Synthesis,characterization and magnetic properties of polythiophene/SrFe12-x(ZrZn)0.5xO19 nanocomposite as a microwave absorber

Ferrites are an important group of magnetic materials which are used as absorbers. The incorporation of ferrite and conducting polymer achieves great enhancement in microwave absorption properties. The nanocomposites of hexagonal ferrites embedded by conducting polymers such as polypyrrole, polyaniline and polythiophene (PTH) have been paid much attention. In the present study, strontium hexagonal ferrite doped by Zr and Zn with the final formula of SrFe_12-x(ZrZn)_0.5xO19 considering x = 0.9 and embedded by PTH was produced to achieve a nanocomposite with the highest microwave absorbing ability. In this study, after synthesis of SrFe₁₂O₁₉(ZrZn)_0.5xO19 and PTH, the nanocomposite was prepared by in situ polymerization. Wrapping the ferrite particles and PTH chains could form nanocomposite properly, and therefore acceptable interactions were observable between SrFe_12-x(ZrZn)_0.5xO19ferrite particles and PTH polymer chains in the composites. Assessing the X-ray diffraction (XRD) patterns of SrFe_12-x(ZrZn)_0.5xO19, PTH, and PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite indicated that the PTH characteristic peak shifts slightly and its peak intensity reduces, which may be attribute to the coating of PTH polymer chains onto SrFe_12-x(ZrZn)_0.5xO19 particles. We revealed also lower magnetic properties in the obtained nanocomposite. The morphological assessment also suggested that PTH could effectively coat the SrFe_12-x(ZrZn)_0.5xO19 particles. The synergistic effect of SrFe_12-x(ZrZn)_0.5xO19 particle plus PTH leads to microwave absorption percentage higher than 95% by PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite. Overall, nanocomposite creating by coupling interaction between SrFe_12-x(ZrZn)_0.5xO19 particles (x = 0.9) and PTH can effectively lead to achieve the highest rate of absorption of electromagnetic waves.     

CaDHN3, a Pepper (Capsicum annuum L.) Dehydrin Gene Enhances the Tolerance against Salt and Drought Stresses by Reducing ROS Accumulation

Dehydrins (DHNs) play an important role in abiotic stress tolerance in a large number of plants, but very little is known about the function of DHNs in pepper plants. Here, we isolated a Y₁SK₂-type DHN gene “CaDHN3” from pepper. To authenticate the function of CaDHN3 in salt and drought stresses, it was overexpressed in Arabidopsis and silenced in pepper through virus-induced gene silencing (VIGS). Sub-cellular localization showed that CaDHN3 was located in the nucleus and cell membrane. It was found that CaDHN3-overexpressed (OE) in Arabidopsis plants showed salt and drought tolerance phenotypic characteristics, i.e., increased the initial rooting length and germination rate, enhanced chlorophyll content, lowered the relative electrolyte leakage (REL) and malondialdehyde (MDA) content than the wild-type (WT) plants. Moreover, a substantial increase in the activities of antioxidant enzymes; including the superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), ascorbate peroxidase (APX), and lower hydrogen peroxide (H₂O₂) contents and higher O₂^•− contents in the transgenic Arabidopsis plants. Silencing of CaDHN3 in pepper decreased the salt- and drought-stress tolerance, through a higher REL and MDA content, and there was more accumulation of reactive oxygen species (ROS) in the CaDHN3-silenced pepper plants than the control plants. Based on the yeast two-hybrid (Y2H) screening and Bimolecular Fluorescence Complementation (BiFC) results, we found that CaDHN3 interacts with CaHIRD11 protein in the plasma membrane. Correspondingly, the expressions of four osmotic-related genes were significantly up-regulated in the CaDHN3-overexpressed lines. In brief, our results manifested that CaDHN3 may play an important role in regulating the relative osmotic stress responses in plants through the ROS signaling pathway. The results of this study will provide a basis for further analyses of the function of DHN genes in pepper.     

Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

Scattering of an induced surface electromagnetic field by fatiguecracks in ferromagnetic metals

In crack detection and sizing by the alternating current field measurement technique, U-shaped wires or coils excited by a high-frequency AC current source can be used to induce the surface field in the workpiece. The authors present a modeling technique for the interaction of a fatigue crack in a ferromagnetic metal with the surface field resulting from an inducer with two U-shaped wires. This work is an extension of a previous modeling technique to have developed for infinitely long (one-dimensional) cracks. In the present technique, the boundary of the fatigue crack is approximated by a circular arc, leading to a formulation for an efficient computation of the field-flaw interaction. Various numerical and experimental results supporting the modeling and illustrating the behavior of the magnetic field and electric potential at the metal surface around circular-arc cracks are presented     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

     

Incorporation of a Regularization Term to Control Negative Correlation in Mixture of Experts

Combining accurate neural networks (NN) in the ensemble with negative error correlation greatly improves the generalization ability. Mixture of experts (ME) is a popular combining method which employs special error function for the simultaneous training of NN experts to produce negatively correlated NN experts. Although ME can produce negatively correlated experts, it does not include a control parameter like negative correlation learning (NCL) method to adjust this parameter explicitly. In this study, an approach is proposed to introduce this advantage of NCL into the training algorithm of ME, i.e., mixture of negatively correlated experts (MNCE). In this proposed method, the capability of a control parameter for NCL is incorporated in the error function of ME, which enables its training algorithm to establish better balance in bias-variance-covariance trade-off and thus improves the generalization ability. The proposed hybrid ensemble method, MNCE, is compared with their constituent methods, ME and NCL, in solving several benchmark problems. The experimental results show that our proposed ensemble method significantly improves the performance over the original ensemble methods.     

A mashup based framework for multi level healthcare interoperability

Healthcare delivery is evolving from disease-centered to patient-centered care delivery where patients are active participants in their healthcare delivery. This calls for more communication and collaboration among all healthcare actors. There is also an increasing demand for personalized healthcare systems that provide effective information management, facilitate communication and collaboration, and support applications to meet user requirements. To address these challenges, we need to advance the integration and interoperability of healthcare applications in a controlled manner. Drawing upon a conceptual model from a collaborative care case study, we identified a set of interoperability requirements and developed a Mashup based interoperability framework. Our framework allows patients and other healthcare actors to engage in collaborative processes through online applications facilitated by mashups. We then use proof-of-concept implementations to demonstrate how our framework is able to facilitate different types of interoperability. We believe that collaborative technologies such as mashups can implement process interoperability requirements to support collaborative care delivery, particularly for asynchronous care delivery.     

A Methionine Chemical Shift Based Order Parameter Characterizing Global Protein Dynamics

Coupling of side chain dynamics over long distances is an important component of allostery. Methionine side chains show the largest intrinsic flexibility among methyl-containing residues but the actual degree of conformational averaging depends on the proximity and mobility of neighboring residues. The ¹³C NMR chemical shifts of the methyl groups of methionine residues located at long distances in the same protein show a similar scaling with respect to the values predicted from the static X-ray structure by quantum methods. This results in a good linear correlation between calculated and observed chemical shifts. The slope is protein dependent and ranges from zero for the highly flexible calmodulin to 0.7 for the much more rigid calcineurin catalytic domain. The linear correlation is indicative of a similar level of side-chain conformational averaging over long distances, and the slope of the correlation line can be interpreted as an order parameter of the global side-chain flexibility.