Search results for: contextual toxicity detection

Authors: Zhengyu Yan, Yan Yu, Jianqiu Chen

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A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analysis cost with the recovery rate as 97.43%-103.2%, which has potential application prospect.

Keywords: CdS quantum dots, modification, detection, naphthalene

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Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

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Authors: Sawsan Al-Saaidi, Ghayth K. Shaker Al-Shaibani

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This paper investigates certain linguistics properties of four selected speeches by Al-Qaeda’s former leader Osama bin Laden who legitimated the use of jihad by Muslims in various countries when he was alive. The researchers adopt van Dijk’s (2009; 1998) Socio-Cognitive approach and Ideological Square theory respectively. Socio-Cognitive approach revolves around various cognitive, socio-political, and discursive aspects that can be found in political discourse as in Osama bin Laden’s one. The political discourse can be defined in terms of textual properties and contextual models. Pertaining to the ideological square, it refers to positive self-presentation and negative other-presentation which help to enhance the textual and contextual analyses. Therefore, among the most significant properties in Osama bin Laden’s discourse are the use of presuppositions and implicatures which are based on background knowledge and contextual models as well. Thus, the paper concludes that Osama bin Laden used a number of manipulative strategies which augmented and embellished the use of ‘jihad’ in order to develop a more effective discourse for his audience. In addition, the findings have revealed that bin Laden used different implicit and embedded interpretations of different topics which have been accepted as taken-for-granted truths for him to legitimate Jihad against his enemies. There are many presuppositions in the speeches analysed that result in particular common-sense assumptions and a world-view about the selected speeches. More importantly, the assumptions in the analysed speeches help consolidate the ideological analysis in terms of in-group and out-group members.

Keywords: Al-Qaeda, cognition, critical discourse analysis, Osama Bin Laden, jihad, implicature, legitimisation, presupposition, political discourse

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Authors: G. Amariei, K. Boltes, R. Rosal, P. Leton

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Wastewater treatment plants (WWTPs) are supposed to hold an important place in the reduction of emerging contaminants, but provide an environment that has potential for the development and/or spread of adaptation, as bacteria are continuously mixed with contaminants at sub-inhibitory concentrations. Reviewing the literature, there are little data available regarding the use of adapted bacteria forming activated sludge community for toxicity assessment, and only individual validations have been performed. Therefore, the aim of this work was to study the toxicity of Triclosan (TCS) and Ibuprofen (IBU), individually and in binary combination, on adapted activated sludge (AS). For this purpose a battery of biomarkers were assessed, involving oxidative stress and cytotoxicity responses: glutation-S-transferase (GST), catalase (CAT) and viable cells with FDA. In addition, we compared the toxic effects on adapted bacteria with unadapted bacteria, from a previous research. Adapted AS comes from three continuous-flow AS laboratory systems; two systems received IBU and TCS, individually; while the other received the binary combination, for 14 days. After adaptation, each bacterial culture condition was exposure to IBU, TCS and the combination, at 12 h. The concentration of IBU and TCS ranged 0.5-4mg/L and 0.012-0.1 mg/L, respectively. Batch toxicity experiments were performed using Oxygraph system (Hansatech), for determining the activity of CAT enzyme based on the quantification of oxygen production rate. Fluorimetric technique was applied as well, using a Fluoroskan Ascent Fl (Thermo) for determining the activity of GST enzyme, using monochlorobimane-GSH as substrate, and to the estimation of viable cell of the sludge, by fluorescence staining using Fluorescein Diacetate (FDA). For IBU adapted sludge, CAT activity it was increased at low concentration of IBU, TCS and mixture. However, increasing the concentration the behavior was different: while IBU tends to stabilize the CAT activity, TCS and the mixture decreased this one. GST activity was significantly increased by TCS and mixture. For IBU, no variations it was observed. For TCS adapted sludge, no significant variations on CAT activity it was observed. GST activity it was significant decreased for all contaminants. For mixture adapted sludge the behaviour of CAT activity it was similar to IBU adapted sludge. GST activity it was decreased at all concentration of IBU. While the presence of TCS and mixture, respectively, increased the GST activity. These findings were consistent with the viability cells evaluation, which clearly showed a variation of sludge viability. Our results suggest that, compared with unadapted bacteria, the adapted bacteria conditions plays a relevant role in the toxicity behaviour towards activated sludge communities.

Keywords: adapted sludge community, mixture, PPCPs, toxicity

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Authors: Murali Munisamy, Gauthaman Karunakaran, Mubarak Al-Gahtany, Vivekanandhan Subbiah, M. Manjari Tripati

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Background: Sodium valproate is a widely prescribed broad-spectrum anti-epileptic drug. It shows high inter-individual variability in pharmacokinetics and pharmacodynamics and has a narrow therapeutic range. We evaluated the effects of polymorphic uridine diphosphate glucuronosyltransferase (UGT1A9) metabolizing enzyme on the pharmacokinetics of sodium valproate in the patients with epilepsy who showed toxicity to therapy. Methods: Genotype analysis of the patients was made with polymerase chain–restriction fragment length polymorphism (RFLP) with sequencing. Plasma drug concentrations were measured with reversed phase high-performance liquid chromatography (HPLC) and concentration–time data were analyzed by using a non-compartmental approach. Results: The results of this study suggested a significant genotypic as well as allelic association with valproic acid toxicity for UGT1A9 polymorphic enzymes. The elimination half-life (t 1/2=40.2 h) of valproic acid was longer and the clearance rate (CL=937 ml/h) was lower in the poor metabolizers group of UGT1A9 polymorphism who showed toxicity than in the intermediate metabolizers group (t1/2=35.5 h, CL=1042 ml/h) or the extensive metabolizers group (t1/2=26. h, CL=1,302 ml/h). Conclusion: Our findings suggest that the UGT1A9 genetic polymorphism plays a significant role in the steady state concentration of sodium valproate, and it thereby has an impact on the toxicity of the sodium valproate used in the patients with epilepsy.

Keywords: UGT1A9, sodium valporate, pharmacogenetics, polymorphism

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Authors: Preston Nabors, Nasseh Tabrizi

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Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: Sang-Hoon Park, Yeji Ho, Gwang-Moon Eom

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Fast and accurate detection of Freezing of Gait (FOG) is desirable for appropriate application of cueing which has been shown to ameliorate FOG. Utilization of frequency spectrum of leg acceleration to derive the freeze index requires much calculation and it would lead to delayed cueing. We hypothesized that FOG can be reasonably detected from the time domain amplitude of foot acceleration. A time instant was recognized as FOG if the mean amplitude of the acceleration in the time window surrounding the time instant was in the specific FOG range. Parameters required in the FOG detection was optimized by simulated annealing. The suggested time domain methods showed performances comparable to those of frequency domain methods.

Keywords: freezing of gait, detection, Parkinson's disease, time-domain method

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Authors: Sanjay Singh, Parameswara Rao Vuddanda

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The aim of the present study is study the factual benefit of nano size and surface coating of p-gp efflux inhibitor on enhancement of bioavailability of Berberine chloride (BBR); a p-gp substrate. In addition, 28 days sub acute oral toxicity study was also conducted to assess the toxicity of the formulation on chronic administration. BBR loaded polymeric nanoparticles (BBR-NP) were prepared by nanoprecipitation method. BBR NP were surface coated (BBR-SCNP) with the 1 % w/v of vitamin E TPGS. For bioavailability study, total five groups (n=6) of rat were treated as follows first; pure BBR, second; physical mixture of BBR, carrier and vitamin E TPGS, third; BBR-NP, fourth; BBR-SCNP and fifth; BBR and verapamil (widely used p-gp inhibitor). Blood was withdrawn at pre-set timing points in 24 hrs study and drug was quantified by HPLC method. In oral chronic toxicity study, total four groups (n=6) were treated as follows first (control); water, second; pure BBR, third; BBR surface coated nanoparticles and fourth; placebo BBR surface coated nanoparticles. Biochemical levels of liver (AST, ALP and ALT) and kidney (serum urea and creatinine) along with their histopathological studies were also examined (0-28 days). The AUC of BBR-SCNP was significantly 3.5 folds higher compared to all other groups. The AUC of BBR-NP was 3.23 and 1.52 folds higher compared to BBR solution and BBR with verapamil group, respectively. The physical mixture treated group showed slightly higher AUC than BBR solution treated group but significantly low compared to other groups. It indicates that encapsulation of BBR in nanosize form can circumvent P-gp efflux effect. BBR-NP showed pharmacokinetic parameters (Cmax and AUC) which are near to BBR-SCNP. However, the difference in values of T1/2 and clearance indicate that surface coating with vitamin E TPGS not only avoids the P-gp efflux at its absorption site (intestine) but also at organs which are responsible for metabolism and excretion (kidney and liver). It may be the reason for observed decrease in clearance of BBR-SCNP. No toxicity signs were observed either in biochemical or histopathological examination of liver and kidney during toxicity studies. The results indicate that administration of BBR in surface coated nanoformulation would be beneficial for enhancement of its bioavailability and longer retention in systemic circulation. Further, sub acute oral dose toxicity studies for 28 days such as evaluation of intestine, liver and kidney histopathology and biochemical estimations indicated that BBR-SCNP developed were safe for long use.

Keywords: bioavailability, berberine nanoparticles, p-gp efflux inhibitor, nanoprecipitation method

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Authors: Levylee Bautista, Dawn Grace Santos, Aishwarya Veluchamy, Jesusa Santos, Ghafoor Haque, Jr. I, Rodolfo Rafael

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Sesbania grandiflora is widely used in traditional medicine to treat a wide range of ailments. Assessment of its toxic properties is hence crucial when considering public health protection because exposure to plant extracts may pose adverse effects on consumers. This study aimed to investigate the acute intraperitoneal toxicity of S. grandiflora flower methanolic extract (SGFME) in Swiss albino mice. Four different concentrations (11.25, 22.5, 40, and 90 mg/kg) of SGFME were administered intraperitoneally and immediate behavioral and clinical signs were observed. All concentrations of SGFME-treated mice exhibited gasping and faster respiratory rate, writhing, reddening and fanning of the ears, paralysis of the hind leg, and mortality. Such reactions may be attributed to the histamine and saponin content of S. grandiflora. Results of this study suggests that intraperitoneal administration of SGFME produced significant adverse effect in mice, therefore, caution should be exercised in using it as herbal remedy since there is little control over its quality.

Keywords: acute toxicity test, histamine, medicinal plants, Sesbania grandiflora

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: M. Khouil, N. Saber, M. Mestari

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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Zdenek Silar, Martin Dobrovolny

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This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

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Authors: Norsyamimi Hassim, Masturah Markom

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Supercritical fluid extraction (SFE) has been known as a sustainable and safe extraction technique for plant extraction due to the minimal usage of organic solvent. In this study, a scale-up process for the selected herbal plant (Phyllanthus niruri) was investigated by using supercritical carbon dioxide (SC-CO2) with food-grade (ethanol-water) cosolvent. The quantification of excess ethanol content in the final dry extracts was conducted to determine the safety of enriched extracts. The extraction yields obtained by scale-up SFE unit were not much different compared to the predicted extraction yields with an error of 2.92%. For component contents, the scale-up extracts showed comparable quality with laboratory-scale experiments. The final dry extract showed that the excess ethanol content was 1.56% g/g extract. The fish embryo toxicity test (FETT) on the zebrafish embryos showed no toxicity effects by the extract, where the LD50 value was found to be 505.71 µg/mL. Thus, it has been proven that SFE with food-grade cosolvent is a safe extraction technique for the production of bioactive compounds from P. niruri.

Keywords: scale-up, supercritical fluid extraction, enriched extract, toxicity, ethanol content

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

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This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

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Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

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Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

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Authors: Susan Hall, Gary D. Grant, Catherine McDermott, Devinder Arora

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Introduction /Aim: The kynurenine pathway is thought to play an important role in the pathophysiology of numerous neurodegenerative diseases including depression, Alzheimer’s disease, and Parkinson’s disease. Numerous neuroactive compounds, including the neurotoxic 3-hydroxyanthranilic acid, 3-hydroxykynurenine and quinolinic acid and the neuroprotective kynurenic acid and picolinic acid, are produced through the metabolism of kynurenine and are thought to be the causative agents responsible for neurodegeneration. The toxicity of 3-hydroxykynurenine, 3-hydroxyanthranilic acid and quinolinic acid has been widely evaluated and demonstrated in primary cell cultures but to date only 3-hydroxykynurenine and 3-hydroxyanthranilic acid have been shown to cause toxicity in immortal tumour cells. The aim of this study was to evaluate the toxicity of kynurenine metabolites, both individually and in combination, on SH-SY5Y neuroblastoma cells after 24 and 72 h exposure in order to explore a cost-effective model to study their neurotoxic effects and potential protective agents. Methods: SH-SY5Y neuroblastoma cells were exposed to various concentrations of the neuroactive kynurenine metabolites, both individually and in combination, for 24 and 72 h, and viability was subsequently evaluated using the Resazurin (Alamar blue) proliferation assay. Furthermore, the effects of these compounds, alone and in combination, on specific death pathways including apoptosis, necrosis and free radical production was evaluated using various assays. Results: Consistent with literature, toxicity was shown with short-term 24-hour treatments at 1000 μM concentrations for both 3-hydroxykynurenine and 3-hydroxyanthranilic acid. Combinations of kynurenine metabolites showed modest toxicity towards SH-SY5Y neuroblastoma cells in a concentration-dependent manner. Specific cell death pathways, including apoptosis, necrosis and free radical production were shown to be increased after both 24 and 72 h exposure of SH-SY5Y neuroblastoma cells to 3-hydroxykynurenine and 3-hydroxyanthranilic acid and various combinations of neurotoxic kynurenine metabolites. Conclusion: It is well documented that neurotoxic kynurenine metabolites show toxicity towards primary human neurons in the nanomolar to low micromolar concentration range. Results show that the concentrations required to show significant cell death are in the range of 1000 µM for 3-hydroxykynurenine and 3-hydroxyanthranilic acid and toxicity of quinolinic acid towards SH-SY5Y was unable to be shown. This differs significantly from toxicities observed in primary human neurons. Combinations of the neurotoxic metabolites were shown to have modest toxicity towards these cells with increased toxicity and activation of cell death pathways observed after 72 h exposure. This study suggests that the 24 h model is unsuitable for use in neurotoxicity studies, however, the 72 h model better represents the observations of the studies using primary human neurons and may provide some benefit in providing a cost-effective model to assess possible protective agents against kynurenine metabolite toxicities.

Keywords: kynurenine metabolites, neurotoxicity, quinolinic acid, SH-SY5Y neuroblastoma

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Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

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The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

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Authors: Muhammad Rosli Abdullah, Noor Hasmiza Harun

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A microorganism detection system has a potential to be used with the advancement in a biosensor development. The detection system requires an optical sensing system, microfluidic device and biological reagent. Although, the biosensors are available in the market, a label free and a lab-on-chip approach will promote a flexible solution. As a preliminary study of microorganism detection, three mechanisms such as Total Internal Reflection (TIR), Micro Fluidic Channel (MFC) and magnetic-electric field propagation were study and simulated. The objective are to identify the TIR angle, MFC parabolic flow and the wavelength for the microorganism detection. The simulation result indicates that evanescent wave is achieved when TIR angle > 42°, the corner and centre of a parabolic velocity are 0.02 m/s and 0.06 m/s respectively, and a higher energy distribution of a perfect electromagnetic scattering with dipole resonance radiation occurs at 500 nm. This simulation is beneficial to determine the components of the microorganism detection system that does not rely on classical microbiological, immunological and genetic methods which are laborious, time-consuming procedures and confined to specialized laboratories with expensive instrumentation equipment.

Keywords: microorganism, microfluidic, total internal reflection, lab on chip

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Raymond C. Hawkins II, Catherine A. Hawkins

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The System Contextual Integrated Model (SCIM), developed as a trans-theoretical framework for selecting measures for psychotherapy process and outcome, is reformulated for behavioral health applications. The SCIM “healing cycle” is an allostatic hedonic affective-cognitive right-hemisphere–left-hemisphere coordinated process involving positive alliesthesia that mitigates traumatic pain and generates psychological flexibility. The SCIM “trauma cycle” is an allostatic overload alliesthesia opponent process with long-lasting pathology sequelae. The social ecological context moderates the “healing cycle” and the “trauma cycle.” Repeated evocation of the “healing cycle” in a therapeutic relationship can gradually relieve trauma sequelae. The SCIM is applied to pain, obese binge eating, and substance use disorders.

Keywords: allostasis, alliesthesia, opponent process, behavioral health, assessment

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

Abstract:

Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

Procedia PDF Downloads 279

Authors: Elise M. Shauf

Abstract:

Beryllium can be found naturally in some fruits and vegetables (carrots, garden peas, kidney beans, pears) at very low concentrations, but is typically not clinically significant due to the low-level exposure and limited absorption of beryllium by the stomach and intestines. However, acute or chronic beryllium exposure can result in harmful toxic and carcinogenic biological effects. Beryllium can be both a workplace hazard and an environmental pollutant, therefore determining the presence of beryllium at trace levels can be essential to protect workers as well as the environment. Analysis of gallein, C₂₀H₁₂O₇, to determine if it is usable as a fluorescent dye for beryllium detection. The primary detection method currently in use includes hydroxybenzoquinoline sulfonates (HBQS), for which alternative indicators are desired. Unfortunately, gallein does not have the desired aspects needed as a dye for beryllium detection due to the peak shift properties.

Keywords: beryllium detection, fluorescent, gallein dye, indicator, spectroscopy

Procedia PDF Downloads 119

Authors: Dana Craciun, Daniela Dascalu, Adriana Isvoran

Abstract:

Phthalates are a class of plastic additives that are used to enhance the physical properties of plastics and as solvents in paintings and some of them proved to be of particular concern for the human health. There are insufficient data concerning the health risks of phthalates and further research on evaluating their effects in humans is needed. As humans are not volunteers for such experiments, computational analysis may be used to predict the biological effects of phthalates in humans. Within this study we have used some computational approaches (SwissADME, admetSAR, FAFDrugs) for predicting the absorption, distribution, metabolization, excretion and toxicity (ADME-Tox) profiles and pharmacokinetics for the most common used phthalates. These computational tools are based on quantitative structure-activity relationship modeling approach. The predictions are further compared to the known effects of each considered phthalate in humans and correlations between computational results and experimental data are discussed. Our data revealed that phthalates are a class of compounds reflecting high toxicity both when ingested and when inhaled, but by inhalation their toxicity is even greater. The predicted harmful effects of phthalates are: toxicity and irritations of the respiratory and gastrointestinal tracts, dyspnea, skin and eye irritations and disruption of the functions of liver and of the reproductive system. Many of investigated phthalates are predicted to be able to inhibit some of the cytochromes involved in the metabolism of numerous drugs and consequently to affect the efficiency of administrated treatments for many diseases and to intensify the adverse drugs reactions. The obtained predictions are in good agreement with clinical data concerning the observed effects of some phthalates in cases of acute exposures. Our study emphasizes the possible health effects of numerous phthalates and underlines the applicability of computational methods for predicting the biological effects of xenobiotics.

Keywords: phthalates, ADME-Tox, pharmacokinetics, biological effects

Procedia PDF Downloads 231