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With the fast advancement of AI technology in recent years, many excellent Data Augmentation (DA) approaches have been investigated to increase data efficiency in Natural Language Processing (NLP). The reliance on a large amount of data prohibits NLP models from performing tasks such as labelling enormous amounts of textual data, which require a substantial amount of time, money, and human resources; hence, a better model requires more data. Text DA technique rectifies the data by extending it, enhancing the model's accuracy and resilience. A novel lexical-based matching approach is the cornerstone of this work; it is used to improve the quality of the Machine Translation (MT) system. This study includes resource-rich Indic (i.e., Indo-Aryan and Dravidian language families) to examine the proposed techniques. Extensive experiments on a range of language pairs depict that the proposed method significantly improves scores in the enhanced dataset compared to the baseline system's BLEU, METEOR and ROUGE evaluation scores. [ABSTRACT FROM AUTHOR]

The accumulation of damage due to repeated loading is considered as the primary reason for the fatigue cracking of bituminous pavements. Due to the intermittent nature of loading in the field, the bituminous mixtures tend to heal during the rest period resulting in increased fatigue life. The healing of the bituminous mixtures is predominantly governed by the binder component, and hence quantifying the healing potential of the binder is indicative of the healing potential of the mix. Currently, the increased use of recycled asphalt pavements (RAP) in new construction, as well as rehabilitation has triggered the use of rejuvenators for restoring the RAP binder properties. As such, the rheological and physico-chemical evaluation of blender RAP binders (with rejuvenators) is critical. In the present study, four different rejuvenators are used for rejuvenating the RAP binder, which include two types of Paraffinic oils, Tall oils and Fatty acids. The healing potential of the RAP binder blended with different rejuvenators is investigated with the help of Linear Amplitude Sweep (LAS) tests carried out in two ways. The first method is a continuous LAS test without any rest period and the second method incorporates rest periods of various duration at different damage levels. The advantages of incorporating rest periods in a LAS test have been quantified in terms of improved binder healing potential. In addition, the physico-chemical properties of the blended RAP binders were assessed through SARA analysis. An attempt has been made to explain the fatigue performance and healing potential of blended RAP binders in LAS tests by virtue of their chemical composition obtained from physico-chemical analysis (SARA analysis). Also, the effectiveness of various rejuvenators in improving the healing potential of RAP binders has been evaluated. [ABSTRACT FROM AUTHOR]

Networked computers can potentially support classrooms to be more interactive. It can help students share representations amongst themselves and work together on a shared virtual activity space. In research on the role of shared screens or shared virtual workspace in learning settings, there has been less attention paid to contexts where learners are co-located. This paper looks at the impact of the shared screen in a computational game environment on mathematics learning and practices and the construction of learners' emotions and social status in classroom interactions. We designed two versions of a simple arithmetic game: a solo version in which the student played the game alone and a multi-player version in which the screen was shared, and the players could see the arithmetic moves of the other players. We implemented these two versions of the game in a 4th-grade classroom in a suburban school in a large metropolis in India. Classroom sessions were video recorded, computer logs were collected, and field notes were taken. Focus group sessions were held with the students. We coded a portion of the data to get at patterns of classroom interactions. Then we drew on qualitative video analysis tools to analyze specific episodes to understand the fine timescale dynamics of dominant interaction patterns in each setting. Our analysis shows that the shared screen served as a shared memory device, keeping a record of all the students' posts, and was entangled in the moment-to-moment dynamics of self- and peer- assessments of arithmetic. These findings suggest that thoughtful integration of networked digital tools in computer-supported learning environments can increase student–student interactions and support disciplinary learning. [ABSTRACT FROM AUTHOR]

Carbon in many different forms especially, Graphene, Carbon nanotubes (CNTs), and Fullerene is emerging as an important material in the areas of the biomedical field for various applications. This review comprehensively describes the nano antibiotic effect of carbon-based nanocomposites: epicenter on graphene, carbon nanotubes, and fullerene Composites. It summarises the studies conducted to evaluate their antimicrobial applications as they can disrupt the cell membrane of bacteria resulting in cell death. The initial section gives a glimpse of both "Gram"—positive and negative bacteria, which have been affected by Graphene, CNTs, and Fullerene-based nanocomposites. These bacteria include Staphylococcus Aureus, Bacillus Thuringiensis, Enterococcus faecalis, Enterococcus faecium, Bacillus subtilis, Escherichia coli, Klebseilla pneumoniae, Pseudomonas aeroginosa, Pseudomonas syringae, Shigella flexneri,Candida Albicans, Mucor. Another section is dedicated to the insight of Graphene, and its types such as Graphene Oxide (GO), Reduced graphene oxide (rGO), Graphene Nanoplatelets (GNPs), Graphene Nanoribbons (GNRs), and Graphene Quantum Dots (GQDs). Insight into CNT, including both the types SWCNT and MWCNT, studied, followed by understanding fullerene is also reported. Another section is dedicated to the antibacterial mechanism of Graphene, CNT, and Fullerene-based nanocomposites. Further, an additional section is dedicated to a comprehensive review of the antibacterial characteristics of Graphene, CNT, and nanocomposites based on fullerene. Future perspectives and recommendations have also been highlighted in the last section. [ABSTRACT FROM AUTHOR]

One of the most prevalent forms of tumor found in males all over the world is prostate cancer. The main risk factors are age and family history. Magnetic Resonance Imaging (MRI) is highly recommended for detecting and localizing prostate cancer. It is very important for precise segmentation of the prostate region in MRI scans to improve the treatment possibilities and the chance of patient survival with prostate cancer. Manually segmenting the prostate region is a daunting task and often time-consuming because of the variation in shapes of prostates among patients, poor delineation of the boundary, and the use of different MRI modes. In this paper, we propose an automatic segmentation model for the prostate regions in MRI scans based on Unet and Xception net. To boost the performance of model, local residual connections are added in the decoder stage of the Unet. The empirical results are compared to different Unet based models with different preprocessing methods to assess the effectiveness of the proposed model. The experimentations are performed to support the fact that the proposed model performs better than other methods taken under study. [ABSTRACT FROM AUTHOR]

Computational materials discovery efforts are enabled by large databases of properties derived from high-throughput density functional theory (DFT), which now contain millions of calculations at the generalized gradient approximation (GGA) level of theory. It is now feasible to carry out high-throughput calculations using more accurate methods, such as meta-GGA DFT; however recomputing an entire database with a higher-fidelity method would not effectively leverage the enormous investment of computational resources embodied in existing (GGA) calculations. Instead, we propose here a general procedure by which higher-fidelity, low-coverage calculations (e.g., meta-GGA calculations for selected chemical systems) can be combined with lower-fidelity, high-coverage calculations (e.g., an existing database of GGA calculations) in a robust and scalable manner. We then use legacy PBE(+U) GGA calculations and new r2SCAN meta-GGA calculations from the Materials Project database to demonstrate that our scheme improves solid and aqueous phase stability predictions, and discuss practical considerations for its implementation. [ABSTRACT FROM AUTHOR]

Due to the increasing complexity of manufacturing processes and automation, maintenance of all machines and equipments has become challenging task for production managers today. Due to lack of sensitivity for maintenance, share of maintenance cost in total product cost is also increasing along with decreased productivity. Organizations are either quite slow or getting failed in updating their maintenance systems with time. Keeping in view the importance of maintenance in today's context, this study has tried to develop a framework for a sustainable maintenance system for manufacturing organizations. Usually organizations are not able to identify critical factors for effective maintenance. Therefore, in this context, the study has identified fourteen factors for the effective maintenance management from the literature review. Some of these factors are process oriented and some are result oriented. Interpretive structural modeling approach is applied for the development of structural relationship among the factors from a strategic perspective. Fuzzy MICMAC analysis is then carried out to categorize these factors based on their driving and dependence value. Further to prioritise major driving factors, Technique for order preferences by similarity of an ideal solution approach has been also applied. It is observed that top management support and commitment, strategic planning and implementation, continuous upgradation of maintenance system to reduce manufacturing lead time and cost are major factors to ensure the sustainable competitive advantage. [ABSTRACT FROM AUTHOR]

Amyloidosis secondary to juvenile idiopathic arthritis is a known complication of poorly controlled systemic juvenile idiopathic arthritis (SJIA), occurring in 1–2% of the patients. The IL-6 inhibitor tocilizumab is effective in controlling systemic signs and symptoms of sJIA and may be of therapeutic benefit in secondary amyloidosis. Herein, we report the clinical timeline of a 10-year boy with sJIA and secondary amyloidosis, who showed a sustained improvement of systemic symptoms and a reduction in proteinuria with tocilizumab. Compared to the data on adult patients affected with the secondary amyloidosis, there are very few reports on therapeutic options for the children affected with SJIA and secondary amyloidosis in the paediatric population. While doing a systematic literature search for writing this review, we could only retrieve nine case reports and one case series of the children affected with SJIA and secondary amyloidosis, including five cases which were treated with tocilizumab. We also looked into the clinical and biochemical response to various agents that have been used in the previous cases, including tocilizumab. The available literature and the present case report suggest that tocilizumab may be considered as a safe and effective option to treat SJIA-related secondary amyloidosis. [ABSTRACT FROM AUTHOR]

The heat transfer and flow performance of the plate fin heat sink in a horizontal rectangular channel with dimples and protrusions on the fin surfaces has been experimentally investigated in forced convection. The Nusselt number and friction factor are obtained by varying the system parameters as depth and pitch of the dimples for inline and staggered arrangements. The Reynolds number is considered in the range of 6800 to 15,200. The effect of depth and pitch of dimples are examined under constant heat flux while keeping the constant diameter of dimples. Experimental results indicate that the heat transfer and flow performance of fin array are significantly influenced by increasing the depth of dimples. The heat transfer from fin array is enhanced and the flow resistance is increased by decreasing the pitch ratio (s/d) and increasing the depth ratio (D/d). The maximum fin performance of dimpled fin heat sink corresponds to the staggered arrangement of dimpled heat sink with dimple pitch ratio (s/d) of 2.5 and dimple depth ratio (D/d) of 0.5. [ABSTRACT FROM AUTHOR]

Purpose: Published literature lacks systematic studies on disseminated histoplasmosis in India, and previous reviews on its epidemiology in India were conducted two decades back. Thus, we review the Indian studies published in this century to understand the recent epidemiology of histoplasmosis in India and do a retrospective analysis of all cases diagnosed at our institute. Methods: A literature of review search was done in Pubmed/Medline and Scopus. Studies published during January 2001-December 2015 were considered along with retrospective analysis of cases presented to us. A distinction was made in the clinical presentation of immunocompetent and immunocompromised cases. Results: Ninety-five included studies described 204 cases, and 10 cases from our retrospective analysis were included. The mean age at presentation was 45.1 ± 15.4 years [range 3-83, median 45, interquartile range 37-55], and male-to-female ratio was 6:1. Most cases were reported from northern and northeastern states of India along the rivers Ganges, Yamuna and Brahmaputra and in people associated with agricultural activity. About 33% of cases were immunocompromised, out of which immunosuppression due to HIV was seen in 72% cases. The mean age of presentation was significantly lower in immunocompromised cases (37.9 vs. 49.2 years; p < 0.00001, Mann-Whitney test), and mortality was also higher (10 vs. 27.5%, p = 0.01, Fisher's exact test). Adrenal involvement was in significantly higher proportion of immunocompetent patients compared to immunocompromised population. Conclusions: Disseminated histoplasmosis is being increasingly recognized in India. There is a need to undertake well-designed, analytical studies utilizing appropriate diagnostic modalities to understand the epidemiology of this neglected disease in proper perspective. [ABSTRACT FROM AUTHOR]

In this paper we investigate information-theoretic image coding techniques that assign longer codes to improbable, imprecise and non-distinct intensities in the image. The variable length coding techniques when applied to cropped facial images of subjects with different facial expressions, highlight the set of low probability intensities that characterize the facial expression such as the creases in the forehead, the widening of the eyes and the opening and closing of the mouth. A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effective platform for future emotion categorization experiments. [ABSTRACT FROM AUTHOR]

Grephene is a substance composed of pure carbon with atoms arranged in a regular hexagonal pattern similar to graphite, but in a one-atom thick sheet. It is very light, with a 1-square-meter sheet weighing only 0.77 mg. It is the basic structural element of some carbon allotropes including graphite, charcoal, carbon nanotubes and fullerenes. It has considerable interest over recent years due to its intrinsic mechanical, thermal and electrical properties. Incorporation of small quantity of graphene fillers into polymer can create novel nano-composites with improved structural and functional properties. Recent investigation clearly confirmed that graphene-polymer nano-composites are promising materials with applications ranging from transportation, biomedical systems, sensors, electrodes for solar cells and electromagnetic interference. This review discusses the different methods of manufacturing graphene based composites and also compiles their electrical, mechanical and thermal properties. Many references to the latest work on properties and processing have been cited in this review. [ABSTRACT FROM AUTHOR]

Background: While there has been increasing recognition of the importance of attending to students' views about what counts as knowing and learning a STEM field, surveys that measure these "epistemological" beliefs are often used in ways that implicitly assume the fields, e.g., "physics," to be a single domain about which students might have sophisticated or naïve beliefs. We demonstrate this is not necessarily the case and argue for attending to possible differences in students' epistemological beliefs across different sub-domains of physics. In modern physics and quantum mechanics courses for engineering and physics students, we administered a set of modified Colorado Learning Attitudes about Science Survey (CLASS) items. Each selected item was turned into two items, with the word "physics" changed to "classical physics" in one and "quantum physics" in the other. Results: We found significant splits between students' survey responses about classical vs. quantum physics on some items, both pre- and post-instruction. In classical physics, as compared to quantum physics, students were more likely to report the salience of real-world connections and the possibility of combining mathematical and conceptual reasoning during problem solving. Conclusions: These findings suggest that attending to sub-domain specificity of students' beliefs about physics can be fruitful and ought to influence our instructional choices. [ABSTRACT FROM AUTHOR]

Global scarcity of freshwater has been gearing towards an unsustainable river basin management and corresponding services to the humans. It needs a holistic approach, which exclusively focuses on effective river water quality monitoring and quantification and identification of pollutant sources, in order to address the issue of sustainability. These days, rivers are heavily contaminated due to the presence of organic and metallic pollutants released from several anthropogenic sources, such as industrial effluents, domestic sewage, and agricultural runoff. It is astonishing to note that even in many developing countries, most of these contaminants are carried through open drains, which enter river premises without proper treatment. Such practice not only devastates riverine ecosystem but also gives rise to deadly diseases, such as minimata and cancer in humans. Considering these issues, the present study develops a novel approach towards simultaneous identification of major sources of pollution in the rivers, along with critical pollutants and locations using an advanced hierarchical cluster and multivariate statistical analysis. A systematic approach has been developed by agglomerating both R-mode and Q-mode analysis, which develops monoplots, two-dimensional biplots, rotated component matrices, and dendrograms (using "SPSS" and "Analyse It" software) to reveal relationships among various quality parameters to identify the pollutant sources along with clustering of critical sampling sites and pollutants. A case study of the Ganges River Basin of India has been considered to demonstrate the efficacy and usefulness of the model by analyzing 85 open drains. Both organic and metallic pollutants are analyzed simultaneously as well as separately to get a holistic understanding of all the relationships and to broaden the perspective of water characterization. Results provide a comprehensive guidance to the policy makers and water managers to optimize corrective efforts, minimize further damage, and improve the water quality condition to ensure sustainable development of the river basin. [ABSTRACT FROM AUTHOR]