Analysis of grapefruit sulphur volatiles using SPME and pulsed flame photometric detection

Sulphur volatiles are major factors in the perceived aroma of grapefruit juice, GFJ. The objective of this study was to develop a procedure to concentrate, separate, identify and quantify the major volatile sulphur compounds, VSC’s, in grapefruit juices. SPME parameters such as headspace atmosphere, fibre coating, extraction time and temperature were evaluated. High resolution capillary GC using ZB-5, DB-Wax and PLOT columns coupled with pulsed flame photometric detection, PFPD, were employed for separation and detection. Thirteen sulphur volatiles were identified including; hydrogen sulphide, sulphur dioxide, methanethiol, dimethyl sulphide, carbon disulphide, dimethyl disulphide, 2-methyl thiophene, 3-methyl thiophene, methional, dimethyl trisulphide, 3-mercaptohexylacetate, 2,8-epithio-cis-p-menthane and 1-p-menthene-8-thiol. Five additional VSC’s were tentatively identified. Canned reconstituted GFJ had more total sulphur volatiles and a greater number than fresh GFJ. Hydrogen sulphide comprised over 80% of total sulphur volatiles in fresh GFJ but only 5% in canned GFJ.     

Wear Behavior of Composites Based on ZA-27 Alloy Reinforced by Al<Subscript>2</Subscript>O<Subscript>3</Subscript> Particles Under Dry Sliding Condition

In present study, the effect of Al₂O₃ particle reinforcement on the sliding behavior of ZA-27 alloy composites was investigated. The composites with 3, 5, and 10 wt% of Al₂O₃ particles were produced by the compocasting procedure. Tribological properties of unreinforced alloy and composite were studied, using block-on-disk tribometer under unlubricated sliding conditions at different specific loads and sliding speeds. The worn surfaces of samples were examined by the scanning electron microscopy (SEM). The test results revealed that those composite specimens exhibited significantly lower wear rate than the ZA-27 matrix alloy specimens in all combinations of applied loads and sliding speeds. The difference in the wear resistance of composite with respect to the matrix alloy, increased with the increase of the applied load/sliding speed and Al₂O₃ particle content. The highest degree of improvement of the ZA-27 alloy tribological behavior corresponded with change of the Al₂O₃ particles content from 3 to 5 wt%. At low sliding speed, moderate lower wear rate of the composites over that of the matrix alloy was noticed. This has been attributed to micro cracking tendency of the composites. Significantly reduced wear rate, experienced by the composite over that of the matrix alloy at the higher sliding speeds and loads, could be explained due to enhanced compatibility of matrix alloy with dispersoid phase and greater thermal stability of the composite in view of the presence of the dispersoid. Level of wear rate of tested ZA-27/Al₂O₃ samples pointed to the process of mild wear, which was primarily controlled by the formation and destruction of mechanical mixed layers (MMLs).     

Correction of pressure drop in a heavily loaded hybrid bearing when starting by using a constant flow lubrication system- Application to a rotary cement mill

We analyzed a lubricated journal plain bearing supporting heavy loaded rotary mill. During start-up operating, after the shaft is lifted by high external pressure lubricant, the speed of the shaft grows from 0 to the operating hydrodynamic speed when, suddenly after the first thirty seconds of shaft rotation, the pressure drops in one recess causing excessive damage to the pad bearing interface. The aim was to understand and provide some answers to the pressure drop in order to give an appropriate correction. Misalignment between the shaft and bearing surfaces was considered and analyzed in first part of the study. According to the obtained results the proposed correction is to use a suitable constant flow lubrication system which avoids the pressure to drop in recesses. A real application was made on a partial pad bearing supporting a heavy rotary cement mill localized at the cement plant of Chlef in Algeria.

     

Aerobic Training in Young Men Increases the Transfer of Cholesterol to High Density Lipoprotein In Vitro: Impact of High Density Lipoprotein Size

Exercise training not only improves the plasma lipid profile but also reduces risk of developing coronary heart disease. We investigate whether plasma lipids and high density lipoprotein (HDL) metabolism are affected by aerobic training and whether the high-density lipoprotein cholesterol (HDL-C) levels at baseline influence exercise-induced changes in HDL. Seventy-one male sedentary volunteers were evaluated and allocated in two subgroups, according to the HLD-C levels (< or >40 mg/dL). Participants underwent an 18-week aerobic training period. Blood was sampled before and after training for biochemical analysis. Plasma lipids, apolipoproteins, HDL diameter, and VO₂ peak were determined. Lipid transfers to HDL were determined in vitro by incubating plasma samples with a donor lipid artificial nanoemulsion. After the 18-week period of aerobic training, the VO₂ peak increased, while the mean body mass index (BMI) decreased. HDL-C concentration was higher after the training period, but low-density lipoprotein cholesterol (LDL-C) and non-HDL-C did not change. The transfer of esterified cholesterol and phospholipids was greater after exercise training, but the triacylglycerol and unesterified cholesterol transfers were unchanged. The HDL particle diameter increased after aerobic training in all participants. When the participants were separated in low-HDL and normal-HDL groups, the postaerobic exercise increment in HDL-C was higher in the low-HDL group, while the transfer of esterified cholesterol was lower. In conclusion, aerobic exercise training increases the lipid transfers to HDL, as measured by an in vitro method, which possibly contributes to the classical elevation of the HDL-C associated with training.     

Nanocomposites of ultrahigh molar mass polyethylene and modified carbon nanotubes

In this work, the use of a laboratory twin-screw extruder was evaluated to process ultrahigh molar mass polyethylene and composites with carbon nanotubes (CNTs). Commercial polymer samples with lubricant (1%) and different percentages (0.01%, 0.05%, and 0.1%) of pure, oxidized, and chemically surface treated multi-walled carbon nanotubes (MWCNTs) were evaluated. The results showed that polymer melting and crystallization temperatures were not affected by CNTs, although an increase in the degree of crystallinity in all nanocomposites was observed along with a decrease in crystal size. Therefore, CNTs behaved as nucleating agents. All ultrahigh molar mass polyethylene (UHMWPE)/CNT samples showed increased initial degradation temperature, although this was not very great when introducing acetylated and stearic acid modified CNTs. Both oxidized CNTs and stearic acid CNTs did not markedly improve the composites' mechanical properties. Therefore, the nanocomposites containing pure CNTs and most of those with acetylated CNTs resulted in higher reinforcement for UHMWPE. The addition of the lubricant allowed the polymer matrix to be processed in the extruder, whereas the increase in CNT content in UHMWPE improved the stiffness of the material. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47459     

Prediction of postpartum depression using machine learning techniques from social media text

Early screening of mental disorders plays a crucial role in diagnosis and treatment. This study explores how data‐driven methods can leverage the information available on social media platforms to predict postpartum depression (PPD). A generalized approach is proposed where linguistic features are extracted from user‐generated textual posts on social media and categorized as general, depressive, and PPD representative using multiple machine learning techniques. We find that techniques used in our study exhibit strong predictive capabilities for PPD content. Holdout validation showed that multilayer perceptron outperformed other techniques such as support vector machine and logistic regression used in this study with 91.7% accuracy for depressive content identification and up to 86.9% accuracy for PPD content prediction. This work adopts a hierarchical approach to predict PPD. Therefore, the reported PPD accuracy represents the performance of the model to correctly classify PPD content from non‐PPD depressive content.     

Boundary stabilisation of the wave equation in the presence of singularities

We study the boundary stabilisation of the wave equation by a nonlinear feedback active on a part of the boundary in geometric situations for which the solutions have singularities. These singularities appear at the interfaces at which the mixed Neumann–Dirichlet boundary conditions meet. Under a simple geometrical condition concerning the orientation of the boundary, we obtain sharp energy decay rates under a general growth assumption on the feedback. We show that the singularities do not affect the energy decay rates and give examples.     

IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19

The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables in layer 2. In layer 1, the initial identification for COVID-19 is considered, whereas in layer 2, the different factors involved are studied. Finally, advanced lab tests are conducted to identify the actual current status of the disease. The major focus of this study is to build an IoMT-based smart monitoring system that can be used by anyone exposed to COVID-19; the system would evaluate the user’s health condition and inform them if they need consultation with a specialist for quarantining. MATLAB-2019a tool is used to conduct the simulation. The COVID-19 IoMTSM-HMFIS system has an overall accuracy of approximately 83%. Finally, to achieve improved performance, the analysis results of the system were shared with experts of the Lahore General Hospital, Lahore, Pakistan.     

Nanoparticle–Plant Interactions: Two‐Way Traffic

In this Review, an effort is made to discuss the most recent progress and future trend in the two‐way traffic of the interactions between plants and nanoparticles (NPs). One way is the use of plants to synthesize NPs in an environmentally benign manner with a focus on the mechanism and optimization of the synthesis. Another way is the effects of synthetic NPs on plant fate with a focus on the transport mechanisms of NPs within plants as well as NP‐mediated seed germination and plant development. When NPs are in soil, they can be adsorbed at the root surface, followed by their uptake and inter/intracellular movement in the plant tissues. NPs may also be taken up by foliage under aerial deposition, largely through stomata, trichomes, and cuticles, but the exact mode of NP entry into plants is not well documented. The NP–plant interactions may lead to inhibitory or stimulatory effects on seed germination and plant development, depending on NP compositions, concentrations, and plant species. In numerous cases, radiation‐absorbing efficiency, CO₂ assimilation capacity, and delay of chloroplast aging have been reported in the plant response to NP treatments, although the mechanisms involved in these processes remain to be studied.