Multi-Granularity Detector for Vulnerability Fixes

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and boost the effectiveness of prior works, we propose MiDas (Multi-Granularity Detector for Vulnerability Fixes). Unique from prior works, Midas constructs different neural networks for each level of code change granularity, corresponding to commit-level, file-level, hunk-level, and line-level, following their natural organization. It then utilizes an ensemble model that combines all base models to generate the final prediction. This design allows MiDas to better handle the noisy and highly imbalanced nature of vulnerability-fixing commit data. Additionally, to reduce the human effort required to inspect code changes, we have designed an effort-aware adjustment for Midas's outputs based on commit length. The evaluation results demonstrate that MiDas outperforms the current state-of-the-art baseline in terms of AUC by 4.9% and 13.7% on Java and Python-based datasets, respectively. Furthermore, in terms of two effort-aware metrics, EffortCost@L and Popt@L, MiDas also outperforms the state-of-the-art baseline, achieving improvements of up to 28.2% and 15.9% on Java, and 60% and 51.4% on Python, respectively

Single‐atom catalyst application in distributed renewable energy conversion and storage

Abstract In recent years, owing to the depletion of fossil energy and the aggravation of environmental pollution, the conversion and storage of distributed renewable energy (such as solar energy, wind energy, and tidal energy) based on electrochemical technology have attracted extensive attention. Electrocatalytic processes with high efficiency and high selectivity play a key role in clean energy conversion and storage. With the nearly 100% atomic utilization rate and unique catalytic activity, single‐atom catalysts (SACs) have been rapidly developed and widely used in the field of energy conversion and storage. In this review, we first introduce the characteristics of SACs. Then, we focus on the application of SACs in energy conversion, including water electrolysis reaction, nitrogen reduction reaction, nitrate reduction reaction, oxygen reduction reaction, and carbon dioxide reduction reaction. In terms of energy storage, we focus on supercapacitors and Li–S batteries. Further, we enumerate some of the methods for the synthesis of SACs in high metal loading or large scale. Finally, the main challenges and opportunities for this emerging field in the future are discussed and prospected

Effects of microendoscopy-assisted reduction and screw fixation through a single mini-incision on posterior cruciate ligament tibial avulsion fracture

Introduction There are various surgical approaches for the treatment of posterior cruciate ligament (PCL) injury-associated tibial fracture avulsion, including arthroscopy-assisted surgery and open posterior surgery. However, none of these treatments are perfect. We have established a simple procedure with microendoscopy-assisted reduction and cannulated screw fixation for the treatment of this disease through a single mini-incision. In this study, we delineated the effects of this surgical approach for patients with PCL tibial avulsion fracture. Patients and methods We retrospectively reviewed 24 patients with acute PCL tibial avulsion fracture treated via this method from 2004 to 2008. All the patients were implanted with cannulated screws (AO/ASIF, 3.5, 4.0 or 4.5 mm in diameter, 3-4 mm in length) for fixation by microendoscopy. The posterior drawer test (PDT) and KT-2000 arthrometer examination were performed to evaluate knee stability. The Lysholm knee scoring scale and the International Knee Documentation Committee (IKDC) scoring scale were used to assess knee function. Types and rates of complications and radiographic follow-up were reviewed for all cases. Results 23 of 24 cases achieved knee stability by PDT and KT-2000 examination. The Lysholm's score was improved from 43.8 +/- 4.6 to 95.3 +/- 3.8. The IKDC evaluation demonstrated an improved function in 17 cases with grade A, 6 with grade B, and 1 with grade C. No relevant complications were experienced by any patient. Conclusions Increased stability, functional improvement, and few complications were observed in patients of PCL injury-associated tibial fracture avulsion treated with the microendoscopy-assisted reduction and cannulated screw fixation through a single mini-incision.Nanjing Military Medical Technology Innovation Project during the 11th Five-Year Plan Period of China [08MA077

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma

Objectives. Although patients with grade 2 glioma have a relatively better prognosis and longer survival than those with high-grade glioma, there are still a number of patients with disappointing outcomes. In order to accurately predict the prognosis of patients, relevant risk factors were included in the analysis to establish a clinical prediction model so as to provide a basis for clinically individualized treatment. Methods. A retrospective study was conducted in patients diagnosed with grade 2 glioma. Data including clinical features, pathological type, molecular classification, neuroimaging examination, treatment, and survival were collected. The data sets were randomly assigned, with 80% of the data used for model building and 20% for validation. Cox proportional hazard regression analysis was used to construct the model using important risk factors and present it in the form of a nomogram. The nomogram was evaluated a using C-index and calibration chart. Results. A total of 160 patients were enrolled in this analysis, including 128 in the training group and 32 in the validation group. In the training group, eight important risk factors including preoperative KPS, the first presenting symptom, the extent of resection, the gross tumor size, 1p19q, IDH, radiotherapy, and chemotherapy were identified to construct the model. The C-index of the training group and the validation group was 0.832 and 0.801, respectively, indicating that the model had good prediction ability. The calibration charts of the two groups were drawn respectively, which showed that the calibration line and the standard line had a good consistency, which suggested that the model-predicted risk had a good consistency with the actual risk. Conclusions. Based on the data of our center, a nomogram prediction model with eight variables has been established as an off-the-rack tool and verified its accuracy, which can guide clinical work and provide consultation for patients

A Novel Individual Carbon Emission Evaluation and Carbon Trading Model for Low-Carbon University Campuses

Individual carbon accounting and trading is significant for building and achieving low-/zero-carbon university campuses. This manuscript examines various aspects of individual carbon trading on campus, such as assessing personal carbon emissions, students’ willingness to participate in individual carbon trading on campus, and its influencing factors, policy setting, and emission reduction benefits. Based on the Theory of Planned Behavior, this manuscript uses the conditional process analysis method and conducts a questionnaire survey on a university campus in Beijing to evaluate individuals’ carbon emissions on campus and explore their willingness to trade personal carbon. Moreover, a system dynamics approach is adopted to propose a simulation model of individual carbon trading on the campus and assess its feasibility and emission reduction benefits. The results indicate an average annual emission reduction of 8.18% per person, providing a theoretical foundation to implement and promote the individual carbon trading pilot on campus. These findings highlight the potential benefits of individual carbon trading policies that may effectively reduce carbon emissions on university campuses

Seasonal variation and size distribution of biogenic secondary organic aerosols at urban and continental background sites of China

Size-resolved biogenic secondary organic aerosols (BSOA) derived from isoprene and monoterpene photooxidation in Qinghai Lake, Tibetan Plateau (a continental background site) and five cities of China were measured using gas chromatography/mass spectrometry (GC/MS). Concentrations of the determined BSOA are higher in the cities than in the background and are also higher in summer than in winter. Moreover, strong positive correlations (R-2] = 0.44-0.90) between BSOA and sulfate were found at the six sites, suggesting that anthropogenic pollution (i.e., sulfate) could enhance SOA formation, because sulfate provides a surface favorable for acid-catalyzed formation of BSOA. Size distribution measurements showed that most of the determined SOA tracers are enriched in the fine mode (< 3.3 mu m) except for cis-pinic and cis-pinonic acids, both presented a comparable mass in the fine and coarse (> 3.3 mu m) modes, respectively. Mass ratio of oxidation products derived from isoprene to those from monoterpene in the five urban regions during summer are much less than those in Qinghai Lake region. In addition, in the five urban regions relative abundances of monoterpene oxidation products to SOA are much higher than those of isoprene. Such phenomena suggest that BSOA derived from monoterpenes are more abundant than those from isoprene in Chinese urban areas. (C) 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V