Abstract

The diverse excitabilities of cells often produce various spiking‑bursting oscillations that are found in the neural system. We establish the ability of a fractional‑order excitable neuron model with Caputo’s fractional derivative to analyze the effects of its dynamics on the spike train features observed in our results. The significance of this generalization relies on a theoretical framework of the model in which memory and hereditary properties are considered. Employing the fractional exponent, we first provide information about the variations in electrical activities. We deal with the 2D class I and class II excitable Morris‑Lecar (M‑L) neuron models that show the alternation of spiking and bursting features including MMOs & MMBOs of an uncoupled fractional‑order neuron. We then extend the study with the 3D slow‑fast M‑L model in the fractional domain. The considered approach establishes a way to describe various characteristics similarities between fractional‑order and classical integer‑order dynamics. Using the stability and bifurcation analysis, we discuss different parameter spaces where the quiescent state emerges in uncoupled neurons. We show the characteristics consistent with the analytical results. Next, the Erdös‑Rényi network of desynchronized mixed neurons (oscillatory and excitable) is constructed that is coupled through membrane voltage. It can generate complex firing activities where quiescent neurons start to fire. Furthermore, we have shown that increasing coupling can create cluster synchronization, and eventually it can enable the network to fire in unison. Based on cluster synchronization, we develop a reduced‑order model which can capture the activities of the entire network. Our results reveal that the effect of fractional‑order depends on the synaptic connectivity and the memory trace of the system. Additionally, the dynamics captures spike frequency adaptation and spike latency that occur over multiple timescales as the effects of fractional derivative, which has been observed in neural computation.

Abstract

Peripheral nerve blocks are crucial to treatment of post-surgical pain and are associated with reduction in perioperative opioid use and hospital stay. Accurate interpretation of sono-anatomy is critical for the success of ultrasound (US) guided peripheral nerve blocks and can be challenging to the new operators. This prospective study enrolled 227 subjects who were systematically scanned for supraclavicular and interscalene brachial plexus in various settings using three different US machines to create a dataset of 227 unique videos. In total, 41,000 video frames were annotated by experienced anaesthesiologists using partial automation with object tracking and active contour algorithms. Four baseline neural network models were trained on the dataset and their performance was evaluated for object detection and segmentation tasks. Generalizability of the best suited model was then tested on the datasets constructed from separate US scanners with and without fine-tuning. The results demonstrate that

Abstract

UV radiation-induced DNA damages have adverse effects on genome integrity and cellular function. The most prevalent UV-induced DNA lesion is the cyclobutane pyrimidine dimer (CPD), which can cause skin disorders and cancers in humans. Rad4/XPC is a damage sensing protein that recognizes and repairs CPD lesions with high fidelity. However, the molecular mechanism of how Rad4/XPC interrogates CPD lesions remains elusive. Emerging viewpoints indicate that the association of Rad4/XPC with DNA, the insertion of a lesion- sensing β-hairpin of Rad4/XPC into the lesion site, and the flipping of CPD’s partner bases (5’-dA and 3’-dA) are essential for damage recognition. Characterizing these slow events is challenging due to their infrequent occurrence on molecular time scales. Herein, we have used enhanced sampling and molecular dynamics simulations to investigate the mechanism and energetics of lesion recognition by Rad4/XPC, considering multiple plausible pathways between the crystal structure of the Rad4-DNA complex and nine intermediate states. Our results shed light on the most likely sequence of events, their potential coupling and energetics. Upon association, Rad4 and DNA form an encounter complex in which CPD and its partner bases remain in the duplex and the BHD3 β- hairpin is yet to be inserted into the lesion site. Subsequently, sequential base flipping occurs, with the flipping of the 5’-dA base preceding that of the 3’-dA base, followed by the insertion of the BHD3 β-hairpin into the lesion site. The results presented here have significant implications for understanding the molecular basis of UV-related skin disorders and cancers and for paving the way for novel therapeutic strategies. INTRODUCTION DNA plays a central role in the

Abstract

n this paper, we try to tackle the problem of erroneous English-Hindi machine translation (MT) outputs due to the presence of the Verb Phrase Ellipsis (VPE) in English. The phenomenon of VPE is prominent in spoken English, and the antecedent to the ellipsis can come from previous sentences in a conversation as well. MT systems translate sentences as a whole and ignore the contextual information from the previous sentences. For these two reasons, spoken English-Hindi transla- tions suffer. We approached this problem by manually annotating 1200 two-person conversations that contain VPE and by studying how their resolution affects the translation qualities. Using our studies, we designed a rule-based system for the detection and resolution of VPE in English with the goal of improving their subsequent Hindi translation qualities. Our rule-based system is capable of the following: 1) Detection of VPE, 2) Resolution of Elided Head verb, 3) Resolution of Elided Head verb’s children, 4) Resolution of non-verbal predicates of a copula or a ’be’ main verb, 5) Modifying original sentence in the conversation with the resolved verb phrase. We also tested the system’s performance on VPE datasets outside of our annotated data. In this paper, we present our annotated corpus on conversational English VPE, our rule-based system to tackle VPE in the context of improving English-Hindi MT, the observations made as we designed this rule-based system and the performance-related observations of our system

Abstract

Across the globe, stone has been extensively used as a building construction material due to its local availability and high durability. The scenario for the construction of buildings in India is no more different than compared to other parts of the world. According to the 2011 Census of India, 43.48 million houses (~ 14% of the total number of houses) have stone as the predominant wall material. Owing to the fact of non-engineered construction, wide variations in terms of stone masonry construction can be seen in the Indian subcontinent, particularly in the Himalayan belt. In this study, a field survey is conducted to identify the seismic resistant features in traditional building practices which make use of stone for construction, e.g. Thathara construction, Dry stack construction, Koti Banal construction, etc. The percentage of these types of structures is decreasing due to an increase in urbanization, increasing housing demands, non-availability of traditional construction materials and skilled artesian for building new structures as well as costly repair and retrofitting techniques for damaged and existing structures. Thus, there is a dire need to safeguard these structures as if this trend continues, these buildings will become things of the past. In this paper, a review of structural configuration, roofing systems, foundation type and potential failure modes of these construction typologies are studied, and the effect of different retrofitting techniques that exist in the construction type on their expected seismic performance is discussed.

Abstract

Recurrent earthquakes in the past two decades have taken thousands of lives (e.g., the Kashmir earthquake killed some 80,000 people) and destroyed millions of homes and other buildings. This colossal loss of lives was not because of the earthquake but because people were inside buildings (e.g., stone masonry structures) that were highly vulnerable. The death toll would have been significantly lower, if the structures had been retrofitted with a small fraction of the cost of reconstruction. The past earthquakes have brought out many weaknesses in masonry design and construction practices as these structures behaved unsatisfactorily and sustained major damage. Hence, the safety and retrofitting of existing stone masonry houses are very important. Considerable research work has been directed toward evolving suitable methods of earthquake resistance in stone masonry houses.Despite the availability of such methods, masonry buildings have been damaged in the event of earthquakes, because of the following reasons: (i) lack of awareness, formal training, and technical knowledge in earthquake-resistant construction; (ii) lack of concern about seismic safety because of the infrequent occurrence of earthquakes; (iii) people lack financial resources to meet the earthquake-resistant requirement; and (iv) despite the availability of provisions and recommendations of earthquake-resistant measures to be applied on stone masonry buildings in the form of various codes, and these are rarely being implemented in actual practice. Therefore, in the present study, an overview is presented about how the retrofitting of existing stone masonry houses using different techniques can be implemented to reduce their seismic vulnerability and loss of life.

Abstract

Stone masonry walls have inherent weaknesses against the lateral forces of an earthquake. These weaknesses result in inadequate performance during earthquakes. Mistakes are commonly committed in the construction of stone walls, especially in the random rubble-type masonry. These mistakes further erode strength. When shaken, poorly constructed walls having inadequate interlocking between the inside and the outside faces (wythes), the faces begin to separate, resulting in rapid weakening of the wall and leading to the collapse of one or both wythes. In the presence of excessive openings, the wall becomes weak against the tearing action caused by the earthquake forces that are parallel to the length of the wall. This results in diagonal cracking of varying severity in the walls. Further, due to poor connection between the walls and the floor/roof, it results in failure of the floor diaphragm and affects the overall stability of the structure. Hence, while choosing to construct a building with stone masonry, the owner must make sure that the measures required to counter these weaknesses are taken during the construction so that in the event of a potentially destructive earthquake, the structure can withstand its impact without suffering much damage. Therefore, in the present study, an overview is presented for different failure modes of stone masonry houses, seismic safety provisions for the new construction considering the regulations for the wall, floor/roof construction and the provision of horizontal and vertical reinforcement to ensure good seismic performance against the future earthquakes.

Abstract

Evaluating the risk level of adversarial images is essential for safely deploying face authentication models in the real world. Popular approaches for physical-world attacks, such as print or replay attacks, suffer from some limitations, like including physical and geometrical artifacts. Recently adversarial attacks have gained attraction, which try to digitally deceive the learning strategy of a recognition system using slight modifications to the captured image. While most previous research assumes that the adversarial image could be digitally fed into the authentication systems, this is not always the case for systems deployed in the real world. This paper demonstrates the vulnerability of face authentication systems to adversarial images in physical world scenarios. We propose AdvGen, an automated Generative Adversarial Network, to simulate print and replay attacks and generate adversarial images that can fool state-of-the-art PADs in a physical domain attack setting. Using this attack strategy, the attack success rate goes up to 82.01%. We test AdvGen extensively on four datasets and ten state-of-the-art PADs. We also demonstrate the effectiveness of our attack by conducting experiments in a realistic, physical environment.

Abstract

We present a novel second-order cone programming frame- work to learn robust classifiers that can tolerate uncertainty in the obser- vations of partially labeled multiclass classification problems. We call it RPL-SVM. Our formulation is based on a chance-constrained framework. Experimental results show that RPL-SVM efficiently learns multiclass classifiers with missing values in a partial label setting.

Abstract

Sentiment Analysis is an important task for analysing online content across languages for tasks such as content moderation and opinion mining. Though a significant amount of resources are available for Sentiment Analysis in several Indian languages, there do not exist any large-scale, open-access corpora for Gujarati. Our paper presents and describes the Gujarati Sentiment Analysis Corpus (GSAC), which has been sourced from Twitter and manually annotated by native speakers of the language. We describe in detail our collection and annotation processes and conduct extensive experiments on our corpus to provide reliable baselines for future work using our dataset.