Search results for: feature noise

Authors: Sara Matsuzaka

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At the center of emerging policy debates on the rights of transgender individuals in public accommodations is the collision of gender binary views with transgender perspectives that challenge conventional gender norms. The results of such socio-political debates could have significant ramifications for the policies and infrastructures of public and private institutions nationwide, including within the addiction treatment field. Despite having disproportionately high rates of substance use disorder compared to the general population, transgender individuals experience significant barriers to engaging in addiction treatment programs. Inpatient addiction treatment centers were originally designed to treat heterosexual cisgender populations and, as such, feature gender segregated housing, bathrooms, and counseling sessions. Such heteronormative structural barriers, combined with exposures to stigmatic al attitudes, may dissuade transgender populations from benefiting from the addiction treatment they so direly need. A literature review is performed to explore the mechanisms by which gender segregation alienates transgender populations within inpatient addiction treatment. The constituent parts of the current debate on the rights of transgender individuals in public accommodations are situated the context of inpatient addiction treatment facilities. Minority Stress Theory is used as a theoretical framework for understanding substance abuse issues among transgender populations as a maladaptive behavioral response for coping with chronic stressors related to gender minority status and intersecting identities. The findings include that despite having disproportionately high rates of substance use disorder compared to the general population, transgender individuals experience significant barriers to engaging in and benefiting from addiction treatment. These barriers are present in the form of anticipated or real interpersonal stigma and discrimination by service providers and structural stigma in the form of policy and programmatic components in addiction treatment that marginalize transgender populations. Transphobic manifestations within addiction treatment may dissuade transgender individuals from seeking help, if not reinforce a lifetime of stigmatic experience, potentially exacerbating their substance use issues. Conclusive recommendations for social workers and addiction treatment professionals include: (1) dismantling institutional policies around gender segregation that alienate transgender individuals, (2) developing policies that provide full protections for transgender clients against discrimination based on their gender identity, and (3) implementing trans-affirmative cultural competency training requirements for all staff. Directions for future research are provided.

Keywords: addiction treatment, gender segregation, stigma, transgender

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Authors: Mehwish Jamil Noor

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Morphological features of pollen (sculpturing) were useful for identification of different floral taxa. In this study 49 pollen grains, types belonging to 25 families were studied using Scanning Electron Microscope. Shape and sculpturing of pollen ranging from Psilate, scabrate to reticulate, bireticulate and echinolophate. Honey pollen was identified using morphological features, number and arrangement of pore and colpi, size and shape. It presents the first attempt from Pakistan involving extraction of pollen from honey, its identification and taxonomic analysis. Among pollen studied diversity in shape and sculpturing has been observed ranging from Psilate, scabrate to reticulate to bireticulate and echinolophate condition. Pollen has been identified with the help of morphological feature, number and arrangement of pore and colpi, size and shape, reference slides, light microscopic data and previous literature have been consulted for pollen identification. Pollen of closely related species resemble each other therefore pollen identification of airborne and honey pollen is not possible till species level. Survey of flora was carried in parallel to keep the record about the allergenic and melliferous preference of specific sites through surveys and interviews. Their pollination season and geographical distribution were recorded. Two hundred and five including wild and cultivated taxa were identified belonging to sixty-seven families. Major bee attracting wild shrub and trees includes Justicia adhatoda, Acacia nilotica, Ziziphus jujuba, Taraxicum officinalis, Artemisia dubia, Casuarina sp., Ulmus sp., Broussonetia papyrifera, Cupressus sp. or Pinus roxburghii etc. Cultivated crops like Pennisetum typhoides, Nigella sativa, Triticum sativum along with fruit trees of Pyrus, Prunus, Eryobotria, Citrus etc. are popular melliferous floras. Exotic/ introduced species like Eucalyptus or Parthenium hysterophorus, are also frequently visited by bees indicating the significance of those plants in the honey industry. It is concluded that different microscopic analysis techniques give more clear and authentic pictures of and melliferous pollen identification which is well supported by the floral calendar. The diversity of pollen are observed in case of melliferous pollen, and most of the windborne pollen were found less sculptured or psilate expressing the adaptation to the specific mode of pollination. Pollen morphology and sculpturing would serve as a reference for future studies.

Keywords: pollen, allergenic flora, sem, pollen key, Scanning Electron Microscopy (SEM)

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Jun Ren, Zhen-Hua Ming, He-Feng Huang, Jian-Zhong Sheng

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Adverse intrauterine stimulus during critical or sensitive periods in early life, may lead to health risk not only in later life span, but also further generations. Intrauterine hyperglycaemia, as a major feature of gestational diabetes mellitus (GDM), is a typical adverse environment for both F1 fetus and F1 gamete cells development. However, there is scare information of phenotypic difference of metabolic memory between somatic cells and germ cells exposed by intrauterine hyperglycaemia. The direct transmission effect of intrauterine hyperglycaemia per se has not been assessed either. In this study, we built a GDM mice model and selected male GDM offspring without pre-diabetic phenotype as our founders, to exclude postnatal diabetic influence on gametes, thereby investigate the direct transmission effect of intrauterine hyperglycaemia exposure on F2 offspring, and we further compared the metabolic difference of affected F1-GDM male offspring and F2 offspring. A GDM mouse model of intrauterine hyperglycemia was established by intraperitoneal injection of streptozotocin after pregnancy. Pups of GDM mother were fostered by normal control mothers. All the mice were fed with standard food. Male GDM offspring without metabolic dysfunction phenotype were crossed with normal female mice to obtain F2 offspring. Body weight, glucose tolerance test, insulin tolerance test and homeostasis model of insulin resistance (HOMA-IR) index were measured in both generations at 8 week of age. Some of F1-GDM male mice showed impaired glucose tolerance (p < 0.001), none of F1-GDM male mice showed impaired insulin sensitivity. Body weight of F1-GDM mice showed no significance with control mice. Some of F2-GDM offspring exhibited impaired glucose tolerance (p < 0.001), all the F2-GDM offspring exhibited higher HOMA-IR index (p < 0.01 of normal glucose tolerance individuals vs. control, p < 0.05 of glucose intolerance individuals vs. control). All the F2-GDM offspring exhibited higher ITT curve than control (p < 0.001 of normal glucose tolerance individuals, p < 0.05 of glucose intolerance individuals, vs. control). F2-GDM offspring had higher body weight than control mice (p < 0.001 of normal glucose tolerance individuals, p < 0.001 of glucose intolerance individuals, vs. control). While glucose intolerance is the only phenotype that F1-GDM male mice may exhibit, F2 male generation of healthy F1-GDM father showed insulin resistance, increased body weight and/or impaired glucose tolerance. These findings imply that intrauterine hyperglycaemia exposure affects germ cells and somatic cells differently, thus F1 and F2 offspring demonstrated distinct metabolic dysfunction phenotypes. And intrauterine hyperglycaemia exposure per se has a strong influence on F2 generation, independent of postnatal metabolic dysfunction exposure.

Keywords: inheritance, insulin resistance, intrauterine hyperglycaemia, offspring

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Authors: Preet Shah, Om Shrivastav

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Introduction : In India, Leishmania donovani is the only parasite causing Leishmaniasis. The parasite infects the reticuloendothelial system and is found in the bone marrow, spleen and liver. Treatment of choice is amphotericin-B with sodium stibogluconate being an alternative. Miltefosine is useful in refractory cases. In our case, Leishmaniasis occurred in a person residing in western India (which is quite rare) and it failed to respond to two different drugs (again an uncommon feature) before it finally responded to a third one. Description: A 50 year old lady, a resident of western India, with no history of recent travel, presented with an ulcer on the left side of the nose since 8 months. She was apparently alright 8 months back, when she noticed a small ulcerated lesion on the left ala of the nose which was immediately biopsied. The biopsy revealed amastigotes of Leishmania for which she was administered intra-lesional sodium stibogluconate for 1 month (4 doses every 8 days).Despite this, there was no regression of the ulcer and hence she presented to us for further management. On examination, her vital parameters were normal. Barring an ulcer on the left side of the nose, rest of the examination findings were unremarkable. Complete blood count was normal. Ultrasound abdomen showed hepatomegaly. PET-CT scan showed increased metabolic activity in left ala of nose, hepatosplenomegaly and increased metabolic activity in spleen and bone marrow. Bone marrow biopsy was done which showed hypercellular marrow with erythroid preponderance. Considering a diagnosis of leishmaniasis which had so far been unresponsive to sodium stibogluconate, she was started on liposomal amphotericin-B. At the time of admission, her creatinine level was normal, but it started rising with the administration of liposomal amphotericin-B, hence the dose was reduced. Despite this, creatinine levels did not improve, and she started developing hypokalemia and hypomagnesemia as side effects of the drug, hence further reductions in the dosage were made. Despite a total of 3 weeks of liposomal amphotericin-B, there was no improvement in the ulcer. As had so far failed to respond to sodium stibogluconate and liposomal amphotericin-B, it was decided to start her on miltefosine. She received the miltefosine for a total of 12 weeks. At the end of this duration, there was a marked regression of the cutaneous lesion. Conclusion: Refractoriness to amphotericin-B in leishmaniasis may be seen in up to 5 % cases. Here, an alternative drug such as miltefosine is useful and hence we decided to use it, to which she responded adequately. Furthermore, although leishmaniasis is common in the eastern part of India, it is a relatively unknown entity in the western part of the country with the occurrence being very rare. Because of these 2 reasons, we consider our case to be a unique one.

Keywords: amphotericin-b, leishmaniasis, miltefosine, tropical diseases

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Payal Sudhan

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Popular films in India, Bollywood, and other local industries make a range of commercial films that attract vast viewership. Love, Heroism, Action, Adventure, Revenge, etc., are some of the dearest themes chosen by many filmmakers of various popular film Industries across the world. However, sexuality has become an issue to address within the cinema. Such films feature in small numbers compared to other themes. One can easily assume that homosexuality is unlikely to be a favorite theme found in Indian popular cinema. It doesn’t mean that there is absolutely no film made on the issues of homosexuality. There have been several attempts. Earlier, some movies depicted homosexual (gay) characters as comedians, which continued until the beginning of the 21st century. The study aims to explore how modern homophobia and stereotype are represented in the films and how it affects homosexuality in the recent Malayalam Cinema. The study wills primarily focusing on Mumbai Police (2013) and My Life Partner (2014). The study tries to explain social space, the idea of a cure, and criminality. The film that has been selected for the analysis Mumbai Police (2013) is a crime thriller. The nonlinear narration of the movie reveals, towards the end, the murderer of ACP Aryan IPS, who was shot dead in a public meeting. In the end, the culprit is the enquiring officer, ACP Antony Moses, himself a close friend and colleague of the victim. Much to one’s curiosity, the primary cause turns out to be the sexual relation Antony has. My Life Partner generically can be classified as a drama. The movie puts forth male bonding and visibly riddles the notions of love and sex between Kiran and his roommate Richard. Running through the same track, the film deals with a different ‘event.’ The ‘event’ is the exclusive celebration of male bonding. The socio-cultural background of the cinema is heterosexual. The elements of heterosexual social setup meet the ends of diplomacy of the Malayalam queer visual culture. The film reveals the life of two gays who were humiliated by the larger heterosexual society. In the end, Kiran dies because of extreme humiliation. The paper is a comparative and cultural analysis of the two movies, My Life Partner and Mumbai Police. I try to bring all the points of comparison together and explain the similarities and differences, how one movie differs from another. Thus, my attempt here explains how stereotypes and homophobia with other related issues are represented in these two movies.

Keywords: queer cinema, homophobia, malayalam cinema, queer films

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: D. O. Miranda, L. R. Azevedo, J. F. C. Cordeiro, A. H. Dos Santos, S. F. Lisboa, F. S. Guimarães, G. S. Bisson

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Background: The Colorectal cancer (CRC) is one of the most common cancers and the fourth leading cause of cancer death in the world. The prevalence of psychiatric-disorders among CRC patients, mainly depression, is high, resulting in impaired quality of life and side effects of primary treatment. High levels of proinflammatory cytokines at tumor microenvironment is a feature of CRC and the literature suggests that those mediators could contribute to the development of psychiatric disorders. Nevertheless, the ability of tumor-associated biological processes to affect the central nervous system (CNS) has only recently been explored in the context of symptoms of depression and is still not well understood. Therefore, the aim of the present study was to test the hypothesis that depressive-like behavior in an experimental model of CCR induced by N-methyl-N-nitro-N-nitrosoguanidine (MNNG) was correlated to proinflammatory profile in the periphery and in the brain. Methods: Colorectal carcinogenesis was induced in adult C57BL/6 mice (n=12) by administration of MNNG (5mg/kg, 0.1ml/intrarectal instillation) 2 times a week, for 2 week. Control group (n=12) received saline (0.1ml/intrarectal instillation). Eight weeks after beginning of MNNG administration animals were submitted to the forced swim test (FST) and the sucrose preference test for evaluation, respectively, of depressive- and anhedonia-like behaviors. After behavioral evaluation, the colon was collected and brain regions dissected (cortex-C, striatum-ST and hippocampus-HIP) for posterior evaluation of cytokine levels (IL-1β, IL-10, IL-17, and CX3CL1) by ELISA. Results: MNNG induced depressive-like behavior, represented by increased immobility time in the FST (Student t test, p < 0.05) and lower sucrose preference (Student t test, p < 0.05). Moreover, there were increased levels of IL-1β, IL-17 and CX3CL1 in the colonic tissue (Student t test, p < 0.05) and in the brain (IL-1 β in the ST and HIP, Student t test, p < 0.05; IL-17 and CX3CL1 in the C and HIP, p < 0.05). IL-10 levels, in contrast, were decreased in both the colon (p < 0.05) and the brain (C and HIP, p < 0.05). Conclusions: The results obtained in the present work support the notion that tumor growth induces neuroinflammation in stress-related brain regions and depressive-like behavior, which could be related to the high incidence of depression in colorectal carcinogenesis. This work have important clinical and research implications, taken into account that cytokine levels may be a marker promissory for the developing depression in CRC patients. New therapeutic strategies to assist in alleviating mental suffering in cancer patients might result from a better understanding of the role of cytokines in the pathophysiology of depression in these subjects.

Keywords: cytokines, brain, depression, colorectal cancer

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Authors: Orkide Donma, Mustafa M. Donma

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Association between insulin resistance (IR) and hematological parameters has long been a matter of interest. Within this context, body mass index (BMI), red blood cells, white blood cells and platelets were involved in this discussion. Parameters related to platelets associated with IR may be useful indicators for the identification of IR. Platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT) are being questioned for their possible association with IR. The aim of this study was to investigate the association between platelet (PLT) count as well as PLT indices and the surrogate indices used to determine IR in morbid obese (MO) children. A total of 167 children participated in the study. Three groups were constituted. The number of cases was 34, 97 and 36 children in the normal BMI, MO and metabolic syndrome (MetS) groups, respectively. Sex- and age-dependent BMI-based percentile tables prepared by World Health Organization were used for the definition of morbid obesity. MetS criteria were determined. BMI values, homeostatic model assessment for IR (HOMA-IR), alanine transaminase-to-aspartate transaminase ratio (ALT/AST) and diagnostic obesity notation model assessment laboratory (DONMA-lab) index values were computed. PLT count and indices were analyzed using automated hematology analyzer. Data were collected for statistical analysis using SPSS for Windows. Arithmetic mean and standard deviation were calculated. Mean values of PLT-related parameters in both control and study groups were compared by one-way ANOVA followed by Tukey post hoc tests to determine whether a significant difference exists among the groups. The correlation analyses between PLT as well as IR indices were performed. Statistically significant difference was accepted as p-value < 0.05. Increased values were detected for PLT (p < 0.01) and PCT (p > 0.05) in MO group compared to those observed in children with N-BMI. Significant increases for PLT (p < 0.01) and PCT (p < 0.05) were observed in MetS group in comparison with the values obtained in children with N-BMI (p < 0.01). Significantly lower MPV and PDW values were obtained in MO group compared to the control group (p < 0.01). HOMA-IR (p < 0.05), DONMA-lab index (p < 0.001) and ALT/AST (p < 0.001) values in MO and MetS groups were significantly increased compared to the N-BMI group. On the other hand, DONMA-lab index values also differed between MO and MetS groups (p < 0.001). In the MO group, PLT was negatively correlated with MPV and PDW values. These correlations were not observed in the N-BMI group. None of the IR indices exhibited a correlation with PLT and PLT indices in the N-BMI group. HOMA-IR showed significant correlations both with PLT and PCT in the MO group. All of the three IR indices were well-correlated with each other in all groups. These findings point out the missing link between IR and PLT activation. In conclusion, PLT and PCT may be related to IR in addition to their identities as hemostasis markers during morbid obesity. Our findings have suggested that DONMA-lab index appears as the best surrogate marker for IR due to its discriminative feature between morbid obesity and MetS.

Keywords: children, insulin resistance, metabolic syndrome, plateletcrit, platelet indices

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Authors: Juan-Pedro Rica-Peromingo

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Nowadays, corpus linguistics has become a key research methodology for Translation Studies, which broadens the scope of cross-linguistic studies. In the case of the study presented here, the approach used focuses on learners with little or no experience to study, at an early stage, general mistakes and errors, the correct or incorrect use of translation strategies, and to improve the translational competence of the students. Led by Sylviane Granger and Marie-Aude Lefer of the Centre for English Corpus Linguistics of the University of Louvain, the MUST corpus (MUltilingual Student Translation Corpus) is an international project which brings together partners from Europe and worldwide universities and connects Learner Corpus Research (LCR) and Translation Studies (TS). It aims to build a corpus of translations carried out by students including both direct (L2 > L1) an indirect (L1 > L2) translations, from a great variety of text types, genres, and registers in a wide variety of languages: audiovisual translations (including dubbing, subtitling for hearing population and for deaf population), scientific, humanistic, literary, economic and legal translation texts. This paper focuses on the work carried out by the Spanish team from the Complutense University (UCMA), which is part of the MUST project, and it describes the specific features of the corpus built by its members. All the texts used by UCMA are either direct or indirect translations between English and Spanish. Students’ profiles comprise translation trainees, foreign language students with a major in English, engineers studying EFL and MA students, all of them with different English levels (from B1 to C1); for some of the students, this would be their first experience with translation. The MUST corpus is searchable via Hypal4MUST, a web-based interface developed by Adam Obrusnik from Masaryk University (Czech Republic), which includes a translation-oriented annotation system (TAS). A distinctive feature of the interface is that it allows source texts and target texts to be aligned, so we can be able to observe and compare in detail both language structures and study translation strategies used by students. The initial data obtained point out the kind of difficulties encountered by the students and reveal the most frequent strategies implemented by the learners according to their level of English, their translation experience and the text genres. We have also found common errors in the graduate and postgraduate university students’ translations: transfer errors, lexical errors, grammatical errors, text-specific translation errors, and cultural-related errors have been identified. Analyzing all these parameters will provide more material to bring better solutions to improve the quality of teaching and the translations produced by the students.

Keywords: corpus studies, students’ corpus, the MUST corpus, translation studies

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Authors: Michalina Aniola, Andrzej Katrusiak

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4,4-Bipyridine is an important compound often used in chemical practice and more recently frequently applied for designing new metal organic framework (MoFs). Here we present a systematic high-pressure study of its hydrobromide salt. 4,4-Bipyridine hydrobromide monohydrate, 44biPyHBrH₂O, at ambient-pressure is orthorhombic, space group P212121 (phase a). Its hydrostatic compression shows that it is stable to 1.32 GPa at least. However, the recrystallization above 0.55 GPa reveals a new hidden b-phase (monoclinic, P21/c). Moreover, when the 44biPyHBrH2O is heated to high temperature the chemical reactions of this compound in methanol solution can be observed. High-pressure experiments were performed using a Merrill-Bassett diamond-anvil cell (DAC), modified by mounting the anvils directly on the steel supports, and X-ray diffraction measurements were carried out on a KUMA and Excalibur diffractometer equipped with an EOS CCD detector. At elevated pressure, the crystal of 44biPyHBrH₂O exhibits several striking and unexpected features. No signs of instability of phase a were detected to 1.32 GPa, while phase b becomes stable at above 0.55 GPa, as evidenced by its recrystallizations. Phases a and b of 44biPyHBrH2O are partly isostructural: their unit-cell dimensions and the arrangement of ions and water molecules are similar. In phase b the HOH-Br- chains double the frequency of their zigzag motifs, compared to phase a, and the 44biPyH+ cations change their conformation. Like in all monosalts of 44biPy determined so far, in phase a the pyridine rings are twisted by about 30 degrees about bond C4-C4 and in phase b they assume energy-unfavorable planar conformation. Another unusual feature of 44biPyHBrH2O is that all unit-cell parameters become longer on the transition from phase a to phase b. Thus the volume drop on the transition to high-pressure phase b totally depends on the shear strain of the lattice. Higher temperature triggers chemical reactions of 44biPyHBrH2O with methanol. When the saturated methanol solution compound precipitated at 0.1 GPa and temperature of 423 K was required to dissolve all the sample, the subsequent slow recrystallization at isochoric conditions resulted in disalt 4,4-bipyridinium dibromide. For the 44biPyHBrH2O sample sealed in the DAC at 0.35 GPa, then dissolved at isochoric conditions at 473 K and recrystallized by slow controlled cooling, a reaction of N,N-dimethylation took place. It is characteristic that in both high-pressure reactions of 44biPyHBrH₂O the unsolvated disalt products were formed and that free base 44biPy and H₂O remained in the solution. The observed reactions indicate that high pressure destabilized ambient-pressure salts and favors new products. Further studies on pressure-induced reactions are carried out in order to better understand the structural preferences induced by pressure.

Keywords: conformation, high-pressure, negative area compressibility, polymorphism

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Angela U. Makolo

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

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

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Authors: Thayalan Nall, Harry Poulos

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Piling is the most widely used foundation method for heavy structures in poor soil conditions. The geotechnical engineer can choose among a variety of piling methods, but in most cases, driving piles by impact hammer is the most cost-effective alternative. Under unfavourable conditions, driving piles can cause environmental problems, such as noise, ground movements and vibrations, with the risk of ground disturbance leading to potential damage to proposed structures. In one of the project sites in which the authors were involved, three offshore container terminals, namely CT1, CT2 and CT3, were constructed over thick compressible marine mud. The seabed was around 6m deep and the soft clay thickness within the project site varied between 9m and 20m. CT2 and CT3 were connected together and rectangular in shape and were 2600mx800m in size. CT1 was 400m x 800m in size and was located on south opposite of CT2 towards its eastern end. CT1 was constructed first and due to time and environmental limitations, it was supported on a “forest” of large diameter driven piles. CT2 and CT3 are now under construction and are being carried out using a traditional dredging and reclamation approach with ground improvement by surcharging with vertical drains. A few months after the installation of the CT1 piles, a 2600m long sand bund to 2m above mean sea level was constructed along the southern perimeter of CT2 and CT3 to contain the dredged mud that was expected to be pumped. The sand bund was constructed by sand spraying and pumping using a dredging vessel. About 2000m length of the sand bund in the west section was constructed without any major stability issues or any noticeable distress. However, as the sand bund approached the section parallel to CT1, it underwent a series of deep seated failures leading the displaced soft clay materials to heave above the standing water level. The crest of the sand bund was about 100m away from the last row of piles. There were no plausible geological reasons to conclude that the marine mud only across the CT1 region was weaker than over the rest of the site. Hence it was suspected that the pile driving by impact hammer may have caused ground movements and vibrations, leading to generation of excess pore pressures and cyclic softening of the marine mud. This paper investigates the probable cause of failure by reviewing: (1) All ground investigation data within the region; (2) Soil displacement caused by pile driving, using theories similar to spherical cavity expansion; (3) Transfer of stresses and vibrations through the entire system, including vibrations transmitted from the hammer to the pile, and the dynamic properties of the soil; and (4) Generation of excess pore pressure due to ground vibration and resulting cyclic softening. The evidence suggests that the problems encountered at the site were primarily caused by the “side effects” of the pile driving operations.

Keywords: pile driving, ground vibration, excess pore pressure, cyclic softening

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Authors: Stefan Fuchs

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Against the backdrop of the proliferation of shopping malls in Japan during the last two decades, this paper presents the results of an ethnography conducted at a recently built suburban shopping mall in Western Tokyo. Through the analysis of the lived experiences of local residents, mall customers and the mall management this paper evaluates the benefits and disadvantages of the Business Improvement District (BID) model, which was implemented as urban redevelopment strategy in the area surrounding the shopping mall. The results of this research project show that while the BID model has in some respects contributed to the economic prosperity and to the perceived convenience of the area, it has led to gentrification and the redevelopment shows some deficiencies with regard to the inclusion of the elderly population as well as to the democratization of the decision-making process within the area. In Japan, shopping malls have been steadily growing both in size and number since a series of deregulation policies was introduced in the year 2000 in an attempt to push the domestic economy and to rejuvenate urban landscapes. Shopping malls have thereby become defining spaces of the built environment and are arguably important places of social interaction. Notwithstanding the vital role they play as factors of urban transformation, they have been somewhat overlooked in the research on Japan; especially with respect to their meaning for people’s everyday lives. By examining the ways, people make use of space in a shopping mall the research project presented in this paper addresses this gap in the research. Moreover, the research site of this research project is one of the few BIDs of Japan and the results presented in this paper can give indication on the scope of the future applicability of this urban redevelopment model. The data presented in this research was collected during a nine-months ethnographic fieldwork in and around the shopping mall. This ethnography includes semi-structured interviews with ten key informants as well as direct and participant observations examining the lived experiences and perceptions of people living, shopping or working at the shopping mall. The analysis of the collected data focused on recurring themes aiming at ultimately capturing different perspectives on the same aspects. In this manner, the research project documents the social agency of different groups within one communal network. The analysis of the perceptions towards the urban redevelopment around the shopping mall has shown that mainly the mall customers and large businesses benefit from the BID redevelopment model. While local residents benefit to some extent from their neighbourhood becoming more convenient for shopping they perceive themselves as being disadvantaged by changing demographics due to rising living expenses, the general noise level and the prioritisation of a certain customer segment or age group at the shopping mall. Although the shopping mall examined in this research project is just an example, the findings suggest that in future urban redevelopment politics have to provide incentives for landowners and developing companies to think of other ways of transforming underdeveloped areas.

Keywords: business improvement district, ethnography, shopping mall, urban redevelopment

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Bharatkumar Doshi

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Electro-Magnetic Pulse Welding (EMPW) is a solid state welding process carried out at almost room temperature, in which joining is enabled by high impact velocity deformation. In this process, high voltage capacitor’s stored energy is discharged in an EM coil resulting in a damped, sinusoidal current with an amplitude of several hundred kiloamperes. Due to these transient magnetic fields of few tens of Tesla near the coil is generated. As the conductive (tube) part is positioned in this area, an opposing eddy current is induced in this part. Consequently, high Lorentz forces act on the part, leading to acceleration away from the coil. In case of a tube, it gets compressed under forming velocities of more than 300 meters per second. After passing the joining gap it collides with the second metallic joining rod, leading to the formation of a jet under appropriate collision conditions. Due to the prevailing high pressure, metallurgical bonding takes place. A characteristic feature is the wavy interface resulting from the heavy plastic deformations. In the process, the formation of intermetallic compounds which might deteriorate the weld strength can be avoided, even for metals with dissimilar thermal properties. In order to optimize the process parameters like current, voltage, inductance, coil dimensions, workpiece dimensions, air gap, impact velocity, effective plastic strain, shear stress acting in the welding zone/impact zone etc. are very critical and important to establish. These process parameters could be determined by simulation using Finite Element Methods (FEM) in which electromagnetic –structural couple field analysis is performed. The feasibility of welding could thus be investigated by varying the parameters in the simulation using COMSOL. Simulation results shall be applied in performing the preliminary experiments of welding the different alloy steel tubes and/or alloy steel to other materials. The single turn coil (S.S.304) with field shaper (copper) has been designed and manufactured. The preliminary experiments are performed using existing EMPW facility available Institute for Plasma Research, Gandhinagar, India. The experiments are performed at 22kV charged into 64µF capacitor bank and the energy is discharged into single turn EM coil. Welding of axi-symetric components such as aluminum tube and rod has been proven experimentally using EMPW techniques. In this paper EM coil design, manufacturing, Electromagnetic-structural FEM simulation of Magnetic Pulse Welding and preliminary experiment results is reported.

Keywords: COMSOL, EMPW, FEM, Lorentz force

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Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

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Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

Procedia PDF Downloads 151

Authors: Joo-Heon Lee, Ho-Won Jang, Hyung-Won Cho, Tae-Woong Kim

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Drought is a recurrent climatic feature that occurs in virtually every climatic zone around the world. Korea experiences the drought almost every year at the regional scale mainly during in the winter and spring seasons. Moreover, extremely severe droughts at a national scale also occurred at a frequency of six to seven years. Various drought indices had developed as tools to quantitatively monitor different types of droughts and are utilized in the field of drought analysis. Since drought is closely related with climatological and topographic characteristics of the drought prone areas, the basins where droughts are frequently occurred need separate drought preparedness and contingency plans. In this study, an analysis using statistical methods was carried out for the historical droughts occurred in the five major river basins in Korea so that drought characteristics can be quantitatively investigated. It was also aimed to provide information with which differentiated and customized drought preparedness plans can be established based on the basin level analysis results. Conventional methods which quantifies drought execute an evaluation by applying a various drought indices. However, the evaluation results for same drought event are different according to different analysis technique. Especially, evaluation of drought event differs depend on how we view the severity or duration of drought in the evaluation process. Therefore, it was intended to draw a drought history for the most severely affected five major river basins of Korea by investigating a magnitude of drought that can simultaneously consider severity, duration, and the damaged areas by applying drought run theory with the use of SPI (Standardized Precipitation Index) that can efficiently quantifies meteorological drought. Further, quantitative analysis for the historical extreme drought at various viewpoints such as average severity, duration, and magnitude of drought was attempted. At the same time, it was intended to quantitatively analyze the historical drought events by estimating the return period by derived SDF (severity-duration-frequency) curve for the five major river basins through parametric regional drought frequency analysis. Analysis results showed that the extremely severe drought years were in the years of 1962, 1988, 1994, and 2014 in the Han River basin. While, the extreme droughts were occurred in 1982 and 1988 in the Nakdong river basin, 1994 in the Geumg basin, 1988 and 1994 in Youngsan river basin, 1988, 1994, 1995, and 2000 in the Seomjin river basin. While, the extremely severe drought years at national level in the Korean Peninsula were occurred in 1988 and 1994. The most damaged drought were in 1981~1982 and 1994~1995 which lasted for longer than two years. The return period of the most severe drought at each river basin was turned out to be at a frequency of 50~100 years.

Keywords: drought magnitude, regional frequency analysis, SPI, SDF(severity-duration-frequency) curve

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Authors: Cristina Felipeto, Catherine Bore, Eduardo Calil

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This work aims to analyze and compare the punctuation marks (PM) in school texts of Brazilian and French students and the comments on these PM made spontaneously by the students during the ongoing text. Assuming textual genetics as an investigative field within a dialogical and enunciative approach, we defined a common methodological design in two 1st year classrooms (7 years old) of the primary school, one classroom in Brazil (Maceio) and the other one in France (Paris). Through a multimodal capture system of writing processes in real time and space (Ramos System), we recorded the collaborative writing proposal in dyads in each of the classrooms. This system preserves the classroom’s ecological characteristics and provides a video recording synchronized with dialogues, gestures and facial expressions of the students, the stroke of the pen’s ink on the sheet of paper and the movement of the teacher and students in the classroom. The multimodal register of the writing process allowed access to the text in progress and the comments made by the students on what was being written. In each proposed text production, teachers organized their students in dyads and requested that they should talk, combine and write a fictional narrative. We selected a Dyad of Brazilian students (BD) and another Dyad of French students (FD) and we have filmed 6 proposals for each of the dyads. The proposals were collected during the 2nd Term of 2013 (Brazil) and 2014 (France). In 6 texts written by the BD there were identified 39 PMs and 825 written words (on average, a PM every 23 words): Of these 39 PMs, 27 were highlighted orally and commented by either student. In the texts written by the FD there were identified 48 PMs and 258 written words (on average, 1 PM every 5 words): Of these 48 PM, 39 were commented by the French students. Unlike what the studies on punctuation acquisition point out, the PM that occurred the most were hyphens (BD) and commas (FD). Despite the significant difference between the types and quantities of PM in the written texts, the recognition of the need for writing PM in the text in progress and the comments have some common characteristics: i) the writing of the PM was not anticipated in relation to the text in progress, then they were added after the end of a sentence or after the finished text itself; ii) the need to add punctuation marks in the text came after one of the students had ‘remembered’ that a particular sign was needed; iii) most of the PM inscribed were not related to their linguistic functions, but the graphic-visual feature of the text; iv) the comments justify or explain the PM, indicating metalinguistic reflections made by the students. Our results indicate how the comments of the BD and FD express the dialogic and subjective nature of knowledge acquisition. Our study suggests that the initial learning of PM depends more on its graphic features and interactional conditions than on its linguistic functions.

Keywords: collaborative writing, erasure, graphic marks, learning, metalinguistic awareness, textual genesis

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Adriana Garcia G., Alberto A. Escobar P., Amira D. Calvo L., Gabriel Lizama U., Alejandro Zepeda P., Fernando Martínez B., Susana Rincón A.

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Different studies have recently been focused on the use of antioxidants such as polyphenols because of to its anticarcinogenic capacity. However, these compounds are highly sensible to environmental factors such as light and heat, so lose its long-term stability, besides possess an astringent and bitter taste. Nevertheless, the polyphenols can be protected by microcapsule formulation. In this sense, a rich source of polyphenols is sorghum, besides presenting a high starch content. Due to the above, the aim of this work was to obtain modified starches from sorghum by extrusion to encapsulate polyphenols the sorghum by spray drying. Polyphenols were extracted by ethanol solution from sorghum (Pajarero/red) and determined by the method of Folin-Ciocalteu, obtaining GAE at 30 mg/g. Moreover, was extracted starch of sorghum (Sinaloense/white) through wet milling (yield 32 %). The hydrolyzed starch was modified with three treatments: acetic anhydride (2.5g/100g), sodium tripolyphosphate (4g/100g), and sodium tripolyphosphate/ acetic anhydride (2g/1.25g by each 100 g) by extrusion. Processing conditions of extrusion were as follows: barrel temperatures were of 60, 130 and 170 °C at the feeding, transition, and high-pressure extrusion zones, respectively. Analysis of Fourier Transform Infrared spectroscopy (FTIR), showed bands exhibited of acetyl groups (1735 cm-1) and phosphates (1170 cm-1, 910 cm-1 and 525 cm-1), indicating the respective modification of starch. Besides, all modified starches not developed viscosity, which is a characteristic required for use in the encapsulation of polyphenols using the spray drying technique. As result of the modification starch, was obtained a water solubility index (WSI) from 33.8 to 44.8 %, and crystallinity from 8 to 11 %, indicating the destruction of the starch granule. Afterwards, microencapsulation of polyphenols was developed by spray drying, with a blend of 10 g of modified starch, 60 ml polyphenol extract and 30 ml of distilled water. Drying conditions were as follows: inlet air temperature 150 °C ± 1, outlet air temperature 80°C ± 5. As result of the microencapsulation: were obtained yields of 56.8 to 77.4 % and an efficiency of encapsulation from 84.6 to 91.4 %. The FTIR analysis showed evidence of microcapsules loaded with polyphenols in bands 1042 cm-1, 1038 cm-1 and 1148 cm-1. Analysis Differential scanning calorimetry (DSC) showed transition temperatures from 144.1 to 173.9 °C. For the order hand, analysis of Scanning Electron Microscopy (SEM), were observed rounded surfaces with concavities, typical feature of microcapsules produced by spray drying, how result of rapid evaporation of water. Finally, the modified starches were obtained by extrusion with good characteristics for use as cover materials by spray drying, where the phosphorylated starch was the best treatment in this work, according to the encapsulation yield, efficiency, and transition temperature.

Keywords: encapsulation, extrusion, modified starch, polyphenols, spray drying

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Authors: Nebojsa Stefanovic, Sasa Milijic, Natasa Danilovic Hristic

Abstract:

Spatial plan of the special purpose area constitutes a basic tool in the planning of infrastructure corridor of a highway. The aim of the plan is to define the planning basis and provision of spatial conditions for the construction and operation of the highway, as well as for developing other infrastructure systems in the corridor. This paper presents a methodology and approach to the preparation of the Spatial Plan for the special purpose area for the infrastructure corridor of the highway E-80, Section Niš-Merdare in Serbia. The applied methodological approach is based on the combined application of the integrative and participatory method in the decision-making process on the sustainable development of the highway corridor. It was found that, for the planning and management of the infrastructure corridor, a key problem is coordination of spatial and urban planning, strategic environmental assessment and sectoral traffic planning and designing. Through the development of the plan, special attention is focused on increasing the accessibility of the local and regional surrounding, reducing the adverse impacts on the development of settlements and the economy, protection of natural resources, natural and cultural heritage, and the development of other infrastructure systems in the corridor of the highway. As a result of the applied methodology, this paper analyzes the basic features such as coverage, the concept, protected zones, service facilities and objects, the rules of development and construction, etc. Special emphasis is placed to methodology and results of the Strategic Environmental Assessment of the Spatial Plan, and to the importance of protection measures, with the special significance of air and noise protection measures. For evaluation in the Strategic Environmental Assessment, a multicriteria expert evaluation (semi-quantitative method) of planned solutions was used in relation to the set of goals and relevant indicators, based on the basic set of indicators of sustainable development. Evaluation of planned solutions encompassed the significance and size, spatial conditions and probability of the impact of planned solutions on the environment, and the defined goals of strategic assessment. The framework of the implementation of the Spatial Plan is presented, which is determined for the simultaneous elaboration of planning solutions at two levels: the strategic level of the spatial plan and detailed urban plan level. It is also analyzed the relationship of the Spatial Plan to other applicable planning documents for the planning area. The effects of this methodological approach relate to enabling integrated planning of the sustainable development of the infrastructure corridor of the highway and its surrounding area, through coordination of spatial, urban and sectoral traffic planning and design, as well as the participation of all key actors in the adoption and implementation of planned decisions. By the conclusions of the paper, it is pointed to the direction for further research, particularly in terms of harmonizing methodology of planning documentation and preparation of technical-design documentation.

Keywords: corridor, environment, highway, impact, methodology, spatial plan, urban

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Authors: Oscar Nieto-Garzón, Angélica Lozano

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In urban areas, on-road freight transportation creates several social and environmental externalities. Then, it is crucial that freight transport considers not only economic aspects, like retailer distribution cost reduction and service improvement, but also environmental effects such as global CO2 and local emissions (e.g. Particulate Matter, NOX, CO) and noise. Inadequate infrastructure development, high rate of urbanization, the increase of motorization, and the lack of transportation planning are characteristics that urban areas from developing countries share. The Metropolitan Area of Mexico City (MAMC), the Metropolitan Area of São Paulo (MASP), and Bogota are three of the largest urban areas in Latin America where air pollution is often a problem associated with emissions from mobile sources. The effect of the lockdown due to COVID-19 was analyzedfor these urban areas, comparing the same period (January to August) of years 2016 – 2019 with 2020. A strong reduction in the concentration of primary criteria pollutants emitted by road traffic were observed at the beginning of 2020 and after the lockdown measures.Daily mean concentration of NOx decreased 40% in the MAMC, 34% in the MASP, and 62% in Bogota. Daily mean ozone levels increased after the lockdown measures in the three urban areas, 25% in MAMC, 30% in the MASP and 60% in Bogota. These changes in emission patterns from mobile sources drastically changed the ambient atmospheric concentrations of CO and NOX. The CO/NOX ratioat the morning hours is often used as an indicator of mobile sources emissions. In 2020, traffic from cars and light vehicles was significantly reduced due to the first lockdown, but buses and trucks had not restrictions. In theory, it implies a decrease in CO and NOX from cars or light vehicles, maintaining the levels of NOX by trucks(or lower levels due to the congestion reduction). At rush hours, traffic was reduced between 50% and 75%, so trucks could get higher speeds, which would reduce their emissions. By means an emission model, it was found that an increase in the average speed (75%) would reduce the emissions (CO, NOX, and PM) from diesel trucks by up to 30%. It was expected that the value of CO/NOXratio could change due to thelockdownrestrictions. However, although there was asignificant reduction of traffic, CO/NOX kept its trend, decreasing to 8-9 in 2020. Hence, traffic restrictions had no impact on the CO/NOX ratio, although they did reduce vehicle emissions of CO and NOX. Therefore, these emissions may not adequately represent the change in the vehicle emission patterns, or this ratio may not be a good indicator of emissions generated by vehicles. From the comparison of the theoretical data and those observed during the lockdown, results that the real NOX reduction was lower than the theoretical reduction. The reasons could be that there are other sources of NOX emissions, so there would be an over-representation of NOX emissions generated by diesel vehicles, or there is an underestimation of CO emissions. Further analysis needs to consider this ratioto evaluate the emission inventories and then to extend these results forthe determination of emission control policies to non-mobile sources.

Keywords: COVID-19, emissions, freight transport, latin American metropolis

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Authors: Quoc Hung Le Pham

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In the field of language study, classifier is an interesting research feature. In the world’s languages, some languages have classifier system, some do not. Mandarin Chinese and Vietnamese languages are a rich classifier system, however, because of the language system, the cognitive, cultural differences, so that the syntactic structure of classifier of them also dissimilar. When using Mandarin Chinese classifiers must collocate with nouns or verbs, in the lexical category it is not like nouns or verbs, belong to the open class. But some scholars believe that Mandarin Chinese measure words are similar to English and other Indo European languages. The word hanging on the structure and word formation (suffix), is a closed class. Compared to other languages, such as Chinese, Vietnamese, Thai and other Asian languages are still belonging to the classifier language’s second type, this type of language is classifier, it is in the majority of quantity must exist, and following deictic, anaphoric or quantity appearing together, not separation between its modified noun, also known as numeral classifier language. Main syntactic structure of Chinese classifiers are as follows: ‘quantity+measure+noun’, ‘pronoun+measure+noun’, ‘pronoun+quantity+measure+noun’, ‘prefix+quantity+measure +noun’, ‘quantity +adjective + measure +noun’, ‘ quantity (above 10 whole number), + duo (多)measure +noun’, ‘ quantity (around 10) + measure + duo (多) +noun’. Main syntactic structure of Vietnamese classifiers are: ‘quantity+measure+noun’, ‘ measure+noun+pronoun’, ‘quantity+measure+noun+pronoun’, ‘measure+noun+prefix+ quantity’, ‘quantity+measure+noun+adjective', ‘duo (多) +quanlity+measure+noun’, ‘quantity+measure+adjective+pronoun (quantity word could not be 1)’, ‘measure+adjective+pronoun’, ‘measure+pronoun’. In daily life, classifiers are commonly used, if Chinese learners failed to standardize this using catergory, because the negative impact might occur on their verbal communication. The richness of the Chinese classifier system contributes to the complexity in the study of the system by foreign learners, especially in the inter language of Vietnamese learners. As above mentioned, Vietnamese language also has a rich system of classifiers, however, the basic structure order of two languages are similar but both still have differences. These similarities and dissimilarities between Chinese and Vietnamese classifier systems contribute significantly to the common errors made by Vietnamese students while they acquire Chinese, which are distinct from the errors made by students from the other language background. This article from a comparative perspective of language, has an orientation towards Chinese and Vietnamese languages commonly used in classifiers semantics and structural form two aspects. This comparative study aims to identity Vietnamese students while learning Chinese classifiers may face some negative transference of mother language, beside that through the analysis of the classifiers questionnaire, find out the causes and patterns of the errors they made. As the preliminary analysis shows, Vietnamese students while learning Chinese classifiers made some errors such as: overuse classifier ‘ge’(个); misuse the other classifiers ‘*yi zhang ri ji’(yi pian ri ji), ‘*yi zuo fang zi’(yi jian fang zi), ‘*si zhang jin pai’(si mei jin pai); homonym words ‘dui, shuang, fu, tao’ (对、双、副、套), ‘ke, li’ (颗、粒).

Keywords: acquisition, classifiers, negative transfer, Vietnamse learners

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Authors: Elizabeth O. Odewale, Sachithra T. Wanasinghe, Aaron S. Rury

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Cavity polaritons form when molecular excitons strongly couple to photons in carefully constructed optical cavities. These polaritons, which are hybrid light-matter states possessing a unique combination of photonic and excitonic properties, present the opportunity to manipulate the properties of various semiconductor materials. The systematic manipulation of materials through polariton formation could potentially improve the functionalities of many optoelectronic devices such as lasers, light-emitting diodes, photon-based quantum computers, and solar cells. However, the prospects of leveraging polariton formation for novel devices and device operation depend on more complete connections between the properties of molecular chromophores, and the hybrid light-matter states they form, which remains an outstanding scientific goal. Specifically, for most optoelectronic applications, it is paramount to understand how polariton formation affects the spectra of light absorbed by molecules coupled strongly to cavity photons. An essential feature of a polariton state is its dispersive energy, which occurs due to the enhanced spatial delocalization of the polaritons relative to bare molecules. To leverage the spatial delocalization of cavity polaritons, angle-resolved photoluminescence excitation spectroscopy was employed in characterizing light emission from the polaritonic states. Using lasers of appropriate energies, the polariton branches were resonantly excited to understand how molecular light absorption changes under different strong light-matter coupling conditions. Since an excited state has a finite lifetime, the photon absorbed by the polariton decays non-radiatively into lower-lying molecular states, from which radiative relaxation to the ground state occurs. The resulting fluorescence is collected across several angles of excitation incidence. By modeling the behavior of the light emission observed from the lower-lying molecular state and combining this result with the output of angle-resolved transmission measurements, inferences are drawn about how the behavior of molecules changes when they form polaritons. These results show how the intrinsic properties of molecules, such as the excitonic lifetime, affect the rate at which the polaritonic states relax. While it is true that the lifetime of the photon mediates the rate of relaxation in a cavity, the results from this study provide evidence that the lifetime of the molecular exciton also limits the rate of polariton relaxation.

Keywords: flourescece, molecules in cavityies, optical cavity, photoluminescence excitation, spectroscopy, strong coupling

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Authors: Stefano Zaninotto, Geoffrey Farrugia, Johan Debattista, Jason Gauci

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The need to reduce fuel and noise during taxi operations in the airports with a scenario of constantly increasing air traffic has resulted in an effort by the aerospace industry to move towards electric taxiing. In fact, this is one of the problems that is currently being addressed by SESAR JU and two main solutions are being proposed. With the first solution, electric motors are installed in the main (or nose) landing gear of the aircraft. With the second solution, manned or unmanned electric tow trucks are used to tow aircraft from the gate to the runway (or vice-versa). The presence of the tow trucks results in an increase in vehicle traffic inside the airport. Therefore, it is important to design the system in a way that the workload of Air Traffic Control (ATC) is not increased and the system assists ATC in managing all ground operations. The aim of this work is to develop an electric taxiing system, based on the use of autonomous tow trucks, which optimizes aircraft ground operations while keeping ATC in the loop. This system will consist of two components: an optimization tool and a Graphical User Interface (GUI). The optimization tool will be responsible for determining the optimal path for arriving and departing aircraft; allocating a tow truck to each taxiing aircraft; detecting conflicts between aircraft and/or tow trucks; and proposing solutions to resolve any conflicts. There are two main optimization strategies proposed in the literature. With centralized optimization, a central authority coordinates and makes the decision for all ground movements, in order to find a global optimum. With the second strategy, called decentralized optimization or multi-agent system, the decision authority is distributed among several agents. These agents could be the aircraft, the tow trucks, and taxiway or runway intersections. This approach finds local optima; however, it scales better with the number of ground movements and is more robust to external disturbances (such as taxi delays or unscheduled events). The strategy proposed in this work is a hybrid system combining aspects of these two approaches. The GUI will provide information on the movement and status of each aircraft and tow truck, and alert ATC about any impending conflicts. It will also enable ATC to give taxi clearances and to modify the routes proposed by the system. The complete system will be tested via computer simulation of various taxi scenarios at multiple airports, including Malta International Airport, a major international airport, and a fictitious airport. These tests will involve actual Air Traffic Controllers in order to evaluate the GUI and assess the impact of the system on ATC workload and situation awareness. It is expected that the proposed system will increase the efficiency of taxi operations while reducing their environmental impact. Furthermore, it is envisaged that the system will facilitate various controller tasks and improve ATC situation awareness.

Keywords: air traffic control, electric taxiing, autonomous tow trucks, graphical user interface, ground operations, multi-agent, route optimization

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