A bibliometric analysis and visualization of literature on non-fasting lipid research from 2012 to 2022

BackgroundNon-fasting lipid assessment can help predict cardiovascular disease risks and is linked to multiple diseases, particularly diabetes. The significance of non-fasting lipid levels in routine screening and postprandial lipid tests for potential dyslipidemia has not been conclusively determined. Various new lipid-lowering strategies have been developed to improve non-fasting dyslipidemia. Therefore, analysis of scientific outputs over the past decade is essential to reveal trends, hotspots, and frontier areas for future research in this field.MethodsThe Science Citation Index Expanded in the Web of Science Core Collection database was searched for publications related to non-fasting lipid research from 2012 to 2022. The regional distributions, authors, disciplines, journals, references, and keywords of the studies were analyzed using the bibliometric software VOSviewer and CiteSpace.ResultsA total of 4160 articles and reviews that met the inclusion criteria were included in this study. The output trend was established to be stable and the number of citation indices has been persistently increasing. A total of 104 countries/regions, 4668 organizations, and 20782 authors were involved in this research area. In terms of country, the United States had the largest number of publications (979). The University of Copenhagen was the most productive institution, publishing 148 papers. Professor Børge G Nordestgaard has made the most significant contribution to this field. Nutrients was the most productive journal while the American Journal of Clinical Nutrition was the highest co-cited journal. Analysis of co-cited references indicated that lipid-lowering strategies, statin therapy, high-fat meals, insulin resistance, physical exercise, and fructose were hotspots. Analysis of co-cited keywords revealed that apolipoprotein B, especially apolipoprotein B48, is becoming a key research focus. The keywords “gut microbiota” and “meal timing” were the most extensively studied.ConclusionThe causal relationship between non-fasting dyslipidemia and diseases is currently being explored and the standards for non-fasting or postprandial lipid assessment are continuously being updated. Among the hotspots, lipid-lowering strategies are a potential research direction. Apolipoprotein B48, gut microbiota, and chrononutrition are the research frontiers. This initial bibliometric analysis of non-fasting lipids will enable researchers to monitor swift transformations and recognize novel concepts for upcoming research

Longquan celadon: a quantified archaeological analysis of a pan-Indian Ocean industry of the 12th to 15th centuries

This paper examines the Longquan celadon industry, located in Zhejiang province in China, which flourished mainly between the Southern Song and early Ming dynasties (12th to 15th century). The products of this industry are found on archaeological sites from across China and the Indian Ocean. This paper attempts a quantified analysis of the development of the industry based on archaeological data, focussing on four aspects: production, domestic consumption, overseas consumption and, to a lesser degree, workshop organisation. Although much of the data is still, in many ways, problematic, and many of the conclusions drawn are necessarily tentative, it is possible to demonstrate the value and timeliness of the approach by charting the overall development of this industry and by arguing that the close integration of the four aspects examined indicates that the Longquan celadon industry was an industry of considerable economic significance across much of the Indian Ocean

Meta-Analysis: Overweight, Obesity, and Parkinson's Disease

Objective. Parkinson's disease (PD) is a severe neurological disease and its risk factors remain largely unknown. A meta-analysis was carried out to investigate the relationship of overweight and obesity with PD. Methods. We used PubMed, EMBASE, and the Chinese National Knowledge Infrastructure (CNKI) databases to identify studies of associations between overweight/obesity and PD. Overweight, obesity, and PD were used as keywords, and published works were retrieved until September 30, 2013. The extracted data were classified (BMI≥30,25≤BMI<30,  and BMI<25) according to BMI values and analyzed using RevMan5.2 and Stata11.0. Results. Four cohort studies and three case-control studies were used to evaluate the association between overweight/obesity and PD, including 2857 PD patients and 5, 683, 939 cases of non-PD controls. There was a statistically significant difference between 25≤BMI<30  and BMI<25 in the cohort study (RR=1.17, 95% CI, 1.03–1.32,  P=0.03), but there was no difference between BMI≥30  and BMI<25 or BMI≥30  and 25≤BMI<30, where the respective RR was 1.16 and 0.84; the respective 95% CI was 0.67–2.01 and 0.61–1.15, respectively, and the P values were 0.60 and 0.28, respectively. Case-control studies showed that there was no statistical difference between any two groups. Conclusion. Meta-analysis showed that overweight might be a potential risk factor of PD. Demonstration of a causal role of overweight/obesity in PD development could have important therapeutic implications

On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks

Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks. These are typically not compared nor discussed in the literature due to a lack of multi-modal datasets. Texture-less regions are problematic for structure from motion and stereo, reflective material poses issues for active sensing, and distances for translucent objects are intricate to measure with existing hardware. Training on inaccurate or corrupt data induces model bias and hampers generalisation capabilities. These effects remain unnoticed if the sensor measurement is considered as ground truth during the evaluation. This paper investigates the effect of sensor errors for the dense 3D vision tasks of depth estimation and reconstruction. We rigorously show the significant impact of sensor characteristics on the learned predictions and notice generalisation issues arising from various technologies in everyday household environments. For evaluation, we introduce a carefully designed dataset\footnote{dataset available at https://github.com/Junggy/HAMMER-dataset} comprising measurements from commodity sensors, namely D-ToF, I-ToF, passive/active stereo, and monocular RGB+P. Our study quantifies the considerable sensor noise impact and paves the way to improved dense vision estimates and targeted data fusion.Comment: Accepted at CVPR 2023, Main Paper + Supp. Mat. arXiv admin note: substantial text overlap with arXiv:2205.0456

Comparing the effectiveness of long-term use of daily and weekly glucagon-like peptide-1 receptor agonists treatments in patients with nonalcoholic fatty liver disease and type 2 diabetes mellitus: a network meta-analysis

ObjectiveIn the present network meta-analysis (NMA), we aimed to compare the effectiveness of daily and weekly treatment with glucagon-like peptide-1 receptor agonists for patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM).MethodWe used Stata 17.0 for the NMA. Eligible Randomized controlled trials (RCTs) were searched in PubMed, Cochrane, and Embase databases until December 2022. Two researchers independently screened the available studies. The Cochrane Risk of Bias tool was used to assess the risk of bias in the included studies. We used GRADEprofiler (version3.6) to analyze the evidence certainty. Primary outcomes such as liver fat content (LFC), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels, as well as secondary outcomes such as γ-glutamyltransferase (γGGT) and body weight, were evaluated. Then, each intervention was ranked by the surface under the cumulative ranking curve (SUCRA). As a supplement, we drew forest plots of subgroup using RevMan (version 5.4).ResultsFourteen RCTs involving 1666 participants were included in the present study. The NMA results showed that exenatide (bid) was the best treatment for improving LFC compared with other agents, liraglutide, dulaglutide, semaglutide (qw) and placebo), and the SUCRA values were 66.8%. Among five interventions (except exenatide (bid) and semaglutide (qw)) evaluated for AST outcome, and six interventions (except exenatide (bid)) evaluated for ALT outcome, semaglutide (qd) was the most effective drug (SUCRA (AST) = 100%, SUCRA (ALT) = 95.6%). The result of LFC in daily group was MD = -3.66, 95% CI [-5.56, -1.76] and in weekly GLP-1RAs group, it was MD = -3.51, 95% CI [-4, -3.02]. As to AST and ALT, the results in daily group versus weekly group were AST: MD = -7.45, 95% CI [-14.57, -0.32] versus MD= -0.58, 95% CI [-3.18, 2.01] and ALT: MD = -11.12, 95% CI [-24.18, 1.95] versus MD = -5.62, 95% CI [-15.25, 4]. The quality of evidence was assessed as moderate or low.ConclusionThe daily GLP-1RAs may be more effective in primary outcomes. And the daily semaglutide may be the most effective treatment for NAFLD and T2DM among the six interventions

Inter-comparison of wind measurements in the atmospheric boundary layer with Aeolus and a ground-based coherent Doppler lidar network over China

After the successful launch of Aeolus which is the first spaceborne wind lidar developed by the European Space Agency (ESA) on 22 August 2018, we deployed several ground-based coherent Doppler wind lidars (CDLs) to verify the wind observations from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations over China, the Rayleigh-clear and Mie-cloudy horizontal-line-of-sight (HLOS) wind velocities from Aeolus in the atmospheric boundary layer are compared with that from CDLs

Integrated Photonics for NASA Applications

No abstract availabl

Depolarization Ratio Profiles Calibration and Observations of Aerosol and Cloud in the Tibetan Plateau Based on Polarization Raman Lidar

A brief description of the Water vapor, Cloud and Aerosol Lidar (WACAL) system is provided. To calibrate the volume linear depolarization ratio, the concept of “ Δ 90 ° -calibration” is applied in this study. This effective and accurate calibration method is adjusted according to the design of WACAL. Error calculations and analysis of the gain ratio, calibrated volume linear depolarization ratio and particle linear depolarization ratio are provided as well. In this method, the influences of the gain ratio, the rotation angle of the plane of polarization and the polarizing beam splitter are discussed in depth. Two groups of measurements with half wave plate (HWP) at angles of (0 ° , 45 ° ) and (22.5 ° , −22.5 ° ) are operated to calibrate the volume linear depolarization ratio. Then, the particle linear depolarization ratios measured by WACAL and CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization) during the simultaneous observations were compared. Good agreements are found. The calibration method was applied in the third Tibetan Plateau Experiment of Atmospheric Sciences (TIPEX III) in 2013 and 2014 in China. Vertical profiles of the particle depolarization ratio of clouds and aerosol in the Tibetan Plateau were measured with WACAL in Litang (30.03° N, 100.28° E, 3949 m above sea level (a.s.l.)) in 2013 and Naqu (31.48° N, 92.06° E, 4508 m a.s.l.) in 2014. Then an analysis on the polarizing properties of the aerosol, clouds and cirrus over the Tibetan Plateau is provided. The particle depolarization ratio of cirrus clouds varies from 0.36 to 0.52, with a mean value of 0.44 ± 0.04. Cirrus clouds occurred between 5.2 and 12 km above ground level (a.g.l.). The cloud thickness ranges from 0.12 to 2.55 km with a mean thickness of 1.22 ± 0.70 km. It is found that the particle depolarization ratio of cirrus clouds become larger as the height increases. However, the increase rate of the particle depolarization ratio becomes smaller as the height increases

Statistics of optical and geometrical properties of cirrus cloud over tibetan plateau measured by lidar and radiosonde

Cirrus clouds affect the energy budget and hydrological cycle of the earth’s atmosphere. The Tibetan Plateau (TP) plays a significant role in the global and regional climate. Optical and geometrical properties of cirrus clouds in the TP were measured in July-August 2014 by lidar and radiosonde. The statistics and temperature dependences of the corresponding properties are analyzed. The cirrus cloud formations are discussed with respect to temperature deviation and dynamic processes