Search results for: echocardiographic view detection

Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

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Authors: Katerina H. Takova, Ivan N. Minkov, Gergana G. Zahmanova

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Molecular farming is the production of recombinant proteins in plants with the aim to use the protein as a purified product, crude extract or directly in the planta. Plants gain more attention as expression systems compared to other ones due to the cost effective production of pharmaceutically important proteins, appropriate post-translational modifications, assembly of complex proteins, absence of human pathogens to name a few. In addition, transient expression in plant leaves enables production of recombinant proteins within few weeks. Hepatitis E virus (HEV) is a causative agent of acute hepatitis. HEV causes epidemics in developing countries and is primarily transmitted through the fecal-oral route. Presently, all efforts for development of Hepatitis E vaccine are focused on the Open Read Frame 2 (ORF2) capsid protein as it contains epitopes that can induce neutralizing antibodies. For our purpose, we used the CMPV-based vector-pEAQ-HT for transient expression of HEV ORF2 in Nicotiana benthamina. Different molecular analysis (Western blot and ELISA) showed that HEV ORF2 capsid protein was expressed in plant tissue in high-yield up to 1g/kg of fresh leaf tissue. Electron microscopy showed that the capsid protein spontaneously assembled in low abundance virus-like particles (VLPs), which are highly immunogenic structures and suitable for vaccine development. The expressed protein was recognized by both human and swine HEV positive sera and can be used as a diagnostic reagent for the detection of HEV infection. Production of HEV capsid protein in plants is a promising technology for further HEV vaccine investigations. Here, we reported for a rapid high-yield transient expression of a recombinant protein in plants suitable for vaccine production as well as a diagnostic reagent. Acknowledgments -The authors’ research on HEV is supported with grants from the Project PlantaSYST under the Widening Program, H2020 as well as under the UK Biotechnological and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Grant ‘Understanding and Exploiting Plant and Microbial Secondary Metabolism’ (BB/J004596/1). The authors want to thank Prof. George Lomonossoff (JIC, Norwich, UK) for his contribution.

Keywords: hepatitis E virus, plant molecular farming, transient expression, vaccines

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Authors: Andleeb Zahra, Itrat Rubab, Sumaira Malik, Amina Khan, Muhammad Jawad Khan, M. Qaiser Fatmi

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Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use in an early diagnostic tool. miRNAs are small, double stranded, non-coding RNAs that regulate gene expression by deregulating mRNAs. miRNAs play important roles in modifying various cellular processes such as cell growth, differentiation, apoptosis, and immune response. Dis-regulated expression of miRNAs is known to affect the cell growth, and this may function as tumor suppressors or oncogenes in various cancers. Objectives: The main objectives of this study were to characterize the extracellular miRNAs involved in oral cancer (OC) to assist early detection of cancer as well as to propose a list of genes that can potentially be used as biomarkers of OC. We used gene expression data by microarrays already available in literature. Materials and Methods: In the first step, a total of 318 miRNAs involved in oral carcinoma were shortlisted followed by the prediction of their target genes. Simultaneously, the differentially expressed genes (DEGs) of oral carcinoma from all experiments were identified. The common genes between lists of DEGs of OC based on experimentally proven data and target genes of each miRNA were identified. These common genes are the targets of specific miRNA, which is involved in OC. Finally, a list of genes was generated which may be used as biomarker of OC. Results and Conclusion: In results, we included some of pathways in cancer to show the change in gene expression under the control of specific miRNA. Ingenuity pathway analysis (IPA) provided a list of major biomarkers like CDH2, CDK7 and functional enrichment analysis identified the role of miRNA in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes are regulated by maximum number of miRNAs, and thereby, they can be used as biomarkers of OC. To better understand the role of miRNA with respect to their target genes further experiments are required, and our study provides a platform to better understand the miRNA-OC relationship at genomics level.

Keywords: biomarkers, gene expression, miRNA, oral carcinoma

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Authors: Renata Hrecska

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This research seeks to fully examine the internal employment law of international organizations by comparing it with the characteristics of the national civil service. The aim of the research is to compare the legal system that has developed over many centuries and the relatively new internal staffing regulations to find out what solution schemes can help each other through mutual legal development in order to respond effectively to the social challenges of everyday life. Generally, the rules of civil service of any country or international entity have in common that they have, in their pragmatics inherently, the characteristic that makes them serving public interests. Though behind the common base there are many differences: there is the clear fragmentation of state regulation and the unity of organizational regulation. On the other hand, however, this difference disappears to some extent: the public service regulation of international organizations can be considered uniform until we examine it within, but not outside an organization. As soon as we compare the different organizations we may find many different solutions for staffing regulations. It is clear that the national civil service is a strong model for international organizations, but the question may be whether the staffing policy of international organizations can serve the national civil service as an example, too. In this respect, the easiest way to imagine a legislative environment would be to have a single comprehensive code, the general part of which is the Civil Service Act itself, and the specific part containing specific, necessarily differentiating rules for each layer of the civil service. Would it be advantageous to follow the footsteps of the leading international organizations, or is there any speciality in national level civil service that we cannot avoid during regulating processes? In addition to the above, the personal competencies of officials working in international organizations and public administrations also show a high degree of similarity, regardless of the type of employment. Thus, the whole public service system is characterized by the fundamental and special values that a person capable of holding a public office must be able to demonstrate, in some cases, even without special qualifications. It is also interesting how we can compare the two spheres of employment in light of the theory of Lawyer Louis Brandeis, a judge at the US Supreme Court, who formulated a complex theory of profession as distinguished from other occupations. From this point of view we can examine the continuous development of research and specialized knowledge at work; the community recognition and social status; that to what extent we can see a close-knit professional organization of altruistic philosophy; that how stability grows in the working conditions due to the stability of the profession; and that how the autonomy of the profession can prevail.

Keywords: civil service, comparative law, international organizations, regulatory systems

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Authors: Arunas Burinskas, Aurelija Burinskiene

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On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Rammah Abdlbagi, Egmen Tazcan, Kiriti Tripathi, Vinayagam Sudhakar, Thomas Swallow, Aakash Pai

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Introduction and Objectives: MRI has an increasing role in the diagnosis and staging of prostate cancer. Multiparametric MRI includes multiple sequences, including T2 weighting, diffusion weighting, and dynamic contrast enhancement (DCE). Administration of DCE is expensive, time-consuming, and requires medical supervision due to the risk of anaphylaxis. Biparametric MRI (bpMRI), without DCE, overcomes many of these issues; however, there is conflicting data on its accuracy. Furthermore, data on the concordance between bpMRI lesion and pathology specimen, as well as the rates of cancer stage upgrading after surgery, is limited within the available literature. This study aims to examine the diagnostic test accuracy of bpMRI in the diagnosis of prostate cancer and radiological assessment of prostate cancer staging. Specifically, we aimed to evaluate the ability of bpMRI to accurately localise malignant lesions to better understand its accuracy and application in MRI-targeted biopsies. Materials and Methods: One hundred and forty patients who underwent bpMRI prior to radical prostatectomy (RP) were retrospectively reviewed from a single institution. Histological grade from the prostate biopsy was compared with surgical specimens from RP. Clinically significant prostate cancer (csPCa) was defined as Gleason grade group ≥2. bpMRI staging was compared with RP histology. Results: Overall sensitivity of bpMRI in diagnosing csPCa independent of location and staging was 98.87%. Of the 140 patients, 29 (20.71%) had their prostate biopsy histology upgraded at RP. 61 (43.57%) patients had csPca noted on RP specimens in areas that were not identified on the bpMRI. 55 (39.29%) had upstaging after RP from the original staging with bpMRI. Conclusions: Whilst the overall sensitivity of bpMRI in predicting any clinically significant cancer was good, there was notably poor concordance in the location of the tumour between bpMRI and eventual RP specimen. The results suggest that caution should be exercised when using bpMRI for targeted prostate biopsies and validates the continued role of systemic biopsies. Furthermore, a significant number of patients were upstaged at RP from their original staging with bpMRI. Based on these findings, bpMRI results should be interpreted with caution and can underestimate TNM stage, requiring careful consideration of treatment strategy.

Keywords: biparametric MRI, Ca prostate, staging, post prostatectomy histology

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Authors: T. I. Mbata, M. J. Ikenebomeh

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Background: The study was aim at formulating a complementary foods based on maize and bambara groundnut with a view of reducing malnutrition in low income families. Protein-energy malnutrition is a major health challenge attributed to the inappropriate complementary feeding practices, low nutritional quality of traditional complementary foods and high cost of quality protein-based complementary foods. Methods: The blends 70% maize, 30% bambara groundnut were evaluated for proximate analyses, minerals, amino acids profile, and antinutritional factors, using proprietary formula (‘Nutrend’) as standard. Antinutritional factors, amino acids, microbiological properties and sensory attributes were determined using standard methods. Results; For Protein, the results were 15.0% for roasted bambara groundnut maize germinated flour (RBMGF), 13.80% for cooked bambara groundnut maize germinated flour (CBMGF), 15.18% for soaked bambara groundnut maize germinated flour (SBMGF); values for maize flour and nutrend had 10.4% and 23.21% respectively. With respect to energy value, RBMGF, CBMGF, SBMGF, maize flour and nutrend had 494.9, 327.58, 356.49, 366.8 and 467.2 kcal respectively. The percentages of total essential amino acids in the composition of the blends were 36.9%, 40.7% and 38.9% for CBMGF, SBMGF and RBMGF, respectively, non-essential amino acids contents were 63.1%, 59.3% and 61.1% for CBMGF, SBMGF and RBMGF respectively. The mineral content, that is, calcium, potassium, magnesium and sodium, of formulated samples were higher than those obtained for maize flour and Nutrend. The antinutrient composition of RBMGF and CBMGF were lower than of SBMGF. The rats fed with the control diet exhibited better growth performance such as feed intake (1527 g) and body weight gain (93.8 g). For the microbial status, microflora gradually changed from gram negative enteric bacteria, molds, lactic acid bacteria and yeast to be dominated by gram positive lactic acid bacteria (LAB) and yeasts. Yeasts and LAB growth counts in the complementary food varied between 4.44 and 7.36 log cfu/ml. LAB number increased from 5.40 to 7.36 log cfu/ml during fermentation. Yeasts increased from 4.44 to 5.60 log cfu/ml. Organoleptic evaluation revealed that the foods were well accepted. Conclusion: Based on the findings the application of bambara groundnut fortification to traditional foods can promote the nutritional quality of African maize - based traditional foods with acceptable rheological and cooking qualities.

Keywords: bambara groundnut, maize, fortification, complementary food

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Authors: Lorato Itumeleng Kenosi

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Background: Negative attitudes towards the mentally ill are widespread and a course for concern as they have a detrimental impact on individuals affected by mental illness. A possible avenue for changing attitudes towards mental illness is through mental health literacy. In a college or university setting, an abnormal psychology course may be introduced in an attempt to change student’s attitudes towards the mentally ill. Objective: To determine if and how students’ attitudes towards the mentally ill change as a result of taking a course in abnormal psychology. Methods: Twenty nine (29) students were recruited from an abnormal psychology class at the University of Botswana. Attitude Scale for Mental Illness (ASMI) questionnaire was administered to participants at the beginning and end of the semester. SPSS was employed to analyze data. Pooled means were used to determine whether the student’s attitudes towards mental illness were negative or positive. A mean of 2.5 translated to negative attitude for both total attitude and attitudes in different domains of the scale. Paired sample t-test was then used to assess whether any changes noted in attitudes were statistically significant or not. Statistical significance was assumed at p < 0.05. Results: Students’ general attitude towards mental illness remained positive although the pooled mean value increased from 2.08 to 2.24. The change was not statistically significant. In relation to different sub scales, the values of the pooled means for all the sub scales showed an increase although the changes were not statistically significant except for the Stereotyping sub scale (p = 0.031). The stereotyping domain reflected a statistically significant change in student’s attitude from positive attitude to negative (X² = 2.06 to X² = 2.55). For the pessimistic prediction domain, students consistently showed a negative attitude (X² = 3.34 to X² = 3.55). The other 4 domains indicated that students had positive attitude toward mentally ill throughout. Discussion: Abnormal psychology students have a positive attitude towards the mentally ill generally. This could be attributed to the fact that all students in the abnormal psychology course are majoring in psychology and research has shown that interest in psychology can affect one’s attitude towards mental illness. The students continuously held the view that people with mental illness are unlikely to improve as evidenced by a high score for Pessimistic prediction domain for both pre and post-test. Students initially had no stereotyping attitude towards the mentally ill, but at the end of the course, they were of the opinion that people with mental illness can be defined in a certain behavioural pattern and mental ability. This results could be an indication that students have learnt well how to differentiate abnormal from normal behaviour not necessarily that students had developed a negative attitude. Conclusion: A course in abnormal psychology does have an impact on the students’ attitudes towards the mentally ill. The impact does not solely depend on knowledge of mental illness but also on several other factors such as contact with the mentally ill, interest in psychology, and teaching methods. However, it should be noted that sometimes improved knowledge in mental illness can be misunderstood for a negative attitude. For example, stereotyping attitudes may be a reflection of the ability to differentiate between abnormal and normal behaviour.

Keywords: attitudes, mental illness, psychopathology, students

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Authors: A. G. Cunha, M. Inácio, M. C. Freitas, C. Antunes, T. Silva, C. Andrade, V. Lopes

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Saltmarshes are essential ecosystems both from an ecological and biological point of view. Furthermore, they constitute an important social niche, providing valuable economic and protection functions. Thus, understanding their rates and patterns of sedimentation is critical for functional management and rehabilitation, especially in an SLR scenario. The Sado estuary is located 40 km south of Lisbon. It is a bar built estuary, separated from the sea by a large sand spit: the Tróia barrier. Caldeira de Tróia is located on the free edge of this barrier, and encompasses a salt marsh with ca. 21,000 m². Sediment cores were collected in the high and low marshes and in the mudflat area of the North bank of Caldeira de Tróia. From the low marsh core, fifteen samples were chosen for ²¹⁰Pb and ¹³⁷Cs determination at University of Geneva. The cores from the high marsh and the mudflat are still being analyzed. A sedimentation rate of 2.96 mm/year was derived from ²¹⁰Pb using the Constant Flux Constant Sedimentation model. The ¹³⁷Cs profile shows a peak in activity (1963) between 15.50 and 18.50 cm, giving a 3.1 mm/year sedimentation rate for the past 53 years. The adopted sea level rise scenario was based on a model built with the initial rate of SLR of 2.1 mm/year in 2000 and an acceleration of 0.08 mm/year². Based on the harmonic analysis of Setubal-Tróia tide gauge of 2005 data, the tide model was estimated and used to build the tidal tables to the period 2000-2016. With these tables, the average mean water levels were determined for the same time span. A digital terrain model was created from LIDAR scanning with 2m horizontal resolution (APA-DGT, 2011) and validated with altimetric data obtained with a DGPS-RTK. The response model calculates a new elevation for each pixel of the DTM for 2050 and 2100 based on the sedimentation rates specific of each environment. At this stage, theoretical values were chosen for the high marsh and the mudflat (respectively, equal and double the low marsh rate – 2.92 mm/year). These values will be rectified once sedimentation rates are determined for the other environments. For both projections, the total surface of the marsh decreases: 2% in 2050 and 61% in 2100. Additionally, the high marsh coverage diminishes significantly, indicating a regression in terms of maturity.

Keywords: ¹³⁷Cs, ²¹⁰Pb, saltmarsh, sea level rise, response model

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Authors: Binger Lu

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It remains unclear whether second language (L2) speakers could use discourse context cues to predict upcoming information as native speakers do during online comprehension. Some researchers propose that L2 learners may have a reduced ability to generate predictions during discourse processing. At the same time, there is evidence that discourse-level cues are weighed more heavily in L2 processing than in L1. Previous studies showed that L1 prediction is sensitive to the global validity of predictive cues. The current study aims to explore whether and to what extent L2 learners can dynamically and strategically adjust their prediction in accord with the global validity of predictive cues in L2 discourse comprehension as native speakers do. In a self-paced reading experiment, Chinese native speakers (N=128), C-E bilinguals (N=128), and English native speakers (N=128) read high-predictable (e.g., Jimmy felt thirsty after running. He wanted to get some water from the refrigerator.) and low-predictable (e.g., Jimmy felt sick this morning. He wanted to get some water from the refrigerator.) discourses in two-sentence frames. The global validity of predictive cues was manipulated by varying the ratio of predictable (e.g., Bill stood at the door. He opened it with the key.) and unpredictable fillers (e.g., Bill stood at the door. He opened it with the card.), such that across conditions, the predictability of the final word of the fillers ranged from 100% to 0%. The dependent variable was reading time on the critical region (the target word and the following word), analyzed with linear mixed-effects models in R. C-E bilinguals showed reliable prediction across all validity conditions (β = -35.6 ms, SE = 7.74, t = -4.601, p< .001), and Chinese native speakers showed significant effect (β = -93.5 ms, SE = 7.82, t = -11.956, p< .001) in two of the four validity conditions (namely, the High-validity and MedLow conditions, where fillers ended with predictable words in 100% and 25% cases respectively), whereas English native speakers didn’t predict at all (β = -2.78 ms, SE = 7.60, t = -.365, p = .715). There was neither main effect (χ^²(3) = .256, p = .968) nor interaction (Predictability: Background: Validity, χ^²(3) = 1.229, p = .746; Predictability: Validity, χ^²(3) = 2.520, p = .472; Background: Validity, χ^²(3) = 1.281, p = .734) of Validity with speaker groups. The results suggest that prediction occurs in L2 discourse processing but to a much less extent in L1, witha significant effect in some conditions of L1 Chinese and anull effect in L1 English processing, consistent with the view that L2 speakers are more sensitive to discourse cues compared with L1 speakers. Additionally, the pattern of L1 and L2 predictive processing was not affected by the global validity of predictive cues. C-E bilinguals’ predictive processing could be partly transferred from their L1, as prior research showed that discourse information played a more significant role in L1 Chinese processing.

Keywords: bilingualism, discourse processing, global validity, prediction, self-paced reading

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Authors: Murray Anderson, Galina Freed, Karli Jahn

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Trauma is increasingly recognized as an important construct that has health implications for those who struggle with various mental health issues. For those individuals who meet the criteria for a diagnosis of hoarding disorder (HD), many have experienced some form of trauma. Further, some of the therapeutic interventions for those with HD can further perpetuate or magnify the experience of trauma. Therefore, the aim of this scoping review is to identify and document the nature and extent of research evidence related to trauma as it connects with HD. This review was guided by the questions, ‘How can our understanding of the trauma cycle help us to better appreciate the experiences of individuals who hoard, and how will a trauma informed lens inform the interventions for hoarding disorder? A comprehensive literature search was performed to identify original studies that contained the words “hoarding” and “trauma.” PsychINFO”,''EBSCO host,” “CINAHL” and “PubMed” were searched between January 2005 and April 2021. Articles were screened by three reviewers. Data extracted included publication date, demographics, study design, type of analysis, and noted connections between hoarding and trauma. Of the 329 articles, all duplicates, articles on hoardings of animals, articles not in English, and those without full-text availability were removed. Five categories were found in the remaining 45 articles, including (a) traumatic and stressful life events; (b) the link between posttraumatic stress disorder, trauma, and hoarding; (c) the relationships between different comorbidities, trauma, and hoarding; (d) the lack of early emotional expression and other forms of parental deprivation; and (e) the role of attachment. Lastly, the literature explains how the links between hoarding and trauma are difficult to study due to the highly stigmatized identities with this population. The review provided strong support for the connections between the experience of trauma and HD. What is missing from the literature is the use of a trauma-informed lens to better account for the ways in which hoarding disorder is understood. Other missing pieces in the literature are the potential uses of a trauma-informed lens to enhance the therapeutic process, to understand and reduce treatment attrition, and to improve treatment outcomes. The application of a trauma informed lens could improve our understanding of effective interactions among clients, families, and communities and improve the education around hoarding-related matters. Exploring the connections between trauma and HD can improve therapeutic delivery and destigmatize the experience of dealing with clutter and hoarding concerns. This awareness can also provide health care professionals with both the language and skills to liberate them from a reductionist view on HD.

Keywords: hoarding, attachment, parental deprivation, trauma

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Authors: Fadzayi M.Maruza

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The conversation about diversity in the African academy focuses on the need for an international and ethnically diverse population of scholars and students. Operationalising the concept of cognitive diversity offers us an opportunity to broaden our conception of who can know and who can proclaim knowledge by availing new understandings of what knowledge is and how it is made. Limited attention is paid to the value of diversity generated by cognitive disabilities in the African academy. The inclusion of persons with minds labelled disabled in African academia requires an epistemology of disability to reform the still dominant notion of the expert and scholar as an able-bodied and hyper-rational in African academia. This review wants to explore how cognitive disabilities have been represented in higher education research in Africa or has the African academy reinforced ignorance by promoting an able-bodied academia. The review aims to tackle its exploratory objective by using Malcom Tights framework. The main questions this paper would focus on are: (I)What are the major disability themes and concerns discussed in the disability-related articles? (II)What are the major methods or methodologies used to address the topic in the papers? (III)What are the levels of analysis the papers focus on? (IV)How do higher education researchers define and represent cognitive disabilities in higher education research in Africa? To answer the exploratory questions that are aimed at mapping the disability-related higher education research landscape, Malcolm Tights’ framework is seen as most appropriate. In addition to a thematic categorization, that shall be made after reviewing of published empirical studies on disability in African higher education from the period 2010 – 2017. A synthesis of the findings and implications of African disability studies relating to students with cognitive disabilities in the African Academy will be provided using the categories suggested by Tight as a benchmark. Data for the proposed work shall be taken from well-reputed higher education journals between 2010 and 2017.Using the keyword ‘Disability’ in the titles, abstracts and keywords section of journal articles, a selection of disability-focused higher education articles shall be compiled for analysis regarding cognitive disability. It has to be noted as a limitation that the word Disability might not be sufficient to investigate the topic for there can be many more specific disabilities concerns the researchers would discuss. Therefore, the paper is only intended to give a bird’s eye view of cognitive disability in higher education research and therefore is not comprehensive. The paper is expected to shed some light for me, as a beginning researcher, and other researchers like myself as to what has been the focus of higher education researchers about cognitive disability in the African academy. Keywords: Cognitive diversity, cognitive disability, disability, higher education.

Keywords: cognitive disability, cognitive diversity, disability, higher education

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: A. B. Moldes, X. Vecino, L. Rodriguez-López, J. M. Dominguez, J. M. Cruz

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The concept of the circular economy is focus on the importance of providing goods and services sustainably. Thus, in a future it will be necessary to respond to the environmental contamination and to the use of renewables substrates by moving to a more restorative economic system that drives towards the utilization and revalorization of residues to obtain valuable products. During its evolution our industrial economy has hardly moved through one major characteristic, established in the early days of industrialization, based on a linear model of resource consumption. However, this industrial consumption system will not be maintained during long time. On the other hand, there are many industries, like the corn milling industry, that although does not consume high amount of non renewable substrates, they produce valuable streams that treated accurately, they could provide additional, economical and environmental, benefits by the extraction of interesting commercial renewable products, that can replace some of the substances obtained by chemical synthesis, using non renewable substrates. From this point of view, the use of streams from corn milling industry to obtain surface-active compounds will decrease the utilization of non-renewables sources for obtaining this kind of compounds, contributing to a circular and global economy. However, the success of the circular economy depends on the interest of the industrial sectors in the revalorization of their streams by developing relevant and new business models. Thus, it is necessary to invest in the research of new alternatives that reduce the consumption of non-renewable substrates. In this study is proposed the utilization of a corn milling industry stream to obtain an extract with surfactant capacity. Once the biosurfactant is extracted, the corn milling stream can be commercialized as nutritional media in biotechnological process or as animal feed supplement. Usually this stream is combined with other ingredients obtaining a product namely corn gluten feed or may be sold separately as a liquid protein source for beef and dairy feeding, or as a nutritional pellet binder. Following the productive scheme proposed in this work, the corn milling industry will obtain a biosurfactant extract that could be incorporated in its productive process replacing those chemical detergents, used in some point of its productive chain, or it could be commercialized as a new product of the corn manufacture. The biosurfactants obtained from corn milling industry could replace the chemical surfactants in many formulations, and uses, and it supposes an example of the potential that many industrial streams could offer for obtaining valuable products when they are manage properly.

Keywords: biosurfactantes, circular economy, corn, sustainability

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Authors: K. Yuki, R. Tsuji, K. Takai, S. Aramaki, R. Kibushi, N. Unno, K. Suzuki

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A small cold plate with uni-directional porous copper is proposed for cooling power electronics such as an on-vehicle inverter with the heat generation of approximately 500 W/cm2. The uni-directional porous copper with the pore perpendicularly orienting the heat transfer surface is soldered to a grooved heat transfer surface. This structure enables the cooling liquid to evaporate in the pore of the porous copper and then the vapor to discharge through the grooves. In order to minimize the cold plate, a double flow channel concept is introduced for the design of the cold plate. The cold plate consists of a base plate, a spacer, and a vapor discharging plate, totally 12 mm in thickness. The base plate has multiple nozzles of 1.0 mm in diameter for the liquid supply and 4 slits of 2.0 mm in width for vapor discharging, and is attached onto the top surface of the porous copper plate of 20 mm in diameter and 5.0 mm in thickness. The pore size is 0.36 mm and the porosity is 36 %. The cooling liquid flows into the porous copper as an impinging jet flow from the multiple nozzles, and then the vapor, which is generated in the pore, is discharged through the grooves and the vapor slits outside the cold plate. A heated test section consists of the cold plate, which was explained above, and a heat transfer copper block with 6 cartridge heaters. The cross section of the heat transfer block is reduced in order to increase the heat flux. The top surface of the block is the grooved heat transfer surface of 10 mm in diameter at which the porous copper is soldered. The grooves are fabricated like latticework, and the width and depth are 1.0 mm and 0.5 mm, respectively. By embedding three thermocouples in the cylindrical part of the heat transfer block, the temperature of the heat transfer surface ant the heat flux are extrapolated in a steady state. In this experiment, the flow rate is 0.5 L/min and the flow velocity at each nozzle is 0.27 m/s. The liquid inlet temperature is 60 °C. The experimental results prove that, in a single-phase heat transfer regime, the heat transfer performance of the cold plate with the uni-directional porous copper is 2.1 times higher than that without the porous copper, though the pressure loss with the porous copper also becomes higher than that without the porous copper. As to the two-phase heat transfer regime, the critical heat flux increases by approximately 35% by introducing the uni-directional porous copper, compared with the CHF of the multiple impinging jet flow. In addition, we confirmed that these heat transfer data was much higher than that of the ordinary single impinging jet flow. These heat transfer data prove high potential of the cold plate with the uni-directional porous copper from the view point of not only the heat transfer performance but also energy saving.

Keywords: cooling, cold plate, uni-porous media, heat transfer

Procedia PDF Downloads 286

Authors: Bharti Jain, Rajeev Jain, Abuzar Kabir, Torki Zughaibi, Shweta Sharma

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Drug-facilitated crimes (DFCs) entail the use of a single drug or a mixture of drugs to render a victim unable. Traditionally, biological samples have been gathered from victims and conducted analysis to establish evidence of drug administration. Nevertheless, the rapid metabolism of various drugs and delays in analysis can impede the identification of such substances. For this, the present article describes a rapid, sustainable, highly efficient and miniaturized protocol for the identification and quantification of three sedative-hypnotic drugs, namely diazepam, chlordiazepoxide and ketamine in alcoholic beverages and complex food samples (cream of biscuit, flavored milk, juice, cake, tea, sweets and chocolate). The methodology involves utilizing fabric phase sorptive extraction (FPSE) to extract diazepam (DZ), chlordiazepoxide (CDP), and ketamine (KET). Subsequently, the extracted samples are subjected to analysis using gas chromatography-mass spectrometry (GC-MS). Several parameters, including the type of membrane, pH, agitation time and speed, ionic strength, sample volume, elution volume and time, and type of elution solvent, were screened and thoroughly optimized. Sol-gel Carbowax 20M (CW-20M) has demonstrated the most effective extraction efficiency for the target analytes among all evaluated membranes. Under optimal conditions, the method displayed linearity within the range of 0.3–10 µg mL–¹ (or µg g–¹), exhibiting a coefficient of determination (R2) ranging from 0.996–0.999. The limits of detection (LODs) and limits of quantification (LOQs) for liquid samples range between 0.020-0.069 µg mL-¹ and 0.066-0.22 µg mL-¹, respectively. Correspondingly, the LODs for solid samples ranged from 0.056-0.090 µg g-¹, while the LOQs ranged from 0.18-0.29 µg g-¹. Notably, the method showcased better precision, with repeatability and reproducibility both below 5% and 10%, respectively. Furthermore, the FPSE-GC-MS method proved effective in determining diazepam (DZ) in forensic food samples connected to drug-facilitated crimes (DFCs). Additionally, the proposed method underwent evaluation for its whiteness using the RGB12 algorithm.

Keywords: drug facilitated crime, fabric phase sorptive extraction, food forensics, white analytical chemistry

Procedia PDF Downloads 53

Authors: Beatriz Botella-Gil, Patricio Martínez-Barco, Lea Canales

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The Internet and ICT are an integral element of and omnipresent in our daily lives. Technologies have changed the way we see the world and relate to it. The number of companies in the ICT sector is increasing every year, and there has also been an increase in the work that occurs online, from sending e-mails to the way companies promote themselves. In social life, ICT’s have gained momentum. Social networks are useful for keeping in contact with family or friends that live far away. This change in how we manage our relationships using electronic devices and social media has been experienced differently depending on the age of the person. According to currently available data, people are increasingly connected to social media and other forms of online communication. Therefore, it is no surprise that violent content has also made its way to digital media. One of the important reasons for this is the anonymity provided by social media, which causes a sense of impunity in the victim. Moreover, it is not uncommon to find derogatory comments, attacking a person’s physical appearance, hobbies, or beliefs. This is why it is necessary to develop artificial intelligence tools that allow us to keep track of violent comments that relate to violent events so that this type of violent online behavior can be deterred. The objective of our research is to create a guide for detecting and recording violent messages. Our annotation guide begins with a study on the problem of violent messages. First, we consider the characteristics that a message should contain for it to be categorized as violent. Second, the possibility of establishing different levels of aggressiveness. To download the corpus, we chose the social network Twitter for its ease of obtaining free messages. We chose two recent, highly visible violent cases that occurred in Spain. Both of them experienced a high degree of social media coverage and user comments. Our corpus has a total of 633 messages, manually tagged, according to the characteristics we considered important, such as, for example, the verbs used, the presence of exclamations or insults, and the presence of negations. We consider it necessary to create wordlists that are present in violent messages as indicators of violence, such as lists of negative verbs, insults, negative phrases. As a final step, we will use automatic learning systems to check the data obtained and the effectiveness of our guide.

Keywords: human language technologies, language modelling, offensive language detection, violent online content

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Authors: Vadim Kulikov

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The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

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Authors: S. Maleczek, K. Drabczyk, L. Bogdan, A. Iwan

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It is known that for industrial applications using solar panel constructed from silicon solar cells require high-efficiency performance. One of the main problems in solar panels is different mechanical and structural defects, causing the decrease of generated power. To analyse defects in solar cells, various techniques are used. However, the thermal imaging is fast and simple method for locating defects. The main goal of this work was to analyze defects in constructed flexible silicon photovoltaic modules via thermal imaging and electroluminescence method. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. Thermal behavior was observed using thermographic camera (VIGOcam v50, VIGO System S.A, Poland) using a DC conventional source. Electroluminescence was observed by Steinbeis Center Photovoltaics (Stuttgart, Germany) equipped with a camera, in which there is a Si-CCD, 16 Mpix detector Kodak KAF-16803type. The camera has a typical spectral response in the range 350 - 1100 nm with a maximum QE of 60 % at 550 nm. In our work commercial silicon solar cells with the size 156 × 156 mm were cut for nine parts (called single solar cells) and used to create photovoltaic modules with the size of 160 × 70 cm (containing about 80 single solar cells). Flexible silicon photovoltaic modules on polyamides or polyester fabric were constructed and investigated taking into consideration anomalies on the surface of modules. Thermal imaging provided evidence of visible voltage-activated conduction. In electro-luminescence images, two regions are noticeable: darker, where solar cell is inactive and brighter corresponding with correctly working photovoltaic cells. The electroluminescence method is non-destructive and gives greater resolution of images thereby allowing a more precise evaluation of microcracks of solar cell after lamination process. Our study showed good correlations between defects observed by thermal imaging and electroluminescence. Finally, we can conclude that the thermographic examination of large scale photovoltaic modules allows us the fast, simple and inexpensive localization of defects at the single solar cells and modules. Moreover, thermographic camera was also useful to detection electrical interconnection between single solar cells.

Keywords: electro-luminescence, flexible devices, silicon solar cells, thermal imaging

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Authors: Prasanta Saini, Junaid Jibran Jawed, Subrata Majumdar

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Infections caused by soil-transmitted helminths (STH) are the major problem in all the nations of the world. The major focus of STH research is to study the prevalence of three major helminths, such as Ascaris, Trituris and hookworm. Here we are reporting the prevalence and intensity of the STH in the school children of the state of Uttar Pradesh, India. The aim of the study is to assess the prevalence and risk factors of STH infection among the school children, aged between 5-10 years in 27 districts randomly selected districts with covering nine agro-climatic zones of Uttar Pradesh, India. For this cross-sectional survey, we have selected the populations of government primary school going children in Uttar Pradesh. The sampling was performed in the nine different agro-climatic zones. Every individual of the study populations filled their daily information in the questioner's form and then the sample was collected and processed by kato-katz methods by following the guidelines of WHO. In this method, the sampling was performed in total of 6421 populations. A total of 6,421 children from 130 schools were surveyed. Infection with any soil-transmitted helminths was detected among 4,578 children with an overall prevalence of 75.6% (95% CI: 65.3-83.6). Among the 6421 population, the prevalence of Ascaris is 69.6% (95% CL 57.97-79.11), hookworm is 22.7% (95%CL 19.3-26.3) and Trichuris sp is 4.6% (95% CL 0.8-21.6), so the predicted prevalence map indicates that the STH infection was hyperendemic in this state. The findings of our survey in 130 schools covering 9 agro-climatic with one or more soil transmitted helminths. Majority of STH infections were of light intensity. STH infection was hyper-endemic in entire state, except three zones in western Uttar Pradesh. High prevalence ( > 75%) in all age groups also indicate little impact of existing deworming initiatives, including those among pre-school aged children. WHO recommends annual treatment in areas where STH prevalence is between 20% and 50%, and, a bi-annual treatment in areas with prevalence rates of over 50%. In view of high prevalence of STH infection in Uttar Pradesh, it is strongly recommended to initiate a deworming programme for school children in the state. Although our survey was among primary school children, high prevalence among children aged 4-6 years also indicates the need to strengthen the existing deworming programs for pre-school children. Extending the benefits of deworming to pre-school children through deworming in Anganwadi schools would further reduce to decrease the load of infection in community. As a long-term solution for control STH infection, it is also necessary to improve the sanitation levels in the area, as majority of the houses did not have latrines and most of the children were defecating in open fields, a factor that was found to be significantly associated with STH infection.

Keywords: prevalence, school going children, soil transmitted helminthes, Uttar Pradesh-India

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Authors: Michelann Parr

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Family-school-community engagement enhances family-school-community well-being, collective confidence, and school climate. While it is often referred to as a positive thing in the literature for families, schools, and communities, it does not come without its struggles. While there are numerous things families, schools, and communities do each and every day to enhance engagement, it is often difficult to find our way to true belonging and engagement. Working our way surface level barriers is easy; we can provide childcare, transportation, resources, and refreshments. We can even change the environment so that families will feel welcome, valued, and respected. But there are often mindsets and perpsectives buried deep below the surface, most often grounded in societal, familial, and political norms, expectations, pressures, and narratives. This work requires ongoing energy, commitment, and engagement of all stakeholders, including families, schools, and communities. Each and every day, we need to take a reflective and introspective stance at what is said and done and how it supports the overall goal of family-school-community engagement. And whatever we must occur within a paradigm of care in additional to one of critical thinking and social justice. Families, and those working with families, must not simply accept all that is given, but should instead ask these types of questions: a) How, and by whom, are the current philosophies and practices of family-school engagement interrogated? b) How might digging below surface level meanings support understanding of what is being said and done? c) How can we move toward meaningful and authentic engagement that balances knowledge and power between family, school, district, community (local and global), and government? This type of work requires conscious attention and intentional decision-making at all levels bringing us one step closer to authentic and meaningful partnerships. Strategies useful to building a growth mindset include: a) interrogating and exploring consistencies and inconsistencies by looking at what is done and what is not done through multiple perspectives; b) recognizing that enhancing family-engagement and changing mindsets take place at the micro-level (e.g., family and school), but also require active engagement and awareness at the macro-level (e.g., community agencies, district school boards, government); c) taking action as an advocate or activist. Negative narratives about families, schools, and communities should not be maintained, but instead critical and courageous conversations in and out of school should be initiated and sustained; and d) maintaining consistency, simplicity, and steady progress. All involved in engagement need to be aware of the struggles, but keep them in check with the many successes. Change may not be observed on a day-to-day basis or even immediately, but stepping back and looking from the outside in, might change the view. Working toward a growth mindset will produce better results than a fixed mindset, and this takes time.

Keywords: family engagment, family-school-community engagement, parent engagement, parent involvment

Procedia PDF Downloads 173

Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Iryna Biskub

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The interdisciplinary approach to modern linguistic studies is exemplified by the merge of various research methods, which sometimes causes complications related to the verification of the research results. This methodological confusion can be resolved by means of creating new techniques of linguistic analysis combining several scientific paradigms. Modern linguistics has developed really productive and efficient methods for the investigation of cognitive and communicative phenomena of which language is the central issue. In the field of discourse studies, one of the best examples of research methods is the method of Critical Discourse Analysis (CDA). CDA can be viewed both as a method of investigation, as well as a critical multidisciplinary perspective. In CDA the position of the scholar is crucial from the point of view exemplifying his or her social and political convictions. The generally accepted approach to obtaining scientifically reliable results is to use a special well-defined scientific method for researching special types of language phenomena: cognitive methods applied to the exploration of cognitive aspects of language, whereas communicative methods are thought to be relevant only for the investigation of communicative nature of language. In the recent decades discourse as a sociocultural phenomenon has been the focus of careful linguistic research. The very concept of discourse represents an integral unity of cognitive and communicative aspects of human verbal activity. Since a human being is never able to discriminate between cognitive and communicative planes of discourse communication, it doesn’t make much sense to apply cognitive and communicative methods of research taken in isolation. It is possible to modify the classical CDA procedure by means of mapping human cognitive procedures onto the strategic communicative planning of discourse communication. The analysis of the electronic petition 'Block Donald J Trump from UK entry. The signatories believe Donald J Trump should be banned from UK entry' (584, 459 signatures) and the parliamentary debates on it has demonstrated the ability to map cognitive and communicative levels in the following way: the strategy of discourse modeling (communicative level) overlaps with the extraction of semantic macrostructures (cognitive level); the strategy of discourse management overlaps with the analysis of local meanings in discourse communication; the strategy of cognitive monitoring of the discourse overlaps with the formation of attitudes and ideologies at the cognitive level. Thus, the experimental data have shown that it is possible to develop a new complex methodology of discourse analysis, where cognition would meet communication, both metaphorically and literally. The same approach may appear to be productive for the creation of computational models of human-computer interaction, where the automatic generation of a particular type of a discourse could be based on the rules of strategic planning involving cognitive models of CDA.

Keywords: cognition, communication, discourse, strategy

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Authors: Shilpa Avarebeel

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Background: India is one of the seven identified countries in South-East Asia region, regularly reporting dengue infection and may soon transform into a major niche for dengue epidemics. Objective: To study the clinical profile of dengue in our setting with special reference to respiratory complication. Study design: Descriptive and exploratory study, for one year in 2014. All patients confirmed as dengue infection were followed and their clinical profile, along with outcome was determined. Study proforma was designed based on the objective of the study and it was pretested and used after modification. Data was analyzed using statistical software SPSS-Version 16. Data were expressed as mean ±S .D for parametric variables and actual frequencies or percentage for non-parametric data. Comparison between groups was done using students’ t-test for independent groups, Chie square test, one-way ANOVA test, Karl Pearson’s correlation test. Statistical significance is taken at P < 0.05. Results: Study included 134 dengue positive cases. 81% had dengue fever, 18% had dengue hemorrhagic fever, and one had dengue shock syndrome. Most of the cases reported were during the month of June. Maximum number of cases was in the age group of 26-35 years. Average duration of hospital stay was less than seven days. Fever and myalgia was present in all the 134 patients, 16 had bleeding manifestation. 38 had respiratory symptoms, 24 had breathlessness, and 14 had breathlessness and dry cough. On clinical examination of patients with respiratory symptoms, all twenty-eight had hypoxia features, twenty-four had signs of pleural effusion, and four had ARDS features. Chest x-ray confirmed the same. Among the patients with respiratory symptoms, the mean platelet count was 26,537 c/cmm. There was no statistical significant difference in the platelet count in those with ARDS and other dengue complications. Average four units of platelets were transfused to all those who had ARDS in view of bleeding tendency. Mechanical ventilator support was provided for ARDS patients. Those with pleural effusion and pulmonary oedema were given NIV (non-invasive ventilation) support along with supportive care. However, steroids were given to patients with ARDS and 10 patients with signs of respiratory distress. 100%. Mortality was seen in patients with ARDS. Conclusion: Dengue has to be checked for those presenting with fever and breathlessness. Supportive treatments remain the cornerstone of treatment. Platelet transfusion has to be given only by clinical judgment. Steroids have no role except in early ARDS, which is controversial. Early NIV support helps in speedy recovery of dengue patients with respiratory distress.

Keywords: adult respiratory distress syndrome, dengue fever, non-invasive ventilation, pulmonary complication

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: A. O. Glazkov, A. S. Krylova, G. G. Nadareishvili, A. S. Terenchenko, S. I. Yudin

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The topic of the presented materials concerns the design of the exhaust system for a certain internal combustion engine. The exhaust system can be divided into two parts. The first is the engine exhaust manifold, turbocharger, and catalytic converters, which are called “hot part.” The second part is the gas exhaust system, which contains elements exclusively for reducing exhaust noise (mufflers, resonators), the accepted designation of which is the "cold part." The design of the exhaust system from the point of view of acoustics, that is, reducing the exhaust noise to a predetermined level, consists of working on the second part. Modern computer technology and software make it possible to design "cold part" with high accuracy in a given frequency range but with the condition of accurately specifying the input parameters, namely, the amplitude spectrum of the input noise and the acoustic impedance of the noise source in the form of an engine with a "hot part". Getting this data is a difficult problem: high temperatures, high exhaust gas velocities (turbulent flows), and high sound pressure levels (non-linearity mode) do not allow the calculated results to be applied with sufficient accuracy. The aim of this work is to obtain the most reliable acoustic output parameters of an engine with a "hot part" based on a complex of computational and experimental studies. The presented methodology includes several parts. The first part is a finite element simulation of the "cold part" of the exhaust system (taking into account the acoustic impedance of radiation of outlet pipe into open space) with the result in the form of the input impedance of "cold part". The second part is a finite element simulation of the "hot part" of the exhaust system (taking into account acoustic characteristics of catalytic units and geometry of turbocharger) with the result in the form of the input impedance of the "hot part". The next third part of the technique consists of the mathematical processing of the results according to the proposed formula for the convergence of the mathematical series of summation of multiple reflections of the acoustic signal "cold part" - "hot part". This is followed by conducting a set of tests on an engine stand with two high-temperature pressure sensors measuring pulsations in the nozzle between "hot part" and "cold part" of the exhaust system and subsequent processing of test results according to a well-known technique in order to separate the "incident" and "reflected" waves. The final stage consists of the mathematical processing of all calculated and experimental data to obtain a result in the form of a spectrum of the amplitude of the engine noise and its acoustic impedance.

Keywords: acoustic impedance, engine exhaust system, FEM model, test stand

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Somnath Mukhuti, Prem Kumar Ghosh

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Background and significance of the study Indian stock market has undergone sudden changes after the current China crisis in terms of turnover, market capitalization, share prices, etc. The average returns on equity investment in both markets have more than three and half times after global financial crisis owing to the development of industrial activity, corporate sectors development, enhancement in global consumption, change of global financial association and fewer imports from developed countries. But the economic policies of both the economies are far different, that is to say, where Indian economy maintaining a conservative policy, Chinese economy maintaining an aggressive policy. Besides this, Chinese economy recently lowering its currency for increasing mysterious growth but Indian does not. But on August 24, 2015 Indian stock market and world stock markets were fall down due to the reason of Chinese stock market. Keeping in view of the above, this study seeks to examine the influence of Chinese stock on Indian stock market. Methodology This research work is based on daily time series data obtained from yahoo finance database between 2009 (April 1) to 2015 (September 28). This study is based on two important stock markets, that is, Indian stock market (Bombay Stock Exchange) and Chinese stock market (Shanghai Stock Exchange). In the course of analysis, the daily raw data were converted into natural logarithm for minimizing the problem of heteroskedasticity. While tackling the issue, correlation statistics, ADF and PP unit root test, bivariate cointegration test and causality test were used. Major findings Correlation statistics show that both stock markets are associated positively. Both ADF and PP unit root test results demonstrate that the time series data were not normal and were not stationary at level however stationary at 1st difference. The bivariate cointegration test results indicate that the Indian stock market was associated with Chinese stock market in the long-run. The Granger causality test illustrates there was a unidirectional causality between Indian stock market and Chinese stock market. Concluding statement The empirical results recommend that India’s stock market was not very much dependent on Chinese stock market because of Indian economic conservative policies. Nevertheless, Indian stock market might be sturdy if Indian economic policies are changed slightly and if increases the portfolio investment with Chinese economy. Indian economy might be a third largest economy in 2030 if India increases its portfolio investment and trade relations with both Chinese economy and US economy.

Keywords: Indian stock market, China stock market, bivariate cointegration, causality test

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Authors: Stephanie Lehmann, Esther Ruf, Sabina Misoch

Abstract:

Background: Due to demographic change and shortage of skilled nursing staff, assistive robots are built to support older adults at home and nursing staff in care institutions. When assistive robots facilitate tasks that are usually performed by humans, user acceptance is essential. Even though they are an important aspect of acceptance, emotions towards different assistive robots and different situations of robot-use have so far not been examined in detail. The appearance of assistive robots can trigger emotions that affect their acceptance. Acceptance of robots is assumed to be greater when they look more human-like; however, too much human similarity can be counterproductive. Regarding different groups, it is assumed that older adults have a more negative attitude towards robots than younger adults. Within the framework of a simulated robot study, the aim was to investigate emotions of older adults compared to students towards robots with different appearances and in different situations and so contribute to a deeper view of the emotions influencing acceptance. Methods: In a questionnaire study, vignettes were used to assess emotions toward robots in different situations and of different appearance. The vignettes were composed of two situations (service and care) shown by video and four pictures of robots varying in human similarity (machine-like to android). The combination of the vignettes was randomly distributed to the participants. One hundred forty-two older adults and 35 bachelor students of nursing participated. They filled out a questionnaire that surveyed 30 positive and 30 negative emotions. For each group, older adults and students, a sum score of “positive emotions” and a sum score of “negative emotions” was calculated. Mean value, standard deviation, or n for sample size and % for frequencies, according to the scale level, were calculated. For differences in the scores of positive and negative emotions for different situations, t-tests were calculated. Results: Overall, older adults reported significantly more positive emotions than students towards robots in general. Students reported significantly more negative emotions than older adults. Regarding the two different situations, the results were similar for the care situation, with older adults reporting more positive emotions than students and less negative emotions than students. In the service situation, older adults reported significantly more positive emotions; negative emotions did not differ significantly from the students. Regarding the appearance of the robot, there were no significant differences in emotions reported towards the machine-like, the mechanical-human-like and the human-like appearance. Regarding the android robot, students reported significantly more negative emotions than older adults. Conclusion: There were differences in the emotions reported by older adults compared to students. Older adults reported more positive emotions, and students reported more negative emotions towards robots in different situations and with different appearances. It can be assumed that older adults have a different attitude towards the use of robots than younger people, especially young adults in the health sector. Therefore, the use of robots in the service or care sector should not be rejected rashly based on the attitudes of younger persons, without considering the attitudes of older adults equally.

Keywords: emotions, robots, seniors, young adults

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Authors: Blessings Masuku

Abstract:

This study positions itself within the nascent of street food vending that plays a crucial role in addressing urban household food security across the urban landscape of South Africa. The study aimed to understand how various forms of infrastructure systems (i.e., energy, water and sanitation, housing, and transport, among others) intersect with food and urban informality and how vendors and households’ choices and decisions made around food are influenced by infrastructure assemblages. This study noted that most of the literature studies on food security have mainly focused on the rural agricultural sector, with limited attention to urban food security, notably the role of informality practices in addressing urban food insecurity at the household level. This study pays close attention to how informal informality practices such as street food vending can be used as a catalyst to address urban poverty and household food security and steer local economies for sustainable livelihoods of the urban poor who live in the periphery of the city in Johannesburg. This study deconstructs the infrastructure needs of street food vendors, and the aim was to understand how such infrastructure needs intersect with food and policy that governs urban informality practices. The study argues that the decisions and choices of informality actors in the city of Johannesburg are chiefly determined by the assemblages of infrastructure, including regulatory frameworks that govern the informal sector in the city of Johannesburg. A qualitative approach that includes surveys (open-ended questions), archival research (i., e policy and other key document reviews), and key interviews mainly with city officials and informality actors. A thematic analysis was used to analyze the data collected. This study contributes to greater debates on urban studies and burgeoning literature on urban food security in many ways that include Firstly, the pivotal role that the informal food sector, notably street food vending, plays within the urban economy to address urban poverty and household food security, therefore questioning the conservative perspectives that view the informal sector as a hindrance to a ‘modern city’ and an annoyance to ‘modern’ urban spaces. Secondly, this study contributes to the livelihood and coping strategies of the urban poor who, despite harsh and restrictive regulatory frameworks, devise various agentive ways to generate incomes and address urban poverty and food insecurities.

Keywords: urban food security, street food vending, informal food sector, infrastructure systems, livelihood strategies, policy framework and governance

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