Implementation of a 1GHZ frontend using transform domain charge sampling techniques

The recent popularity and convenience of Wireless communication and the need for integration demands the development of Software Defined Radio (SDR). First defined by Mitoal, the SDR processed the entire bandwidth using a high resolution and high speed ADC and remaining operations were done in DSP. The current trend in SDRs is to design highly reconfigurable analog front ends which can handle narrow-band and wideband standards, one at a time. Charge sampling has been widely used in these architectures due to the built in antialiasing capabilities, jitter robustness at high signal frequencies and flexibility in filter design. This work proposed a 1GHz wideband front end aimed at SDR applications using Transform Domain (TD) sampling techniques. Frequency Domain (FD) sampling, a special case of TD sampling, efficiently parallelizes the signal for digital processing, relaxing the sampling requirements and enabling parallel digital processing at a much lower rate and is a potential candidate for SDR. The proposed front end converts the RF signal into current and then it is downconverted using passive mixers. The front end has five parallel paths, each acting on a part of the spectrum effectively parallelizing the front end and relaxing the requirements. An overlap introduced between successive integration windows for jitter robustness was exploited to create a novel sinc2 downsample by two filter topology. This topology was compared to a conventional topology and found to be equivalent and area efficient by about 44%. The proposed topology was used as a baseband filter for all paths in the front end. The chip was sent for fabrication in 45nm technology. The active area of the chip was 6:6mm2. The testing and measurement of the chip still remains to be done

Predictive Internet of Things Based Detection Model of Comatose Patient using Deep Learning

The needs and demands of the healthcare sector are increasing exponentially. Also, there has been a rapid development in diverse technologies in totality. Hence varied advancements in different technologies like Internet of Things (IoT) and Deep Learning are being utilised and play a vital role in healthcare sector. In health care domain, specifically, there is also increasing need to find the possibility of patient going into coma. This is because if it is found that the patient is going into coma, preventive steps could be initiated helping patient and this could possibly save the life of the patient. The proposed work in this paper is in this direction whereby the advancement in technology is utilised to build a predictive model towards forecasting the chances of a patient going into coma state. The proposed system initially consists of different medical devices like sensors which take inputs from the patient and helps aid to monitor the condition of the patient. The proposed system consists of varied sensing devices which will help to record patient’s details such as blood pressure (B.P.), pulse rate, heart rate, brain signal and continuous monitoring the motion of coma patient. The various vital parameters from the patient are taken in continuously and displayed across a graphical display unit. Further as and when even if one vital parameter exceeds certain thresholds, the probability that patient will go into coma increases. Immediately an alert is given in. Further, all such records where there are chances that patient goes into coma state are stored in cloud. Subsequently, based on the data retrieved from the cloud a predictive model using Convolutional Neural Network (CNN) is built to forecast the status of the coma patient as an output for any set of health-related parameters of the patient. The effectiveness of the built predictive model is evaluated in terms of performance metrics such as accuracy, precision and recall. The built forecasting model displays high accuracy up to 98%. Such a system will greatly benefit health sector and coma patients and enable build futuristic and superior predictive and preventive model helping in reducing cases of patient going into coma state

DETERMINING THE EFFICACY OF ISOXYL, A MYCOLIC ACID INHIBITOR, IN VITRO AGAINST MYCOBACTERIA OTHER THAN MYCOBACTERIUM TUBERCULOSIS (MOTT) STRAINS

Mycobacteria other than Mycobacterium tuberculosis (MOTT) cause infections more commonly in the presence of predisposing factors and underlying diseases.They are also notably resistant to commonly used antituberculosis drugs. Total 11 clinical isolates MOTT were included in the study.Drug susceptibility testing of these isolates was performed by Resistant Ratio method. Minimum inhibitory concentration (MIC) pattern of these isolates of MOTT to mycelia acid synthesis inhibitors namely, Isoxyl(ISO) and Isoniazid (INH) were determined by agar dilution and broth dilution method. Minimum bactericidal concentration (MBC) pattern of these isolates to ISO and INH werealso determined. Out of 11 MOTT isolates, 3 isolates were characterized as Mycobacteriumscrofulaceum, 3 isolates as Mycobacteriumfortuitum, 2 isolates as Mycobacteriumflavescens, 1 isolates as Mycobacterium terrae and 2 isolates as Mycobacteriumkansasi depending upon the results of biochemical tests.The MBC range of INH was found to be 0.025 to 6.4 μg/ml and of ISO was found to be 0.6 to 20 μg/ml. Bactericidal activity of ISO was 7.25 times lower than the activity of INH. It is well known that most MOTT species are more resistant to chemotherapeutic agents other than tubercle bacilli.The inhibitory activity of ISO was more to MOTT strains than Mycobacterium tuberculosis strains.There was low bactericidal activity of ISO to MOTT strains, but better than for Mycobacterium tuberculosis strains.&nbsp

Marathi-English Code-mixed Text Generation

Code-mixing, the blending of linguistic elements from distinct languages to form meaningful sentences, is common in multilingual settings, yielding hybrid languages like Hinglish and Minglish. Marathi, India's third most spoken language, often integrates English for precision and formality. Developing code-mixed language systems, like Marathi-English (Minglish), faces resource constraints. This research introduces a Marathi-English code-mixed text generation algorithm, assessed with Code Mixing Index (CMI) and Degree of Code Mixing (DCM) metrics. Across 2987 code-mixed questions, it achieved an average CMI of 0.2 and an average DCM of 7.4, indicating effective and comprehensible code-mixed sentences. These results offer potential for enhanced NLP tools, bridging linguistic gaps in multilingual societies

Congenital acute myeloid leukemia with unique translocation t(11;19)(q23;p13.3)

Congenital leukemia is rarely encountered in clinical practice, even in tertiary children's hospitals. Leukemia may cause significant coagulopathy, putting the patient at risk of intracranial hemorrhage. In this case, the authors present a female infant with a unique mixed phenotypic congenital acute myeloid leukemia showing mixed-lineage leukemia (MLL) rearrangement and severe coagulopathy resulting in a large subdural hematoma. Despite the fatal outcome in this case, neurosurgical treatment of patients with acute myeloid leukemia should be considered if coagulopathy and the clinical scenario allow

A dynamic database of microarray-characterized cell lines with various cytogenetic and genomic backgrounds

The Human Genetic Cell Repository sponsored by the National Institute of General Medical Sciences (NIGMS) contains more than 11,000 cell lines and DNA samples collected from numerous individuals. All of these cell lines and DNA samples are categorized into several collections representing a variety of disease states, chromosomal abnormalities, heritable diseases, distinct human populations, and apparently healthy individuals. Many of these cell lines have previously been studied with detailed conventional cytogenetic analyses, including G-banded karyotyping and fluorescence in situ hybridization. This work was conducted by investigators at submitting institutions and scientists at Coriell Institute for Medical Research, where the NIGMS Repository is hosted. Recently, approximately 900 cell lines, mostly chosen from the Chromosomal Aberrations and Heritable Diseases collections, have been further characterized in detail at the Coriell Institute using the Affymetrix Genome-Wide Human SNP Array 6.0 to detect copy number variations and copy number neutral loss of heterozygosity. A database containing detailed cytogenetic and genomic information for these cell lines has been constructed and is freely available through several sources, such as the NIGMS Repository website and the University of California at Santa Cruz Genome Browser. As additional cell lines are analyzed and subsequently added into it, the database will be maintained dynamically

The Origin and Evolution of Mutations in Acute Myeloid Leukemia

SummaryMost mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is “captured” as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse

Dosage Effects of Cohesin Regulatory Factor PDS5 on Mammalian Development: Implications for Cohesinopathies

Cornelia de Lange syndrome (CdLS), a disorder caused by mutations in cohesion proteins, is characterized by multisystem developmental abnormalities. PDS5, a cohesion protein, is important for proper chromosome segregation in lower organisms and has two homologues in vertebrates (PDS5A and PDS5B). Pds5B mutant mice have developmental abnormalities resembling CdLS; however the role of Pds5A in mammals and the association of PDS5 proteins with CdLS are unknown. To delineate genetic interactions between Pds5A and Pds5B and explore mechanisms underlying phenotypic variability, we generated Pds5A-deficient mice. Curiously, these mice exhibit multiple abnormalities that were previously observed in Pds5B-deficient mice, including cleft palate, skeletal patterning defects, growth retardation, congenital heart defects and delayed migration of enteric neuron precursors. They also frequently display renal agenesis, an abnormality not observed in Pds5B−/− mice. While Pds5A−/− and Pds5B−/− mice die at birth, embryos harboring 3 mutant Pds5 alleles die between E11.5 and E12.5 most likely of heart failure, indicating that total Pds5 gene dosage is critical for normal development. In addition, characterization of these compound homozygous-heterozygous mice revealed a severe abnormality in lens formation that does not occur in either Pds5A−/− or Pds5B−/− mice. We further identified a functional missense mutation (R1292Q) in the PDS5B DNA-binding domain in a familial case of CdLS, in which affected individuals also develop megacolon. This study shows that PDS5A and PDS5B functions other than those involving chromosomal dynamics are important for normal development, highlights the sensitivity of key developmental processes on PDS5 signaling, and provides mechanistic insights into how PDS5 mutations may lead to CdLS