Search results for: semantic library

Authors: Afaf Manzoor, Abdul Hameed

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Children with hearing impairment face several challenges in accessing primary and secondary education in general and higher education in particular in Pakistan. A large number of these children are excluded from formal education system through segregated special institutions. The enrollment rate of these children at school level is very low and it continues decreasing as they move on the ladder of education. Negligible number of students with hearing impairment gets any chance to be enrolled at tertiary or higher education institutes. The segregated system of education at primary and secondary level makes it even more difficult to adjust in an inclusive classroom at a higher level not only for students with hearing impairment but for their teachers and peers as well. A false belief of teachers and parents about low academic profile of students with hearing impairment is one of the major challenges to overcome for their participation at higher education. This case study was conducted to document an innovative step taken by the Department of Special Education Needs, University of Management & Technology, Lahore Pakistan. The prime objective of this study was to assess the satisfaction level of students with hearing impairment in BS 4 Years and MA Special Education programs at Lahore campus. Structured interviews were of 40 students with hearing impairment to assess the satisfaction on service delivery (admission process, classroom pedagogy, content, assessment/results, access to other services centers i.e. library, cafeteria, hostel, co-curricular activities) and campus life. Their peers without disabilities were also interviewed to assess their acceptance level. The findings of the study revealed positive results about their educational as well as social inclusion in the university. The students also shared their fears at the time of admission and how fear eventually faded out with the passage of time due to the proper academic support system. The findings of the study will be shared in detail with the audience during the presentation.

Keywords: students with hearing impairment, higher education, inclusive education, marginalization

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Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

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The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

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Authors: Sathyaseelan Subramaniam, Jacqueline Bober, Jennifer Chao, Shahriar Zehtabchi

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Background: Emergency physicians frequently evaluate skin and soft tissue infections in order to differentiate abscess from cellulitis. This helps determine which patients will benefit from incision and drainage. Our objective was to determine the operating characteristics of point-of-care ultrasound (POCUS) compared to clinical examination in identifying abscesses in emergency department (ED) patients with features of skin and soft tissue infections. Methods: We performed a comprehensive search in the following databases: Medline, Web of Science, EMBASE, CINAHL and Cochrane Library. Trials were included if they compared the operating characteristics of POCUS with clinical examination in identifying skin and soft tissue abscesses. Trials that included patients with oropharyngeal abscesses or that requiring abscess drainage in the operating room were excluded. The presence of an abscess was determined by pus drainage. No pus seen on incision or resolution of symptoms without pus drainage at follow up, determined the absence of an abscess. Quality of included trials was assessed using GRADE criteria. Operating characteristics of POCUS are reported as sensitivity, specificity, positive likelihood (LR+) and negative likelihood (LR-) ratios and the respective 95% confidence intervals (CI). Summary measures were calculated by generating a hierarchical summary receiver operating characteristic model (HSROC). Results: Out of 3203 references identified, 5 observational studies with 615 patients in aggregate were included (2 adults and 3 pediatrics). We rated the quality of 3 trials as low and 2 as very low. The operating characteristics of POCUS and clinical examination in identifying soft tissue abscesses are presented in the table. The HSROC for POCUS revealed a sensitivity of 96% (95% CI = 89-98%), specificity of 79% (95% CI = 71-86), LR+ of 4.6 (95% CI = 3.2-6.8), and LR- of 0.06 (95% CI = 0.02-0.2). Conclusion: Existing evidence indicates that POCUS is useful in identifying abscesses in ED patients with skin or soft tissue infections.

Keywords: abscess, point-of-care ultrasound, pocus, skin and soft tissue infection

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Authors: M. Ahmadi, Sh. Damanabi, F. Sadoughi

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National Health Information System plays an important role in ensuring timely and reliable access to Health information which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, by using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system for better planning and management influential factors of performance seems necessary, therefore, in this study, different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process, and output. In this context, search for information using library resources and internet search were conducted and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system, Lippeveld, Sauerborn, and Bodart Model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008 and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities, and equipment. In addition, in the ‘process’ section from three models, we pointed up the actions ensuring the quality of health information system and in output section, except Lippeveld Model, two other models consider information products, usage and distribution of information as components of the national health information system. Conclusion: The results showed that all the three models have had a brief discussion about the components of health information in input section. However, Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process, and output.

Keywords: National Health Information System, components of the NHIS, Lippeveld Model

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Authors: Ruichong Zhang, Fadi Sawaged, Lotfi Gargab

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This paper introduces a wave-based approach for system identification of high-rise building structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response functions (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings, and GIRF is then found with the inverse Fourier transformation of GFRF. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found in terms of wave transmission and reflection coefficients, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002. The building is modelled as piecewise continuous layers, with which GFRF is derived as function of such building parameters as impedance, cross-sectional area, and damping. GIRF can then be found in closed form for some special cases and numerically in general. Not only does this study reveal the influential factors of building parameters in wave features of GIRF and GRFR, it also shows some system-identification results, which are consistent with other vibration- and wave-based results. Finally, this paper discusses the effectiveness of the proposed model in system identification.

Keywords: wave-based approach, seismic responses of buildings, wave propagation in structures, construction

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Authors: Stefanache Stefania, Ioana R. Podina

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Background: Embodied Conversational Agents (ECAs) are revolutionizing education and healthcare by offering cost-effective, adaptable, and portable solutions. Research on the Uncanny Valley effect (UVE) involves various embodied agents, including ECAs. Achieving the optimal level of anthropomorphism, no consensus on how to overcome the uncanniness problem. Objectives: This systematic review aims to identify the user characteristics, agent features, and context factors that influence the UVE. Additionally, this review provides recommendations for creating effective ECAs and conducting proper experimental studies. Methods: We conducted a systematic review following the PRISMA 2020 guidelines. We included quantitative, peer-reviewed studies that examined human-ECA interaction. We identified 17,122 relevant records from ACM Digital Library, IEE Explore, Scopus, ProQuest, and Web of Science. The quality of the predictors, mediators, and moderators adheres to the guidelines set by prior systematic reviews. Results: Based on the included studies, it can be concluded that females and younger people perceive the ECA as more attractive. However, inconsistent findings exist in the literature. ECAs characterized by extraversion, emotional stability, and agreeableness are considered more attractive. Facial expressions also play a role in the UVE, with some studies indicating that ECAs with more facial expressions are considered more attractive, although this effect is not consistent across all studies. Few studies have explored contextual factors, but they are nonetheless crucial. The interaction scenario and exposure time are important circumstances in human-ECA interaction. Conclusions: The findings highlight a growing interest in ECAs, which have seen significant developments in recent years. Given this evolving landscape, investigating the risk of the UVE can be a promising line of research.

Keywords: human-computer interaction, uncanny valley effect, embodied conversational agent, systematic review

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Authors: Van Truong Pham

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Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

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Authors: Beatrice Fenu, Francesco Niosi, Giovanni Bracco, Giuliana Mattiazzo

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In recent years, Europe has seen a great development of renewable energy, in a perspective of reducing polluting emissions and transitioning to cleaner forms of energy, as established by the European Green New Deal. Wind energy has come to cover almost 15% of European electricity needs andis constantly growing. In particular, far-offshore wind turbines are attractive from the point of view of exploiting high-speed winds and high wind availability. Considering offshore wind turbine siting that combines the resources analysis, the bathymetry, environmental regulations, and maritime traffic and considering the waves influence in the stability of the platform, the hydrodynamic characteristics of the platform become fundamental for the evaluation of the performances of the turbine, especially for the pitch motion. Many platform's geometries have been studied and used in the last few years. Their concept is based upon different considerations as hydrostatic stability, material, cost and mooring system. A new method to reach a high-performances substructure for different kinds of wind turbines is proposed. The system that considers substructure, mooring, and wind turbine is implemented in Orcaflex, and the simulations are performed considering several sea states and wind speeds. An external dynamic library is implemented for the turbine control system. The study shows the comparison among different substructures and the new concepts developed. In order to validate the model, CFD simulations will be performed by mean of STAR CCM+, and a comparison between rigid and elastic body for what concerns blades and tower will be carried out. A global model will be built to predict the productivity of the floating turbine according to siting, resources, substructure, and mooring. The Levelized Cost of Electricity (LCOE) of the system is estimated, giving a complete overview about the advantages of floating offshore wind turbine plants. Different case studies will be presented.

Keywords: aero-hydrodynamic model, computational fluid dynamics, floating offshore wind, siting, verification, and validation

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Authors: Miriam Fahmy, Shalini Fernando

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Educational links between teaching hospitals and universities can provide visits with great impact for both sides. As a visitor, one is responsible for the content, respecting current practice while offering guidance from a completely different perspective. There is little documented guidance for establishing links with universities in developing countries and providing meaningful teaching and exchange programmes. An initial contact retrieved one response with regards to written curriculum. The otolaryngology department from a Swansea teaching hospital visited a university in the Gambia. A consultant and clinical fellow visited with medical students to deliver lectures, clinical skills and informal teaching such as bedside and small group teaching. Students who had participated in teaching provided by the visiting university were asked to give feedback. This information was collated and used to evaluate the impact, and to guide future visits, including thinking of establishing a curriculum tailored to the West Africa region. The students felt they gained the most from informal sessions such as bedside teaching and felt that more practical experience on real patients and pathology would be most beneficial to them. Given that internet is poor, they also suggested a video library for their reference. Many of them look forward to visiting Swansea and are interested in the differences in practice and technologies. The findings are limited to little previous literature and student feedback. Student feedback sparked further questions and careful contemplation. There is great scope for introducing a range of teaching resources but it is important to avoid assumptions and imposition of a western curriculum and education system, a larger sample is needed with input from lecturers and curriculum writers in leading universities. In conclusion, more literature and guidance needs to be established for future visitors contemplating an educational link.

Keywords: education, impact, West Africa, university links

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Authors: Olga Giovani

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In this research, Bronfenbrenner's theory will be used to investigate the individual, microsystemic, and exosystemic factors that may affect adolescents' academic achievement as well as their expectations in Greece. First, the topic of academic achievement in an adolescent developmental context will be set as the target of the proposed study while focusing on the aspects of community influences on adolescents. More specifically, the effect of available resources and the perceived sense of safety and support will be further investigated. Then the issue of family factors will be analyzed, as they are subjectively perceived by the adolescents, focusing on the perceived parental style, parental monitor, and involvement as a mesosystemic factor. In turn, the school will also be discussed with emphasis on the perceived school climate and support as well as the academic aspects of student achievement. Finally, the adolescent's individual perspective will be taken into consideration in developmental terms, examining their perceptions regarding their community/neighborhood, their family, their school, as well as their sense of self-concept and self-esteem as these are expressed through their academic performance and prosocial behavior. The aim of the proposed research is to study these associations through the prism of the systemic perspective, the relationship between aspects of educational achievement and socioeconomic background, with an emphasis on the role of the community, which has not been adequately researched in the Greek context. Community will be defined by the available community resources (recreational activities, public library, local orchestras, free entrance museums, etc.), adolescents' own perception of social support, safety, and support inside that community. These perceptions need to be investigated since they may serve as possible predictors of a child's current cognitive, developmental, and psycho-social outcomes, such as their perceived self-concept and self-esteem, as well as on their future expectations related to the entrance to university and job expectations.

Keywords: bioecological model, developmental psychology, ecosystemic approach, student achievement, microsystemic factors, mesosystemic factors, individual perceptions

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

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Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Gubair Tarabeh, Ghadir Zriek, David Oppenheim, Avi Sagi-Schwartz, Nina Koren-Karie

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Introduction: Mind-Mindedness (MM) focuses on mothers' attunement to their infant's mental states as reflected in their speech to the infant. Appropriate MM comments are associated with attachment security in individualistic Western societies where parents value their children’s autonomy and independence, and may therefore be more likely to engage in mind-related discourse with their children that highlights individual thoughts, preferences, emotions, and motivations. Such discourse may begin in early infancy, even before infants are likely to understand the semantic meaning of parental speech. Parents in collectivistic societies, by contrast, are thought to emphasize conforming to social norms more than individual goals, and this may lead to parent-child discourse that emphasizes appropriate behavior and compliance with social norms rather than internal mental states of the self and the other. Therefore, the examination of maternal MM and its relationship with attachment in Arab collectivistic culture in Israel was of particular interest. Aims of the study: The goal of the study was to examine whether the associations between MM and attachment in the Arab culture in Israel are the same as in Western samples. An additional goal was to examine whether appropriate and non-attuned MM comments could, together, distinguish among mothers of children in the different attachment classifications. Material and Methods: 76 Arab mothers and their infants between the ages of 12 and 18 months were observed in the Strange Situation Procedure (49 secure (B), 11 ambivalent (C), 14 disorganized (D), and 2 avoidant (A) infants). MM was coded from an 8-minute free-play sequence. Results: Mothers of B infants used more appropriate and less non-attuned MM comments than mothers of D infants, with no significant differences with mothers of C infants. Also, mothers of B infants used less non-attuned MM comments than both mothers of D infants and mothers of C infants. In addition, Mothers of B infants were most likely to show the combination of high appropriate and low non-attuned MM comments; Mothers of D infants were most likely to show the combination of high non-attuned and low appropriate MM comments; and a non-significant trend indicated that mothers of C infants were most likely to show a combination of high appropriate and high non-attuned MM comments. Conclusion: Maternal MM was associated with attachment in the Arab culture in Israel with combinations of appropriate and non-attuned MM comments distinguishing between different attachment classifications.

Keywords: attachment, maternal mind-mindedness, Arab culture, collectivistic culture

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Authors: Doua AlSaad, Ahmed Awaisu, Samah Elsalem, Palli Valapila Abdulrouf, Binny Thomas, Moza AlHail

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Background: It has been suggested that pyridoxine has an anti-lactogenic effect. Studies of the efficacy of pyridoxine in suppressing lactation have reported conflicting results. The aim of this review is to evaluate the effectiveness and safety of high-dose pyridoxine in postpartum lactation inhibition. Methods: This systematic review included published trials that compared the efficacy and/or safety of pyridoxine to placebo or to other pharmacological agents for the inhibition of postpartum lactation. We searched PubMed, Embase, ScienceDirect, CINAHL, AMED, the Cochrane library, and the clinical trials registry to identify relevant literature. No limit was imposed on the year of publication of the studies, and the review included studies published until 15 January 2016. Two reviewers independently extracted data and assessed the risk of bias. Results: Seven studies were included, with a total of 1155 women, of which 471 women received pyridoxine. Three studies were randomized controlled trials, while the remaining four studies were non-randomized controlled trials. All of the included studies were relatively small (n = 18 – 482). The studies compared pyridoxine with placebo, bromocriptine, and/or stilboestrol. Pyridoxine was given orally, with a total daily dose of 450 – 600 mg for 5 to 7 days. Two trials (n = 349 participants) indicated that pyridoxine was effective in inhibiting lactation in approximately 95% of the enrolled patients. All other studies failed to demonstrate pyridoxine efficacy through either clinical assessment or prolactin level measurements. Pyridoxine safety was assessed by two trials in which no serious untoward side-effects were reported. Overall, the risk of bias for most of the studies was low to moderate. Conclusion: Current evidence supporting the effectiveness of high dose pyridoxine in the inhibition of postpartum lactation is inconsistent and insufficient. Larger randomized trials are needed to confirm the efficacy of pyridoxine in postpartum lactation inhibition. Acknowledgment: This review received a grant from the Medical Research Center of Hamad Medical Corporation in Qatar (grant number: 15100/15).

Keywords: pyridoxine, safety, effectiveness, lactation inhibition

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Authors: Remya Radhakrishnan, Hema Perinbanathan, Anukriti Rath, Reshmi Ramachandran, Rohith Thazhathuvetil Sasindrababu, Maria Karizhenskaia

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Childhood adversities have lasting effects on health and well-being. This abstract explores the connection between adverse childhood experiences (ACEs) and health consequences, including substance abuse and obesity. Understanding the impact of childhood trauma and emphasizing the importance of culturally sensitive treatments and focused interventions help to mitigate these effects. Research consistently shows a strong link between ACEs and poor health outcomes. Our team conducted a comprehensive literature review of depression and anxiety in Canadian children and youth, exploring diverse treatment methods, including medical, psychotherapy, and alternative therapies like art and music therapy. We searched Medline, Google Scholar, and St. Lawrence College Library. Only original research papers, published between 2012 and 2023, peer-reviewed, and reporting on childhood adversities on health and its treatment methods in children and youth in Canada were considered. We focused on their significance in treating depression and anxiety. According to the study's findings, the prevalence of adverse childhood experiences (ACEs) is still a significant concern. In Canada, 40% of people report having had multiple ACEs, and 78% report having had at least one ACE, highlighting the persistence of childhood adversity and indicating that the issue is unlikely to fade off in the near future. Likewise, findings revealed that individuals who experienced abuse, neglect, or violence during childhood are likelier to engage in harmful behaviors like polydrug use, suicidal ideation, and victimization and suffer from mental health problems such as depression and post-traumatic stress disorder (PTSD).

Keywords: adverse childhood experiences (ACEs), obesity, post-traumatic stress disorder (PTSD), resilience, substance abuse, trauma-informed care

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Authors: Małgorzata Osowiecka

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Negative emotions are rather seen as creativity inhibitor. On the other hand, it is worth noting that negative emotions may be good for our functioning. Negative emotions enhance cognitive resources and improve evaluative processes. Moreover maintaining a negative emotional state allow for cognitive reinterpretation of the emotional stimuli, what is good for our creativity, especially cognitive flexibility. Writing a diary or writing about difficult emotional experiences in general can be the way to not only improve psychical health, but also – enhance creative behaviors. Thanks to translating difficult emotions to the verbal level and giving them ‘a name’ or ‘a label’, we can get easier access to both emotional content of an experience and to the semantic content, without the need of speaking out loud. Expressive writing improves academic results and the efficiency of working memory. The classical method of writing about emotions consists in a long-term process of describing negative experiences. Present research demonstrate the efficiency of this process over a shorter period of time - one writing session, on school children sample. Participants performed writing task. Writing task had two different topics: emotions connected with their negative emotions (expressive writing) and content not connected with negative emotional state (writing about one’s typical day). Creativity was measured by Guilford’s Alternative Uses Task. Results have shown that writing about negative emotions results in the higher level of divergent thinking in all three parameters: fluency, flexibility and originality. After the writing task mood of expressive writing participants remained negative more than the mood of the controls. Taking an expressive action after a difficult emotional experience can support functioning, which can be observed in enhancement of divergent thinking. Writing about emotions connected with negative experience makes one more creative, than writing about something unrelated with difficult emotional moments. Research has shown that young people should not demonize negative emotions. Sometimes, properly applied, negative emotions can be the basis of creation. Preparation was supported by a The Young Scientist University grant titled ‘Dynamics of emotions in the creative process’ from The Polish Ministry of Science and Higher Education.

Keywords: creativity, divergent thinking, emotions, expressive writing

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

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Authors: Jéssica Ferreira Rodrigues, Júlio Silvio De Sousa Bueno Filho, Vanessa Rios De Souza, Ana Carla Marques Pinheiro

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This study aimed to evaluate the implications of the block size and testing order on efficiency and precision of preference estimation for Dulce de leche samples. Efficiency was defined as the inverse of the average variance of pairwise comparisons among treatments. Precision was defined as the inverse of the variance of treatment means (or effects) estimates. The experiment was originally designed to test 16 treatments as a series of 8 Sudoku 16x16 designs being 4 randomized independently and 4 others in the reverse order, to yield balance in testing order. Linear mixed models were assigned to the whole experiment with 112 testers and all their grades, as well as their partially balanced subgroups, namely: a) experiment with the four initial EU; b) experiment with EU 5 to 8; c) experiment with EU 9 to 12; and b) experiment with EU 13 to 16. To record responses we used a nine-point hedonic scale, it was assumed a mixed linear model analysis with random tester and treatments effects and with fixed test order effect. Analysis of a cumulative random effects probit link model was very similar, with essentially no different conclusions and for simplicity, we present the results using Gaussian assumption. R-CRAN library lme4 and its function lmer (Fit Linear Mixed-Effects Models) was used for the mixed models and libraries Bayesthresh (default Gaussian threshold function) and ordinal with the function clmm (Cumulative Link Mixed Model) was used to check Bayesian analysis of threshold models and cumulative link probit models. It was noted that the number of samples tested in the same session can influence the acceptance level, underestimating the acceptance. However, proving a large number of samples can help to improve the samples discrimination.

Keywords: acceptance, block size, mixed linear model, testing order, testing order

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Authors: Wen Zhen

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Compared to content words, function words have been relatively overlooked by English learners especially articles. The article system, to a certain extent, becomes a resistance to know English better, driven by different elements. Three principal factors can be summarized in term of the nature of the articles when referring to the difficulty of the English article system. However, making the article system more complex are difficulties in the second acquisition process, for [-ART] learners have to create another category, causing even most non-native speakers at proficiency level to make errors. According to the sequences of acquisition of the English article, it is showed that the zero article is first acquired and in high inaccuracy. The zero article is often overused in the early stages of L2 acquisition. Although learners at the intermediate level move to underuse the zero article for they realize that the zero article does not cover any case, overproduction of the zero article even occurs among advanced L2 learners. The aim of the study is to investigate noun-phrase factors which give rise to incorrect usage or overuse of the zero article, thus providing suggestions for L2 English acquisition. Moreover, it enables teachers to carry out effective instruction that activate conscious learning of students. The research question will be answered through a corpus-based, data- driven approach to analyze the noun-phrase elements from the semantic context and countability of noun-phrases. Based on the analysis of the International Thurber Thesis corpus, the results show that: (1) Although context of [-definite,-specific] favored the zero article, both[-definite,+specific] and [+definite,-specific] showed less influence. When we reflect on the frequency order of the zero article , prototypicality plays a vital role in it .(2)EFL learners in this study have trouble classifying abstract nouns as countable. We can find that it will bring about overuse of the zero article when learners can not make clear judgements on countability altered from (+definite ) to (-definite).Once a noun is perceived as uncountable by learners, the choice would fall back on the zero article. These findings suggest that learners should be engaged in recognition of the countability of new vocabulary by explaining nouns in lexical phrases and explore more complex aspects such as analysis dependent on discourse.

Keywords: noun phrase, zero article, corpus, second language acquisition

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Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

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Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: control, milling, multibody, robotic, simulation

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Anita Chhatwal

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Purpose: The purpose of this paper is to evaluate and investigate the scope of usage of Academic Social Networking Websites (ASNs) by the Science faculty members across universities of North India, viz. Panjab University, Punjabi University and University of Delhi, Delhi. Design/Methodology/Approach: The present study is based upon the primary data collected from 81 science faculty participants from three universities of North India. Questionnaire method was used as an instrument for survey. The study is descriptive and research-based to investigate the popular ASNs amongst the participants from three sample universities and the purpose for which they use them along with the problems they encounter while using ASNs. Findings: The findings of the study revealed that majority of the participants were using ASNs for their academic needs. It was observed that majority of the participants (78%) used ASNs to access scientific papers, while 73.8% of the participants used them to share their research publications. ResearchGate (60.5%) and Google Scholar (59.7%) were the top two most preferred and widely used ASNs by the participants. The critical analysis of the data shows that laptops (86.3%) emerged as major tools for accessing ASNs. Shortage of computers was found to be the chief obstacle in accessing ASNs by the participants. Results of the study demonstrate that 56.3% of participants suggested conduct of seminars and training as the most effective method to increase the awareness of ASNs. Research Limitations/Implications: The study in hand absorbed the 81 faculty (Assistant Professors) members from 15 Science teaching departments across three sample universities of North India. The findings of this study will help the Government of India to regulate and simultaneously make effort to develop and enhance ASNs usage among faculty, researchers, and students. The present study will add to the existing library and information science literature and will be advantageous for all the information professionals as well. Originality/Value: This study is original survey based on primary data investigate the usage of ASNs by the academia. This study will be useful for research scholars, academicians and students all over the world.

Keywords: academic social networks, awareness and usage, North India, scholarly communication, web 2.0

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Authors: Ebtisam A. Al-Mslemani, Khalid A. Enan, Asmaa Abdelgadier, Nada Assaad, Zaynab Elhussein, Khalid Eltom

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Background: Toxoplasma gondii (T. gondii) is a zoonotic parasite that can be transmitted from animals to humans, with felids acting as its definitive host. Thus, understanding the epidemiology of this parasite in animal populations is vital to controlling its transmission to humans as well as to other animal groups. Objectives: This systematic review and meta-analysis aim to summarise and analyse reports of T. gondii infection in animal species residing in the Arabian Peninsula. Methods: It was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), with relevant studies being retrieved from MEDLINE/PubMed, Scopus, Cochrane Library, Google Scholar and ScienceDirect. All articles published in Arabic or English languages between January 2000 and December 2020 were screened for eligibility. The random effects model was used to calculate the pooled prevalence of T. gondii infection in different animal populations which were found to harbour this infection. The critical appraisal tool for prevalence studies designed by the Joanna Briggs Institute (JBI) was used to assess the risk of bias in all included studies. Results: A total of 15 studies were retrieved, reporting prevalence estimates from 4 countries in this region and in 13 animal species. A quantitative meta-analysis estimated a pooled prevalence of 43% in felids [95% confidence interval (CI) = 23-64%, I2 index = 100%], 48% in sheep (95% CI = 27-70%, I2 = 99%) and 21% in camels (95% CI = 7-35%, I2 = 99%). Evidence of possible publication bias was found in both felids and sheep. Conclusions: This meta-analysis estimates a high prevalence of T. gondii infection in animal species that are of high economic and cultural importance to countries of this region. Hence, these findings provide valuable insight to public health authorities as well as economic and animal resources advisors in countries of the Arabian Peninsula.

Keywords: Arabian Peninsula, toxoplasma gondii, animals; meta-analysis, toxoplasmosis

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Yexin Qu

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Izafe is a construction typically found in Iranian languages, which is attested already in Old Avestan and Old Persian. The narrow sense of izafe can be described as the linear structure of [NP pt Modifier] with pt as an uninflectable particle or clitic. The history of the Iranian izafe has the following stages: Stage I: Verbless nominal relative clauses, Stage II: Verbless nominal relative clauses with Case Attraction; and Stage III: Narrow sense izafe. Previous works suggest that embedded relative clauses and correlatives in other Indo-European languages might be relevant for the source of the izafe-construction. Stage I, as the precursor of narrow sense izafe, or so-called “prezafe” is not found in branches other than Iranian. Comparable cases have been demonstrated in Vedic, Greek, and some rare cases in Latin. This suggests “prezafe” may date back very early in Indo-European. Izafe-like structures are not attested in branches such as Balto-Slavic and Germanic, but Balto-Slavic definite adjectives and Germanic weak adjectives can be compared to the verbless nominal relative clauses and analyzed as developments of verbless relative clauses parallel to izafe in Indo-Iranian, as are called “parizafe” in this paper. In this paper, the verbless RC is compared with Germanic weak adjectives. The Germanic languages used n-stem derivation to form determined derivatives, which are semantically equivalent to the appositive RC and eventually became weak adjectives. To be more precise, starting from an adjective “X”, the Germanic weak adjective structure is formed as [det X-n], literally “the X”, with the meaning “the X one”, which can be shown to be semantically equivalent to “the one which is X”. In this paper, Stage I suggest that, syntactically, the Germanic verbless relative clauses went through CP to DP relabeling like Iranian, based on the following observations: (1) Germanic relative pronouns (e.g., Gothic saei, Old English se) and determiners (e.g., Gothic sa, Old English se) are both from the *so/to pronominal roots; (2) the semantic equivalence of Germanic weak adjectives and the izafe structure. This may suggest that Germanic may also have had “Prezafe” Stages I and II. In conclusion: “Prezafe” in Stage I may have been a phenomenon of the proto-language, Stage II was the result of independent parallel developments and then each branch had its own strategy.

Keywords: izafe, relative clause, Germanic, Indo-European

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Authors: Shankaran Sitarama

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Teamwork is an extremely effective pedagogical tool in engineering education. New Product Development (NPD) has been an effective strategy of companies to streamline and bring innovative products and solutions to customers. Thus, Engineering curriculum in many schools, some collaboratively with business schools, have brought NPD into the curriculum at the graduate level. Teamwork is invariably used during instruction, where students work in teams to come up with new products and solutions. There is a significant emphasis of grade on the semester long teamwork for it to be taken seriously by students. As the students work in teams and go through this process to develop the new product prototypes, their effectiveness and learning to a great extent depends on how they function as a team and go through the creative process, come together, and work towards the common goal. A core attribute of a successful NPD team is their creativity and innovation. The team needs to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas resulting in a POC (proof-of-concept) implementation or a prototype of the product. The simultaneous requirement of teams to be creative and at the same time also converge and work together imposes different types of tensions in their team interactions. These ideational tensions / conflicts and sometimes relational tensions / conflicts are inevitable. Effective teams will have to deal with the Team dynamics and manage it to be resilient enough and yet be creative. This research paper provides a computational analysis of the teams’ communication that is reflective of the team dynamics, and through a superimposition of latent semantic analysis with social network analysis, provides a computational methodology of arriving at patterns of visual interaction. These team interaction patterns have clear correlations to the team dynamics and provide insights into the functioning and thus the effectiveness of the teams. 23 student NPD teams over 2 years of a course on Managing NPD that has a blend of engineering and business school students is considered, and the results are presented. It is also correlated with the teams’ detailed and tailored individual and group feedback and self-reflection and evaluation questionnaire.

Keywords: team dynamics, social network analysis, team interaction patterns, new product development teamwork, NPD teams

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Authors: Choonsik Lee, Les Folio

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Pregnant patients may undergo CT in emergencies unrelated with pregnancy, and potential risk to the developing fetus is of concern. It is critical to accurately estimate fetal organ doses in CT scans. We developed a fetal organ dose calculation tool using pregnancy-specific computational phantoms combined with Monte Carlo radiation transport techniques. We adopted a series of pregnancy computational phantoms developed at the University of Florida at the gestational ages of 8, 10, 15, 20, 25, 30, 35, and 38 weeks (Maynard et al. 2011). More than 30 organs and tissues and 20 skeletal sites are defined in each fetus model. We calculated fetal organ dose-normalized by CTDIvol to derive organ dose conversion coefficients (mGy/mGy) for the eight fetuses for consequential slice locations ranging from the top to the bottom of the pregnancy phantoms with 1 cm slice thickness. Organ dose from helical scans was approximated by the summation of doses from multiple axial slices included in the given scan range of interest. We then compared dose conversion coefficients for major fetal organs in the abdominal-pelvis CT scan of pregnancy phantoms with the uterine dose of a non-pregnant adult female computational phantom. A comprehensive library of organ conversion coefficients was established for the eight developing fetuses undergoing CT. They were implemented into an in-house graphical user interface-based computer program for convenient estimation of fetal organ doses by inputting CT technical parameters as well as the age of the fetus. We found that the esophagus received the least dose, whereas the kidneys received the greatest dose in all fetuses in AP scans of the pregnancy phantoms. We also found that when the uterine dose of a non-pregnant adult female phantom is used as a surrogate for fetal organ doses, root-mean-square-error ranged from 0.08 mGy (8 weeks) to 0.38 mGy (38 weeks). The uterine dose was up to 1.7-fold greater than the esophagus dose of the 38-week fetus model. The calculation tool should be useful in cases requiring fetal organ dose in emergency CT scans as well as patient dose monitoring.

Keywords: computed tomography, fetal dose, pregnant women, radiation dose

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

Procedia PDF Downloads 110