Detection of radio-frequency modulated optical signals by two and three terminal microwave devices

An interdigitated photoconductor (two terminal device) on GaAlAs/GaAs heterostructure was fabricated and tested by an electro-optical sampling technique. Further, the photoresponse of GaAlAs/GaAs HEMT (three terminal device) was obtained by illuminating the device with an optical signal modulated up to 8 GHz. Gain-bandwidth product, response time, and noise properties of photoconductor and HEMT devices were obtained. Monolithic integration of these photodetectors with GaAs microwave devices for optically controlled phased array antenna applications is discussed

Effect of soy in men with type 2 diabetes mellitus and subclinical hypogonadism: a randomised controlled study

Context: Isoflavones found in soy products have a chemical structure similar to estrogen, leading to concerns of an adverse estrogenic effect in men, particularly in those with type 2 diabetes mellitus (T2DM) who have low testosterone levels due to hypogonadism. Objective: The primary outcome was change in total testosterone levels. The secondary outcomes were the changes in glycaemia and cardiovascular risk markers. Design: Randomised double blind parallel study. Setting: Secondary care setting in UK. Participants: 200 men with T2DM with a total testosterone level≤12nmol/L Intervention: 15g soy protein with 66mg of isoflavones (SPI) or 15g soy protein alone without isoflavones (SP) daily as snack bars for three months. Results: There was no change in either total testosterone or in absolute free testosterone levels with either SPI or SP. There was an increase in TSH and reduction in fT4 (p<0.01) after SPI supplementation. Glycaemic control improved with a significant reduction in HbA1c (-4.19(7.29)mmol/mol,p<0.01) and HOMA-IR after SPI. Cardiovascular risk improved with a reduction in triglycerides, CRP and diastolic BP (p<0.05) with SPI versus SP supplementation. There was 6% improvement in 10-year coronary heart disease risk after three months of SPI supplementation. Endothelial function improved with both SPI and SP supplementation (p<0.01) with an increased reactive hyperemia index that was greater for the SPI group (p<0.05). Conclusions: Testosterone levels were unchanged and there was a significant improvement in glycaemia and cardiovascular risk markers with SPI compared to SP alone over three months. There was significant increase in TSH and a reduction in fT4

Special Section on Attacking and Protecting Artificial Intelligence

Modern artificial intelligence systems largely rely on advanced algorithms, including machine learning techniques such as deep learning. The research community has invested significant efforts in understanding these algorithms, optimally tuning them, and improving their performance, but it has mostly neglected the security facet of the problem. Recent attacks and exploits demonstrated that machine learning-based algorithms are susceptible to attacks targeting computer systems, including backdoors, hardware trojans and fault attacks, but are also susceptible to a range of attacks specifically targeting them, such as adversarial input perturbations. Implementations of machine learning algorithms are often crucial proprietary assets for companies thus need to be protected. It follows that implementations of artificial intelligence-based algorithms are an attractive target for piracy and illegitimate use and, as such, they need to be protected as all other IPs. This is equally important for machine learning algorithms running on remote servers vulnerable to micro-architectural exploits.Published versio

C-band superconductor/semiconductor hybrid field-effect transistor amplifier on a LaAlO3 substrate

A single-stage C-band superconductor/semiconductor hybrid field-effect transistor amplifier was designed, fabricated, and tested at 77 K. The large area (1 inch x 0.5 inches) high temperature superconducting Tl-Ba-Ca-Cu-O (TBCCO) thin film was rf magnetron sputtered onto a LaAlO3 substrate. The film had a transition temperature of about 92 K after it was patterned and etched. The amplifier showed a gain of 6 dB and a 3 dB bandwidth of 100 MHz centered at 7.9 GHz. An identical gold amplifier circuit was tested at 77 K, and these results are compared with those from the hybrid amplifier

Performance of a Y-Ba-Cu-O superconducting filter/GaAs low noise amplifier hybrid circuit

A superconducting 7.3 GHz two-pole microstrip bandpass filter and a GaAs low noise amplifier (LNA) were combined into an active circuit and characterized at liquid nitrogen temperatures. This superconducting/semiconducting circuit's performance was compared to a gold filter/GaAs LNA hybrid circuit. The superconducting filter/GaAs LNA hybrid circuit showed higher gain and lower noise figure than its gold counterpart

Measurement techniques for cryogenic Ka-band microstrip antennas

The measurement of cryogenic antennas poses unique logistical problems since the antenna under test must be embedded in a cooling chamber. A method of measuring the performance of cryogenic microstrip antennas using a closed cycle gas cooled refrigerator in a far field range is described. Antenna patterns showing the performance of gold and superconducting Ka-band microstrip antennas at various temperatures are presented

Pcleavage: an SVM based method for prediction of constitutive proteasome and immunoproteasome cleavage sites in antigenic sequences

This manuscript describes a support vector machine based method for the prediction of constitutive as well as immunoproteasome cleavage sites in antigenic sequences. This method achieved Matthew's correlation coefficents of 0.54 and 0.43 on in vitro and major histocompatibility complex ligand data, respectively. This shows that the performance of our method is comparable to that of the NetChop method, which is currently considered to be the best method for proteasome cleavage site prediction. Based on the method, a web server, Pcleavage, has also been developed. This server accepts protein sequences in any standard format and present results in a user-friendly format. The server is available for free use by all academic users at the URL or

Co(II) Complexes of Pyridine-2-aldoxime & 6-Methylpyridine-2-aldoxime

1018-101

SVM based method for predicting HLA-DRB1<SUP>&#8727;</SUP>0401 binding peptides in an antigen sequence

Summary: Prediction of peptides binding with MHC class II allele HLA-DRB10401 can effectively reduce the number of experiments required for identifying helper T cell epitopes.This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1&#8727;0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique. Available: A web server HLA-DR4Pred based on above approach is available at http://www.imtech.res.in/raghava/ hladr4pred/ and http://bioinformatics.uams.edu/mirror/ ladr4pred/ (Mirror Site)

Classification of nuclear receptors based on amino acid composition and dipeptide composition

Nuclear receptors are key transcription factors that regulate crucial gene networks responsible for cell growth, differentiation, and homeostasis. Nuclear receptors form a superfamily of phylogenetically related proteins and control functions associated with major diseases (e.g. diabetes, osteoporosis, and cancer). In this study, a novel method has been developed for classifying the subfamilies of nuclear receptors. The classification was achieved on the basis of amino acid and dipeptide composition from a sequence of receptors using support vector machines. The training and testing was done on a non-redundant data set of 282 proteins obtained from the NucleaRDB data base (1). The performance of all classifiers was evaluated using a 5-fold cross validation test. In the 5-fold cross-validation, the data set was randomly partitioned into five equal sets and evaluated five times on each distinct set while keeping the remaining four sets for training. It was found that different subfamilies of nuclear receptors were quite closely correlated in terms of amino acid composition as well as dipeptide composition. The overall accuracy of amino acid composition-based and dipeptide compositionbased classifiers were 82.6 and 97.5%, respectively. Therefore, our results prove that different subfamilies of nuclear receptors are predictable with considerable accuracy using amino acid or dipeptide composition. Furthermore, based on above approach, an online web service, NRpred, was developed, which is available at www.imtech.res.in/raghava/nrpred