Miracle-dz/UniFAR-FTUs huggingface dataset:
HM2LP: Hybrid Multilevel Multihop LEACH Protocol for Conserving Energy in Large Area WSN

: Wireless Sensor Network (WSN) for a large area is the need of the hour due to ever-growing demand on the fly services in different application fields. More senders deployed in a large area will generate an enormous amount of data and will communicate to the base station (BS). The distance of a device from the BS will affect the energy of the transmitting sensor. While collecting data at the BS required distance of the route to travel by the data packets is also longer. More energy of the nodes is consumed during transmission, reception, and data aggregation phases. Systems designed for small networks perform poorly in large networks due to more energy dissipation. This work proposes using Rendezvous nodes (RN) to reduce energy consumption. The network is divided into grids. Each grid has an RN. All the selected cluster head (CH) sends their data to the RN of its zone, and then the RN transmits this data to the BS. Using this method, the traffic load of the network is reduced. The lifetime of the network is improved, which is the fundamental need of large WSNs. Existing protocols Energy Efficient Sleep Awake Aware (EESAA), Energy Efficient Scalable Routing Algorithm (EESRA), Modified Invasive Weed Optimization Clustering Approach (M-IWOCA), and Low Energy Adaptive Clustering Hierarchy (LEACH) are also implemented in the proposed scenario. Total network lifetime shows growth by 12% using the developed Hybrid Multilevel Multihop LEACH Protocol (HM2LP).
Curcumin Inhibits Papillary Thyroid Cancer Cell Proliferation by Regulating lncRNA LINC00691

Papillary thyroid cancer (PTC) is a type of epithelial-derived differentiated TC that reportedly accounts for a majority of TCs. Curcumin, a polyphenolic compound and a member of the Zingiberaceae (ginger) family derived from turmeric plants, can exhibit anticancer effects. Herein, we aimed to investigate the effect of curcumin on PTC and elucidate underlying mechanisms. Accordingly, PTC B-CPAP cells were treated with curcumin, in combination with/without long noncoding RNA LINC00691 inhibition, to determine the effect of curcumin and its relationship with LINC00691 in PTC cells. We observed that curcumin treatment decreased B-CPAP cell proliferation and promoted apoptosis. Curcumin inhibited LINC00691 expression in B-CPAP cells. Curcumin administration or si-LINC00691 transfection alone promoted ATP levels, inhibited glucose uptake and lactic acid levels, and inhibited lactate dehydrogenase A and hexokinase 2 protein expression in B-CPAP cells, which were further enhanced by combination treatment. Moreover, curcumin administration or si-LINC00691 transfection alone inhibited p-Akt activity, further suppressed by combination treatment. Akt inhibition promoted apoptosis and suppressed the Warburg effect in B-CPAP cells. In conclusion, our findings indicate that curcumin promotes apoptosis and suppresses proliferation and the Warburg effect by inhibiting LINC00691 in B-CPAP cells. The precise molecular mechanism might be mediated through the Akt signaling pathway, providing a theoretical basis for the treatment of PTC with curcumin.
Morphing-Based Reharmonization using LSTM-VAE

We present a method of morphing between reharmonized chord progressions using long short-term memory (LSTM) and a variational autoencoder (VAE). If the reharmonization is automated, begin-ner musicians can easily change impressions of a harmony even without having expert musical knowledge. Morphing between many instances of reharmonization can be a practical approach to generating various rehar-monizations. This study speciﬁcally examines interpolation in the latent space of an LSTM-VAE and achieves morphing between two chord pro-gressions. Experimental results demonstrate that our method generates chord progressions that ﬁt the melody based on interpolation between prepared chord progressions in the latent space obtained through the model.
Modeling of a Rectifier for Power Operation and Design of Control-loop Circuit

In this paper,the small signal modeling of the electric rectifier based on limited double poled control scheme is presented,and the control loop circuit is designed.This scheme overcomes the disadvantage that the range of soft switching is limited by the load current.And this control loop circuit resolves the shortcomings of slow response with conventional voltage-control mode.The circuit is characterized by simplification,credibility and stabilization.
A review on Cloud Computing Issues and Benefits in Higher education institutes

: Organizations around the globe especially the ones in emerging countries are stroked with the issue of providing their services to users with the use of information technology. Universities have faced such issue for the provision of services like teaching, research, learning and development activities in line with the quality of education. Major concern for that is the high cost factor of providing and maintaining the required software and hardware for their system. Technology like cloud computing that works on the model of provisioning IT resources on-demand criteria can be adopted to overcome this problem. This technology ensures improved quality of services linked to IT, as the services are available for users whenever and wherever they want at a reduced cost as they have to pay according to pay per use criteria which can be said as utility-based model. Despite of these advantages, challenges that are associated with its adoption in various sectors especially higher education sector have faced hurdles to commit to cloud computing. This paper identifies various issues and benefits of cloud computing in higher education institutes
Estonian Morphology: What is Learned and How?*

This paper is about some theoretical considerations that one should be aware of when applying quantificational methods for describing Estonian morphology. Estonian is a morphologically rich language, and being available for researchers in the form of various large and tagged text corpora, it should be a good testbed to investigations into the nature of morphology. The paper is based on evidence from text corpora, although it does not rely on very sophisticated statistics. It proposes an alternative view to explain the data that has inspired theories about the dual and single mechanisms for morphological processing, and namely that during learning the morphological rules, the learners overgeneralize from the regularities they see in naturally occurring communication. The paper serves as a preliminary to a lot more counting and calculating that could be done on Estonian text
IJSRD-International Journal for Scientific Research & Development| Vol. 3, Issue 12, 2016 | ISSN (online): 2321-0613

In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. So there is a need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. There are two methods for drowsiness detection. The first one is intrusive methods and the second one is non-intrusive methods. The intrusive methods include measurement of heartbeat rate, mind wave monitoring etc. It is most accurate, but it is not realistic, because sensing electrodes would have to be attached directly onto the user’s body, and hence it would be annoying and distracting the user. while the nonintrusive methods include the yawn detection, eye closure, eye blinking rate, head pose etc. It is realistic because it does not irritate the user while driving because no sensing electrodes would be attached to user’s body. In this paper, various methods are included by which the drowsiness can be detected and warning can be issued to the driver while driving. And also compared different parameters for different methods.
RANLP 2021 Workshop Recent Advances in Natural Language Processing 14th Workshop on Building and Using Comparable Corpora

AI now and in future will have to grapple continuously with the problem of low resource. AI will increasingly be ML intensive. But ML needs data often with annotation. However, annotation is costly. Over the years, through work on multiple problems, we have developed insight into how to do language processing in low resource setting. Following 6 methods—individually and in combination—seem to be the way forward: 1. Artificially augment resource (e.g. subwords) 2. Cooperative NLP (e.g., pivot in MT) 3. Linguistic embellishment (e.g. factor based MT, source reordering) 4. Joint Modeling (e.g., Coref and NER, Sentiment and Emotion: each task helping the other to either boost accuracy or reduce resource requirement) 5. Multimodality (e.g., eye tracking based NLP, also picture+text+speech based Sentiment Analysis) 6. Cross Lingual Embedding (e.g., embedding from multiple languages helping MT, close to 2 above) The present talk will focus on low resource machine translation. We describe the use of techniques from the above list and bring home the seriousness and methodology of doing Machine Translation in low resource settings. Invited Presentation Machine Translation in Low Resource Setting Pushpak Bhattacharyya Computer Science and Engineering Department Indian Institute of Technology Bombay
A Case Report on a Successful Treatment of Profound Proteinuria in a Pediatric Patient with Membranous Nephropathy Secondary to Systemic Lupus Erythematous

Membranous Nephropathy (MN) is a leading cause of nephrotic syndrome in adults. The common etiology of MN in adults is primary form in which approximately 70% of patients express circulating antibodies against Phospholipase A2 Receptor (PLA2R), a podocyte antigen. Although primary MN is relatively uncommon in children, secondary MN occurs in 20% of the children with systemic lupus erythematous nephropathy. Systemic Lupus Erythematous (SLE) is an autoimmune disorder affecting multiple organ systems. Renal involvement is seen in approximately 60-80% of patients. Class V Lupus Nephritis is characterized by nephrotic range proteinuria. Here we discuss the case of a 14-year-old girl born in Thailand with a past medical history of hypothyroidism and Nonalcoholic Steatohepatitis (NASH) who presented to the Emergency Department with anasarca and 25 kg of weight gain in several months. Patient was hypertensive. Physical examination revealed abdominal skin striae, hyperpigmented papules on her arms bilaterally, exanthem on the face and wrists, arthritis and alopecia of the scalp. Laboratory blood work showed patient had an anemia (Hgb of 6.6 g/dL), high levels of Anti-Nuclear Antibody (ANA) (1:2560), low complement C3 (48 mg/dL) and C4 (8.2 mg/dL), and positive dsDNA antibodies. Urine analysis revealed nephrotic range of proteinuria. Renal biopsy revealed negative PLA2R in glomeruli, but positive and diffuse granular/ pseudolinear IgG staining along the glomerular capillary loops by immunofluorescence, the pathologic diagnosis consistent with secondary form of MN due to class V membranous lupus nephritis. Patient started on diuretics and ACE inhibitor for edema and hypertension; steroid, CellCept and Plaquenil for SLE. 4 months after therapy, patient had significant improvement with 25 kg of weight loss. Her 24 hr urine protein decreased from 24 g/day to 3.5 g/day. 8 months after therapy, proteinuria was further reduced to 1 g/day after rituximab infusion.
Learning in a Post-Truth World ∗ ( Forthcoming in Management Science )

Misinformation has emerged as a major societal challenge in the wake of the 2016 U.S. elections, Brexit, and the COVID-19 pandemic. One of the most active areas of inquiry into misinformation examines how the cognitive sophistication of people impacts their ability to fall for misleading content. In this paper, we capture sophistication by studying how misinformation affects the two canonical models of the social learning literature: sophisticated (Bayesian) and naive (DeGroot) learning. We show that sophisticated agents can be more likely to fall for misinformation. Our model helps explain several experimental and empirical facts from cognitive science, psychology, and the social sciences. It also shows that the intuitions developed in a vast social learning literature should be approached with caution when making policy decisions in the presence of misinformation. We conclude by discussing the relationship between misinformation and increased partisanship, and provide an example of how our model can inform the actions of policymakers trying to contain the spread of misinformation.
Supplementary Material: Towards Efficient and Effective Adversarial Training

We first prove that the Nuclear norm forms a uniform upper-bound of the Frobenius norm of a matrix: Theorem 1: Suppose A is any real/complex m× n matrix. Then ||A||∗ ≥ ||A||F . Proof: Let A = UΛV T , be the Singular Value Decomposition of A, where U, V are Unitary square matrices of size m×m and n× n respectively, and Λ is a m× n rectangular diagonal matrix with non-negative entries σ1, σ2, . , which are the singular values of A. As is standard convention, we assume descending order of singular values. Further, if ρ is the rank of matrix A, then σi = 0 for all i > ρ. Then, by definition, ||A||∗ := ∑minm,n i=1 σi = ∑ρ i=1 σi. We now observe that
Design And Fabrication Flow Focusing Microfluidic Device For Continuous Dielectrophoretic Separation

We present a flow focusing microfluidic device for continuous dielectrophoretic separation. Our method relies on our unique microfluidic geometry which performs hydrodynamic focusing, generates flow with three inlets and three outlets. To improve particle separation in array type microelectrode, we hydrodynamically focus the main flow into the region of interest to the gap between the two electrodes. We design the geometry of the device using 3D CAD software and study the fluid flow using Comsol Multiphysics 5.4. Then, we fabricate this microfluidics device using the micro-milling process combine with soft lithography using PDMS. Lastly, we do an experimental flow setup using our microfluidic device to see the hydrodynamic flow focusing within the channel with three different main flow rate ratio to the sheath flow.
TERAHERTZ BAND COMMUNICATIONS AS A NEW FRONTIER FOR DRONE NETWORKS

Terahertz band (0.1‐10 THz) communications is one of the candidates for 6G systems due to intrinsic massive bandwidth and data rate support. Having demonstrated the signi icant potential of THz band at various atmospheric alti‐ tudes, in this article, we discuss the prospects of THz communications for drone networks, more speci ically, for Drone Sensor Networks (DSNs). For 6G non‐terrestrial communication scenarios, drones will not only serve as on‐demand base‐stations, as supporting alternatives or backhauls for the terrestrial base stations, but they will also provide seamless connectivity for distributed monitoring and surveillance applications, which require an ultra‐reliable low latency service for carrying multimedia data. THz band sensing will also provide additional sensing capabilities from the sky to THz‐enabled DSNs. Presenting this vision, in this paper, we irst discuss possible use cases of THz‐enabled drone networks considering communication, sensing and localization aspects. Then, for revealing the capacity potential of THz‐enabled drone networks, we provide motivating channel capacity results for communication of drones at different altitudes, under ideal channel conditions with no fading and realistic channel with beam misalignment and multipath fading. We further present major challenges pertaining to employing the THz band for DSNs, addressing physical layer issues, followed with spectrum and interference management, medium access control and higher layers and security, while reviewing some prominent solutions. Finally, we highlight future research directions with Arti icial Intelligence (AI)/Machine Learning (ML)‐based approaches and mobile edge computing.
In vitro antibacterial study of aqueous and methanolic extracts of some selected medicinal plants

In the present study six aqueous and methanolic plant extracts (Adhatoda vasica, Nyctanthes arbortristis, Phyllanthus amarus, Vitex Negundo, Terminalia arjuna and Terminalia chebula) from botanical species have been subjected to a screening study to detect potential antibacterial activity against Staphylococcus aureus and Escherichia coli. The antibacterial activity of the products was evaluated using colonies growing in solid medium, establishing the zone of inhibition in vitro growth (ZOI). A small portion of the dry extract was used for the phytochemical tests for compounds which include alkaloids, hydrolysable tannins, flavonoids, saponins and glycosides in accordance with the methods. The results showed that extracts from Terminalia arjuna and Terminalia chebula possess strong in vitro antibacterial activity against the tested microorganisms.
A STUDY ON THE FEASIBILITY OF APPLYING IOT TO IRAN WITH AN EMPHASIS ON ENVIRONMENTAL AND HEALTH COMMUNICATION

This paper will address achievements of Web 3.0 recognized as Internet of Things (IoT), and will examine the effects of IoT in the field of health and environment in Iran. IoT is one of the applications of semantic Web that uses layered architecture and is a new platform that was completed in 2020. Web 3.0 makes omnipresence communication possible and can make all electronic apparatuses to communicate with each other while communicating with human agents. It also enables computers to generate data by communicating to each other. This can contribute to developments in many fields and field of health and environment are no exception and probably are on top of priorities. Here, we will launch a documentary study and will focus on IoT and how it is related to the field of health/environment and will enumerate the priorities that can be set in this field if IoT is applied. Some of the priorities that can contribute to prolonging life span, diminishing contagious diseases, facilitating medical care for chronic diseases, child care, preventing life-threatening epidemics, and promoting quality of life among elderly consist of: Diagnosis of falling, caring the physiological state of individuals, monitoring patients remotely, managing chronic diseases and controlling pollutions. Some results indicate: Iran needs to change its approach towards IoT; this will help Iran to respond to its development needs in the field of health and environment with regard to its long-term development plan known as Ofogh 1404 (2025 outlook). One of these needs is to move towards technologies that comply with IoT while taking distance from technologies that are associated with Web 2.0.
Analysing Musical Performance in Videos Using Deep Neural Networks

This paper proposes a method to facilitate labelling of music performance videos with automatic methods (3D-Convolutional Neural Networks) instead of tedious labelling by human experts. In particular, we are interested in the detection of the 17 musical performance gestures generated during the performance (guitar play) of musical pieces which have been video-recorded. In earlier work, these videos have been annotated manually by a human expert according to the labels in the musical analysis methodology. Such a labelling method is time-consuming and would not be scalable to big collections of video recordings. In this paper, we use a 3D-CNN model from activity recognition tasks and adapt it to the music performance dataset following a transfer learning approach. In particular, the weights of the ﬁrst blocks were kept and only the later layers as well as additional classiﬁcation layers were re-trained. The model was evaluated on a set of 17 music performance gestures and reports an average accuracy of 97.9% (F1:77.8%) on the training set and 85.7% (F1:38.6%) on the test set. An additional analysis shows which gestures are particularly diﬃcult and suggest improvements for future work.
The Nexus of India and the Gulf Cooperation Council: The Dynamics of Partnership and Dissension

Strategic partnership represents one of the essential tools of inter-state engagement in International Relations, primarily from the post-Cold War period. Contrary to the erstwhile partnership agreements, the nature of alignment in this rubric demands more cooperation, interaction, flexibility and encompasses both strategic and non-military attributes at a much wide-ranging dimension, by defying the conventional understanding of alliance networks. Within this broad setting, India and the Gulf Cooperation Council (GCC) seek to redefine their partnership with a fresh orientation and nurture a reciprocal relationship through their shared political, historic and cultural linkages. As an emerging economy, India harps on the geo-strategic and geo-economic primacy of the GCC and acknowledges this regional bloc as its promising source of energy and reliable partner in pursuit of its national interest vis-à-vis China and Pakistan. Likewise, the Gulf monarchs are attracted to India’s democratic political tradition and ever-growing significance in world politics and recognize New Delhi’s unequivocal cooperation and support in advancing the politico-economic necessities of the region. This paper examines the efficacy of strategic, energy, maritime and economic security realms, and cultural quotients as crucial determinants behind the success of strategic partnership that these two regional powers seek to solidify in this polycentric world, drawing from the theoretical framework of alliance formation both from the Cold War and post-Cold War perspectives. This article also unravels the presence of divergences that affect their relationship and concludes by highlighting the significance of India-GCC partnership as the representation of South-South cooperation in this critical world scenario.
SEGMENTATION STRATEGIES IN THE FIELD OF MRI IMAGES: A COMPREHENSIVE ANALYSIS

With the advancement of technology, it almost becomes apparent that user requires information on the go. Health related problems are common and users do not possess much time in order to tackle the issue related to health. On the go information is required to the user to monitor their health. Digital image processing works towards this aspect and provides the mechanisms known as segmentation of MRI images to provide user on the go information about health related issues. MRI images are prone to noise hence handling MRI image with pre-processing phase is critical. This paper presents comprehensive analysis of techniques used to operate on image and classify the diseases based on abnormality detection. Phases associated with disease detection are also discussed and parameter optimized in existing work is elaborated. These parameters can be considered for improvement in future endeavours.
jaki : User-Controllable Generation of Drum Patterns using an LSTM Encoder-Decoder and Deep Reinforcement Learning

In this paper we present ongoing work on jaki , an automatic drum pattern generation algorithm designed for use in computer-assisted composition. Using an LSTM Encoder-Decoder model and Deep Q-learning, jaki generates 1-bar continuations of a ‘seed’ pattern that can be controlled by musical features, thus generating pattern variations that ﬁt the style of the seed whilst exhibiting certain user-deﬁned characteristics. This paper provides an overview of the algorithm, with several examples of patterns that have been generated with it, along with evaluation and discussion of potential further improvements to it. The algorithm is available for public use, and may be found at https:// github.com/fredbru/jaki , with further examples.
Assessing the ACL Injury Risk Estimation Quiz

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