DST Systems

About: DST Systems is a based out in . It is known for research contribution in the topics: Population & Acquired immunodeficiency syndrome (AIDS). The organization has 1341 authors who have published 1336 publications receiving 25018 citations.

Managed virtual point to point communication service having verified directory, secure transmission and controlled delivery

Abstract: A system for providing a managed virtual point to point communication service having a verified directory and providing secure transmission and controlled delivery of electronic document images may include a memory, an interface, and a processor. The memory may store a verified directory of users. The interface may communicate with devices of sending and receiving users in the verified directory. The processor may be operative to receive a request to deliver an electronic document image from a sending user to a receiving user. The processor may provide secure access to the electronic document image to the receiving user. The processor may provide a delivery confirmation to the sending device of the sending user upon determining that the electronic document image was securely accessed by the receiving user. The delivery confirmation may indicate that the electronic document image was securely transmitted to the receiving user.

Structures of nucleobases trapped within Au triangles and its effects on hydrogen bonding in base pairs of DNA.

Abstract: Nucleobases (adenine (A), thymine (T), cytosine (C), and guanine (G)) trapped within two metal clusters such as Au3 undergo expansion. Our investigation reveals that this primarily arises due to the concomitant increase in all the bond lengths in molecules. Such expansion of the molecules can be qualitatively understood on the basis of classical harmonic potentials in the bonds and loss of aromaticity in the rings. Specifically, the highly electronegative O and N elements in the base pairs anchor to Au atoms and form X−Au bonds, which leads to charge redistribution within the molecules. As a very important consequence of this, the nature of the hydrogen bonds (in Au3−A···T−Au3 and in Au3−G···C−Au3) change substantially within these electrodes in comparison to gas-phase structures. These hydrogen bonds have a single-well potential energy profile (of the type N···H···O and N···H···N) instead of double-well potentials (like N−H···O or N−H···N/ N···H−N types). A detailed energy calculation along the proton mo...

Excessive Cytolytic Responses Predict Tuberculosis Relapse After Apparently Successful Treatment

Abstract: Background Identification of patients at risk of tuberculosis relapse following treatment would revolutionize clinical trials of new drugs and regimens and facilitate clinical management. The study aim was to determine whether tuberculosis patients who subsequently suffer relapse have different immune responses to mycobacteria in vitro compared to patients who remain cured for two years post-treatment. Methods First episode pulmonary tuberculosis patients were recruited into a surrogate marker study in Cape Town, South Africa. Peripheral blood samples were collected at diagnosis and after two and four weeks of tuberculosis treatment. Diluted blood was cultured with live Mycobacterium tuberculosis for six days and cellular RNA was frozen. Gene expression in samples from ten patients who subsequently relapsed, confirmed by stain genotyping, was compared to those who remained cured using Affymetrix microarrays. Results At diagnosis, the expression of 668 genes was significantly different in samples from patients who subsequently relapsed compared to successfully cured patients, and these differences persisted for at least four weeks. Gene Ontology and biological pathways analyses revealed the most significant difference was up-regulation of genes involved in cytotoxic cell-mediated killing, such as perforin, granulysin and fas ligand. Results were confirmed by qRT-PCR in a wider patient cohort. Conclusions These data show that patients who will subsequently relapse exhibit altered immune responses at diagnosis, including excessively robust cytolytic responses to M. tuberculosis in vitro, compared to patients who will achieve durable cure. Together with microbiological and clinical indices, these differences could be exploited for patient stratification in drugs trials, or for host-directed therapy development. Venous blood samples were diluted in culture medium and stimulated with live M. tuberculosis for 6 days. Samples from 10 TB patients who subsequently relapsed and 10 patients whore remained disease-free for 2 years. Samples collected at TB diagnosis and after 2 weeks or 4 weeks of treatment of first TB episode.

Real time speech emotion recognition using RGB image classification and transfer learning

Abstract: This paper describes a real-time Speech Emotion Recognition (SER) task formulated as an image classification problem The shift to an image classification paradigm provided the advantage of using an existing Deep Neural Network (AlexNet) pre-trained on a very large number of images, and thus eliminating the need for a lengthy network training process Two alternative multi-class SER systems, AlexNet-SVM and FTAlexNet, were investigated Both systems were shown to achieve state-of-the-art results when tested on a popular Berlin Emotional Speech (EMO-DB) database Transformation from speech to image classification was achieved by creating RGB images depicting speech spectrograms The ALEXNet-SVM method passes the spectrogram images as inputs to a pre-trained Convolutional Neural Network (AlexNet) to provide features for the Support Vector Machine (SVM) classifier, whereas the FTAlexNet method simply applies the images to a fine tuned AlexNet to provide emotional class labels The FTAlexNet offers slightly higher accuracy compared to the AlexNet-SVM, while the AlexNet-SVM requires a lower number of computations due to the elimination of the neural network training procedure A real-time demo is given on: https://wwwyoutubecom/watch?v=fuMpF3cUqDU&t=6s

A fuzzy similarity-based rough set approach for attribute selection in set-valued information systems

Abstract: Databases obtained from different search engines, market data, patients’ symptoms and behaviours, etc., are some common examples of set-valued data, in which a set of values are correlated with a single entity. In real-world data deluge, various irrelevant attributes lower the ability of experts both in speed and in predictive accuracy due to high dimension and insignificant information, respectively. Attribute selection is the concept of selecting those attributes that ideally are necessary as well as sufficient to better describe the target knowledge. Rough set-based approaches can handle uncertainty available in the real-valued information systems after the discretization process. In this paper, we introduce a novel approach for attribute selection in set-valued information system based on tolerance rough set theory. The fuzzy tolerance relation between two objects using a similarity threshold is defined. We find reducts based on the degree of dependency method for selecting best subsets of attributes in order to obtain higher knowledge from the information system. Analogous results of rough set theory are established in case of the proposed method for validation. Moreover, we present a greedy algorithm along with some illustrative examples to clearly demonstrate our approach without checking for each pair of attributes in set-valued decision systems. Examples for calculating reduct of an incomplete information system are also given by using the proposed approach. Comparisons are performed between the proposed approach and fuzzy rough-assisted attribute selection on a real benchmark dataset as well as with three existing approaches for attribute selection on six real benchmark datasets to show the supremacy of proposed work.