Search results for: post processing

Authors: Anupama A. P.

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The Malayalam film industry, known as Mollywood, has a rich tradition of storytelling and cultural significance within Indian cinema. Middlebrow films have emerged as a distinct influential category, particularly in the 1980s, with directors like K.G. George, who engaged with female subjectivity and drew inspiration from the ‘women’s cinema’ of the 1950s and 1960s. In recent decades, particularly post-2010, the industry has transformed significantly with a new generation of filmmakers diverging from melodrama and new wave of the past, incorporating advanced technology and modern content. This study examines the evolution and impact of Malayalam middlebrow cinema in the 21st century, focusing on post-2000 films and their influence on contemporary spectator experiences. These films appeal to a wide range of audiences without compromising on their artistic integrity, tackling social issues and personal dramas with thematic and narrative complexity. Historically, middlebrow films in Malayalam cinema have portrayed realism and addressed the socio-political climate of Kerala, blending realism with reflexivity and moving away from traditional sentimentality. This shift is evident in the new generation of Malayalam films, which present a global representation of characters and a modern treatment of individuals. To provide a comprehensive understanding of this evolution, the study analyzes a diverse selection of films such as Kerala Varma Pazhassi Raja (2009), Drishyam (2013), Maheshinte Prathikaaram (2016), Take Off (2017), and Thondimuthalum Driksakshiyum (2017) and Virus (2019) illustrating the broad thematic range and innovative narrative techniques characteristic of this genre. These films exemplify how middlebrow cinema continues to evolve, adapting to changing societal contexts and audience expectations. This research employs a theoretical methodology, drawing on cultural studies and audience reception theory, utilizing frameworks such as Bordwell’s narrative theory, Deleuze’s concept of deterritorialization, and Hall’s encoding/decoding model to analyze the changes in Malayalam middlebrow cinema and interpret the storytelling methods, spectator experience, and audience reception of these films. The findings indicate that Malayalam middlebrow cinema post-2010 offers a spectator experience that is both intellectually stimulating and broadly appealing. This study highlights the critical role of middlebrow cinema in reflecting and shaping societal values, making it a significant cultural artefact within the broader context of Indian and global cinema. By bridging entertainment with thought-provoking narratives, these films engage audiences and contribute to wider cultural discourse, making them pivotal in contemporary cinematic landscapes. To conclude, this study highlights the importance of Malayalam middle-brow cinema in influencing contemporary cinematic tastes. The nuanced and approachable narratives of post-2010 films are posited to assume an increasingly pivotal role in the future of Malayalam cinema. By providing a deeper understanding of Malayalam middlebrow cinema and its societal implications, this study enriches theoretical discourse, promotes regional cinema, and offers valuable insights into contemporary spectator experiences and the future trajectory of Malayalam cinema.

Keywords: Malayalam cinema, middlebrow cinema, spectator experience, audience reception, deterritorialization

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Authors: Azin Zargham, Gholamreza Rouhi, Allahyar Geramy

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One of the most prevalent types of alveolar bone loss is horizontal bone loss (HBL) in which the bone height around teeth is reduced homogenously. In the presence of HBL the magnitudes of forces during orthodontic treatment should be altered according to the degree of HBL, in a way that without further bone loss, desired tooth movement can be obtained. In order to investigate the appropriate orthodontic force system in the presence of HBL, a three-dimensional numerical model capable of the simulation of orthodontic tooth movement was developed. The main goal of this research was to evaluate the effect of different degrees of HBL on a long-term orthodontic tooth movement. Moreover, the effect of different force magnitudes on orthodontic tooth movement in the presence of HBL was studied. Five three-dimensional finite element models of a maxillary lateral incisor with 0 mm, 1.5 mm, 3 mm, 4.5 mm and 6 mm of HBL were constructed. The long-term orthodontic tooth tipping movements were attained during a 4-weeks period in an iterative process through the external remodeling of the alveolar bone based on strains in periodontal ligament as the bone remodeling mechanical stimulus. To obtain long-term orthodontic tooth movement in each iteration, first the strains in periodontal ligament under a 1-N tipping force were calculated using finite element analysis. Then, bone remodeling and the subsequent tooth movement were computed in a post-processing software using a custom written program. Incisal edge, cervical, and apical area displacement in the models with different alveolar bone heights (0, 1.5, 3, 4.5, 6 mm bone loss) in response to a 1-N tipping force were calculated. Maximum tooth displacement was found to be 2.65 mm at the top of the crown of the model with a 6 mm bone loss. Minimum tooth displacement was 0.45 mm at the cervical level of the model with a normal bone support. Tooth tipping degrees of models in response to different tipping force magnitudes were also calculated for models with different degrees of HBL. Degrees of tipping tooth movement increased as force level was increased. This increase was more prominent in the models with smaller degrees of HBL. By using finite element method and bone remodeling theories, this study indicated that in the presence of HBL, under the same load, long-term orthodontic tooth movement will increase. The simulation also revealed that even though tooth movement increases with increasing the force, this increase was only prominent in the models with smaller degrees of HBL, and tooth models with greater degrees of HBL will be less affected by the magnitude of an orthodontic force. Based on our results, the applied force magnitude must be reduced in proportion of degree of HBL.

Keywords: bone remodeling, finite element method, horizontal bone loss, orthodontic tooth movement.

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Authors: Naqoosh Haidry

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Objective & Goal: Enucleation of the maxillomandibular cysts will lead to the creation of post-surgical bone defects which may take more than a year for complete bone healing. The use of bone grafts is common to aid bone regeneration in large defects. The study aimed to evaluate the healing and bone formation capabilities of polymer of injectable platelet fibrin (i-PRF) and hydroxyapatite (HA) as bone graft substitute in maxilla-mandibular postsurgical defects compared to hydroxyapatite alone. The primary objective was to find out the clinical and radiological assessment of healing postoperatively and compare the outcome of both groups. Material and Methods: After surgical enucleation of 19 maxillomandibular cysts/tumors, either HA or HA+ i-PRF graft was adapted to the defect. Clinical outcome variables such as pain (VAS score), edema, and mucosal color were evaluated on postoperative days 01, 03, and 07 while radiological outcome variables such as volume of defect (cc), density of new bone (HU) on computed tomography were evaluated at 2nd and 4th month. The results obtained were tabulated and compared with the inferential analysis. Results: Clinical parameters seem to be better in the HA + i-PRF group, but the result was non-significant. Radiologically, the mean healing ratios were significantly greater in the HA + i-PRF group (63.5 ± 2.34 at 2nd month, 90.3 ± 7.32 at 4th month) compared to the HA group (57.2 ± 5.21at 2nd month, 80.8 ± 5.33 at 4th month). When comparing the mean density of new bone, there was a statistically significant difference with a mean difference of 95.2 HU more in the HA + i-PRF (623 HU ± 42.9) compared to the HA group (528 HU ± 96.5) in 2nd month. Conclusion: The polymer of i-PRF and HA prepared as the sticky bone yields faster and better bone healing in post-enucleation maxillomandibular bony defects as compared to hydroxyapatite alone based on radiological findings till four months.

Keywords: bone defect, density of new bone, hydroxyapatite, injectable platelet rich fibrin, maxillomandibular cysts, surgical defect

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Authors: R. Suresh, C. B. Singh, A. K. Sarda

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Background: Over the decades, several surgical techniques have been developed to treat anal fistulas with variable success rates and complications. Large amount of work has been done in radiofrequency excision of the fistula for several years but no work has been done for ablating the tract. Therefore one can consider for obliteration ofanal fistula by Radiofrequency ablation (RFA). Material and Methods: A randomized controlled clinical trial was conducted at Lok Nayak Hospital, where a total of 40 patients were enrolled in the study and they were randomly assigned to Group I (fistulectomy)(n=20) and Group II (RFA) (n=20). Aim of the study was to compare the efficacy of RFA of fistula versus fistulectomy in the treatment of a low anal fistula and to evaluate RFA as an effective alternative to fistulectomy with respect to time taken for wound healing as primary outcome and post-operative pain, time taken to return to work as secondary outcomes. Patients with simple low anal fistulas, single internal and external opening, not more than two secondary tracts were included. Patients with high complex fistula, fistulas communicating with cavity, fistula due to condition like tuberculosis, Crohn's, malignancy were excluded from the study. Results: Both groups were comparable with respect to age, sex ratio, type of fistula. Themean healing time was significantly shorter in group II (41.02 days) than in group I(62.68 days).The mean operative time was significantly shorter in groupII (21.40 min) than in group I(28.50 min). The mean time taken to return to work was significantly shorter in group II(8.30 days)than in group I(12.01 days).There was no significant difference in the post operative hospital stay, mean postoperative pain score, wound infection and recurrence between the two groups. Conclusion: The patients who underwent RFA of fistula had shorter wound healing time, operative time and time taken to return to work when compared to those who underwent fistulectomy and therefore RFA shows outcome comparable to fistulectomy in the treatment of low anal fistula.

Keywords: fistulectomy, low anal fistula, radio frequency ablation, wound healing

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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Authors: Nataša Šimić, Ljiljana Gregov, Matilda Nikolić, Andrea Tokić, Ana Proroković

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Moral development takes place in six phases which can be divided in a pre-conventional, conventional and post-conventional level. Moral reasoning, as a key concept of moral development theories, involves a process of discernment/inference in doubtful situations. In research to date, education has proved to be a significant predictor of moral reasoning. The aim of this study was to investigate differences in moral reasoning and Kohlberg's phases of moral development between Croatian adolescents with different levels of education. In Study 1 comparisons between the group of secondary school students aged 17-18 (N=192) and the group of university students aged 21-25 (N=383) were made. Study 2 included comparison between university students group (N=69) and non-students group (N=43) aged from 21 to 24 (these two groups did not differ in age). In both studies, the Croatian Test of Moral Reasoning by Proroković was applied. As a measure of moral reasoning, the Index of Moral Reasoning (IMR) was calculated. This measure has some advantages compared to other measures of moral reasoning, and includes individual assessments of deviations from the ‘optimal profile’. Results of the Study 1 did not show differences in the IMR between secondary school students and university students. Both groups gave higher assessments to the arguments that correspond to higher phases of moral development. However, group differences were found for pre-conventional and conventional phases. As expected, secondary school students gave significantly higher assessments to the arguments that correspond to lower phases of moral development. Results of the Study 2 showed that university students, in relation to non-students, have higher IMR. Respecting to phases of moral development, both groups of participants gave higher assessments to the arguments that correspond to the post-conventional phase. Consistent with expectations and previous findings, results of both studies did not confirm gender differences in moral reasoning.

Keywords: education, index of moral reasoning, Kohlberg's theory of moral development, moral reasoning

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Authors: Rosana Goncalves Das Dores, Maira Fonseca, Fernando Finger, Vicente Casali

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Equisetum hyemale L. (horsetail, Equisetaceae) is a medicinal plant used and commercialized in simple paper bags or non-ecological packaging in Brazil. The aim of this work was to evaluate the relation between the bioactive compounds of horsetail stems stored in ecological packages (multi-ply paper sacks) at room temperature. Stems in primary and secondary stage were harvested from an organic estate, on December 2016, selected, measured (length from the soil to the apex (cm), stem diameter at ground level (DGL mm) and breast height (DBH mm) and cut into 10 cm. For the post-harvest evaluations, stems were stored in multi-ply paper sacks and evaluated daily to the respiratory rate, fresh weight loss, pH, presence of fungi / mold, phenolic compounds and antioxidant activity. The analyses were done with four replicates, over time (regression) and compared at 1% significance (Tukey test). The measured heights were 103.7 cm and 143.5 cm, DGL was 2.5mm and 8.4 mm and DBH of 2.59 and 6.15 mm, respectively for primary and secondary stems stage. At both stages of development, in storage in multi-ply paper sacks, the greatest mass loss occurred at 48 h, decaying up to 120 hours, stabilizing at 192 hours. The peak respiratory rate increase occurred in 24 hours, coinciding with a change in pH (temperature and mean humidity was 23.5°C and 55%). No fungi or mold were detected, however, there was loss of color of the stems. The average yields of ethanolic extracts were equivalent (approximately 30%). Phenolic compounds and antioxidant activity were higher in secondary stems stage in up to 120 hours (AATt0 = 20%, AATt30 = 45%), decreasing at the end of the experiment (240 hours). The packaging used allows the commercialization of fresh stems of Equisetum for up to five days.

Keywords: paper sacks, phenolic content, antioxidant activity, medicinal plants, post-harvest, ecological packages, Equisetum

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Authors: S. Djaziri, F. Sket, A. Hynowska, S. Milenkovic

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The use of Fe-Al based intermetallics as an alternative to Cr/Ni based stainless steels is very promising for industrial applications that use critical raw materials parts under extreme conditions. However, the development of advanced Fe-Al based intermetallics with appropriate mechanical properties presents several challenges that involve appropriate processing and microstructure control. A processing strategy is being developed which aims at producing a net-shape porous Fe-based preform that is infiltrated with molten Al or Al-alloy. In the present work, porous Fe-based preforms produced by two different methods (selective laser melting (SLM) and Kochanek-process (KE)) are studied during infiltration with molten aluminum. In the objective to elucidate the mechanisms underlying the formation of Fe-Al intermetallic phases during infiltration, an in-house furnace has been designed for in situ observation of infiltration at synchrotron facilities combining x-ray radiography (XR) and x-ray diffraction (XRD) techniques. The feasibility of this approach has been demonstrated, and information about the melt flow front propagation has been obtained. In addition, reactive infiltration has been achieved where a bi-phased intermetallic layer has been identified to be formed between the solid Fe and liquid Al. In particular, a tongue-like Fe₂Al₅ phase adhering to the Fe and a needle-like Fe₄Al₁₃ phase adhering to the Al were observed. The growth of the intermetallic compound was found to be dependent on the temperature gradient present along the preform as well as on the reaction time which will be discussed in view of the different obtained results.

Keywords: combined synchrotron radiography and diffraction, Fe-Al intermetallic compounds, in-situ molten Al infiltration, porous solid Fe preforms

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Authors: Vaishali Joshi, Pallav Joshi

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The main objective of this study is to examine the fashion consumption behavior of females with respect to their age group. Differences were studied in the pre-purchase, purchase and post-purchase behavior of females belonging to three age cohorts such as Generation X, Generation Y, and Generation Z. Quantitative approach was used to conduct this research. Data was collected through structured questionnaire. The questionnaire consisted of three sections. Section one included a question of the source of information of purchasing fashion apparels which measure the pre-purchase behavior. Section two measures purchase behavior which included two questions: i. motivations for purchasing fashion apparel and ii. important attributes considered for purchasing fashion apparel. The last section included a question regarding disposal of fashion apparel which measures the post-purchase behavior. Hundred females were selected as the respondents for this study through convenience sampling in the fashion streets. They were categorized into three age groups and then the results were analyzed. Four hypotheses were developed after reviewing the existing literature. Regression analysis was conducted for testing the hypothesis. Hypothesis one was accepted which stated that ‘social influence’ as a source of information for purchasing fashion apparels decreases with age. Hypothesis two was accepted which suggested that motivation of ‘Attention seeking’ for purchasing fashion apparel decreases with age. Hypothesis three and four also accepted which suggested that the importance of ‘Quality’ and ‘Price’ increases with age but hypothesis five was rejected which suggested that the importance of ‘Fit’ increases with age and last but not the least hypothesis six was accepted which suggested that the ‘duration’ of using fashion apparel increases with age. Limitation of the study deals with the sample of only female respondents. Implication can be made from this research in the field of Fashion apparel industry with respect to consumer segmentation and better marketing approaches can be implemented by the marketers form this study. Further research can be concluded by including male respondents also.

Keywords: fashion, consumption behavior, age cohorts, motivation

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Debananda Mohapatra, Subramanya Badrayyana, Smrutiranjan Parida

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Carbon nano-onions (CNOs) are the spherical graphitic nanostructures composed of concentric shells of graphitic carbon can be hypothesized as the intermediate state between fullerenes and graphite. These are very important members in fullerene family also known as the multi-shelled fullerenes can be envisioned as promising supercapacitor electrode with high energy & power density as they provide easy access to ions at electrode-electrolyte interface due to their curvature. There is still very sparse report concerning on CNOs as electrode despite having an excellent electrodechemical performance record due to their unavailability and lack of convenient methods for their high yield preparation and purification. Keeping all these current pressing issues in mind, we present a facile scalable and straightforward flame synthesis method of pure and highly dispersible CNOs without contaminated by any other forms of carbon; hence, a post processing purification procedure is not necessary. To the best of our knowledge, this is the very first time; we developed an extremely simple, light weight, novel inexpensive, flexible free standing pristine CNOs electrode without using any binder element. Locally available daily used cotton wipe has been used for fabrication of such an ideal electrode by ‘dipping and drying’ process providing outstanding stretchability and mechanical flexibility with strong adhesion between CNOs and porous wipe. The specific capacitance 102 F/g, energy density 3.5 Wh/kg and power density 1224 W/kg at 20 mV/s scan rate are the highest values that ever recorded and reported so far in symmetrical two electrode cell configuration with 1M Na2SO4 electrolyte; indicating a very good synthesis conditions employed with optimum pore size in agreement with electrolyte ion size. This free standing CNOs electrode also showed an excellent cyclic performance and stability retaining 95% original capacity after 5000 charge –discharge cycles. Furthermore, this unique method not only affords binder free - freestanding electrode but also provide a general way of fabricating such multifunctional promising CNOs based nanocomposites for their potential device applications in flexible solar cells and lithium-ion batteries.

Keywords: binder-free, flame synthesis, flexible, carbon nano onion

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Authors: Laura Rueda-Gensini, Jader Rodríguez, Juan C. Cruz, Carolina Munoz-Camargo

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There is an emerging interest in botanicals and plant extracts for medicinal practices due to their widely reported health benefits. A large variety of phytochemicals found in plants have been correlated with antioxidant, immunomodulatory, and analgesic properties, which makes plant-derived products promising candidates for modulating the progression and treatment of numerous diseases. Non-centrifugal cane sugar (NCS), in particular, has been known for its high antioxidant and nutritional value, but composition-wise variability due to changing environmental and processing conditions have considerably limited its use in the nutraceutical and biomedical fields. This work is therefore aimed at assessing the effect of thermal exposure during NCS production over its bioactive composition and, in turn, its therapeutic value. Accordingly, two modified dehydration methods are proposed that employ: (i) vacuum-aided evaporation, which reduces the necessary temperatures to dehydrate the sample, and (ii) window refractance evaporation, which reduces thermal exposure time. The biochemical composition of NCS produced under these two methods was compared to traditionally-produced NCS by estimating their total polyphenolic and protein content with Folin-Ciocalteu and Bradford assays, as well as identifying the major phenolic compounds in each sample via HPLC-coupled mass spectrometry. Their antioxidant activities were also compared as measured by their scavenging potential of ABTS and DPPH radicals. Results show that the two modified production methods enhance polyphenolic and protein yield in resulting NCS samples when compared to traditional production methods. In particular, reducing employed temperatures with vacuum-aided evaporation demonstrated to be superior at preserving polyphenolic compounds, as evidenced both in the total and individual polyphenol concentrations. However, antioxidant activities were not significantly different between these. Although additional studies should be performed to determine if the observed compositional differences affect other therapeutic activities (e.g., anti-inflammatory, analgesic, and immunoprotective), these results suggest that reducing thermal exposure holds great promise for the production of natural products with enhanced nutritional value.

Keywords: non-centrifugal cane sugar, polyphenolic compounds, thermal processing, antioxidant activity

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Authors: Shoba Bandi-Rao

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The lack of college readiness is one of the major contributors to low graduation rates at community colleges, especially among educationally and financially disadvantaged students. About 45% of underprepared high school graduates are required to complete ‘remedial’ reading/writing courses before they can begin taking college-level courses. Mobile apps present ‘bite-size’ learning materials that can be useful for practicing certain literacy skills, such as vocabulary learning. The convenience of mobile phones is ideal for a majority of students at community colleges who hold full or part-time jobs. Mobile apps allow students to learn during small ‘chunks’ of time available to them outside of the class—during subway commute, between classes, etc. Learning with mobile apps is a relatively new area in research, and their effectiveness for learning new words has been inconclusive. Using Mishra & Koehler’s TPCK theoretical framework, this study explored the effectiveness of the mobile app (Quizlet) for learning one hundred common college-level words in ‘remedial’ writing class over one semester. Each week, before coming to class, students studied a list of 10-15 words presented in context within sentences. Students came across these words in the article they read in class making their learning more meaningful. A pre and post-test measured the number of words students knew, learned and remembered. Statistical analysis shows that students performed better by 41% on the post-test indicating that the mobile app was helpful for learning words. Students also completed a short survey each week that sought to determine the amount of time students spent on the vocabulary app. A positive correlation was found between the amount of time spent on the mobile app and the number of words learned. The goal of this research is to capitalize on the convenience of smartphones to (1) better prepare them for college-level course work, and (2) contribute to current literature on mobile learning.

Keywords: mobile learning, vocabulary learning, literacy skills, Quizlet

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Authors: Hosia T. Pule, Julius T. Tjelele, Michelle J. Tedder, Dawood Hattas

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Acceptability of plant material to herbivores is influenced by, among other factors; nutrients, plant secondary metabolites and growth stage of the plants. However, the effect of these factors on Seriphium plumosum L. acceptability to livestock is still not clearly understood, despite its importance in managing its encroachment in grassland communities. The study used 2 x 2 x 2 factorial analysis of variance to investigate the effect of season (wet and dry), fire, slope position (top and bottom) and their interaction on Seriphium plumosum chemistry. We tested the hypothesis that S. plumosum chemistry varies temporally, spatially and pre- and post-fire treatment. Seriphium plumosum edible material was collected during the wet and dry season from burned and unburned areas on both top and bottom slopes before being analysed for protein (CP) content, neutral detergent fibre (NDF), total phenolics (TP) and condensed tannins (CT). Season had a significant effect on S. plumosum protein content, neutral detergent fibre, total phenolics and condensed tannins. Fire had a significant effect on CP. Interaction of season x fire had a significant effect on NDF and CP (p < 0.05). Seriphium plumosum in the wet season (6.69% ± 0.20 (SE)) had significantly higher CP than in the dry season (5.22% ± 0.13). NDF was significantly higher (58.01% ± 0.41) in the dry season than in the wet season (53.17% ± 0.34), while TP were significantly higher in the dry season (14.44 mg/gDw ± 1.03) than in the wet season (11.08 mg/gDw ± 1.07). CT in the wet season were significantly higher (1.56 mg/gDw ± 0.13) than in the dry season (1 mg/gDw ± 0.03). CP was significantly higher in burned (6. 31 % ± 0.22) than in unburned S. plumosum edible material (5.60 % ± 0.15). Seriphium plumosum CP was significantly higher in wet season x burned (7.34 % ± 0.31) than wet season x unburned (6.08 % ± 0.20) material and dry season x burned (5.34 % ± 0.18) and unburned (5.09 % ± 0.18) material were similar. NDF was similar in dry season x burned (58.31% ± 0.54) and dry season x unburned (57.69 % ± 0.62) material and significantly higher than similar wet season x burned (52.43% ± 0.45) and wet season x post-unburned (53.88% ± 0.47) material. This study suggests integrating fire, browsers, and supplements as encroacher S. plumosum control agents, especially in the wet season, following fire due to high S. plumosum CP content.

Keywords: acceptability, chemistry, edible material, encroachment, phenolics, tannins

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Vineet Agrawal, Deepanjali S., Medha R., Subitha L.

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Background. Hospital malnutrition is a highly prevalent issue and is known to increase the morbidity, mortality, length of hospital stay, and cost of care. In India, studies on hospital malnutrition have been restricted to ICU, post-surgical, and cancer patients. We designed this study to assess the impact of hospital malnutrition on 30-day post-discharge and in-hospital mortality in patients admitted in the general medicine department, irrespective of diagnosis. Methodology. All patients aged above 18 years admitted in the medicine wards, excluding medico-legal cases, were enrolled in the study. Nutritional assessment was done within 72 h of admission, using Subjective Global Assessment (SGA), which classifies patients into three categories: Severely malnourished, Mildly/moderately malnourished, and Normal/well-nourished. Anthropometric measurements like Body Mass Index (BMI), Triceps skin-fold thickness (TSF), and Mid-upper arm circumference (MUAC) were also performed. Patients were followed-up during hospital stay and 30 days after discharge through telephonic interview, and their final diagnosis, comorbidities, and cause of death were noted. Multivariate logistic regression and cox regression model were used to determine if the nutritional status at admission independently impacted mortality at one month. Results. The prevalence of malnourishment by SGA in our study was 67.3% among 395 hospitalized patients, of which 155 patients (39.2%) were moderately malnourished, and 111 (28.1%) were severely malnourished. Of 395 patients, 61 patients (15.4%) expired, of which 30 died in the hospital, and 31 died within 1 month of discharge from hospital. On univariate analysis, malnourished patients had significantly higher morality (24.3% in 111 Cat C patients) than well-nourished patients (10.1% in 129 Cat A patients), with OR 9.17, p-value 0.007. On multivariate logistic regression, age and higher Charlson Comorbidity Index (CCI) were independently associated with mortality. Higher CCI indicates higher burden of comorbidities on admission, and the CCI in the expired patient group (mean=4.38) was significantly higher than that of the alive cohort (mean=2.85). Though malnutrition significantly contributed to higher mortality on univariate analysis, it was not an independent predictor of outcome on multivariate logistic regression. Length of hospitalisation was also longer in the malnourished group (mean= 9.4 d) compared to the well-nourished group (mean= 8.03 d) with a trend towards significance (p=0.061). None of the anthropometric measurements like BMI, MUAC, or TSF showed any association with mortality or length of hospitalisation. Inference. The results of our study highlight the issue of hospital malnutrition in medicine wards and reiterate that malnutrition contributes significantly to patient outcomes. We found that SGA performs better than anthropometric measurements in assessing under-nutrition. We are of the opinion that the heterogeneity of the study population by diagnosis was probably the primary reason why malnutrition by SGA was not found to be an independent risk factor for mortality. Strategies to identify high-risk patients at admission and treat malnutrition in the hospital and post-discharge are needed.

Keywords: hospitalization outcome, length of hospital stay, mortality, malnutrition, subjective global assessment (SGA)

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Halima Sadia Qureshi, Urooj Sadiq, Noshi Eram Zaman

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The goal of this study was to see how cognitive behavior hypnotherapy affected nonsuicidal self-injury. DSM 5 invites the researchers to explore the newly added condition under the chapter of conditions under further study named Nonsuicidal self-injury disorder. To date, no empirical sound intervention has been proven effective for NSSI as given in DSM 5. Nonsuicidal self-injury is defined by DSM 5 as harming one's self physically, without suicidal intention. Around 7.6% of teenagers are expected to fulfill the NSSI disorder criteria. 3 Adolescents, particularly university students, account for around 87 percent of self-harm studies. Furthermore, one of the risks associated with NSSI is an increased chance of suicide attempts, and in most cases, the cycle repeats again. 6 The emotional and psychological components of the illness might lead to suicide, either intentionally or unintentionally. 7 According to a research done at a Pakistani military hospital, over 80% of participants had no intention of committing suicide. Furthermore, it has been determined that improvements in NSSI prevention and intervention are necessary as a stand-alone strategy. The quasi-experimental study took place in Islamabad and Rawalpindi, Pakistan, from May 2019 to April 2020 and included students aged 18 to 25 years old from several institutions and colleges in the twin cities. According to the Diagnostic and Statistical Manual of Mental Disorders 5th edition, the individuals were assessed for >2 episodes without suicidal intent using the intentional self-harm questionnaire. The Clinician Administered Nonsuicidal Self-Injury Disorder Index (CANDI) was used to assess the individual for NSSI condition. Symptom checklist-90 (SCL-90) was used to screen the participants for differential diagnosis. Mclean Screening Instrument for Borderline Personality Disorder (MSI-BPD) was used to rule out the BPD cases. The selected participants, n=106 from the screening sample of 600, were selected. They were further screened to meet the inclusion and exclusion criteria, and the total of n=71 were split into two groups: intervention and control. The intervention group received cognitive behavior hypnotherapy for the next three months, whereas the control group received no treatment. After the period of three months, both the groups went through the post assessment, and after the three months’ period, follow-up assessment was conducted. The groups were evaluated, and SPSS 25 was used to analyse the data. The results showed that each of the two groups had 30 (50 percent) of the 60 participants. There were 41 males (68 percent) and 19 girls (32 percent) in all. The bulk of the participants were between the ages of 21 and 23. (48 percent). Self-harm events were reported by 48 (80 percent) of the pupils, and suicide ideation was found in 6 (ten percent). In terms of pre- and post-intervention values (d=4.90), post-intervention and follow-up assessment values (d=0.32), and pre-intervention and follow-up values (d=5.42), the study's effect size was good. The comparison of treatment and no-treatment groups revealed that treatment was more successful than no-treatment, F (1, 58) = 53.16, p.001. The results reveal that the treatment manual of CBH is effective for Nonsuicidal self-injury disorder.

Keywords: NSSI, nonsuicidal self injury disorder, self-harm, self-injury, Cognitive behaviour hypnotherapy, CBH

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Authors: Tannistha Dasgupta

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This study explores the aspects of second language (L2) spoken fluency that are related to L2 linguistic knowledge and processing skill. It draws on Levelt’s ‘blueprint’ of the L2 speaker which discusses the cognitive issues underlying the act of speaking. However, L2 speaking assessments have largely neglected the underlying mechanism involved in language production; emphasis is given on the relationship between subjective ratings of L2 speech sample and objectively measured aspects of fluency. Hence, in this study, the relation between L2 linguistic knowledge and processing skill i.e. Cognitive Fluency (CF), and objectively measurable aspects of L2 spoken fluency i.e. Utterance Fluency (UF) is examined. The participants of the study are L2 learners of English, studying at high school level in Hyderabad, India. 50 participants with intermediate level of proficiency in English performed several lexical retrieval tasks and attention-shifting tasks to measure CF, and 8 oral tasks to measure UF. Each aspect of UF (speed, pause, and repair) were measured against the scores of CF to find out those aspects of UF which are reliable indicators of CF. Quantitative analysis of the data shows that among the three aspects of UF; speed is the best predictor of CF, and pause is weakly related to CF. The study suggests that including the speed aspect of UF could make L2 fluency assessment more reliable, valid, and objective. Thus, incorporating the assessment of psycholinguistic mechanisms into L2 spoken fluency testing, could result in fairer evaluation.

Keywords: attention-shifting, cognitive fluency, lexical retrieval, utterance fluency

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Authors: Farzaneh Bahrami

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Different indicators, such as modal shares in mobility practices or car ownership, may suggest that the century of car dominance - at least in Europe and North America - is already behind us. If the emergence of the car had radical spatial and social consequences, what would be the implications of its gradual disappearance - which could be expected in the context of ecological consciousness, economic and energetic constraints as a result of both urban policies as well as lifestyle choices? To what extend shall urban experts account for this limited but visible transition from car-dominated systems towards alternative models of mobility in which the individual-motorized mobility (car) is not central; what models of urbanity could be imagined to support such a transformation? We have examined a selection of projects at different scales and within different contexts - new planned cities, dense urban areas or territories of dispersion – whose visions involve a significant shift from the current car system. We have been looking into their tools, strategies and different measures of car reduction, as well as their varied approaches to public space as an inevitable corollary to this change. The car’s dominance was formerly questioned by advocates of public space, rather than through interests in ecological urban design or other urban planning concerns. In the 60s already a universal longing for the qualities of traditional urban space led to a critique of the proliferation of fast roads, and thus the car’s colonization of everyday life. Reclamation of public space as the city’s quintessential social territory reappears today in contemporary discourses and reinforces the shift-provoking trends towards a new urbanity freed from car dominance. In a hypothetical process of the progressive phasing-out of the car, we shall expect fundamental transformations in spatial practices of the city, accompanied by the physical configuration of its public spaces. What will be the main characteristics of the new emerging spaces of sociability and where shall we encounter them? This contribution is an ongoing research within the framework of Post-Car World, an interdisciplinary project that explores the future of mobility through the role of the car.

Keywords: mobility, urbanity, future visions, public space

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Authors: Andrei Nosov

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This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

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Authors: Eyob Seife, Tesfalem Teshome, Bereket Seyoum, Behailu Getachew, Yohans Demis

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Developing countries continue to face preventable communicable diseases, such as vaccine-preventable diseases. The Expanded Programme on Immunization (EPI) was established by the World Health Organization in 1974 to control these diseases. Health data use is crucial in decision-making, but ensuring data quality remains challenging. The study aimed to assess the accuracy ratio, timeliness, and quality index of regular immunization programme data in the Birkod district of the Somali Region, Ethiopia. For poor data quality, technical, contextual, behavioral, and organizational factors are among contributors. The study used a quantitative cross-sectional design conducted in September 2022GC using WHO-recommended data quality self-assessment tools. The accuracy ratio and timeliness of reports on regular immunization programmes were assessed for two health centers and three health posts in the district for one fiscal year. Moreover, the quality index assessment was conducted at the district level and health facilities by trained assessors. The study found poor data quality in the accuracy ratio and timeliness of reports at all health units, which includes zeros. Overreporting was observed for most facilities, particularly at the health post level. Health centers showed a relatively better accuracy ratio than health posts. The quality index assessment revealed poor quality at all levels. The study recommends that responsible bodies at different levels improve data quality using various approaches, such as the capacitation of health professionals and strengthening the quality index components. The study highlighted the need for attention to data quality in general, specifically at the health post level, and improving the quality index at all levels, which is essential.

Keywords: Birkod District, data quality, quality index, regular immunization programme, Somali Region-Ethiopia

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Anastasia Papachristou, Anastasia Ntikoudi, Vasileios Saridakis

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The safety and health care needs of refugees have become an increasingly important issue all over the world especially during last few decades. Wars are the primary reason for refugees to leave their countries. Moreover, refugees are frequently exposed to a variety of stressors such as socioeconomic disadvantages, poverty, changes in family structure and functioning, losing social support, difficulty to access education, living in very crowded places, experiencing racism and isolation. This systematic review included research studies published between 2007-2017 from the search databases Medline, Scopus, Cinahl and PubMed, with keywords 'war survivors', 'war trauma', 'psychiatric disorders', 'refugees'. In order to meet the purpose of the systematic review, further research for complementary studies was conducted into the literature references of the research articles included in this study that would meet the criteria. Overall, 14 studies were reviewed and evaluated. The majority of them demonstrated that the most common psychiatric disorders observed among war refugees are post-traumatic stress disorder (PTSD), depression, anxiety and multiple somatic complaints. Moreover, significant relationship was shown between the number of traumatic events experienced by the refugees and sociodemographic features such as gender, age and previous family history of any psychological disorder. War violence is highly traumatic, causing multiple, long-term negative outcomes such as the aforementioned psychiatric disorders. The number of the studies reviewed in this systematic review is not representative of the problem and its significance. The need for care of the survivors and their families is vital. Further research is necessary in order to clarify the role of predictive factors in the development and maintenance of post-traumatic stress and the rest psychiatric disorders following war trauma. In conclusion, it is necessary to have large multicenter studies in the future in order to be able to draw reliable conclusions about the effects of war.

Keywords: psychiatric disorders, refugees, war survivors, war trauma

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Authors: Venkatgiri, Ranganath, L. Nagaraja, B. N. Sagar Pandav, S. M. Usturge, D. Dilipkumar, B. V. Shivprakash, B. Bhagwanthappa, D. Jahangir

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A comparative evaluation of Tramadol and Pentazocine as a pre-emptive analgesic in clinical cases of female dogs undergoing ovariohysterectomy was undertaken during this study. During the study, the following parameters were assessed viz., Rectal temperature (ᵒF), Respiratory rate (breaths/min) and Heart rate (beats/min). Hematological and biochemical parameters viz., total erythrocyte count (TEC) (millions/cmm), hemoglobin (g %), otal leucocytes count (TLC) (thousands/cmm), differential leucocytes count (DLC) (%), serum creatinine (mg/dl), plasma protein (mg/dl), blood glucose (mg/dl) was estimated before the surgery and after administration of general anaesthesia and immediate postoperative periods of 0, 12 and 24 hr respectively. Mean Total Pain Score (MTPS) includes measurement of parameters like posture, vocalization, activity level, response to palpation and agitation at different intervals was calculated before surgery and after administration of general anesthesia and post-operative periods of 1, 2, 4, 6, 12hrs and 24 hrs respectively. Mean Total Pain Score (MTPS) was given for each parameter (Posture, Vocalization, Activity Level, Response to Palpation and Agitation) like 0,1,2,3. (maximum score will be given was 4.). Results were revealed in all three groups including control group. There were significant minor alterations in physiological, hematological and biochemical parameters. MTPS (mean total pain score) were revealed and found a significant alteration when compared with control group. In conclusion, Tramadol found to be a better analgesic and had up to 8hrs of analgesic effect and Pentazocine is superior in post-operative pain management when compared to Tramadol because this group of dogs experienced less surgical stress, consumed less anesthetic dose, they recovered early, and they had less MTPS score.

Keywords: dog, pentazocine, tramadol, ovariohysterectomy

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Basil Nkosilathi Dube, Wilson R. Nyemba, Panashe Mandevu

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In highway driving, over 50 percent of the power produced by the engine is used to overcome aerodynamic drag, which is a force that opposes a body’s motion through the air. Aerodynamic drag and thus fuel consumption increase rapidly at speeds above 90kph. It is desirable to minimize fuel consumption. Aerodynamic drag reduction in highway driving is the best approach to minimize fuel consumption and to reduce the negative impacts of greenhouse gas emissions on the natural environment. Fuel economy is the ultimate concern of automotive development. This study aims to design and analyze drag-reducing devices for a Mazda T3500 truck, namely, the cab roof and rear (trailer tail) fairings. The aerodynamic effects of adding these append devices were subsequently investigated. To accomplish this, two 3D CAD models of the Mazda truck were designed using the Design Modeler. One, with these, append devices and the other without. The models were exported to ANSYS Fluent for computational fluid dynamics analysis, no wind tunnel tests were performed. A fine mesh with more than 10 million cells was applied in the discretization of the models. The realizable k-ε turbulence model with enhanced wall treatment was used to solve the Reynold’s Averaged Navier-Stokes (RANS) equation. In order to simulate the highway driving conditions, the tests were simulated with a speed of 100 km/h. The effects of these devices were also investigated for low-speed driving. The drag coefficients for both models were obtained from the numerical calculations. By adding the cab roof and rear (trailer tail) fairings, the simulations show a significant reduction in aerodynamic drag at a higher speed. The results show that the greatest drag reduction is obtained when both devices are used. Visuals from post-processing show that the rear fairing minimized the low-pressure region at the rear of the trailer when moving at highway speed. The rear fairing achieved this by streamlining the turbulent airflow, thereby delaying airflow separation. For lower speeds, there were no significant differences in drag coefficients for both models (original and modified). The results show that these devices can be adopted for improving the aerodynamic efficiency of the Mazda T3500 truck at highway speeds.

Keywords: aerodynamic drag, computation fluid dynamics, fluent, fuel consumption

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Authors: Mohammad A. Bani-Khaled

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In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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