63 research outputs found
Velocity-selective direct frequency-comb spectroscopy of atomic vapors
We present an experimental and theoretical investigation of two-photon direct
frequency-comb spectroscopy performed through velocity-selective excitation. In
particular, we explore the effect of repetition rate on the
two-photon transitions
excited in a rubidium atomic vapor cell. The transitions occur via step-wise
excitation through the states by use of the direct
output of an optical frequency comb. Experiments were performed with two
different frequency combs, one with a repetition rate of MHz and
one with a repetition rate of MHz. The experimental spectra are
compared to each other and to a theoretical model.Comment: 10 pages, 7 figure
Double burden of malnutrition in Nepal: A trend analysis of protein-energy malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010–2019
Background The co-existence of undernutrition and overnutrition is a global public health threat. We aim to report the burden of both nutritional deficiency (Protein-Energy Malnutrition) and overweight (high Body Mass Index) in Nepal over a decade (2010–2019) and observe the changes through trend charts. Methods We did a secondary data analysis using the Institute for Health Metrics and Evaluation (IHME)’s Global Burden of Disease (GBD) database to download age-standardized data on Protein Energy Malnutrition (PEM) and high Body Mass Index (BMI). We presented the trend of death, Disability Adjusted Life Years (DALYs), Years of Life Lost (YLL), and Years Lost due to Disability (YLD) of PEM and high BMI in Nepal from 2010 to 2019 and also compared data for 2019 among South Asian countries. Results Between 2010 and 2019, in Nepal, the Disability Adjusted Life Years (DALYs) due to PEM were declining while high BMI was in increasing trend. Sex-specific trends revealed that females had higher DALYs for PEM than males. In contrast, males had higher DALYs for high BMI than females. In 2019, Nepal had the highest death rate for PEM (5.22 per 100,000 populations) than any other South Asian country. The burden of PEM in terms of DALY was higher in under-five children (912 per 100,000 populations) and elderly above 80 years old (808.9 per 100,000 populations), while the population aged 65–69 years had the highest burden of high BMI (5893 per 100,000 populations). In the last decade, the DALYs for risk factors contributing to PEM such as child growth failure (stunting and wasting), unsafe water, sanitation and handwashing, and sub-optimal breastfeeding have declined in Nepal. On the contrary, the DALYs for risk factors contributing to high BMI, such as a diet high in sugar-sweetened beverages, a diet high in trans fatty acid, and low physical activity, have increased. This could be a possible explanation for the increasing trend of high BMI and decreasing trend of PEM. Conclusion Rapidly growing prevalence of high BMI and the persistent existence of undernutrition indicate the double burden of malnutrition in Nepal. Public health initiatives should be planned to address this problem
Deep Learning Techniques for Geospatial Data Analysis
Consumer electronic devices such as mobile handsets, goods tagged with RFID
labels, location and position sensors are continuously generating a vast amount
of location enriched data called geospatial data. Conventionally such
geospatial data is used for military applications. In recent times, many useful
civilian applications have been designed and deployed around such geospatial
data. For example, a recommendation system to suggest restaurants or places of
attraction to a tourist visiting a particular locality. At the same time, civic
bodies are harnessing geospatial data generated through remote sensing devices
to provide better services to citizens such as traffic monitoring, pothole
identification, and weather reporting. Typically such applications are
leveraged upon non-hierarchical machine learning techniques such as Naive-Bayes
Classifiers, Support Vector Machines, and decision trees. Recent advances in
the field of deep-learning showed that Neural Network-based techniques
outperform conventional techniques and provide effective solutions for many
geospatial data analysis tasks such as object recognition, image
classification, and scene understanding. The chapter presents a survey on the
current state of the applications of deep learning techniques for analyzing
geospatial data.
The chapter is organized as below: (i) A brief overview of deep learning
algorithms. (ii)Geospatial Analysis: a Data Science Perspective (iii)
Deep-learning techniques for Remote Sensing data analytics tasks (iv)
Deep-learning techniques for GPS data analytics(iv) Deep-learning techniques
for RFID data analytics.Comment: This is a pre-print of the following chapter: Arvind W. Kiwelekar,
Geetanjali S. Mahamunkar, Laxman D. Netak, Valmik B Nikam, {\em Deep Learning
Techniques for Geospatial Data Analysis}, published in {\bf Machine Learning
Paradigms}, edited by George A. TsihrintzisLakhmi C. Jain, 2020, publisher
Springer, Cham reproduced with permission of publisher Springer, Cha
Gene- and variant-specific efficacy of serum/glucocorticoid-regulated kinase 1 inhibition in long QT syndrome types 1 and 2.
AIMS
Current long QT syndrome (LQTS) therapy, largely based on beta-blockade, does not prevent arrhythmias in all patients; therefore, novel therapies are warranted. Pharmacological inhibition of the serum/glucocorticoid-regulated kinase 1 (SGK1-Inh) has been shown to shorten action potential duration (APD) in LQTS type 3. We aimed to investigate whether SGK1-Inh could similarly shorten APD in LQTS types 1 and 2.
METHODS AND RESULTS
Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and hiPSC-cardiac cell sheets (CCS) were obtained from LQT1 and LQT2 patients; CMs were isolated from transgenic LQT1, LQT2, and wild-type (WT) rabbits. Serum/glucocorticoid-regulated kinase 1 inhibition effects (300 nM-10 µM) on field potential durations (FPD) were investigated in hiPSC-CMs with multielectrode arrays; optical mapping was performed in LQT2 CCS. Whole-cell and perforated patch clamp recordings were performed in isolated LQT1, LQT2, and WT rabbit CMs to investigate SGK1-Inh (3 µM) effects on APD. In all LQT2 models across different species (hiPSC-CMs, hiPSC-CCS, and rabbit CMs) and independent of the disease-causing variant (KCNH2-p.A561V/p.A614V/p.G628S/IVS9-28A/G), SGK1-Inh dose-dependently shortened FPD/APD at 0.3-10 µM (by 20-32%/25-30%/44-45%). Importantly, in LQT2 rabbit CMs, 3 µM SGK1-Inh normalized APD to its WT value. A significant FPD shortening was observed in KCNQ1-p.R594Q hiPSC-CMs at 1/3/10 µM (by 19/26/35%) and in KCNQ1-p.A341V hiPSC-CMs at 10 µM (by 29%). No SGK1-Inh-induced FPD/APD shortening effect was observed in LQT1 KCNQ1-p.A341V hiPSC-CMs or KCNQ1-p.Y315S rabbit CMs at 0.3-3 µM.
CONCLUSION
A robust SGK1-Inh-induced APD shortening was observed across different LQT2 models, species, and genetic variants but less consistently in LQT1 models. This suggests a genotype- and variant-specific beneficial effect of this novel therapeutic approach in LQTS
The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding
© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Cold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations.Peer reviewe
A memetic algorithm for a multi-objective obnoxious waste location-routing problem : a case study
How Important are Exports and Foreign Direct Investment for Economic Growth in the People's Republic of China?
The Australasian Resuscitation In Sepsis Evaluation : fluids or vasopressors in emergency department sepsis (ARISE FLUIDS), a multi-centre observational study describing current practice in Australia and New Zealand
Objectives: To describe haemodynamic resuscitation practices in ED patients with suspected sepsis and hypotension. Methods: This was a prospective, multicentre, observational study conducted in 70 hospitals in Australia and New Zealand between September 2018 and January 2019. Consecutive adults presenting to the ED during a 30-day period at each site, with suspected sepsis and hypotension (systolic blood pressure <100 mmHg) despite at least 1000 mL fluid resuscitation, were eligible. Data included baseline demographics, clinical and laboratory variables and intravenous fluid volume administered, vasopressor administration at baseline and 6- and 24-h post-enrolment, time to antimicrobial administration, intensive care admission, organ support and in-hospital mortality. Results: A total of 4477 patients were screened and 591 were included with a mean (standard deviation) age of 62 (19) years, Acute Physiology and Chronic Health Evaluation II score 15.2 (6.6) and a median (interquartile range) systolic blood pressure of 94 mmHg (87–100). Median time to first intravenous antimicrobials was 77 min (42–148). A vasopressor infusion was commenced within 24 h in 177 (30.2%) patients, with noradrenaline the most frequently used (n = 138, 78%). A median of 2000 mL (1500–3000) of intravenous fluids was administered prior to commencing vasopressors. The total volume of fluid administered from pre-enrolment to 24 h was 4200 mL (3000–5661), with a range from 1000 to 12 200 mL. Two hundred and eighteen patients (37.1%) were admitted to an intensive care unit. Overall in-hospital mortality was 6.2% (95% confidence interval 4.4–8.5%). Conclusion: Current resuscitation practice in patients with sepsis and hypotension varies widely and occupies the spectrum between a restricted volume/earlier vasopressor and liberal fluid/later vasopressor strategy
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