400 research outputs found
Spectral-spatial classification of hyperspectral images: three tricks and a new supervised learning setting
Spectral-spatial classification of hyperspectral images has been the subject
of many studies in recent years. In the presence of only very few labeled
pixels, this task becomes challenging. In this paper we address the following
two research questions: 1) Can a simple neural network with just a single
hidden layer achieve state of the art performance in the presence of few
labeled pixels? 2) How is the performance of hyperspectral image classification
methods affected when using disjoint train and test sets? We give a positive
answer to the first question by using three tricks within a very basic shallow
Convolutional Neural Network (CNN) architecture: a tailored loss function, and
smooth- and label-based data augmentation. The tailored loss function enforces
that neighborhood wavelengths have similar contributions to the features
generated during training. A new label-based technique here proposed favors
selection of pixels in smaller classes, which is beneficial in the presence of
very few labeled pixels and skewed class distributions. To address the second
question, we introduce a new sampling procedure to generate disjoint train and
test set. Then the train set is used to obtain the CNN model, which is then
applied to pixels in the test set to estimate their labels. We assess the
efficacy of the simple neural network method on five publicly available
hyperspectral images. On these images our method significantly outperforms
considered baselines. Notably, with just 1% of labeled pixels per class, on
these datasets our method achieves an accuracy that goes from 86.42%
(challenging dataset) to 99.52% (easy dataset). Furthermore we show that the
simple neural network method improves over other baselines in the new
challenging supervised setting. Our analysis substantiates the highly
beneficial effect of using the entire image (so train and test data) for
constructing a model.Comment: Remote Sensing 201
Wearable devices for remote monitoring of hospitalized patients with COVID-19 in Vietnam
Patients with severe COVID-19 disease require monitoring with pulse oximetry as a minimal requirement. In many low- and middle- income countries, this has been challenging due to lack of staff and equipment. Wearable pulse oximeters potentially offer an attractive means to address this need, due to their low cost, battery operability and capacity for remote monitoring. Between July and October 2021, Ho Chi Minh City experienced its first major wave of SARS-CoV-2 infection, leading to an unprecedented demand for monitoring in hospitalized patients. We assess the feasibility of a continuous remote monitoring system for patients with COVID-19 under these circumstances as we implemented 2 different systems using wearable pulse oximeter devices in a stepwise manner across 4 departments
Assessment of seasonal winter temperature forecast errors in the regcm model over northern Vietnam
This study verified the seasonal six-month forecasts for winter temperatures for northern Vietnam in 1998–2018 using a regional climate model (RegCM4) with the boundary conditions of the climate forecast system Version 2 (CFSv2) from the National Centers for Environmental Prediction (NCEP). First, different physical schemes (land-surface process, cumulus, and radiation parameterizations) in RegCM4 were applied to generate 12 single forecasts. Second, the simple ensemble forecasts were generated through the combinations of those different physical formulations. Three subclimate regions (R1, R2, R3) of northern Vietnam were separately tested with surface observations and a reanalysis dataset (Japanese 55-year reanalysis (JRA55)). The highest sensitivity to the mean monthly temperature forecasts was shown by the land-surface parameterizations (the biosphere−atmosphere transfer scheme (BATS) and community land model version 4.5 (CLM)). The BATS forecast groups tended to provide forecasts with lower temperatures than the actual observations, while the CLM forecast groups tended to overestimate the temperatures. The forecast errors from single forecasts could be clearly reduced with ensemble mean forecasts, but ensemble spreads were less than those root-mean-square errors (RMSEs). This indicated that the ensemble forecast was underdispersed and that the direct forecast from RegCM4 needed more postprocessing
Solar models and solar neutrino oscillations
We provide a summary of the current knowledge, theoretical and experimental,
of solar neutrino fluxes and of the masses and mixing angles that characterize
solar neutrino oscillations. We also summarize the principal reasons for doing
new solar neutrino experiments and what we think may be learned from the future
measurements.Comment: Submitted to the Neutrino Focus Issue of New Journal of Physics at
http://www.njp.or
Clinical implications of reduced susceptibility to fluoroquinolones in paediatric Shigella sonnei and Shigella flexneri infections.
OBJECTIVES: We aimed to quantify the impact of fluoroquinolone resistance on the clinical outcome of paediatric shigellosis patients treated with fluoroquinolones in southern Vietnam. Such information is important to inform therapeutic management for infections caused by this increasingly drug-resistant pathogen, responsible for high morbidity and mortality in young children globally. METHODS: Clinical information and bacterial isolates were derived from a randomized controlled trial comparing gatifloxacin with ciprofloxacin for the treatment of paediatric shigellosis. Time-kill experiments were performed to evaluate the impact of MIC on the in vitro growth of Shigella and Cox regression modelling was used to compare clinical outcome between treatments and Shigella species. RESULTS: Shigella flexneri patients treated with gatifloxacin had significantly worse outcomes than those treated with ciprofloxacin. However, the MICs of fluoroquinolones were not significantly associated with poorer outcome. The presence of S83L and A87T mutations in the gyrA gene significantly increased MICs of fluoroquinolones. Finally, elevated MICs and the presence of the qnrS gene allowed Shigella to replicate efficiently in vitro in high concentrations of ciprofloxacin. CONCLUSIONS: We found that below the CLSI breakpoint, there was no association between MIC and clinical outcome in paediatric shigellosis infections. However, S. flexneri patients had worse clinical outcomes when treated with gatifloxacin in this study regardless of MIC. Additionally, Shigella harbouring the qnrS gene are able to replicate efficiently in high concentrations of ciprofloxacin and we hypothesize that such strains possess a competitive advantage against fluoroquinolone-susceptible strains due to enhanced shedding and transmission
Clinically and microbiologically derived azithromycin susceptibility breakpoints for Salmonella enterica serovars Typhi and Paratyphi A.
Azithromycin is an effective treatment for uncomplicated infections with Salmonella enterica serovar Typhi and serovar Paratyphi A (enteric fever), but there are no clinically validated MIC and disk zone size interpretative guidelines. We studied individual patient data from three randomized controlled trials (RCTs) of antimicrobial treatment in enteric fever in Vietnam, with azithromycin used in one treatment arm, to determine the relationship between azithromycin treatment response and the azithromycin MIC of the infecting isolate. We additionally compared the azithromycin MIC and the disk susceptibility zone sizes of 1,640 S. Typhi and S. Paratyphi A clinical isolates collected from seven Asian countries. In the RCTs, 214 patients who were treated with azithromycin at a dose of 10 to 20 mg/ml for 5 to 7 days were analyzed. Treatment was successful in 195 of 214 (91%) patients, with no significant difference in response (cure rate, fever clearance time) with MICs ranging from 4 to 16 μg/ml. The proportion of Asian enteric fever isolates with an MIC of ≤ 16 μg/ml was 1,452/1,460 (99.5%; 95% confidence interval [CI], 98.9 to 99.7) for S. Typhi and 207/240 (86.3%; 95% CI, 81.2 to 90.3) (P 16 μg/ml and to determine MIC and disk breakpoints for S. Paratyphi A
Differential prevalence and geographic distribution of hepatitis C virus genotypes in acute and chronic hepatitis C patients in Vietnam.
BACKGROUND: The highest burden of disease from hepatitis C virus (HCV) is found in Southeast Asia, but our understanding of the epidemiology of infection in many heavily burdened countries is still limited. In particular, there is relatively little data on acute HCV infection, the outcome of which can be influenced by both viral and host genetics which differ within the region. We studied HCV genotype and IL28B gene polymorphism in a cohort of acute HCV-infected patients in Southern Vietnam alongside two other cohorts of chronic HCV-infected patients to better understand the epidemiology of HCV infection locally and inform the development of programs for therapy with the increasing availability of directly acting antiviral therapy (DAAs). METHODS: We analysed plasma samples from patients with acute and chronic HCV infection, including chronic HCV mono-infection and chronic Human Immunodeficiency Virus (HIV)-HCV coinfection, who enrolled in four epidemiological or clinical research studies. HCV infection was confirmed with RNA testing. The 5' UTR, core and NSB5 regions of HCV RNA positive samples were sequenced, and the genotype and subtype of the viral strains were determined. Host DNA from all HCV positive patients and age- and sex-matched non-HCV-infected control individuals were analysed for IL28B single nucleotide polymorphism (SNP) (rs12979860 and rs8099917). Geolocation of the patients were mapped using QGIS. RESULTS: 355 HCV antibody positive patients were analysed; 54.6% (194/355) and 46.4% (161/355) were acute and chronic infections, respectively. 50.4% (81/161) and 49.6.4% (80/161) of chronic infections had HCV mono-infection and HIV-HCV coinfection, respectively. 88.7% (315/355) and 10.1% (36/355) of the patients were from southern and central regions of Vietnam, respectively. 92.4% (328/355) of patients were HCV RNA positive, including 86.1% (167/194) acute and 100% (161/161) chronic infections. Genotype could be determined in 98.4% (322/328) patients. Genotypes 1 (56.5%; 182/322) and 6 (33.9%; 109/322) predominated. Genotype 1 including genotype 1a was significantly higher in HIV-HCV coinfected patients compared to acute HCV patients [43.8% (35/80) versus 20.5% (33/167)], (p = <0.001), while genotype 6 was significantly higher in chronic HCV mono-infected patients [(44.4% (36/81) versus 20.0% (16/80)] (p = < 0.004) compared to HIV-HCV coinfected patients. The prevalence of IL28B SNP (rs12979860) homozygous CC was 86.46% (83/96) in control individuals and was significantly higher in acutely-infected compared to chronically-infected patients [93.2 (82/88) versus 76.1% (35/46)] (p = < 0.005). CONCLUSION: HCV genotype 6 is highly prevalent in Vietnam and the high prevalence in treatment naïve chronic HCV patients may results from poor spontaneous clearance of acute HCV infection with genotype 6
Evolution of average multiplicities of quark and gluon jets
The energy evolution of average multiplicities of quark and gluon jets is
studied in perturbative QCD. Higher order (3NLO) terms in the perturbative
expansion of equations for the generating functions are found. First and second
derivatives of average multiplicities are calculated. The mean multiplicity of
gluon jets is larger than that of quark jets and evolves more rapidly with
energy. It is shown which quantities are most sensitive to higher order
perturbative and nonperturbative corrections. We define the energy regions
where the corrections to different quantities are important. The latest
experimental data are discussed.Comment: 23 pages including 3 figures. Version 2 contains small correction to
equation (41
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