Search results for: signal processing for transmission carrier frequency offset

Authors: Hossam N. Alhawatmeh, Areen I. Albustanji

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Hemodialysis negatively affects physical and psychological health. Pain, poor sleep quality, and low self-esteem are highly prevalent among patients with end-stage renal disease (ESRD) who receive hemodialysis, significantly increasing mortality and morbidity of those patients. Mind-body interventions (MBI), such as mindfulness meditation, have been recently gaining popularity that improved pain, sleep quality, and self-esteem in different populations. However, to our best knowledge, its effects on these health problems in patients receiving hemodialysis have not been studied in Jordan. Thus, the purpose of the study was to examine the effect of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESR receiving hemodialysis in Jordan. An experimental repeated-measures, randomized, parallel control design was conducted on (n =60) end-stage renal disease patients undergoing hemodialysis between March and June 2023 in the dialysis center at a public hospital in Jordan. Participants were randomly assigned to the experimental (n =30) and control groups (n =30) using a simple random assignment method. The experimental group practiced mindfulness meditation for 30 minutes three times per week for five weeks during their hemodialysis treatments. The control group's patients continued to receive hemodialysis treatment as usual for five weeks during hemodialysis sessions. The study variables for both groups were measured at baseline (Time 0), two weeks after intervention (Time 1), and at the end of intervention (Time 3). The numerical rating scale (NRS), the Rosenberg Self-Esteem Scale (RSES-M), and the Pittsburgh Sleep Quality Index (PSQI) were used to measure pain, self-esteem, and sleep quality, respectively. SPSS version 25 was used to analyze the study data. The sample was described by frequency, mean, and standard deviation as an appropriate. The repeated measures analysis of variance (ANOVA) tests were run to test the study hypotheses. The results of repeated measures ANOVA (within-subject) revealed that mindfulness meditation significantly decrease pain by the end of the intervention in the experimental group. Additionally, mindfulness meditation improved sleep quality and self-esteem in the experimental group, and these improvements occurred significantly after two weeks of the intervention and at the end of the intervention. The results of repeated measures ANOVA (within and between-subject) revealed that the experimental group, compared to the control group, experienced lower levels of pain and higher levels of sleep quality and self-esteem over time. In conclusion, the results provided substantial evidence supporting the positive impacts of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESRD undergoing hemodialysis. These results highlight the potential of mindfulness meditation as an adjunctive therapy in the comprehensive care of this patient population. Incorporating mindfulness meditation into the treatment plan for patients receiving hemodialysis may contribute to improved well-being and overall quality of life.

Keywords: hemodialysis, pain, sleep quality, self-esteem, mindfulness

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Authors: Kichan Lee, Kwang-Ho Choi, Mi-Hye Hwang, Young Min Son, Bang-Hun Hyun, Byeong Yeal Jung

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Recently, worldwide food safety authorities have been strengthening food hygiene in order to curb foodborne illness outbreaks. The hygiene status of Korean slaughterhouses has been monitored annually by Animal and Plant Quarantine Agency and provincial governments through foodborne pathogens investigation using slaughtered pig and cattle meats. This study presented the prevalence of food-borne pathogens from 2014 to 2016 in Korean slaughterhouses. Sampling, microbiological examinations, and analysis of results were performed in accordance with ‘Processing Standards and Ingredient Specifications for Livestock Products’. In total, swab samples from 337 pig carcasses (100 samples in 2014, 135 samples in 2015, 102 samples in 2016) and 319 cattle carcasses (100 samples in 2014, 119 samples in 2015, 100 samples in 2016) from twenty slaughterhouses were examined for Listeria monocytogenes, Campylobacter jejuni, Campylobacter coli, Salmonella spp., Staphylococcus aureus, Clostridium perfringens, Yersinia enterocolitica, Escherichia coli O157:H7 and non-O157 enterohemorrhagic E. coli (EHEC, serotypes O26, O45, O103, O104, O111, O121, O128 and O145) as foodborne pathogens. The samples were analyzed using cultural and PCR-based methods. Foodborne pathogens were isolated in 78 (23.1%) out of 337 pig samples. In 2014, S. aureus (n=17) was predominant, followed by Y. enterocolitica (n=7), C. perfringens (n=2) and L. monocytogenes (n=2). In 2015, C. coli (n=14) was the most prevalent, followed by L. monocytogenes (n=4), S. aureus (n=3), and C. perfringens (n=2). In 2016, S. aureus (n=16) was the most prevalent, followed by C. coli (n=13), L. monocytogenes (n=2) and C. perfringens (n=1). In case of cattle carcasses, foodborne bacteria were detected in 41 (12.9%) out of 319 samples. In 2014, S. aureus (n=16) was the most prevalent, followed by Y. enterocolitica (n=3), C. perfringens (n=3) and L. monocytogenes (n=2). In 2015, L. monocytogenes was isolated from 4 samples, S. aureus from three, C. perfringens, Y. enterocolitica and Salmonella spp. from one, respectively. In 2016, L. monocytogenes (n=6) was the most prevalent, followed by C. perfringens (n=3) C. jejuni (n=1), respectively. It was found that 10 carcass samples (4 cattle and 6 pigs) were contaminated with two bacterial pathogen tested. Interestingly, foodborne pathogens were more detected from pig carcasses than cattle carcasses. Although S. aureus was predominantly detected in this study, other foodborne pathogens were also isolated in slaughtered meats. Results of this study alerted the risk of foodborne pathogen infection for humans from slaughtered meats. Therefore, the authors insisted that it was important to enhance hygiene level of slaughterhouses according to Hazard Analysis and Critical Control Point.

Keywords: carcass, cattle, foodborne, Korea, pathogen, pig

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Authors: Clarence Dissanayake, Anishka A. Hettiarachchi

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Landscape architecture needs to encompass a placemaking process carefully composing and manipulating landscape elements to address perceptual needs of humans, especially aesthetic, psychological and spiritual. The objective of this qualitative investigation is to inquire the impact of elements of rock and water combination on landscape perception and related feelings, emotions, and behavior. The past empirical studies have assessed the impact of landscape elements in isolation on user preference, yet the combined effect of elements have been less considered. This research was conducted with reference to the verity of qualities of water and rock through a visual landscape quality assessment focusing on landscape qualities derived from five visual concepts (coherence, historicity imageability, naturalness, and ephemera). 'Kaludiya Pokuna' archeological site in Anuradhapura was investigated with a sample of University students (n=19, male 14, female 5, age 20-25) using a five-point Likert scale via a perception based questionnaire and a visitor employed photographic survey (VEP). Two hypothetical questions were taken into investigation concerning biophilic (naturalness) and topophilic (historicity) aspects of humans to prefer a landscape with rock and water. The findings revealed that this combination encourages both biophilic and topophilic aspects, but in varying degrees. The identified hierarchy of visual concepts based on visitor’s preference signify coherence (93%), historicity (89%), imageability (79%), naturalness (75%) and ephemera (70%) respectively. It was further revealed that this combination creates a scenery more coherent dominating information processing aspect of humans to perceive a landscape over the biophilic and topophilic aspects. Different characteristics and secondary landscape effects generated by rock and water combination were found to affect in transforming a space into a place, full filling the aesthetic and spiritual aspects of the visitors. These findings enhance a means of making places for people, resource management and historical landscape conservation. Equalization of gender based participation, taking diverse cases and increasing the sample size with more analytical photographic analysis are recommended to enhance the quality of further research.

Keywords: landscape perception, visitor’s preference, rock and water combination, visual concepts

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Authors: Lena Lapidot, Amir Amnon, Rita Nosenko, Veitsman Ella, Cohen-Ezra Oranit, Davidov Yana, Segev Shlomo, Koren Omry, Safran Michal, Ben-Ari Ziv

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Introduction: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer related mortality worldwide. Liver Cirrhosis is the main predisposing risk factor for the development of HCC. The factor(s) influencing disease progression from Cirrhosis to HCC remain unknown. Gut microbiota has recently emerged as a major player in different liver diseases, however its association with HCC is still a mystery. Moreover, there might be an important association between the gut microbiota, nutrition, life style and the progression of Cirrhosis and HCC. The aim of our study was to characterize the gut microbial signature in association with life style and nutrition of patients with Cirrhosis, HCC-Cirrhosis and healthy controls. Design: Stool samples were collected from 95 individuals (30 patients with HCC, 38 patients with Cirrhosis and 27 age, gender and BMI-matched healthy volunteers). All participants answered lifestyle and Food Frequency Questionnaires. 16S rRNA sequencing of fecal DNA was performed (MiSeq Illumina). Results: There was a significant decrease in alpha diversity in patients with Cirrhosis (qvalue=0.033) and in patients with HCC-Cirrhosis (qvalue=0.032) compared to healthy controls. The microbiota of patients with HCC-cirrhosis compared to patients with Cirrhosis, was characterized by a significant overrepresentation of Clostridium (pvalue=0.024) and CF231 (pvalue=0.010) and lower expression of Alphaproteobacteria (pvalue=0.039) and Verrucomicrobia (pvalue=0.036) in several taxonomic levels: Verrucomicrobiae, Verrucomicrobiales, Verrucomicrobiaceae and the genus Akkermansia (pvalue=0.039). Furthermore, we performed an analysis of predicted metabolic pathways (Kegg level 2) that resulted in a significant decrease in the diversity of metabolic pathways in patients with HCC-Cirrhosis (qvalue=0.015) compared to controls, one of which was amino acid metabolism. Furthermore, investigating the life style and nutrition habits of patients with HCC-Cirrhosis, we found significant correlations between intake of artificial sweeteners and Verrucomicrobia (qvalue=0.12), High sugar intake and Synergistetes (qvalue=0.021) and High BMI and the pathogen Campylobacter (qvalue=0.066). Furthermore, overweight in patients with HCC-Cirrhosis modified bacterial diversity (qvalue=0.023) and composition (qvalue=0.033). Conclusions: To the best of the our knowledge, we present the first report of the gut microbial composition in patients with HCC-Cirrhosis, compared with Cirrhotic patients and healthy controls. We have demonstrated in our study that there are significant differences in the gut microbiome of patients with HCC-cirrhosis compared to Cirrhotic patients and healthy controls. Our findings are even more pronounced because the significantly increased bacteria Clostridium and CF231 in HCC-Cirrhosis weren't influenced by diet and lifestyle, implying this change is due to the development of HCC. Further studies are needed to confirm these findings and assess causality.

Keywords: Cirrhosis, Hepatocellular carcinoma, life style, liver disease, microbiome, nutrition

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: O. Ekrami, P. Claes, S. Van Dongen

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Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

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Authors: Natalia Lukasik, Ewa Wagner-Wysiecka

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Development of selective, fast-responsive, and economical sensors for diverse ions detection and determination is one of the most extensively studied areas due to its importance in the field of clinical, environmental and industrial analysis. Among chemical sensors, vast popularity has gained ionophore-based optical sensors, where the generated analytical signal is a consequence of the molecular recognition of ion by the ionophore. Change of color occurring during host-guest interactions allows for quantitative analysis and for 'naked-eye' detection without the need of using sophisticated equipment. An example of application of such sensors is colorimetric detection of iron(III) cations. Iron as one of the most significant trace elements plays roles in many biochemical processes. For these reasons, the development of reliable, fast, and selective methods of iron ions determination is highly demanded. Taking all mentioned above into account a chromogenic amide derivative of 3,4-dihydroxybenzoic acid was synthesized, and its ability to iron(III) recognition was tested. To the best of authors knowledge (according to chemical abstracts) the obtained ligand has not been described in the literature so far. The catechol moiety was introduced to the ligand structure in order to mimic the action of naturally occurring siderophores-iron(III)-selective receptors. The ligand–ion interactions were studied using spectroscopic methods: UV-Vis spectrophotometry and infrared spectroscopy. The spectrophotometric measurements revealed that the amide exhibits affinity to iron(III) in dimethyl sulfoxide and fully aqueous solution, what is manifested by the change of color from yellow to green. Incorporation of the tested amide into a polymeric matrix (cellulose triacetate) ensured effective recognition of iron(III) at pH 3 with the detection limit 1.58×10⁻⁵ M. For the obtained sensor material parameters like linear response range, response time, selectivity, and possibility of regeneration were determined. In order to evaluate the effect of the size of the sensing material on iron(III) detection nanospheres (in the form of nanoemulsion) containing the tested amide were also prepared. According to DLS (dynamic light scattering) measurements, the size of the nanospheres is 308.02 ± 0.67 nm. Work parameters of the nanospheres were determined and compared with cellulose triacetate-based material. Additionally, for fast, qualitative experiments the test strips were prepared by adsorption of the amide solution on a glass microfiber material. Visual limit of detection of iron(III) at pH 3 by the test strips was estimated at the level 10⁻⁴ M. In conclusion, reported here amide derived from 3,4- dihydroxybenzoic acid proved to be an effective candidate for optical sensing of iron(III) in fully aqueous solutions. N. L. kindly acknowledges financial support from National Science Centre Poland the grant no. 2017/01/X/ST4/01680. Authors thank for financial support from Gdansk University of Technology grant no. 032406.

Keywords: ion-selective optode, iron(III) recognition, nanospheres, optical sensor

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Authors: Disha Bhanot, Vinish Kathuria

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This study focusses on the issue of distress sale in horticulture sector in India, which faces unique challenges, given the perishable nature of horticulture crops, seasonal production and paucity of post-harvest produce management links. Distress sale, from a farmer’s perspective may be defined as urgent sale of normal or distressed goods, at deeply discounted prices (way below the cost of production) and it is usually characterized by unfavorable conditions for the seller (farmer). The small and marginal farmers, often involved in subsistence farming, stand to lose substantially if they receive lower prices than expected prices (typically framed in relation to cost of production). Distress sale maximizes price uncertainty of produce leading to substantial income loss; and with increase in input costs of farming, the high variability in harvest price severely affects profit margin of farmers, thereby affecting their survival. The objective of this study is to model the occurrence of distress sale by tomato cultivators in the Indian state of Maharashtra, against the background of differential access to set of factors such as - capital, irrigation facilities, warehousing, storage and processing facilities, and institutional arrangements for procurement etc. Data is being collected using primary survey of over 200 farmers in key tomato growing areas of Maharashtra, asking information on the above factors in addition to seeking information on cost of cultivation, selling price, time gap between harvesting and selling, role of middleman in selling, besides other socio-economic variables. Farmers selling their produce far below the cost of production would indicate an occurrence of distress sale. Occurrence of distress sale would then be modelled as a function of farm, household and institutional characteristics. Heckman-two-stage model would be applied to find the probability/likelihood of a famer falling into distress sale as well as to ascertain how the extent of distress sale varies in presence/absence of various factors. Findings of the study would recommend suitable interventions and promotion of strategies that would help farmers better manage price uncertainties, avoid distress sale and increase profit margins, having direct implications on poverty.

Keywords: distress sale, horticulture, income loss, India, price uncertainity

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Authors: Ahuva Even-Zohar, Shoshi Werner

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Context: Sexuality is an important aspect of overall quality of life for individuals across different age groups and health conditions. Sexual interest and activity continue to be important and play a role in people's life as they age. Despite this, there is limited research on the sexual health of older adults. Research Aim: The study aims to examine the knowledge, attitudes, and sexual activity of older adults and to explore the relationship between sexual activity and quality of life among this population. Methodology: The study involved 203 Jewish participants from Israel, with an average age of 69.59. The participants completed questionnaires administered through an Internet panel. The questionnaires measured variables such as knowledge about and attitudes towards sexuality, sexual activity, quality of life, and socio-demographic information. Findings: The study found that a majority of the participants reported engaging in sexual activity, with most of them experiencing full sexual intercourse. Approximately half of the participants expressed high levels of satisfaction with their sexual activity. The results indicated that older adults demonstrated a moderate level of knowledge and permissive attitudes towards sexuality in later life. Moreover, higher levels of knowledge and permissive attitudes were associated with increased sexual activity. The frequency of sexual activity was identified as a predictor of quality of life, with a mediating effect on the relationship between attitudes towards older adults' sexuality and quality of life. Notably, men and older adults who were married or in a relationship reported higher frequencies of sexual activity compared to women and older adults without a partner. Furthermore, a majority of participants did not seek professional help or discuss their sexual concerns with a therapist. Theoretical Importance: This research contributes to our understanding of a topic that is often considered taboo - sexuality among older adults. It highlights that older adults maintain an interest in sexual activity, and that engaging in such activity contributes to their overall quality of life. Data Collection and Analysis Procedures: The data for this study were collected using structured questionnaires administered through an Internet panel. The questionnaires included closed-ended questions, allowing for quantitative data analysis. Descriptive statistics and regression analysis were performed to examine the relationships between the variables. Questions Addressed: This study aimed to address the following questions: What is the level of knowledge and attitudes towards sexuality among older adults? How prevalent is sexual activity among older adults and what factors are associated with it? How does sexual activity impact the quality of life of older adults? Do older adults seek professional help for their sexual concerns? Conclusion: The main conclusion drawn from this research is that sexuality is a crucial aspect of older adults' lives and significantly contributes to their quality of life. The study emphasizes the need for educational programs aimed at older adults and professionals, which promote the understanding and benefits of sexuality in later life. It also suggests that professionals should actively encourage older individuals to seek help and support when experiencing difficulties related to sexuality.

Keywords: men, older adults, quality of life, sexuality, women

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Authors: Moayyad Shawaqfah, Ibtehal Alqdah, Amjad Adaileh

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Coridoor area (400 km2) lies to the north – east of Amman (60 km). It lies between 285-305 E longitude and 165-185 N latitude (according to Palestine Grid). It been subjected to exploitation of groundwater from new eleven wells since the 1999 with a total discharge of 11 MCM in addition to the previous discharge rate from the well field 14.7 MCM. Consequently, the aquifer balance is disturbed and a major decline in water level. Therefore, suitable groundwater resources management is required to overcome the problems of over pumping and its effect on groundwater quality. Three–dimensional groundwater flow model Processing Modeflow for Windows Pro (PMWIN PRO, 2003) has been used in order to calculate the groundwater budget, aquifer characteristics, and to predict the aquifer response under different stresses for the next 20 years (2035). The model was calibrated for steady state conditions by trial and error calibration. The calibration was performed by matching observed and calculated initial heads for year 2001. Drawdown data for period 2001-2010 were used to calibrate transient model by matching calculated with observed one, after that, the transient model was validated by using the drawdown data for the period 2011-2014. The hydraulic conductivities of the Basalt- A7/B2 aquifer System are ranging between 1.0 and 8.0 m/day. The low conductivity value was found at the north-west and south-western parts of the study area, the high conductivity value was found at north-western corner of the study area and the average storage coefficient is about 0.025. The water balance for the Basalt and B2/A7 formation at steady state condition with a discrepancy of 0.003%. The major inflows come from Jebal Al Arab through the basalt and through the limestone aquifer (B2/A7 12.28 MCMY aquifer and from excess rainfall is about 0.68 MCM/a. While the major outflows from the Basalt-B2/A7 aquifer system are toward Azraq basin with about 5.03 MCMY and leakage to A1/6 aquitard with 7.89 MCMY. Four scenarios have been performed to predict aquifer system responses under different conditions. Scenario no.2 was found to be the best one which indicates that the reduction the abstraction rates by 50% of current withdrawal rate (25.08 MCMY) to 12.54 MCMY. The maximum drawdowns were decreased to reach about, 7.67 and 8.38m in the years 2025 and 2035 respectively.

Keywords: Amman/Zarqa Basin, Jordan, groundwater management, groundwater modeling, modflow

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Authors: Khalid Omari, Rene Chenier, Enrique Blondel, Ryan Ahola

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Northern Canadian coasts have vulnerable and very dynamic intertidal zones with very high tides occurring in several areas. The impact of climate change presents challenges not only for maintaining this biodiversity but also for navigation safety adaptation due to the high sediment mobility in these coastal areas. Thus, frequent mapping of shorelines and intertidal changes is of high importance. To help in quantifying the changes in these fragile ecosystems, remote sensing provides practical monitoring tools at local and regional scales. Traditional methods based on high-resolution optical sensors are often used to map intertidal areas by benefiting of the spectral response contrast of intertidal classes in visible, near and mid-infrared bands. Tidal areas are highly reflective in visible bands mainly because of the presence of fine sand deposits. However, getting a cloud-free optical data that coincide with low tides in intertidal zones in northern regions is very difficult. Alternatively, the all-weather capability and daylight-independence of the microwave remote sensing using synthetic aperture radar (SAR) can offer valuable geophysical parameters with a high frequency revisit over intertidal zones. Multi-polarization SAR parameters have been used successfully in mapping intertidal zones using incoherence target decomposition. Moreover, the crustal displacements caused by ocean tide loading may reach several centimeters that can be detected and quantified across differential interferometric synthetic aperture radar (DInSAR). Soil moisture change has a significant impact on both the coherence and the backscatter. For instance, increases in the backscatter intensity associated with low coherence is an indicator for abrupt surface changes. In this research, we present primary results obtained following our investigation of the potential of the fully polarimetric Radarsat-2 data for mapping an inter-tidal zone located on Tasiujaq on the south-west shore of Ungava Bay, Quebec. Using the repeat pass cycle of Radarsat-2, multiple seasonal fine quad (FQ14W) images are acquired over the site between 2016 and 2018. Only 8 images corresponding to low tide conditions are selected and used to build an interferometric stack of data. The observed displacements along the line of sight generated using HH and VV polarization are compared with the changes noticed using the Freeman Durden polarimetric decomposition and Touzi degree of polarization extrema. Results show the consistency of both approaches in their ability to monitor the changes in intertidal zones.

Keywords: SAR, degree of polarization, DInSAR, Freeman-Durden, polarimetry, Radarsat-2

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Authors: Mustafa Malki, Ewan R. Pearson

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Tools utilized by health care practitioners to flag potential adverse drug reactions secondary to drug-drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To our best knowledge, there have been limited published studies on the impact of genetic variation on drug-drug interactions. Therefore, our aim in this project is the discovery of previously unrecognized, clinically important drug-drug-gene interactions (DDGIs) within the list of most commonly used drug combinations in the UK. The UKBB database was utilized to identify the top most frequently prescribed drug combinations in the UK with at least one route of interaction (over than 200 combinations were identified). We have recognised 37 common and unique interacting genes considering all of our drug combinations. Out of around 600 potential genetic variants found in these 37 genes, 100 variants have met the selection criteria (common variant with minor allele frequency ≥ 5%, independence, and has passed HWE test). The association between these variants and the use of each of our top drug combinations has been tested with a case-control analysis under the log-additive model. As the data is cross-sectional, drug intolerance has been identified from the genotype distribution as presented by the lower percentage of patients carrying the risky allele and on the drug combination compared to those free of these risk factors and vice versa with drug tolerance. In GoDARTs database, the same list of common drug combinations identified by the UKBB was utilized here with the same list of candidate genetic variants but with the addition of 14 new SNPs so that we have a total of 114 variants which have met the selection criteria in GoDARTs. From the list of the top 200 drug combinations, we have selected 28 combinations where the two drugs in each combination are known to be used chronically. For each of our 28 combinations, three drug response phenotypes have been identified (drug stop/switch, dose decrease, or dose increase of any of the two drugs during their interaction). The association between each of the three phenotypes belonging to each of our 28 drug combinations has been tested against our 114 candidate genetic variants. The results show replication of four findings between both databases : (1) Omeprazole +Amitriptyline +rs2246709 (A > G) variant in CYP3A4 gene (p-values and ORs with the UKBB and GoDARTs respectively = 0.048,0.037,0.92,and 0.52 (dose increase phenotype)) (2) Simvastatin + Ranitidine + rs9332197 (T > C) variant in CYP2C9 gene (0.024,0.032,0.81, and 5.75 (drug stop/switch phenotype)) (3) Atorvastatin + Doxazosin + rs9282564 (T > C) variant in ABCB1 gene (0.0015,0.0095,1.58,and 3.14 (drug stop/switch phenotype)) (4) Simvastatin + Nifedipine + rs2257401 (C > G) variant in CYP3A7 gene (0.025,0.019,0.77,and 0.30 (drug stop/switch phenotype)). In addition, some other non-replicated, but interesting, significant findings were detected. Our work also provides a great source of information for researchers interested in DD, DG, or DDG interactions studies as it has highlighted the top common drug combinations in the UK with recognizing 114 significant genetic variants related to drugs' pharmacokinetic.

Keywords: adverse drug reactions, common drug combinations, drug-drug-gene interactions, pharmacogenomics

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Authors: Ali H. Daraji, Ye Jianqiao

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The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

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Authors: Namasivayam Navaranjan, Eric Dimla

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The world needs more quality food, shelter and transportation to meet the demands of growing population and improving living standard of those who currently live below the poverty line. Materials are essential commodities for various applications including food and pharmaceutical packaging, building and automobile. Petroleum based plastics are widely used materials amongst others for these applications and their demand is expected to increase. Use of plastics has environment related issues because considerable amount of plastic used worldwide is disposed in landfills, where its resources are wasted, the material takes up valuable space and blights communities. Some countries have been implementing regulations and/or legislations to increase reuse, recycle, renew and remanufacture materials as well as to minimise the use of non-environmentally friendly materials such as petroleum plastics. However, issue of material waste is still a concern in the countries who have low environmental regulations. Development of materials, mostly bioplastics from renewable biomass resources has become popular in the last decade. It is widely believed that the potential for up to 90% substitution of total plastics consumption by bioplastics is technically possible. The global demand for bioplastics is estimated to be approximately six times larger than in 2010. Recently, standard polymers like polyethylene (PE), polypropylene (PP), Polyvinyl Chloride (PVC) or Polyethylene terephthalate (PET), but also high-performance polymers such as polyamides or polyesters have been totally or partially substituted by their renewable equivalents. An example is Polylactide (PLA) being used as a substitute in films and injection moulded products made of petroleum plastics, e.g. PET. The starting raw materials for bio-based materials are usually sugars or starches that are mostly derived from food resources, partially also recycled materials from food or wood processing. The risk in lower food availability by increasing price of basic grains as a result of competition with biomass-based product sectors for feedstock also needs to be considered for the future bioplastic production. Manufacturing of bioplastic materials is often still reliant upon petroleum as an energy and materials source. Life Cycle Assessment (LCA) of bioplastic products has being conducted to determine the sustainability of a production route. However, the accuracy of LCA depends on several factors and needs improvement. Low oil price and high production cost may also limit the technically possible growth of these plastics in the coming years.

Keywords: bioplastics, plastics, renewable resources, biomass

Procedia PDF Downloads 298

Authors: Bibha Kumari, Nigel P. Brunton, Dilip K. Rai, Brijesh K. Tiwari

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Edible mushrooms possess numerous functional components like homo- and hetero- β-glucans [β(1→3), β(1→4) and β(1→6) glucosidic linkages], chitins, ergosterols, bioactive polysaccharides and peptides imparting health beneficial properties to mushrooms. Some of the proven biological activities of mushroom extracts are antioxidant, antimicrobial, immunomodulatory, cholesterol lowering activity by inhibiting a key cholesterol metabolism enzyme i.e. 3-hydroxy-3-methyl-glutaryl CoA reductase (HMGCR), angiotensin I-converting enzyme (ACE) inhibition. Application of novel extraction technologies like pulsed electric field (PEF) and high power ultrasound offers clean, green, faster and efficient extraction alternatives with enhanced and good quality extracts. Sequential PEF followed by ultrasound assisted extraction (UAE) were applied to recover bioactive enriched fractions from industrial white button mushroom (Agaricus bisporus) stalk waste using environmentally friendly and GRAS solvents i.e. water and water/ethanol combinations. The PEF treatment was carried out at 60% output voltage, 2 Hz frequency for 500 pulses of 20 microseconds pulse width, using KCl salt solution of 0.6 mS/cm conductivity by the placing 35g of chopped fresh mushroom stalks and 25g of salt solution in the 4x4x4cm3 treatment chamber. Sequential UAE was carried out on the PEF pre-treated samples using ultrasonic-water-bath (USB) of three frequencies (25 KHz, 35 KHz and 45 KHz) for various treatment times (15-120 min) at 80°C. Individual treatment using either PEF or UAE were also investigation to compare the effect of each treatment along with the combined effect on the recovery and bioactivity of the crude extracts. The freeze dried mushroom stalk powder was characterised for proximate compositional parameters (dry weight basis) showing 64.11% total carbohydrate, 19.12% total protein, 7.21% total fat, 31.2% total dietary fiber, 7.9% chitin (as glucosamine equivalent) and 1.02% β-glucan content. The total phenolic contents (TPC) were determined by the Folin-Ciocalteu procedure and expressed as gallic-acid-equivalents (GAE). The antioxidant properties were ascertained using DPPH and FRAP assays and expressed as trolox-equivalents (TE). HMGCR activity and molecular mass of β-glucans will be measured using the commercial HMG-CoA Reductase Assay kit (Sigma-Aldrich) and size exclusion chromatography (HPLC-SEC), respectively. Effects of PEF, UAE and their combination on the antioxidant capacity, HMGCR inhibition and β-glucans content will be presented.

Keywords: β-glucan, mushroom stalks, pulsed electric field (PEF), ultrasound assisted extraction (UAE)

Procedia PDF Downloads 273

Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

Procedia PDF Downloads 327

Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Desmond F. Bellamy

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Discourses about animal rights usually assume an ontological abyss between human and animal. This supposition of non-animality allows us to utilise and exploit non-humans, particularly those with commercial value, with little regard for their rights or interests. We can and do confine them, inflict painful treatments such as castration and branding, and slaughter them at an age determined only by financial considerations. This paper explores the way images and texts depicting human cannibalism reflect this deprivation of rights back onto our species and examines how this offers new perspectives on our granting or withholding of rights to farmed animals. The animals we eat – sheep, pigs, cows, chickens and a small handful of other species – are during processing de-animalised, turned into commodities, and made unrecognisable as formerly living beings. To do the same to a human requires the cannibal to enact another step – humans must first be considered as animals before they can be commodified or de-animalised. Different iterations of cannibalism in a selection of fiction and non-fiction texts will be considered: survivalism (necessitated by catastrophe or dystopian social collapse), the primitive savage of colonial discourses, and the inhuman psychopath. Each type of cannibalism shows alternative ways humans can be animalised and thereby dispossessed of both their human and animal rights. Human rights, summarised in the UN Universal Declaration of Human Rights as ‘life, liberty, and security of person’ are stubbornly denied to many humans, and are refused to virtually all farmed non-humans. How might this paradigm be transformed by seeing the animal victim replaced by an animalised human? People are fascinated as well as repulsed by cannibalism, as demonstrated by the upsurge of films on the subject in the last few decades. Cannibalism is, at its most basic, about envisaging and treating humans as objects: meat. It is on the dinner plate that the abyss between human and ‘animal’ is most challenged. We grasp at a conscious level that we are a species of animal and may become, if in the wrong place (e.g., shark-infested water), ‘just food’. Culturally, however, strong traditions insist that humans are much more than ‘just meat’ and deserve a better fate than torment and death. The billions of animals on death row awaiting human consumption would ask the same if they could. Depictions of cannibalism demonstrate in graphic ways that humans are animals, made of meat and that we can also be butchered and eaten. These depictions of us as having the same fleshiness as non-human animals reminds us that they have the same capacities for pain and pleasure as we do. Depictions of cannibalism, therefore, unconsciously aid in deconstructing the human/animal binary and give a unique glimpse into the often unnoticed repudiation of animal rights.

Keywords: animal rights, cannibalism, human/animal binary, objectification

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Authors: Jayati Bhattacharjee

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Teaching is a very dynamic profession. Teaching Science is as much challenging as Learning the subject if not more. For instance teaching of Chemistry. From the introductory concepts of subatomic particles to atoms of elements and their symbols and further presenting the chemical equation and so forth is a challenge on both side of the equation Teaching Learning. This paper combines the Neuroscience of Learning and memory with the knowledge of Learning style (VAK) and presents an effective tool for the teacher to authenticate Learning. The model of ‘Working Memory’, the Visio-spatial sketchpad, the central executive and the phonological loop that transforms short-term memory to long term memory actually supports the psychological theory of Learning style i.e. Visual –Auditory-Kinesthetic. A closer examination of David Kolbe’s learning model suggests that learning requires abilities that are polar opposites, and that the learner must continually choose which set of learning abilities he or she will use in a specific learning situation. In grasping experience some of us perceive new information through experiencing the concrete, tangible, felt qualities of the world, relying on our senses and immersing ourselves in concrete reality. Others tend to perceive, grasp, or take hold of new information through symbolic representation or abstract conceptualization – thinking about, analyzing, or systematically planning, rather than using sensation as a guide. Similarly, in transforming or processing experience some of us tend to carefully watch others who are involved in the experience and reflect on what happens, while others choose to jump right in and start doing things. The watchers favor reflective observation, while the doers favor active experimentation. Any lesson plan based on the model of Prescriptive design: C+O=M (C: Instructional condition; O: Instructional Outcome; M: Instructional method). The desired outcome and conditions are independent variables whereas the instructional method is dependent hence can be planned and suited to maximize the learning outcome. The assessment for learning rather than of learning can encourage, build confidence and hope amongst the learners and go a long way to replace the anxiety and hopelessness that a student experiences while learning Science with a human touch in it. Application of this model has been tried in teaching chemistry to high school students as well as in workshops with teachers. The response received has proven the desirable results.

Keywords: working memory model, learning style, prescriptive design, assessment for learning

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Authors: Z. Yousefniayejahr, S. Bolognini, A. Bonini, C. Campobasso, N. Poma, F. Vivaldi, M. Di Luca, A. Tavanti, F. Di Francesco

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Pathogenic bacteria represent a threat to healthcare systems and the food industry because their rapid detection remains challenging. Electrochemical biosensors are gaining prominence as a novel technology for the detection of pathogens due to intrinsic features such as low cost, rapid response time, and portability, which make them a valuable alternative to traditional methodologies. These sensors use biorecognition elements that are crucial for the identification of specific bacteria. In this context, bacteriophages are promising tools for their inherent high selectivity towards bacterial hosts, which is of fundamental importance when detecting bacterial pathogens in complex biological samples. In this study, we present the development of a low-cost and portable sensor based on the Zeno phage for the rapid detection of Staphylococcus aureus. Screen-printed gold electrodes functionalized with the Zeno phage were used, and electrochemical impedance spectroscopy was applied to evaluate the change of the charge transfer resistance (Rct) as a result of the interaction with S. aureus MRSA ATCC 43300. The phage-based biosensor showed a linear range from 101 to 104 CFU/mL with a 20-minute response time and a limit of detection (LOD) of 1.2 CFU/mL under physiological conditions. The biosensor’s ability to recognize various strains of staphylococci was also successfully demonstrated in the presence of clinical isolates collected from different geographic areas. Assays using S. epidermidis were also carried out to verify the species-specificity of the phage sensor. We only observed a remarkable change of the Rct in the presence of the target S. aureus bacteria, while no substantial binding to S. epidermidis occurred. This confirmed that the Zeno phage sensor only targets S. aureus species within the genus Staphylococcus. In addition, the biosensor's specificity with respect to other bacterial species, including gram-positive bacteria like Enterococcus faecium and the gram-negative bacterium Pseudomonas aeruginosa, was evaluated, and a non-significant impedimetric signal was observed. Notably, the biosensor successfully identified S. aureus bacterial cells in a complex matrix such as a nasal swab, opening the possibility of its use in a real-case scenario. We diluted different concentrations of S. aureus from 108 to 100 CFU/mL with a ratio of 1:10 in the nasal swap matrices collected from healthy donors. Three different sensors were applied to measure various concentrations of bacteria. Our sensor indicated high selectivity to detect S. aureus in biological matrices compared to time-consuming traditional methods, such as enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and radioimmunoassay (RIA), etc. With the aim to study the possibility to use this biosensor to address the challenge associated to pathogen detection, ongoing research is focused on the assessment of the biosensor’s analytical performances in different biological samples and the discovery of new phage bioreceptors.

Keywords: electrochemical impedance spectroscopy, bacteriophage, biosensor, Staphylococcus aureus

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Authors: Birgul Hizlar, Sibel Karakaya

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Recently, increasing attention has been given to carotenoid bioaccessibility and bioavailability in the field of nutrition research. As a consequence of their lipophilic nature and their specific localization in plant-based tissues, carotenoid bioaccessibility and bioavailability is generally quite low in raw fruits and vegetables, since carotenoids need to be released from the cellular matrix and incorporated in the lipid fraction during digestion before being absorbed. Today’s approach related to improving the bioaccessibility is to design food matrix. Recently, the newest approach, excipient food, has been introduced to improve the bioavailability of orally administered bioactive compounds. The main idea is combining food and another food (the excipient food) whose composition and/or structure is specifically designed for improving health benefits. In this study, effects of food processing, food matrix and the addition of excipient foods on the carotenoid bioaccessibility of carrots were determined. Different excipient foods (olive oil, lemon juice and whey curd) and different food matrices (grating, boiling and mashing) were used. Total carotenoid contents of the grated, boiled and mashed carrots were 57.23, 51.11 and 62.10 μg/g respectively. No significant differences among these values indicated that these treatments had no effect on the release of carotenoids from the food matrix. Contrary to, changes in the food matrix, especially mashing caused significant increase in the carotenoid bioaccessibility. Although the carotenoid bioaccessibility was 10.76% in grated carrots, this value was 18.19% in mashed carrots (p<0.05). Addition of olive oil and lemon juice as excipients into the grated carrots caused 1.23 times and 1.67 times increase in the carotenoid content and the carotenoid bioaccessibility respectively. However, addition of the excipient foods in the boiled carrot samples did not influence the release of carotenoid from the food matrix. Whereas, up to 1.9 fold increase in the carotenoid bioaccessibility was determined by the addition of the excipient foods into the boiled carrots. The bioaccessibility increased from 14.20% to 27.12% by the addition of olive oil, lemon juice and whey curd. The highest carotenoid content among mashed carrots was found in the mashed carrots incorporated with olive oil and lemon juice. This combination also caused a significant increase in the carotenoid bioaccessibility from 18.19% to 29.94% (p<0.05). When compared the results related with the effect of the treatments on the carotenoid bioaccessibility, mashed carrots containing olive oil, lemon juice and whey curd had the highest carotenoid bioaccessibility. The increase in the bioaccessibility was approximately 81% when compared to grated and mashed samples containing olive oil, lemon juice and whey curd. In conclusion, these results demonstrated that the food matrix and addition of the excipient foods had a significant effect on the carotenoid content and the carotenoid bioaccessibility.

Keywords: carrot, carotenoids, excipient foods, food matrix

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Authors: Juliet Sorensen, Anna Maitland

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Introduction: Characterized by lack of water and sanitation, food insecurity, and low access to hospitals and clinics, informal urban settlements in Lagos, Nigeria have very poor health outcomes. With little education and a general inability to demand basic rights, these communities are often disempowered and isolated from understanding, claiming, or owning their health needs. Utilizing community-based participatory research characterized by interdisciplinary, cross-cultural partnerships, evidence-based assessments, and both primary and secondary source research, a holistic health education and advocacy program was developed in Lagos to address health barriers for targeted communities. This includes a first of its kind guide formulated to teach community-based health educators how to transmit health information to low-literacy Nigerian audiences while supporting behavior change models and social support mechanisms. This paper discusses the interdisciplinary contributions to developing a health education program while also looking at the need for greater beneficiary ownership and implementation of health justice and access. Methods: In March 2016, an interdisciplinary group of medical, legal, and business graduate students and faculty from Northwestern University conduced a Health Needs Assessment (HNA) in Lagos with a partner and a local non-governmental organization. The HNA revealed that members of informal urban communities in Lagos were lacking basic health literacy, but desired to remedy this lacuna. Further, the HNA revealed that even where the government mandates specific services, many vulnerable populations are unable to access these services. The HNA concluded that a program focused on education, advocacy, and organizing around anatomy, maternal and sexual health, infectious disease and malaria, HIV/AIDS, emergency care, and water and sanitation would respond to stated needs while also building capacity in communities to address health barriers. Results: Based on the HNA, including both primary and secondary source research on integrated health education approaches and behavior change models and responsive, adaptive material development, a holistic program was developed for the Lagos partners and first implemented in November 2016. This program trained community-nominated health educators in adult, low-literacy, knowledge exchange approaches, utilizing information identified by communities as a priority. After a second training in March 2017, these educators will teach community-based groups and will support and facilitate behavior change models and peer-support methods around basic issues like hand washing and disease transmission. They will be supported by community paralegals who will help ensure that newly trained community groups can act on education around access, such as receiving free vaccinations, maternal health care, and HIV/AIDS medicines. Materials will continue to be updated as needs and issues arise, with a focus on identifying best practices around health improvements that can be shared across these partner communities. Conclusion: These materials are the first of their kind, and address a void of health information and understanding pervasive in informal-urban Lagos communities. Initial feedback indicates high levels of commitment and interest, as well as investment by communities in these materials, largely because they are responsive, targeted, and build community capacity. This methodology is an important step in dignity-based health justice solutions, albeit in the process of refinement.

Keywords: community health educators, interdisciplinary and cross cultural partnerships, health justice and access, Nigeria

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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Authors: Doni Dermawan

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Modern sports competition as a consequence of the increase in the value of the business and entertainment in the field of sport has been demanding athletes to always have excellent physical endurance performance. Physical exercise is done in a long time, and intensive may pose a risk of muscle tissue damage caused by the increase of the enzyme creatine kinase. Branched Chain Amino Acids (BCAA) is an essential amino acid that is composed of leucine, isoleucine, and valine which serves to maintain muscle tissue, keeping the immune system, and prevent further loss of coordination and muscle pain. Pea (Pisum sativum L.) is a kind of leguminous plants that are rich in Branched Chain Amino Acids (BCAA) where every one gram of protein pea contains 82.7 mg of leucine; 56.3 mg isoleucine; and 56.0 mg of valine. This research aims to develop Branched Chain Amino Acids (BCAA) from pea extract is applied in dosage forms Gel PVP Kinesio Tape technology using Ultrasound-assisted Extraction. The method used in the writing of this paper is the Cochrane Collaboration Review that includes literature studies, testing the quality of the study, the characteristics of the data collection, analysis, interpretation of results, and clinical trials as well as recommendations for further research. Extraction of BCAA in pea done using ultrasound-assisted extraction technology with optimization variables includes the type of solvent extraction (NaOH 0.1%), temperature (20-250C), time (15-30 minutes) power (80 watt) and ultrasonic frequency (35 KHz). The advantages of this extraction method are the level of penetration of the solvent into the membrane of the cell is high and can increase the transfer period so that the BCAA substance separation process more efficient. BCAA extraction results are then applied to the polymer PVP (Polyvinylpyrrolidone) Gel powder composed of PVP K30 and K100 HPMC dissolved in 10 mL of water-methanol (1: 1) v / v. Preparations Kinesio Tape Gel PVP is the BCAA in the gel are absorbed into the muscle tissue, and joints through tensile force then provides stimulation to the muscle circulation with variable pressure so that the muscle can increase the biomechanical movement and prevent damage to the muscle enzyme creatine kinase. Analysis and evaluation of test preparation include interaction, thickness, weight uniformity, humidity, water vapor permeability, the levels of the active substance, content uniformity, percentage elongation, stability testing, release profile, permeation in vitro and in vivo skin irritation testing.

Keywords: branched chain amino acid, BCAA, Kinesio tape, pea, PVP gel, ultrasound-assisted extraction

Procedia PDF Downloads 270

Authors: Yang Cao

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Analyzing the oral production of Chinese-speaking learners of English as a second language (L2), we can find a large variety of verb inflections – Why does it seem so hard for them to use consistent correct past morphologies in obligatory past contexts? Failed Functional Features Hypothesis (FFFH) attributes the rather non-target-like performance to the absence of [±past] feature in their L1 Chinese, arguing that for post puberty learners, new features in L2 are no more accessible. By contrast, Missing Surface Inflection Hypothesis (MSIH) tends to believe that all features are actually acquirable for late L2 learners, while due to the mapping difficulties from features to forms, it is hard for them to realize the consistent past morphologies on the surface. However, most of the studies are limited to the verb morphologies in finite clauses and few studies have ever attempted to figure out these learners’ performance in non-finite clauses. Additionally, it has been discussed that Chinese learners may be able to tell the finite/infinite distinction (i.e. the [±finite] feature might be selected in Chinese, even though the existence of [±past] is denied). Therefore, adopting a self-paced reading task (SPR), the current study aims to analyze the processing patterns of Chinese-speaking learners of L2 Russian, in order to find out if they are sensitive to misuse of tense morphologies in both finite and non-finite clauses and whether they are sensitive to the finite/infinite distinction presented in Russian. The study targets L2 Russian due to its systematic morphologies in both present and past tenses. A native Russian group, as well as a group of English-speaking learners of Russian, whose L1 has definitely selected both [±finite] and [±past] features, will also be involved. By comparing and contrasting performance of the three language groups, the study is going to further examine and discuss the two theories, FFFH and MSIH. Preliminary hypotheses are: a) Russian native speakers are expected to spend longer time reading the verb forms which violate the grammar; b) it is expected that Chinese participants are, at least, sensitive to the misuse of inflected verbs in non-finite clauses, although no sensitivity to the misuse of infinitives in finite clauses might be found. Therefore, an interaction of finite and grammaticality is expected to be found, which indicate that these learners are able to tell the finite/infinite distinction; and c) having selected [±finite] and [±past], English-speaking learners of Russian are expected to behave target-likely, supporting L1 transfer.

Keywords: features, finite clauses, morphosyntax, non-finite clauses, past morphologies, present morphologies, Second Language Acquisition, self-paced reading task, verb inflections

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Authors: Federica Verna, Alessandra Pautasso, Maria Caramelli, Cristiana Maurella, Walter Mignone, Cristina Casalone

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Mosquito-Borne Diseases (MBDs) are dangerously increasing in prevalence, geographical distribution and severity, representing an emerging threat for both humans and animals. Interaction between multiple disciplines is needed for an effective early warning, surveillance and control of MBDs, according to the One Health concept. This work reports the integrated surveillance system enforced by IZSPLV in Piedmont, Liguria and Valle d’Aosta regions (Northwestern Italy) in order to control MDBs spread. Veterinary services and local human health authority are involved in an information network, to connect the surveillance of human clinical cases with entomological surveillance and veterinary monitoring in order to implement control measures in case of outbreak. A systematic entomological surveillance is carried out during the vector season using mosquitoes traps located in sites selected according to risk factors. Collected mosquitoes are counted, identified to species level by morphological standard classification keys and pooled by collection site, date and species with a maximum of 100 individuals. Pools are analyzed, after RNA extraction, by Real Time RT-PCR distinctive for West Nile Virus (WNV) Lineage 1 and Lineage 2, Real Time RT-PCR USUTU virus (USUV) and a traditional flavivirus End-point RT-PCR. Positive pools are sequenced and the related sequences employed to perform a basic local alignment search tool (BLAST) in the GenBank library. Positive samples are sent to the National Reference Centre for Animal Exotic Diseases (CESME, Teramo) for confirmation. With particular reference to WNV, after the confirmation, as provided by national legislation, control measures involving both local veterinary and human health services are activated: equine sera are randomly sampled within a 4 km radius from the positive collection sites and tested with ELISA kit and WNV NAT screening of blood donors is introduced. This surveillance network allowed to detect since 2011 USUV circulation in this area of Italy. WNV was detected in Piedmont and Liguria for the first time in 2014 in mosquitoes. During the 2015 vector season, we observed the expansion of its activity in Piedmont. The virus was detected in almost all Provinces both in mosquitoes (6 pools) and animals (19 equine sera, 4 birds). No blood bag tested resulted infected. The first neuroinvasive human case occurred too. Competent authorities should be aware of a potentially increased risk of MBDs activity during the 2016 vector season. This work shows that this surveillance network allowed to early detect the presence of MBDs in humans and animals, and provided useful information to public authorities, in order to apply control measures. Finally, an additional value of our diagnostic protocol is the ability to detect all viruses belonging to the Flaviviridae family, considering the emergence caused by other Flaviviruses in humans such as the recent Zika virus infection in South America. Italy has climatic and environmental features conducive to Zika virus transmission, the competent vector and many travellers from Brazil reported every year.

Keywords: integrated surveillance, mosquito borne disease, West Nile virus, Zika virus

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Hilal Köse, Şeyma Dombaycıoğlu, Ali Osman Aydın, Hatem Akbulut

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Rechargeable lithium-ion batteries (LIBs) have become promising power sources for a wide range of applications, such as mobile communication devices, portable electronic devices and electrical/hybrid vehicles due to their long cycle life, high voltage and high energy density. Graphite, as anode material, has been widely used owing to its extraordinary electronic transport properties, large surface area, and high electrocatalytic activities although its limited specific capacity (372 mAh g-1) cannot fulfil the increasing demand for lithium-ion batteries with higher energy density. To settle this problem, many studies have been taken into consideration to investigate new electrode materials and metal oxide/graphene composites are selected as a kind of promising material for lithium ion batteries as their specific capacities are much higher than graphene. Among them, SnO₂, an n-type and wide band gap semiconductor, has attracted much attention as an anode material for the new-generation lithium-ion batteries with its high theoretical capacity (790 mAh g-1). However, it suffers from large volume changes and agglomeration associated with the Li-ion insertion and extraction processes, which brings about failure and loss of electrical contact of the anode. In addition, there is also a huge irreversible capacity during the first cycle due to the formation of amorphous Li₂O matrix. To obtain high capacity anode materials, we studied on the synthesis and characterization of SnO₂-Graphene nanocomposites and investigated the capacity of this free-standing anode material in this work. For this aim, firstly, graphite oxide was obtained from graphite powder using the method described by Hummers method. To prepare the nanocomposites as free-standing anode, graphite oxide particles were ultrasonicated in distilled water with SnO2 nanoparticles (1:1, w/w). After vacuum filtration, the GO-SnO₂ paper was peeled off from the PVDF membrane to obtain a flexible, free-standing GO paper. Then, GO structure was reduced in hydrazine solution. Produced SnO2- graphene nanocomposites were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), and X-ray diffraction (XRD) analyses. CR2016 cells were assembled in a glove box (MBraun-Labstar). The cells were charged and discharged at 25°C between fixed voltage limits (2.5 V to 0.2 V) at a constant current density on a BST8-MA MTI model battery tester with 0.2C charge-discharge rate. Cyclic voltammetry (CV) was performed at the scan rate of 0.1 mVs-1 and electrochemical impedance spectroscopy (EIS) measurements were carried out using Gamry Instrument applying a sine wave of 10 mV amplitude over a frequency range of 1000 kHz-0.01 Hz.

Keywords: SnO₂-graphene, nanocomposite, anode, Li-ion battery

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Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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