The Influences of International Trade on Sustainable Economic Growth: An Economic Policy Perspective

This study uses the Gregory–Hansen cointegration method and the vector error correction model in the vector autoregression system to reveal how international trade contributes to economic sustainability. The Gregory–Hansen test for cointegration method reveals a permanent equilibrium relation among sustainably economic growth, exports, and imports and shows that exports facilitate GDP growth and accelerate improvements in the capability of imports in the long-run. The causality between GDP and exports is unidirectional, indicating that exports area determinant of sustainable economic growth. The bidirectional causality from imports to GDP also sheds light on the important influence of imports on economic sustainability; however, GDP growth also drives import growth. The interaction between imports and exports corresponds to their bidirectional causal relationship, which is indicative of imports contributing to export production and of export growth expanding the capacity for imports. This finding indicates that imports are both exogenous and endogenous factors for exports

Embracing corruption burstiness: Fast error recovery for ZigBee under wi-Fi interference

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The ZigBee communication can be easily and severely interfered by Wi-Fi traffic. Error recovery, as an important means for ZigBee to survive Wi-Fi interference, has been extensively studied in recent years. The existing works add upfront redundancy to in-packet blocks for recovering a certain number of random corruptions. Therefore the bursty nature of ZigBee in-packet corruptions under Wi-Fi interference is often considered harmful, since some blocks are full of errors which cannot be recovered and some blocks have no errors but still requiring redundancy. As a result, they often use interleaving to reshape the bursty errors, before applying complex FEC codes to recover the re-shaped random distributed errors. In this paper, we take a different view that burstiness may be helpful. With burstiness, the in-packet corruptions are often consecutive and the requirement for error recovery is reduced as ”recovering any k consecutive errors” instead of ”recovering any random k errors”. This lowered requirement allows us to design far more efficient code than the existing FEC codes. Motivated by this implication, we exploit the corruption burstiness to design a simple yet effective error recovery code using XOR operations (called ZiXOR). ZiXOR uses XOR code and the delay is significantly reduced. More, ZiXOR uses RSSI-hinted approach to detect in packet corruptions without CRC, incurring almost no extra transmission overhead. The testbed evaluation results show that ZiXOR outperforms the state-of-the-art works in terms of the throughput (by 47%) and latency (by 22%)This work was supported by the National Natural Science Foundation of China (No. 61602095 and No. 61472360), the Fundamental Research Funds for the Central Universities (No. ZYGX2016KYQD098 and No. 2016FZA5010), National Key Technology R&D Program (Grant No. 2014BAK15B02), CCFIntel Young Faculty Researcher Program, CCF-Tencent Open Research Fund, China Ministry of Education—China Mobile Joint Project under Grant No. MCM20150401 and the EU FP7 CLIMBER project under Grant Agreement No. PIRSES-GA- 2012-318939. Wei Dong is the corresponding author

Bias Assessment and Mitigation in LLM-based Code Generation

Utilizing state-of-the-art Large Language Models (LLMs), automatic code generation models play a pivotal role in enhancing the productivity and efficiency of software development coding procedures. As the adoption of LLMs becomes more widespread in software coding ecosystems, a pressing issue has emerged: does the generated code contain social biases, such as those related to age, gender, and race? This issue concerns the integrity, fairness, and ethical foundation of software applications that depend on the code generated by these models, yet is under-explored in the literature. This paper presents a novel bias assessment framework that is specifically designed for code generation tasks. Based on this framework, we conduct an extensive evaluation on the bias of nine state-of-the-art LLM-based code generation models. Our findings reveal that first, 31.45\% to 79.93\% code functions generated by our evaluated code generation models are biased, and 9.68\% to 37.37\% code functions' functionality are affected by the bias, which means biases not only exist in code generation models but in some cases, directly affect the functionality of the generated code, posing risks of unintended and possibly harmful software behaviors. To mitigate bias from code generation models, we propose three mitigation strategies, which can decrease the biased code ratio to a very low level of 0.4\% to 4.57\%

Use of low-dose computed tomography to assess pulmonary tuberculosis among healthcare workers in a tuberculosis hospital

BACKGROUND: According to the World Health Organization, China is one of 22 countries with serious tuberculosis (TB) infections and one of the 27 countries with serious multidrug-resistant TB strains. Despite the decline of tuberculosis in the overall population, healthcare workers (HCWs) are still at a high risk of infection. Compared with high-income countries, the TB prevalence among HCWs is higher in low- and middle-income countries. Low-dose computed tomography (LDCT) is becoming more popular due to its superior sensitivity and lower radiation dose. However, there have been no reports about active pulmonary tuberculosis (PTB) among HCWs as assessed with LDCT. The purposes of this study were to examine PTB statuses in HCWs in hospitals specializing in TB treatment and explore the significance of the application of LDCT to these workers. METHODS: This study retrospectively analysed the physical examination data of healthcare workers in the Beijing Chest Hospital from September 2012 to December 2015. Low-dose lung CT examinations were performed in all cases. The comparisons between active and inactive PTB according to the CT findings were made using the Pearson chi-square test or the Fisher’s exact test. Comparisons between the incidences of active PTB in high-risk areas and non-high-risk areas were performed using the Pearson chi-square test. Analyses of active PTB were performed according to different ages, numbers of years on the job, and the risks of the working areas. Active PTB as diagnosed by the LDCT examinations alone was compared with the final comprehensive diagnoses, and the sensitivity and positive predictive value were calculated. RESULTS: A total of 1 012 participants were included in this study. During the 4-year period of medical examinations, active PTB was found in 19 cases, and inactive PTB was found in 109 cases. The prevalence of active PTB in the participants was 1.24%, 0.67%, 0.81%, and 0.53% for years 2012 to 2015. The corresponding incidences of active PTB among the tuberculosis hospital participants were 0.86%, 0.41%, 0.54%, and 0.26%. Most HCWs with active TB (78.9%, 15/19) worked in the high-risk areas of the hospital. There was a significant difference in the incidences of active PTB between the HCWs who worked in the high-risk and non-high-risk areas (odds ratio [OR], 14.415; 95% confidence interval (CI): 4.733 – 43.896). Comparisons of the CT signs between the active and inactive groups via chi-square tests revealed that the tree-in-bud, cavity, fibrous shadow, and calcification signs exhibited significant differences (P = 0.000, 0.021, 0.001, and 0.024, respectively). Tree-in-bud and cavity opacities suggest active pulmonary tuberculosis, whereas fibrous shadow and calcification opacities are the main features of inactive pulmonary tuberculosis. Comparison with the final comprehensive diagnoses revealed that the sensitivity and positive predictive value of the diagnoses of active PTB based on LDCT alone were 100% and 86.4%, respectively. CONCLUSIONS: Healthcare workers in tuberculosis hospitals are a high-risk group for active PTB. Yearly LDCT examinations of such high-risk groups are feasible and necessary. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40249-017-0274-6) contains supplementary material, which is available to authorized users

Poly[{μ2-1,2-bis­[4-(3-pyrid­yl)pyrimidin-2-ylsulfan­yl]ethane}di-μ2-cyanido-dicopper(I)]

The asymmetric unit of the title complex, [Cu2(CN)2(C20H16N6S2)]n, contains one CuI cation, one cyanide ligand and half of a centrosymmetric 1,2-bis­[4-(3-pyrid­yl)pyrimidin-2-ylsulfan­yl]ethane (bppe) ligand. The CuI atom displays a trigonal coordination geometry, being surrounded by one C atom from one cyanide anion and two N atoms from one cyanide and one bppe ligand. In the complex, each cyanide anion links two CuI atoms in a bis-monodentate mode into a zigzag [–Cu—CN–]n chain. Two parallel chains are linked by bppe ligands into a ladder chain

Exploring the shared genes of hypertension, diabetes and hyperlipidemia based on microarray

Given their relationship with metabolic syndrome and systematic inflammatory diseases, the pathogenesis of hypertension, hyperglycemia, and hyperlipidemia is closely related. To explore the common genes among these three conditions, spontaneous hypertensive rats (SHR), spontaneous diabetic Goto-Kakizaki rats (GK) and hyperlipidemia rats (HMR) were reared for experiments. Gene array was used to identify the genes of SHR, GK and HMR compared with normal Wistar rats using TBtools software. First, real-time PCR was applied to verify these genes, and Cytoscape software was used to construct networks based on the National Center for Biotechnology Information (NCBI) database. Second, Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was performed to classify the genes. Visualization and Integrated Discovery (DAVID) database and Gene Ontology database were used to explore the biological function. Finally, Onto-tools Pathway Express was used to analyze the pathways of shared genes. Importantly, upregulated common genes, such as Bad, Orm1, Arntl and Zbtb7a, were used to construct a network of 150 genes, while downregulated genes, such as Mif and Gpx1, formed a network of 29 genes. Interestingly, the networks were involved in various pathways, such as insulin signal pathway, endometrial cancer pathway, circadian rhythm pathway, and pancreatic cancer pathway. We discovered common genes of SHR, GK and HMR compared with normal Wistar rats, and the association of these genes together with biological function were preliminarily revealed

HybridFusion: LiDAR and Vision Cross-Source Point Cloud Fusion

Recently, cross-source point cloud registration from different sensors has become a significant research focus. However, traditional methods confront challenges due to the varying density and structure of cross-source point clouds. In order to solve these problems, we propose a cross-source point cloud fusion algorithm called HybridFusion. It can register cross-source dense point clouds from different viewing angle in outdoor large scenes. The entire registration process is a coarse-to-fine procedure. First, the point cloud is divided into small patches, and a matching patch set is selected based on global descriptors and spatial distribution, which constitutes the coarse matching process. To achieve fine matching, 2D registration is performed by extracting 2D boundary points from patches, followed by 3D adjustment. Finally, the results of multiple patch pose estimates are clustered and fused to determine the final pose. The proposed approach is evaluated comprehensively through qualitative and quantitative experiments. In order to compare the robustness of cross-source point cloud registration, the proposed method and generalized iterative closest point method are compared. Furthermore, a metric for describing the degree of point cloud filling is proposed. The experimental results demonstrate that our approach achieves state-of-the-art performance in cross-source point cloud registration

A novel frame-shift mutation in FRMD7 causes X-linked idiopathic congenital nystagmus in a Chinese family

Purpose: To screen mutations in the FERM domain-containing 7 (FRMD7) gene in a Chinese family with X-linked idiopathic congenital nystagmus (ICN). Methods: It has been reported that FRMD7 mutations account for approximately 47% of X-linked nystagmus in Chinese patients. We collected 5 ml of blood samples from members of a family with X-linked ICN and 100 normal controls. Mutations in FRMD7 were determined by sequencing PCR products. Results: We identified a previously unreported 4 bp deletion in FRMD7 (c.1486-1489 del TTTT) in a Chinese family. The mutation co-segregated with the disease phenotype in patients and female carriers, while it was not detected in other relatives or in the 100 normal controls. Conclusions: Our results expand the spectrum of FRMD7 mutations causing ICN, and further confirm the role of FRMD7 in the pathogenesis of ICN. Direct sequencing of FRMD7 could be used as a diagnostic testing of idiopathic congenital nystagmus.Biochemistry & Molecular BiologyOphthalmologySCI(E)PubMed4ARTICLE297-992765-27681