A flame retarded chitosan binder for insulating miscanthus/recycled textile fibers reinforced biocomposites

The main objective of this study is devoted to the development of new insulating and ignifuged miscanthus fibers (Mf)/recycled textile fibers (RTf) reinforced biocomposites (BCs) using chitosan as polysaccharide-based binder and aluminum trihydroxide (ATH) fillers while focusing on the fire behavior. To achieve this goal, a preliminary study was carried out on flame retarded chitosan-based films with various ATH-filler ratios (20, 33, 50, and 60 wt %). ATG and pyrolysis-combustion flow calorimeter analysis showed significant improvement of chitosan thermal behavior with the addition of 33 wt % and above of ATH. Mechanical properties of films were, however, degraded. Thereafter, different ratios of miscanthus/RTf reinforced BCs (fibers content up to 89.5–90 wt %) were elaborated through thermocompression process using neat chitosan and chitosan/ATH (67/33 wt %) as a binder. Mechanical, thermal, and fire behavior were evaluated. Higher mechanical properties were found for hybrid materials containing the association of both RTf and Mf in comparison to those containing only RTf or Mf. Fireproof BCs (E rating: according to the NF EN ISO 11925-2), with thermal conductivity values between 0.07 and 0.09 W m⁻¹ K⁻¹ and density range between 270 and 299 kg m⁻³ were successfully elaborated. The results of this study show a promising use of the chitosan/ATH system as flame retardant for biobased insulating building materials. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47306.     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

Allicin May Promote Reversal of T-Cell Dysfunction in Periodontitis via the PD-1 Pathway

We evaluated the role of allicin in periodontitis using an in silico and in vitro design. An in silico docking analysis was performed to assess the plausible interactions between allicin and PD-L1. The cytokine profile of gingival crevicular fluid (GCF) samples obtained from periodontitis patients was estimated by cytometric bead array. CD3+ lymphocytes isolated from the peripheral blood were sorted and characterized using immunomagnetic techniques. Cultured and expanded lymphocytes were treated with the GCF samples to induce T-cell exhaustion. Optimum concentrations of allicin were added to exhausted lymphocytes to compare the expression of TIM-3 and LAG-3 gene expression at baseline and post-treatment. Allicin was found to bind to the PD-L1 molecule as revealed by the in-silico experiment, which is possibly an inhibitory interaction although not proven. GCF from periodontitis patients had significantly higher concentrations of TNF-α, CCL2, IL-6, IFN-γ, and CXCL8 than controls. GCF treatment of CD3+ lymphocytes from the periodontitis patients significantly increased expression of T-cell exhaustion markers TIM-3 and LAG-3. Allicin administration with GCF treatment resulted in significant lowering of the expression of exhaustion markers. Allicin may exert an immunostimulatory role and reverse immune-destructive mechanisms such as T-cell exhaustion.     

Detection,Identification, and Prevalence of Pathogenic Vibrio parahaemolyticus in Fish and Coastal Environment in Jordan

Vibrio parahaemolyticus is widely distributed in the marine environments and considered the leading cause of human gastroenteritis in Asian countries. A total of 150 marketed fish and 50 water and sediment samples from the Gulf of Aqaba were examined for the prevalence of pathogenic strains of V. parahaemolyticus. A total of 132 typical isolates obtained from the primary selective medium (thiosulfate‐citrate bile salt sucrose agar) and showed positive biochemical properties were subjected to confirmation by polymerase chain reaction targeting the gyrB and toxR genes. These genes were confirmed at rates of 82% (108 isolates) and 72% (95 isolates), respectively. The toxR positive isolates were tested for the presence of thermolabile hemolysin (tlh), thermostable direct hemolysin (tdh), and tdh‐related hemolysin (trh) virulence genes. Accordingly, the prevalence rates of pathogenic V. parahaemolyticus were 4%, 8%, and 12% in sediment, water, and fish samples, respectively. The 16S rRNA amplification and sequences were conducted for confirmation of the isolates and showing the relatedness among these isolates. The results showed that both 16S rRNA and toxR assays had same sensitivity and tested isolates had high nucleotide similarity irrespective of their sources.     

The bacteriological quality of Kishfa and Yoghurt in Mosul City, Iraq

Bacteriological quality of the milk products Al-Kishfa and Yoghurt sold in Mosul was investigated. The incidence of Escherichia coli and Faecal streptococci was higher in Kishfa, while Staphylococcus aureus and Pseudomonas aeruginosa were higher in Yoghurt.     

A Competition between Hydrogen,Stacking, and Halogen Bonding in N-(4-((3-Methyl-1,4-dioxo-1,4-dihydronaphthalen-2-yl)selanyl)phenyl)acetamide: Structure,Hirshfeld Surface Analysis, 3D Energy Framework Approach,and DFT Calculation

N-(4-((3-Methyl-1,4-dioxo-1,4-dihydronaphthalen-2-yl)selanyl)phenyl)acetamide (5), C₁₉H₁₅NO₃Se, was prepared in two steps from 4,4′-diselanediyldianiline (3) via reduction and subsequent nucleophilic reaction with 2-methyl-3-bromo-1,4-naphthalenedione, followed by acetylation with acetic anhydride. The cytotoxicity was estimated against 158N and 158JP oligodendrocytes and the redox profile was also evaluated using different in vitro assays. The technique of single-crystal X-ray diffraction is used to confirm the structure of compound 5. The enantiopure 5 crystallizes in space group P21 with Flack parameter 0.017 (8), exhibiting a chiral layered absolute structure. Molecular structural studies showed that the crystal structure is foremost stabilized by N-H···O and relatively weak C-H···O contacts between molecules, and additionally stabilized by weak C-H···π and Se···N interactions. Hirshfeld surface analysis is used to quantitatively investigate the noncovalent interactions that stabilize crystal packing. Framework energy diagrams were used to graphically represent the stabilizing interaction energies for crystal packing. The analysis of the energy framework shows that the interactions energies of and C-H···π and C-O···π are primarily dispersive and are the crystal’s main important forces. Density functional theory (DFT) calculations were used to determine the compound’s stability, chemical reactivity, and other parameters by determining the HOMO-LUMO energy differences. The determination of its optimized surface of the molecular electrostatic potential (MEP) was also carried out. This study was conducted to demonstrate both the electron-rich and electron-poor sites.     

A Heuristics-Based Cost Model for Scientific Workflow Scheduling in Cloud

Scientific Workflow Applications (SWFAs) can deliver collaborative tools useful to researchers in executing large and complex scientific processes. Particularly, Scientific Workflow Scheduling (SWFS) accelerates the computational procedures between the available computational resources and the dependent workflow jobs based on the researchers’ requirements. However, cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate (near-optimal) solution within polynomial computational time. Motivated by this, current work proposes a novel SWFS cost optimization model effective in solving this challenge. The proposed model contains three main stages: (i) scientific workflow application, (ii) targeted computational environment, and (iii) cost optimization criteria. The model has been used to optimize completion time (makespan) and overall computational cost of SWFS in cloud computing for all considered scenarios in this research context. This will ultimately reduce the cost for service consumers. At the same time, reducing the cost has a positive impact on the profitability of service providers towards utilizing all computational resources to achieve a competitive advantage over other cloud service providers. To evaluate the effectiveness of this proposed model, an empirical comparison was conducted by employing three core types of heuristic approaches, including Single-based (i.e., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Invasive Weed Optimization (IWO)), Hybrid-based (i.e., Hybrid-based Heuristics Algorithms (HIWO)), and Hyper-based (i.e., Dynamic Hyper-Heuristic Algorithm (DHHA)). Additionally, a simulation-based implementation was used for SIPHT SWFA by considering three different sizes of datasets. The proposed model provides an efficient platform to optimally schedule workflow tasks by handling data-intensiveness and computational-intensiveness of SWFAs. The results reveal that the proposed cost optimization model attained an optimal Job completion time (makespan) and total computational cost for small and large sizes of the considered dataset. In contrast, hybrid and hyper-based approaches consistently achieved better results for the medium-sized dataset.