Enhancement in magnetic permeability of Ni-Co-Zn ferrites using CuO doping for RF and microwave devices

Novel soft magnetic ferrite materials will play a crucial role in next-generation trillion-dollar sensor technologies related to 5G communications and internet of things as these materials can achieve improved wireless power/signal transfer efficiency with high operation frequency. In this work, Ni_0.4Co_0.25Zn_0.35Fe₂O₄ ferrites with high permeability and low magnetic loss were prepared for RF and microwave device applications. Composition and microstructure control is crucial to obtain the desired magnetic and loss properties. CuO dopant (x = 0 wt% to 20 wt%) were employed during the synthesis of Ni_0.4Co_0.25Zn_0.35Fe₂O₄ ferrite specimens to modify the microstructures, thus improving the magnetic properties of the ferrites. High value of measured relative permeability (μ’ of 4-10) and relatively low magnetic loss tangent ( of 0.01-0.1) has been achieved at frequency range between 100 and 800 MHz. Addition of CuO, especially up to 3 wt%, can cause a significant increase in permeability. Real part of the permeability of 3.87 and 10.9 has been achieved for undoped and 3 wt% CuO doped specimens, while noticeable reduction in magnetic losses has been observed for the doped sample measured at 400 MHz. The resonance frequency of synthesized ferrites has also been shifted into GHz range, when higher concentration of CuO dopants (>5 wt%) were employed.     

A low cost approach for the fabrication of microwave phase shifter on laminates

This paper presents a simple and low cost fabrication approach using extended printed circuit board processing techniques for an electrostatically actuated phase shifter on a common microwave laminate. This approach uses 15 μm thin copper foils for realizing the bridge structures as well as for a spacer. A polymeric thin film deposited by spin coating and patterned using lithographic process is used as a dielectric layer to improve the reliability of the device. The prototype of the phase shifter for X-band operation is fabricated and tested for electrical and electromechanical performance parameters. The realized devices have a figure of merit of 70°/dB for a maximum applied bias potential of 85 V. Since these phase shifters can be conveniently fabricated directly on microwave substrates used for feed distribution networks of phased arrays, the overall addition in cost, dimensions and processing for including these phase shifters in these arrays is minimal.

     

The interaction between skill, postures, forces and back pain in wool handling

Wool handling is an important rural occupation where workers process 200 or more fleeces daily, separating them into various quality components. Loads and postures they experience carry substantial risk of low back pain (LBP). Although a formal skill training structure exists, interaction with loads and LBP is unknown. We examined whether skill and LBP influenced trunk postures and loads of 60 wool handlers representing 3 skill levels. LBP prevalence ranged from 20% for junior (lowest skill) to 45% for open class (highest skill) wool handlers. Open class wool handlers demonstrated increased lateral bend and more axially twisted postures, generating greater medio-lateral shear forces and lateral bend and axial twist moments. LBP was associated with open class wool handlers spending more time in severe axially twisted postures. These findings suggest that skill-based training needs to be reviewed to reduce the quantity of axially twisted posture which may help reduce the prevalence of LBP in this workforce.     

Security-Performance Tradeoffs in a Class of Wireless Network Scenarios

There has been an extensive and widespread deployment of wireless local area networks (WLANs) for information access. The transmission, being of a broadcast nature, is vulnerable to security threats and hence, the aspect of security provisioning in these networks has assumed an important dimension. The security of the transmitted data over a wireless channel aims at protecting the data from unauthorized access. The objective is achieved by providing advanced security mechanisms. Implementing strong security mechanisms however, affects the throughput performance and increases the complexity of the communication system. In this paper, we investigate the security performance of a WLAN based on IEEE 802.11b/g/n standards on an experimental testbed in congested and uncongested networks in a single and multi-client environment. Experimental results are obtained for a layered security model encompassing nine security protocols in terms of throughput, response time, and encryption overhead. The performance impact of transmission control protocol and user datagram protocol traffic streams on secure wireless networks has also been studied. Through numerical results obtained from the testbed, we have presented quantitative and realistic findings for both security mechanisms as well as network performance. The tradeoff between the strength of the security protocol and the associated performance is analyzed through computer simulation results. The present real time analysis enables the network designers to make intelligent choices about the implementation of security features and the perceived network performance for a given application scenario.     

N‐Methyl‐Substituted Fluorescent DAG–Indololactone Isomers Exhibit Dramatic Differences in Membrane Interactions and Biological Activity

N‐methyl‐substituted diacylglycerol–indololactones (DAG–indololactones) are newly synthesized effectors of protein kinase C (PKC) isoforms and exhibit substantial selectivity between RasGRP3 and PKCα. We present a comprehensive analysis of membrane interactions and biological activities of several DAG–indololactones. Translocation and binding activity assays underline significant variations between the PKC translocation characteristics affected by the ligands as compared to their binding activities. In parallel, the fluorescent properties of the ligands were employed for analysis of their membrane association profiles. Specifically, we found that a slight change in the linkage to the indole ring resulted in significant differences in membrane binding and association of the DAG–indololactones with lipid bilayers. Our analysis shows that seemingly small structural modifications of the hydrophobic regions of these biomimetic PKC effectors contribute to pronounced modulation of membrane interactions of the ligands.     

Densities and excess molar volumes of mixtures containing diesel,biodiesel and alkanols at temperatures from 288.15 to 313.15 K

The present work is focusing on the synthesization and physico-chemical properties of Jatropha curcas biodiesel with diesel and alcohols.The densities of binary diesel (2)+1-alkanols (C_3 or C_4)(3) and ternary Jatropha curcas biodiesel (1)+diesel (2)+1-alkanols (C_3or C_4)(3) blends have been reported over full range of composition at temperatures within range 288.15 to 313.15 K.Also densities of Jatropha curcas biodiesel (1)+diesel or 1-alkanols (C_3 or C_4)(2) blends have been measured at 313.15 K.Excess molar volumes,V~E,V~E_(123)of binary and ternary blends were calculated from the measured data and the derived properties were correlated to composition using Redlich–Kister equation.A reasonable agreement was found between the measured and estimated values.Further,densities and excess molar volumes data were reasoned to discuss molecular interactions taking into consideration effect of composition and temperature.     

Nanostructured Zn-Fe2O3 thin film modified by Fe-TiO2 for photoelectrochemical generation of hydrogen

Nanostructured semiconductor thin films of Zn-Fe₂O₃ modified with underlying layer of Fe-TiO₂ have been synthesized and studied as photoelectrode in photoelectrochemical (PEC) cell for generation of hydrogen through water splitting. The Zn-Fe₂O₃ thin film photoelectrodes were designed for best performance by tailoring thickness of the Fe-TiO₂ film. A maximum photocurrent density of 748 μA/cm² at 0.95 V/SCE and solar to hydrogen conversion efficiency of 0.47% was observed for 0.89 μm thick modified photoelectrode in 1 M NaOH as electrolyte and under 1.5 AM solar simulator. To analyse the PEC results the films were characterized for various physical and semiconducting properties using XRD, SEM, EDX and UV–Visible spectrophotometer. Zn-Fe₂O₃ thin films modified with Fe-TiO₂ exhibited improved visible light absorption. A noticeable change in surface morphology of the modified Zn-Fe₂O₃ film was observed as compared to the pristine Zn-Fe₂O₃ film. Flatband potential values calculated from Mott–Schottky curves also supported the PEC response.     

Apolipoprotein B mRNA editing and apolipoprotein gene expression in the liver of hyperinsulinemic fatty zucker rats: Relationship to very low density lipoprotein composition

We previously demonstrated increased apolipoprotein B (apoB) mRNA editing, elevated levels of mRNA for the catalytic component of the apoB mRNA editing complex, apobec-1, and increased secretion of the product of the edited mRNA, apoB48, in very low density lipoproteins (VLDL) in primary cultures of Sprague-Dawley rat hepatocytes following insulin treatment. In order to determine the effect of in vivo hyperinsulinemia on these processes, we determined apoB mRNA editing, apobec-1 expression, hepatic expression of mRNA for apoB and other VLDL apoproteins, and the quantity and composition of plasma VLDL in the hyperinsulinemic fatty Zucker rat. Total apoB mRNA content of the livers of the fatty rats and lean littermates did not differ, however, edited apoB message coding for hepatic apo B48, and abundance of mRNA for the catalytic subunit of the apoB mRNA editing complex, apobec-1, was increased by 1.7-and 3.3-fold, respectively, in fatty rats. ApoCIII mRNA abundance was increased in livers of fatty rats as well, but the abundance of hepatic apoE mRNA in the fatty animal was not different from that of the lean rat. Hepatic apoAI mRNA abundance was also increased in the fatty rats. Associated with increased apoB mRNA editing, was the 1.7-fold increase in the fraction of apoB in plasma as apoB48 in fatty rats. VLDL-triglyceride and-apoB in plasma were 15-and 3-fold higher, respectively, in fatty Zucker rats compared to lean littermates, indicating both enrichment of VLDL with triglycerides and increased accumulation of VLDL particles. Increased hepatic expression of mRNA for apoCIII and apoAI was associated with increased content of apoC (and relative depletion of apoE) in VLDL of fatty rats, and plasma apoAI was increased in fatty Zucker rats, primarily in the HDL fraction. The current study provides further evidence that chronic exposure to high levels of insulin influences both the quantity of and lipid/apoprotein composition of VLDL in plasma. The increased apoC and decreased apoE (as well as increased triglyceride) content of VLDL in the fatty Zucker rat observed in the current study may affect VLDL clearance and therefore may be a factor in the observed accumulation of VLDL in the plasma of the fatty hyperinsulinemic Zucker rats.     

Efficient prediction of drug–drug interaction using deep learning models

A drug–drug interaction or drug synergy is extensively utilised for cancer treatment. However, prediction of drug–drug interaction is defined as an ill‐posed problem, because manual testing is only implementable on small group of drugs. Predicting the drug–drug interaction score has been a popular research topic recently. Recently many machine learning models have proposed in the literature to predict the drug–drug interaction score efficiently. However, these models suffer from the over‐fitting issue. Therefore, these models are not so‐effective for predicting the drug–drug interaction score. In this work, an integrated convolutional mixture density recurrent neural network is proposed and implemented. The proposed model integrates convolutional neural networks, recurrent neural networks and mixture density networks. Extensive comparative analysis reveals that the proposed model significantly outperforms the competitive models.Inspec keywords: cancer, learning (artificial intelligence), drugs, recurrent neural nets, convolutional neural nets, drug delivery systemsOther keywords: drug synergy, drug–drug interaction score, drug–drug interaction prediction, deep learning, cancer treatment, machine learning, convolutional mixture density recurrent neural network