Abstract

UN World Conference on Disaster Risk Reduction held in 2015 at Sendai, Japan, reiterated the need for substantial reduction in loss of life and property. Thus, assessing disaster risk and identifying key items for risk mitigation are in focus. Assessment of disaster risk is a multidisciplinary effort, which includes expected tangible physical loss, such as collapse and damage to built environment. In countries with limited resources, prioritizing risk reduction effort across the different parts of the country needs a quantitative (yet simple) approach to bring objectivity into the decision-making process. This paper presents a simple method, called Earthquake Disaster Risk Index (EDRI), for estimating relative earthquake risk across the different regions in a country; it uses three major constituents of risk, namely Hazard, Exposure and Vulnerability. Hazard is taken as the acceleration hazard specified in the national earthquake design standard, Exposure as per the permitted occupancy in the Local Municipal Byelaws, and Vulnerability through a Level 2 Detailed Qualitative Assessment of buildings built in the Town or City (with penalty points for missing features of earthquake resistance compared to an Ideal Building). First, the EDRI of a Town or City is estimated for each typology of building in the Town or City, and then the net EDRI of the Town or City is obtained as a weighted average of the EDRI of each typology of buildings using the number of buildings of each typology present in the city.

Abstract

A ground-structure vibration response study was carried out at the Ramappa Temple near Warangal, Telangana, India, shaken by underground blasting undertaken at the neighbouring Devadula Lift Irrigation Project to build water tunnels. The intensities of vibrations were examined–subsurface and ground vibrations were measured using velocity meters, and shaking at the temple using accelerometers. The study concluded that high-frequency vibrations of the ground were filtered by the soft natural clay bed underneath, and vibrations at the temple structure were small and well below the levels that can cause damage to it. Here we present the scientific findings of the vibrations recorded during the blasts and their implications.

Abstract

In building construction, reinforced concrete (RC) Frame structures are frequently used due to ease of construction and rapid progress of work. In this study, two types of infill’s are used ie, unreinforced masonry infill and semi-interlocked masonry infill. For the analysis purpose of infill, a double strut nonlinear cyclic model is used. The main objective of the study is to investigate the importance of interlocked brick infill in the RC frame structure. For understanding the same, nonlinear static pushover analysis is carried out on analytical models using finite element based software, SeismoStruct. The response reduction factor components such as ductility reduction factor and overstrength factors were computed from nonlinear static pushover analysis and finally, the response reduction factor is calculated for all models. The primary focus is given to numerical modeling, nonlinear behavior of brick masonry RC buildings subjected to lateral loads and calculation of the response reduction factor of'RC'infilled frames with different aspect ratios.

Abstract

In the present study, it was attempted to investigate the cyclic resistance of equi-proportionate silt–sand range pond ash (with 50% fines) at relatively high shear strains using the strain-controlled cyclic triaxial test. The cyclic triaxial tests have been performed considering the effect of relative compaction (97–99%), cyclic shear strain (0.6–1.35%), frequency of loading (0.3–1 Hz) and effective confining pressure (50–100 kPa) on cyclic resistance of pond ash. Dynamic characteristics such as dynamic shear modulus and damping ratio of equi-proportionate silt–sand range pond ash was evaluated for all the parameters considered at high shear strain. The maximum value of the dynamic shear modulus and damping ratio of pond ash observed in this study was 6534.8 kPa and 23.64%, respectively. The dynamic shear modulus and damping ratio of pond ash was decreased from 6534.8 to 5023.87 kPa and 23.64 to 14.17 …

Abstract

We thank the respected discussers for appreciating the relevance of the present work, critically analyzing it, and bringing forth the possible constraints in its applicability. This discussion provides us an opportunity to elaborate the point related to the scope and applicability of original work, especially with focus on the hydrological community that otherwise would possibly remain unclarified. Because there are two discussions of our paper, we have addressed them in two different sections.

Abstract

Rice blast disease is a major threat to rice production worldwide; the causative pathogenic fungus Magnaporthe oryzae induces rice (Oryza sativa) plants to undergo molecular changes that help them to circumvent this fungal attack. Transcriptome studies have demonstrated that many genes are involved in the defense response of rice to M. oryzae, but most of these studies focused on the screening of differentially expressed genes and the studies did not investigate the interactions among genes. We examined the interaction of rice and M. oryzae in a network context. Two near-isogenic lines were profiled at different time-points. Using transcriptome data obtained from an RNASeq analysis, a network based on the relationships among genes was developed through weighted gene co-expression network analysis. The analysis of degree centrality identified numerous hub genes and potential key regulators that control the rice response, providing new insights into the molecular network underlying the resistance of rice to M. oryzae infection. Additionally, a protein-protein interaction network was derived to identify complexes that might physically interact. For example, complexes of OsbHLH148/OsJAZ, OsMYB4 and some components of the phenylpropanoid pathway, as well as MYB/bHLH

Abstract

The Standard Model (SM), when extended with a leptoquark (LQ) and right-handed neutrinos, can have interesting new implications for Higgs physics. We show that sterile neutrinos can induce a boost to the down-type quark Yukawa interactions through a diagonal coupling associated with the quarks and a scalar LQ of electromagnetic charge 1/3. The relative change is moderately larger in the case of the first two generations of quarks, as they have vanishingly small Yukawa couplings in the SM. The enhancement in the couplings would also lead to a non-negligible contribution from the quark fusion process to the production of the 125 GeV Higgs scalar in the SM, though the gluon fusion always dominates. However, this may not be true for a general scalar. As an example, we consider a scenario with a SM-gauge-singlet scalar ϕ where an O (1) coupling between ϕ and the LQ is allowed. The ϕ q q Yukawa …

Abstract

Patterns of DNA methylation are significantly altered in cancers. Interpreting the functional consequences of DNA methylation requires the integration of multiple forms of data. The recent advancement in the next-generation sequencing can help to decode this relationship and in biomarker discovery. In this study, we investigated the methylation patterns of papillary renal cell carcinoma (PRCC) and its relationship with the gene expression using The Cancer Genome Atlas (TCGA) multi-omics data. We found that the promoter and body of tumor suppressor genes, microRNAs and gene clusters and families, including cadherins, protocadherins, claudins and collagens, are hypermethylated in PRCC. Hypomethylated genes in PRCC are associated with the immune function. The gene expression of several novel candidate genes, including interleukin receptor IL17RE and immune checkpoint genes HHLA2, SIRPA and …

Abstract

Information acquisition through crowdsourcing with mobile agents is a popular way to collect data, especially in the context of smart cities where the deployment of dedicated data collectors is expensive and ineffective. It requires trustworthy and effective mechanisms to guarantee that the collected data are accurately acquired and reported. Trustworthy and transparent frameworks can be implemented via smart contracts on blockchain to enable robust information elicitation mechanisms. In this work we develop Orthos, a blockchain-based trustworthy framework for spontaneous location-based information aggregation queries without assuming any prior knowledge about them. We employ game-theoretic mechanisms to incentivize agents to report truthfully and ensure that the information is collected at the desired location while ensuring the privacy of the agents. We identify six necessary characteristics for information aggregation mechanisms to be applicable in spontaneous location-based settings. Orthos implements the function of robust peer truth serum for crowdsourcing (RPTSC), the state-of-the-art information aggregation mechanism using smart contracts. Additionally, as location information is exogenous to RPTSC, we design the Proof-of-Location protocol to ensure that agents gather the data at the desired locations. We examine the performance of Orthos on Rinkeby Ethereum testnet and conduct experiments with live audience.

Abstract

Demand response is a crucial tool to maintain the stability of the smart grids. With the upcoming research trends in the area of electricity markets, it has become a possibility to design a dynamic pricing system, and consumers are made aware of what they are going to pay. Though the dynamic pricing system (pricing based on the total demand a distributor company is facing) seems to be one possible solution, the current dynamic pricing approaches are either too complex for a consumer to understand or are too naive leading to inefficiencies in the system (either consumer side or distributor side). Due to these limitations, the recent literature is focusing on the approach to provide incentives to the consumers to reduce the electricity, especially in peak hours. For each round, the goal is to select a subset of consumers to whom the distributor should offer incentives so as to minimize the loss which comprises of cost of buying the electricity from the market, uncertainties at consumer end, and cost incurred to the consumers to reduce the electricity which is a private information to the consumers. Due to the uncertainties in the loss function (arising from renewable energy resources as well as consumption needs), traditional auction theory-based incentives face manipulation challenges. Towards this, we propose a novel combinatorial multi-armed bandit (MAB) algorithm, which we refer to as GLS-MAB to learn the uncertainties along with an auction to elicit true costs incurred by the consumers. We prove that our mechanism is regret optimal and is incentive compatible. We further demonstrate efficacy of our algorithms via simulations.