Search results for: injury identification

Authors: Igor Jerkovic

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Biodiversity of flora provides many different nectar sources for the bees. Unifloral honeys possess distinctive flavours, mainly derived from their nectar sources (characteristic volatile organic components (VOCs)). Specific or nonspecific VOCs (chemical markers) could be used for unifloral honey characterisation as addition to the melissopalynologycal analysis. The main honey volatiles belong, in general, to three principal categories: terpenes, norisoprenoids, and benzene derivatives. Some of these substances have been described as characteristics of the floral source, and other compounds, like several alcohols, branched aldehydes, and furan derivatives, may be related to the microbial purity of honey processing and storage conditions. Selection of the extraction method for the honey volatiles profiling should consider that heating of the honey produce different artefacts and therefore conventional methods of VOCs isolation (such as hydrodistillation) cannot be applied for the honey. Two-way approach for the isolation of the honey VOCs was applied using headspace solid-phase microextraction (HS-SPME) and ultrasonic solvent extraction (USE). The extracts were analysed by gas chromatography and mass spectrometry (GC-MS). HS-SPME (with the fibers of different polarity such as polydimethylsiloxane/ divinylbenzene (PDMS/DVB) or divinylbenzene/carboxene/ polydimethylsiloxane (DVB/CAR/PDMS)) enabled isolation of high volatile headspace VOCs of the honey samples. Among them, some characteristic or specific compounds can be found such as 3,4-dihydro-3-oxoedulan (in Centaurea cyanus L. honey) or 1H-indole, methyl anthranilate, and cis-jasmone (in Citrus unshiu Marc. honey). USE with different solvents (mainly dichloromethane or the mixture pentane : diethyl ether 1 : 2 v/v) enabled isolation of less volatile and semi-volatile VOCs of the honey samples. Characteristic compounds from C. unshiu honey extracts were caffeine, 1H-indole, 1,3-dihydro-2H-indol-2-one, methyl anthranilate, and phenylacetonitrile. Sometimes, the selection of solvent sequence was useful for more complete profiling such as sequence I: pentane → diethyl ether or sequence II: pentane → pentane/diethyl ether (1:2, v/v) → dichloromethane). The extracts with diethyl ether contained hydroquinone and 4-hydroxybenzoic acid as the major compounds, while (E)-4-(r-1’,t-2’,c-4’-trihydroxy-2’,6’,6’-trimethylcyclo-hexyl)but-3-en-2-one predominated in dichloromethane extracts of Allium ursinum L. honey. With this two-way approach, it was possible to obtain a more detailed insight into the honey volatile and semi-volatile compounds and to minimize the risks of compound discrimination due to their partial extraction that is of significant importance for the complete honey profiling and identification of the chemical biomarkers that can complement the pollen analysis.

Keywords: honey chemical biomarkers, honey volatile compounds profiling, headspace solid-phase microextraction (HS-SPME), ultrasonic solvent extraction (USE)

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: A. T. Perez Fontenla, S. Sgobba, A. Bartkowska, Y. Askar, M. Dalemir Celuch, A. Newborough, M. Karppinen, H. Haalien, S. Deleval, S. Larcher, C. Charvet, L. Bruno, R. Trant

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The present study investigates the corrosion behavior of copper (Cu) based conducts predominantly brazed with Sil-Fos (self-fluxing copper-based filler with silver and phosphorus) within various cooling circuits of demineralized water across different particle accelerator components at CERN. The study covers a range of sample service time, from a few months to fifty years, and includes various accelerator components such as quadrupoles, dipoles, and bending magnets. The investigation comprises the established sample extraction procedure, examination methodology including non-destructive testing, evaluation of the corrosion phenomena, and identification of commonalities across the studied components as well as analysis of the environmental influence. The systematic analysis included computed microtomography (CT) of the joints that revealed distributed defects across all brazing interfaces. Some defects appeared to result from areas not wetted by the filler during the brazing operation, displaying round shapes, while others exhibited irregular contours and radial alignment, indicative of a network or interconnection. The subsequent dry cutting performed facilitated access to the conduct's inner surface and the brazed joints for further inspection through light and electron microscopy (SEM) and chemical analysis via Energy Dispersive X-ray spectroscopy (EDS). Brazing analysis away from affected areas identified the expected phases for a Sil-Fos alloy. In contrast, the affected locations displayed micrometric cavities propagating into the material, along with selective corrosion of the bulk Cu initiated at the conductor-braze interface. Corrosion product analysis highlighted the consistent presence of sulfur (up to 6 % in weight), whose origin and role in the corrosion initiation and extension is being further investigated. The importance of this study is paramount as it plays a crucial role in comprehending the underlying factors contributing to recently identified water leaks and evaluating the extent of the issue. Its primary objective is to provide essential insights for the repair of impacted brazed joints when accessibility permits. Moreover, the study seeks to contribute to the improvement of design and manufacturing practices for future components, ultimately enhancing the overall reliability and performance of magnet systems within CERN accelerator facilities.

Keywords: accelerator facilities, brazed copper conducts, demineralized water, magnets

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Meri Khakhutaishvili, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Cultivation of blueberry in Georgia started in 21st century. There are more than 20 species of blueberry cultivated in this region from all other the world. The species are mostly planted on acidic soil, previously occupied by tea plantations. Many of the plantations have pretty good yield. It is known that changing the location of a plant to a new soil or climate effects chemical compositions of the plant. However, even though these plants are brought from other countries, no research has been conducted to fully examine the blueberry fruit cultivated in Georgia. Shota Rustaveli National Science Foundation Grant FR/335/10-160/14, gave us an opportunity to continue our previous works and conduct research on several berries, among them of course the chemical composition of stored Blueberry. We were able to conduct the first study that included examining qualitative and quantitative features of bioactive compounds in Georgian Blueberry. This experiments were held in the ‘West Georgia Regional Chromatography center’ (Grant AP/96/13) of our university, that is equipped with modern equipment like HPLC UV-Vis, RI-detector, HPLC-conductivity detector, UPLC-MS-detector. Biochemical analysis was conducted using different physico-chemical and instrumental methods. Separation-identification and quantitative analysis were conducted using UPLC-MS (Waters Acquity QDa detector), HPLC (Waters Brceze 1525, UV-Vis 2489 detectors), pH-meters (Mettler Toledo). Refractrometer -Misco , Spectrometer –Cuvette Changer (Mettler Toledo UV5A), C18 Cartridge Solid Phase Extraction (SPE) Waters Sep-Pak C18 (500 mg), Chemicals – stability radical- 2,2-Diphenil-1-picrilhydrazyl (Aldrich-germany), Acetonitrile, Methanol, Acetic Acid (Merck-Germany), AlCl3, Folin Ciocalteu reagent (preparation), Standarts –Callic acid, Quercetin. Carbohydrate HPLC-RI analysis used systems acetonitrile-water (80-20). UPLC-MS analysis used systems- solvent A- Water +1 % acetic acid და solvent -B Methanol +1% acetic acid). It was concluded that the amount of sugars was in range of 5-9 %, mostly glucose and fructose. Also, the amount of organic acids was 0.2-1.2% most of which was malic and citric acid. Anthocians were also present in the sample 200-550mg/100g. We were able to identify up to 15 different compounds, most of which were products of delphinidine and cyanide. All species have high antioxidant level(DPPH). By rapidly freezing the sample and then keeping it in specific conditions allowed us to keep the sample for 12 months.

Keywords: antioxidants, bioactive, blueberry, storage

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Authors: Niharika Kaushal, Minni Singh

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Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: Nazish Badar

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In early 2009, Pandemic type A (H1N1) Influenza virus emerged globally. Since then, it has continued circulation causing considerable morbidity and mortality. The purpose of this study was to evaluate the evolutionary changes in Influenza A (H1N1) pdm09 viruses from 2009-15 and their relevance with the current vaccine viruses. Methods: Respiratory specimens were collected with influenza-like illness and Severe Acute Respiratory Illness. Samples were processed according to CDC protocol. Sequencing and phylogenetic analysis of Haemagglutinin (HA) and neuraminidase (NA) genes was carried out comparing representative isolates from Pakistan viruses. Results: Between Jan2009 - Feb 2016, 1870 (13.2%) samples were positive for influenza A out of 14086. During the pandemic period (2009–10), Influenza A/ H1N1pdm 09 was the dominant strain with 366 (45%) of total influenza positives. In the post-pandemic period (2011–2016), a total of 1066 (59.6%) cases were positive Influenza A/ H1N1pdm 09 with co-circulation of different Influenza A subtypes. Overall, the Pakistan A(H1N1) pdm09 viruses grouped in two genetic clades. Influenza A(H1N1)pdm09 viruses only ascribed to Clade 7 during the pandemic period whereas viruses belong to clade 7 (2011) and clade 6B (2015) during the post-pandemic years. Amino acid analysis of the HA gene revealed mutations at positions S220T, I338V and P100S specially associated with outbreaks in all the analyzed strains. Sequence analyses of post-pandemic A(H1N1)pdm09 viruses showed additional substitutions at antigenic sites; S179N,K180Q (SA), D185N, D239G (CA), S202A (SB) and at receptor binding sites; A13T, S200P when compared with pandemic period. Substitution at Genetic markers; A273T (69%), S200P/T (15%) and D239G (7.6%) associated with severity and E391K (69%) associated with virulence was identified in viruses isolated during 2015. Analysis of NA gene revealed outbreak markers; V106I (23%) among pandemic and N248D (100%) during post-pandemic Pakistan viruses. Additional N-Glycosylation site; HA S179N (23%), NA I23T(7.6%) and N44S (77%) in place of N386K(77%) were only found in post-pandemic viruses. All isolates showed histidine (H) at position 275 in NA indicating sensitivity to neuraminidase inhibitors. Conclusion: This study shows that the Influenza A(H1N1)pdm09 viruses from Pakistan clustered into two genetic clades, with co-circulation of some variants. Certain key substitutions in the receptor binding site and few changes indicative of virulence were also detected in post-pandemic strains. Therefore, it is imperative to continue monitoring of the viruses for early identification of potential variants of high virulence or emergence of drug-resistant variants.

Keywords: Influenza A (H1N1) pdm09, evolutionary analysis, post pandemic period, Pakistan

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Authors: Orit Baruth, Anat Cohen

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Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

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Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

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Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in the control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, and the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

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Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

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Authors: Kailash Chandra, Devanshu Gupta

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The Himalayan Mountains of India fall under two biogeographic zones Trans Himalaya (TH) and Himalaya and seven biotic provinces (TH-Ladakh Mountains, TH-Tibetan Plateau, TH-Sikkim, North-West Himalaya, West Himalaya, Central Himalaya, and East Himalaya). Because of the extreme environment and altitudinal variations, unique physiography, varied ecological conditions, and different vegetations, the Himalaya exhibit a rich assemblage of life, both flora, and fauna, further subjected to the impacts of climate change. To the authors’ best knowledge, there is no comprehensive account except for sporadic faunal investigations, to assess or interpret the insect diversity and their biogeographic distribution in Indian Himalaya (IH), one of the biodiversity hotspots. Therefore, in this paper, a compelling review of the extensive knowledge of insect diversity of IH is presented for the first time to the best of our knowledge. The inventory of the known insect species of IH was compiled from the exploration cum faunal-study data ready with the zoological survey of India, Kolkata as well as from the information published in the scientific literature till date. The species were listed with their valid names with their distribution in seven biotic provinces of IH. The insect fauna of IH represents about 38% of the identified insect diversity of India. The interpretation of data provided significant information in detecting possible gap areas in the taxonomic representation of different insect orders. Archaeognatha, Zygentoma, Ephemeroptera, Phasmida, Embioptera, Psocoptera, Phthiraptera, Strepsiptera, Megaloptera, Raphidioptera, Siphonaptera, and Mecoptera need revisions, and it is required to collect more samples from remote areas of the region. Scope for finding new taxa even in the most diverse orders, Coleoptera, Lepidoptera, Hymenoptera, Diptera, and Hemiptera cannot be overlooked. Exploration of cold deserts of Trans Himalaya and East Himalaya (Arunachal Pradesh) may result in a good number of new species from these regions. The most notable data was that many of the species recorded from Himalaya are still known from their type localities only, so there is an urgency to revisit and resurvey those collection localities for the evaluation of the status of those species. It is also required to assess and monitor the impact of climate change on the diversity of insects inhabiting in the fragile Himalayan ecosystem. DNA barcoding especially pests and biological control agents to solve the problems of identification in species complexes is also the need of the hour. In a nutshell, it can be concluded that the inventory of insects of this region is extensive but is far from final as every year hundreds of new species are described.

Keywords: catalog, climate change, diversity, DNA barcoding

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Diana Cunha, Catarina Coelho, Ana Paula Relvas, Elisabeth Kastenholz

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Context: Tourist experiences have a recognized impact on the well-being of individuals. However, studies on the specific benefits of tourist experiences for families are scattered across different disciplines. This study aims to systematically review the literature to synthesize the evidence on the benefits of tourist experiences for families. Research Aim: The main objective is to systematize the evidence in the literature regarding the benefits of tourist experiences for families. Methodology: A systematic literature review was conducted using Nvivo, analyzing 33 scientific studies obtained from various databases. The search terms used were "family"/ "couple" and "tourist experience". The studies included quantitative, qualitative, mixed methods, and literature reviews. All works prior to the year 2000 were excluded, and the search was restricted to full text. A language filter was also used, considering articles in Portuguese, English, and Spanish. For NVivo analysis, information was coded based on both deductive and inductive perspectives. To minimize the subjectivity of the selection and coding process, two of the authors discussed the process and agreed on criteria that would make the coding more objective. Once the coding process in NVivo was completed, the data relating to the identification/characterization of the works were exported to the Statistical Package for the Social Sciences (SPPS), to characterize the sample. Findings: The results highlight that tourist experiences have several benefits for family systems, including the strengthening of family and marital bonds, the creation of family memories, and overall well-being and life satisfaction. These benefits contribute to both immediate relationship quality improvement and long-term family identity construction and transgenerational transmission. Theoretical Importance: This study emphasizes the systemic nature of the effects and relationships within family systems. It also shows that no harm was reported within these experiences, with only some challenges related to positive outcomes. Data Collection and Analysis Procedures: The study collected data from 33 scientific studies published predominantly after 2013. The data were analyzed using Nvivo, employing a systematic review approach. Question Addressed: The study addresses the question of the benefits of tourist experiences for families and how these experiences contribute to family functioning and individual well-being. Conclusion: Tourist experiences provide opportunities for families to enhance their interpersonal relationships and create lasting memories. The findings suggest that formal interventions based on evidence could further enhance the potential benefits of these experiences and be a valuable preventive tool in therapeutic interventions.

Keywords: family systems, individual and family well-being, marital satisfaction, tourist experiences

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Authors: G. V. Manzane, S. J. Modise

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Uterine fibroids, also known as leiomyomas or myomas, are non-cancerous growths that develop in the muscular wall of the uterus during the reproductive years. The cause of uterine fibroids includes hormonal, genetic, growth factors, and extracellular matrix factors. Common symptoms of uterine fibroids include heavy and prolonged menstrual bleeding which can lead to a high risk of anemia, lower abdominal pains, pelvic pressure, infertility, and pregnancy loss. The growth of this tumor is a concern because of its negative impact on women’s health and the increase in their economic burden. Traditional medicinal plants have long been used in Africa for their potential therapeutic effects against various ailments. In this study, we aimed to identify and characterize bioactive compounds from selected African medicinal plants with potential anti-fibrotic properties using Fourier-transform infrared spectroscopy (FTIR) and gas chromatography-mass spectrometry (GCMS) analysis. Two medicinal plant species known for their traditional use in fibrosis-related conditions were selected for investigation. Aqueous extracts were prepared from the plant materials, and FTIR analysis was conducted to determine the functional groups present in the extracts. GCMS analysis was performed to identify the chemical constituents of the extracts. The FTIR analysis revealed the presence of various functional groups, such as phenols, flavonoids, terpenoids, and alkaloids, known for their potential therapeutic activities. These functional groups are associated with antioxidant, anti-inflammatory, and anti-fibrotic properties. The GCMS analysis identified several bioactive compounds, including flavonoids, alkaloids, terpenoids, and phenolic compounds, which are known for their pharmacological activities. The discovery of bioactive compounds in African medicinal plants that exhibit anti-fibrotic effects, opens up promising avenues for further research and development of potential treatments for fibrosis. This suggests the potential of these plants as a valuable source of novel therapeutic agents for treating fibrosis-related conditions. In conclusion, our study identified and characterized bioactive compounds from selected African medicinal plants using FTIR and GCMS analysis. The presence of compounds with known antifibrotic properties suggests that these plants hold promise as a potential source of natural products for the development of novel anti-fibrotic therapies.

Keywords: uterine fibroids, african medicinal plants, bioactive compounds, identify and characterized

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Authors: I. Berger, N. Machour, F. Portet-Koltalo

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Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic pollutants produced in majority by incomplete combustion processes in industrialized and urbanized areas. After being emitted in atmosphere, these persistent contaminants are deposited to soils or sediments. Even if persistent, some can be partially degraded (photodegradation, biodegradation, chemical oxidation) and they lead to oxygenated metabolites (oxy-PAHs) which can be more toxic than their parent PAH. Oxy-PAHs are less measured than PAHs in sediments and this study aims to compare different analytical tools in order to extract and quantify a mixture of four hydroxylated PAHs (OH-PAHs) and four carbonyl PAHs (quinones) in sediments. Methodologies: Two analytical systems – HPLC with on-line UV and fluorescence detectors (HPLC-UV-FLD) and GC coupled to a mass spectrometer (GC-MS) – were compared to separate and quantify oxy-PAHs. Microwave assisted extraction (MAE) was optimized to extract oxy-PAHs from sediments. Results: First OH-PAHs and quinones were analyzed in HPLC with on-line UV and fluorimetric detectors. OH-PAHs were detected with the sensitive FLD, but the non-fluorescent quinones were detected with UV. The limits of detection (LOD)s obtained were in the range (2-3)×10-4 mg/L for OH-PAHs and (2-3)×10-3 mg/L for quinones. Second, even if GC-MS is not well adapted to the analysis of the thermodegradable OH-PAHs and quinones without any derivatization step, it was used because of the advantages of the detector in terms of identification and of GC in terms of efficiency. Without derivatization, only two of the four quinones were detected in the range 1-10 mg/L (LODs=0.3-1.2 mg/L) and LODs were neither very satisfying for the four OH-PAHs (0.18-0.6 mg/L). So two derivatization processes were optimized, comparing to literature: one for silylation of OH-PAHs, one for acetylation of quinones. Silylation using BSTFA/TCMS 99/1 was enhanced using a mixture of catalyst solvents (pyridine/ethyle acetate) and finding the appropriate reaction duration (5-60 minutes). Acetylation was optimized at different steps of the process, including the initial volume of compounds to derivatize, the added amounts of Zn (0.1-0.25 g), the nature of the derivatization product (acetic anhydride, heptafluorobutyric acid…) and the liquid/liquid extraction at the end of the process. After derivatization, LODs were decreased by a factor 3 for OH-PAHs and by a factor 4 for quinones, all the quinones being now detected. Thereafter, quinones and OH-PAHs were extracted from spiked sediments using microwave assisted extraction (MAE) followed by GC-MS analysis. Several mixtures of solvents of different volumes (10-25 mL) and using different extraction temperatures (80-120°C) were tested to obtain the best recovery yields. Satisfactory recoveries could be obtained for quinones (70-96%) and for OH-PAHs (70-104%). Temperature was a critical factor which had to be controlled to avoid oxy-PAHs degradation during the MAE extraction process. Conclusion: Even if MAE-GC-MS was satisfactory to analyze these oxy-PAHs, MAE optimization has to be carried on to obtain a most appropriate extraction solvent mixture, allowing a direct injection in the HPLC-UV-FLD system, which is more sensitive than GC-MS and does not necessitate a previous long derivatization step.

Keywords: derivatizations for GC-MS, microwave assisted extraction, on-line HPLC-UV-FLD, oxygenated PAHs, polluted sediments

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Authors: Sinem Bulkan

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This study introduces the construct of psychopathic manager behaviour and aims for the development of psychopathic manager behaviour (Psycho-Man B) measure. The study also aims for the understanding of the relationship between psychopathic manager behaviour and workplace deviance while investigating the mediating role of a revenge motive and the moderating roles of the core self-evaluations and the attitude importance. Data were collected from 519 employees from a wide variety of jobs and industries who currently work for or previously worked for a manager in a collectivist culture, Turkey. Psycho-Man B Measure was developed resulting in five dimensions as opposed to the proposed ten dimensions. Simple linear and hierarchical regression analyses were conducted to test the hypotheses. The results of simple linear regression analyses showed that psychopathic manager behaviour was positively significantly related to supervisor-directed and organisation-directed deviance. Revenge motive towards the manager partially mediated the relationship between psychopathic manager behaviour and supervisor-directed deviance. Similarly, revenge motive towards the organisation partially mediated the relationship between psychopathic manager behaviour and organisation-directed deviance. Furthermore, no support was found for the expected moderating role of core self-evaluations in the revenge motive towards the manager-supervisor-directed deviance and revenge motive towards the organisation-organisation-directed deviance relationships. Attitude importance moderated the relationship between revenge motive towards the manager and supervisor-directed deviance; revenge motive towards the organisation and organisation-directed deviance. Moderated-mediation hypotheses were not supported for core self-evaluations but were supported for the attitude importance. Additional analyses for sub-dimensions were conducted to further examine the hypotheses. Demographic variables were examined through independent samples t-tests, and one way ANOVA. Finally, findings are discussed; limitations, suggestions and implications are presented. The major contribution of this study is that ‘psychopathic manager behaviour’ construct was introduced to the literature and a scale for the reliable identification of psychopathic manager behaviour was developed in to evaluate managers’ level of sub-clinical psychopathy in the workforce. The study introduced that employees engage in different forms of supervisor-directed deviance and organisation-directed deviance depending on the level of the emotions and personal goals. Supervisor-directed deviant behaviours and organisation-directed deviant behaviours became distinct in a way as impulsive and premeditated, active or passive, direct and indirect actions. Accordingly, it is important for organisations to notice that employees’ level of affective state and attitude importance for psychopathic manager behaviours predetermine the certain type of employee deviant behaviours.

Keywords: attitude importance, core self evaluations, psychopathic manager behaviour, revenge motive, workplace deviance

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Authors: Jiangbo Li, Wenqian Huang

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Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

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Authors: Othman E. Othman, Amira M. Nowier, Medhat El-Denary

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Camels play an important socio-economic role within the pastoral and agricultural system in the dry and semidry zones of Asia and Africa. Camels are economically important animals in Egypt where they are dual purpose animals (meat and milk). The analysis of chemical composition of camel milk showed that the total protein contents ranged from 2.4% to 5.3% and it is divided into casein and whey proteins. The casein fraction constitutes 52% to 89% of total camel milk protein and it divided into 4 fractions namely αs1, αs2, β and κ-caseins which are encoded by four tightly genes. In spite of the important role of casein genes and the effects of their genetic polymorphisms on quantitative traits and technological properties of milk, the studies for the detection of genetic polymorphism of camel milk genes are still limited. Due to this fact, this work focused - using PCR-RFP and sequencing analysis - on the identification of genetic polymorphisms and SNPs of two casein genes in Maghrabi camel breed which is a dual purpose camel breed in Egypt. The amplified fragments at 488-bp of the camel κ-CN gene were digested with AluI endonuclease. The results showed the appearance of three different genotypes in the tested animals; CC with three digested fragments at 203-, 127- and 120-bp, TT with three digested fragments at 203-, 158- and 127-bp and CT with four digested fragments at 203-, 158-, 127- and 120-bp. The frequencies of three detected genotypes were 11.0% for CC, 48.0% for TT and 41.0% for CT genotypes. The sequencing analysis of the two different alleles declared the presence of a single nucleotide polymorphism (C→T) at position 121 in the amplified fragments which is responsible for the destruction of a restriction site (AG/CT) in allele T and resulted in the presence of two different alleles C and T in tested animals. The nucleotide sequences of κ-CN alleles C and T were submitted to GenBank with the accession numbers; KU055605 and KU055606, respectively. The primers used in this study amplified 942-bp fragments spanning from exon 4 to exon 6 of camel αS1-Casein gene. The amplified fragments were digested with two different restriction enzymes; SmlI and AluI. The results of SmlI digestion did not show any restriction site whereas the digestion with AluI endonuclease revealed the presence of two restriction sites AG^CT at positions 68^69 and 631^632 yielding the presence of three digested fragments with sizes 68-, 563- and 293-bp.The nucleotide sequences of this fragment from camel αS1-Casein gene were submitted to GenBank with the accession number KU145820. In conclusion, the genetic characterization of quantitative traits genes which are associated with the production traits like milk yield and composition is considered an important step towards the genetic improvement of livestock species through the selection of superior animals depending on the favorable alleles and genotypes; marker assisted selection (MAS).

Keywords: genetic polymorphism, SNP polymorphism, Maghrabi camels, κ-Casein gene, αS1-Casein gene

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Authors: Patcharaporn Sakulpong, Wiriya Phokhwang

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Background: Banpunrug (Love Sharing House) established in 2013 provides a community-based palliative care for patients with cancer from 7 provinces in southern Thailand. These patients come to receive outpatient chemotherapy and radiotherapy at Suratthani Cancer Hospital. They are poor and uneducated; they need an accommodation during their 30-45 day course of therapy. Methods: A community-participatory action research (PAR) was employed to establish a model of palliative care for patients with cancer. The participants included health care providers, community, and patients and families. The PAR process includes problem identification and need assessment, community and team establishment, field survey, organization founding, model of care planning, action and inquiry (PDCA), outcome evaluation, and model distribution. Results: The model of care at Banpunrug involves the concepts of HHHS model, in that Banpunrug is a Home for patients; patients live in a house comfortable like in a Hotel resource; the patients are given care and living facilities similarly to those in a Hospital; the house is a School for patients to learn how to take care themselves, how to live well with cancer, and most importantly how to prepare themselves for a good death. The house is also a humanized care school for health care providers. Banpunrug’s philosophy of care is based on friendship therapy, social and spiritual support, community partnership, patient-family centeredness, Live & Love sharing house, and holistic and humanized care. With this philosophy, the house is managed as a home of the patients and everyone involved; everything is costless for all eligible patients and their family members; all facilities and living expense are donated from benevolent people, friends, and community. Everyone, including patients and family, has a sense of belonging to the house and there is no authority between health care providers and the patients in the house. The house is situated in a temple and a community and supported by many local nonprofit organizations and healthcare facilities such as a health promotion hospital at sub-disctrict level and Suratthani Cancer Hospital. Village health volunteers and multi-professional health care volunteers have contributed not only appropriate care, but also knowledge and experience to develop a distinguishing HHHS community-based palliative care model for patients with cancer. Since its opening the house has been a home for more than 400 patients and 300 family members. It is also a model for many national and international healthcare organizations and providers, who come to visit and learn about palliative care in and by community. Conclusions: The success of this palliative care model comes from community involvement, multi-professional volunteers and distributions, and concepts of HHHS model. Banpunrug promotes a consistent care across the cancer trajectory independent of prognosis in order to strengthen a full integration of palliative

Keywords: community-based palliative care, model, participatory action research, patients with cancer

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Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

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Authors: Revathi S. Rajan, Pratibha Malik, Nupur Garg, Smitha Avula, Kamini A. Rao

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This study aimed to analyse the pregnancy outcomes in patients with TPO positivity after appropriate L-Thyroxin supplementation with close surveillance. All pregnant women attending the antenatal clinic at Milann-The Fertility Center, Bangalore, India- from Aug 2013 to Oct 2014 whose booking TSH was more than 2.5 mIU/L were included along with those pregnant women with prior hypothyroidism who were TPO positive. Those with TPO positive status were vigorously managed with appropriate thyroxin supplementation and the doses were readjusted every 3 to 4 weeks until delivery. Women with recurrent pregnancy loss were also tested for TPO positivity and if tested positive, were monitored serially with TSH and fT4 levels every 3 to 4 weeks and appropriately supplemented with thyroxin when the levels fluctuated. The testing was done after an informed consent in all these women. The statistical software namely SAS 9.2, SPSS 15.0, Stata 10.1, MedCalc 9.0.1, Systat 12.0 and R environment ver.2.11.1 were used for the analysis of the data. 460 pregnant women were screened for thyroid dysfunction at booking of which 52% were hypothyroid. Majority of them (31.08%) were subclinically hypothyroid and the remaining were overt. 25% of the total no. of patients screened were TPO positive. The various pregnancy complications that were observed in the TPO positive women were gestational glucose intolerance [60%], threatened abortion [21%], midtrimester abortion [4.3%], premature rupture of membranes [4.3%], cervical funneling [4.3%] and fetal growth restriction [3.5%]. 95.6% of the patients who followed up till the end delivered beyond 30 weeks. 42.6% of these patients had previous history of recurrent abortions or adverse obstetric outcome and 21.7% of the delivered babies required NICU admission. Obstetric outcomes in our study in terms of midtrimester abortions, placental abruption, and preterm delivery improved for the better after close monitoring of the thyroid hormone [TSH and fT4] levels every 3 to 4 weeks with appropriate dose adjustment throughout pregnancy. Euthyroid women with TPO positive status enrolled in the study incidentally were those with recurrent abortions/infertility and required thyroxin supplements due to elevated Thyroid hormone (TSH, fT4) levels during the course of their pregnancy. Significant associations were found with age>30 years and Hyperhomocysteinemia [p=0.017], recurrent pregnancy loss or previous adverse obstetric outcomes [p=0.067] and APLA [p=0.029]. TPO antibody levels >600 I U/ml were significantly associated with development of gestational hypertension [p=0.041] and fetal growth restriction [p=0.082]. Euthyroid women with TPO positivity were also screened periodically to counter fluctuations of the thyroid hormone levels with appropriate thyroxin supplementation. Thus, early identification along with aggressive management of thyroid dysfunction and stratification of these patients based on their TPO status with appropriate thyroxin supplementation beginning in the first trimester will aid risk modulation and also help avert complications.

Keywords: TPO antibody, subclinical hypothyroidism, anti nuclear antibody, thyroxin

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Piotr Wisniewski, Sławomir Dykas

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Condensation has a negative impact on turbomachinery efficiency in many energy processes.In technical applications, it is often impossible to dry the working fluid at the nozzle inlet. One of the most popular working fluid is atmospheric air that always contains water in form of steam, liquid, or ice crystals. Moreover, it always contains some amount of suspended particles which influence the phase change process. It is known that the phenomena of evaporation or condensation are connected with release or absorption of latent heat, what influence the fluid physical properties and might affect the machinery efficiency therefore, the phase transition has to be taken under account. This researchpresents an attempt to evaluate the impact of solid and liquid particles suspended in the air on the expansion of moist air in a low expansion rate, i.e., with expansion rate, P≈1000s⁻¹. The numerical study supported by analytical and experimental research is presented in this work. The experimental study was carried out using an in-house experimental test rig, where nozzle was examined for different inlet air relative humidity values included in the range of 25 to 51%. The nozzle was tested for a supersonic flow as well as for flow with shock waves induced by elevated back pressure. The Schlieren photography technique and measurement of static pressure on the nozzle wall were used for qualitative identification of both condensation and shock waves. A numerical model validated against experimental data available in the literature was used for analysis of occurring flow phenomena. The analysis of the suspended particles number, diameter, and character (solid or liquid) revealed their connection with heterogeneous condensation importance. If the expansion of fluid without suspended particlesis considered, the condensation triggers so called condensation wave that appears downstream the nozzle throat. If the solid particles are considered, with increasing number of them, the condensation triggers upwind the nozzle throat, decreasing the condensation wave strength. Due to the release of latent heat during condensation, the fluid temperature and pressure increase, leading to the shift of normal shock upstream the flow. Owing relatively large diameters of the droplets created during heterogeneous condensation, they evaporate partially on the shock and continues to evaporate downstream the nozzle. If the liquid water particles are considered, due to their larger radius, their do not affect the expanding flow significantly, however might be in major importance while considering the compression phenomena as they will tend to evaporate on the shock wave. This research proves the need of further study of phase change phenomena in supersonic flow especially considering the interaction of droplets with the aerodynamic waves in the flow.

Keywords: aerodynamics, computational fluid dynamics, condensation, moist air, multi-phase flows

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Authors: Susan C. Graham

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Islands have a long established allure for travellers the world over. From earliest accounts of human history, travellers were drawn by the sense of islandness embodied by these destinations. The concept of islandness describes the essence of what makes islands unique relative to non-islands and extends beyond geographic interpretations by attempting to capture the specific sense of self-exhibited by islanders in relation to their connection to place. The themes most strongly associated with islandness include a) a strong connection to water as both the life blood and a physical barrier, b) a unique culture and robust arts community that is deeply linked to both the island and islanders, c) an appreciation of and for nature, d) a rich sense of history and tradition connected to the place, e) a sense of community and belonging that arose through shared triumphs and struggles, and f) a profound awareness of independence, separateness, and uniqueness derived from both physical and social experience. The island brand, like all brands, is a marketing tactic designed to succinctly express a specific value proposition in simplistic ways which might include a brand symbol, logo, slogan, or representation meant to distinguish one brand from another. If a value proposition is the identification of attributes that separate one brand from another by highlighting the brand’s uniqueness, then presumably island brands may, at least in part, emphasize islandness as part of the destination brand. Yet it may in naïve to expect all islands to brand themselves using similar themes when islands can differ so substantially in terms of population, geography, political climate, economy, culture, and history. Of particular interest is the increased focus on tourism among 'cold-water' islands. This paper will examine the incorporation of themes related to islandness in tourism branding among cold-water, warm-water, and temperate-water islands. The tourism logos of 83 islands were collected and assessed for the use of themes related to islandness, namely water, arts and culture, nature, history and tradition, community and belongingness, and independence, separateness, and uniqueness. The ratings for each theme related to islandness for each of the 83 island destinations were then analyzed to identify if differences exist between cold-water, warm-water, and temperate-water islands. A general consensus of what constitutes 'cold-water' destinations is lacking, therefore a water temperature of 15C was adopted using the guidelines from the National Center for Cold Water Safety. Among these 83 islands, the average high and average low water temperatures of 196 specific locations, including the capital, northern, and southern most points of each island, was recorded to determine if the location was a cold-water (average high and low below 15C), warm-water (average high and low above 15C), or temperate-water (average high above 15C and low below 15C) location.

Keywords: branding, cold-water, islands, tourism

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Authors: Anna Fowler

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When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

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Authors: Leila Fozouni, Anahita Mazandarani

Abstract:

Background: Maternal infections are the most common cause of infections in infants, and the level of infection and its severity highly depends on the degree of colonization of the bacteria in the mother; so, the occurrence of aggressive diseases is not unpredictable in mothers with very high colonization. Group B Streptococcus is part of the normal flora of the gastrointestinal and genital tracts in women and is the leading cause of septicemia and meningitis in newborns. Today Zinc oxide nanoparticle is regarded as one of the most commonly used and safest nanoparticles for defeating Gram-positive and Gram-negative bacteria. This study aims to determine the antibacterial effects of Zinc oxide on the growth of drug-resistant group B Streptococcus strains isolated from pregnant women. Materials and Methods: This cross-sectional study was conducted on 150 pregnant women of 28–37 weeks admitted to seven hospitals and maternity wards in Golestan province, northeast of Iran. For bacterial identification, rectovaginal swabs were firstly inoculated to the Todd-Hewitt Broth and cultured in blood agar (containing 5% sheep blood). Then microbiologic and PCR methods were performed to detect group B Streptococci. Disk diffusion and broth microdilution tests were used to determine the bacterial susceptibility to antibiotics according to CLSI M100(2021) criteria. The antibacterial properties of Zinc oxide nanoparticles were evaluated using the agar well-diffusion method. Results: The prevalence of group B Streptococcus was 18% in pregnant women. Out of twenty-seven positive cultures, 62.96% were higher than thirty years old. Ninety percent and 45% of isolates were resistant to clindamycin and erythromycin, respectively, and susceptibility to cefazolin was 71%. In addition, susceptibility to ampicillin and penicillin were 74% and 55%, respectively. The results showed that 82% of erythromycin-resistant, 92% clindamycin-resistant, and 78% of cefazolin-resistant isolates were eliminated by zinc oxide nanoparticles at a concentration of 100 mg/L of the nanoparticle. Furthermore, ZnONPs could inhibit all drug-resistant isolates at a concentration of 200 mg/mL (MIC90 ≥ 200). Conclusion: Since the drug resistance of group B streptococci against various antibiotics is increasing, determining and investigating the drug-resistance pattern of this bacterium to different antibiotics in order to prevent arbitrary consumption of antibiotics by pregnant women and ultimately prevent Infant mortality seems necessary. Generally, ZnONPs showed a high antimicrobial effect, and it was revealed that the bactericide effect increases upon the increase in the concentration of the nanoparticle.

Keywords: group B beta-hemolytic streptococcus, pregnant women, zinc oxide nanoparticles, drug resistance

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Authors: Ranjita Ghoshmoulick, Aswathi Madhavan, Subhavna Juneja, Prasenjit Sen, Jaydeep Bhattacharya

Abstract:

Type 2 diabetes mellitus (T2DM) is a very complex and multifactorial metabolic disease where the blood sugar level goes up. One of the major consequence of this elevated blood sugar is the formation of AGE (Advance Glycation Endproducts), from a series of chemical or biochemical reactions. AGE are detrimental because it leads to severe pathogenic complications. They are a group of structurally diverse chemical compounds formed from nonenzymatic reactions between the free amino groups (-NH2) of proteins and carbonyl groups (>C=O) of reducing sugars. The reaction is known as Maillard Reaction. It starts with the formation of reversible schiff’s base linkage which after sometime rearranges itself to form Amadori Product along with dicarbonyl compounds. Amadori products are very unstable hence rearrangement goes on until stable products are formed. During the course of the reaction a lot of chemically unknown intermediates and reactive byproducts are formed that can be termed as Early Glycation Products. And when the reaction completes, structurally stable chemical compounds are formed which is termed as Advanced Glycation Endproducts. Though all glycation products have not been characterized well, some fluorescence compounds e.g pentosidine, Malondialdehyde (MDA) or carboxymethyllysine (CML) etc as AGE and α-dicarbonyls or oxoaldehydes such as 3-deoxyglucosone (3-DG) etc as the intermediates have been identified. In this work Gold NanoParticle (GNP) was used as an optical indicator of glycation products. To achieve faster glycation kinetics and high AGE accumulation, fructose was used instead of glucose. Hemoglobin A0 (HbA0) was fructosylated by in-vitro method. AGE formation was measured fluorimetrically by recording emission at 450nm upon excitation at 350nm. Thereafter this fructosylated HbA0 was fractionated by column chromatography. Fractionation separated the proteinaceous substance from the AGEs. Presence of protein part in the fractions was confirmed by measuring the intrinsic protein fluorescence and Bradford reaction. GNPs were synthesized using the templates of chromatographically separated fractions of fructosylated HbA0. Each fractions gave rise to GNPs of varying color, indicating the presence of distinct set of glycation products differing structurally and chemically. Clear solution appeared due to settling down of particles in some vials. The reactive groups of the intermediates kept the GNP formation mechanism on and did not lead to a stable particle formation till Day 10. Whereas SPR of GNP showed monotonous colour for the fractions collected in case of non fructosylated HbA0. Our findings accentuate the use of GNPs as a simple colorimetric sensing platform for the identification of intermediates of glycation reaction which could be implicated in the prognosis of the associated health risk due to T2DM and others.

Keywords: advance glycation endproducts, glycation, gold nano particle, sensor

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Authors: Kevin Potoczny, Katsuichiro Goda

Abstract:

The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.

Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility

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