Centralized Intermediation in a Decentralized Web3 Economy: Value Accrual and Extraction

The advent of Web3 has ushered in a new era of decentralized digital economy, promising a shift from centralized authority to distributed, peer-to-peer interactions. However, the underlying infrastructure of this decentralized ecosystem often relies on centralized cloud providers, creating a paradoxical concentration of value and power. This paper investigates the mechanics of value accrual and extraction within the Web3 ecosystem, focusing on the roles and revenues of centralized clouds. Through an analysis of publicly available material, we elucidate the financial implications of cloud services in purportedly decentralized contexts. We further explore the individual's perspective of value creation and accumulation, examining the interplay between user participation and centralized monetization strategies. Key findings indicate that while blockchain technology has the potential to significantly reduce infrastructure costs for financial services, the current Web3 landscape is marked by a substantial reliance on cloud providers for hosting, scalability, and performance

TSO: Curriculum Generation using continuous optimization

The training of deep learning models poses vast challenges of including parameter tuning and ordering of training data. Significant research has been done in Curriculum learning for optimizing the sequence of training data. Recent works have focused on using complex reinforcement learning techniques to find the optimal data ordering strategy to maximize learning for a given network. In this paper, we present a simple and efficient technique based on continuous optimization. We call this new approach Training Sequence Optimization (TSO). There are three critical components in our proposed approach: (a) An encoder network maps/embeds training sequence into continuous space. (b) A predictor network uses the continuous representation of a strategy as input and predicts the accuracy for fixed network architecture. (c) A decoder further maps a continuous representation of a strategy to the ordered training dataset. The performance predictor and encoder enable us to perform gradient-based optimization in the continuous space to find the embedding of optimal training data ordering with potentially better accuracy. Experiments show that we can gain 2AP with our generated optimal curriculum strategy over the random strategy using the CIFAR-100 dataset and have better boosts than the state of the art CL algorithms. We do an ablation study varying the architecture, dataset and sample sizes showcasing our approach's robustness.Comment: 10 pages, along with all experiment detail

Delay, fuel loss and noise pollution during idling of vehicles at signalized intersection in Agartala city, India

Agartala, capital of Tripura, India faces traffic congestion particularly in the different road intersection due to rapid and uncontrolled development by an unacceptable level of disparity in transportation demand and supply scenario resulting in environmental degradation as well as delay and fuel loss. When the vehicles are waiting for their turn to clear the intersection, the drivers normally keep the engines of their vehicle on and unnecessary hoot horns. As a result vehicle delay, fuel loss & noise level are increased particularly at the signalized intersection. 5 (five) representative signalized intersections of varying traffic volume have been selected in this study to ascertain delay, fuel loss & noise level during idling of vehicles. The study indicates that the noise level exceeds permissible levels and vehicular delays are high as more than 60 sec/vehicle during peak hour at all important signalized intersections. The study reveals that North Gate intersection is found to be the busiest intersection as well as the noisiest intersection. In North Gate, during daytime noise level is in between 66.7 dB (A) to 108.6 dB (A) and during night time 60.4 dB (A) to 100.9 dB (A) which is ill effective on human health and environment. In Math Chowmuhani intersection fuel loss is maximum comparing to other four intersections.  A direct correlation between vehicular delay versus noise level, traffic volume versus delay and traffic volume versus noise level have been proposed. These equations could be used as an effective tool in traffic management, land use planning and pollution control. After implementation of remedial measures, vehicular delay, fuel loss and noise level of all signalized intersection of Agartala city can be reduced. Delay, fuel loss and noise level at different signalized intersection of Agartala city and strategies to control the noise pollution have been discussed in this paper. Keywords: Signalized Intersection, Average Daily Traffic (ADT), Noise Level, Fuel los

ARBEKACIN – A RAY OF HOPE TO FIGHT AGAINST MDR AND XDR GRAM-NEGATIVE BACTERIA IN A SCIENTIFIC AND COST-EFFECTIVE WAY IN INDIAN SCENARIO

Objective: The objective of the study was to see the in vitro activity of arbekacin, a novel aminoglycoside, against multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacilli (GNB) so that it can become a good alternative as empirical treatment for severe sepsis. Methods: Identification and antibiotic sensitivity testing of the GNB isolated from the clinical samples were done using the VITEK-II system in a tertiary care hospital, Kolkata. MDR and XDR strains were selected by their definitions and molecular characterization was done by multiplex polymerase chain reaction. The minimum inhibitory concentration (MIC) value of arbekacin was detected by the E-test strip and compared with other aminoglycosides. Results: A total of 140 drug-resistant strains including ESBL- and carbapenemase-producing GNB were selected for the study. Arbekacin showed reduced values of MIC50 and MIC90 compared to other aminoglycosides for most of the drug-resistant GNB. Conclusion: Hence, in this drug-resistant era, arbekacin with the advantage of a single daily dose can be used as an empirical choice in severe sepsis as monotherapy or in combination with other antibiotics such as colistin or polymyxin to fight against MDR and XDR bugs

Optical spectroscopy of single InAs/A1As quantum dots

Tesis doctoral inédita. Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Física de Materiales. Fecha de lectura: 18-03-0

(SI10-077) A Novel Collocation Method for Solving Second-order Volterra Integro-differential Equations

In this article, we present an efficient numerical methodology to solve second-order linear Volterra integro-differential equations. Further, the modified Chebyshev collocation method is used at the Gauss-Lobatto collocation points. In that context, some theoretical investigation related to error analysis is suggested through residual function. Numerical examples are also encountered to study the applicability of the present method. In order to get a vivid illustration of the efficiency, we present a comparative survey with three existing collocation methods