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.     

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.     

Positively equicontinuous flows

Let G be a positively equicontinuous flow of homeomorphisms of a locally compact metric space E. We show how the dynamics of such a flow are rich. We study when regularly almost periodic elements in G are periodic and we describe orbits and their limit sets. In particular, we show that the limit set L(G?) of G is a closed subset on which G is equicontinuous and that if G moreover has closed orbits, then any w-limit set is a periodic orbit.     

Risk analysis: Casing-while-Drilling (CwD) and modeling approach

In today's volatile economy and uncertain drilling environment, managers are encouraged to reduce well cost and time and have implemented Casing-while-Drilling (CwD) to improve operational excellence. Risk analysis is another valid tool that can be used to improve drilling operations. This paper discusses CwD as a new technology and how its benefits can be strengthened by including risk analysis as a complementary technique. A modeling approach is presented to demonstrate how risk analysis can be applied to CwD programs and to discuss the main concerns a well planner must address to achieve a successful drilling program. The integration of both CwD and risk analysis will add value to the overall excellence of the well operation. Very little work has been done on this integration, and the hope is that this approach will be a standard practice in the future.     

Systems Approach Vs. Decision-Tree Analysis: An Offshore Development Decision

A good investment decision-making process is one that is able to assess risk and uncertainty and is able to manage these in a balanced manner. A common practice in the oil and gas industry is to use a decision-tree analysis as a way to incorporate risk and uncertainty in investment decisions. In this article, we introduce an alternative called the system's approach based on a stochastic integrated asset model. The objective is to use the tried and tested decision-tree approach to show the validity of the system's approach and to show that with the incorporation of an infinite number of outcomes, decision-tree analysis results would approximate the results of the system's approach and then demonstrate the superiority of the system's approach. For a hypothetical but realistic example, we demonstrate that the decision-tree results differ by 5% for the mean and 20% for the standard deviation when compared to the system's approach. The decision-tree approach tends to underestimate the low side and overestimate the high side. This difference is due to the fact that the system's approach captures complexity, uncertainty, dependency, and interaction more accurately than the decision tree approach.     

Effect of metal oxide nanofluids on the performance of passive solar still single slope for two different absorbent plates

This study aims to improve the performances of a solar still single slope using metal oxide nanofluid (Al₂O₃–water, Cu₂O–water, and TiO₂–water). The numerical study was carried out for the climatic conditions of Agadir, Morocco, with different concentrations of nanofluids inside a basin equipped with an absorber plate with two different absorptivities. The numerical study is based on thermal balance equations applied on different solar system components and solved using the Runge Kutta method. The numerical model is validated by comparing our results with the literature available data. A comparison study of the effect of these nanofluids on solar still productivity is done. The results show that the productivity of the solar still using nanoparticles Cu₂O, TiO₂, and Al₂O₃ are 7.38, 7.1, and 7.064 kg m⁻² day⁻¹, respectively. It is obtained that the maximum efficiency of the solar still is found to be 55.27% by using cuprous oxide nanoparticles. Furthermore, an enhancement in solar still productivity of 6.36%, 19.54%, and 33.25% is obtained by dispersing 1%, 3%, and 5% volume fraction of Cu₂O nanoparticles in pure water, respectively compared to the conventional solar. Moreover, the impact of the absorptivity of the absorber plate on the solar still effectiveness is investigated. Two types of coatings are considered to change the absorber plate absorptivity. The results indicate that the efficiencies of the solar system are 58.81% and 51.77% using an absorber plate with 0.95 and 0.85 of absorptivity, respectively.     

Experimental and numerical study of granular medium-rough wall interface friction

Wall roughness plays a crucial role in granular medium - rough wall interface friction. In this study, an experimental device has been designed to study the influence of boundary conditions, more specifically wall roughness, on the behavior of sheared granular medium. The study is based on use of an analog model, and consists of simulating roughness by means of notches and grains in the medium by monodisperse beads and on use of a numerical model based on the discrete element method. The test protocol entails displacing at fixed speed notched rods under confined granular medium. Movement of the beads layer near the rods as well as friction of the beads against the rods are both studied herein. Results indicate that the parameter controlling friction at the granular medium - rough wall interface is primarily the depth of beads embedment in surface asperities. The objective of the associated numerical modeling is to supplement the experimental results.     

Influence of Alumina-Supported M–Pt Catalysts in DeNOx Reactions with M = Pd or Ir or Ru

To better understand N₂ formation in the selective catalytic reduction of NO _x by propene under oxidative atmosphere, we studied the catalytic behavior of bimetallics. Surface segregation phenomena may provoke geometric and electronic modifications of the catalytic active sites. To explain our results we invoked: (i) the facile way to oxidize the bimetallic aggregates, (ii) the presence of atoms with low coordination number able to be oxidized first and (iii) an eventual formation of like vic-diNO _x species on such bimetallics leading to N₂ formation.     

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.