65 research outputs found
Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction
Understanding Origin-Destination (O-D) travel demand is crucial for transportation management. However, traditional spatialtemporal deep learning models grapple with addressing the sparse
and long-tail characteristics in high-resolution O-D matrices and
quantifying prediction uncertainty. This dilemma arises from the
numerous zeros and over-dispersed demand patterns within these
matrices, which challenge the Gaussian assumption inherent to
deterministic deep learning models. To address these challenges,
we propose a novel approach: the Spatial-Temporal Tweedie Graph
Neural Network (STTD). The STTD introduces the Tweedie distribution as a compelling alternative to the traditional ’zero-inflated’
model and leverages spatial and temporal embeddings to parameterize travel demand distributions. Our evaluations using realworld datasets highlight STTD’s superiority in providing accurate
predictions and precise confidence intervals, particularly in highresolution scenarios. GitHub code is available online
Enhancing Large Language Models for Secure Code Generation: A Dataset-driven Study on Vulnerability Mitigation
Large language models (LLMs) have brought significant advancements to code
generation, benefiting both novice and experienced developers. However, their
training using unsanitized data from open-source repositories, like GitHub,
introduces the risk of inadvertently propagating security vulnerabilities. To
effectively mitigate this concern, this paper presents a comprehensive study
focused on evaluating and enhancing code LLMs from a software security
perspective. We introduce SecuCoGen\footnote{SecuCoGen has been uploaded as
supplemental material and will be made publicly available after publication.},
a meticulously curated dataset targeting 21 critical vulnerability types.
SecuCoGen comprises 180 samples and serves as the foundation for conducting
experiments on three crucial code-related tasks: code generation, code repair
and vulnerability classification, with a strong emphasis on security. Our
experimental results reveal that existing models often overlook security
concerns during code generation, leading to the generation of vulnerable code.
To address this, we propose effective approaches to mitigate the security
vulnerabilities and enhance the overall robustness of code generated by LLMs.
Moreover, our study identifies weaknesses in existing models' ability to repair
vulnerable code, even when provided with vulnerability information.
Additionally, certain vulnerability types pose challenges for the models,
hindering their performance in vulnerability classification. Based on these
findings, we believe our study will have a positive impact on the software
engineering community, inspiring the development of improved methods for
training and utilizing LLMs, thereby leading to safer and more trustworthy
model deployment
Contamination status and molecular typing of Legionella pneumophila in artificial water environment in Shanghai hospitals from 2019 to 2020
BackgroundThe incidence of Legionnaires' disease is increasing globally and artificial water environment is becoming a common source of outbreaks. Molecular typing techniques can help prevent and control Legionella. ObjectiveTo understand the molecular epidemiological characteristics of Legionella pneumophila in artificial water environment of Shanghai hospitals, and provide a scientific basis for the prevention and control of Legionnaires' disease. MethodsWater samples were collected from artificial water environment in 14 hospitals from May to October each year from 2019 to 2020 in Shanghai. A total of 984 water samples were collected from 8 Grade-A tertiary hospitals and 6 non-Grade-A tertiary hospitals, including 312 samples of cooling water, 72 samples of chilled water, and 600 samples of tap water. The water samples were isolated and serotyped for Legionella pneumophila and preserved, and the positive rate of Legionella pneumophila in the samples was used as an indicator of contamination. The preserved strains were resuscitated and 81 surviving strains were obtained for pulsed field gel electrophoresis (PFGE) typing analysis. ResultsA total of 124 Legionella pneumophila positive water samples were detected, with a positive rate of 12.60%. The positive rate was higher in the Grade-A tertiary hospitals (16.54%, 87/526) than in the non-Grade-A tertiary hospitals (8.08%, 37/458) (χ2=15.91, P<0.001). The positive rate of cooling water (23.40%) was the highest among different types of water samples, and the difference was statistically significant (χ2=61.19, P<0.001). The difference in positive rate of tap water was statistically significant among different hospital departments (χ2=11.37, P<0.05). The positive rate in 2019 (15.06%) was higher than that in 2020 (9.84%) (χ2=6.23, P<0.05). From May to October, August had the highest annual average positive rate (16.46%) and October had the lowest (8.54%), but the difference in positive rates among months was not statistically significant (χ2=5.39, P=0.37). The difference in positive rate among districts was statistically significant (χ2=24.88, P<0.001). A total of 131 strains of Legionella pneumophila were isolated, with serotype 1 (80.15%, 105/131) predominating. Among the 81 surviving strains of Legionella pneumophila subjected to PFGE typing, the band-based similarity coefficients ranged from 41.30% to 100%. Among the 29 PFGE band types (S1-S29) recorded, each band type included 1-10 strains, and S28 was the dominant band type. Four clusters (I-IV) of PFGE band types were identified, accounting for 66.67% (54/81) of all strains and containing 13 band types. ConclusionLegionella pneumophila contamination is present in the artificial water environment of hospitals in Shanghai from 2019 to 2020, and the contamination in tap water deserves attention. The detected serotype of Legionella pneumophila is predominantly type 1, and PFGE typing reveals the presence of genetic polymorphism. Therefore, the monitoring and control of Legionella pneumophila in hospital artificial water environment should be strengthened
Stability and genetic insights of the co-existence of blaCTX-M-65, blaOXA-1, and mcr-1.1 harboring conjugative IncI2 plasmid isolated from a clinical extensively-drug resistant Escherichia coli ST744 in Shanghai
BackgroundCo-existence of colistin, β-lactam and carbapenem in multidrug-resistant Enterobacteriaceae isolates poses a serious threat to public health. In this study, we investigated and characterized the co-occurrence of blaCTX-M-65, blaOXA-1, and mcr-1.1 strain isolated from a clinical extensively-drug-resistant Escherichia coli ST744 in Shanghai.MethodsAntimicrobial susceptibility test was carried out by agar dilution methods. Whole genome sequencing was conducted, and resistance genes, and sequence types of colistin in E. coli isolates were analyzed. Plasmid stability and amino acid mutations were assessed in E. coli isolates.ResultsA colistin resistant E. coli ST744, named ECPX221, was identified out of 145 fecal samples collected. The strain carries a 60,168 IncI2 plasmid with the mcr-1.1 gene. The strain also has blaCTX-M-65, blaOXA-1, dfrA14, qnrS1, cmlA5, arr2, ampC, aph(4)-Ia, sul1, and aadA5 resistance genes. The plasmid pECPX221 was capable of conjugation with an efficiency of 2.6 × 10−2. Notably, 45% of the transconjugants were determined as mcr-1.1-harboring in the colistin-free environment after 60 generation of passage. No mutations occurred in pmrB, mgrB, and phoPQ gene in the mcr-1.1-harboring transconjugants. Bioinformatic analysis indicated pECPX221 shared highly similar backbone with the previously reported mcr-1.1-harboring pAH62-1, pMFDS1339.1, pSCZE4, and p2018-10-2CC. Furthermore, sequencing and phylogenetic analyses revealed a similarity between other MCR-1-homolog proteins, indicating that ECPX221 was colistin resistant.ConclusionThe stable transferable mcr-1.1-harboring plasmid found in the E. coli ST744 strain indicated the high risk to disseminate the extensively-drug-resistance phenotype among Enterobacteriaceae
Three-dimensional biofabrication of nanosecond laser micromachined nanofibre meshes for tissue engineered scaffolds
There is a high demand for bespoke grafts to replace damaged or malformed bone and cartilage tissue. Three-dimensional (3D) printing offers a method of fabricating complex anatomical features of clinically relevant sizes. However, the construction of a scaffold to replicate the complex hierarchical structure of natural tissues remains challenging. This paper reports a novel biofabrication method that is capable of creating intricately designed structures of anatomically relevant dimensions. The beneficial properties of the electrospun fibre meshes can finally be realised in 3D rather than the current promising breakthroughs in two-dimensional (2D). The 3D model was created from commercially available computer-aided design software packages in order to slice the model down into many layers of slices, which were arrayed. These 2D slices with each layer of a defined pattern were laser cut, and then successfully assembled with varying thicknesses of 100 μm or 200 μm. It is demonstrated in this study that this new biofabrication technique can be used to reproduce very complex computer-aided design models into hierarchical constructs with micro and nano resolutions, where the clinically relevant sizes ranging from a simple cube of 20 mm dimension, to a more complex, 50 mm-tall human ears were created. In-vitro cell-contact studies were also carried out to investigate the biocompatibility of this hierarchal structure. The cell viability on a micromachined electrospun polylactic-co-glycolic acid fibre mesh slice, where a range of hole diameters from 200 μm to 500 μm were laser cut in an array where cell confluence values of at least 85% were found at three weeks. Cells were also seeded onto a simpler stacked construct, albeit made with micromachined poly fibre mesh, where cells can be found to migrate through the stack better with collagen as bioadhesives. This new method for biofabricating hierarchical constructs can be further developed for tissue repair applications such as maxillofacial bone injury or nose/ear cartilage replacement in the future
When guanxi meets structural holes : exploring the guanxi networks of Chinese entrepreneurs on digital platforms
In this exploratory study, we investigate how Chinese entrepreneurs on digital platforms interact and leverage guanxi (a system of relationships and social network) to buffer the negative impacts of structural holes on knowledge orchestration. We develop our research model and formulate ten hypotheses by drawing on the literature. We adopt a mixed-methods research approach in which we use quantitative surveys to test the hypotheses, and qualitative interviews to explain why certain relationships are stronger in one stage of entrepreneurial development than the other. The study contributes to the literature on digital entrepreneurship in two ways. First, this study offers an initial understanding of the dynamics of guanxi networks for knowledge mobilisation and knowledge coordination across start-up and growth stages of Chinese entrepreneurs on digital platforms. Second, by drawing on the relevant literature, our findings extend the current understanding of knowledge orchestration of digital entrepreneurs and contribute to the literatures of structural holes theory and guanxi
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