Correction to: Comparative analysis of limit equilibrium and numerical methods for prediction of a landslide

Bulletin of Engineering Geology and the Environment - Landslides that occur due to the rapid motion of a rock-mass are a primary risk in mountainous terrains and are a danger to human life and...     

Software‐defined network‐enabled opportunistic offloading and charging scheme in multi‐unmanned aerial vehicle ecosystem

Unmanned aerial vehicles (UAVs) are autonomous fliers, which can play different roles in modern day applications. In one of the important role, UAVs can act as aerial data forwarding nodes for communication range enhancement in remote areas. UAVs form a web of drones, which can be geo‐distributed across a large area to serve various applications. However, the two major contradicting challenges with respect to multi‐UAV networks are channel congestion and flight time enhancement. The use of effective data transmission techniques to handle congestion can lead to higher battery dissipation, which in turn end up in the reduction in flight time. However, it is utmost necessity to provide an effective framework, which can provide a viable solution for handling congestion in multi‐UAV networks while enhancing the flight time of UAVs. To handle these issues, software‐defined network (SDN)–enabled opportunistic offloading and charging scheme (SOOCS) in multi‐UAV ecosystem is designed in this paper. In this scheme, an opportunistic offloading scheme is proposed, which uses an SDN‐based control model to handle congestion issues. Apart from this, an opportunistic energy‐charging scheme is designed, wherein the UAVS can either replenish their batteries using solar plates or they can wirelessly charge energy from charging points deployed at various geo‐distributed locations. The proposed scheme is evaluated using a simulation‐based study over the realistic deployment of charging points in Chandigarh City, India. The results obtained show the superiority of SOOCS over other variants of its category in terms of end‐to‐end delay, throughput, and hand‐over latency.     

Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral filter that regulates the contrast while preserving the edges. Therefore, in this paper a fusion algorithm is recommended by fusing fast bilateral filter that can effectively preserve the edge details and curvelet transform that has better capability to detect the edge direction feature and better investigation and tracking of significant characteristics of the image. Afterwards C mean thresholding is used for the extraction of vessel. The recommended fusion approach is assessed on DRIVE dataset. Experimental results illustrate that the fusion algorithm preserved the advantages of the both and provides better result. The results demonstrate that the recommended method outperforms the traditional approaches.     

Detection of Therapeutic Levels of Ionizing Radiation Using Plasmonic Nanosensor Gels

Radiotherapy is a highly complex and efficient treatment modality for ablation of malignant tumors. Despite several technological advances, determination of the dose delivered to the tumor remains a challenge due to limitations of complex fabrication, cumbersome operation, and high costs associated with current dosimeters. This study describes fundamental studies and development of a novel gel‐based colorimetric nanosensor for detecting therapeutic levels of X‐rays (1–10 Gy) administered in clinical radiotherapy. Following exposure to X‐rays, gold salts in the gel are converted to nanoparticles within the matrix, resulting in the formation of a maroon‐colored plasmonic gel. Differences in color intensity of the gel following irradiation are used as a quantitative indicator of the radiation dose employed. The gel‐based nanosensor is able to detect doses as low as 0.5 Gy, and demonstrates a linear detection range of 0–3 Gy, which indicates its application in the fractionated radiotherapy regime. The gel is also able to successfully report therapeutic levels of radiation doses administered to anthropomorphic tissue phantoms. The range of detection, ease of fabrication, simplicity of colorimetric detection, and relatively lower costs indicate that this technology can be potentially translated to different radiotherapy applications in the clinic.     

Unraveling the Mystery of the Blue Fog: Structure,Properties, and Applications of Amorphous Blue Phase III

The amorphous blue phase III of cholesteric liquid crystals, also known as the “blue fog,” are among the rising stars in materials science that can potentially be used to develop next‐generation displays with the ability to compete toe‐to‐toe with disruptive technologies like organic light‐emitting diodes. The structure and properties of the practically unobservable blue phase III have eluded scientists for more than a century since it was discovered. This progress report reviews the developments in this field from both fundamental and applied research perspectives. The first part of this progress report gives an overview of the 130‐years‐long scientific tour‐de‐force that very recently resulted in the revelation of the mysterious structure of blue phase III. The second part reviews progress made in the past decade in developing electrooptical, optical, and photonic devices based on blue phase III. The strong and weak aspects of the development of these devices are underlined and criticized, respectively. The third‐ and‐final part proposes ideas for further improvement in blue phase III technology to make it feasible for commercialization and widespread use.     

Applications of biofiltration in drinking water treatment – a review

Biofiltration is a process in which an otherwise conventional granular filter is designed to remove not only fine particulates but also dissolved organic compounds through microbial degradation. Biofiltration can reduce the need for chemicals in drinking water treatment and thus improved applications of biofiltration in drinking water treatment can be viewed as green or sustainable engineering technology. Recent trends in biofiltration technology for drinking water treatment have or have attempted to extend the performance of biofilters through gaining a better understanding of operational constraints. This review articles summarizes important operational parameters influencing biofiltration performance such as hydraulic loading, empty bed contact time (EBCT), temperature, media type, and backwashing conditions. In addition, recent advancements in biofiltration operations including, ozonation, ammonia removal and the influence of nutrient (nitrogen, phosphorous) supplementation to facilitate carbon removal are explored. ? 2015 Society of Chemical Industry     

Hyperspectral imaging of nanoparticles in biological samples: Simultaneous visualization and elemental identification

While engineered nanomaterials (ENMs) are increasingly incorporated into industrial processes and consumer products, the potential biological effects and health outcomes of exposure remain unknown. Novel advanced direct visualization techniques that require less time, cost, and resource investment than electron microscopy (EM) are needed for identifying and locating ENMs in biological samples. Hyperspectral imaging (HSI) combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400 to 1000 nm at each pixel in an enhanced dark‐field microscopic (EDFM) image. HSI‐EDFM can be used to confirm the identity of the materials of interest in a sample and generate an image “mapping” their presence and location in a sample. Hyperspectral mapping is particularly important for biological samples, where ENM morphology is visually indistinct from surrounding tissue structures. While use of HSI (without mapping) is increasing, no studies to date have compared results from hyperspectral mapping with conventional methods. Thus, the objective of this study was to utilize EDFM‐HSI to locate, identify, and map metal oxide ENMs in ex vivo histological porcine skin tissues, a toxicological model of cutaneous exposure, and compare findings with those of Raman spectroscopy (RS), energy‐dispersive X‐ray spectroscopy (EDS), and scanning electron microscopy (SEM). Results demonstrate that EDFM‐HSI mapping is capable of locating and identifying ENMs in tissue, as confirmed by conventional methods. This study serves as initial confirmation of EDFM‐HSI mapping as a novel and higher throughput technique for ENM identification in biological samples, and serves as the basis for further protocol development utilizing EDFM‐HSI for semiquantitation of ENMs. Microsc. Res. Tech. 79:349–358, 2016. © 2016 Wiley Periodicals, Inc.