TransEdge: Supporting Efficient Read Queries Across Untrusted Edge Nodes

We propose Transactional Edge (TransEdge), a distributed transaction processing system for untrusted environments such as edge computing systems. What distinguishes TransEdge is its focus on efficient support for read-only transactions. TransEdge allows reading from different partitions consistently using one round in most cases and no more than two rounds in the worst case. TransEdge design is centered around this dependency tracking scheme including the consensus and transaction processing protocols. Our performance evaluation shows that TransEdge's snapshot read-only transactions achieve an 9-24x speedup compared to current byzantine systems

“Millennial India”: Global Digital Politics in Context

In this special issue, we examine the two decades of digital media expansion in India, the world’s second largest Internet user domain, to propose the idea of “millennial India.” Millennial India highlights the processes of digitalization as a distinct sociopolitical moment entailing new conditions of communication, and the stakes of “millennials” who are drawn to digital media to articulate political matters. These processes, we suggest, have led to a democratization of public participation through the self-activity of online users. Qualifying the assumption that participation leads to empowerment, we show that a politics of civic action has grown simultaneously with violent exclusions via digital circulation. Millennial India emphasizes the need to take a contextual approach to global digital politics, and recognizes the continuities in the structures of political action in as much as the disruptions engendered by digital infrastructures

Utilization of Integrative Technique for Partial Recovery of Proteases from Soil Microbes

Aqueous two-phase system (ATPS) is an efficient, cost effective, fast, simple and ecofriendly method for the recovery of biomolecules. In the present study, an ATPS composed of polyethylene glycol and ammonium sulphate (NH4)2SO4 was used for the partial purification of proteases from microbial source. The effects of different parameters such as molecular weight of PEG (4000, 6000 and 10000), concentration of PEG (15, 17.5 and 20 %) and concentration of (NH4)2SO4 (7.5, 8.3, 9.1 and 9.9 %) on the partitioning behavior of proteases at room temperature were investigated. Generally, increasing the concentration of PEG and (NH4)2SO4 moved the protease to the top i.e., polymer-rich phase. Increasing the molecular weight of PEG from 4000 to 10000 the partition coefficient decreased subsequently. The highest partition coefficient i.e., 3.32 and maximum activity i.e., 16.06 soxhlet unit was found in an optimum system composed of 20 % PEG 4000 and 9.9 % (NH4)2SO4

Blockchain Applications in Smart Sustainable City Context—A Systematic Mapping Study

The advancement in blockchain applications in the smart sustainable city infrastructure is evaluated in this paper through a comprehensive mapping review. The evaluation is carried out by posing four research questions that address current developments in blockchain technology in the context of smart cities and point out areas where additional study is needed. This study also includes a scoping of blockchain applications in a smart city context to highlight the obstacles to incorporating blockchain technology into smart city infrastructure. Finally, some suggestions for overcoming the problems of incorporating blockchain technology with smart city infrastructure are offered. This research will help researchers and policymakers gain a better understanding of blockchain applications in smart cities

Integration of Large-Scale Electric Vehicles into Utility Grid: An Efficient Approach for Impact Analysis and Power Quality Assessment

Electric vehicles (EVs) have received massive consideration in the automotive industries due to their improved performance, efficiency and capability to minimize global warming and carbon emission impacts. The utilization of EVs has several potential benefits, such as increased use of renewable energy, less dependency on fossil-fuel-based power generations and energy-storage capability. Although EVs can significantly mitigate global carbon emissions, it is challenging to maintain power balance during charging on-peak hours. Thus, it mandates a comprehensive impact analysis of high-level electric vehicle penetration in utility grids. This paper investigates the impacts of large-scale EV penetration on low voltage distribution, considering the charging time, charging method and characteristics. Several charging scenarios are considered for EVs’ integration into the utility grid regarding power demand, voltage profile, power quality and system adequacy. A lookup-table-based charging approach for EVs is proposed for impact analysis, while considering a large-scale integration. It is observed that the bus voltage and line current are affected during high-level charging and discharging of the EVs. The residential grid voltage sag increases by about 1.96% to 1.77%, 2.21%, 1.96 to 1.521% and 1.93% in four EV-charging profiles, respectively. The finding of this work can be adopted in designing optimal charging/discharging of EVs to minimize the impacts on bus voltage and line current

In Search of a “Social-AQI”

Globally, datafication is being adopted as a solution for socio-environmental issues, with the belief that it will democratize decision-making by simplifying knowledge through data. However, this process can further alienate marginalized groups from governance by disregarding practical exposure levels and the sociopolitical contexts in which people live and engage at the community level. In this paper, we use community participation as a tool to develop the Social Air Quality Index (S-AQI), which shapes neighborhood air pollution mapping and monitoring in Delhi. We first question the impact of datafication on air pollution quality measurements and challenge the claim that air quality governance is possible simply through the deployment of high-tech devices and AQI standardization, which is often used to produce and share data about air pollution across Delhi. Instead, we propose an alternative community-oriented methodology and incorporate an interactive approach that relies on public workshops, offline questionnaires, and low-cost sensors to engage with six neighborhoods. Through this intervention-based approach, we seek to explore how to develop AQI understanding among local stakeholders and identify pathways to build greater social awareness and knowledge of AQI as a means of dealing with the pollution crisis

Heterologous Expression of Genes in Plants for Abiotic Stresses

Abiotic stresses are considered to be the major factors causing a decrease in crop yield globally, these stresses include high and low temperature, salinity, drought, and light stress etc. To overcome the consistent food demand for the ever-growing population, various genes from micro-organisms and non-plant sources have been expressed in transgenic plants to improve their tolerance against abiotic stresses. Gene expression in transgenic plants through conventional methods are time-consuming and laborious that’s why advanced genetic engineering methods for example Agrobacterium-mediated transformation and biolistic methods are more accurate, useful, and less time-consuming. This review provides an insight into various bacterial genes for example mtID, codA, betA, ADH, IPT, DRNF1 and ggpPS, etc. that have been successfully expressed in transgenic plants against various abiotic stress for stress tolerance enhancement and crop yield improvement which exhibited good encouraging results. Genes from yeast (Saccharomyces cerevisiae) have been introduced in transgenic plants against drought and salinity stress. All these genes expressed from non-plant sources in plants can be very helpful to enhance crops for better yield productivity in the future to meet the demands of the consistently rising population of the world

Artificial intelligence-driven approach to identify and recommend the winner in a tied event in sports surveillance

The proliferation of fractal artificial intelligence (AI)-based decision-making has propelled advances in intelligent computing techniques. Fractal AI-driven decision-making approaches are used to solve a variety of real-world complex problems, especially in uncertain sports surveillance situations. To this end, we present a framework for deciding the winner in a tied sporting event. As a case study, a tied cricket match was investigated, and the issue was addressed with a systematic state-of-the-art approach by considering the team strength in terms of the player score, team score at different intervals, and total team scores (TTSs). The TTSs of teams were compared to recommend the winner. We believe that the proposed idea will help to identify the winner in a tied match, supporting intelligent surveillance systems. In addition, this approach can potentially address many existing issues and future challenges regarding critical decision-making processes in sports. Furthermore, we posit that this work will open new avenues for researchers in fractal AI

National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma

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