Design formulations for non-welded and welded aluminium columns using Continuous Strength Method

Aluminium members are used in structural applications due to their high strength-to-weight ratio, corrosion resistance, attractive appearance, recyclability, ease of production and availability. Thin aluminium sections are susceptible to buckling at a relatively low stress and welding makes it even worse; the design stress i.e. 0.2% proof stress is almost halved in the vicinity of the heat affected zones (HAZs). Currently available design codes have their guidelines both for welded and non-welded aluminium columns, but the predictions for welded aluminium columns are often quite inconsistent. The current research exploits a newly developed strain based design approach the ‘Continuous Strength Method’ (CSM) to predict the behaviour of aluminium members with SHS and RHS cross-sections subjected to compression. A new design curve is proposed herein to predict the cross-sectional resistance in compression; this concept is further extended to propose a new Perry type buckling curve to predict the flexural buckling resistance of aluminium columns. A simplified technique is proposed to include the effect of heat affected zone (HAZ) in CSM formulations. The CSM predictions for aluminium columns are compared against those obtained using available guidelines proposed by the European, American and Australian/ New Zealand standards of aluminium structures. The CSM predictions for non-welded columns are in line with the code predictions, whilst the proposed simple technique for transversely welded columns seems to produce significantly improved predictions.     

One‐Step Hydrothermal Synthesis of 2D Hexagonal Nanoplates of α‐Fe2O3/Graphene Composites with Enhanced Photocatalytic Activity

There has been significant progress in the field of semiconductor photocatalysis, but it is still a challenge to fabricate low‐cost and high‐activity photocatalysts because of safety issues and non‐secondary pollution to the environment. Here, 2D hexagonal nanoplates of α‐Fe₂O₃/graphene composites with relatively good distribution are synthesized for the first time using a simple, one‐step, template‐free, hydrothermal method that achieves the effective reduction of the graphene oxide (GO) to graphene and intimate and large contact interfaces of the α‐Fe₂O₃ nanoplates with graphene. The α‐Fe₂O₃/graphene composites showed significantly enhancement in the photocatalytic activity compared with the pure α‐Fe₂O₃ nanoplates. At an optimal ratio of 5 wt% graphene, 98% of Rhodamine (RhB) is decomposed with 20 min of irradiation, and the rate constant of the composites is almost four times higher than that of pure α‐Fe₂O₃ nanoplates. The decisive factors in improving the photocatalytic performance are the intimate and large contact interfaces between 2D hexagonal α‐Fe₂O₃ nanoplates and graphene, in addition to the high electron withdrawing/storing ability and the highconductivity of reduced graphene oxide (RGO) formed during the hydrothermal reaction. The effective charge transfer from α‐Fe₂O₃ nanoplates to graphene sheets is demonstrated by the significant weakening of photoluminescence in α‐Fe₂O₃/graphene composites.     

Efficient Self‐Assembly Synthesis of Uniform CdS Spherical Nanoparticles‐Au Nanoparticles Hybrids with Enhanced Photoactivity

The treatment of environmental pollution has become one of the most critical issues in the world. Despite the progress made in the study of semiconductor photocatalysis, it is still a challenge to obtain photocatalysts with high activity through relatively simple fabrication processes. In this work, monodisperse CdS spherical nanoparticles (SNPs) of various sizes and good crystallinity are obtained by only adjusting the starting ratio of reactants and the reaction temperature, exhibiting high photocatalytic performances. The photocatalytic rate constant of the ≈ 100 nm CdS SNPs, especially, is more than double that of P25. Furthermore, 3‐mercaptopropyltrimethoxysilane is used to assist the interaction between ≈ 200 nm CdS SNPs and citrate‐stabilized Au nanoparticles (NPs). The significant increase of photocatalytic activity is confirmed by the degradation of Rodamine B (RhB) under Xe light irradiation. At the optimal Au concentration (0.5 wt%), the prepared nanohybrids show the highest photocatalytic activity, exceeding that of pure CdS two times. The superior photocatalytic performances of the CdS SNPs‐Au nanohybrids can be attributed to the intimate interfacial contact between CdS SNPs and Au NPs, which is a contributing factor to the improvement of transfer and the fate of photogenerated charge carriers from CdS SNPs to Au NPs.     

A robust neural network model for fault detection in the presence of mislabelled data

Several data-driven methodologies for process monitoring and detection of faults or abnormalities have been developed for the safety of processing systems. The effectiveness of data-based models, however, is impacted by the volume and quality of training data. This work presents a robust neural network model for addressing the mislabelled and low-quality data in detecting faults and process abnormalities. The approach is based on harnessing data quality features along with supervisory labels in the network training. The data quality has been computed using the Mahalanobis distances and trusted centres of each class of data such as normal and faulty data. The method has been examined for detecting abnormalities in two case studies; a continuous stirred tank heater problem for detecting leaks and the Tennessee Eastman chemical process for detecting step and sticking faults. The performance of the proposed robust artificial neural networks (ANN) model is evaluated in terms of accuracy, fault detection rate, false alarm rate, and classification index at varying extents of mislabelling, namely, 1%, 5%, and 10% mislabelled data. The proposed model demonstrates higher detection performance, especially at increased labels of mislabelled data where the performance of the conventional ANN is severely impacted. The proposed methodology can be advantageous in handling mislabelled and low-quality data issues which are crucial in the data-driven modelling of processing systems.     

Advanced modeling and control of wind conversion systems based on hybrid generators using fractional order controllers

The focus of this study is on modeling and management of a Wind Energy Conversion System (WECS) based on a Hybrid Excitation Synchronous Generator (HESG). Using a wind simulator, two controllers, CRONE and H_∞, are evaluated for Maximum Power Point Tracking (MPPT) and optimal rotation speed. The results show the CRONE controller's higher tracking capability, and robustness tests investigate the influence of parametric uncertainty. Space harmonic effects, commutation effects, and turbine shaft flexibility are all addressed in the sophisticated models. The introduction of Fractional Order Proportional-Integral (FOPI) control for MPPT is a game changer. Although fractional calculus-based accuracy and robustness are uncommon in WECS, they show promise for emissions reduction and increased energy efficiency. This work validates a dependable control approach inside an isolated HESG-based WECS's power-maximizing range. Extensive investigation of the parameters impacting FOPI control efficiency yields useful insights for effective MPPT control. A variable-speed wind turbine (WT) is linked to a HESG through a multiplier, with a controller controlling generator coil excitation voltages and a rectifier connecting the WECS to a load. A thorough 3 kW HESG electrical model that includes generator space harmonics and converter commutation effects is among the contributions. For HESG-based WECS stability, frequency analysis finds important resonant and anti-resonant frequencies. These issues are addressed by a FOPI control technique, which ensures system stability and performance. The necessity of exact frequency analysis in HESG-based WECS is highlighted by a step-by-step controller parameter tuning approach.     

Peripheral mRNA Expression and Prognostic Significance of Emotional Stress Biomarkers in Metastatic Breast Cancer Patients

Emotional stress is believed to be associated with increased tumor progression. Stress-induced epigenetic modifications can contribute to the severity of disease and poor prognosis in cancer patients. The current study aimed to investigate the expression profiles along with the prognostic significance of psychological stress-related genes in metastatic breast cancer patients, to rationalize the molecular link between emotional stress and cancer progression. We profiled the expression of selected stress-associated genes (5-HTT, NR3C1, OXTR, and FKBP5) in breast cancer including the stress evaluation of all participants using the Questionnaire on Distress in Cancer Patients–short form (QSC-R10). A survival database, the Kaplan–Meier Plotter, was used to explore the prognostic significance of these genes in breast cancer. Our results showed relatively low expressions of 5-HTT (p = 0.02) and OXTR (p = 0.0387) in metastatic breast cancer patients as compared to the non-metastatic group of patients. The expression of NR3C1 was low in tumor grade III as compared to grade II (p = 0.04). Additionally, the expression of NR3C1 was significantly higher in patients with positive estrogen receptor status. However, no significant difference was found regarding FKBP5 expression in breast cancer. The results suggest a potential implication of these genes in breast cancer pathology and prognosis.     

Nontoxic and Naturally Occurring Active Compounds as Potential Inhibitors of Biological Targets in Liriomyza trifolii

In recent years, novel strategies to control insects have been based on protease inhibitors (PIs). In this regard, molecular docking and molecular dynamics simulations have been extensively used to investigate insect gut proteases and the interactions of PIs for the development of resistance against insects. We, herein, report an in silico study of (disodium 5′-inosinate and petunidin 3-glucoside), (calcium 5′-guanylate and chlorogenic acid), chlorogenic acid alone, (kaempferol-3,7-di-O-glucoside with hyperoside and delphinidin 3-glucoside), and (myricetin 3′-glucoside and hyperoside) as potential inhibitors of acetylcholinesterase receptors, actin, α-tubulin, arginine kinase, and histone receptor III subtypes, respectively. The study demonstrated that the inhibitors are capable of forming stable complexes with the corresponding proteins while also showing great potential for inhibitory activity in the proposed protein-inhibitor combinations.     

Preliminary Evidence of the Potent and Selective Adenosine A2B Receptor Antagonist PSB-603 in Reducing Obesity and Some of Its Associated Metabolic Disorders in Mice

The adenosine A_2A and A_2B receptors are promising therapeutic targets in the treatment of obesity and diabetes since the agonists and antagonists of these receptors have the potential to positively affect metabolic disorders. The present study investigated the link between body weight reduction, glucose homeostasis, and anti-inflammatory activity induced by a highly potent and specific adenosine A_2B receptor antagonist, compound PSB-603. Mice were fed a high-fat diet for 14 weeks, and after 12 weeks, they were treated for 14 days intraperitoneally with the test compound. The A₁/A_2A/A_2B receptor antagonist theophylline was used as a reference. Following two weeks of treatment, different biochemical parameters were determined, including total cholesterol, triglycerides, glucose, TNF-α, and IL-6 blood levels, as well as glucose and insulin tolerance. To avoid false positive results, mouse locomotor and spontaneous activities were assessed. Both theophylline and PSB-603 significantly reduced body weight in obese mice. Both compounds had no effects on glucose levels in the obese state; however, PSB-603, contrary to theophylline, significantly reduced triglycerides and total cholesterol blood levels. Thus, our observations showed that selective A_2B adenosine receptor blockade has a more favourable effect on the lipid profile than nonselective inhibition.     

Anticoagulants as Potential SARS-CoV-2 Mpro Inhibitors for COVID-19 Patients: In Vitro,Molecular Docking,Molecular Dynamics,DFT, and SAR Studies

In this article, 34 anticoagulant drugs were screened in silico against the main protease (M^pro) of SARS-CoV-2 using molecular docking tools. Idraparinux, fondaparinux, eptifibatide, heparin, and ticagrelor demonstrated the highest binding affinities towards SARS-CoV-2 M^pro. A molecular dynamics study at 200 ns was also carried out for the most promising anticoagulants to provide insights into the dynamic and thermodynamic properties of promising compounds. Moreover, a quantum mechanical study was also conducted which helped us to attest to some of the molecular docking and dynamics findings. A biological evaluation (in vitro) of the most promising compounds was also performed by carrying out the MTT cytotoxicity assay and the crystal violet assay in order to assess inhibitory concentration 50 (IC₅₀). It is worth noting that ticagrelor displayed the highest intrinsic potential for the inhibition of SARS-CoV-2 with an IC₅₀ value of 5.60 µM and a safety index of 25.33. In addition, fondaparinux sodium and dabigatran showed promising inhibitory activities with IC₅₀ values of 8.60 and 9.40 µM, respectively, and demonstrated safety indexes of 17.60 and 15.10, respectively. Moreover, the inhibitory potential of the SARS-CoV-2 M^pro enzyme was investigated by utilizing the SARS-CoV-2 M^pro assay and using tipranavir as a reference standard. Interestingly, promising SARS-CoV-2 M^pro inhibitory potential was attained for fondaparinux sodium with an IC₅₀ value of 2.36 µM, surpassing the reference tipranavir (IC₅₀ = 7.38 µM) by more than three-fold. Furthermore, highly eligible SARS-CoV-2 M^pro inhibitory potential was attained for dabigatran with an IC₅₀ value of 10.59 µM. Finally, an SAR was discussed, counting on the findings of both in vitro and in silico approaches.