Distribution and Abundance of Archaea in South China Sea Sponge Holoxea sp. and the Presence of Ammonia-Oxidizing Archaea in Sponge Cells

Compared with bacterial symbionts, little is known about archaea in sponges especially about their spatial distribution and abundance. Understanding the distribution and abundance of ammonia-oxidizing archaea will help greatly in elucidating the potential function of symbionts in nitrogen cycling in sponges. In this study, gene libraries of 16S rRNA gene and ammonia monooxygenase subunit A (amoA) genes and quantitative real-time PCR were used to study the spatial distribution and abundance of archaea in the South China Sea sponge Holoxea sp. As a result, Holoxea sp. specific AOA, mainly group C1a (marine group I: Crenarchaeota) were identified. The presence of ammonia-oxidizing crenarchaea was observed for the first time within sponge cells. This study suggested a close relationship between sponge host and its archaeal symbionts as well as the archaeal potential contribution to sponge host in the ammonia-oxidizing process of nitrification

ADGym: Design Choices for Deep Anomaly Detection

Deep learning (DL) techniques have recently found success in anomaly detection (AD) across various fields such as finance, medical services, and cloud computing. However, most of the current research tends to view deep AD algorithms as a whole, without dissecting the contributions of individual design choices like loss functions and network architectures. This view tends to diminish the value of preliminary steps like data preprocessing, as more attention is given to newly designed loss functions, network architectures, and learning paradigms. In this paper, we aim to bridge this gap by asking two key questions: (i) Which design choices in deep AD methods are crucial for detecting anomalies? (ii) How can we automatically select the optimal design choices for a given AD dataset, instead of relying on generic, pre-existing solutions? To address these questions, we introduce ADGym, a platform specifically crafted for comprehensive evaluation and automatic selection of AD design elements in deep methods. Our extensive experiments reveal that relying solely on existing leading methods is not sufficient. In contrast, models developed using ADGym significantly surpass current state-of-the-art techniques.Comment: NeurIPS 2023. The first three authors contribute equally. Code available at https://github.com/Minqi824/ADGy

The hidden inequality: the disparities in the quality of daily use masks associated with family economic status

Wearing high-quality masks plays a critical role in reducing COVID-19 transmission. However, no study has investigated socioeconomic inequality in the quality of masks. Addressing this gap, this paper explored the relationships between mask’s quality and family economic status. The cross-sectional survey was conducted in two Chinese universities by distributing structured questionnaires to assess participants’ characteristics including family economic status, and meanwhile collecting their masks to evaluate the quality by measuring particle filtration efficiency. The valid responses were obtained from 912 students with mean age of 19.556 ± 1.453  years and were analyzed by using fractional or binary logistic regression. Three main findings were presented. First, inequality existed in the quality of masks. 36.07% of students were using unqualified masks with average filtration efficiency of 0.795 ± 0.119, which was much lower than China’s national standard (0.9). Of those masks with identified production date, 11.43% were manufactured during COVID-19 outbreak when market was flooded with counterfeit production, and thus were of poor quality with average filtration efficiency of 0.819 ± 0.152. Second, better family economic status was associated with better masks’ filtration efficiency and greater probability of using qualified masks. Third, students with better family economic status tend to use masks with individual packaging, and unique patterns and special designs, which may lead to inequality on a psychological level. Our analysis reveals the hidden socioeconomic inequality that exist behind cheap masks. In facing the challenges of future emerging infectious diseases, it is important to address the inequity to ensure equal access to affordable qualified personal protection equipment

Automatic View Selection in Graph Databases

Peer reviewe

Study on the Electromagnetic Design and Analysis of Axial Flux Permanent Magnet Synchronous Motors for Electric Vehicles

In order to provide a complete solution for designing and analyzing the axial flux permanent magnet synchronous motor (AFPMSM) for electric vehicles, this paper covers the electromagnetic design and multi-physics analysis technology of AFPMSM in depth. Firstly, an electromagnetic evaluation method based on an analytical algorithm for efficient evaluation of AFPMSM was studied. The simulation results were compared with the 3D electromagnetic field simulation results to verify the correctness of the analytical algorithm. Secondly, the stator core was used to open the auxiliary slot to optimize the torque ripple of the AFPMSM, which reduced the torque ripple peak-to-peak value by 2%. From the perspective of ensuring the reliability, safety, and driving comfort of the traction motor in-vehicle working conditions, multi-physics analysis software was used to analyze and check the vibration and noise characteristics and temperature rise of several key operating conditions of the automotive AFPMSM. The analysis results showed that the motor designed in this paper can operate reliably

PestLite: A Novel YOLO-Based Deep Learning Technique for Crop Pest Detection

Timely and effective pest detection is essential for agricultural production, facing challenges such as complex backgrounds and a vast number of parameters. Seeking solutions has become a pressing matter. This paper, based on the YOLOv5 algorithm, developed the PestLite model. The model surpasses previous spatial pooling methods with our uniquely designed Multi-Level Spatial Pyramid Pooling (MTSPPF). Using a lightweight unit, it integrates convolution, normalization, and activation operations. It excels in capturing multi-scale features, ensuring rich extraction of key information at various scales. Notably, MTSPPF not only enhances detection accuracy but also reduces the parameter size, making it ideal for lightweight pest detection models. Additionally, we introduced the Involution and Efficient Channel Attention (ECA) attention mechanisms to enhance contextual understanding. We also replaced traditional upsampling with Content-Aware ReAssembly of FEatures (CARAFE), which enable the model to achieve higher mean average precision in detection. Testing on a pest dataset showed improved accuracy while reducing parameter size. The mAP50 increased from 87.9% to 90.7%, and the parameter count decreased from 7.03 M to 6.09 M. We further validated the PestLite model using the IP102 dataset, and on the other hand, we conducted comparisons with mainstream models. Furthermore, we visualized the detection targets. The results indicate that the PestLite model provides an effective solution for real-time target detection in agricultural pests

Using an extended protection motivation theory to explain vaccine hesitancy: a cross-sectional study among Chinese adults

Background Vaccine hesitancy was listed as one of the top 10 issues threatening global health in 2019. The objectives of this study were to (a) use an extended protection motivation theory (PMT) with an added trust component to identify predictors of vaccine hesitancy and (b) explore the predictive ability of vaccine hesitancy on vaccination behavior. Methods We conducted an online questionnaire from February 9 to April 9, 2021, in China. The target population was Chinese residents aged 18 and over. A total of 14,236 responses were received. Structural equation modeling was used to test the extended PMT model hypotheses. Results A total of 10,379 participants were finally included in this study, of whom 52.0% showed hesitancy toward vaccination. 2854 (27.5%) participants reported that they got flu shots in the past year, and 2561 (24.7%) participants were vaccinated against COVID-19. 2857 (27.5%) participants engaged in healthcare occupation. The model explained 85.7% variance of vaccine hesitancy. Self-efficacy was the strongest predictor, negatively associated with vaccine hesitancy (β = −0.584; p < .001). Response efficacy had a negative effect on vaccine hesitancy (β = −0.372; p < .001), while threat appraisal showed a positive effect (β = 0.104; p < .001). Compared with non-health workers, health workers showed more vaccine hesitancy, and response efficacy was the strongest predictor (β = −0.560; p < .001). Vaccine hesitancy had a negative effect on vaccination behavior (β = −0.483; p < .001), and the model explained 23.4% variance of vaccination behavior. Conclusions This study demonstrates that the extended PMT model is efficient in explaining vaccine hesitancy. However, the predictive ability of vaccine hesitancy on vaccination behavior is limited

Impact of Native Form Oat &beta;-Glucan on the Physical and Starch Digestive Properties of Whole Oat Bread

To investigate the effect of oat bran on bread quality and the mechanism of reducing the glycemic index (GI) of bread, wheat bran (10%, w/w, flour basis), oat bran (10%), and &beta;-glucan (0.858%) were individually added to determine the expansion of dough, the specific volume, texture, color, GI, starch digestion characteristics, and &alpha;-amylase inhibition rate of bread. The results showed that the incorporation of wheat bran and oat bran both reduced the final expanded volume of the dough, decreased the specific volume of the bread, and increased the bread hardness and crumb redness and greenness values as compared to the control wheat group. The above physical properties of bran-containing bread obviously deteriorated while the bread with &beta;-glucan did not change significantly (p &lt; 0.05). The GI in vitro of bread was in the following order: control (94.40) &gt; wheat bran (69.24) &gt; &beta;-glucan (65.76) &gt; oat bran (64.93). Correspondingly, the oat bran group had the highest content of slowly digestible starch (SDS), the &beta;-glucan group had the highest content of resistant starch (RS), and the control group had the highest content of rapidly digestible starch (RDS). For the wheat bran, oat bran, and &beta;-glucan group, their inhibition rates of &alpha;-amylase were 9.25%, 28.93%, and 23.7%, respectively. The &beta;-glucan reduced the bread GI and &alpha;-amylase activity by intertwining with starch to form a more stable gel network structure, which reduced the contact area between amylase and starch. Therefore, &beta;-glucan in oat bran might be a key component for reducing the GI of whole oat bread

Wind Effects for Floating Algae Dynamics in Eutrophic Lakes

Wind-speed decline is an important impact of climate change on the eastern Asian atmospheric circulation. Although wind does not determine algae biomass in eutrophic lakes, it is a decisive factor in the formation and severity of algae blooms. Based on 2000–2018 MODIS images, this study compared the effects of wind speed on algal blooms in three typical eutrophic lakes in China: Lake Taihu, Lake Chaohu and Lake Dianchi. The results indicate that climate change has different effects on the wind speed of the three lakes, but a common effect on the vertical distribution of algae. A wind speed of 3.0 m/s was identified as the critical threshold in the vertical distribution of chlorophyll-a concentrations in the three study lakes. The basic characteristics of the periodic variation of wind speed were different, but there was a significant negative correlation between wind speed and floating algal bloom area in all three lakes. In addition, considering lake bathymetry, wind direction could be used to identify locations that were particularly susceptible to algae blooms. We estimated that algal bloom conditions will worsen in the coming decades due to the continuous decline of wind, especially in Lake Taihu, even though the provincial and national governments have made major efforts to reduce eutrophication drivers and restore lake conditions. These results suggest that early warning systems should include a wind-speed threshold of 3.0 m/s to improve control and mitigation of algal blooms on these intensively utilized lakes

Data_Sheet_1_Flavonoids metabolism and physiological response to ultraviolet treatments in Tetrastigma hemsleyanum Diels et Gilg.ZIP

Tetrastigma hemsleyanum Diels et Gilg is a folk herb in Zhejiang Province with anti-inflammatory, antineoplastic, and anti-oxidation effects. Given its pharmacological activity, T. hemsleyanum is known as New “Zhebawei” and included in the medical insurance system of Zhejiang and other provinces. Flavonoids are the most important components of T. hemsleyanum, and their contents are mainly regulated by ultraviolet (UV) radiation. In this study, the total flavonoid contents, flavonoid monomer contents, and flavonoid synthesis related enzyme activities (phenylalanine ammonia–lyase, chalcone synthase, and chalcone isomerase), anti-oxidant enzyme activities (catalase, peroxidase, and superoxide dismutase), and biochemical indicators (malondialdehyde, free amino acid, soluble protein, and soluble sugar) in the leaves (L) and root tubers (R) of T. hemsleyanum with UV treatments were determined. Three kinds of UV radiation (UV-A, UV-B, and UV-C) and six kinds of radiation durations (15 and 30 min, 1, 2, 3, and 5 h) were used. Appropriate doses of UV-B and UV-C radiation (30 min to 3 h) induced eustress, which contributed to the accumulation of flavonoids and improve protective enzyme system activities and bioactive compound contents. Especially, certain results were observed in several special structures of the flavonoid monomer: quercetin contents in L increased by nearly 20 times, isoquercitrin contents in R increased by nearly 34 times; most of flavonoids with glycoside content, such as quercitrin (19 times), baicalin (16 times), and apigenin-7G (13 times), increased multiple times. Compared with the CK group, the flavonoid synthase activities, anti-oxidant enzyme activities, and biochemical substance contents in L and R all increased with UV treatments. This study provides a theoretical foundation for regulating flavonoids by light factors and improving the quality of T. hemsleyanum in production and medical industries.</p