The role of translocases was underappreciated and was not included as a separate class in the enzyme commission until August 2018. The recent research interests in proteomics of orphan enzymes, ...ionomics, and metallomics along with high‐throughput sequencing technologies generated overwhelming data and revamped this enzyme into a separate class. This offers a great opportunity to understand the role of new or orphan enzymes in general and specifically translocases. The enzymes belonging to translocases regulate/permeate the transfer of ions or molecules across the membranes. These enzyme entries were previously associated with other enzyme classes, which are now transferred to a new enzyme class 7 (EC 7). The entries that are reclassified are important to extend the enzyme list, and it is the need of the hour. Accordingly, there is an upgradation of entries of this class of enzymes in several databases. This review is a concise compilation of translocases with reference to the number of entries currently available in the databases. This review also focuses on function as well as dysfunction of translocases during normal and disordered states, respectively.
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In this paper we examine the different coping mechanisms used by customers when they confront service failure. It was found that the coping mechanism used by customers changes depending on the ...severity of the service failure. Further, it was observed that brand reputation moderates the relationship between severity of service failure and coping strategies, customer satisfaction and behavioral intentions under different conditions. We conducted an experimental study in an airline travel context. The data supports the proposed model.
Internet of things (IoT) is a very unique platform which is getting very popular day by day. The very reason for this to happen is the advancement in technology and its ability to get linked to ...everything. This feature of getting linked has in itself provided multiple opportunities and a vast scope of development. The fact that technology in various fields has evolved through the years, is the reason why we observe a rapid change in the shape, size and capacity of various instruments, components and the products used in daily life. And this benefit of simplified technology when accompanied by a platform like IoT eases the work as well as benefits both the manufacturer and the end user. The Internet of Things gives us an opportunity to construct effective administrations, applications for manufacturing, lifesaving solutions, proper cultivation and more. This paper proposes an extensive overview of the IoT technology and its varied applications in life saving, smart cities, agricultural, industrial etc. by reviewing the recent research works and its related technologies. It also accounts the comparison of IoT with M2M, points out some disadvantages of IoT. Furthermore, a detailed exploration of the existing protocols and security issues that would enable such applications is elaborated. Potential future research directions, open areas and challenges faced in the IoT framework are also summarized.
The Internet of Things (IoT) intelligently facilitates individuals interacting with the real-world applications which forms smart environment through internet connectivity at anywhere anytime ...(dynamic in nature), the devices in an IoT environment encounters several security threats. To overcome these security challenges numerous state of art approaches have been implemented to ensure the security of IoT appliances, but still innovative methods are desirable. The traditional Machine learning (ML) integrates with deep learning algorithm exhibits a potential of detecting abnormal intrusion patterns by formulating a seamless option for anomaly-based detection. This work proposed a Dynamic Distributed—Generative Adversarial Network (DD-GAN) with Improved Firefly Optimization- Hybrid Deep Learning based Convolutional Neural Network -Adaptive Neuro-Fuzzy Inference System (IFFO-HDLCNN + ANFIS) that takes gain of IoT's power, offers enhanced behavior for efficiently examining the entire traffic which traverses in the IoT. Initially, Synthetic Minority Over-sampling Technique (SMOTE) is engaged for pre-processing of data and then Modified Principal Component Analysis (MPCA) is being applied for feature reduction. The optimal features are selected through the Improve Firefly Optimization (IFFO) for optimum fitness value to enhance the classification accuracy of HDLCNN. Finally the intrusion detection is carried out by HDLCNN + ANFIS model, which is competent in detecting threats. The experimental results have proven that model demonstrates ability to perceive any kind of probable intrusion and anomalous behavior. In comparison to existing methods, the suggested IFFO-HDLCNN + ANFIS algorithm delivers improved intrusion detection performance regarding higher accuracy, precision, recall, f-measure, reduced False Positive Rate (FPR).
Detection of malignant lung nodules at an early stage may allow for clinical interventions that increase the survival rate of lung cancer patients. Using hybrid deep learning techniques to detect ...nodules will improve the sensitivity of lung cancer screening and the interpretation speed of lung scans. Accurate detection of lung nodes is an important step in computed tomography (CT) imaging to detect lung cancer. However, it is very difficult to identify strong nodes due to the diversity of lung nodes and the complexity of the surrounding environment. Here, we proposed lung nodule detection and classification with CT images based on hybrid deep learning (LNDC-HDL) techniques. First, we introduce a chaotic bird swarm optimization (CBSO) algorithm for lung nodule segmentation using statistical information. Second, we illustrate an improved Fish Bee (IFB) algorithm for feature extraction and selection. Third, we develop a hybrid classifier i.e. hybrid differential evolution-based neural network (HDE-NN) for tumor prediction and classification. Experimental results have shown that the use of computed tomography, which demonstrates the efficiency and importance of the HDE-NN specific structure for detecting lung nodes on CT scans, increases sensitivity and reduces the number of false positives. The proposed method shows that the benefits of HDE-NN node detection can be reaped by combining clinical practice.
Flexible energy storage devices are the cornerstone to the development of future-generation electronics such as flexible displays on phones, smart bands, laptops, and televisions. The advancement of ...flexible supercapacitors has turned into an essential task because supercapacitors are designed with the rewards of optimum power and energy density. Owing to the dual function as an electrical double-layer capacitor and a pseudocapacitor, heteroatom-doped graphene is presumed to be a promising electrode material for supercapacitor applications. Herein, we report p-toluenesulfonic acid as the precursor to the formation of sulfur-doped graphene by supercritical fluid-aided processing. Both the existence and nature of S doping in graphene were confirmed with the elemental and X-ray photoelectron spectroscopy techniques. Full cell analysis indicated that the energy density achieved using hydroquinone (HQ) as a redox additive in 1 M H2SO4 solution was found to be 27 W h/kg, which is twice that of an aqueous solution of 1 M H2SO4 (13 W h/kg). To extend the application of the symmetric cell, a flexible device using polyvinyl alcohol (PVA)/HQ/H2SO4 is fabricated. A 3-fold increase in energy density is observed for the flexible solid-state single device using PVA/HQ/H2SO4 (E = 21.3 W h/kg) when compared with PVA/H2SO4 as an electrolyte (E = 7.7 W h/kg).
End-functionalised polymer grafted nanoparticles (PGNs) form bonds when their coronas overlap. The bonded interactions between the overlapping PGNs depend on the energy of the bonds (
U
). In the ...present study, oscillatory deformation imposed on a simple system with interacting PGNs placed on the vertices of a triangle is employed to examine the local dynamics as a function of energy of the bonds and the frequency of oscillation relative to the characteristic rupture frequency,
ω
0
= 2π
ν
exp(−
U
/
k
B
T
), of the bonds. In particular, the effect of functional anisotropy is studied by introducing bonds of two different energies between adjacent PGNs. A multicomponent model developed by Kadre and Iyer,
Macromol. Theory Simul.
, 2021,
30
, 2100005, that combines the features of effective interactions between PGNs, self-consistent field theory and master equation approach to study bond kinetics is employed to obtain the local dynamics. The resulting force-strain curves are found to exhibit a simple broken symmetry where
F
x
(
γ
,
&z.ggrda;
) ≠ −
F
x
(−
γ
,−
&z.ggrda;
) and
F
y
(
γ
,
&z.ggrda;
) ≠
F
y
(−
γ
,−
&z.ggrda;
) in systems with functional anisotropy. Fourier analysis of the dynamic response reveals that functional anisotropy leads to finite even harmonic terms and systematic variation of both the elastic and dissipative response from that of the isotropic systems. Furthermore, the intra-cycle variations in the strain stiffening and shear thickening ratios obtained from the analysis indicate that functional anisotropy leads to anisotropic nonlinear response.
Dynamics depends on anisotropy introduced
via
energy of bonded interactions between end-functionalised polymer grafted nanoparticles (PGNs).
A simple one-pot methodology is developed for the synthesis of nitrogen doped graphene via supercritical fluid (SCF) processing using glycine as a nitrogen precursor. The presence of various ...N-containing functional groups was determined by FT-IR and the amount of N-doping in the graphene was found to be 4.5 wt% using the elemental analysis and X-ray photoelectron spectroscopy. The electrochemical capacitance measurements are performed using cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance spectroscopy. The nitrogen doped graphene exhibited enhanced capacitive performance with a maximum specific capacitance of 270 F/g at 0.5 A/g current density with high specific capacitance retention of 90% over 10,000 cycles at 10 A/g current density. The fabricated symmetric supercapacitor cell showed a high energy density of 4.1 and 36 Wh/kg in aqueous and ionic liquid electrolyte, respectively. The high energy density obtained in ionic liquid is promising for their potential application in electrochemical energy system.
•N-doped graphene synthesis via supercritical fluid processing using glycine.•N-doped graphene (4.5 wt%) got a high specific capacitance of 270 F/g @ 0.5 A/g.•High specific capacitance retention of 90% over 10,000 cycles at 10 A/g.•Energy density in ionic liquid is 9 times higher than aqueous electrolyte.
