Low Complexity Estimator for Downlink MC-CDMA System

Multi-carrier code division multiple access (MC-CDMA) is a strong candidate for downlink of future mobile communication to obtain high data rates. Nevertheless, during transmission over fading channel, performance of MC-CDMA systems are highly degraded due to presence of multiple access interference(MAI).Therefore channel estimation play an important role in overcoming MAI and characterising the channel to correct the received signal. A low complexity estimator for downlink MC-CDMA is proposed and simulated by MATLAB over a frequency selective fading channel. Comparing with conventional MMSE this algorithm has advantages of low computational complexity. The simulation results demonstrate that MC-CDMA with proposed channel estimator outperforms the OFDM in the practical case of Rayleigh fading environment

Hepatitis B Virus: Inactive carriers

Inactive carriers forms the largest group in chronic HBV infected patients. Around 300 million people are inactive carriers The inactive HBsAg carrier state is diagnosed by absence of HBeAg and presence of anti-HBe, undetectable or low levels of HBV DNA in PCR-based assays, repeatedly normal ALT levels, and minimal or no necroinflammation, slight fibrosis, or even normal histology on biopsy. Inactive cirrhosis may be present in patients who had active liver disease during the replicative phase of infection. The prognosis of the inactive HBsAg carrier state is usually benign. Long-term follow- up (up to 18 years) of these carriers has indicated that the vast majority show sustained biochemical remission and very low risk of cirrhosis or hepatocellular carcinoma (HCC). Rarely, patients, even noncirrhotics, may develop liver cancer during the inactive HBsAg carrier state. In addition, approximately 20 to 30% of persons in the inactive HBsAg carrier state may undergo spontaneous reactivation of hepatitis B during follow-up. Multiple episodes of reactivation or sustained reactivation can cause progressive hepatic damage and even hepatic decompensation. Introductio

SmartMocap: Joint Estimation of Human and Camera Motion using Uncalibrated RGB Cameras

Markerless human motion capture (mocap) from multiple RGB cameras is a widely studied problem. Existing methods either need calibrated cameras or calibrate them relative to a static camera, which acts as the reference frame for the mocap system. The calibration step has to be done a priori for every capture session, which is a tedious process, and re-calibration is required whenever cameras are intentionally or accidentally moved. In this paper, we propose a mocap method which uses multiple static and moving extrinsically uncalibrated RGB cameras. The key components of our method are as follows. First, since the cameras and the subject can move freely, we select the ground plane as a common reference to represent both the body and the camera motions unlike existing methods which represent bodies in the camera coordinate. Second, we learn a probability distribution of short human motion sequences ($\sim$1sec) relative to the ground plane and leverage it to disambiguate between the camera and human motion. Third, we use this distribution as a motion prior in a novel multi-stage optimization approach to fit the SMPL human body model and the camera poses to the human body keypoints on the images. Finally, we show that our method can work on a variety of datasets ranging from aerial cameras to smartphones. It also gives more accurate results compared to the state-of-the-art on the task of monocular human mocap with a static camera. Our code is available for research purposes on https://github.com/robot-perception-group/SmartMocap

Connection Design of Precast Concrete Structures Using Machine Learning Techniques

In this research, the number of dowels (horizontal connection) has been determined using support vector machines (SVM), gradient boosting and artificial neural networks (ANN-Multilayer perceptron). Building height, length and thickness of the wall, maximum shear, maximum compressive force and maximum tension were the input parameters while the output parameter was the number of dowels. 1140 machine learning models were used, out of which 814 were used as training datasets and 326 as test datasets. A coefficient of correlation of 0.9264, root mean square error of 0.3677 and scattering Index of 4.75 % was achieved by SVM radial basis kernel function (SVM-RBF) as compared to a coefficient of correlation of 0.9232, root mean square error of 0.3743 and scattering Index of 4.83 % by resilient ANN-Multilayer perceptron, suggesting that SVM-RBF is more accurate in estimating the number of dowels. The study's encouraging findings highlight the need for additional research into the use of machine learning in civil engineering

Molecular Characterization of Heat Shock Protein 70-1 Gene of Goat (Capra hircus)

Heat shock protein 70 (HSP 70) plays a vital role by bestowing cytoprotection against diverse kinds of stresses. The ubiquitous HSP 70 proteins are the most abundant and temperature sensitive among all the HSPs. The present paper has characterized HSP70-1 cDNA in goat (Capra hircus). Total RNA isolated from goat peripheral blood mononuclear cells was reverse transcribed to cDNA that was used for amplification of HSP 70-1 gene. PCR product (1926 bp) was cloned in pGEM-T easy vector and sequenced. Sequence analysis revealed 1926-bp-long open reading frame of HSP 70-1 gene encoding 641 amino acids in goat, as reported in cattle. At nucleotide level, goat HSP 70-1 was found to be 96–99% similar to that of sheep (partial), cattle, and buffalo whereas the similarity at amino acid level was 95–100%. Nonsynonymous substitutions exceeding synonymous substitutions indicate the evolution of this protein through positive selection among domestic animals. Goat and sheep appear to have diverged from a common ancestor in phylogenetic analysis. Predicted protein structures of goat HSP 70 protein obtained from deduced amino acid sequence indicated that the functional amino acids involved in chaperoning through ATPase hydrolytic cycle and in uncoating of clathrin coated vesicles are highly conserved

The SWI/SNF ATPase Brm Is a Gatekeeper of Proliferative Control in Prostate Cancer

Factors that drive prostate cancer progression remain poorly defined, thus hindering the development of new therapeutic strategies. Disseminated tumors are treated through regimens that ablate androgen signaling, as prostate cancer cells require androgen for growth and survival. However, recurrent, incurable tumors that have bypassed the androgen requirement ultimately arise. This study reveals that the Brm ATPase, a component of selected SWI/SNF complexes, has significant antiproliferative functions in the prostate that protect against these transitions. First, we show that targeted ablation of Brm is causative for the development of prostatic hyperplasia in mice. Second, in vivo challenge revealed that Brm−/− epithelia acquire the capacity for lobe-specific, castration-resistant cellular proliferation. Third, investigation of human specimens revealed that Brm mRNA and protein levels are attenuated in prostate cancer. Fourth, Brm down-regulation was associated with an increased proliferative index, consistent with the mouse model. Lastly, gene expression profiling showed that Brm loss alters factors upstream of E2F1; this was confirmed in murine models, wherein Brm loss induced E2F1 deregulation in a tissue-specific manner. Combined, these data identify Brm as a major effector of serum androgen–induced proliferation in the prostate that is disrupted in human disease, and indicate that loss of Brm confers a proliferative advantage in prostate cancer

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

Primitive neuroectodermal tumor of the kidney in a young male: Case report and review of literature

Primitive neuroectodermal tumor of the kidney is a rare tumor. A total of approximately 79 primary renal cases have been reported to date. Primitive neuroectodermal tumors occur preferentially in the soft-tissues of the paravertebral region and chest wall, less frequently in extremities, with a slight male predominance. We report a case of primitive neuroectodermal tumor of the kidney in a 17-year-old male with a pre-operative diagnosis of renal cell carcinoma-stage 4. The patient underwent radical nephrectomy and histopathological examination revealed a highly aggressive tumor of monotonous sheets of round cells with focal areas of rosette formations and high mitotic rate with Ki67 index of 25-30%. Tumor cells were positive for CD 99 confirming the diagnosis of primitive neuroectodermal tumor. Primitive neuroectodermal tumor of the kidney needs to be kept in mind as a differential diagnosis in young adults presenting with a large kidney mass