One-pot preparation of alumina-modified polysulfone-graphene oxide nanocomposite membrane for separation of emulsion-oil from wastewater

In recent years, polysulfone-based nanocomposite membranes have been widely used for contaminated water treatment because they comprise properties such as high thermal stability and chemical resistance. In this study, a polysulfone (PSf) nanocomposite membrane was fabricated using the wet-phase inversion method with the fusion of graphene oxide (GO) and alumina (Al2O3) nanoparticles. We also showed that GO-Al2O3 nanoparticles were synthesised successfully by using a one-pot hydrothermal method. The nanocomposite membranes were characterised by Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), nitrogen adsorption-desorption isotherms, energy-dispersive X-ray spectroscopy (EDX), thermogravimetric analysis (TGA), and water contact angle. The loading of GO and Al2O3 was investigated to improve the hydrophilic and oil rejection of the matrix membrane. It was shown that by using 1.5 wt.% GO-Al2O3 loaded in polysulfone, ~74% volume of oil was separated from the oil/water emulsion at 0.87 bar and 30 min. This figure was higher than that of the process using the unmodified membrane (PSf/GO) at the same conditions, in which only ~60% volume of oil was separated. The pH, oil/water emulsion concentration, separation time, and irreversible fouling coefficient (FRw) were also investigated. The obtained results suggested that the GO-Al2O3 nanoparticles loaded in the polysulfone membrane might have potential use in oily wastewater treatment applications

Multichannel Photon Counting Lidar Measurements Using USB-based Digital Storage Oscilloscope

We present a simple method of making multichannel photon counting measurements of weak lidar signal from large ranges, using commonly available USB-based digital storage oscilloscopes. The single photon pulses from compact photomultiplier tubes are amplified and stretched so that the pulses are large and broad enough to be sampled efficiently by the USB oscilloscopes. A software interface written in Labview is then used to count the number of photon pulses in each of the prescribed time bins to form the histogram of LIDAR signal. This method presents a flexible alternative to the modular multichannel scalers and facilitate the development of sensitive lidar systems

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

A Framework for paper submission recommendation system

Nowadays, recommendation systems play an indispensable role in many fields, including e-commerce, finance, economy, and gaming. There is emerging research on publication venue recommendation systems to support researchers when submitting their scientific work. Several publishers such as IEEE, Springer, and Elsevier have implemented their submission recommendation systems only to help researchers choose appropriate conferences or journals for submission. In this work, we present a demo framework to construct an effective recommendation system for paper submission. With the input data (the title, the abstract, and the list of possible keywords) of a given manuscript, the system recommends the list of top relevant journals or conferences to authors. By using state-of-the-art techniques in natural language understanding, we combine the features extracted with other useful handcrafted features. We utilize deep learning models to build an efficient recommendation engine for the proposed system. Finally, we present the User Interface (UI) and the architecture of our paper submission recommendation system for later usage by researchers

Monitoring for Plasmodium falciparum drug resistance to artemisinin and artesunate in Binh Phuoc Province, Vietnam: 1998-2009

<p>Abstract</p> <p>Background</p> <p>Artemisinin derivatives have been used for malaria treatment in Vietnam since 1989. Reported malaria cases have decreased from 1,672,000 with 4,650 deaths in 1991, to 91,635 with 43 deaths in 2006. Current national guidelines recommend artemisinin-based combination therapy (ACT), although artesunate is still available as monotherapy through the private sector. Recent reports suggest that effectiveness of ACT and artesunate monotherapy has declined in western Cambodia. This study examined <it>Plasmodium falciparum </it>resistance patterns over 10 years in southwest Vietnam in infected patients treated with artemisinin compounds.</p> <p>Methods</p> <p>The study was conducted in two communes in Phuoc Long district, Binh Phuoc province, 100 km west of the Cambodian border. This was chosen as a likely site for emerging artemisinin resistance because of the high prevalence of <it>P. falciparum </it>malaria, and the length of time that artemisinin had been in use. In <it>vivo </it>and <it>in vitro </it>monitoring of <it>P. falciparum </it>susceptibility to anti-malarial drugs was conducted in 1998, 2001, 2004/5, and 2008/9. Patients with confirmed <it>P. falciparum </it>malaria received therapy with 5 or 7 days of artemisinin (1998 and 2001 respectively) or 7 days of artesunate</p> <p>Results</p> <p>In the four surveys, 270 patients were recruited and treated. The mean parasite clearance times differed between 1998, 2001 and 2004/5 (1.8, 2.3 and 2.1 days, P < 0.01) but not between 1998 and 2008/2009. The mean parasite clearance times were correlated with parasite density at day 0 (r = 0.4; P < 0.001). Treatment failure rates after PCR adjustment were 13.8%, 2.9%, 1.2%, and 0% respectively. Susceptibility of <it>P. falciparum </it>to artemisinin in <it>in vitro </it>tests was stable during the period, except for a rise in EC90 and EC99 in 2001.</p> <p>Conclusions</p> <p>This study showed stable levels of <it>P. falciparum </it>sensitivity to artemisinin compounds in the two sites over a ten-year period. The introduction of ACT in this area in 2003 may have protected against the development of artemisinin resistance. Adherence to the latest WHO and Vietnamese guidelines, which recommend ACT as first-line therapy in all malarious areas, and continued monitoring along the Vietnam-Cambodia border will be essential to prevent the spread of artemisinin resistance in Vietnam.</p

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p &lt; 0.001) and anxiety (OR = 2.86; p &lt; 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p &lt; 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p &lt; 0.001), or “unchanged/more” drinking (p &lt; 0.001 for only anxiety), or “unchanged/healthier” eating (p &lt; 0.001), and high PB score (p &lt; 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors

Induced pseudoscalar coupling of the proton weak interaction

The induced pseudoscalar coupling $g_p$ is the least well known of the weak coupling constants of the proton's charged--current interaction. Its size is dictated by chiral symmetry arguments, and its measurement represents an important test of quantum chromodynamics at low energies. During the past decade a large body of new data relevant to the coupling $g_p$ has been accumulated. This data includes measurements of radiative and non radiative muon capture on targets ranging from hydrogen and few--nucleon systems to complex nuclei. Herein the authors review the theoretical underpinnings of $g_p$, the experimental studies of $g_p$, and the procedures and uncertainties in extracting the coupling from data. Current puzzles are highlighted and future opportunities are discussed.Comment: 58 pages, Latex, Revtex4, prepared for Reviews of Modern Physic

Time to Osteoporosis and Major Fracture in Older Men

For older men who undergo bone mineral density (BMD) testing, the optimal osteoporosis screening schedule is unknown. Time-to-disease estimates are necessary to inform screening intervals

Time to Osteoporosis and Major Fracture in Older Men

For older men who undergo bone mineral density (BMD) testing, the optimal osteoporosis screening schedule is unknown. Time-to-disease estimates are necessary to inform screening intervals

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types