Search results for: virus detection

Authors: Atefeh Esmailnejad, Mohammad Abbaszadeh Hasiri

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Coxiella burnetii is a gram-negative obligatory intracellular bacterium that causes Q fever, a significant zoonotic disease. Sheep, cattle, and goats are the most commonly reported reservoirs for the bacteria, but infected cats and dogs have also been implicated in the transmission of the disease to human. The aim of present study was to investigate the presence of antibodies against Coxiella burnetii among companion dogs in Fars province, South of Iran. A total of 181 blood samples were collected from asymptomatic dogs, mostly referred to Veterinary Hospital of Shiraz University for regular vaccination. The IgG antibody detection against Coxiella burnetii was made by indirect Enzyme-linked Immunosorbent Assay (ELISA), employing phase I and II Coxiella burnetii antigens. A logistic regression model was developed to analyze multiple risk factors associated with seropositivity. An overall seropositivity of 7.7% (n=14) was observed. Prevalence was significantly higher in adult dogs above five years (18.18 %) compared with dogs between 1 and five years (7.86 %) and less than one year (6.17%) (P=0.043). Prevalence was also higher in male dogs (11.21 %) than in female (2.7 %) (P=0.035). There were no significant differences in the prevalence of positive cases and breed, type of housing, type of food and exposure to other farm animals (P>0.05). The results of this study showed the presence of Coxiella burnetii infection among the companion dogs population in Fars province. To our knowledge, this is the first study regarding Q fever in dogs carried out in Iran. In areas like Iran, where human cases of Q fever are not common or remain unreported, the public health implications of Q fever seroprevalence in dogs are quite significant.

Keywords: Coxiella burnetii, dog, Iran, Q fever

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Authors: Hyun-Kyung Lee, Jehyung Oh, Young Eun Jeong, Hyun-Shik Lee

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Perfluoroalkyl compounds (PFCs) are environmental toxicants that persistently accumulate in the human blood. Their widespread detection and accumulation in the environment raise concerns about whether these chemicals might be developmental toxicants and teratogens in the ecosystem. We evaluated and compared the toxicity of PFCs of containing various numbers of carbon atoms (C8-11 carbons) on vertebrate embryogenesis. We assessed the developmental toxicity and teratogenicity of various PFCs. The toxic effects on Xenopus embryos were evaluated using different methods. We measured teratogenic indices (TIs) and investigated the mechanisms underlying developmental toxicity and teratogenicity by measuring the expression of organ-specific biomarkers such as xPTB (liver), Nkx2.5 (heart), and Cyl18 (intestine). All PFCs that we tested were found to be developmental toxicants and teratogens. Their toxic effects were strengthened with increasing length of the fluorinated carbon chain. Furthermore, we produced evidence showing that perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFuDA) are more potent developmental toxicants and teratogens in an animal model compared to the other PFCs we evaluated [perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA)]. In particular, severe defects resulting from PFDA and PFuDA exposure were observed in the liver and heart, respectively, using the whole mount in situ hybridization, real-time PCR, pathologic analysis of the heart, and dissection of the liver. Our studies suggest that most PFCs are developmental toxicants and teratogens, however, compounds that have higher numbers of carbons (i.e., PFDA and PFuDA) exert more potent effects.

Keywords: PFC, xenopus, fetax, development

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: Shenghui Wu, Patricia Chalela, Amelie G. Ramirez

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Background: Cervical cancer (CC), colorectal cancer (CRC), and breast cancer (BC) are diseases that can be prevented/detected through early test. Through educational programs, individuals can become better informed about these cancers and understand the importance of screening and early detection. A community-based educational program was developed to improve knowledge and awareness toward the screening of the three cancer types in a South Texas underserved population. Methods: Residents living in Laredo, Texas were invited to participate in the present study. From January 2020 to April 2021, participants were recruited using social media and flyer distributions in general community. Participants received a free live web cancer education presentation delivered by bilingual community health educators, and online pre- and post-education surveys for CC, CRC, and BC separately. Pre-post changes in knowledge for individual items were compared using McNemar’s chi-squared tests. Results: Overall, participants demonstrated increases in CC (n=237), CRC (n=59), and BC (n=56) screening knowledge and awareness after receiving the cancer screening education (Ps<0.05). After receiving the cancer screening education, 85-97% of participants had an intent to talk to a healthcare provider about CC/CRC/BC screening, 88-97% had an intent to get a CC/CRC/BC screening test in the next 12 months or at the next routine appointment, and 90-97% had an intent to talk about CC/CRC/BC with their family members or friends. Conclusion: A community-based educational program can help increase knowledge and awareness about cervical, colorectal, and breast cancer screening, promote positive changes in population's knowledge and awareness about the benefits of cancer screening.

Keywords: cervical cancer, colorectal cancer, breast cancer, educational program, health knowledge, awareness, Hispanics, screening, health education

Procedia PDF Downloads 107

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

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Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck, Jason Stanley, Leroy Whilby

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Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major threat to fruit and vegetable industries in the United States. The establishment of pest fruit fly in the agricultural industries and produce severe ecological and economic impacts on agricultural diversification and trade. Detection and identification of these agricultural pests in a timely manner will facilitate the possibility of eradication from newly invaded areas. Identification of larval stages to species level is difficult, but is required to determine pest loads and their pathways into the United States. The aim of this study is the New World genus, Anastrepha which includes pests of major economic importance. Mitochondrial cytochrome c oxidase I (COI) gene sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level. During phylogenetics analysis numerous nuclear mitochondrial pseudogenes (numts) were discovered in different specimens. The numts are nonfunctional copies of the mtDNA present in the nucleus and are easily coamplified with the mitochondrial COI gene copy by using conserved universal primers. This is problematic for DNA Barcoding, which attempts to characterize all living organisms by using the COI gene. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed.

Keywords: tephritid, Anastrepha fraterculus, COI, numts

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Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan

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Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.

Keywords: silver nanoparticles, dithizone, DFT, NMR

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Authors: Lu Zhao, Yanrong Kang, Lili Guo, Yuan Long, Guidong Xing

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Smart watches, as a handy device with rich functionality, has become one of the most popular wearable devices all over the world. Among the various function, the most basic is health monitoring. The monitoring data can be provided as an effective evidence or a clue for the detection of crime cases. For instance, the step counting data can help to determine whether the watch wearer was quiet or moving during the given time period. There is, however, still quite few research on the analysis of human character based on these data. The purpose of this research is to analyze the health monitoring data to distinguish the drinking state from normal state. The analysis result may play a role in cases involving drinking, such as drunk driving. The experiment mainly focused on finding the figures of smart watch health monitoring data that change with drinking and figuring up the change scope. The chosen subjects are mostly in their 20s, each of whom had been wearing the same smart watch for a week. Each subject drank for several times during the week, and noted down the begin and end time point of the drinking. The researcher, then, extracted and analyzed the health monitoring data from the watch. According to the descriptive statistics analysis, it can be found that the heart rate change when drinking. The average heart rate is about 10% higher than normal, the coefficient of variation is less than about 30% of the normal state. Though more research is needed to be carried out, this experiment and analysis provide a thought of the application of the data from smart watches.

Keywords: character analysis, descriptive statistics analysis, drink state, heart rate, smart watch

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Authors: D. S. Malatesh, K. J. Ananda, C. Ansar Kamran, K. Ganesh Udupa

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Dirofilaria repens is a mosquito-borne filarioid nematode of dogs and other carnivores and accidentally affects humans. D. repens is reported in many countries, including India. Subcutaneous dirofilariosis caused by D. repens is a zoonotic disease, widely distributed throughout Europe, Asia, and Africa, with higher prevalence reported in dogs from Sri Lanka (30-60%), Iran (61%) and Italy (21-25%). Dirofilariasis in dogs was diagnosed by detection of microfilariae in blood. Identification of different Dirofilaria species was done by using molecular methods like polymerase chain reaction (PCR). Even though many researchers reported molecular evidence of D. repens across India, to our best knowledge there is no data available on molecular diagnosis of D. repens in dogs and its zoonotic implication in Karnataka state a southern state in India. The aim of the present study was to identify the Dirofilaria species occurring in dogs from Karnataka, India. Out of 310 samples screened for the presence of microfilariae using traditional diagnostic methods, 99 (31.93%) were positive for the presence of microfilariae. Based on the morphometry, the microfilariae were identified as D. repens. For confirmation of species, the samples were subjected to PCR using pan filarial primers (DIDR-F1, DIDR-R1) for amplification of internal transcribed spacer region 2 (ITS2) of the ribosomal DNA. The PCR product of 484 base pairs on agarose gel was indicative of D. repens. Hence, a single PCR reaction using pan filarial primers can be used to differentiate filarial species found in dogs. The present study confirms that dirofilarial species occurring in dogs from Karnataka is D. repens and further sequencing studies are needed for genotypic characterization of D. repens.

Keywords: Dirofilaria repens, molecular characterization, polymerase chain reaction, Karnataka, India

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Authors: Sze Shin Low, Michelle T. T. Tan, Poi Sim Khiew, Hwei-San Loh

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An efficient graphene/zinc oxide (PSE-G/ZnO) platform based on pi-pi stacking, non-covalent interactions for the development of aptamer-based biosensor was presented in this study. As a proof of concept, the DNA recognition capability of the as-developed PSE-G/ZnO enhanced aptamer-based biosensor was evaluated using Coconut Cadang-cadang viroid disease (CCCVd). The G/ZnO nanocomposite was synthesised via a simple, green and efficient approach. The pristine graphene was produced through a single step exfoliation of graphite in sonochemical alcohol-water treatment while the zinc nitrate hexahydrate was mixed with the graphene and subjected to low temperature hydrothermal growth. The developed facile, environmental friendly method provided safer synthesis procedure by eliminating the need of harsh reducing chemicals and high temperature. The as-prepared nanocomposite was characterised by X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) to evaluate its crystallinity, morphology and purity. Electrochemical impedance spectroscopy (EIS) was employed for the detection of CCCVd sequence with the use of potassium ferricyanide (K3[Fe(CN)6]). Recognition of the RNA analytes was achieved via the significant increase in resistivity for the double stranded DNA, as compared to single-stranded DNA. The PSE-G/ZnO enhanced aptamer-based biosensor exhibited higher sensitivity than the bare biosensor, attributing to the synergistic effect of high electrical conductivity of graphene and good electroactive property of ZnO.

Keywords: aptamer-based biosensor, graphene/zinc oxide nanocomposite, green synthesis, screen printed carbon electrode

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Authors: Hoda Mahgoub, Abeer Hanafy

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Linagliptin (LNG) belongs to dipeptidyl-peptidase-4 (DPP-4) inhibitor class. DPP-4 inhibitors represent a new therapeutic approach for the treatment of type 2 diabetes in adults. The aim of this work was to develop and validate an accurate and reproducible HPLC method for the determination of LNG with high sensitivity in rat plasma. The method involved separation of both LNG and pindolol (internal standard) at ambient temperature on a Zorbax Eclipse XDB C18 column and a mobile phase composed of 75% methanol: 25% formic acid 0.1% pH 4.1 at a flow rate of 1.0 mL.min-1. UV detection was performed at 254nm. The method was validated in compliance with ICH guidelines and found to be linear in the range of 5–1000ng.mL-1. The limit of quantification (LOQ) was found to be 5ng.mL-1 based on 100µL of plasma. The variations for intra- and inter-assay precision were less than 10%, and the accuracy values were ranged between 93.3% and 102.5%. The extraction recovery (R%) was more than 83%. The method involved a single extraction step of a very small plasma volume (100µL). The assay was successfully applied to an in-vivo pharmacokinetic study of LNG in rats that were administered a single oral dose of 10mg.kg-1 LNG. The maximum concentration (Cmax) was found to be 927.5 ± 23.9ng.mL-1. The area under the plasma concentration-time curve (AUC0-72) was 18285.02 ± 605.76h.ng.mL-1. In conclusion, the good accuracy and low LOQ of the bioanalytical HPLC method were suitable for monitoring the full pharmacokinetic profile of LNG in rats. The main advantages of the method were the sensitivity, small sample volume, single-step extraction procedure and the short time of analysis.

Keywords: HPLC, linagliptin, pharmacokinetic study, rat plasma

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Authors: Asma Lamin, Anna H. Kaksonen, Ivan Cole, Paul White, Xiao-Bo Chen

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Microbiologically influenced corrosion (MIC) is a process in which microorganisms initiate, facilitate, or accelerate the electrochemical corrosion reactions of metallic components. Several reports documented that MIC accounts for about 20 to 40 % of the total cost of corrosion. Biofilm formation due to the presence of microorganisms on the surface of metal components is known to play a vital role in MIC, which can lead to severe consequences in various environmental and industrial settings. Quorum sensing (QS) system plays a major role in regulating biofilm formation and control the expression of some microbial enzymes. QS is a communication mechanism between microorganisms that involves the regulation of gene expression as a response to the microbial cell density within an environment. This process is employed by both Gram-positive and Gram-negative bacteria to regulate different physiological functions. QS involves production, detection, and responses to signalling chemicals, known as auto-inducers. QS controls specific processes important for the microbial community, such as biofilm formation, virulence factor expression, production of secondary metabolites and stress adaptation mechanisms. The use of QS inhibitors (QSIs) has been proposed as a possible solution to biofilm related challenges in many different applications. Although QSIs have demonstrated some strength in tackling biofouling, QSI-based strategies to control microbially influenced corrosion have not been thoroughly investigated. As such, our research aims to target the QS mechanisms as a strategy for mitigating MIC on metal surfaces in engineered systems.

Keywords: quorum sensing, quorum quenching, biofilm, biocorrosion

Procedia PDF Downloads 90

Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study.These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production.

Keywords: Escherichia coli, Klebsiella spp, Uropathogens, virulence features

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Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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Authors: Husham Bayazed

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Immune responses following surgical trauma play a pivotal role in predicting postoperative outcomes from healing and recovery to postoperative complications. Postoperative complications, including infections and protracted recovery, occur in a significant number of about 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on the healthcare system in any community. The accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain major clinical provocations. Recent Findings: Recent studies are focusing on immune dysregulation mechanisms that occur in response to surgical trauma as a key determinant of postoperative complications. Antecedent studies mainly were plunging into the detection of inflammatory plasma markers, which facilitate in providing important clues regarding their pathogenesis. However, recent Single-cell technologies, such as mass cytometry or single-cell RNA sequencing, have markedly enhanced our ability to understand the immunological basis of postoperative immunological trauma complications and to identify their prognostic biological signatures. Summary: The advent of proteomic technologies has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers and providing patients and surgeons with information to improve surgical outcomes. However, more studies are required to accurately predict the risk of postoperative complications in individual patients.

Keywords: immune dysregulation, postoperative complications, surgical trauma, flow cytometry

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Authors: Man Ying Kang, Joshua Kin Man Nan

Abstract:

The prolonged pandemic has posed alarming public health challenges to various parts of the world, and face-to-face mental health treatment is largely discounted for the control of virus transmission, online psychological services and self-help mental health kits have become essential. Online self-help mindfulness-based interventions have proved their effects on fostering mental health for different populations over the globe. This paper was to test the effectiveness of an online short-term audio-based mindfulness (SAM) program in enhancing wellbeing, dispositional mindfulness, and reducing stress and negative affect in community settings in China, and to explore possible mechanisms of how dispositional mindfulness, stress, and negative affect influenced the intervention effects on wellbeing. Community-dwelling adults were recruited via online social networking sites (e.g., QQ, WeChat, and Weibo). Participants (n=100) were randomized into the mindfulness group (n=50) and a waitlist control group (n=50). In the mindfulness group, participants were advised to spend 10–20 minutes listening to the audio content, including mindful-form practices (e.g., eating, sitting, walking, or breathing). Then practice daily mindfulness exercises for 3 weeks (a total of 21 sessions), whereas those in the control group received the same intervention after data collection in the mindfulness group. Participants in the mindfulness group needed to fill in the World Health Organization Five Well-Being Index (WHO), Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and Freiburg Mindfulness Inventory (FMI) four times: at baseline (T0) and at 1 (T1), 2 (T2), and 3 (T3) weeks while those in the waitlist control group only needed to fill in the same scales at pre- and post-interventions. Repeated-measure analysis of variance, paired sample t-test, and independent sample t-test was used to analyze the variable outcomes of the two groups. The parallel process latent growth curve modeling analysis was used to explore the longitudinal moderated mediation effects. The dependent variable was WHO slope from T0 to T3, the independent variable was Group (1=SAM, 2=Control), the mediator was FMI slope from T0 to T3, and the moderator was T0NA and T0PSS separately. The different levels of moderator effects on WHO slope was explored, including low T0NA or T0PSS (Mean-SD), medium T0NA or T0PSS (Mean), and high T0NA or T0PSS (Mean+SD). The results found that SAM significantly improved and predicted higher levels of WHO slope and FMI slope, as well as significantly reduced NA and PSS. FMI slope positively predict WHO slope. FMI slope partially mediated the relationship between SAM and WHO slope. Baseline NA and PSS as the moderators were found to be significant between SAM and WHO slope and between SAM and FMI slope, respectively. The conclusion was that SAM was effective in promoting levels of mental wellbeing, positive affect, and dispositional mindfulness as well as reducing negative affect and stress in community settings in China. SAM improved wellbeing faster through the faster enhancement of dispositional mindfulness. Participants with medium-to-high negative affect and stress buffered the therapy effects of SAM on wellbeing improvement speed.

Keywords: mindfulness, negative affect, stress, wellbeing, randomized control trial

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Authors: Paria Soleimani, Arezoo Neshati

Abstract:

Myocardial infarction is one of the leading causes of ‎death in the world. Some of these deaths occur even before the patient ‎reaches the hospital. Myocardial infarction occurs as a result of ‎impaired blood supply. Because the most of these deaths are due to ‎coronary artery disease, hence the awareness of the warning signs of a ‎heart attack is essential. Some heart attacks are sudden and intense, but ‎most of them start slowly, with mild pain or discomfort, then early ‎detection and successful treatment of these symptoms is vital to save ‎them. Therefore, importance and usefulness of a system designing to ‎assist physicians in the early diagnosis of the acute heart attacks is ‎obvious.‎ The purpose of this study is to determine how well a predictive ‎model would perform based on the only patient-reportable clinical ‎history factors, without using diagnostic tests or physical exams. This ‎type of the prediction model might have application outside of the ‎hospital setting to give accurate advice to patients to influence them to ‎seek care in appropriate situations. For this purpose, the data were ‎collected on 711 heart patients in Iran hospitals. 28 attributes of clinical ‎factors can be reported by patients; were studied. Three logistic ‎regression models were made on the basis of the 28 features to predict ‎the risk of heart attacks. The best logistic regression model in terms of ‎performance had a C-index of 0.955 and with an accuracy of 94.9%. ‎The variables, severe chest pain, back pain, cold sweats, shortness of ‎breath, nausea, and vomiting were selected as the main features.‎

Keywords: Coronary heart disease, Acute heart attacks, Prediction, Logistic ‎regression‎

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Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

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The translation of healthcare technologies is an expensive, complex affair, current healthcare challenges in Asian countries and their efforts to meet Millennium Development Goals (MDGs), necessitates continuous technology advancement to save countless lives, improve the quality of life and for socio-economic development. India’s consistently improving global innovation index (57) demonstrates its innovation potential, but access to health care is asymmetric and lacks priority in India. Therefore, there is utmost need of a robust translation system for point-of-care (POC) solutions, inexpensive, low-maintenance, reliable, and easy-to-use diagnostic technologies. Few cases of POC technologies viz. Elisa based diagnostic kits for regional viral disease, a device for detection of cancerous lesions were studied to understand the process and challenges involved in their translation. Accordingly, the entire translation ecosystem was summarized proposing a nexus of various actors such as technology developer, technology transferor technology receiver, funding entities, government/regulatory bodies and their effect on translation of different medical technologies. This study highlights the role and concerns pertaining to these actors for POC such as unsystematic and unvalidated research roadmap, low profit preposition, unfocused approach of up-scaling, low market acceptability and multiple window regulatory framework, etc. This provides an opportunity to devise solutions to overcome problem areas in translation path.

Keywords: healthcare technologies, point-of-care solutions, public health, translation

Procedia PDF Downloads 171

Authors: Ha T. T. Ly, Truc B. Truc, Hai N. Truong, Mai P. T. Nguyen, Ngoc D. Ngo, Khanh V. Tran, Hai T. Le

Abstract:

Beta thalassemia is one of the most common inherited blood disorders, which is characterized by decreased or absent in beta globin expression. Patients with Beta thalassemia whose anemia is not so severe as to necessitate transfusions are said to have thalassemia intermedia. Objective: The goal of this study is prenatal diagnosis for pregnancy woman with Beta thalassemia intermedia and her husband with Beta thalassemia carrier at high risk of Beta thalassemia major in Northern of Vietnam. Material and method: The family has a 6 years-old compound heterozygous thalassemia major for CD71/72(+A) and Hbb:c. -78A>G/nt-28(A>G) male child. The father was heterozygous for CD71/72(+A) mutation which is Beta plus type and the mother was compound heterozygosity of two different variants, namely, Hbb: c. -78A>G/nt-28(A>G) and CD26(A-G) HbE. Prenatal Beta thalassemia mutation detection in fetal DNA was carried out using multiplex Amplification-refractory mutation system ARMS-PCR and confirmed by direct Sanger-sequencing Hbb gene. Prenatal diagnoses were perfomed by amniotic fluid sampling from pregnant woman in the 16-18th week of pregnancy after the genotypes of parents of the probands were identified. Result: When amniotic fluid sample was analyzed for Beta globin gene (Hbb), we found that the genotype is heterozygous for CD71/72(+A) and CD26(A-G) HbE. This genotype is different from the 1st child of this family. Conclusion: Prenatal diagnosis helps the parents to know the genotype and the thalassemia status of the fetus, so they can have early decision on their pregnancy. Genetic diagnosis provided a useful method in diagnosis for familial members in pedigree, genetic counseling and prenatal diagnosis.

Keywords: beta thalassemia intermedia, Hbb gene, pedigree, prenatal diagnosis

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Authors: Riya Thomas, Denis Music, Tautgirdas Ruzgas

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The detection of tyrosinase holds considerable interest in the domains of food nutrition and human health due to its significant role in causing a detrimental effect on the colour, flavour, and nutritional value of food as well as in the synthesis of melanin causing skin melanoma. Compared to other conventional analytical techniques, electrochemical (EC) sensors are highly promising owing to their quick response, great sensitivity, ease of use, and low cost. Particularly, titania nanoparticle-based electrochemical sensors have drawn special attention in identifying several biomolecules including enzymes, antibodies, and receptors, owing to their enhanced electrocatalytic activity and electron-accepting properties. In this study, Ti-O film-modified electrode is fabricated using reactive magnetron sputtering, and its affinity towards tyrosinase is examined via electrochemical methods. To comprehend the physiochemical and surface properties-governed electrocatalytic activity of modified electrodes, Ti-O films are grown under various compositional ranges and deposition temperature, and their corresponding electrochemical activity towards tyrosinase is studied. Further, to understand the underlying atomistic mechanisms and electronic-scale electrochemical characteristics, density functional theory (DFT) is employed. The main goal of the current work is to determine the correlation between macroscopic measurements and the underlying atomic properties to improve the tyrosinase activity on Ti-O surfaces. Moreover, this work offers an intriguing new perspective on the use of Ti-O-modified electrodes to detect tyrosinase in the areas of clinical diagnosis, skincare, and food science.

Keywords: density functional theory, electrochemical sensor, Ti-O film, tyrosinase

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Authors: Chun-Lin Chiang, Che-Yen Lee, Yu-Shan Yeh, Jiunn-Haur Shaw

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Wafer fabrication is a critical part of the semiconductor process, when the finest linewidth with the improvement of technology continues to decline and the structure development from 2D towards to 3D. The nanoparticles contained in the slurry or in the ultrapure water which used for cleaning have a large influence on the manufacturing process. Therefore, semiconductor industry is hoping to find a viable method for on-line detection the nanoparticles size and concentration. The resistive pulse sensing technology is one of the methods that may cover this question. As we know that nanoparticles properties of material differ significantly from their properties at larger length scales. So, we want to clear that the metal and non-metal nanoparticles translocation dynamic when we use the resistive pulse sensing technology. In this study we try to use the finite element method that contains three governing equations to do multiphysics coupling simulations. The Navier-Stokes equation describes the laminar motion, the Nernst-Planck equation describes the ion transport, and the Poisson equation describes the potential distribution in the flow channel. To explore that the metal nanoparticles and the non-metal nanoparticles in different concentration electrolytes, through the nanochannel caused by ion current changes. Then the reliability of the simulation results was verified by resistive pulse sensing test. The existing results show that the lower ion concentration, the greater effect of nanoparticles on the ion concentration in the nanochannel. The conductive spikes are correlated with nanoparticles surface charge. Then we can be concluded that in the resistive pulse sensing technique, the ion concentration in the nanochannel and nanoparticle properties are important for the translocation dynamic, and they have the interactions.

Keywords: multiphysics simulations, resistive pulse sensing, nanoparticles, nanochannel

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

Procedia PDF Downloads 47

Authors: Zakaria Boual, Abdellah Kemassi, Toufik Chouana, Philippe Michaud, Mohammed Didi Ould El Hadj

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In order to investigate the prebiotic potential of oligosaccharides prepared by chemical hydrolysis of water-soluble polysaccharides (WSP) from Zizyphus lotus leaves, the effect of oligosaccharides on bacterial growth was studied. The chemical composition of WSP was evaluated by colorimetric assays revealed the average values: 7.05±0.73% proteins and 86.21±0.74% carbohydrates, among them 64.81±0.42% are neutral sugar and the rest 16.25±1.62% are uronic acids. The characterization of monosaccharides was determined by high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) was found to be composed of galactose (23.95%), glucose (21.30%), rhamnose (20.28%), arabinose (9.55%), and glucuronic acid (22.95%). The effects of oligosaccharides on the growth of lactic acid bacteria were compared with those of fructo-oligosaccharide (RP95). The oligosaccharides concentration was 1g/L of man rogosa sharpe broth. Bacterial growth was assessed during 2, 4.5, 6.5, 9, 12, 16 and 24 h by measuring the optical density of the cultures at 600 nm (OD600) and pH values. During fermentation, pH in broth cultures decreased from 6.7 to 5.87±0.15. The enumeration of lactic acid bacteria indicated that oligosaccharides led to a significant increase in bacteria (P≤0.05) compared to the control. The fermentative metabolism appeared to be faster on RP95 than on oligosaccharides from Zizyphus lotus leaves. Both RP95 and oligosaccharides showed clear prebiotic effects, but had differences in fermentation kinetics because of to the different degree of polymerization. This study shows the prebiotic effectiveness of oligosaccharides, and provides proof for the selection of leaves of Zizyphus lotus for use as functional food ingredients.

Keywords: Zizyphus lotus, polysaccharides, characterization, prebiotic effects

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

Procedia PDF Downloads 107

Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Majed Ahmed Al-Mansoub, Muhammad Qamar

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There is a progressive increase in the prevalence of early onset Type 2 diabetes mellitus. Early detection of Type 2 diabetes enhances the length and/or quality of life which might result from a reduction in the severity, frequency or prevent or delay of its long-term complications. The study aims to determine the onset age for the first diagnosis of Type 2 diabetes mellitus. A retrospective study conducted in the endocrine clinic at Hospital Pulau Pinang in Penang, Malaysia, January- December 2016. Records of 519 patients with Type 2 diabetes mellitus were screened to collect demographic data and determine the age of first-time diabetes mellitus diagnosis. Patients classified according to the age of diagnosis, gender, and ethnicity. The study included 519 patients with age (55.6±13.7) years, female 265 (51.1%) and male 254 (48.9%). The ethnicity distribution was Malay 191 (36.8%), Chinese 189 (36.4%) and Indian 139 (26.8%). The age of Type 2 diabetes diagnosis was (42±14.8) years. The female onset of diabetes mellitus was at age (41.5±13.7) years, while male (42.6±13.7) years. Distribution of diabetic onset by ethnicity was Malay at age (40.7±13.7) years, Chinese (43.2±13.7) years and Indian (42.3±13.7) years. Diabetic onset was classified by age as follow; ≤20 years’ cohort was 33 (6.4%) cases. Group >20- ≤40 years was 190 (36.6%) patients, and category >40- ≤60 years was 270 (52%) subjects. On the other hand, the group >60 years was 22 (4.2%) patients. The range of diagnosis was between 10 and 73 years old. Conclusion: Malay and female have an earlier onset of diabetes than Indian, Chinese and male. More than half of the patients had diabetes between 40 and 60 years old. Diabetes mellitus is becoming more common in younger age <40 years. The age at diagnosis of Type 2 diabetes mellitus has decreased with time.

Keywords: age of onset, diabetes diagnosis, diabetes mellitus, Malaysia, outpatients, type 2 diabetes, retrospective study

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Authors: Suprit Pradhan, Tshering Yangzom

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Even with availability of the modern day online insulation diagnostic technologies like partial discharge monitoring, the measurements like Dissipation Factor (tanδ), DC High Voltage Insulation Currents, Polarization Index (PI) and Insulation Resistance Measurements are still widely used as a diagnostic tools to assess the condition of stator insulation in hydro power plants. To evaluate the condition of stator winding insulation in one of the generators that have been operated since 1999, diagnostic tests were performed on the stator bars of 15 MVA generators of Basochhu Hydropower Plant. This paper presents diagnostic study done on the data gathered from the measurements which were performed in 2015 and 2016 as part of regular maintenance as since its commissioning no proper aging data were maintained. Measurement results of Dissipation Factor, DC High Potential tests and Polarization Index are discussed with regard to their effectiveness in assessing the ageing condition of the stator insulation. After a brief review of the theoretical background, the strengths of each diagnostic method in detecting symptoms of insulation deterioration are identified. The interesting results observed from Basochhu Hydropower Plant is taken into consideration to conclude that Polarization Index and DC High Voltage Insulation current measurements are best suited for the detection of humidity and contamination problems and Dissipation Factor measurement is a robust indicator of long-term ageing caused by oxidative degradation.

Keywords: dissipation Factor (tanδ), polarization Index (PI), DC High Voltage Insulation Current, insulation resistance (IR), Tan Delta Tip-Up, dielectric absorption ratio

Procedia PDF Downloads 312

Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

Procedia PDF Downloads 178

Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

Procedia PDF Downloads 368