SimiSketch: Efficiently Estimating Similarity of streaming Multisets

The challenge of estimating similarity between sets has been a significant concern in data science, finding diverse applications across various domains. However, previous approaches, such as MinHash, have predominantly centered around hashing techniques, which are well-suited for sets but less naturally adaptable to multisets, a common occurrence in scenarios like network streams and text data. Moreover, with the increasing prevalence of data arriving in streaming patterns, many existing methods struggle to handle cases where set items are presented in a continuous stream. Consequently, our focus in this paper is on the challenging scenario of multisets with item streams. To address this, we propose SimiSketch, a sketching algorithm designed to tackle this specific problem. The paper begins by presenting two simpler versions that employ intuitive sketches for similarity estimation. Subsequently, we formally introduce SimiSketch and leverage SALSA to enhance accuracy. To validate our algorithms, we conduct extensive testing on synthetic datasets, real-world network traffic, and text articles. Our experiment shows that compared with the state-of-the-art, SimiSketch can improve the accuracy by up to 42 times, and increase the throughput by up to 360 times. The complete source code is open-sourced and available on GitHub for reference

Performance evaluation on the factors affecting the heat extraction performance of deep coaxial borehole heat exchanger

Geothermal energy has the characteristics of stability, efficiency, and abundant reserves. Fully developing and utilizing geothermal energy is of great significance for achieving the “dual carbon” goal. This article selects and analyzes nine key factors and their weight relationships that affect the heat extraction capacity of deep coaxial borehole heat exchanger from three aspects: operating parameters, geological parameters, and exchanger parameters, providing useful references and guidance for researcher and decision makers in related fields

Identification of a major QTL and candidate genes analysis for branch angle in rapeseed (Brassica napus L.) using QTL-seq and RNA-seq

IntroductionBranching angle is an essential trait in determining the planting density of rapeseed (Brassica napus L.) and hence the yield per unit area. However, the mechanism of branching angle formation in rapeseed is not well understood.MethodsIn this study, two rapeseed germplasm with extreme branching angles were used to construct an F2 segregating population; then bulked segregant analysis sequencing (BSA-seq) and quantitative trait loci (QTL) mapping were utilized to localize branching anglerelated loci and combined with transcriptome sequencing (RNA-seq) and quantitative real-time PCR (qPCR) for candidate gene miningResults and discussionA branching angle-associated quantitative trait loci (QTL) was mapped on chromosome C3 (C3: 1.54-2.65 Mb) by combining BSA-seq as well as traditional QTL mapping. A total of 54 genes had SNP/Indel variants within the QTL interval were identified. Further, RNA-seq of the two parents revealed that 12 of the 54 genes were differentially expressed between the two parents. Finally, we further validated the differentially expressed genes using qPCR and found that six of them presented consistent differential expression in all small branching angle samples and large branching angles, and thus were considered as candidate genes related to branching angles in rapeseed. Our results introduce new candidate genes for the regulation of branching angle formation in rapeseed, and provide an important reference for the subsequent exploration of its formation mechanism

A Systematic Analysis on DNA Methylation and the Expression of Both mRNA and microRNA in Bladder Cancer

Background: DNA methylation aberration and microRNA (miRNA) deregulation have been observed in many types of cancers. A systematic study of methylome and transcriptome in bladder urothelial carcinoma has never been reported. Methodology/Principal Findings: The DNA methylation was profiled by modified methylation-specific digital karyotyping (MMSDK) and the expression of mRNAs and miRNAs was analyzed by digital gene expression (DGE) sequencing in tumors and matched normal adjacent tissues obtained from 9 bladder urothelial carcinoma patients. We found that a set of significantly enriched pathways disrupted in bladder urothelial carcinoma primarily related to "neurogenesis" and "cell differentiation" by integrated analysis of -omics data. Furthermore, we identified an intriguing collection of cancer-related genes that were deregulated at the levels of DNA methylation and mRNA expression, and we validated several of these genes (HIC1, SLIT2, RASAL1, and KRT17) by Bisulfite Sequencing PCR and Reverse Transcription qPCR in a panel of 33 bladder cancer samples. Conclusions/Significance: We characterized the profiles between methylome and transcriptome in bladder urothelial carcinoma, identified a set of significantly enriched key pathways, and screened four aberrantly methylated and expressed genes. Conclusively, our findings shed light on a new avenue for basic bladder cancer research

Toward bridging gaps in patient navigation: A study on the adoption of artificial intelligence technologies

Abstract Background Patient navigators, whose value has become increasingly apparent, still face significant challenges, including a lack of support, funding, and recognition. These challenges have been exacerbated in the wake of COVID‐19 pandemic. Methods This study explored the potential use of artificial intelligence (AI) in patient navigation. Data were collected through structured surveys and individual interviews with patient navigators from a variety of institutions and professional backgrounds. The data were analyzed to understand the current state of patient navigation, identify existing gaps, and suggest best practices for the future. Results The findings showed that patient navigators (a) have diverse backgrounds and responsibilities, (b) lack technology support for their work, (c) are at risk for burnout, with the extent varying based on the level of technical support received, and (d) report significant overlap between current barriers and those that could potentially be addressed with AI‐driven technologies. Conclusion A novel intervention, that is enabled by AI and other technologies and tailored to individual needs, has the potential to reduce burnout, increase capacity, and help ensure the sustainability of patient navigation and other areas of healthcare. By addressing the specific needs of individual patients, this type of intervention could help improve the overall effectiveness of patient navigation and support the long‐term sustainability of the role

Analysis of Influencing Factors on Soil Thermal Conductivity Test in Ground Source Heat Pump

A three dimensional numerical model of ground source heat pump system was established. The effects of testing time, starting time, borehole radius, initial ground temperature and heat injection rate on identified thermal conductivity of the deep ground soil were analyzed based on the numerical model. The simulation results showed that thermal response test time should be more than 70 h; For cylinder-source model, with the increase of the size of the borehole, the identified thermal conductivity gradually decreased; The initial temperature of ground soil has no effect on the result of thermal conductivity identification, but the testing precision of the initial temperature has larger effects to identification results when the parameter estimation method is adopted; For pure thermal conductivity model, heat injection rate has no effect on thermal conductivity identification results

Highly efficient and cheap treatment of dye by graphene-doped TiO2 microspheres

Abstract Highly efficient dye wastewater treatment by photocatalytic catalysis commonly requires expensive catalysts, long degradation time and a complicated procedure. Here, we for the first time prepared cheap graphene-doped titanium dioxide microspheres with a simple procedure to degrade dye with high efficiency. When the catalyst concentration was 0.2 g·L−1, the photocatalysis degradation extent of methylene blue solution, methylene green solution and 1,9-dimethyl methylene blue solution reached 96.4, 85.9 and 98.7%, respectively. The results showed that the degradation reactions accorded with the Langmuir–Hinshelwood model, and the photocatalytic reactions belonged to a first-order reaction in the primary stage. Furthermore, different photocatalytic degradation mechanisms were proposed, which have not been found in other literature. This work opened a new route for simple preparation of cheap microspheres in photocatalytic dye wastewater treatment with high efficiency.</jats:p