Healthy or Not: A Way to Predict Ecosystem Health in GitHub

With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development

Meta-Reinforcement Learning for Timely and Energy-efficient Data Collection in Solar-powered UAV-assisted IoT Networks

Unmanned aerial vehicles (UAVs) have the potential to greatly aid Internet of Things (IoT) networks in mission-critical data collection, thanks to their flexibility and cost-effectiveness. However, challenges arise due to the UAV's limited onboard energy and the unpredictable status updates from sensor nodes (SNs), which impact the freshness of collected data. In this paper, we investigate the energy-efficient and timely data collection in IoT networks through the use of a solar-powered UAV. Each SN generates status updates at stochastic intervals, while the UAV collects and subsequently transmits these status updates to a central data center. Furthermore, the UAV harnesses solar energy from the environment to maintain its energy level above a predetermined threshold. To minimize both the average age of information (AoI) for SNs and the energy consumption of the UAV, we jointly optimize the UAV trajectory, SN scheduling, and offloading strategy. Then, we formulate this problem as a Markov decision process (MDP) and propose a meta-reinforcement learning algorithm to enhance the generalization capability. Specifically, the compound-action deep reinforcement learning (CADRL) algorithm is proposed to handle the discrete decisions related to SN scheduling and the UAV's offloading policy, as well as the continuous control of UAV flight. Moreover, we incorporate meta-learning into CADRL to improve the adaptability of the learned policy to new tasks. To validate the effectiveness of our proposed algorithms, we conduct extensive simulations and demonstrate their superiority over other baseline algorithms

Radiomics optimizing the evaluation of endometrial receptivity for women with unexplained recurrent pregnancy loss

BackgroundThe optimization of endometrial receptivity (ER) through individualized therapies has been shown to enhance the likelihood of successful gestation. However, current practice lacks comprehensive methods for evaluating the ER of patients with recurrent pregnancy loss (RPL). Radiomics, an emerging AI-based technique that enables the extraction of mineable information from medical images, holds potential to offer a more objective and quantitative approach to ER assessment. This innovative tool may facilitate a deeper understanding of the endometrial environment and enable clinicians to optimize ER evaluation in RPL patients.ObjectiveThis study aimed to identify ultrasound radiomics features associated with ER, with the purpose of predicting successful ongoing pregnancies in RPL patients, and to assess the predictive accuracy of these features against regular ER parameters.MethodsThis retrospective, controlled study involved 262 patients with unexplained RPL and 273 controls with a history of uncomplicated full-term pregnancies. Radiomics features were extracted from ultrasound endometrial segmentation images to derive a radiomics score (rad-score) for each participant. Associations between rad-scores, baseline clinical variables, and sonographic data were evaluated using univariate and multivariate logistic regression analyses to identify potential indicators of RPL. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive accuracy of the rad-score and other identified indicators in discriminating RPL cases. Furthermore, the relationships between age and these identified indicators were assessed via Pearson correlation analysis.ResultsFrom the 1312 extracted radiomics features, five non-zero coefficient radiomics signatures were identified as significantly associated with RPL, forming the basis of the rad-score. Following multivariate logistic regression analysis, age, spiral artery pulsatility index (SA-PI), vascularisation index (VI), and rad-score emerged as independent correlates of RPL (all P<0.05). ROC curve analyses revealed the superior discriminative capability of the rad-score (AUC=0.882) over age (AUC=0.778), SA-PI (AUC=0.771), and VI (AUC=0.595). There were notable correlations between age and rad-score (r=0.275), VI (r=-0.224), and SA-PI (r=0.211), indicating age-related variations in RPL predictors.ConclusionThis study revealed a significant association between unexplained RPL and elevated endometrial rad-scores during the WOI. Furthermore, it demonstrated the potential of rad-scores as a promising predictive tool for successful ongoing pregnancies in RPL patients

A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC

Congestion control is a fundamental technology to balance the traffic load and the network. The Internet Engineering Task Force (IETF) Quick UDP Internet Connection (QUIC) protocol has flexible congestion control and at the same time possesses the advantages of high efficiency, low latency, and easy deployment at the application layer. Bottleneck bandwidth and round-trip propagation time (BBR) is an optional congestion control algorithm adopted by QUIC. BBR can significantly increase throughput and reduce latency, in particular over long-haul paths. However, BBR results in high packet loss in low bandwidth and low fairness in multi-stream scenarios. In this article, we propose the enhanced BBR congestion control (eBCC) algorithm, which improves the BBR algorithm in two aspects: (1) 10.87% higher throughput and 74.58% lower packet loss rate in the low-bandwidth scenario and (2) 8.39% higher fairness in the multi-stream scenario. This improvement makes eBCC very suitable for IoT communications to provide better QoS services

A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters

Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no attention has been paid to standardizing and analyzing the design of few-shot experiments. In this work, we highlight a fundamental risk posed by this shortcoming, illustrating that the model exhibits a high degree of sensitivity to the selection of few shots. We conduct a large-scale experimental study on 40 sets of sampled few shots for six diverse NLP tasks across up to 40 languages. We provide an analysis of success and failure cases of few-shot transfer, which highlights the role of lexical features. Additionally, we show that a straightforward full model finetuning approach is quite effective for few-shot transfer, outperforming several state-of-the-art few-shot approaches. As a step towards standardizing few-shot crosslingual experimental designs, we make our sampled few shots publicly available

Ground beetle assemblages in Beijing’s new mountain forests

Mature forests have been almost completely destroyed in China’s northern regions, but this has been followed by large-scale reforestation in the wake of environmental degradation. Although future forest plantations are expected to expand over millions of hectares, knowledge about the ecology and biodiversity of China’s replanted forests remains very limited. Addressing these knowledge gaps, we recorded ground beetle (Coleoptera: Carabidae) communities in five secondary forest types: plantations of Chinese Pine (Pinus tabulaeformis) and Prince Rupprecht’s Larch (Larix principis-rupprechtii), Oak (Quercus wutaishanica) and Asian White Birch (Betula platyphylla) woodlands, and naturally regenerated mixed forest. Species richness peaked in mixed forests, while pine and oak woodlands harboured discrete communities of intermediate species richness. Oak, pine and mixed forest habitats also showed high levels of species turnover between plots. Canopy closure was an important factor influencing ground beetle assemblages and diversity, and a number of forest specialist species only occurred in pine or oak forests. We believe that some forest specialists have survived earlier deforestation and appear to be supported by new plantation forests, but maintenance of secondary native oak and mixed forests is crucial to safeguard the overall species pool

Association between parental unhealthy behaviors and offspring’s cardiovascular health status: Results from a cross-sectional analysis of parent–offspring pairs in China

BackgroundCardiovascular health (CVH) in children and adolescents, which might be largely influenced by parental behaviors, may affect the incidence of cardiovascular diseases in adulthood. However, few studies have been conducted to explore the associations between parental behaviors and CVH status of offspring in China.MethodsData were obtained from a cross-sectional survey conducted in Chinese children and adolescents aged 7–18 years old, with a total of 10,043 parent–offspring pairs included. Parental behaviors included moderate to vigorous physical activity (MVPA), dietary behaviors, and weight status. The CVH status of offspring was consulted by The American Heart Association, including seven factors. The associations between parental behaviors and CVH status of offspring were evaluated by multilevel logistic regression. Stratified analyses were conducted to explore the potential modifying influence of sociodemographic factors.ResultsMost of the offspring had five ideal CVH factors; only 21.04% had six to seven ideal CVH factors. Parental unhealthy behaviors were associated with high odds of nonideal CVH status of offspring. Parental overweight/obesity, insufficient MVPA, and unhealthy dietary behaviors could increase the odds of owning one to three ideal CVH factors in offspring, with corresponding odds ratios (ORs) (95% confidence interval) of 1.61 (1.32–1.96), 1.31 (1.10–1.56), and 2.05 (1.43–2.94), respectively. There was a dose–response relationship between parental single unhealthy behavior and the odds of nonideal CVH status in offspring (P-trend < 0.001). Offspring with overweight parents had ORs of 1.25 for nonideal CVH status, compared to offspring with normal-weight parents. Among offspring who had the same number of ideal CVH factors, the cumulative association between unhealthy behaviors of parents and offspring’s nonideal CVH status increased if parents had more unhealthy behaviors (P-trend < 0.001).ConclusionsParental overweight/obesity, insufficient MVPA, and unhealthy dietary behaviors were strongly associated with CVH status in offspring. With a cumulative association, more unhealthy parental behaviors were associated with higher odds of offspring’s nonideal CVH status, suggesting that targeting parental behaviors might facilitate attainment of improving CVH status of children and adolescents

Indoleamine 2,3-dioxygenase 1 promotes osteosarcoma progression by regulating tumor-derived exosomal miRNA hsa-miR-23a-3p

Background: Osteosarcoma (OS) is the most common primary malignant tumor originating in bone. Immunosuppressive enzyme indoleamine 2,3-dioxygenase 1 (IDO1) participates in tumor immune tolerance and promotes tumor progression, while the study of IDO1 in OS is limited.Methods: Immunohistochemistry analysis was performed to test the expression of IDO1 and Ki67. The relationship between IDO1 or Ki67 positive count and clinical stage of the patient was analyzed. Laboratory test indexes including serum alkaline phosphatase (ALP), lactate dehydrogenase (LDH), white blood cell (WBC) count and C-reactive protein (CRP) at diagnosis of OS patients were collected. The relationship between positive count of IDO1 and Ki67 or laboratory test indexes was analyzed by Pearson’s correlation analysis. IDO1 stably overexpressed cell lines of these cells (MG63 OE, 143B OE and hFOB1.19 OE) were constructed and validated by Western blot and Elisa. Exosomes were isolated from conditioned culture media of these cells and were identified by Zetaview nanoparticle tracking analyzer. Next-generation sequencing was conducted to identify miRNAs enriched in exosomes. Differentially expressed miRNAs (DE miRNAs) were verified in clinical samples and cell lines by qPCR. Biological processes and cell components analysis of DE miRNAs was conducted by GO enrichment analysis using the protein interaction network database.Results: Immunosuppressive enzyme IDO1 was highly expressed in tumor tissues. 66.7% (6/9) of the tissues showed moderately or strongly positive immunostaining signal of IDO1, and 33.3% (3/9) were weakly positive. The expression of IDO1 was positively related to Ki67 and associated with prognostic-related clinical features of OS patients. Overexpression of IDO1 significantly affected the exosome-derived miRNA subsets from MG63, 143B and hFOB1.19 cells. A total of 1244 DE miRNAs were identified, and hsa-miR-23a-3p was further screened as key DE miRNA involved in the progression of OS. GO analysis of target genes of the DE miRNA results showed that target enrichment in the functions of immune regulation and tumor progression.Discussion: Our results indicate that IDO1 has the potential to promote the progression of OS that is related to miRNAs mediated tumor immunity. Targeting IDO1-mediated hsa-miR-23a-3p may be a potential therapeutic strategy for OS treatment

Tembusu Virus in Ducks, China

In China in 2010, a disease outbreak in egg-laying ducks was associated with a flavivirus. The virus was isolated and partially sequenced. The isolate exhibited 87%–91% identity with strains of Tembusu virus, a mosquito-borne flavivirus of the Ntaya virus group. These findings demonstrate emergence of Tembusu virus in ducks