Supervised Multi‐Rejector of Periodic Disturbances for Nonlinear Systems Using Decoupled State Multimodel

In this paper, a multi‐rejector of periodic disturbances is proposed for discrete‐time nonlinear systems represented by a decoupled state multimodel. We report a decoupled state multimodel repetitive‐predictive control based on a supervised algorithm to ensure reference trajectory tracking and periodic disturbances rejection. Partial predictors associated to the local controllers make the best choice of the most valid partial controller that meets the desired closed loop performances. The effectiveness of the supervised multi‐rejector is shown via a simulation example. The obtained results are satisfactory and show a good rejection of periodic disturbances and reference trajectory tracking.     

Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

With the increased advancements of smart industries, cybersecurity has become a vital growth factor in the success of industrial transformation. The Industrial Internet of Things (IIoT) or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether. In industry 4.0, powerful Intrusion Detection Systems (IDS) play a significant role in ensuring network security. Though various intrusion detection techniques have been developed so far, it is challenging to protect the intricate data of networks. This is because conventional Machine Learning (ML) approaches are inadequate and insufficient to address the demands of dynamic IIoT networks. Further, the existing Deep Learning (DL) can be employed to identify anonymous intrusions. Therefore, the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection (HGSODL-ID) model for the IIoT environment. The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format. The HGSO algorithm is employed for Feature Selection (HGSO-FS) to reduce the curse of dimensionality. Moreover, Sparrow Search Optimization (SSO) is utilized with a Graph Convolutional Network (GCN) to classify and identify intrusions in the network. Finally, the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model. The proposed HGSODL-ID model was experimentally validated using a benchmark dataset, and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.     

Chitosan/CNTs nanocomposite as green carrier material for pesticides controlled release

Chitosan-based nanocomposites containing gamma-treated carbon nanotubes (CNTs) were developed for controlled release of pesticide. The CNTs were irradiated under gamma irradiation in air at different doses. The transmission electron microscopic images of gamma-treated CNTs showed disentanglement of the tubes without distorting their tubular structure which effectively increased the dispersion properties of CNTs in nanocomposites. X-ray diffraction analysis of CNTs showed some structural changes, and an irradiation dose of 150 kGy is the most effective. Azinphos methyl (AZM) was selected as a model drug, and its release was studied using HPLC technique. Controlled release response of CNTs-based nanocomposites opens a new avenue for pesticides applications because it requires less quantity of pesticides. As a result, the side effects of pesticide in our environment are minimized.     

Conformational transition of Poly (vinylbenzyltrimethylammonium chloride) (PVBTMAC) brush in the presence of Hofmeister anions

This study pertains to the conformational changes of Poly (vinylbenzyltrimethylammonium chloride) (PVBTMAC) brush onto SiO₂-coated resonator; which was further incorporated by using quartz crystal microbalance with dissipation (QCM-D) in the presence of Hofmeister series of anions as a function of ionic strength. Gradual shrinkage of highly extended PVBTMAC followed by loose inhomogeneous layer was on account of change in frequency (?f) and dissipation (??D) at low ionic strength. On the contrary, the increase in ionic strength collapses chains and dense homogenous layer is formed. The chaotropic anions comparativley bring drastic change in frequency unlike kosmotropic anions. This is because weakly hydrated chaotropic anions form strong ion pair with weakly hydrated trimethyl ammonium group on the PVBTMAC brush and as a result strong counter ion condensation was observed on polymer chain. Thus, the apparent mass associated with PVBTMAC chains increases that accounts for large change in ?f.     

Inflammation,Oxidative Stress,Senescence in Atherosclerosis: Thioredoxine-1 as an Emerging Therapeutic Target

Atherosclerosis is a leading cause of cardiovascular diseases (CVD) worldwide and intimately linked to aging. This pathology is characterized by chronic inflammation, oxidative stress, gradual accumulation of low-density lipoproteins (LDL) particles and fibrous elements in focal areas of large and medium arteries. These fibrofatty lesions in the artery wall become progressively unstable and thrombogenic leading to heart attack, stroke or other severe heart ischemic syndromes. Elevated blood levels of LDL are major triggering events for atherosclerosis. A cascade of molecular and cellular events results in the atherosclerotic plaque formation, evolution, and rupture. Moreover, the senescence of multiple cell types present in the vasculature were reported to contribute to atherosclerotic plaque progression and destabilization. Classical therapeutic interventions consist of lipid-lowering drugs, anti-inflammatory and life style dispositions. Moreover, targeting oxidative stress by developing innovative antioxidant agents or boosting antioxidant systems is also a well-established strategy. Accumulation of senescent cells (SC) is also another important feature of atherosclerosis and was detected in various models. Hence, targeting SCs appears as an emerging therapeutic option, since senolytic agents favorably disturb atherosclerotic plaques. In this review, we propose a survey of the impact of inflammation, oxidative stress, and senescence in atherosclerosis; and the emerging therapeutic options, including thioredoxin-based approaches such as anti-oxidant, anti-inflammatory, and anti-atherogenic strategy with promising potential of senomodulation.     

Theranostic Interpolation of Genomic Instability in Breast Cancer

Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. “Omics” technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.     

Eco-friendly food products as source of natural colorant for wool yarn dyeing

ABSTRACT

Food products as a source of natural colorants are gaining widespread popularity around the globe due to their ayurvedic and eco-friendly nature. Current study is aimed with the utilization of food products (Saffron and madder) as a source of dye for woolen yarn. It is found that, for Saffron, irradiation of yarn for 6 min gives high color strength by dyeing for 45 min in the presence of 2% of salts using un-irradiated dye bath of 1 pH, whereas for madder, 4 min is optimal irradiation time for extract to dye irradiated yarn for 25 min in the presence of 6% of salts using the irradiated dye bath of pH 1. The mordanting carried out at optimal conditions show that using both extracts, woolen yarn dyed at optimal conditions has given good color characteristics. It is concluded that microwave radiation has not only improved natural dyeing process but also make the process more eco-friendly and sustainable as well.     

煤矿开采特高压线塔保护煤柱设计与合理留设研究

文中统计分析了11座特高压线塔所处位置煤层的埋深、松散层厚度等地质采矿条件;结合《规范》经验值、两个工作面的地表移动变形实测值,并综合考虑山体采动滑移附加影响,分析得到了地表移动角值参数;采用垂线法,理论计算了保护煤柱尺寸,并通过地质块段法对煤柱压煤量进行了估算.     

Quasi-maximum likelihood estimation of periodic GARCH and periodic ARMA-GARCH processes

Abstract.  This article establishes the strong consistency and asymptotic normality (CAN) of the quasi-maximum likelihood estimator (QMLE) for generalized autoregressive conditionally heteroscedastic (GARCH) and autoregressive moving-average (ARMA)-GARCH processes with periodically time-varying parameters. We first give a necessary and sufficient condition for the existence of a strictly periodically stationary solution of the periodic GARCH (PGARCH) equation. As a result, it is shown that the moment of some positive order of the PGARCH solution is finite, under which we prove the strong consistency and asymptotic normality of the QMLE for a PGARCH process without any condition on its moments and for a periodic ARMA-GARCH (PARMA-PGARCH) under mild conditions.     

Influence of germination techniques on sprout yield,biosynthesis of ascorbic acid and cooking ability,in chickpea (Cicer arietinum L.)

Effects of germination time and illuminations on sprout yield, biosynthesis of ascorbic acid, cooking ability and moisture accumulation in chickpeas were significant (p ? 0.01). Green light had the highest promoting effect on the ascorbic acid level (40.59 mg/100 g) as compared to other illuminations but significantly reduced the sprout yield (188.6 g) as compared to dark, fluorescence and γ-rays illuminations with significantly high sprout yield (196 g) and imbibing moisture (51%). Cooking time was reduced by 43% due to γ-rays in un-soaked seed. Cooking time increased in all treated chickpea samples after 24 h germination and thereafter decreased significantly. Red light significantly increased the cooking time (68.44 min) followed by fluorescent (64.5 min), yellow (61.8 min) and green light (60.9 min). The results indicated that germination of chickpea under green light was an effective process in enhancing ascorbic acid content while dark, fluorescence and γ-rays were effective in promoting sprout growth and to some extent biosynthesis of ascorbic acid.