Miracle-dz/UniFAR-FTUs huggingface dataset:
Biosynthesis of Ag nanoparticles using Salicornia bigelovii and its antibacterial activity

Background and aim In recent years, the field of nanotechnology has become the most active area of research in modern material science. While many chemical- as well as physical methods are also used, green synthesis of nanoparticles is becoming the most evolved method of synthesis. In this study, we synthesized silver nanoparticles from the seed extract of Salicornia bigelovii. Methods This experimental study was conducted from December 2017 to January 2018 in Kerman University of Medical Sciences, Kerman, Iran. The effects of two concentrations (1m M and 4mM) on the synthesis of nanoparticles were studied. Characterizations were done using different methods including ultraviolet (UV) visible spectroscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Antibacterial activity of Ag nanoparticles against Staphylococcus aureus and Escherichia coli was studied using microdilution method. The data were analyzed using Probit test in SPSS (Version 20, USA). Results Formation of the AgNPs was confirmed by surface plasmon spectra using UV–Vis spectrophotometer and absorbance peaks at 434 nm. The FTIR spectra showed the possible role of the functional group like carbonyl groups in reduction of silver ions to silver nanoparticles. The XRD analysis showed that the synthesized silver nanoparticles are of face-centered cubic structure. The TEM showed the formation of silver nanoparticles ranging in diameter from 1 to 50 nm. The minimal inhibitory concentration and minimal bactericidal concentration of AgNPs were determined for both S. aureus and E. coli 6.25 and 12.5 μg/mL, respectively. Conclusion An environmentally friendly approach is more affordable than chemical methods. Physicochemical approaches can be harmful to the environment and to human health. Thus, the green synthesis methods are simple, less expensive, and can cut consumption of energy; they can be used for synthesis of fixed nanoparticles with preferred shape and size, without the use of toxic chemical agents.
Soft Memory Box: A Virtual Shared Memory Framework for Fast Deep Neural Network Training in Distributed High Performance Computing

Deep learning is one of the major promising machine learning methodologies. Deep learning is widely used in various application domains, e.g., image recognition, voice recognition, and natural language processing. In order to improve learning accuracy, deep neural networks have evolved by: 1) increasing the number of layers and 2) increasing the number of parameters in massive models. This implies that distributed deep learning platforms need to evolve to: 1) deal with huge/complex deep neural networks and 2) process with high-performance computing resources for massive training data. This paper proposes a new virtual shared memory framework, called Soft Memory Box (SMB), which enables sharing the memory of remote node among distributed processes in the nodes so as to improve communication performance via parameter sharing. According to data-intensive performance evaluation results, the communication time of deep learning using the proposed SMB is 2.1 times faster than that using the massage passing interface (MPI). In addition, the communication time of the SMB-based asynchronous parameter update becomes 2–7 times faster than that using the MPI depending on deep learning models and the number of deep learning workers.
DrowsyNet: Convolutional neural networks with runtime power-accuracy tunability using inference-stage dropout

Convolutional neural networks (CNNs) have many future artificial intelligence (AI) applications; CNN hardware is an enabling technology to make this AI future come true. Two main specifications of CNN hardware are power and accuracy, which are determined at the design time by the CNN model, CNN hardware architecture, and the transformation scheme that maps the model onto the hardware. This paper points out that the above three design parameters share one common limitation that they are not flexible enough to offer power-accuracy tunability at deployment time and runtime. In response to this demand, we propose DrowsyNet, which randomly drops out a fraction of convolutional neurons to achieve a power-accuracy tradeoff. DrowsyNet is an inference-stage technique, which is different from traditional training-stage dropout. We further present that the dropout rates would better be set non-uniformly among convolutional layers. Experimental results show that up to 50% savings in the number of convolutions are available by trading away less than 11% of top-5 accuracy.
Task Specific Networks for Identity and Face Variation

Pose and illumination variations are considered as two main challenges that face recognition system encounters. Most existing methods perform face normalization, aiming at untangling identity representation from these variations to improve recognition accuracy. Taking into account face variation representations, this paper proposes Task Specific Networks for the two representations with two novelties. First, we rotate and normalize face image to multi-pose view for one subtask, and learn face variation representations for another. Second, we learn face variation representations in an unsupervised way, which is more robust and more universal. We couple these two representations in the part of reconstructing the original face, where the two representations effect and restrict each other. Extensive experiments demonstrate the superiority of our method in both learning representations and rotating non-frontal face image.
Shape Robust Text Detection With Progressive Scale Expansion Network

Scene text detection has witnessed rapid progress especially with the recent development of convolutional neural networks. However, there still exists two challenges which prevent the algorithm into industry applications. On the one hand, most of the state-of-art algorithms require quadrangle bounding box which is in-accurate to locate the texts with arbitrary shape. On the other hand, two text instances which are close to each other may lead to a false detection which covers both instances. Traditionally, the segmentation-based approach can relieve the first problem but usually fail to solve the second challenge. To address these two challenges, in this paper, we propose a novel Progressive Scale Expansion Network (PSENet), which can precisely detect text instances with arbitrary shapes. More specifically, PSENet generates the different scale of kernels for each text instance, and gradually expands the minimal scale kernel to the text instance with the complete shape. Due to the fact that there are large geometrical margins among the minimal scale kernels, our method is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances. Extensive experiments on CTW1500, Total-Text, ICDAR 2015 and ICDAR 2017 MLT validate the effectiveness of PSENet. Notably, on CTW1500, a dataset full of long curve texts, PSENet achieves a F-measure of 74.3% at 27 FPS, and our best F-measure (82.2%) outperforms state-of-art algorithms by 6.6%. The code will be released in the future.
Experimental demonstration of the impact of hard and soft selection regimes on polymorphism maintenance in spatially heterogeneous environments †

Predicting and managing contemporary adaption requires a proper understanding of the determinants of genetic variation. Spatial heterogeneity of the environment may stably maintain polymorphism when habitat contribution to the next generation can be considered independent of the degree of adaptation of local populations within habitats (i.e., under soft selection). In contrast, when habitats contribute proportionally to the mean fitness of the populations they host (hard selection), polymorphism is not expected to be maintained by selection. Although mathematically established decades ago, this prediction had never been demonstrated experimentally. Here, we provide an experimental test in which polymorphic populations of Escherichia coli growing in heterogeneous habitats were exposed to hard and soft selection regimes. As predicted by theory, polymorphism was preserved longer under soft selection. Complementary tests established that soft selection slowed fixation processes and could even protect polymorphism in the long term by providing a systematic advantage to rare genotypes.
Utility Aware Snoozy Caches for Energy Efficient Chip Multi-Processors

Heavy leakage power consumption of on-chip last level caches (LLCs) has become the primary obstacle for architecting chip multi-processors (CMPs) in recent times. As leakage power has a direct relationship with the supply voltage, hence, periodic access profile based dynamic voltage scaling (DVS) in the LLC banks can be a promising option towards reducing this heavy cache leakage. A plethora of prior attempts have reduced this by anticipating working set size (WSS) of the applications and eventually putting some portions of the cache banks in low power mode. This proposed work aims to reduce leakage by putting a whole LLC bank into a low power (snoozy) mode through exploiting DVS at cache banks having minimal usages. Additionally, the resulting performance impacts of the low power snoozy mode are alleviated further by putting some snoozy banks in active mode on-demand. Experimental evaluations using full system simulation on a multi-banked 2MB 8-way set associative L2 cache show 10% more leakage savings on an average over a prior drowsy technique.
Vegetable Purée: A Pilot Study to Increase Vegetable Consumption among School Lunch Participants in US Elementary Schools.

Purpose/Objectives Recent US Department of Agriculture regulations increased the amount and variety of vegetables required for school lunches. Vegetables are the most wasted components of lunch while entrees are selected and consumed by the majority of children. This study examined how adding vegetable puree to an elementary school lunch entree affected the weight and calories of the entree consumed and the amount of vegetables consumed. Differences between genders and among grade levels were also assessed. Methods A convenience sample (839 students) from three elementary schools in a large Central Illinois school district participated in this study. A vegetable puree of carrots, beans, and tomato paste was added to a standard entree to increase vegetable content from the Control of 0.25 cup to 0.4 cup (Recipe 1) and 0.45 cup (Recipe 2). Children were randomly served one of three entrees, and plate waste was measured by weighing the leftover portion of the entrees. Analysis of variance and t tests were used to compare the weight of the entree consumed and the vegetable and calorie consumption for the entrees and identify differences between genders. Univariate linear models tested interaction between entree and grade. Results There was no difference in consumption of the Control and Recipe 1 (p = .279). Recipe 2 was significantly less consumed than Recipe 1 (p < 0.001) and the Control (p < 0.05) suggesting that there may be a limit of how much vegetable puree one can add to an entree for a student to consume a comparable amount. Significantly more vegetables (p < 0.001) and fewer calories (p < 0.001) were consumed from the entrees with added vegetables than the Control entree. There were significant interactions between grade level and all factors, but no differences between genders were identified. Application to Child Nutrition Professionals The study suggests that adding pureed vegetables to lunch entrees may be an effective strategy to increase vegetable consumption and reduce energy intake of elementary school children. School nutrition programs can benefit by helping meet vegetable and nutrient requirements and reducing plate waste. Keywords: vegetable consumption; elementary school meals; National School Lunch Program.
Role of interleukin-21 and interleukin-21 receptor polymorphisms in the treatment of HBeAg-positive chronic hepatitis B patients with peginterferon

Abstract The aim of this study was to evaluate the relationship between interleukin-21 (IL-21) and interleukin-21 receptor (IL-21R) polymorphisms and the response to peginterferon alfa (PEG-IFN &agr;) therapy in HBeAg-positive chronic hepatitis B (CHB) patients. A total of 143 HBeAg-positive CHB patients treated for 48 weeks with PEG-IFN &agr; and followed up for 24 weeks post-treatment were retrospectively evaluated. Genotypes analysis was performed for IL-21 polymorphisms rs907715, rs2221903, and IL-21R polymorphisms rs3093301 and rs2285452. Serum IL-21 levels were measured by enzyme-linked immunosorbent assay. The end of virological response (EVR) rate was 46.9% (67/143) at the end of treatment, the sustained virological response (SVR) rate was 43.4% (62/143) and the complete response (CR) rate was 32.1% (46/143) at 24 weeks post-treatment. Patients who carried IL-21 rs 2221903 genotype AA had a rather higher rate of EVR (response rate: 52.4%, odds ratio [OR] 0.42, 95% confidence interval [CI]: 0.19–0.91, P = .021), SVR (response rate: 47.6%, OR 0.43, 95% CI: 0.19–0.95, P = .028), and CR (response rate: 38.1%, OR 0.31, 95% CI: 0.12–0.79, P = .014) when compared to those had AG genotype. Meanwhile, IL-21rs 2221903 genotype AA was also independently associated with markedly reduced HBsAg levels (>1og10 IU/mL) after 24 weeks treatment and low HBsAg levels (<100 IU/mL) at the end of treatment. IL-21 rs907715 AG/GG genotype was independently associated with SVR (OR: 2.92, 95% CI: 0.98–8.6, P = .039; OR: 3.23, 95% CI: 1.0–10.4, P = .039). Patients with IL-21 rs907715 AG/GG genotype had higher serum IL-21 levels than those with rs907715 AA genotype (P = .021). IL-21 rs2221903 and rs907715 polymorphisms were significantly associated with the treatment response to PEG-IFN &agr; among Chinese HBeAg-positive CHB patients.
Data collection methodology for dynamic temperature model testing and corroboration

This article describes a data collection approach for determining the significance of individual heat fluxes within streams with an emphasis on testing (i.e. identification of possible missing heat fluxes), development, calibration and corroboration of a dynamic temperature model. The basis for developing this approach was a preliminary temperature modelling effort on the Virgin River in southwestern Utah during a low‐flow period that suggested important components of the energy balance might be missing in the original standard surface‐flux temperature model. Possible missing heat fluxes were identified as bed conduction, hyporheic exchange, dead zone warming and exchange and poor representation of the amount of solar radiation entering the water column. To identify and estimate the relative importance of the missing components, a comprehensive data collection effort was developed and implemented. In particular, a method for measuring shortwave radiation behaviour in the water column and an in situ method for separating out bed conduction and hyporheic influences were established. The resulting data and subsequent modelling effort indicate that hyporheic and dead zone heat fluxes are important, whereas solar radiation reflection at the water surface was found to be insignificant. Although bed conduction can be significant in certain rivers, it was found to have little effect on the overall heat budget for this section of the Virgin River. Copyright © 2009 John Wiley & Sons, Ltd.
Impact of sarcopenia on the risk of advanced colorectal neoplasia

Sarcopenia is a pathological condition characterized by the progressive loss of muscle mass and increased amount of visceral fat. Recent evidence has revealed that sarcopenia is associated with certain diseases. However, the impact of sarcopenia on colorectal neoplasia has not been documented clearly. We studied the association between sarcopenia and advanced colorectal neoplasia in a large screening population.
The Effect of Silver Diamine Fluoride in Preventing Caries in the Primary Dentition: A Systematic Review and Meta-Analysis

Objectives: To investigate whether silver diamine fluoride (SDF) is effective in preventing new caries lesions in primary teeth when compared to placebo or active treatments. Methods: Systematic review (CRD42016036963) of controlled clinical trials. Searches were performed in 9 electronic databases, 5 registers of ongoing trials, and reference lists of identified review articles. Two researchers carried out data extraction and quality appraisal independently. The primary outcome was the difference in caries increment (decayed, missing, and filled surfaces or teeth – dmfs or dmft) between SDF and control groups. These differences were pooled as weighted mean differences (WMD) and prevented fractions (PF). Results: Searches yielded 2,366 unique records; 6 reports of 4 trials that randomized 1,118 and analyzed 915 participants were included. Two trials compared SDF to no treatment, 1 compared SDF to placebo and sodium fluoride varnish (FV), and 1 compared SDF to high-viscosity glass ionomer cement (GIC). All studies had at least 1 domain with unclear or high risk of bias. After 24 months of follow-up, in comparison to placebo, no treatment, and FV, SDF applications significantly reduced the development of new dentin caries lesions (placebo or no treatment: WMD = –1.15, PF = 77.5%; FV: WMD = –0.43, PF = 54.0%). GIC was more effective than SDF after 12 months of follow-up but the difference between them was not statistically significant (WMD, dmft: 0.34, PF: –6.09%). Conclusion: When applied to caries lesions in primary teeth, SDF compared to no treatment, placebo or FV appears to effectively prevent dental caries in the entire dentition. However, trials specifically designed to assess this outcome are needed.
Trace gas emissions from savanna fires in northern Australia

[1] We present analyses of near-infrared ground-based Fourier transform infrared solar absorption spectra recorded from a site in Darwin, Northern Territory, Australia (12.4°S, 130.9°E) from August 2005 to June 2008. Total column amounts of carbon monoxide derived from these spectra show a very clear annual cycle, with evidence of transported pollution from Indonesian fires in 2006. Aerosol optical depth measurements from the same site show a similar annual cycle but without exceptional values in 2006, suggesting significant loss of aerosol loading in the transported and aged smoke. In addition, we report the first ever measurements by remote sensing solar Fourier transform infrared of emission ratios with respect to carbon monoxide for formaldehyde (0.022 ± 0.007), acetylene (0.0024 ± 0.0003), ethane (0.0020 ± 0.0003), and hydrogen cyanide (0.0018 ± 0.0003) from Australian savanna fires. These are derived from mid-infrared spectra recorded through smoke plumes over Darwin on 20 separate days. The only previous measurements of emission ratios for formaldehyde and hydrogen cyanide from Australian savanna fires involved cryogenic trapping and storage of samples that were gathered in very fresh smoke. The results reported here are nearly an order of magnitude higher (but in agreement with laboratory studies), suggesting losses in the collection, storage, or transfer of the gases in the earlier measurements and/or chemical production of these reactive gases within the smoke plumes. Emission ratios for acetylene and ethane from this work are in broad agreement with other literature values.
Audio-visual interaction in emotion perception for communication: doctoral symposium, extended abstract

Information from multiple modalities contributes to recognizing emotions. While it is known interactions occur between modalities, it is unclear what characterizes these. These interactions, and changes in these interactions due to sensory impairments, are the main subject of this PhD project. This extended abstract for the Doctoral Symposium of ETRA 2018 describes the project; its background, what I hope to achieve, and some preliminary results.
Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis

Oral squamous cell carcinoma (OSCC) is a malignant disease. Methylation plays a key role in the etiology and pathogenesis of OSCC. The goal of this study was to identify aberrantly methylated differentially expressed genes (DEGs) in OSCCs, and to explore the underlying mechanisms of tumorigenesis by using integrated bioinformatic analysis. Gene expression profiles (GSE30784 and GSE38532) were analyzed using the R software to obtain aberrantly methylated DEGs. Functional enrichment analysis of screened genes was performed using the DAVID software. Protein–protein interaction (PPI) networks were constructed using the STRING database. The cBioPortal software was used to exhibit the alterations of genes. Lastly, we validated the results with the Cancer Genome Atlas (TCGA) data. Twenty-eight upregulated hypomethylated genes and 24 downregulated hypermethylated genes were identified. These genes were enriched in the biological process of regulation in immune response, and were mainly involved in the PI3K-AKT and EMT pathways. Additionally, three upregulated hypomethylated oncogenes and four downregulated hypermethylated tumor suppressor genes (TSGs) were identified. In conclusion, our study indicated possible aberrantly methylated DEGs and pathways in OSCCs, which could improve the understanding of the underlying molecular mechanisms. Aberrantly methylated oncogenes and TSGs may also serve as biomarkers and therapeutic targets for the precise diagnosis and treatment of OSCCs in the future.
Precoding design in two-way cooperative system with energy harvesting relay

We consider a two-way relay network (TWRN) where one relay simultaneously harvest radio frequency (RF) energy emitted from both source nodes and forward the message for both sources. We proposed a recursive algorithm to design the precoding at the relay, including a phase rotating factor to combine the receive signal coherently, the precodin matrix and power splitting factors to maximize the achievable sum-rate. Simulation results show that the proposed scheme is able to improve the throughput of the TWRN.