293 research outputs found
Catheter associated urinary tract infection in an acute care setting of a tertiary care centre in South India
Background: Catheter associated UTI is a serious cause of morbidity and mortality in intensive care unit (ICU) patients. Hence, authors undertook the present study to know the prevalence of catheter associated urinary tract infections (CAUTI) in medical ICU patients of tertiary care centre and to know the antibiotic resistance pattern of the causative organisms.Methods: A one-year prospective study was carried out from September 2015 to August 2016. Demographic data from the catheterized patients were collected daily and scrutinized for the signs and symptoms as per CDC criteria for confirmation as CAUTI. Relevant antimicrobial resistance data of etiologic agents were also collected to ascertain the prevalent resistance pattern.Results: The overall incidence of CAUTI was 14.69 per 1000 catheterized days in the present study. Out of the 37 diagnosed CAUTI cases, 12 (32.4%) were males and 25 (67.6%) were females with maximum patients being between 40 to 60 years of age. The commonest uropathogens was Escherichia coli (n=26) followed by K. pneumoniae (n=5). Both Escherichia coli and Klebsiella pneumoniae isolates were found to be 100% resistant to cefotaxime, ceftazidime and cefuroxime. Pseudomonas aeruginosa and Acinetobacter species were least common etiological culprits and demonstrated complete resistance to all the tested antibiotics.Conclusions: In the present study the prevalence of CAUTI is much higher which needs to be rectified by continuous monitoring and training of the staff in implementation of infection control practices in a proactive manner
Quality Analysis of Software Applications using Software Reliability Growth Models and Deep Learning Models
Finding the faults in the software is a very tedious task. Many software companies are trying to develop high-quality software which is having no faults. It is very important to analyze the errors, faults, and bugs in software development. Software reliability growth models (SRGM's) are used to help the software industries to create quality software products. Quality is the software metric that is used to analyze the performance of the software product. The software product which is having no errors or faults is considered the best software product. SRGM is also utilized to analyze the software quality based on the programming language. Deep Learning (DL) is a sub-domain in machine learning to solve several complex issues in software development. Finding accurate patterns from software faults is a very tedious task. DL algorithm performs better in integrating the SRGM with the DL approaches giving better results based on software fault detection. Many software faults real-time datasets are available to analyze the DL approaches. The performances of the various integrated models are analyzed by showing the quality metrics
Living, moving, breathing : ranking of European cities in sustainable transport
The study shows that more cyclists and pedestrians can make cities safer. The ranking, compiled by the Wuppertal Institute and funded by Greenpeace, compared 13 metropolises in terms of public transport, road safety, air quality, mobility management, and the proportion of cyclists and pedestrians. The result: Amsterdam and Copenhagen, residents travel about a third of their trips by bicycle, and these cities have the fewest bicycle accidents
Experimental studies on effect of speaking mode on spoken term detection
The objective of this paper is to study the effect of speaking mode on spoken term detection (STD) system. The experiments are conducted with respect to query words recorded in isolated manner and words cut out from continuous speech. Durations of phonemes in query words greatly vary between these two modes. Hence pattern matching stage plays a crucial role which takes care of temporal variations. Matching is done using Subsequence dynamic time warping (DTW) on posterior features of query and reference utterances, obtained by training Multilayer perceptron (MLP). The difference in performance of the STD system for different phoneme groupings (45, 25, 15 and 6 classes) is also analyzed. Our STD system is tested on Telugu broadcast news. Major difference in STD system performance is observed for recorded and cut-out types of query words. It is observed that STD system performance is better with query words cut out from continuous speech compared to words recorded in isolated manner. This performance difference can be accounted for large temporal variations
Prosody Modification using Allpass Residual of Speech Signals
In this paper, we attempt to signify the role of phase spectrum of speech signals in acquiring an accurate estimate of excitation source for prosody modification. The phase spectrum is parametrically modeled as the response of an all pass (AP) filter, and the filter coefficients are estimated by considering the linear prediction (LP) residual as the output of the AP filter. The resultant residual signal, namely AP residual, exhibits unambiguous peaks corresponding to epochs, which are chosen as pitch markers for prosody modification. This strategy efficiently removes ambiguities associated with pitch marking, required for pitch synchronous overlap-add (PSOLA) method. The prosody modification using AP residual is advantageous than time domain PSOLA (TD-PSOLA) using speech signals, as it offers fewer distortions due to its flat magnitude spectrum. Windowing centered around unambiguous peaks in AP residual is used for segmentation, followed by pitch/duration modification of AP residual by mapping of pitch markers. The modified speech signal is obtained from modified AP residual using synthesis filters. The mean opinion scores are used for performance evaluation of the proposed method, and it is observed that the AP residual-based method delivers equivalent performance as that of LP residual based method using epochs, and better performance than the linear prediction PSOLA (LP-PSOLA)
Cowpea and groundnut haulms fodder trading and its lessons for multidimensional cowpea improvement for mixed crop livestock systems in West Africa
Cowpea is an important legume crop in Africa, valued highly for its grain and also haulms, which are a tradable commodity in fodder markets. Fodder market surveys in Northern Nigeria showed that groundnut haulms were priced higher than cowpea haulms, probably because of their superior nutritive value. The economic value of haulms has prompted cowpea breeders and livestock nutritionists to explore haulm fodder traits as additional selection and breeding criteria. Fifty cowpea genotypes cultivated across five locations in Nigeria in 2013 and 2014 were evaluated for food fodder traits. Significant (P < 0.05) genotypic dependent variations were observed in yields (kg/ha) of grains (537–1082) and haulms (1173–3368), though significant (P < 0.05) effects of location and year were observed. Grain and fodder yield had a tendency to be positively correlated (r = 0.26, P = 0.07). Haulms were analyzed for nitrogen (N), fiber fractions, in vitro digestibility, and metabolizable energy content. Highly significant variations were observed in all genotypic and livestock nutrition traits, although location and year had significant effects. Trade-offs between grain yield and haulm fodder quality traits were largely absent and haulm acid detergent lignin and grain yield were even inversely correlated (r = -0.28, P = 0.05), that is high grain yielders had decreased haulm lignin. However, haulm N and grain yield also tended to be negatively associated (r = -0.26, P = 0.07). Haulm fodder quality traits and haulm yield were mostly positively correlated (P < 0.05). Broad sense heritabilities for grain and fodder yield were 0.50 and 0.29, respectively, while heritability for haulm fodder quality traits ranged from 0.61 to 0.67, providing opportunities for concomitant increase in grain yield and haulm fodder quality traits. Selection of the 10 highest ranking genotypes for grain yield, haulm yield, haulm N, and haulm in vitro organic matter digestibility showed selection groups overlapping, suggesting that multi-trait selection is feasible. Economical evaluation showed that choice of primary traits is context specific, highlighting the need for identifying and targeting appropriate genotypes to fit different production systems. Considering haulm quantity and quality as traits of economic value can increase overall plant value in mixed crop-livestock systems
Klotho pathways, myelination disorders, neurodegenerative diseases, and epigenetic drugs
In this review we outline a rationale for identifying neuroprotectants aimed at inducing endogenous Klotho activity and expression, which is epigenetic action, by definition. Such an approach should promote remyelination and/or stimulate myelin repair by acting on mitochondrial function, thereby heralding a life-saving path forward for patients suffering from neuroinflammatory diseases. Disorders of myelin in the nervous system damage the transmission of signals, resulting in loss of vision, motion, sensation, and other functions depending on the affected nerves, currently with no effective treatment. Klotho genes and their single-pass transmembrane Klotho proteins are powerful governors of the threads of life and death, true to the origin of their name, Fates, in Greek mythology. Among its many important functions, Klotho is an obligatory co-receptor that binds, activates, and/or potentiates critical fibroblast growth factor activity. Since the discovery of Klotho a little over two decades ago, it has become ever more apparent that when Klotho pathways go awry, oxidative stress and mitochondrial dysfunction take over, and age-related chronic disorders are likely to follow. The physiological consequences can be wide ranging, potentially wreaking havoc on the brain, eye, kidney, muscle, and more. Central nervous system disorders, neurodegenerative in nature, and especially those affecting the myelin sheath, represent worthy targets for advancing therapies that act upon Klotho pathways. Current drugs for these diseases, even therapeutics that are disease modifying rather than treating only the symptoms, leave much room for improvement. It is thus no wonder that this topic has caught the attention of biomedical researchers around the world.https://www.liebertpub.com/doi/10.1089/biores.2020.0004Published versio
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