DRT

A well developed financial system plays a pivotal role in deciding the pace of development of an economy as it acts as a catalyst in boosting country's growth. In the lending process, banks face credit risk which creates non-performing assets (NPAs), that is, the risk of not paying interest on the loan by the borrower. As on March 2019, the gross NPAs of scheduled commercial banks (SCBs) accounted to Rs. 9364.74 billion on which a provision of Rs. 3001.51 billion has been made. The problem of stressed assets has been a major concern for banks and policy makers as it affects the profitability, liquidity, soundness, and efficiency of banks severely. If rigorous efforts should not be undertaken immediately, the existence of the banking sector may be at risk. In this perspective, the current paper analyzes the trend of NPAs in Indian SCBs for the period covering 2010-2019. The study further investigates the legal resolution techniques for NPAs in general and evaluated the performance of DRTs, Lok Adalats, and SARFAESI in particular. The results of ANOVA and Kruskal-Wallis test revealed that there is significant difference in recovering NPAs across group and pairwise comparisons showed that Lok Adalats and SARFAESI are significantly different. The study also found that there is continuous deterioration in asset quality of SCBs and SARFAESI is the most effective recovery channel.

The author points out an unclarity in linguistic discourse representation
theory, as developed by Hans Kamp. This unclarity concerns the concept of
internal anchoring in the case of anaphoric backwards reference. Following this,
the author sketches his own account of cognitive dynamics, on the basis of which
he finally makes an alternative proposal on the semantics/pragmatics of both referential expressions in general and anaphoric pronouns as well as demonstratives in
particular.

Donkey sentences have existential and universal readings, but they are not often perceived as ambiguous. We extend the pragmatic theory of nonmaximality in plural definites by Križ (2016) to explain how context disambiguates donkey sentences. We propose that the denotations of such sentences produce truth-value gaps — in certain scenarios the sentences are neither true nor false — and demonstrate that Križ’s pragmatic theory fills these gaps to generate the standard judgments of the literature. Building on Muskens’s (1996) Compositional Discourse Representation Theory and on ideas from supervaluation semantics, the semantic analysis defines a general schema for quantification that delivers the required truth-value gaps. Given the independently motivated pragmatic theory of Križ 2016, we argue that mixed readings of donkey sentences require neither plural information states, contra Brasoveanu 2008, 2010, nor error states, contra Champollion 2016, nor singular donkey pronouns with plural referents, contra Krifka 1996, Yoon 1996. We also show that the pragmatic account improves over alternatives like Kanazawa 1994 that attribute the readings of donkey sentences to the monotonicity properties of the embedding quantifier.

This paper proposes a proof-theoretic, compositional discourse semantics of natural language, which we call Dependent Type Semantics (DTS). The formalization of DTS is based on polymorphic dependent type theory, instead of standard Montagovian or dynamic frameworks. We show that DTS provides a solution to the cases of dynamic binding where double negation elimination is involved in order to establish a dynamic link, which has long been problematic to most dynamic semantics. A comparison is made with the previous work including Double Negation DRT.

A sound banking industry is imperative to expand the other sectors as it advances loans to smoothly carry on their business. However, the banking sector these days is overburdened with voluminous Non-Performing Assets (NPAs), which influence not only the profitability and liquidity of the bank but also its reputation. In the credit stream there has been an extension to various areas of the economy, such as the market, manufacturing, administrations and agribusiness. But at the same time, the Indian banking sector has seen an increase in the Non-Performing Assets (NPAs). NPA has strong effects on bank profitability and net worth. Banks need to take steps to get the Non-Performing Assets down. The Gross NPA represents the efficiency of bank lending, and the Net NPA represents the banks' real burden. This paper makes an attempt to focus on the trends of Gross NPA, Net NPA, the impact of NPAs, and ongoing policy projections to minimize NPAs.

In this study, a concatenative text-to-speech system for Turkish is built. The system uses simple techniques and the concatenation units are obtained from the atomic units. This approach is very well suited for Turkish language structure and it is flexible enough to allow the synthesis of all types texts. The Turkish TTS system is tested considering the naturalness and intelligibility criterion. It is evaluated by using MOS, DRT and CT. Naturalness and intelligibility of the Turkish TTS system is tested by MOS and CT-DRT, respectively. Although the system uses simple techniques, it provides promising results for Turkish TTS, since the selected concatenative method is very well suited for Turkish language structure.

The best indicator of the measure of the health of the banking industry in a country is its volume of Non-Performing Assets (NPAs). The increasing number of NPAs in commercial banks is a major concern in India. The best solution to reduce the volume of NPAs depends on good management of recovery mechanisms. The present context of research focuses on the recovery mechanism of NPAs with three important legal measures. Most of the cases are being negotiated and monitored through Lok Adalats in order to reduce the burden of those assets which cease to generate revenue. In addition to this, there is Debt Recovery Tribunals mechanism (DRTs), which focuses on diminishing the balance of NPAs. However, the third measure includes Securitisation and Reconstruction of Financial Assets and Enforcement of Securities Interest Act (SARFAESI Act), which allows banks to curb NPAs. The entire study is based on secondary data and SPSS is used to analyze the data. The study revealed that there is a statistically significant difference between the number of cases referred to the recovery mechanisms and the amount recovered through various recovery channels.