Differences in the bacterial community structure associated with 7 skin sites in 71 healthy people over five days showed significant correlations with age, gender, physical skin parameters, and ...whether participants lived in urban or rural locations in the same city. While body site explained the majority of the variance in bacterial community structure, the composition of the skin-associated bacterial communities were predominantly influenced by whether the participants were living in an urban or rural environment, with a significantly greater relative abundance of Trabulsiella in urban populations. Adults maintained greater overall microbial diversity than adolescents or the elderly, while the intragroup variation among the elderly and rural populations was significantly greater. Skin-associated bacterial community structure and composition could predict whether a sample came from an urban or a rural resident ~5x greater than random.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Feature extraction for fault signals is critical and difficult in all kinds of fault detection schemes. A novel simple and effective method of faulty feeder detection in resonant grounding ...distribution systems based on the continuous wavelet transform (CWT) and convolutional neural network (CNN) is presented in this paper. The time-frequency gray scale images are acquired by applying the CWT to the collected transient zero-sequence current signals of the faulty feeder and sound feeders. The features of the gray scale image will be extracted adaptively by the CNN, which is trained by a large number of gray scale images under various kinds of fault conditions and factors. The features extraction and the faulty feeder detection can be implemented by the trained CNN simultaneously. As a comparison, two faulty feeder detection methods based on artificial feature extraction and traditional machine learning are introduced. A practical resonant grounding distribution system is simulated in power systems computer aided design/electromagnetic transients including DC, the effectiveness and performance of the proposed faulty feeder detection method is compared and verified under different fault circumstances.
Learning powerful discriminative features is the key for remote sensing scene classification. Most existing approaches based on convolutional neural network (CNN) have achieved great results. ...However, they mainly focus on global-based visual features while ignoring object-based location features, which is important for large-scale scene classification. There are a large number of scene-related ground objects in remote sensing images, as well as Graph convolutional network (GCN) has the potential to capture the dependencies among objects. This article introduces a novel two-stream architecture that combines global-based visual features and object-based location features, so as to improve the feature representation capability. First, we extract appearance visual features from whole scene image based on CNN. Second, we detect ground objects and construct a graph to learn the spatial location features based on GCN. As a result, the network can jointly capture appearance visual information and spatial location information. To the best of authors' knowledge, we are the first to investigate the dependencies among objects in remote sensing scene classification task. Extensive experiments on two datasets show that our framework improves the discriminative ability of features and achieves competitive accuracy against other state-of-the-art approaches.
The limited capacity to recognise faces under occlusions is a long‐standing problem that presents a unique challenge for face recognition systems and even humans. The problem regarding occlusion is ...less covered by research when compared to other challenges such as pose variation, different expressions, etc. Nevertheless, occluded face recognition is imperative to exploit the full potential of face recognition for real‐world applications. In this article, the scope to occluded face recognition is restricted and a systematic categorisation that new as well as classic methods fit into is presented. First, the authors explore the kind of the occlusion problem and the type of inherent difficulties that can arise. As a part of this review, face detection under occlusion, a preliminary step in face recognition. Second the authors analyse how the existing face recognition methods cope with the occlusion problem and classify them into three categories, which are given as: 1) occlusion robust feature extraction approaches, 2) occlusion aware face recognition approaches, and 3) occlusion recovery based face recognition approaches. Furthermore, the motivations, innovations, pros and cons, and the performance of representative approaches for comparison are analyzed. Finally, future challenges and method trends of occluded face recognition are thoroughly discussed.
Recently, many researchers have been dedicated to using convolutional neural networks (CNNs) to extract global-context features (GCFs) for remote-sensing scene classification. Commonly, accurate ...classification of scenes requires knowledge about both the global context and local objects. However, unlike the natural images in which the objects cover most of the image, objects in remote-sensing images are generally small and decentralized. Thus, it is hard for vanilla CNNs to focus on both global context and small local objects. To address this issue, this paper proposes a novel end-to-end CNN by integrating the GCFs and local-object-level features (LOFs). The proposed network includes two branches, the local object branch (LOB) and global semantic branch (GSB), which are used to generate the LOFs and GCFs, respectively. Then, the concatenation of features extracted from the two branches allows our method to be more discriminative in scene classification. Three challenging benchmark remote-sensing datasets were extensively experimented on; the proposed approach outperformed the existing scene classification methods and achieved state-of-the-art results for all three datasets.
The factors driving the composition of gut microbiota are still only partly understood but appear to include environmental, cultural, and genetic factors. In order to obtain more insight into the ...relative importance of these factors, we analyzed the microbiome composition in subjects of Tibetan or Han descent living at different altitudes. DNA was isolated from stool samples. Using polymerase chain reaction methodology, the 16S rRNA V1-V3 regions were amplified and the sequence information was analyzed by principal coordinates analysis and Lefse analyses. Contrasting the Tibetan and Han populations both living at the 3600 m altitude, we found that the Tibetan microbiome is characterized by a relative abundance of Prevotella whereas the Han stool was enriched in Bacteroides. Comparing the microbiome of Han stool obtained from populations living at different altitudes revealed a more energy efficient flora in samples from those living at higher altitude relative to their lower-altitude counterparts. Comparison of the stool microbiome of Tibetan herders living at 4800 m to rural Tibetans living at 3600 m altitude shows that the former have a flora enriched in butyrate-producing bacteria, possibly in response to the harsher environment that these herders face. Thus, the study shows that both altitude and genetic/cultural background have a significant influence on microbiome composition, and it represents the first attempt to compare stool microbiota of Tibetan and Han populations in relation to altitude.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Acute viral hepatitis (AVH) represents an important global health problem; however, the progress in understanding AVH is limited because of the priority of combating persistent HBV and HCV ...infections. Therefore, an improved understanding of the burden of AVH is required to help design strategies for global intervention.
Data on 4 major AVH types, including acute hepatitis A, B, C, and E, excluding D, were collected by the Global Burden of Disease (GBD) 2019 database. Age-standardized incidence rates and disability-adjusted life year (DALY) rates for AVH were extracted from GBD 2019 and stratified by sex, level of socio-demographic index (SDI), country, and territory. The association between the burden of AVH and socioeconomic development status, as represented by the SDI, was described.
In 2019, there was an age-standardized incidence rate of 3,615.9 (95% CI 3,360.5–3,888.3) and an age-standardized DALY rate of 58.0 (47.3–70.0) per 100,000 person-years for the 4 major types of AVH. Among the major AVH types, acute hepatitis A caused the heaviest burden. There was a significant downward trend in age-standardized DALY rates caused by major incidences of AVH between 1990 and 2019. In 2019, regions or countries located in West and East Africa exhibited the highest age-standardized incidence rates of the 4 major AVH types. These rates were stratified by SDI: high SDI and high-middle SDI locations recorded the lowest incidence and DALY rates of AVH, whereas the low-middle SDI and low SDI locations showed the highest burden of AVH.
The socioeconomic development status and burden of AVH are associated. Therefore, the GBD 2019 data should be used by policymakers to guide cost-effective interventions for AVH.
We identified a negative association between socioeconomic development status and the burden of acute viral hepatitis. The lowest burden of acute viral hepatitis was noted for rich countries, whereas the highest burden of acute viral hepatitis was noted for poor countries.
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•Association of socioeconomic development status with burden of AVH was identified.•Lowest incidence and DALY rate of AVH noted for high- and high-middle SDI location.•Highest burden of AVH noted for low-middle- and low SDI locations.•Our findings may benefit policymakers in allocating resources.
A huge accumulation of domestic waste has caused serious environmental contamination in rural areas of developing countries (RADIC). The characteristics and management of domestic waste are carefully ...discussed, based on field surveys and a literature review. The results indicate that the generation in most of RADIC is less than the median of 0.521 kg day
−1
per capita in China, and much smaller than in rural areas of developed countries (RADEC). Organic waste and inert waste with an accumulative mass percentage of 72.31% are dominant components of domestic waste in the rural areas of China. There are trends of increasing amounts of kitchen waste, paper/cardboard, and plastic/rubber and a decreasing trend of ash waste. The RADIC composition of domestic waste had a high content of organic waste and a low content of recyclable waste compared to the RADEC. Domestic waste has good compressibility and a light bulk density ranging from 40 to 650 kg m
−3
. The moisture, ash, combustible, and calorific values of domestic waste were 53.31%, 18.03%, 28.67%, and 5368 kJ kg
−1
, respectively. The domestic waste has an abundance of nutrients including organic matter (39.05%), nitrogen (1.02%), phosphorus (0.50%), and potassium (1.42%). In RADIC, domestic waste can be used as an agricultural manure only after it has been collected and sorted for the potential risk of heavy metal accumulation. Based on these characteristics of domestic waste and the different situations of rural areas, four waste management modes including centralized treatment, decentralized treatment, group treatment, and mobile treatment are designed and discussed.
Traditional Chinese medicine (TCM) is often used as an adjuvant or alternative therapy for abnormal liver biochemistry or liver fibrosis associated with chronic hepatitis B (CHB). However, the role ...of TCM in HBsAg seroclearance remains unclear. We aimed at exploring the role and possible mechanisms of TCM in HBsAg seroclearance. Fifteen widely used TCM granules invigorating the spleen and kidneys were screened. C57BL/6J mice were administered daily with TCM granules by gavage for 1 week. The effect of TCM on the M1 polarization of macrophages was measured using a CD86 assay. According to the principles of formulating prescriptions, three single TCM with the most noticeable effect on M1 polarization, accompanied by two other TCM granules, were used to develop a TCM formula. The hepatitis B virus‐expressing mouse model was constructed by hydrodynamic injection of the pAAV/HBV1.2 plasmid. Hepatitis B virus‐expressing mice were gavaged daily with phosphate‐buffered saline (PBS), TCM formula, or Codonopsis Radix, for 1 week. HBsAg, HBeAg, and hepatitis B virus DNA levels were measured. In addition, gut microbiota was profiled using 16S rDNA sequencing. Several TCM granules showed significant effects on M1 polarization. The TCM formula accelerated HBsAg seroclearance compared with the Codonopsis Radix and PBS groups. Intrahepatic M1 polarization, as indicated by flow cytometry and immunohistochemistry, was induced in the TCM formula and Codonopsis Radix groups. The abundance of Alloprevotella significantly increased in the TCM formula and Codonopsis Radix groups. These results demonstrate that the TCM formula for invigorating the spleen and kidney can accelerate HBsAg seroclearance. This effect can be attributed, at least in part, to M1 polarization of intrahepatic macrophages.
Soybean root diseases are associated with numerous fungal and oomycete pathogens; however, the community dynamics and interactions of these pathogens are largely unknown. We performed 13 ...loop-mediated isothermal amplification (LAMP) assays that targeted specific soybean root pathogens, and traditional isolation assays. A total of 159 samples were collected from three locations in the Huang-Huai-Hai region of China at three soybean growth stages (30, 60, and 90 days after planting) in 2016. In LAMP results, we found that pathogen communities differed slightly among locations, but changed dramatically between soybean growth stages. Phytophthora sojae, Rhizoctonia solani, and Fusarium oxysporum were most frequently detected at the early stage, whereas Phomopsis longicolla, Fusarium equiseti, and Fusarium virguliforme were most common in the later stages. Most samples (86%) contained two to six pathogen species. Interestingly, the less detectable species tended to exist in the samples containing more detected species, and some pathogens preferentially co-occurred in diseased tissue, including P. sojae–R. solani–F. oxysporum and F. virguliforme–Calonectria ilicicola, implying potential interactions during infection. The LAMP detection results were confirmed by traditional isolation methods. The isolated strains exhibited different virulence to soybean, further implying a beneficial interaction among some pathogens.
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