Analysis of Public Policy and Enforcement of Domestic and Foreign Arbitral Awards in India

The Public Policy doctrine is an unruly horse in India, when it comes to the enforcement of domestic and foreign awards. The main objective behind choosing this topic was to shed light on how public policy has been used by the losing party, in delaying the enforcement of arbitral award, which hampers the whole objective of arbitration. Though one may argue that the 2015 Amendment Act has settled all the controversies regarding public policy and enforcement of arbitral award, the author is of the opinion that there are still some areas that are left unexplored by the Arbitration Amendment Act. The paper primarily focuses on the changing trend of public policy with respect to arbitration in India.  In addition, the author has compared the doctrine of public policy in India with that of countries such as France, Russia, United Kingdom and U.SA. The most important contribution of this research paper is that it analyses the validity of patent illegality in domestic arbitration

Document Classification using LSTM Neural Network

Document Classification is one of the most important topic in Computer Science as the number of electronic documents are increasingly very rapidly each day. Document classification is also known as Document Categorization. Classification is training of known labels to predict the unknown labels. It is the process of assigning a particular document to predefined categories.In this paper, we apply machine learning methods for classification of Documents. Recurrent Neural Networks of which LSTM is one of the most successful and have been developed for Controlling Robots, Natural Language Text Compression, Automatic Speech Recognition, Time Series Prediction, Handwriting Recognition and many more. LSTM can also be used for document classification. Document Classification includes text processing, feature extraction, feature vector construction and label prediction or final classification. Furthermore, we first try some data processing on 20 Newsgroup Dataset, and then we extract a features by using feature weighting and feature selection algorithms. The extracted features are then passed to the LSTM Neural network for future Label Predictions. Therefore, the documents are classified into different categories according to their context

Review of Graphene Technology and Its Applications for Electronic Devices

Graphene has amazing abilities due to its unique band structure characteristics defining its enhanced electrical capabilities for a material with the highest characteristic mobility known to exist at room temperature. The high mobility of graphene occurs due to electron delocalization and weak electron–phonon interaction, making graphene an ideal material for electrical applications requiring high mobility and fast response times. In this review, we cover graphene’s integration into infrared (IR) devices, electro-optic (EO) devices, and field effect transistors (FETs) for radio frequency (RF) applications. The benefits of utilizing graphene for each case are discussed, along with examples showing the current state-of-the-art solutions for these applications

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

Addressing climate change with behavioral science:A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors