Intelligent Intrusion Detection System for Industrial Internet of Things Environment

Rapid increase in the large quantity of industrial data, Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation, data sensing and collection, real-time data processing, and high request arrival rates. The classical intrusion detection system (IDS) is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity. To resolve these issues, this paper designs a new Chaotic Cuckoo Search Optimization Algorithm (CCSOA) with optimal wavelet kernel extreme learning machine (OWKELM) named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform. The CCSOA-OWKELM technique focuses on the design of feature selection with classification approach to achieve minimum computation complexity and maximum detection accuracy. The CCSOA-OWKELM technique involves the design of CCSOA based feature selection technique, which incorporates the concepts of chaotic maps with CSOA. Besides, the OWKELM technique is applied for the intrusion detection and classification process. In addition, the OWKELM technique is derived by the hyperparameter tuning of the WKELM technique by the use of sunflower optimization (SFO) algorithm. The utilization of CCSOA for feature subset selection and SFO algorithm based hyperparameter tuning leads to better performance. In order to guarantee the supreme performance of the CCSOA-OWKELM technique, a wide range of experiments take place on two benchmark datasets and the experimental outcomes demonstrate the promising performance of the CCSOA-OWKELM technique over the recent state of art techniques.     

Determination of methyl gallate in Bauhinia retusa extract by high-performance liquid and thin-layer chromatography

Two stability-indicating chromatographic methods are reported for the determination of methyl gallate in crude extracts of Bauhinia retusa. Separation by high performance thin layer chromatography was conducted on silica gel aluminum sheets using 9.5:0.5:0.2 (v/v/v) chloroform:methanol:acetic acid at 280 nm. The results from the 2–40 µg/band were used to prepare a linear calibration graph. The limits of detection and quantitation were 0.5 and 1.5 µg/band, respectively. The reverse phase high performance liquid chromatographic isolation of methyl gallate was performed at ambient temperature with an injection volume of 10 μL. The mobile phase consisted of 40:60 (v/v) methanol:0.1% ortho-phosphoric acid. The separation was performed at 1 mL/min using a detection wavelength of 280 nm. The calibration graph for methyl gallate was rectilinear from 0.02–40 µg/mL with limits of detection and quantitation of 0.004 and 0.010 µg/mL, respectively. For both methods, intra-day and inter-day precision were evaluated and the relative standard deviation was less than 2%, indicating good precision. The robustness was evaluated by making small and deliberate changes to appropriate parameters and the calculated relative standard deviation was less than 2%.The chromatographic methods were employed to determine methyl gallate in crude Bauhinia retusa extracts.     

Relative importance of informational units and their role in long-term recall by closed-head-injured patients and control groups.

Applied qualitative analysis to the information recalled by control Ss and closed-head-injured (CHI) patients. The Logical Memory subtest of the Wechsler Memory Scale (WMS) was administered to 40 CHI and 40 control Ss. Recall was tested immediately after administration, 40 min later, and 24 hrs later. The analysis took into account the importance of recalled information as determined by a prior rating according to 3 levels of importance. Results suggest that CHI patients have difficulty selectively retrieving the most important information after a long delay. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

PAI-1 in Diabetes: Pathophysiology and Role as a Therapeutic Target

Hypofibrinolysis is a key abnormality in diabetes and contributes to the adverse vascular outcome in this population. Plasminogen activator inhibitor (PAI)-1 is an important regulator of the fibrinolytic process and levels of this antifibrinolytic protein are elevated in diabetes and insulin resistant states. This review describes both the physiological and pathological role of PAI-1 in health and disease, focusing on the mechanism of action as well as protein abnormalities in vascular disease with special focus on diabetes. Attempts at inhibiting protein function, using different techniques, are also discussed including direct and indirect interference with production as well as inhibition of protein function. Developing PAI-1 inhibitors represents an alternative approach to managing hypofibrinolysis by targeting the pathological abnormality rather than current practice that relies on profound inhibition of the cellular and/or acellular arms of coagulation, and which can be associated with increased bleeding events. The review offers up-to-date knowledge on the mechanisms of action of PAI-1 together with the role of altering protein function to improve hypofirbinolysis. Developing PAI-1 inhibitors may form for the basis of future new class of antithrombotic agents that reduce vascular complications in diabetes.     

Analysis of extraocular muscle-infiltrating T cells in thyroid-associated ophthalmopathy (TAO)

Bone morphogenetic protein-2 (BMP-2), a member of transforming growth factor-beta superfamily, inhibits the terminal differentiation of C2C12 myoblasts and changes their differentiation pathway into cells expressing osteoblast phenotypes such as alkaline phosphatase (ALP) activity and osteocalcin production (Katagiri et al., 1994, J. Cell Biol. 127, 1755-1766). Two type I receptors for BMP-2 (BMPR-IA and BMPR-IB) have been cloned, but the role of the respective receptors in signal transduction is not clear. In the present study, we examined the signal transduction of BMP-2 in C2C12 cells using constitutively activated mutant BMPR-IA and BMPR-IB. C2C12 cells expressed BMPR-IA and BMPR-II mRNAs, but not BMPR-IB mRNA at detectable levels in Northern blotting. When mutated BMPR-IA and BMPR-IB were transiently transfected into C2C12 cells, both BMPR-IA and BMPR-IB similarly induced ALP activity in the absence of BMP-2. We also established subclonal cell lines of C2C12 cells by stably transfecting mutated BMPR-IB. When the mutated BMPR-IB-transfected cells were cultured in medium with low serum (differentiation medium) without BMP-2, the cells differentiated into ALP-positive mononuclear cells and not into myosin heavy chain-positive myotubes. These mutated BMPR-IB-transfected cells expressed ALP activity and osteocalcin mRNA in a time-dependent manner, but neither muscle creatine kinase nor myogenin mRNAs. These results indicate that the mutated BMP-2 type I receptors can constitutively transduce BMP-2 signals in the absence of the ligand in C2C12 cells.     

Innovative polyelectrolytes/poly(ionic liquid)s for energy and the environment

This paper presents the work carried out within the European project RENAISSANCE‐ITN, which was dedicated to the development of innovative polyelectrolytes for energy and environmental applications. Within the project different types of innovative polyelectrolytes were synthesized such as poly(ionic liquid)s coming from renewable or natural ions, thiazolium cations, catechol functionalities or from a new generation of cheap deep eutectic monomers. Further, macromolecular architectures such as new poly(ionic liquid) block copolymers and new (semi)conducting polymer/polyelectrolyte complexes were also developed. As the final goal, the application of these innovative polymers in energy and the environment was investigated. Important advances in energy storage technologies included the development of new carbonaceous materials, new lignin/conducting polymer biopolymer electrodes, new iongels and single‐ion conducting polymer electrolytes for supercapacitors and batteries and new poly(ionic liquid) binders for batteries. On the other hand, the use of innovative polyelectrolytes in sustainable environmental technologies led to the development of new liquid and dry water, new materials for water cleaning technologies such as flocculants, oil absorbers, new recyclable organocatalyst platforms and new multifunctional polymer coatings with antifouling and antimicrobial properties. All in all this paper demonstrates the potential of poly(ionic liquid)s for high‐value applications in energy and enviromental areas. © 2017 Society of Chemical Industry     

Hybrid Metaheuristics with Deep Learning Enabled Automated Deception Detection and Classification of Facial Expressions

Automatic deception recognition has received considerable attention from the machine learning community due to recent research on its vast application to social media, interviews, law enforcement, and the military. Video analysis-based techniques for automated deception detection have received increasing interest. This study develops a new self-adaptive population-based firefly algorithm with a deep learning-enabled automated deception detection (SAPFF-DLADD) model for analyzing facial cues. Initially, the input video is separated into a set of video frames. Then, the SAPFF-DLADD model applies the MobileNet-based feature extractor to produce a useful set of features. The long short-term memory (LSTM) model is exploited for deception detection and classification. In the final stage, the SAPFF technique is applied to optimally alter the hyperparameter values of the LSTM model, showing the novelty of the work. The experimental validation of the SAPFF-DLADD model is tested using the Miami University Deception Detection Database (MU3D), a database comprised of two classes, namely, truth and deception. An extensive comparative analysis reported a better performance of the SAPFF-DLADD model compared to recent approaches, with a higher accuracy of 99%.     

Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

Multicarrier Waveform (MCW) has several advantages and plays a very important role in cellular systems. Fifth generation (5G) MCW such as Non-Orthogonal Multiple Access (NOMA) and Filter Bank Multicarrier (FBMC) are thought to be important in 5G implementation. High Peak to Average Power Ratio (PAPR) is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user devices. The paper presents a novel Divergence Selective Mapping (DSLM) and Divergence Partial Transmission Sequence (D-PTS) for 5G waveforms. It is seen that the proposed D-SLM and PTS lower PAPR with low computational complexity. The work highlighted a combination of multi-data block partial transmit schemes along with tone reservation. In this, an overlapping factor is used to determine the number of data blocks for every group. Here, considering only those data blocks that have minimum signal power, the use of DSLM and DPTS are required to eliminate the segment’s peaks. Simulation results reveal that the suggested hybrid technique proves to be better than the conventional PTS scheme. Furthermore, the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing (OFDM) waveform.