bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new construction algorithm of the digital economy innovation system
Authors: Zhai Zhengang , Wu Nannan , Zhu Yunya , Gao Bingtao , Pan Zhiyuan 
Published: November 2020

Abstract
To effectively promote the development of digital economy, we have proposed a new construct algorithm of digital economy innovation system. It mainly researches four indicators: innovation subject, innovation resources, innovation efficiency and innovation environment. The quality synthesis index of digital economy development in recent years is calculated through the entropy method. To further analyse the main factors affecting the development quality, the grey relation analysis method is adopted. Besides, the grey prediction model is established to predict the future development trend of digital economy. Based on the data collected from Jiaxing Statistics Bureau from 2010 to 2018, we find that its overall development is growing year by year, in which the innovation efficiency contributes the most, and it is closely related to the innovation resources and environment, but there is still an uneven development among the indicators. The research is conducive to promoting the development of the digital economy and helping to build a modern industrial system for the digital economy.
Research on observation data compression of hydraulic engineering based on swinging door trending algorithm
Authors: Liu Lihuan , Ceng Jiang , Gu Chunhui 
Published: November 2020

Abstract
With the wide application of big data technology, there is a geometric series increase of the real-time data collection of water conservancy engineering, which causes a large number of storage units and memory. In order to make the huge amount of data easy to collect and process, an improved Swinging Door Trending algorithm is proposed to compress the data of water conservancy project based on the deep research of data compression algorithm. This work firstly analyzed the collected abnormal points, which identified and processed the points in time to realize the timely alarm of abnormal conditions according to the characteristics of water conservancy engineering data and acquisition requirements; then discussed the dynamic adjustment of tolerance, which is carried out according to the fluctuating state of water conservancy engineering data to store less real-time data; and finally put forward that the improved SDT algorithm has higher compression ratio and better compression efficiency than the traditional SDT method does by experiments.
An intelligent diversion method for tourists in scenic spots based on behavioral characteristics
Authors: Li Wenqing 
Published: November 2020

Abstract
This paper focused on the problem of time-space diversion and navigation of tourists in scenic spots. Through the analysis and research on the three major behavior characteristics of tourists in scenic spots, namely, the characteristics of recreation direction, the characteristics of recreation speed and the characteristics of recreation time, a method of real-time diversion with minimum cost is proposed, and an intelligent diversion model based on “behavior characteristics” is constructed Guilin Qixing scenic spot is used as an example for analysis and test. The test results show that the intelligent diversion model can effectively guide tourists to the scenic spots with the shortest waiting time and solve the problem of uneven load on each scenic spot. Through the scientific diversion design in time and space, it can not only improve the satisfaction of tourists, but also help the scenic spot personnel to grasp the use of resources in the scenic spot at any time, improve the quality of normalized management of scenic spots, and provide a theoretical and practical basis for the further development of smart Tourism in major scenic spots.
Design of motor state monitoring system based on cloud
Authors: Jia Weiwei , Li Meifeng , Wang Pengwei 
Published: November 2020

Abstract
Most of the intelligent motor monitoring protectors on the market can only carry out local monitoring, but can’t achieve cloud data monitoring, such as no remote data query, no remote control, limited data storage, etc. This article was based on a variety of sensor module and cellular data communication module to form a complete monitoring system, the clouds could accurately and quickly detect the voltage, current, rotate speed and temperature of the motor, and upload data to the cloud platform, to realize remote data query and monitoring, the system was simple in structure, measurement accuracy, data analysis, remote monitoring, etc.
Key technologies of data security protection system for power grid
Authors: Zhang Yu , Zhao Xichao 
Published: November 2020

Abstract
The extensive application of a large number of intelligent terminals and advanced communication technologies in the smart grid has greatly increased the pathways in which various sensitive business data are destroyed and leaked out. Existing data security protection methods relying mainly on encryption and access control cannot meet the requirements of data security protection in all aspects of the smart grid. Firstly, this paper presents data security protection system management platform architecture for smart grid from the aspects of data classification, data label management, policy management and authority management. On this basis, the data protection system for smart grid introduces the functional modules and flowcharts of the data security protection system for terminals and networks in detail. In the future, the data security protection system can be applied in generation, transmission, substation, power distribution and electricity consumption of power system.
Network completion via deep metric learning
Authors: Wei Qiang 
Published: November 2020

Abstract
Completing networks is often a necessary step when dealing with problems arising from applications in incomplete network data mining. This paper investigates the network completion problem with node attributes. We proposed a new method called DeepMetricNC by exploiting the correlation between node attributes and the underlying network structure. In DeepMetricNC, the correlation is modeled as a nonlinear mapping from node attributes to the probability of edge existence. To obtain the mapping, deep metric learning is applied with batch training and random negative sampling. DeepMetricNC has linear training time complexity and can adapt to large-scale network completion tasks. Experiments of real networks show that DeepMetricNC completes network structures better than other methods, and is more suitable when the portion of the observed part is small.
Research and practice of software protection based on virtual shell technology
Authors: Zhang Long 
Published: November 2020

Abstract
Through software decompilation technology, decompiling software can obtain pseudocode of the program source code, causing more and more events of core technology leakage or threats to software intellectual property rights, especially, the proliferation of pirated software. Aiming at the problem of how to effectively protect the software, this article implements a virtual shell packer with the virtual shell technology based on the QT5 framework as the front-end page frame and the assembly language to write the interpreter. Based on this packer, the code of protected software would be decompiled into logically chaotic code in order to increase the difficulty of cracking. Experiments show that this technology can effectively prevent the original pseudo-code from being restored through decompilation. So the software products are effectively protected.
Target recognition algorithm for compound scanning imaging based on fuzzy theory
Authors: Guo Jiachong , Liu Xing , Cui Silin 
Published: November 2020

Abstract
In order to solve the problem of low recognition rate and poor anti-interference ability of single-mode lidar, a multi-element linear array laser/infrared composite detection device is used to realize scanning images. A target recognition model based on associated information is proposed. The proposed method performs feature extraction and fusion on the top three-dimensional contour of the target and the top infrared radiation information, and comparing with the standard model parameter library. A target recognition algorithm based on fuzzy comprehensive evaluation method is proposed, and three sets of recognition probabilities are obtained. The three types of sub-recognition results use fuzzy theory for decision fusion to obtain the final recognition results. The simulation results show that the recognition probability of the composite detection target is greatly improved compared with the single mode recognition method.
Clinical Utility of Targeted Next-Generation Sequencing in the Evaluation of Low-Grade Lymphoproliferative Disorders
Authors: Jajosky Audrey N , Havens Nathaniel P , Sadri Navid , Oduro Kwadwo A , Moore Erika M , Beck Rose C , Meyerson Howard J 
Published: November 2020

AbstractObjectivesWe investigated the usefulness of a custom-designed 31-gene next-generation sequencing (NGS) panel implemented on a routine basis for the evaluation of low-grade lymphoproliferative disorders (LPDs).MethodsIn total, 147 blood, bone marrow, and tissue specimens were sequenced, including 81% B-cell, 15% T-cell, and 3% natural killer (NK)–cell neoplasms.ResultsOf the cases, 92 (63%) of 147 displayed at least one pathogenic variant while 41 (28%) of 147 had two or more. Low mutation rates were noted in monoclonal B-cell lymphocytoses and samples with small T- and NK-cell clones of uncertain significance. Pathogenic molecular variants were described in specific disorders and classified according to their diagnostic, prognostic, and potential therapeutic value. Diagnostically, in addition to confirming the diagnosis of 15 of 15 lymphoplasmacytic lymphomas, 10 of 12 T large granular lymphocytic leukemias, and 2 of 2 hairy cell leukemias (HCLs), the panel helped resolve the diagnosis of 10 (62.5%) of 16 challenging cases lacking a specified diagnosis based on standard morphology, phenotype, and genetic analysis.ConclusionsOverall, implementation of this targeted lymphoid NGS panel as part of regular hematopathology practice was found to be a beneficial adjunct in the evaluation of low-grade LPDs.
Resting Heart Rate as a Cardiovascular Risk Factor in Hypertensive Patients: An Update
Authors: Palatini Paolo 
Published: November 2020

Abstract
A large body of evidence has shown that resting heart rate (RHR) holds important prognostic information in several clinical conditions. In the majority of the general population studies, a graded association between RHR and mortality from all causes, cardiovascular (CV) disease, ischemic heart disease, and stroke has been observed. These associations appeared even stronger and more consistent in hypertensive patients. Studies performed with 24-hour ambulatory recording have shown that an elevated nighttime heart rate may confer an additional risk on top of office RHR. The mechanisms by which tachycardia alone or in association with sympathetic overactivity induces CV damage are well understood. Fast RHR is a strong predictor of future hypertension, metabolic disturbances, obesity, and diabetes. Several experimental lines of research point to high RHR as a main risk factor for the development of atherosclerosis, large artery stiffness, and CV disease. Elevated RHR is a common feature in patients with hypertension. Thus, there is a large segment of the hypertensive population that would benefit from a treatment able to decrease RHR. Improvement of unhealthy lifestyle should be the first goal in the management of the hypertensive patient with elevated RHR. Most clinical guidelines now recommend the use of combination therapies even in the initial treatment of hypertension. Although no results of clinical trials specifically designed to investigate the effect of RHR lowering in human beings without CV diseases are available, in hypertensive patients with high RHR a combination therapy including a cardiac slowing drug at optimized dose seems a sensible strategy.
Tachycardia can be considered both as a marker of sympathetic overactivity and as a risk factor for cardiovascular events. In this sketch, the main cardiovascular and metabolic effects of increased sympathetic tone underlying high heart rate are shown. The link between tachycardia and cardiovascular events can be explained also by the direct hemodynamic action of heart rate on the arteries and the left ventricular (LV) wall.
Seed germination in Narcissus yepesii (Amaryllidaceae): clinal variation in the morphophysiological dormancy levels
Authors: Copete Elena , Copete Miguel A , Ferrandis Pablo , Herranz José M 
Published: November 2020

Abstract
Seed dormancy classes determine both population and species-level processes which can be crucial in the life cycle of many plants. However, there are no studies of a dormancy cline between levels of morphophysiological dormancy (MPD). We aimed to determine the class of seed dormancy of Narcissus yepesii exhibits in order to explore links between different dormancy levels, previously characterized in two closely related phylogenetic congeners, N. alcaracensis and N. longispathus. Experiments were carried out under both near-natural temperature and controlled laboratory conditions. The parameters calculated were mean embryo length, radicle and shoot emergence percentages. The effects of different periods of storage; and different periods with or without GA3 of warm, cold or warm plus cold were analysed. The Narcissus populations from the Baetic System of mountain ranges in south-eastern Spain show clinal variation in a northeast–southwest gradient from intermediate to non-deep complex MPD, through the coexistence of intermediate and non-deep complex MPD in N. yepesii (21 % and 74 %, respectively). In addition, 54 % of stored seeds were able to show both levels of MPD. Narcissus yepesii occupies an intermediate position between N. alcaracensis and N. longispathus in the geographical distribution and in the clinal germination ranges. It strongly suggests an evolutionary gradient, which connects the intermediate complex MPD with the non-deep complex MPD in southern Iberian daffodils. This is the first study showing a gradient in the evolution between levels of MPD. Our results demonstrate a cline in these levels in response to both an environmental gradient and genetic differences.
Granzyme B Is a Biomarker for Suspicion of Malignant Seromas Around Breast Implants
Authors: Kadin Marshall E , Morgan John , Xu Haiying , Glicksman Caroline , Sieber David , Adams William P , McGuire Pat , Clemens Mark W , Thakur Archana , Lum Lawrence G 
Published: November 2020

Abstract

Background
Granzyme B (GrB) is a serine protease secreted, along with pore-forming perforin, by cytotoxic lymphocytes to mediate apoptosis in target cells. GrB has been detected in tumor cells associated with systemic and breast implant–associated anaplastic large cell lymphoma (BIA-ALCL) but its potential use for detection of early BIA-ALCL has not been fully investigated.

Objectives
Prompted by the increased incidence of BIA-ALCL, the aim of this study was to assess GrB as a new biomarker to detect early disease in malignant seromas and to better understand the nature of the neoplastic cell.

Methods
A Human XL Cytokine Discovery Magnetic Luminex 45-plex Fixed Panel Performance Assay was used to compare cytokine levels in cell culture supernatants of BIA-ALCL and other T-cell lymphomas, as well as malignant and benign seromas surrounding breast implants. Immunohistochemistry was employed to localize GrB to cells in seromas and capsular infiltrates.

Results
Differences in GrB concentrations between malignant and benign seromas were significant (P &lt; 0.001). GrB was found in and around apoptotic tumor cells, suggesting that the protease may be involved in tumor cell death.

Conclusions
GrB is a useful marker for early detection of malignant seromas and to identify tumor cells in seromas and capsular infiltrates. Because there is an overlap between the lowest concentrations of soluble GrB in malignant seromas and the highest concentrations of GrB in benign seromas, it is recommended that GrB be used only as part of a panel of biomarkers for the screening and early detection of BIA-ALCL.

Level of Evidence: 5
Transcriptomic profiling of fetal membranes of mice deficient in biglycan and decorin as a model of preterm birth†
Authors: Pantham Priyadarshini , Armstrong Don L , Bodnariuc Jonathan , Haupt Owen , Johnson Amy Wagoner , Underhill Lori , Iozzo Renato V , Lechner Beatrice E , Wildman Derek E 
Published: November 2020

AbstractApproximately, 25% of all preterm births are due to preterm premature rupture of membranes. Mice deficient in proteoglycans biglycan (Bgn) and decorin (Dcn) display abnormal fetal membranes and increased incidence of preterm birth. We conducted RNA-Seq to profile fetal membranes and identify molecular pathways that may lead to preterm birth in double knockout (DKO) mice (Bgn−/−; Dcn−/−) compared to wild-type (WT) at two different gestational stages, E12 and E18 (n = 3 in each group). 3264 transcripts were differentially regulated in E18 DKO vs. WT fetal membranes, and 96 transcripts differentially regulated in E12 DKO vs. WT fetal membranes (FDR &lt; 0.05, log 2 FC ≥ 1). Differentially regulated transcripts in E18 DKO fetal membranes were significantly enriched for genes involved in cell cycle regulation, extracellular matrix–receptor interaction, and the complement cascade. Fifty transcripts involved in the cell cycle were altered in E18 DKO fetal membranes (40↓, 10↑, FDR &lt; 0.05), including p21 and p57 (↑), and Tgfb2, Smad3, CycA, Cdk1, and Cdk2(↓). Thirty-one transcripts involved in the complement cascade were altered (11↓, 20↑, FDR &lt; 0.05) in E18 DKO fetal membranes, including C1q, C2, and C3 (↑). Differentially expressed genes in the top three molecular pathways (1) showed evidence of negative or purifying selection, and (2) were significantly enriched (Z-score &gt; 10) for transcription factor binding sites for Nr2f1 at E18. We propose that in DKO mice, cell cycle arrest results in lack of cell proliferation in fetal membranes, inability to contain the growing fetus, and preterm birth.
A Nationwide Outbreak of Invasive Pneumococcal Disease in Israel Caused by Streptococcus pneumoniae Serotype 2
Authors: Dagan Ron , Ben-Shimol Shalom , Benisty Rachel , Regev-Yochay Gili , Lo Stephanie W , Bentley Stephen D , Hawkins Paulina A , McGee Lesley , Ron Merav , Givon-Lavi Noga , Valinsky Lea , Rokney Assaf 
Published: November 2020

Abstract

Background
Invasive pneumococcal disease (IPD) caused by Streptococcus pneumoniae serotype 2 (Sp2) is infrequent. Large-scale outbreaks were not been reported following pneumococcal conjugate vaccine (PCV) implementation. We describe a Sp2 IPD outbreak in Israel, in the PCV13 era, with focus on Sp2 population structure and evolutionary dynamics.

Methods
The data were derived from a population-based, nationwide active surveillance of IPD since 2009. PCV7/PCV13 vaccines were introduced in July 2009 and November 2010, respectively. Sp2 isolates were tested for antimicrobial susceptibility, multilocus sequence typing, and whole-genome sequencing (WGS) analysis.

Results
Overall, 170 Sp2 IPD cases were identified during 2009–2019; Sp2 increased in 2015 and caused 6% of IPD during 2015–2019, a 7-fold increase compared with 2009–2014. The outbreak was caused by a previously unreported molecular type (ST-13578), initially observed in Israel in 2014. This clone caused 88% of Sp2 during 2015–2019. ST-13578 is a single-locus variant of ST-1504, previously reported globally including in Israel. WGS analysis confirmed clonality among the ST-13578 population. Single-nucleotide polymorphism–dense regions support a hypothesis that the ST-13578 outbreak clone evolved from ST-1504 by recombination. All tested strains were penicillin-susceptible (minimum inhibitory concentration &lt;0.06 μg/mL). The ST-13578 clone was identified almost exclusively (99%) in the Jewish population and was mainly distributed in 3 of 7 Israeli districts. The outbreak is still ongoing, although it began declining in 2017.

Conclusions
To the best of our knowledge, this is the first widespread Sp2 outbreak since PCV13 introduction worldwide, caused by the emerging ST-13578 clone.
Evaluation of the effect of T regulatory cell depletion and donor BCG vaccination on Mycobacterium tuberculosis H37Ra infection using an in vitro model of human PBMC infection
Authors: Bhavanam Sudha , Rayat Gina R , Keelan Monika , Kunimoto Dennis , Drews Steven J 
Published: November 2020

Abstract
This study evaluated the effect of T regulatory cells (Treg cells) and the impact of BCG vaccination history of donors using an in vitro model of Mycobacterium tuberculosis H37Ra infection of peripheral blood mononuclear cells (PBMCs). PBMCs from donors with or without prior BCG vaccination were depleted of Treg cells (PBMCs-Tregs) or not depleted with Treg cells (PBMCs + Tregs) were infected up to 8 days with Mtb H37Ra. Cell aggregates were smaller in PBMCs-Tregs compared to PBMCs + Tregs at day 8 post-infection. Mtb CFUs were higher in the PBMCs-Tregs compared to PBMCs + Tregs at days 3, 5 and 8. The levels of IL-17, IFN-γ (at days 3 and 5), and TNF-α and IL-6 (at day 3) were lower in PBMCs-Tregs compared to PBMCs + Tregs. In contrast, the levels of IL-10 and IL-4 cytokines were higher at day 3 in PBMCs-Tregs compared to PBMCs + Tregs. BCG vaccination status of donors had no impact on the mycobacterial culture, level of cytokines and immune cell populations. This study shows that depletion of Tregs in human PBMCs infected with Mtb H37Ra in vitro leads to a shift from a Th1 to a Th2 cytokine rich environment that supports the survival of Mtb in this model.
Improvements in the school environment—results of a Swedish school project 2005–2011
Authors: Persson Louise , Hagquist Curt 
Published: November 2020

Summary
To examine whether a public health project to reduce problem behavior in schools and improve the classroom climate, undertaken among eight secondary schools in a municipality in Sweden, was accompanied by favorable changes in the school environment over time. Data were collected from ninth grade students (aged 15–16 years) at three different time points: the year before the project began (2005), during the project (2008) and when the project finished (2011). Changes in the school environment, measured as damage, littering, noise and classroom disorder, were compared between the project municipality and a comparison group of other municipalities in the same county, using multinomial logistic regression analysis. Descriptive comparisons were made between the schools within the project municipality. The school environment improved significantly from 2005 to 2011 in the project municipality compared with the other municipalities. The school environment was improved in all schools within the project municipality. The biggest improvements took place in two schools which systematically worked with one program incorporated into the school schedule. This study demonstrates that it may be possible to improve the school environment by implementing health programs. Further studies based on experimental designs are required in order to confirm the potential and efficiency of school health programs.