The Application Research of OLAP in Police Intelligence Decision System

AbstractAiming at the large amounts of data collected by the public security organs, the technologies of data warehouse and OLAP are used to realize the police intelligence decision system based on SQL Server 2008 platform. The multidimensional analysis results reveal some potential regularity between criminal's action and the cases, so as to help the policemen make correct judgments

Influence of precipitation on the Portevin-Le Chatelier effect in Al-Mg alloys

AbstractIn the alloy with solute content higher than the limiting solubility, the solute atoms that have failed to dissolve will precipitate from the solid solution and form precipitations. In this study, the Portevin-Le Chatelier (PLC) effects in annealed 5456 and 5052 aluminum alloys with different precipitation contents have been investigated under different applied strain rates. The results suggest that precipitations have significant effect on the PLC effect and the more the precipitations are, the greater the influence is. Furthermore, the solute diffusion is pipe diffusion in 5052 alloy with lower precipitation content. However, for 5456 alloy with higher precipitation content, the diffusion is no longer the case but more complex

Study on the Optimization of the Formula of Potato Scone andIts Texture Characteristics

In order to enrich potato staple products and improve the sensory quality of scones, the rheological properties of mixed dough of potato flour and wheat flour were studied. With sensory score and texture characteristics as evaluation indexes, the formulation of potato flour scone was optimized by single factor experiments and orthogonal test. The results showed that potato flour could improve the water absorption of wheat flour and shorten the formation time of dough, but it would lead to a decline in the elasticity and strength of the dough, resulting in a decrease in its quality. Therefore, the appropriate substitution ratio for whole potato flour was considered to be 20%. The best process recipe for scones was based on a mixture of wheat flour and whole potato flour quality, with 20% whole potato flour added, 68% water added, 0.8% yeast added and 6% sugar added. The hardness of the scone prepared under the optimal condition was 342.63 g, and the chewiness was 106.76 N. The research results provided a theoretical basis for the quality improvement of the scones and the development of whole potato flour products

Sluggish and Chemically-Biased Interstitial Diffusion in Concentrated Solid Solution Alloys: Mechanisms and Methods

Interstitial diffusion is a pivotal process that governs the phase stability and irradiation response of materials in non-equilibrium conditions. In this work, we study sluggish and chemically-biased interstitial diffusion in Fe-Ni concentrated solid solution alloys (CSAs) by combining machine learning (ML) and kinetic Monte Carlo (kMC), where ML is used to accurately and efficiently predict the migration energy barriers on-the-fly. The ML-kMC reproduces the diffusivity that was reported by molecular dynamics results at high temperatures. With this powerful tool, we find that the observed sluggish diffusion and the "Ni-Ni-Ni"-biased diffusion in Fe-Ni alloys are ascribed to a unique "Barrier Lock" mechanism, whereas the "Fe-Fe-Fe"-biased diffusion is influenced by a "Component Dominance" mechanism. Inspired by the mentioned mechanisms, a practical AvgS-kMC method is proposed for conveniently and swiftly determining interstitial-mediated diffusivity by only relying on the mean energy barriers of migration patterns. Combining the AvgS-kMC with the differential evolutionary algorithm, an inverse design strategy for optimizing sluggish diffusion properties is applied to emphasize the crucial role of favorable migration patterns.Comment: 30 pages,9 figure

Exploration of the Regulatory Mechanism of Secondary Metabolism by Comparative Transcriptomics in Aspergillus flavus

Mycotoxins cause a huge threaten to agriculture, food safety, and human and animal life. Among them, aflatoxins (AFs) have always been considered the most potent carcinogens, and filamentous fungi from Aspergillus genus are their major producers, especially A. flavus. Although the biosynthesis path of these chemicals had been well-identified, the regulatory mechanisms controlling expression of AF gene cluster were poorly understood. In this report, genome-wide transcriptome profiles of A. flavus from AF conducing [yeast sucrose media (YES)] and non-conducing [yeast peptone media (YEP)] conditions were compared by using deep RNA sequencing (RNA-seq), and the results revealed that AF biosynthesis pathway and biosynthesis of amino acids were significantly upregulated in YES vs. YEP. Further, a novel LaeA-like methyltransferase AFLA_121330 (Lael1) was identified for the first time, to play a specific role in the regulation of AF biosynthesis. Contrary to LaeA, which gene deletion reduced the level, lael1 deletion resulted in a significant increase in AF production. Further, co-expression network analysis revealed that mitochondrial pyruvate transport and signal peptide processing were potentially involved in AF synthesis for the first time, as well as biological processes of ribosome, branched-chain amino acid biosynthetic process and translation were co-regulated by AfRafA and AfStuA. To sum up, our analyses could provide novel insights into the molecular mechanism for controlling the AF and other secondary metabolite synthesis, adding novel targets for plant breeding and making fungicides

ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease

Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms for detecting multidimensional AD digital biomarkers in natural living environments. ADMarker features a novel three-stage multi-modal federated learning architecture that can accurately detect digital biomarkers in a privacy-preserving manner. Our approach collectively addresses several major real-world challenges, such as limited data labels, data heterogeneity, and limited computing resources. We built a compact multi-modality hardware system and deployed it in a four-week clinical trial involving 91 elderly participants. The results indicate that ADMarker can accurately detect a comprehensive set of digital biomarkers with up to 93.8% accuracy and identify early AD with an average of 88.9% accuracy. ADMarker offers a new platform that can allow AD clinicians to characterize and track the complex correlation between multidimensional interpretable digital biomarkers, demographic factors of patients, and AD diagnosis in a longitudinal manner

Impact of meteorological factors on the COVID-19 transmission: A multicity study in China

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID- 19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below0 °C, 12 cities had average AHbelow4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition,we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

An Efficient and Scalable Byzantine Fault-Tolerant Consensus Mechanism Based on Credit Scoring and Aggregated Signatures

Practical Byzantine Fault Tolerance (PBFT), a classic consensus algorithm in blockchain technology, is extensively used in consortium blockchain networks. However, it is challenged by issues such as low consensus efficiency, poor scalability, inability to guarantee throughput with large-scale node access, and complex communication processes. To solve these problems, this paper proposes an improved PBFT consensus mechanism based on credit scoring and aggregated signatures, i.e., the CA-PBFT algorithm. First, the algorithm designs the node credit scoring mechanism, adds the coordination node in the original algorithm model, stipulates the node state and functional limitations, and realizes the dynamic joining and exiting of the nodes, to solve the low efficiency of the PBFT algorithm during the consensus process and the problem of not supporting the dynamic joining and exiting of the nodes; at the same time, the signature scheme based on the BLS aggregated signature is designed, which reduces the length of the signature and simplifies the signing process, to solve the problem of the node’s signature taking up too much space during the consensus process, which affects the efficiency of the signature validation as well as the efficiency of the signature construction. Experimental results show that this consensus mechanism enables an efficient, secure, and scalable consensus process with low resource and computational costs