Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-traumatic cerebral infarction (PTCI), an institutional experience

DOI: 10.4328/ACAM.20221 Received: 2020-05-26 Accepted: 2020-06-26 Published Online: 2020-08-02 Printed: 2021-02-01 Ann Clin Anal Med 2021;12(2):144-149 Corresponding Author: Vikas Chandra Jha, Department of Neurosurgery , All India Institute of Medical Sciences,Patna, India. E-mail: drvikaschandrajha@aiimspatna.org P: 07389831560 Corresponding Author ORCID ID: https://orcid.org/0000-0002-0080-061X Abstract Aim: In this study, we aimed to assess effect of less studied risk factors associated with the development of post-traumatic cerebral infarction (PTCI) as severe systemic injury apart from head injury, length of stay on mechanical ventilation in ICU, sepsis, coagulopathy, DVT together with common risk factors as age, GCS severity, etc. and significance of bedside tool as TCD to detect it earlier and its implication in final clinical outcome in such cases. Material and Methods: 400 patients of head injury treated in our department between July 2018 to July 2019 were included in the study. 28 patients were diagnosed with PTCI. Risk factors for development of PTCI were analysed. Utility of TCD in early detection and clinical management of PTCI was assessed. Results: PTCI was observed in 7 % (28/400) of patients. Among risk factor analysis age (p=0.029), initial Glasgow coma scale score≤8 (p<0.028), decompressive craniotomy (p=0.023) and prolonged ICU stay (0.031) and TCD parameters as MCA velocity≥200cm/s (p≤0.028), PCA velocity≥70cm/s (p=0.025) were significantly associated with PTCI than without it on multivariate regression analysis. Mortality was lower in PTCI cases detected earlier (p<0.09) together with earlier clinical improvement (p<0,009) in neurological features in comparison to cases detected late. Discussion: Prolonged length of stay on a mechanical ventilator with poor GCS is a significant risk factor for the development of PTCI and early detection with a bedside tool as TCD helps in planning management better with a significant improvement in short-term mortality and clinical improvement in such cases.
Splitting and Identifying Czech Compounds: A Pilot Study

We present pilot experiments on splitting and identifying Czech compound words. We created an algorithm measuring the linguistic similarity of two words based on ﬁnding the shortest path through a matrix of mutual estimated correspondences between two phonemic strings. Additionally, a neural compound-splitting tool ( Czech Compound Splitter ) was implemented by using the Marian Neural Machine Translator framework, which was trained on a data set containing 1,164 hand-annotated compounds and about 280,000 synthetically created compounds. In compound splitting, the ﬁrst solution achieved an accuracy of 28% and the second solution achieved 54% on a separate validation data set. In compound identiﬁcation, the Czech Compound Splitter achieved an accuracy of 91%.
Hidden Adversarial Patch Attacks for Optical Flow

Adversarial patches have been of interest to researchers in recent years due to their easy implementation in real world attacks. In this paper we expand upon previous research by demonstrating a new hidden patch attack on optical ﬂow. By altering the transparency during training we can generate patches that are invariant to their background meaning they can be inconspicuously applied using a transparent ﬁlm to any number of objects. This also has the added beneﬁt of reducing training costs when mass producing adversarial objects, since only one trained patch is needed for any application. Although this speciﬁc implementation is demonstrated using a white box attack on optical ﬂow, it can be generalized to other scenarios such as object recognition or semantic segmentation.
Determinants of viral load non-suppression among people living with HIV on antiretroviral therapy in Kumasi, Ghana

www.ghanamedj. org Volume 55 Number 2 June 2021 Copyright © The Author(s). This is an Open Access article under the CC BY license. 111 Determinants of viral load non-suppression among people living with HIV on antiretroviral therapy in Kumasi, Ghana David KO Ansah1, Emmanuel Kumah2, Vitalis Bawontuo1, Peter Agyei-Baffour3 and Emmanuel K Afriyie 4 Ghana Med J 2021; 55(2): 111-117 doi: http://dx.doi. org/10.4314/gmj.v55i2. 3
Enhancing learning in Primary Education with an Interactive Aquarium

Arts have been a vital part of education for years, as they can enhance multiple skills, promote creativity and be integrated with other subjects. Nowadays, with such a high number of computers, tablets and internet accesses at schools, there should be more of an incentive to innovate education with the use of digital art tools. This project aims to showcase the beneﬁts of implementing digital art in the classroom, by creating an interactive art installation that serves as an educational resource. The proposed solution is an online aquarium that runs on a website, to which students can submit their drawings of ﬁsh. These drawings can be given certain feeding and social behaviours. Once submitted, the drawings inhabit the aquar-ium and become animated, interacting with their environment and other submitted sketches according to those behaviours. The result is an artistic experience that students can actively participate in and learn from.
Effects of Sex and 17 β-Estradiol on Cardiac Fibroblast Morphology and Signaling Activities In Vitro

Several studies have demonstrated estrogen’s cardioprotective abilities in decreasing the fibrotic response of cardiac fibroblasts (CFs). However, the majority of these studies are not sex-specific, and those at the cellular level utilize tissue culture plastic, a substrate with a much higher stiffness than physiological conditions. Understanding the intrinsic differences between male and female CFs under more physiologically “healthy” conditions will help to elucidate the divergences in their complex signaling networks. We aimed to do this by conducting a sex-disaggregated analysis of changes in cellular morphology and relative levels of profibrotic signaling proteins in CFs cultured on 8 kPa stiffness plates with and without 17 β-estradiol (E2). Cyclic immunofluorescent analysis indicated that there was a negligible change in cellular morphology due to sex and E2 treatment and that the differences between male and female CFs occur at a biochemical rather than structural level. Several proteins corresponding to profibrotic activity had various sex-specific responses with and without E2 treatment. Single-cell correlation analysis exhibited varied protein–protein interaction across experimental conditions. These findings demonstrate the need for further research into the dimorphisms of male and female CFs to develop better tailored sex-informed prevention and treatment interventions of cardiac fibrosis.
Orbis: Explainable Benchmarking of Information Extraction Tasks

Competitive benchmarking of information extraction methods has considerably advanced the state of the art in this ﬁeld. Nevertheless, methodological support for explainable benchmarking , which provides researchers with feedback on the strengths and weaknesses of their methods and guidance for their development efforts, is very limited. Although aggregated metrics such as F1 and accuracy support comparison of annotators, they do not help in explaining annotator performance. This work addresses the need for explainability by presenting Orbis, a powerful and extensible explainable evaluation framework which supports drill-down analysis, multiple annotation tasks and resource versioning. It, therefore, actively aids developers in better understanding evaluation results and identifying shortcomings in their systems. Orbis currently supports four information extraction tasks: content extraction, named entity recognition, named entity linking and slot ﬁlling. This article introduces a uniﬁed formal framework for evaluating these tasks, presents Orbis’ architecture, and illustrates how it (i) creates simple, concise visualizations that enable visual benchmarking, (ii) supports different visual classiﬁ-cation schemas for evaluation results, (iii) aids error analysis, and (iv) enhances interpretability, reproducibility and explainabil-ity of evaluations by adhering to the FAIR principles, and using lenses which make implicit factors impacting evaluation results such as tasks, entity classes, annotation rules and the target knowledge graph more explicit.
A New Technique to Control Active and Reactive Power for Wind Energy Conversion System under Unbalanced Grid Voltage

In this paper, an innovative control technique for wind power generation for smoothening the stator active or reactive power swell components under unbalanced grid voltage using doubly-fed induction generators (DFIG) is projected. The negative order component of the rotor current is used to diminish the active and reactive power waves, which is extracted by band pass filters. It is revealed that reducing the reactive power ripples can lead to results in the torque ripple reduction. Simulation results shows that the proposed control algorithm can reduce the active or reactive power ripple components as well as reducing the torque and speed ripples.
CUSTOMER RELATIONSHIP MANAGEMENT AN OPPORTUNITY OR BURDEN: A HEALTHCARE SERVICE PERSPECTIVE

Hospitals are one of the major contributors to national GDP. Healthcare is one of India’s largest sectors, and the sector is expected to expand speedily. Indian patients are now capable of paying more to gain health care services of international standards. This change has provided opportunity for healthcare service providers to take share of patient’s healthcare expenditure. For grabbing that opportunity, hospitals have to embrace international technological advances too and customer relationship management is one of such technological strategy. This study has reviewed 40 research articles and white papers for knowing does really CRM provide opportunity to hospitals or it just increases the burden for them. The literature review is presented in three different parts as CRM advantages, CRM issues and CRM in Healthcare.
Approach to Estimation of Hamaker Constant as Taking Hofmeister Effects into Account

The Hamaker constant is an important material parameter for both the description of particle interaction and the prediction of colloidal stability. Existing methods based on the classic Derjaguin–Landau–Verwey–Overbeek theory ignore the Hofmeister effects and would derive flawed results. In this article, approaches to the estimation of the Hamaker constant with and without consideration of the Hofmeister effects were, respectively, suggested, where the Hamaker constant was obtained on the basis of the mathematic relationship between electrostatic repulsive and van der Waals attractive interaction at the critical coagulation concentration (CCC) by using the dynamic light scattering technique. It indicated that the montmorillonite particles aggregation kinetics in the presence of Li+, K+, and Cs+ exhibited remarkable Hofmeister effects and the CCC values show: Li+ (277.2 mM) > K+ (80.3 mM) > Cs+ (27.2 mM). Without consideration of Hofmeister effects, completely distinct Hamaker constants for the same materi.
Operational modal identification based on parallel factor decomposition with the presence of harmonic excitation

One of the main difficulties of the operational modal analysis is to deal with underdetermined problems in which the number of sensors is less than the number of active modes. In the last decade, methods based on the PARAllel FACtor (PARAFAC) decomposition have attracted a lot of attention in the field of modal analysis because it has been proven that these methods can deal with underdetermined cases, as well as the presence of harmonic excitations. Moreover, in combination with kurtosis value as a harmonic indicator, this makes them more efficient in distinguishing between harmonic and structural components. However, it can lead to distorted results as it does not take into account the variation in the length of the covariance functions of the modal coordinates. Since the kurtosis values are estimated from these covariance functions, the length of the latter directly affects the kurtosis. To overcome this limit, the present study proposes to introduce the choice of the length of these functions based on their frequency and damping coefficient. This change improves the existing method by more efficient separating between harmonics and modal components. The proposed procedure is validated using numerical simulations, followed by ambient vibration measurements.
Salicylic acid stimulates the biosynthesis of lignans in the cell suspension culture of Gmelina Arborea Roxb.

Gmelina arborea Roxb. is a well-known timber plant. In addition, it is also used in traditional medicines. The juice of tender leaves mixed with cow's milk and sugar is used as demulcent. Moreover, the various plant parts of G. arborea are also useful in treating gonorrhea, catarrh of the bladder and cough (Tiwari 1995). The medicinal properties of plants, mostly, are due to the presence of a specific secondary metabolite in its tissues. Thus, the presence of an array of secondary metabolites in G. arborea is obvious. The stem bark and heartwood of G. arborea contains phytochemicals such as lignans, alkaloids, flavonoids, saponins, steroids etc. (Nair and Subramanian 1975, Anjaneyulu et al. 1977, Kaswala et al. 2012). Kaswala et al. (2012) has reported a number of lignans including arboreol, isoarboreol, methyl arboreol, gummadiol, gmelanone, arborone and 7-oxodihydrogmelinol from heartwood of the plant. Lignans are anti-cancerous compound effective against breast and prostate cancer (MacRae and Towers 1984). Moreover, they also reinforce durability, longevity and resistance against colon cancer. Lignans have anti-feedant, anti-bacterial and anti-fungal activity in planta (Hano et al. 2005). The plant cell culture has been used by workers for various reasons like for bioassays, to study the metabolic pathways, in rDNA technology and to induce synthesis of commercially important phytochemicals. Production of lignans in cell culture has been reported earlier. In addition, the quantitative enhancement of the lignan production using in vitro techniques like elicitation, addition of biosynthetic precursors, and immobilization has also been reported (Verpoorte et al. 2002, Angelova et al. 2006, Capote 2012, Ramirez-Estrada et al. 2016). Therefore, considering the importance of lignans an investigation was carried out with the aim to study the effect of biotic and abiotic elicitors on the accumulation of lignan in G. arborea cell culture.
Performance Analysis of Heterogeneous Networks in Presence of Deliberate Jammers Using Reverse Frequency Allocation

The demand of high data rate and ubiquitous coverage in heterogeneous cellular (HetNets) is increasing progressively. In order to meet this demand, sophisticated model having applied interference reduction scheme and cell association technique is needed. The small base station (sBS)are deployed inside the broadcasting area of macro base station (mBS), in heterogeneous cellular networks (HetNets). Since mBS has high transmission power therefore a large number of users get connected with mBS. This causes disproportion of load distribution across the HetNets. For load balancing users from high power mBS are migrated to low power sBS to increase network capacity and to decrease the load from mBS. This results in interference in the communication signal because of strong mBS Interference. Hence, we need interference management technique to mitigate interference and user association and to efficiently use sBSs’ resources. Inter-cell interference (ICI) limit the HetNets’ performance. Additionally, there exist deliberate jamming interference which depends on jammers transmission power and its proximity with the target, which notably degrades the network performance. In this paper, we employ reverse frequency allocation scheme (RFA) to reduce inter cell interference, deliberate jamming interference and to accomplish load balancing. The proposed setup is analyzed inquisitively and with the help of simulations. The result shows reduction in interferences as well as balance of load distribution in the network achieved by employing RFA scheme together with cell association.
ON THE STRUCTURE OF PICARD GROUP FOR MOEBIUS LADDER

The notion of the Picard group of a graph (also known as Jacobian group, sandpile group, critical group) was independently given by many authors. This is a very important algebraic invariant of a finite graph. In particular, the order of the Picard group coinsides with the number of spanning trees for a graph. The latter number is known for the simplest families of graphs such as Wheel, Fan, Prism, Ladder and Moebius ladder graphs. At the same time the structure of the Picard group is known only in several cases. The aim of this paper is to determine the structure of the Picard group of the Moebius ladder graphs.
LEVERAGING EDUCATION THROUGH MOBILE APP AND CHATBOT - SKYLANOT

: In today's environment, technology is becoming increasingly significant. One such technology is digital magazines which help teachers and mentors to enhance the learning experience of the students. This technology takes its form in a range of new smart devices and mobile applications which have become extremely useful in the field of academics. In this pandemic situation (COVID-19), right from learning to money transactions, everything has become online. The AIR (Artificial Intelligence & Research) Lab of PSG College of Technology offers to show the infrastructure and works of the students and professors through a mobile app ‘Skylanot’ which helps students to take up projects in the field of Computer Science even in this pandemic situation. Enormous developments have been made in the field of Artificial Intelligence today. Chatbots have gained great attention from researchers and developers. Chatbots are software applications built using Artificial Intelligence (AI), Natural Language Processing (NLP) and Neural Networks (NN)that can simulate a conversation in natural language with the user. Students can learn everything online through various learning environments. One such learning environment is an ML chatbot called Ava which is integrated in the mobile application that helps students learn about Machine Learning. The chatbot ‘Sebastyan’ is also integrated with Skylanot which serves as a virtual assistant to clear the doubts of students regarding AIR Lab. This provides a new and interesting way to learn about Machine Learning which the students would love to do. The Machine Learning Chatbot ‘Ava’ developed by the students of Assam Engineering College is an interactive chatbot which can provide knowledge to the users about Machine Learning. It answers the queries pertaining to Machine Learning by providing insight on various algorithms in ML, the areas where they can be applied and the projects for which applying Machine Learning would be of actual benefit. Platforms are frameworks of services that application programs depend on for performing standard operations. The platform that was used to build the mobile application ‘Skylanot’ is Android Studio. It is an Integrated Development Environment that is used to build mobile applications for android devices. It is developed and maintained by Google. Google’s Dialogflow is the platform that was used to develop the Chatbot ‘Sebastyan’. It is a Natural Language Processing platform that is used to develop chatbots and to integrate the conversational queries of the mobile app with the chatbots.
Transferring Word-Formation Networks Between Languages

We present a method for supervised cross-lingual construction of word-formation networks (WFNs). WFNs are resources capturing derivational, compositional and other relations be-tween lexical units in a single language. Current state-of-the-art methods for automatically creating them typically rely on supervised or unsupervised pattern-matching of aﬀixes in string representations of words, with few recent inroads into deep learning. All methods known to us work purely in a monolingual setting, limiting the use of higher-quality supervised models to high-resource languages. In this paper, we present two methods, one based on cross-lingual word alignments and translation and another based on cross-lingual word embeddings and neural networks. Both methods are capable of transfer of WFNs into languages for which no word-formational data are available. We evaluate our models on manually-annotated word-formation data from the Universal Derivations and UniMorph projects.
Maximum Entropy Models for Σ 1 Sentences

In this paper we investigate the most uninformative models of Σ 1 sentences. We will show that the two main approaches for deﬁning the Maximum Entropy models on ﬁrst order languages are well deﬁned for Σ 1 sentences and that they agree on sets of sentences consisting of only Σ 1 sentences.
DESKTOP BASED APPLICATION FOR CAPTIONING IMAGE AND VIDEO USING DEEP LEARNING

: Methodologies that depend on them Deep Learning has a lot of potential for applications that produce captions or a short summary for images and video frames automatically. In imaging technology, image and video captioning are mentally difficult challenges. Automated caption development for photos and videos for human being with different levels of vision impairment; Among the technology fields are automatic metadata production for videos and images that can be used by online services; robot vision systems; and many others.in The focus of this research is on the algorithmic overlap between images and videos discerption.
Non-Linear Analysis on Transient Heat Transfer in Annular Fin

ISSN: 2455-7994 www.mathsjournal. org Page 1 Non-Linear Analysis on Transient Heat Transfer in Annular Fin J. R. Wadkar *, R. G. Metkar **, B. B. Pandit*** *(Research Scholar, Department of Mathematics, Swami Ramanand Teerth Marathwada University, Nanded, Maharashtra, India. E-mail – jaydeeepwadkar@gmail.com) ** (Department of Mathematics, Indira Gandhi Senior College, Nanded, Maharashtra, India. E-mail rammetkarmath@rediffmail.com) *** (Department of Mathematics, Shri Datta Arts, Commerce and Science College, Hadgaon, Dist. Nanded, Maharashtra, India. E-mail –panditbhagwat51@gmail.com)
ADID-UNET - A segmentation model for 1 COVID-19 infection from lung CT scans 2

16 Currently, the new coronavirus disease (COVID-19) is one of the biggest health crises threatening the world. Automatic detection from computed tomography (CT) scans is a classic method to detect lung infection, but it faces problems such as high variations in intensity, indistinct edges near lung infected region and noise due to data acquisition process.Therefore, this paper proposes a new COVID-19 pulmonary infection segmentation depth network referred as the ADID-UNET (Attention Gate-Dense Network-Improved Dilation Convolution-UNET). The dense network replaces convolution and maximum pooling function to enhance feature propagation and solves gradient disappearance problem. An improved dilation convolution is used to increase the receptive ﬁeld of the encoder output to further obtain more edge features from the small infected regions. The integration of attention gate into the model suppresses the background and improves prediction accuracy. The experimental results show that the ADID-UNET model can accurately segment COVID-19 lung infected areas, with performance measures greater than 80% for metrics like accuracy, speciﬁcity and Dice Coefﬁcient (DC). Further when compared to other state-of-the-art architectures, the proposed model showed excellent segmentation effects with a high DC and F1 score of 0.8031 and 0.82 respectively.