A novel intrusion detection framework for wireless sensor networks

Abstract Vehicle cloud is a new idea that uses the benefits of wireless sensor networks (WSNs) and the concept of cloud computing to provide better services to the community. It is important to secure a sensor network to achieve better performance of the vehicle cloud. Wireless sensor networks are a soft target for intruders or adversaries to launch lethal attacks in its present configuration. In this paper, a novel intrusion detection framework is proposed for securing wireless sensor networks from routing attacks. The proposed system works in a distributed environment to detect intrusions by collaborating with the neighboring nodes. It works in two modes: online prevention allows safeguarding from those abnormal nodes that are already declared as malicious while offline detection finds those nodes that are being compromised by an adversary during the next epoch of time. Simulation results show that the proposed specification-based detection scheme performs extremely well and achieves high intrusion detection rate and low false positive rate

Energy Efficient Rapid Removal of Arsenic in an Electrocoagulation Reactor with Hybrid Fe/Al Electrodes: Process Optimization Using CCD and Kinetic Modeling

Threats due to insufficient, inadequate and costlier methods of treating contaminants such as arsenic have emphasized the significance of optimizing and managing the processes adopted. This study was aimed at the complete elimination of arsenic from an aqueous medium with minimum energy consumption using the electrocoagulation process. Arsenic removal around 95% was rapidly attained for optimized conditions having a pH of 7, 0.46 A current intensity, 10 mg/L initial concentration and only 2 min of applied time duration using the energy of 3.1 watt-hour per gram of arsenic removed. Low values of applied current for longer durations resulted in the complete removal of arsenic with low energy consumption. Various hydroxide complexes including ferrous hydroxide and ferric hydroxide assisted in the removal of arsenic by adsorption along with co-precipitation. Surface models obtained were checked and found with a reasonably good fit having high values of coefficient of determination of 0.933 and 0.980 for removal efficiency and energy consumption, respectively. Adsorption was found to follow pseudo-first-order kinetics. Multivariate optimization proved it as a low-cost effective technology having an operational cost of 0.0974 Indian rupees (equivalent to USD 0.0013) per gram removal of arsenic. Overall, the process was well optimized using CCD based on response surface methodology.Threats due to insufficient, inadequate and costlier methods of treating contaminants such as arsenic have emphasized the significance of optimizing and managing the processes adopted. This study was aimed at the complete elimination of arsenic from an aqueous medium with minimum energy consumption using the electrocoagulation process. Arsenic removal around 95% was rapidly attained for optimized conditions having a pH of 7, 0.46 A current intensity, 10 mg/L initial concentration and only 2 min of applied time duration using the energy of 3.1 watt-hour per gram of arsenic removed. Low values of applied current for longer durations resulted in the complete removal of arsenic with low energy consumption. Various hydroxide complexes including ferrous hydroxide and ferric hydroxide assisted in the removal of arsenic by adsorption along with co-precipitation. Surface models obtained were checked and found with a reasonably good fit having high values of coefficient of determination of 0.933 and 0.980 for removal efficiency and energy consumption, respectively. Adsorption was found to follow pseudo-first-order kinetics. Multivariate optimization proved it as a low-cost effective technology having an operational cost of 0.0974 Indian rupees (equivalent to USD 0.0013) per gram removal of arsenic. Overall, the process was well optimized using CCD based on response surface methodology

Pretreatment of Slaughterhouse Effluent Treatment Plant Sludge Using Electro-Fenton Process for Anaerobic Digestion

Sludge management is an integral process of an effluent treatment plant (ETP). This study aimed at using the electro-Fenton (EF) process for pretreatment of a cattle-based slaughterhouse ETP sludge to enhance biogas production from anaerobic digestion. EF-oxidation experiments were conducted in 0.5 L beakers with mild-steel electrodes, to study the effect of factors, viz., H2O2 concentration, current density and reaction time on soluble chemical oxygen demand (sCOD) concentration, soluble extracellular polymeric substances (sEPS) concentration and volatile suspended solids (VSS) removal efficiency. This was followed by the quantification of biogas production from the raw and pretreated sludge in anaerobic digestion (AD). Experimental conditions for the EF process were optimized using response surface methodology (RSM). At optimized experimental conditions, EF pretreatment resulted in an increase in sCOD and sEPS concentrations, from 0.91 g/L to 6.1 g/L and 0.18 g/L to 1.4 g/L, respectively. VSS removal efficiency was 68.1%. Batch anaerobic digestion studies demonstrated an enhancement in the specific biogas yield, from 110 NmL/g-VS to 460 NmL/g-VS

Pretreatment of Slaughterhouse Effluent Treatment Plant Sludge Using Electro-Fenton Process for Anaerobic Digestion

Sludge management is an integral process of an effluent treatment plant (ETP). This study aimed at using the electro-Fenton (EF) process for pretreatment of a cattle-based slaughterhouse ETP sludge to enhance biogas production from anaerobic digestion. EF-oxidation experiments were conducted in 0.5 L beakers with mild-steel electrodes, to study the effect of factors, viz., H2O2 concentration, current density and reaction time on soluble chemical oxygen demand (sCOD) concentration, soluble extracellular polymeric substances (sEPS) concentration and volatile suspended solids (VSS) removal efficiency. This was followed by the quantification of biogas production from the raw and pretreated sludge in anaerobic digestion (AD). Experimental conditions for the EF process were optimized using response surface methodology (RSM). At optimized experimental conditions, EF pretreatment resulted in an increase in sCOD and sEPS concentrations, from 0.91 g/L to 6.1 g/L and 0.18 g/L to 1.4 g/L, respectively. VSS removal efficiency was 68.1%. Batch anaerobic digestion studies demonstrated an enhancement in the specific biogas yield, from 110 NmL/g-VS to 460 NmL/g-VS

Restoring TRAIL Mediated Signaling in Ovarian Cancer Cells

Ovarian cancer has emerged as a multifaceted and genomically complex disease. Genetic/epigenetic mutations, suppression of tumor suppressors, overexpression of oncogenes, rewiring of intracellular signaling cascades and loss of apoptosis are some of the deeply studied mechanisms. In vitro and in vivo studies have highlighted different molecular mechanisms that regulate tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) mediated apoptosis in ovarian cancer. In this review, we bring to limelight, expansion in understanding systematical characterization of ovarian cancer cells has led to the rapid development of new drugs and treatments to target negative regulators of TRAIL mediated signaling pathway. Wide ranging synthetic and natural agents have been shown to stimulate mRNA and protein expression of death receptors. This review is compartmentalized into programmed cell death protein 4, platelet-derived growth factor signaling and miRNA control of TRAIL mediated signaling to ovarian cancer. Mapatumumab and PRO95780 have been tested for efficacy against ovarian cancer. Use of high-throughput screening assays will aid in dissecting the heterogeneity of this disease and increasing a long-term survival which might be achieved by translating rapidly accumulating information obtained from molecular and cellular studies to clinic researches

Efficacy of Electrocoagulation Treatment for the Abatement of Heavy Metals: An Overview of Critical Processing Factors, Kinetic Models and Cost Analysis

The electrocoagulation (EC) process introduces coagulants by electrochemical means, and is widely adopted for removing heavy metals, besides other contaminants, such as organic pollutants, suspended and dissolved solids, colloidal materials, etc. However, its capability can vary significantly, depending on the operating conditions. Although most of the investigations so far are limited at the laboratory level with artificially prepared solutions or industrial effluent lacking full- and field-scale studies, the success of the process depends a lot on optimizing the process variable. It has been found that the current density (typically 1–20 mA/cm2), type of electrode (generally aluminum or iron) and minimum electrolysis time are the key process parameters that influence performance. Furthermore, key mechanisms involved in the EC process, including charge neutralization, reduction-oxidation and precipitation/co-precipitation, are crucial for pollutant abatement. This review presents a detailed study undertaking all significant parameters that play a crucial role in the EC process, its mechanism, and improving the efficiency of this process by optimization of these parameters, along with suitable kinetic models

Ovarian Cancer: Interplay of Vitamin D Signaling and miRNA Action

Increasing attention is being devoted to the mechanisms by which cells receive signals and then translate these into decisions for growth, death, or migration. Recent findings have presented significant breakthroughs in developing a deeper understanding of the activation or repression of target genes and proteins in response to various stimuli and of how they are assembled during signal transduction in cancer cells. Detailed mechanistic insights have unveiled new maps of linear and integrated signal transduction cascades, but the multifaceted nature of the pathways remains unclear. Although new layers of information are being added regarding mechanisms underlying ovarian cancer and how polymorphisms in VDR gene influence its development, the findings of this research must be sequentially collected and re-interpreted. We divide this multi-component review into different segments: how vitamin D modulates molecular network in ovarian cancer cells, how ovarian cancer is controlled by tumor suppressors and oncogenic miRNAs and finally how vitamin D signaling regulates miRNA expression. Intra/inter-population variability is insufficiently studied and a better understanding of genetics of population will be helpful in getting a step closer to personalized medicine