju, Simona Badilescu, Muthukumaran Packirisamy

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A bio-sensing method, based on the plasmonic property of gold nano-islands, has been developed for detection of exosomes in a clinical setting. The position of the gold plasmon band in the UV-Visible spectrum depends on the size and shape of gold nanoparticles as well as on the surrounding environment. By adsorbing various chemical entities, or binding them, the gold plasmon band will shift toward longer wavelengths and the shift is proportional to the concentration. Exosomes transport cargoes of molecules and genetic materials to proximal and distal cells. Presently, the standard method for their isolation and quantification from body fluids is by ultracentrifugation, not a practical method to be implemented in a clinical setting. Thus, a versatile and cutting-edge platform is required to selectively detect and isolate exosomes for further analysis at clinical level. The new sensing protocol, instead of antibodies, makes use of a specially synthesized polypeptide (Vn96), to capture and quantify the exosomes from different media, by binding the heat shock proteins from exosomes. The protocol has been established and optimized by using a glass substrate, in order to facilitate the next stage, namely the transfer of the protocol to a microfluidic environment. After each step of the protocol, the UV-Vis spectrum was recorded and the position of gold Localized Surface Plasmon Resonance (LSPR) band was measured. The sensing process was modelled, taking into account the characteristics of the nano-island structure, prepared by thermal convection and annealing. The optimal molar ratios of the most important chemical entities, involved in the detection of exosomes were calculated as well. Indeed, it was found that the results of the sensing process depend on the two major steps: the molar ratios of streptavidin to biotin-PEG-Vn96 and, the final step, the capture of exosomes by the biotin-PEG-Vn96 complex. The microfluidic device designed for sensing of exosomes consists of a glass substrate, sealed by a PDMS layer that contains the channel and a collecting chamber. In the device, the solutions of linker, cross-linker, etc., are pumped over the gold nano-islands and an Ocean Optics spectrometer is used to measure the position of the Au plasmon band at each step of the sensing. The experiments have shown that the shift of the Au LSPR band is proportional to the concentration of exosomes and, thereby, exosomes can be accurately quantified. An important advantage of the method is the ability to discriminate between exosomes having different origins.

Keywords: exosomes, gold nano-islands, microfluidics, plasmonic biosensing

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Authors: Sharanya C. H., Pragathi M., Vathsala R. S., Theja K. V., Yashaswini S.

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Identifying counterfeit products have become increasingly important in the product manufacturing industries in recent decades. This current ongoing product issue of counterfeiting has an impact on company sales and profits. To address the aforementioned issue, a functional blockchain technology was implemented, which effectively prevents the product from being counterfeited. By utilizing the blockchain technology, consumers are no longer required to rely on third parties to determine the authenticity of the product being purchased. Blockchain is a distributed database that stores data records known as blocks and several databases known as chains across various networks. Counterfeit products are identified using a QR code reader, and the product's QR code is linked to the blockchain management system. It compares the unique code obtained from the customer to the stored unique code to determine whether or not the product is original.

Keywords: blockchain, ethereum, QR code

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Authors: Muhammad Irfan

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The rise of radicalization within Islam has spawned a new era of global terror. The battlefield Successes of ISIS and the Taliban are fuelled by an ideological war waged, largely and successfully, in the media arena. This research will examine how Islamic extremist groups are using media modalities and populist narratives to influence migrant Muslim populations in Europe towards extremism. In 2014, ISIS shocked the world in exporting horrifically graphic forms of violence on social media. Their Muslim support base was largely disgusted and reviled. In response, they reconfigured their narrative by introducing populist 'hooks', astutely portraying the Muslim populous as oppressed and exploited by unjust, corrupt autocratic regimes and Western power structures. Within this crucible of real and perceived oppression, hundreds of thousands of the most desperate, vulnerable and abused migrants left their homelands, risking their lives in the hope of finding peace, justice, and prosperity in Europe. Instead, many encountered social stigmatization, detention and/or discrimination for being illegal migrants, for lacking resources and for simply being Muslim. This research will examine how Islamic extremist groups are exploiting the disenfranchisement of these migrant populations and using populist messaging on social media to influence them towards violent extremism. ISIS, in particular, formulates specific encoded messages for newly-arriving Muslims in Europe, preying upon their vulnerability. Violence is posited, as a populist response, to the tyranny of European oppression. This research will analyze the factors and indicators which propel Muslim migrants along the spectrum from resilience to violence extremism. Expected outcomes are identification of factors which influence vulnerability towards violent extremism; an early-warning detection framework; predictive analysis models; and de-radicalization frameworks. This research will provide valuable tools (practical and policy level) for European governments, security stakeholders, communities, policy-makers, and educators; it is anticipated to contribute to a de-escalation of Islamic extremism globally.

Keywords: populism, radicalization, de-radicalization, social media, ISIS, Taliban, shariah, jihad, Islam, Europe, political communication, terrorism, migrants, refugees, extremism, global terror, predictive analysis, early warning detection, models, strategic communication, populist narratives, Islamic extremism

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Authors: Cristina Fernandez, Felix Amparano, John Tumberger, Stephani Stancil, Sarah Hampl, Brooke Sweeney, Amy R. Beck, Helena H Laroche, Jared Tucker, Eileen Chaves, Sara Gould, Matthew Lindquist, Lora Edwards, Renee Arensberg, Meredith Dreyer, Jazmine Cedeno, Alleen Cummins, Jennifer Lisondra, Katie Cox, Kelsey Dean, Rachel Perera, Nicholas A. Clark

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Background: Adolescents with obesity are at higher risk of disordered eating than the general population. Detection of eating disorders (ED) is difficult. Screening questionnaires may aid in early detection of ED. Our team’s prior efforts focused on increasing ED screening rates to ≥90% using a validated 10-question adolescent binge eating disorder screening questionnaire (ADO-BED). This aim was achieved. We then aimed to improve treatment plan initiation of patients ≥12 years of age who screen positive for BED within our WMC from 33% to 70% within 12 months. Methods: Our WMC is within a tertiary-care, free-standing children’s hospital. A3, an improvement framework, was used. A multidisciplinary team (physicians, nurses, registered dietitians, psychologists, and exercise physiologists) was created. The outcome measure was documentation of treatment plan initiation of those who screen positive (goal 70%). The process measure was ADO-BED screening rate of WMC patients (goal ≥90%). Plan-Do-Study-Act (PDSA) cycle 1 included provider education on current literature and treatment plan initiation based upon ADO-BED responses. PDSA 2 involved increasing documentation of treatment plan and retrain process to providers. Pre-defined treatment plans were: 1) repeat screen in 3-6 months, 2) resources provided only, or 3) comprehensive multidisciplinary weight management team evaluation. Run charts monitored impact over time. Results: Within 9 months, 166 patients were seen in WMC. Process measure showed sustained performance above goal (mean 98%). Outcome measure showed special cause improvement from mean of 33% to 100% (n=31). Of treatment plans provided, 45% received Plan 1, 4% Plan 2, and 46% Plan 3. Conclusion: Through a multidisciplinary improvement team approach, we maintained sustained ADO-BED screening performance, and, prior to our 12-month timeline, achieved our project aim. Our efforts may serve as a model for other multidisciplinary WMCs. Next steps may include expanding project scope to other WM programs.

Keywords: obesity, pediatrics, clinic, eating disorder

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Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

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About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

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Authors: C. Slim

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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

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Authors: Rade M. Ciric, Sasa Mandic

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Students of Higher Education Technical School of Professional Studies, in Novi Sad follow the subject Maintenance of electric power equipment at the Electrotechnical Department. This paper presents educational plan and program of the subject Maintenance of electric power equipment. The course deals with the problems of preventive and investing maintenance of transformer stations (TS), performing and maintenance of grounding of TS and pillars, as well as tracing and detection the location of the cables failure. There is a special elaborated subject concerning the safe work conditions for the electrician during network maintenance, as well as the basics of making and keeping technical documentation of the equipment.

Keywords: educational plan and program, electric power equipment, maintenance, technical documentation, safe work

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Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

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Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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Authors: Franck Acho

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This is a chronic metabolic disorder which is a fast-growing global problem with a huge social, health, and economic consequences. It is estimated that in 2010 there were globally 285 million people (approximately 6.4% of the adult population) suffering from this disease. This number is estimated to increase to 430 million in the absence of better control or cure. An ageing population and obesity are two main reasons for the increase. Diabetes mellitus is a chronic heterogeneous metabolic disorder with a complex pathogenesis. It is characterized by elevated blood glucose levels or hyperglycemia, which results from abnormalities in either insulin secretion or insulin action or both. Hyperglycemia manifests in various forms with a varied presentation and results in carbohydrate, fat, and protein metabolic dysfunctions. Long-term hyperglycemia often leads to various microvascular and macrovascular diabetic complications, which are mainly responsible for diabetes-associated morbidity and mortality. Hyperglycemia serves as the primary biomarker for the diagnosis of diabetes as well. Furthermore, it has been shown that almost 50% of the putative diabetics are not diagnosed until 10 years after onset of the disease, hence the real prevalence of global diabetes must be astronomically high. This study was conducted in a locality to access the level of knowledge, awareness and risk factors associated with people leaving with diabetes mellitus. A month before the screening was to be conducted, a health screening in some selected churches and on the local community radio as well as on relevant WhatsApp groups were advertised. A general health talk was delivered by the head of the screening unit to all attendees who were all educated on the procedure to be carried out with benefits and any possible discomforts after which the attendee’s consent was obtained. Evaluation of the participants for any leads to the diabetes selected for the screening was done by taking adequate history and physical examinations such as excessive thirst, increased urination, tiredness, hunger, unexplained weight loss, feeling irritable or having other mood changes, having blurry vision, having slow-healing sores, getting a lot of infections, such as gum, skin and vaginal infections. Out of the 94 participants the finding show that 78 were females and 16 were males, 70.21% of participants with diabetes were between the ages of 60-69yrs.The study found that only 10.63% of respondents declared a good level of knowledge of diabetes. Out of 3 symptoms of diabetes analyzed in this study, high blood sugar (58.5%) and chronic fatigue (36.17%) were the most recognized. Out of 4 diabetes risk factors analyzed in this study, obesity (21.27%) and unhealthy diet (60.63%) were the most recognized diabetes risk factors, while only 10.6% of respondents indicated tobacco use. The diabetic foot was the most recognized diabetes complication (50.57%), but some the participants indicated vision problems (30.8%),or cardiovascular diseases (20.21%) as diabetes complications.

Keywords: diabetes mellitus, non comunicable disease, general health talk, hyperglycemia

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Background and Aims: This meta-analysis aimed to evaluate the effect of vitamin D supplementation on key metabolic and cardiovascular parameters, such as glycated hemoglobin (HbA1C), fasting blood sugar (FBS), low-density lipoprotein (LDL), high-density lipoprotein (HDL), systolic blood pressure (SBP), and total vitamin D levels in patients with Type 2 diabetes mellitus (T2DM). Methods: A systematic search was performed across databases, including PubMed, Scopus, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov, from January 1990 to January 2024. A total of 4,177 relevant studies were initially identified. Using an unsupervised K-means clustering algorithm, publications were grouped based on common text features. Maximum entropy classification was then applied to filter studies that matched a pre-identified training set of 139 potentially relevant articles. These selected studies were manually screened for relevance. A parallel manual selection of all initially searched studies was conducted for validation. The final inclusion of studies was based on full-text evaluation, quality assessment, and meta-regression models using random effects. Sensitivity analysis and publication bias assessments were also performed to ensure robustness. Results: The unsupervised K-means clustering algorithm grouped the patients based on their responses to vitamin D supplementation, using key biomarkers such as HbA1C, FBS, LDL, HDL, SBP, and total vitamin D levels. Two primary clusters emerged: one representing patients who experienced significant improvements in these markers and another showing minimal or no change. Patients in the cluster associated with significant improvement exhibited lower HbA1C, FBS, and LDL levels after vitamin D supplementation, while HDL and total vitamin D levels increased. The analysis showed that vitamin D supplementation was particularly effective in reducing HbA1C, FBS, and LDL within this cluster. Furthermore, BMI, weight gain, and disease duration were identified as factors that influenced cluster assignment, with patients having lower BMI and shorter disease duration being more likely to belong to the improvement cluster. Conclusion: The findings of this machine learning-assisted meta-analysis confirm that vitamin D supplementation can significantly improve glycemic control and reduce the risk of cardiovascular complications in T2DM patients. The use of automated screening techniques streamlined the process, ensuring the comprehensive evaluation of a large body of evidence while maintaining the validity of traditional manual review processes.

Keywords: HbA1C, T2DM, SBP, FBS

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: C. Villamizar, M. Serrato

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In the pursuit of athletic performance, the role of physical training which is determined by a number of charges or taxes on physiological stress and musculoskeletal systems of the human body generated by the intensity and duration is fundamental. Given the physical demands of these activities both training and competitive must take into account the optimal relationship with a straining process recovery post favoring the process of overcompensation which aims to facilitate the return and rising energy potential and protein synthesis also of different tissues. Allowing muscle function returns to baseline or pre-exercise states. If this recovery process is not performed or is not allowed in a proper way, will result in an increased state of fatigue. Active recovery, is one of the strategies implemented in the sport for a return to pre-exercise physiological states. However, there are some adverse assumptions regarding the negative effects, as is the possibility of increasing the degradation of muscle glycogen and thus delaying the synthesis thereof. For them, it is necessary to investigate what would be the effects generated application made at different times after the effort. The aim of this study was to determine the effects of active recovery post effort made at three different times: immediately, at 12 and 24 hours on biochemical markers creatine kinase in youth soccer player’s categories. A randomized controlled trial with allocation to three groups was performed: A. active recovery immediately after the effort; B. active recovery performed at 12 hours after the effort; C. active recovery made at 24 hours after the effort. This study included 27 subjects belonging to a Colombian soccer team of the second division. Vital signs, weight, height, BMI, the percentage of muscle mass, fat mass percentage, personal medical history, and family were valued. The velocity, explosive force and Creatin Kinase (CK) in blood were tested before and after interventions. SAFT 90 protocol (Soccer Field specific Aerobic Test) was applied to participants for generating fatigue. CK samples were taken one hour before the application of the fatigue test, one hour after the fatigue protocol and 48 of the initial CK sample. Mean age was 18.5 ± 1.1 years old. Improvements in jumping and speed recovery the 3 groups (p < 0.05), but no statistically significant differences between groups was observed after recuperation. In all participants, there was a significant increment of CK when applied SAFT 90 in all the groups (median 103.1-111.1). The CK measurement after 48 hours reflects a recovery in all groups, however the group C, a decline below baseline levels of -55.5 (-96.3 /-20.4) which is a significant find. Other research has shown that CK does not return quickly to their baseline, but our study shows that active recovery favors the clearance of CK and also to perform recovery 24 hours after the effort generates higher clearance of this biomarker.

Keywords: active recuperation, creatine phosphokinase, post training, young soccer players

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Authors: Nadhiya N. Subramony, Jenifer Vaughan, Lesley E. Scott

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In South Africa, the World Health Organisation estimated 454000 new cases of Mycobacterium tuberculosis (M.tb) infection (MTB) in 2015. Disseminated tuberculosis arises from the haematogenous spread and seeding of the bacilli in extrapulmonary sites. The gold standard for the detection of MTB in bone marrow is TB culture which has an average turnaround time of 6 weeks. Histological examinations of trephine biopsies to diagnose MTB also have a time delay owing mainly to the 5-7 day processing period prior to microscopic examination. Adding to the diagnostic delay is the non-specific nature of granulomatous inflammation which is the hallmark of MTB involvement of the bone marrow. A Ziehl-Neelson stain (which highlights acid-fast bacilli) is therefore mandatory to confirm the diagnosis but can take up to 3 days for processing and evaluation. Owing to this delay in diagnosis, many patients are lost to follow up or remain untreated whilst results are awaited, thus encouraging the spread of undiagnosed TB. The Xpert® MTB/RIF (Cepheid, Sunnyvale, CA) is the molecular test used in the South African national TB program as the initial diagnostic test for pulmonary TB. This study investigates the optimisation and performance of the Xpert® MTB/RIF on bone marrow aspirate specimens (BMA), a first since the introduction of the assay in the diagnosis of extrapulmonary TB. BMA received for immunophenotypic analysis as part of the investigation into disseminated MTB or in the evaluation of cytopenias in immunocompromised patients were used. Processing BMA on the Xpert® MTB/RIF was optimised to ensure bone marrow in EDTA and heparin did not inhibit the PCR reaction. Inactivated M.tb was spiked into the clinical bone marrow specimen and distilled water (as a control). A volume of 500mcl and an incubation time of 15 minutes with sample reagent were investigated as the processing protocol. A total of 135 BMA specimens had sufficient residual volume for Xpert® MTB/RIF testing however 22 specimens (16.3%) were not included in the final statistical analysis as an adequate trephine biopsy and/or TB culture was not available. Xpert® MTB/RIF testing was not affected by BMA material in the presence of heparin or EDTA, but the overall detection of MTB in BMA was low compared to histology and culture. Sensitivity of the Xpert® MTB/RIF compared to both histology and culture was 8.7% (95% confidence interval (CI): 1.07-28.04%) and sensitivity compared to histology only was 11.1% (95% CI: 1.38-34.7%). Specificity of the Xpert® MTB/RIF was 98.9% (95% CI: 93.9-99.7%). Although the Xpert® MTB/RIF generates a faster result than histology and TB culture and is less expensive than culture and drug susceptibility testing, the low sensitivity of the Xpert® MTB/RIF precludes its use for the diagnosis of MTB in bone marrow aspirate specimens and warrants alternative/additional testing to optimise the assay.

Keywords: bone marrow aspirate , extrapulmonary TB, low sensitivity, Xpert® MTB/RIF

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Authors: Gasim Alandjani

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This research paper investigates the use of artificial intelligence (AI) and the Internet of Things (IoT) to improve eye healthcare; it concentrates on eye vision assessment, early discovery of eye ailments, and individualised vision correction. The study offers a broad review of literature and methodology; it features vital findings and inferences for advancing patient results, boosting admittance to care, elevating resource apportionment, and directing future research and practice. The study concluded that the assimilation of AI and IoT advancements provides progressive answers to traditional hurdles in eye healthcare, guaranteeing more precise, comprehensive, and individualised interventions for patients globally. The study emphasizes the significance of sustained innovation and the application of AI and IoT-driven methodologies to improve eye healthcare and vision for forthcoming generations.

Keywords: AI, IoT, eye vision assessment, computer engineering

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Authors: Nimisha Jadon, Rajeev Jain, Swati Sharma

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A chemically modified carbon paste sensor has been developed for the simultaneous determination of amlodipine (AML) and nebivolol (NBV). Carbon paste electrode (CPE) was fabricated by the addition of Gr/PANI-CeO2. Gr/PANI-CeO2/CPE has achieved excellent electrocatalytic activity and sensitivity. AML and NBV exhibited oxidation peaks at 0.70 and 0.90 V respectively on Gr/ PANI-CeO2/CPE. The linearity range of AML and NBV was 0.1 to 1.6 μgmL-1 in BR buffer (pH 8.0). The Limit of detection (LOD) was 20.0 ngmL-1 for AML and 30.0 ngmL-1 for NBV and limit of quantification (LOQ) was 80.0 ngmL-1 for AML and 100 ngmL-1 for NBV respectively. These analyses were also determined in pharmaceutical formulation and human serum and good recovery was obtained for the developed method.

Keywords: amlodipine, nebivolol, square wave voltammetry, carbon paste electrode, simultaneous quantification

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Authors: Firas Gerges, Frank Y. Shih

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Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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Authors: Elena Maria Scalisi

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Currently, photodegradation by nanoparticles (NPs) is a common solution for wastewater treatment. Nanoparticles are efficient for removing organic and inorganic pollutants, heavy metals from wastewater and killing microorganisms through environmentally friendly. In this context, the major representative of photocatalytic technology for industrial wastewater treatment are TiO₂ nanoparticles (TiO₂-NPs). TiO₂-NPs have a strong catalytic activity that depends to their physicochemical properties. Thanks to their small size (between 1-100 nm), nanoparticles occupy less volume, then their surface area increases. The increase in the surface-to-volume ratio results in the increase of the particle surface energy, which improve their reactivity potential. However, these unique properties represent risks to the ecosystems and organisms when unintentionally TiO₂-NPs are release into the environment and absorbed by living organisms. Several studies confirm that there is a high level of interest concerning the safety of TiO₂-NPs in the aquatic environment, furthermore, ecotoxicological tools are useful to correctly evaluate their toxicity. In the current study, we aimed to characterize potential toxic effects of TiO₂-NP suspension to zebrafish during embryo-larval stages to evaluate parameters such as survival rates, malformation, hatching, the overall length of the larvae heartbeat, and biochemical biomarkers that reflect the acute toxicity and sublethal effects of TiO₂-NPs. Zebrafish embryos were exposed to titanium dioxide nanoparticles (TiO₂-NPs at 1mg/L, 2mg/L, and 4mg/L) from fertilization to the free swimming stage (144hpf). Every day, we recorded the toxicological endpoints, moreover, immunohistochemical analysis has been performed at the end of the exposure. In particular, we have evaluate the expression of the following biomarkers: Heat Shock Protein 70 (HSP70), Poly ADP-Ribose Polymerase-1 (PARP-1), Metallothioneins (MTs). Our results have shown that hatch ability, survival, and malformation rate were not affected by TiO₂ NPs at these exposure levels. However, TiO₂-NPs caused an increase of heartbeat and reduction of body length; at the same time, TiO₂-NPs have inducted the production of ROS and the expression of oxidative stress biomarkers HSP70 and PARP-1. Hight positivity for PARP-1 at all concentration tested was observed. As regards MT, positivity was found in the expression of this biomarker in the whole body of the embryo, with the exception of the end of the tail. Metallothioneins (MT) are biomarkers widely used in environmental monitoring programs for aquatic creatures. At the light of our results i.e. no death until the end of the experiment (144hpf), no malformation and expression of the biomarkers mentioned, it is evident that zebrafish larvae with their natural detoxification pathways are able to resist the presence of toxic substances and then they can tolerate the presence of metal concentrations. However, an excessive oxidative state can compromise cell function, therefore the uncontrolled release of nanoparticles into the environment is severe and must be constantly monitored.

Keywords: nanoparticles, embryo zebrafish, HSP70, PARP-1

Procedia PDF Downloads 139

Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

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Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City

Procedia PDF Downloads 434

Authors: Seema Dhariwal, Kiran Maan, Ruchi Baghel, Apoorva Sharma, Poonam Rana

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Introduction: Traumatic brain injury (TBI) is defined as the temporary or permanent alteration in brain function and pathology caused by an external mechanical force. It represents the leading cause of mortality and morbidity among children and youth individuals. Various models of TBI in rodents have been developed in the laboratory to mimic the scenario of injury. Blast overpressure injury is common among civilians and military personnel, followed by accidents or explosive devices. In addition to this, the lateral Controlled cortical impact (CCI) model mimics the blunt, penetrating injury. Method: In the present study, we have developed two different mild TBI models using blast and CCI injury. In the blast model, helium gas was used to create an overpressure of 130 kPa (±5) via a shock tube, and CCI injury was induced with an impact depth of 1.5mm to create diffusive and focal injury, respectively. C57BL/6J male mice (10-12 weeks) were divided into three groups: (1) control, (2) Blast treated, (3) CCI treated, and were exposed to different injury models. Serum was collected on Day1 and day7, followed by biphasic extraction using MTBE/Methanol/Water. Prepared samples were separated on Charged Surface Hybrid (CSH) C18 column and acquired on UHPLC-Q-TOF-MS using ESI probe with inhouse optimized parameters and method. MS peak list was generated using Markerview TM. Data were normalized, Pareto-scaled, and log-transformed, followed by multivariate and univariate analysis in metaboanalyst. Result and discussion: Untargeted profiling of lipids generated extensive data features, which were annotated through LIPID MAPS® based on their m/z and were further confirmed based on their fragment pattern by LipidBlast. There is the final annotation of 269 features in the positive and 182 features in the negative mode of ionization. PCA and PLS-DA score plots showed clear segregation of injury groups to controls. Among various lipids in mild blast and CCI, five lipids (Glycerophospholipids {PC 30:2, PE O-33:3, PG 28:3;O3 and PS 36:1 } and fatty acyl { FA 21:3;O2}) were significantly altered in both injury groups at Day 1 and Day 7, and also had VIP score >1. Pathway analysis by Biopan has also shown hampered synthesis of Glycerolipids and Glycerophospholipiods, which coincides with earlier reports. It could be a direct result of alteration in the Acetylcholine signaling pathway in response to TBI. Understanding the role of a specific class of lipid metabolism, regulation and transport could be beneficial to TBI research since it could provide new targets and determine the best therapeutic intervention. This study demonstrates the potential lipid biomarkers which can be used for injury severity diagnosis and identification irrespective of injury type (diffusive or focal).

Keywords: LipidBlast, lipidomic biomarker, LIPID MAPS®, TBI

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Authors: Shamim Mushtaq, Moazzam Shahid

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Breast cancer (BC) claims the lives of half a million women every year and is the most common cause of death in the developing world. In 2019, it was estimated that BC alone accounts for 15% of all cancer deaths in younger women (aged < 45 years old) with advanced-stage lung metastasis. According to the World Health Organization & International Union against Cancer, in Asia, a high number of cancer-related deaths will be observed in 2020, whereas the burden will be reduced in Western countries due to awareness about the disease, better health facilities and advanced treatments. In the last 15 years, it has been reported that the incidence of BC has increased by 1.1% among Asian compared to the US population from 2003 to 2012. To date, several BC biological subtypes have been reported so far, which are associated with different treatment responses. The heterogeneity and diversity of BC reflected these different subtypes, including Luminal A (23.7% prevalence) and B (38.8% prevalence) that have pathological estrogen receptor (ER+)-positive tumors, the human epidermal growth factor receptor 2 (HER2) (11.2% prevalence) and triple-negative breast cancer (TNBC) (25% prevalence). According to Shaukat Khanum Memorial Cancer Hospital and Research Centre – Pakistan, ten years of data showed that among 636 BC patients, 30.5% had TNBC who were <40 years of age, which is an extremely alarming situation. Therefore, there is a dire need to explore and develop therapeutic targets for the treatment of early TNBC. Since the last decade, unfortunately, there has been little success in understanding the complexity of TNBC and in discovering new biological therapeutic targets. However, conventional chemotherapy is the only choice of treatment for TNBC patients. Many investigators revealed advances in multi-omics (multiple "omes", e.g., genome, proteome, transcriptome, epigenome, and microbiome) which were later identified as actionable targets and increased prevalence in TNBC patients. However, various drugs have been identified so far which are related to a particular diagnostic and prognostic biomarker. For example, Epidermal growth factor receptor ( EGFR or ErbB-1), HER-2/neu (ErbB-2), HER-3 (ErbB-3), and HER-4 (ErbB-4). Protein Transglin-2 (TAGLN 2 ) and Profilins-1 (Pfn-1 ) are the ubiquitously expressed large family of proteins present in all eukaryotes, enabling actin cytoskeletal reorganization. It is known that the oncogenic transformation of cells is accompanied by alteration in the actin cytoskeleton. There are causal connections between altered expression of actin cytoskeletal regulators and cancer progression. Our case-control study identified TAGLN-2 and Pfn-1 proteins in TNBC blood by mass spectrometry. Both TAGLN-2 and Pfn-1 proteins are differentially expressed in early and advanced stages of TNBS patients, which could be potential predictors or therapeutic targets for TNBC.

Keywords: TNBC, blood biomarkers, mass spectrometry, qPCR, ELISA

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Authors: Dêivisson Alves Anjos, Blenda Fonseca Aires Teles, Queitiane Castro Costa

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Fire is one of the biggest dangers for factories, warehouses, mills, among other places, causing unimaginable damage, because besides the material damage also directly affects the lives of workers who are likely to suffer death or very serious consequences. This protection of the lives of these people should be taken seriously, always seeking safety. Thus investment in security and monitoring equipment must be high, so you can prevent or reduce the impacts of a possible fire. Our device, made in PIC micro controller monitors the temperature and the presence of gas in the environment, it sends the data via Bluetooth device to a developed in LabVIEW interface saves these data continuously and alert if the temperature exceeds the allowed or some gas is detected. Currently the device is in operation and can perform several tests, as well as use in different areas for which you need anti-fire protection.

Keywords: pic, bluetooth, fire, temperature, gas, LabVIEW

Procedia PDF Downloads 535

Authors: Valeria Velasco, Ana M. Bonilla, José L. Vergara, Alcides Lofa, Jorge Campos, Pedro Rojas-García

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Staphylococcus aureus is both commensal bacterium and opportunistic pathogen that can cause different diseases in humans and can rapidly develop antimicrobial resistance. Since this bacterium has the ability to colonize the nares and skin of humans and animals, there is a risk of contamination of food in different steps of the food chain supply. Emerging strains have been detected in food-producing animals and meat, such as methicillin-resistant S. aureus (MRSA). The aim of this study was to determine the prevalence and oxacillin susceptibility of S. aureus in the pork chain supply in Chile and to suggest some natural antimicrobials for control. A total of 487 samples were collected from pigs (n=332), carcasses (n=85), and retail pork meat (n=70). Presumptive S. aureus colonies were isolated by selective enrichment and culture media. The confirmation was carried out by biochemical testing (Api® Staph) and molecular technique PCR (detection of nuc and mecA genes, associated with S. aureus and methicillin resistance, respectively). The oxacillin (β-lactam antibiotic that replaced methicillin) susceptibility was assessed by minimum inhibitory concentration (MIC) using the Epsilometer test (Etest). A preliminary assay was carried out to test thymol, carvacrol, oregano essential oil (Origanum vulgare L.), Maqui or Chilean wineberry extract (Aristotelia chilensis (Mol.) Stuntz) as anti-staphylococcal agents using the disc diffusion method at different concentrations. The overall prevalence of S. aureus in the pork chain supply reached 33.9%. A higher prevalence of S. aureus was determined in carcasses (56.5%) than in pigs (28.3%) and pork meat (32.9%) (P ≤ 0.05). The prevalence of S. aureus in pigs sampled at farms (40.6%) was higher than in pigs sampled at slaughterhouses (23.3%) (P ≤ 0.05). The contamination of no packaged meat with S. aureus (43.1%) was higher than in packaged meat (5.3%) (P ≤ 0.05). The mecA gene was not detected in S. aureus strains isolated in this study. Two S. aureus strains exhibited oxacillin resistance (MIC ≥ 4µg/mL). Anti-staphylococcal activity was detected in solutions of thymol, carvacrol, and oregano essential oil at all concentrations tested. No anti-staphylococcal activity was detected in Maqui extract. Finally, S. aureus is present in the pork chain supply in Chile. Although the mecA gene was not detected, oxacillin resistance was found in S. aureus and could be attributed to another resistance mechanism. Thymol, carvacrol, and oregano essential oil could be used as anti-staphylococcal agents at low concentrations. Research project Fondecyt No. 11140379.

Keywords: antimicrobials, mecA gen, nuc gen, oxacillin susceptibility, pork meat

Procedia PDF Downloads 230

Authors: Li Ziming, He Cunfu, Liu Zenghua

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With aim for delamination type defects detection in manufacturing process of seamless pipe,this paper studies the interaction of the circumferential lamb wave with delamination in aluminum pipe.The delamination is located in the middle of pipe wall.A numerical study is carried out,the circumferential lamb wave used here is CL0 mode,which is generated with a finite element method code.Wave structures from the simulation are compared with theoretical results to verify the model’s accuracy.Delamination along the circumferential direction is established by demerging nodes of the same coordinates.When CL0 mode is incident at the entrance and exit of a delamination,it generates new mode-CL1,undergoes multiple reverberation and mode conversions between the two ends of the delamination. Signals of different receptions are obtained to provide insight in using CL0 mode for locating the delamination.

Keywords: circumferential lamb wave, delamination, FEM, seamless pipe

Procedia PDF Downloads 315