Search results for: events detection

Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

Procedia PDF Downloads 276

Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

Procedia PDF Downloads 273

Authors: Waleed K. Saib, Abdulsalam M. Alhawsawi, Essam Banoqitah

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The idea of this research is to design a radiation spectrometer using LSO scintillation detector coupled to a C series of SiPM (silicon photomultiplier). The device can be used to detects gamma and X-ray radiation. This device is also designed to estimates the activity of the source contamination. The SiPM will detect light in the visible range above the threshold and read them as counts. Three gamma sources were used for these experiments Cs-137, Am-241 and Co-60 with various activities. These sources are applied for four experiments operating the SiPM as a spectrometer, energy resolution, pile-up set and efficiency. The SiPM is connected to a MCA to perform as a spectrometer. Cerium doped Lutetium Silicate (Lu₂SiO₅) with light yield 26000 photons/Mev coupled with the SiPM. As a result, all the main features of the Cs-137, Am-241 and Co-60 are identified in MCA. The experiment shows how photon energy and probability of interaction are inversely related. Total attenuation reduces as photon energy increases. An analytical calculation was made to obtain the FWHM resolution for each gamma source. The FWHM resolution for Am-241 (59 keV) is 28.75 %, for Cs-137 (662 keV) is 7.85 %, for Co-60 (1173 keV) is 4.46 % and for Co-60 (1332 keV) is 3.70%. Moreover, the experiment shows that the dead time and counts number decreased when the pile-up rejection was disabled and the FWHM decreased when the pile-up was enabled. The efficiencies were calculated at four different distances from the detector 2, 4, 8 and 16 cm. The detection efficiency was observed to declined exponentially with increasing distance from the detector face. Conclusively, the SiPM board operated with an LSO scintillator crystal as a spectrometer. The SiPM energy resolution for the three gamma sources used was a decent comparison to other PMTs.

Keywords: PMT, radiation, radiation detection, scintillation detectors, silicon photomultiplier, spectrometer

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

Procedia PDF Downloads 180

Authors: Rajendra N. Ghosh, Paramjeet Singh, Niranjan Khandelwal, Sameer Vyas, Pratibha Singhi, Naveen Sankhyan

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Background: Tuberculoma and neurocysticercosis (NCC) are two most common intracranial infections in developing country. They often simulate on neuroimaging and in absence of typical imaging features cause significant diagnostic dilemmas. Differentiation is extremely important to avoid empirical exposure to antitubercular medications or nonspecific treatment causing disease progression. Purpose: Better characterization and differentiation of CNS tuberculoma and NCC by using morphological and multiple advanced functional MRI. Material and Methods: Total fifty untreated patients (20 tuberculoma and 30 NCC) were evaluated by using conventional and advanced sequences like CISS, SWI, DWI, DTI, Magnetization transfer (MT), T2Relaxometry (T2R), Perfusion and Spectroscopy. rCBV,ADC,FA,T2R,MTR values and metabolite ratios were calculated from lesion and normal parenchyma. Diagnosis was confirmed by typical biochemical, histopathological and imaging features. Results: CISS was most useful sequence for scolex detection (90% on CISS vs 73% on routine sequences). SWI showed higher scolex detection ability. Mean values of ADC, FA,T2R from core and rCBV from wall of lesion were significantly different in tuberculoma and NCC (P < 0.05). Mean values of rCBV, ADC, T2R and FA for tuberculoma and NCC were (3.36 vs1.3), (1.09x10⁻³vs 1.4x10⁻³), (0.13 x10⁻³ vs 0.09 x10⁻³) and (88.65 ms vs 272.3 ms) respectively. Tuberculomas showed high lipid peak, more choline and lower creatinine with Ch/Cr ratio > 1. T2R value was most significant parameter for differentiation. Cut off values for each significant parameters have proposed. Conclusion: Quantitative MRI in combination with conventional sequences can better characterize and differentiate similar appearing tuberculoma and NCC and may be incorporated in routine protocol which may avoid brain biopsy and empirical therapy.

Keywords: advanced functional MRI, differentiation, neurcysticercosis, tuberculoma

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Behcet Al, Mustafa Bogan, Mehmet Murat Oktay, Suat Zengin, Hasan Bayram

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Objective: In the last two decades there is a strong scientific interest regarding the role of aerosols for the Earth’s climate and associated changes. Aerosol particles are very important to the Earth-atmosphere climate system playing a crucial role in cloud and precipitation processes, air quality and climate. Here, we evaluated the association between saharran dust and emergency department admission, hospitalization, and mortality. Method: The records of admission to emergency department of Gaziantep University and the dust stroms of 31 months were studied. Patients admitted to ED at dust strom with chronic obstructive lung disease (COLD), asthma bronchiale (AB), serebrovascular events (SVE), acute myocardial infarction (AMI), stabile and unstabile angina pectoris (SAAP andUSAP); and the days with and without dust stroms were included. The study was realized from March 2010 to October 2012. The admission of three days before strom (group 1), during strom days (group 2) and three days after strom (group 3) were determined. The mean level of dust PM10 particulate was calculated, and the results were compared. Results: 5864 patients with chronic obstructive lung disease, asthma bronchiale, serebrovascular events, acute myocardial infarction, stabile and unstabile angyina pectoris admitted during the days with and without dust stroms. 28 dust stroms ocurred during 31 months. The totaliy of stroms continiued 78 days. Of admissions, 35.5% (n=2075) were in group1, 29.8% (n=1746) in group 2, and 34.8% (n=2043) were in group 3. The mean of PM10 for groups (group 1, 2 and 3) were 78.53 mg/m3 (range 19–276) particulate, 108.7 mg/m3 (range 34–631) particulate, and 60.9 mg/m3 (range 17–160) particulate respectively. The mean admission per a day for groups were 24.86, 22.55, and 24.50 respectively. The mortality was 12 in group 1, 12 in group 2, and 17 in grou 3. The hospitalization ratio for groups were 0.24, 0.27, and 0.27 respectively. Conclusion: However, the mean level of PM10 particulate for groups 2 (in dust strom days) is significantly higher (p=0.001) than the days before (group 1) and after (group 3) dust stroms, the mean admissions/day, hostilalization and mortality related to deseases (COLD, AB, SVE, AMI, SAAP andUSA) for group 2 is lower than the group 1 and group 3.

Keywords: Saharran dust, PM10 particulate, emergency department admission, mortality

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Authors: Guillermo E. Quintero, Edwin G. Perez, Oriel Sanchez, Christian Espinosa-Bustos, Denis Fuentealba, Margarita E. Aliaga

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Bisulfite ion (HSO3-) has been used as a preservative in food, drinks, and medication. However, it is well-known that HSO3- can cause health problems like asthma and allergic reactions in people. Due to the above, the development of analytical methods for detecting this ion has gained great interest. In line with the above, the current use of colorimetric and/or fluorescent probes as a detection technique has acquired great relevance due to their high sensitivity and accuracy. In this context, 2-quinolinone derivatives have been found to possess promising activity as antiviral agents, sensitizers in solar cells, antifungals, antioxidants, and sensors. In particular, 7-(diethylamino)-2-quinolinone derivatives have attracted attention in recent years since their suitable photophysical properties become promising fluorescent probes. In Addition, there is evidence that photophysical properties and reactivity can be affected by the study medium, such as micellar media. Based on the above background, 7-(diethylamino)-2-quinolinone derivatives based chalcone will be able to be incorporated into a cationic micellar environment (Cetyltrimethylammonium bromide, CTAB). Furthermore, the supramolecular control induced by the micellar environment will increase the reactivity of these derivatives towards nucleophilic analytes such as HSO3- (Michael-type addition reaction), leading to the generation of new colorimetric and/or fluorescent probes. In the present study, two derivatives of 7-(diethylamino)-2-quinolinone based chalcone DQD1-2 were synthesized according to the method reported by the literature. These derivatives were structurally characterized by 1H, 13C NMR, and HRMS-ESI. In addition, UV-VIS and fluorescence studies determined absorption bands near 450 nm, emission bands near 600 nm, fluorescence quantum yields near 0.01, and fluorescence lifetimes of 5 ps. In line with the foregoing, these photophysical properties aforementioned were improved in the presence of a cationic micellar medium using CTAB thanks to the formation of adducts presenting association constants of the order of 2,5x105 M-1, increasing the quantum yields to 0.12 and the fluorescence lifetimes corresponding to two lifetimes near to 120 and 400 ps for DQD1 and DQD2. Besides, thanks to the presence of the micellar medium, the reactivity of these derivatives with nucleophilic analytes, such as HSO3-, was increased. This was achieved through kinetic studies, which demonstrated an increase in the bimolecular rate constants in the presence of a micellar medium. Finally, probe DQD1 was chosen as the best sensor since it was assessed to detect HSO3- with excellent results.

Keywords: bisulfite detection, cationic micelle, colorimetric probes, quinolinone derivatives

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Authors: P. Selva, B. Lorraina, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

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Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: cruciform specimen, multiaxial fatigue, nickel-based superalloy

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety

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Authors: Abhimanyu Behera

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Over the past few years, energy security and sustainable development have moved rapidly into the global agenda. There are two main reasons: first, the impact of high and often volatile energy prices; second, concerns over environmental sustainability particularly about the global climate. Both issues are critically important in which impressive economic growth has boosted the demand for energy and put corresponding strains on the environment. Energy security is a broad concept that focuses on energy availability and pricing. Specifically, it refers to the ability of the energy supply system i.e. suppliers, transporters, distributors and regulatory, financial and R&D institutions to deliver the amount of competitively priced energy that customers demand, within accepted standards of reliability, timeliness, quality, safety. Traditionally, energy security has been defined in the context of the geopolitical risks to external oil supplies but today it is encompassing all energy forms, all the external and internal links bringing the energy to the final consumer, and all the many ways energy supplies can be disrupted including equipment malfunctions, system design flaws, operator errors, malicious computer activities, deficient market and regulatory frameworks, corporate financial problems, labour actions, severe weather and natural events, aggressive acts (e.g. war, terrorism and sabotage), and geopolitical disruptions. In practice, the most challenging disruptions are those linked to: 1) extreme weather events; 2) mismatched electricity supply and demand; 3) regulatory failures; and 4) concentration of oil and gas resources in certain regions of the world. However, insecure energy supplies inhibit development by raising energy costs and imposing expensive cuts in services when disruptions actually occur. The energy supply sector can best advance sustainable development by producing and delivering secure and environmentally-friendly sources of energy and by increasing the efficiency of energy use. With this objective, this paper seeks to highlight the significance of energy security and sustainable development in today’s world. Moreover, it critically overhauls the major challenges towards sustainability of energy security and what are the major policies are taken to overcome these challenges by Government is lucidly explicated in this paper.

Keywords: energy, policies, security, sustainability

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Authors: Faisal Guru Rashid, Syed Nisar, Mohammad Hussain Mir, Ulfat Ara, Richa Tripathi

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Background: Biosimilar pegylated L-asparaginase is a potential alternative to the innovator version for treating acute lymphoblastic leukaemia (ALL) in Indian children, addressing issues of availability and cost. Biosimilar offers a viable solution, ensuring wider access to essential treatment in resource-limited settings like India. With this in mind, we conducted a study to assess the efficacy and toxicity of Biosimilar Pegaspargase (Asviia) in patients with Acute Leukaemia at our centre. Materials and methods: A retrospective study was conducted to assess the efficacy and safety of biosimilar PEG-asparaginase (Asviia) in newly diagnosed paediatric acute lymphoblastic leukaemia patients at the Paediatric Oncology unit of Department of Medical Oncology at Sher-I-Kashmir Institute of Medical Sciences, SKIMS Srinagar. The study included patients of ALL treated at our centre between January 2021- and December 2023. Each patient received 2 induction doses of pegaspargenase. Results: 45 patients (16 females and 29 males) were included in the study who received biosimilar PEG-asparaginase (Asviia) as a part of the treatment protocol. The age range of patients was between 1 and 16 years with a median age was 7.5 years. Median PEG Asparaginase dose received was 1175 IU (1125-3750 IU). The majority of patients were Pre-B ALL. There was considerable improvement in the haematological parameters, like haemoglobin levels rising by 1.39 and platelet counts rising by 30,402 after the patients received the first dose of Peg-ASP. Biosimilar Pegaspargase in Acute Leukaemia patients showed a tolerable safety profile with no life-threatening events. 13% of patients exhibited allergic reactions, and 17% had sepsis. Two patients (4.4%) had pancreatitis and Transaminitis events. At the end of induction, out of 45 patients, 40 (88.89%) patients had complete remission with Minimal Residual Disease (MRD) negativity, while 5 patients were MRD positive. Conclusion: Biosimilar PEG-Asparaginase (Asviia) demonstrated a tolerable safety profile and good efficacy, with nearly 90% of patients having complete Remission with MRD negativity.

Keywords: acute lymphoblastic leukaemia, biosimilar, PEG-asparaginase, minimal residual disease, remission

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Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic Kidney Disease, Linear Regression, Microfluidics, Urinary Albumin

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Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

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Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: Yagahira E. Castro-Sesquen, Robert H. Gilman, Carolina Mejia, Daniel E. Clark, Jeong Choi, Melissa J. Reimer-Mcatee, Rocio Castro, Jorge Flores, Edward Valencia-Ayala, Faustino Torrico, Ricardo Castillo-Neyra, Lance Liotta, Caryn Bern, Alessandra Luchini

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Early diagnosis of reactivation of Chagas disease in HIV patients could be lifesaving; however, in Latin American the diagnosis is performed by detection of parasitemia by microscopy which lacks sensitivity. To evaluate if levels of T. cruzi antigens in urine determined by Chunap (Chagas urine nanoparticle test) are correlated with parasitemia levels in T. cruzi/HIV co-infected patients. T. cruzi antigens in urine of HIV patients (N=55: 31 T. cruzi infected and 24 T. cruzi serology negative) were concentrated using hydrogel particles and quantified by Western Blot and a calibration curve. The percentage of Chagas positive patients determined by Chunap compared to blood microscopy, qPCR, and ELISA was 100% (6/6), 95% (18/19) and 74% (23/31), respectively. Chunap specificity was 91.7%. Linear regression analysis demonstrated a direct relationship between parasitemia levels (determined by qPCR) and urine T. cruzi antigen concentrations (p<0.001). A cut-off of > 105 pg was chosen to determine patients with reactivation of Chagas disease (6/6). Urine antigen concentration was significantly higher among patients with CD4+ lymphocyte counts below 200/mL (p=0.045). Chunap shows potential for early detection of reactivation and with appropriate adaptation can be used for monitoring Chagas disease status in T. cruzi/HIV co-infected patients.

Keywords: antigenuria, Chagas disease, Chunap, nanoparticles, parasitemia, poly N-isopropylacrylamide (NIPAm)/trypan blue particles (polyNIPAm/TB), reactivation of Chagas disease.

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Authors: Abderahman Efhialelbum

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The period since the fall of the Berlin Wall on November 9, 1989, and the collapse of the former Soviet Union in December 1985 has seen a major change in the economies and labour markets of Eastern Europe. The events also had reverberating effects across Asia and South America and parts of Africa, including Libya. This article examines the typologies and the models of transition economies. Also, it sheds light on the Libyan transition in particular and the impact of Qadhafi’s regime on the transition process. Finally, it illustrates how the Libyan transition process followed the trajectory of other countries using economic indicators such as free trade, property rights, and inflation.

Keywords: transition, economy, typology, model, Libya

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Authors: Thyagi Ponnamperuma

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Background: Comorbidity between posttraumatic stress disorder (PTSD) and other psychological problems is common. Recent studies focused to investigate the underlying relationship between PTSD and comorbid psychopathologies. Among adolescents, higher rates of emotional and behavioral problems (EBP) have been reported following trauma, often coexisted with PTSD. The current study, thus, examined the relationship of posttraumatic stress symptoms to EBP in adolescents exposed to a variety of traumatic events. Further, the study investigated the relationship of trauma and comorbid PTSS to the self-perceived negative impact of EBP on daily functioning. Methods: Participants were 729 Sri Lankan adolescents (age 12 to 16 years; 54.9% female) living in areas impacted in varying degrees by the 2004 tsunami. In 2008, school-based screening was conducted and completed measures of, trauma exposure, PTSS, EBP, and related functional impairment. Results: Participants reported a high prevalence of trauma exposure (n = 438), including interpersonal violence (n = 155). DSM-IV criteria for full or partial PTSD were met by 23.7% of the trauma-exposed sample. Across all participants, 13.4% and 16.7% displayed clinically relevant levels of EBP and functional impairment, respectively. Among the trauma-exposed, 7% met criteria for both EBP and PTSD. EBP total scores and caseness were significantly higher in trauma-exposed adolescents with PTSD than in either those without PTSD or the non-traumatized control group. In subscale analysis, higher prevalence of serious emotional, conduct, and hyperactivity problems were reported in the PTSD positive group; the PTSD negative group did not differ significantly from the control group on any of the problem scales. In regression analyses, PTSS (β = .28, p < .001) and interpersonal violence (β = .13, p = .033) were significant predictors of EBP, cumulative trauma (β = .11, p = .076) showed no significant effect. Further, PTSS exacerbated the impact of EBP on daily functioning (β = 0.29, p = .023). Conclusion: PTSS were closely linked to EBP in adolescents, even years after the traumatic experience. PTSD and emotional and behavioral problems together pose a heightened risk for impaired daily functioning. Longitudinal studies are needed to clarify the causal pathway.

Keywords: adolescents, comorbidity, emotional and behavioral problems, functional impairment, posttraumatic stress, traumatic events

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Authors: Matt S. Van Deren, Michael Papenfus

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Seattle is one of the hundreds of cities in the United States that relies on a combined sewer system to collect and convey municipal wastewater. By design, these systems convey all wastewater, including industrial and commercial wastewater, human sewage, and stormwater runoff, through a single network of pipes. Serious problems arise for combined sewer systems during heavy precipitation events when treatment plants and storage facilities are unable to accommodate the influx of wastewater needing treatment, causing the sewer system to overflow into local waterways through sewer outfalls. CSOs (Combined Sewer Overflows) pose a serious threat to human and environmental health. Principal pollutants found in CSO discharge include microbial pathogens, comprising of bacteria, viruses, parasites, oxygen-depleting substances, suspended solids, chemicals or chemical mixtures, and excess nutrients, primarily nitrogen and phosphorus. While concentrations of these pollutants can vary between overflow events, CSOs have the potential to spread disease and waterborne illnesses, contaminate drinking water supplies, disrupt aquatic life, and effect a waterbody’s designated use. This paper estimates the economic impact of CSOs on residential property values. Using residential property sales data from Seattle, Washington, this paper employs a hedonic valuation model that controls for housing and neighborhood characteristics, as well as spatial and temporal effects, to predict a consumer’s willingness to pay for improved water quality near their homes. Initial results indicate that a 100,000-gallon decrease in the average annual overflow discharged from a sewer outfall within 300 meters of a home is associated with a 0.053% increase in the property’s sale price. For the average home in the sample, the price increase is estimated to be $18,860.23. These findings reveal some of the important economic benefits of improving water quality by reducing the frequency and severity of combined sewer overflows.

Keywords: benefits, hedonic, Seattle, sewer

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Authors: Gabriel Dolabella, Henrique Rangel, Stella Araújo, Carlos Bolonha, Igor de Lazari

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Public security is a common subject on the Brazilian political agenda. The seventh largest economy in the world has high crime and insecurity rates. Specialists try to explain this social picture based on poverty, inequality or public policies addressed to drug trafficking. This excerpt approaches State measures to handle that picture. Therefore, the public security - law enforcement institutions - is at the core of this paper, particularly the relationship among federal and state law enforcement agencies, mainly ruled by a system of urgency. The problems are informal changes on law enforcement management and public opinion collaboration to these changes. Whenever there were huge international events, Brazilian armed forces occupied streets to assure law enforcement - ensuring the order. This logic, considered in the long time, could impact the federal structure of the country. The post-madisonian theorists verify that urgency is often associated to delegation of powers, which is true for Brazilian law enforcement, but here there is a different delegation: States continuously delegate law enforcement powers to the federal government throughout the use of Armed Forces. Therefore, the hypothesis is: Brazil is under a political process of federalization of public security. The political framework addressed here can be explained by the disrespect of legal constraints and the failure of rule of law theoretical models. The methodology of analysis is based on general criteria. Temporally, this study investigates events from 2003, when discussions about the disarmament statute begun. Geographically, this study is limited to Brazilian borders. Materially, the analysis result from the observation of legal resources and political resources (pronouncements of government officials). The main parameters are based on post-madisonianism and federalization of public security can be assessed through credibility and popularity that allow evaluation of this political process of constitutional change. The objective is to demonstrate how the Military Forces are used in public security, not as a random fact or an isolated political event, in order to understand the political motivations and effects that stem from that use from an institutional perspective.

Keywords: public security, governability, rule of law, federalism

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Authors: Nisa Mohan

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Adverse drug event (ADE) related hospital admissions are common among older people. The first step in prevention is accurately estimating the prevalence of ADE admissions. Clinical coding is an efficient method to estimate the prevalence of ADE admissions. The objective of the study is to estimate the rate of under-coding of ADE admissions in older people in New Zealand and to explore how clinical coders decide whether or not to code an admission as an ADE. There has not been any research in New Zealand to explore these areas. This study is done using a mixed-methods approach. Two common and serious ADEs in older people, namely bleeding and hypoglycaemia were selected for the study. In study 1, eight hundred medical records of people aged 65 years and above who are admitted to hospital due to bleeding and hypoglycemia during the years 2015 – 2016 were selected for quantitative retrospective medical records review. This selection was made to estimate the proportion of ADE-related bleeding and hypoglycemia admissions that are not coded as ADEs. These files were reviewed and recorded as to whether the admission was caused by an ADE. The hospital discharge data were reviewed to check whether all the ADE admissions identified in the records review were coded as ADEs, and the proportion of under-coding of ADE admissions was estimated. In study 2, thirteen clinical coders were selected to conduct qualitative semi-structured interviews using a general inductive approach. Participants were selected purposively based on their experience in clinical coding. Interview questions were designed in a way to investigate the reasons for the under-coding of ADE admissions. The records review study showed that 35% (Cl 28% - 44%) of the ADE-related bleeding admissions and 22% of the ADE-related hypoglycemia admissions were not coded as ADEs. Although the quality of clinical coding is high across New Zealand, a substantial proportion of ADE admissions were under-coded. This shows that clinical coding might under-estimate the actual prevalence of ADE related hospital admissions in New Zealand. The interviews with the clinical coders added that lack of time for searching for information to confirm an ADE admission, inadequate communication with clinicians, along with coders’ belief that an ADE is a small thing might be the potential reasons for the under-coding of the ADE admissions. This study urges the coding policymakers, auditors, and trainers to engage with the unconscious cognitive biases and short-cuts of the clinical coders. These results highlight that further work is needed on interventions to improve the clinical coding of ADE admissions, such as providing education to coders about the importance of ADEs, education to clinicians about the importance of clear and confirmed medical records entries, availing pharmacist service to improve the detection and clear documentation of ADE admissions and including a mandatory field in the discharge summary about external causes of diseases.

Keywords: adverse drug events, bleeding, clinical coders, clinical coding, hypoglycemia

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Authors: Maryam Bahreini, Mostafa Talebi Garekani, Fatemeh Rasooli, Atefeh Abdollahi

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Introduction: Procedural sedation and analgesia have been desirable to handle painful procedures. The trend to find the agent with more efficacy and less complications is still controversial; thus, many sedative regimens have been studied. This study tried to assess the effectiveness and adverse effects of thiopental sodium-fentanyl with the known medication, ketamine-propofol for procedural sedation in the emergency department. Methods: Consenting patients were enrolled in this randomized double-blind trial to receive either 1:1 ketamine-propofol (KP) or thiopental-fentanyl (TF) 1:1 mg: Mg proportion on a weight-based dosing basis to reach the sedation level of American Society of Anesthesiologist class III/IV. The respiratory and hemodynamic complications, nausea and vomiting, recovery agitation, patient recall and satisfaction, provider satisfaction and recovery time were compared. The study was registered in Iranian randomized Control Trial Registry (Code: IRCT2015111325025N1). Results: 96 adult patients were included and randomized, 47 in the KP group and 49 in the TF group. 2.1% in the KP group and 8.1 % in the TF group experienced transient hypoxia leading to performing 4.2 % versus 8.1 % airway maneuvers for 2 groups, respectively; however, no statistically significant difference was observed between 2 combinations, and there was no report of endotracheal placement or further admission. Patient and physician satisfaction were significantly higher in the KP group. There was no difference in respiratory, gastrointestinal, cardiovascular and psychiatric adverse events, recovery time and patient recall of the procedure between groups. The efficacy and complications were not related to the type of procedure or patients’ smoking or addiction trends. Conclusion: Ketamine-propofol and thiopental-fentanyl combinations were effectively comparable although KP resulted in higher patient and provider satisfaction. It is estimated that thiopental fentanyl combination can be as potent and efficacious as ketofol with relatively similar incidence of adverse events in procedural sedation.

Keywords: adverse effects, conscious sedation, fentanyl, propofol, ketamine, safety, thiopental

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Authors: Fateme Montazeri

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Literary approaches towards the text of the Quran predate the modern period. Suyuti (d.1505)’s encyclopedia of Quranic sciences, Al-Itqan, provides a notable example. In the modern era, the study of the Quranic rhetorics received particular attention in the second half of the twentieth century by Egyptian scholars. Amin Al-Khouli (d. 1966), who might be considered the first to argue for the necessity of applying a literary-rhetorical lens toward the tafseer, Islamic exegesis, and his students championed the literary analysis as the most effective approach to the comprehension of the holy text. Western scholars continued the literary criticism of the Islamic scripture by applying to the Quran similar methodologies used in biblical studies. In the history of the literary examination of the Quran, the scope of the critical methods applied to the Quranic text has been limited. For, the rhetorical approaches to the Quran, in the premodern as well as the modern period, concerned almost exclusively with the lexical layer of the text, leaving the narratological dimensions insufficiently examined. Recent contributions, by Leyla Ozgur Alhassen, for instance, attempt to fill this lacunae. This paper aims at advancing the studies of the Quranic narratives by investigating the application of a literary device whose role in the Quranic stories remains unstudied, that is, “foreshadowing.” This paper shall focus on Chapter 12, “Surah al-Yusuf,” as its case study. Chapter 12, the single chapter that includes the story of Joseph in one piece, contains several instances in which the events of the story are foreshadowed. As shall be discussed, foreshadowing occurs either through a monolog or dialogue whereby one or more of the characters allude to the future happenings or through the manner in which the setting is described. Through a close reading of the text, it will be demonstrated that the usage of the rhetorical tool of foreshadowing meets a dual purpose: on the one hand, foreshadowing prepares the reader/audience for the upcoming events in the plot, and on the other hand, it highlights the psychological dimensions of the characters, their thoughts, intentions, and disposition. In analyzing the story, this study shall draw on psychoanalytical criticism to explore the layers of meanings embedded in the Quranic narrative that are unfolded through foreshadowing.

Keywords: foreshadowing, quranic narrative, literary criticism, surah yusuf

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Authors: Joel Ballesteros, Harriet Jane Caleja, Florian Del Mundo, Cherrie Pascual

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Diffraction-based sensing was utilized in the quantification of human ferritin in blood serum to provide an alternative to label-based immunoassays currently used in clinical diagnostics and researches. The diffraction intensity was measured by the diffractive optics technology or dotLab™ system. Two methods were evaluated in this study: direct immunoassay and direct sandwich immunoassay. In the direct immunoassay, human ferritin was captured by human ferritin antibodies immobilized on an avidin-coated sensor while the direct sandwich immunoassay had an additional step for the binding of a detector human ferritin antibody on the analyte complex. Both methods were repeatable with coefficient of variation values below 15%. The direct sandwich immunoassay had a linear response from 10 to 500 ng/mL which is wider than the 100-500 ng/mL of the direct immunoassay. The direct sandwich immunoassay also has a higher calibration sensitivity with value 0.002 Diffractive Intensity (ng mL-1)-1) compared to the 0.004 Diffractive Intensity (ng mL-1)-1 of the direct immunoassay. The limit of detection and limit of quantification values of the direct immunoassay were found to be 29 ng/mL and 98 ng/mL, respectively, while the direct sandwich immunoassay has a limit of detection (LOD) of 2.5 ng/mL and a limit of quantification (LOQ) of 8.2 ng/mL. In terms of accuracy, the direct immunoassay had a percent recovery of 88.8-93.0% in PBS while the direct sandwich immunoassay had 94.1 to 97.2%. Based on the results, the direct sandwich immunoassay is a better diffraction-based immunoassay in terms of accuracy, LOD, LOQ, linear range, and sensitivity. The direct sandwich immunoassay was utilized in the determination of human ferritin in blood serum and the results are validated by Chemiluminescent Magnetic Immunoassay (CMIA). The calculated Pearson correlation coefficient was 0.995 and the p-values of the paired-sample t-test were less than 0.5 which show that the results of the direct sandwich immunoassay was comparable to that of CMIA and could be utilized as an alternative analytical method.

Keywords: biosensor, diffraction, ferritin, immunoassay

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Andrea Catorci, Federico Maria Tardella, Alessandro Brica, Muhammad Umair

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Climate change models predict for the Mediterranean region a strong increase of intensity and frequency of drought events, with an expected effect on grassland biodiversity and functioning. The research aim was to understand how the grassland species modulate their resource acquisition and conservation strategies to short-term variation of the pattern of summer water supply. The study area is mountain meadows located in the ‘‘Montagna di Torricchio’’ (1130 m a.s.l.) a Nature Reserve in central Italy. In 2017 we started a manipulative experiment for 2 year (2017-2018), and we defined two treatments, one with increasing water (watering condition) and the other with less water (drought condition). Then, we investigated how species change their resource strategies at different amount of water availability by measuring the specific leaf area (SLA) and leaf area (LA). We used ANOVAs to test the effect of treatment over time on leaf area and specific leaf area, considering all the species together and also separately according to their growth form (forb, grass, legume). Our results showed that species may respond differently depending on their growth form and that using all the species together may cover more detailed variation. Overall, resource retaining strategies (lower SLA, LA) are resulted by increase of drought condition, while increase in water amount and number of watering events fosters acquisitive strategies (higher SLA, LA). However, this pattern is not constant for all growth form. Grass species are able to maintain their strategies to variation of the pattern of water availability. Forb and legume species on the other side have shown decreasing trend of SLA, LA values with increasing drought condition, a pattern more marked for the latter growth form. These variations suggest not only an increase of slow-growing strategies for both growth form, but also a decrease of their nutrient pastoral values since their leaves are supposed to become harder. Local farmers should consider the effect of climate change on grassland and adapt their management practices to guarantee the cattle welfare.

Keywords: function strategies, grasslands, climate change, sub Mediterranean region

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Authors: Alaa Fezai, Anuj Sharma, Wolfgang Mueller-Hirsch, André Zimmermann

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Viscoelastic materials have been widely used in the automotive industry over the last few decades with different functionalities. Besides their main application as a simple and efficient surface damping treatment, they may ensure optimal operating conditions for on-board electronics as thermal interface or sealing layers. The dynamic behavior of viscoelastic materials is generally dependent on many environmental factors, the most important being temperature and strain rate or frequency. Prior to the reliability analysis of systems including viscoelastic layers, it is, therefore, crucial to accurately predict the dynamic and lifetime behavior of these materials. This includes the identification of the dynamic material parameters under critical temperature and frequency conditions along with a precise damage localization and identification methodology. The goal of this work is twofold. The first part aims at applying an inverse viscoelastic material-characterization approach for a wide frequency range and under different temperature conditions. For this sake, dynamic measurements are carried on a single lap joint specimen using an electrodynamic shaker and an environmental chamber. The specimen consists of aluminum beams assembled to adapter plates through a viscoelastic adhesive layer. The experimental setup is reproduced in finite element (FE) simulations, and frequency response functions (FRF) are calculated. The parameters of both the generalized Maxwell model and the fractional derivatives model are identified through an optimization algorithm minimizing the difference between the simulated and the measured FRFs. The second goal of the current work is to guarantee an on-line detection of the damage, i.e., delamination in the viscoelastic bonding of the described specimen during frequency monitored end-of-life testing. For this purpose, an inverse technique, which determines the damage location and size based on the modal frequency shift and on the change of the mode shapes, is presented. This includes a preliminary FE model-based study correlating the delamination location and size to the change in the modal parameters and a subsequent experimental validation achieved through dynamic measurements of specimen with different, pre-generated crack scenarios and comparing it to the virgin specimen. The main advantage of the inverse characterization approach presented in the first part resides in the ability of adequately identifying the material damping and stiffness behavior of soft viscoelastic materials over a wide frequency range and under critical temperature conditions. Classic forward characterization techniques such as dynamic mechanical analysis are usually linked to limitations under critical temperature and frequency conditions due to the material behavior of soft viscoelastic materials. Furthermore, the inverse damage detection described in the second part guarantees an accurate prediction of not only the damage size but also its location using a simple test setup and outlines; therefore, the significance of inverse numerical-experimental approaches in predicting the dynamic behavior of soft bonding layers applied in automotive electronics.

Keywords: damage detection, dynamic characterization, inverse approaches, vibration testing, viscoelastic layers

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Authors: M. A. García, J. Vinolas, A. Hernando

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Steel is nowadays one of the most important structural materials because of its outstanding mechanical properties. Therefore, in order to look for a sustainable economic model and to optimize the use of extensive resources, new methods to monitor and prevent failure of steel-based facilities are required. The classical mechanical tests, as for instance building tasting, are invasive and destructive. Moreover, for facilities where the steel element is embedded, (as reinforced concrete) these techniques are directly non applicable. Hence, non-invasive monitoring techniques to prevent failure, without altering the structural properties of the elements are required. Among them, electromagnetic methods are particularly suitable for non-invasive inspection of the mechanical state of steel-based elements. The magnetoelastic coupling effects induce a modification of the electromagnetic properties of an element upon applied stress. Since most steels are ferromagnetic because of their large Fe content, it is possible to inspect their structure and state in a non-invasive way. We present here a distinct electromagnetic method for contactless evaluation of internal stress in steel-based elements. In particular, this method relies on measuring the magnetic induction between two coils with the steel specimen in between them. We found that the alteration of electromagnetic properties of the steel specimen induced by applied stress-induced changes in the induction allowed us to detect stress well below half of the elastic limit of the material. Hence, it represents an outstanding non-invasive method to prevent failure in steel-based facilities. We here describe the theoretical model, present experimental results to validate it and finally we show a practical application for detection of stress and inhomogeneities in train railways.

Keywords: magnetoelastic, magnetic induction, mechanical stress, steel

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Authors: Yi Li, Rui Lu, Lianjun Wang

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With the rapid development of chemical industry, the consumption of volatile organic compounds (VOCs) has increased extensively. In the process of VOCs production and application, plenty of them have been transferred to environment. As a result, it has led to pollution problems not only in soil and ground water but also to human beings. Thus, it is important to develop a sensitive and cost-effective analytical method for trace VOCs detection in environment. Surface-enhanced Raman Spectroscopy (SERS), as one of the most sensitive optical analytical technique with rapid response, pinpoint accuracy and noninvasive detection, has been widely used for ultratrace analysis. Based on the plasmon resonance on the nanoscale metallic surface, SERS technology can even detect single molecule due to abundant nanogaps (i.e. 'hot spots') on the nanosubstrate. In this work, a self-supported flexible silver nitrate (AgNO3)/ethylene-propylene copolymer (EPM) hybrid nanofibers was fabricated by electrospinning. After an in-situ chemical reduction using ice-cold sodium borohydride as reduction agent, numerous silver nanoparticles were formed on the nanofiber surface. By adjusting the reduction time and AgNO3 content, the morphology and dimension of silver nanoparticles could be controlled. According to the principles of solid-phase extraction, the hydrophobic substance is more likely to partition into the hydrophobic EPM membrane in an aqueous environment while water and other polar components are excluded from the analytes. By the enrichment of EPM fibers, the number of hydrophobic molecules located on the 'hot spots' generated from criss-crossed nanofibers is greatly increased, which further enhances SERS signal intensity. The as-prepared Ag/EPM hybrid nanofibers were first employed to detect common SERS probe molecule (p-aminothiophenol) with the detection limit down to 10-12 M, which demonstrated an excellent SERS performance. To further study the application of the fabricated substrate for monitoring hydrophobic substance in water, several typical VOCs, such as benzene, toluene and p-xylene, were selected as model compounds. The results showed that the characteristic peaks of these target analytes in the mixed aqueous solution could be distinguished even at a concentration of 10-6 M after multi-peaks gaussian fitting process, including C-H bending (850 cm-1), C-C ring stretching (1581 cm-1, 1600 cm-1) of benzene, C-H bending (844 cm-1 ,1151 cm-1), C-C ring stretching (1001 cm-1), CH3 bending vibration (1377 cm-1) of toluene, C-H bending (829 cm-1), C-C stretching (1614 cm-1) of p-xylene. The SERS substrate has remarkable advantages which combine the enrichment capacity from EPM and the Raman enhancement of Ag nanoparticles. Meanwhile, the huge specific surface area resulted from electrospinning is benificial to increase the number of adsoption sites and promotes 'hot spots' formation. In summary, this work provides powerful potential in rapid, on-site and accurate detection of trace VOCs using a portable Raman.

Keywords: electrospinning, ethylene-propylene copolymer, silver nanoparticles, SERS, VOCs

Procedia PDF Downloads 150