scholarly journals The Penetration Analysis of Airborne Ku-Band Radar Versus Satellite Infrared Lidar Based on the Height and Energy Percentiles in the Boreal Forest

2021 ◽  
Vol 13 (9) ◽  
pp. 1650
Author(s):  
Hui Zhou ◽  
Yuwei Chen ◽  
Teemu Hakala ◽  
Ziyi Feng ◽  
Changhui Jiang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Boreal Forest ◽  
Near Infrared ◽  
Infrared Laser ◽  
Airborne Lidar ◽  
Energy Distributions ◽  
Band Frequency ◽  
The Mean ◽  
Mean Square Errors ◽  
Ku Band

The paper investigates the penetration properties of an airborne Ku-band frequency modulated continuous waveform (FMCW) profiling radar named Tomoradar and a satellite near-infrared lidar into the boreal forest of Finland. We achieve the accumulative energy distributions based on the Tomoradar waveforms and the satellite lidar waveforms generated from the high-density airborne lidar data within Tomoradar footprints. By comparing two groups of the height percentiles and energy percentiles derived from the accumulative energy distributions, we evaluate the relationship of penetrations between the Ku-band microwave and near-infrared laser according to the coefficients of the determination (COD), and the root mean square errors (RMSE) of linear regression analyses. The quantitative analysis results demonstrate that the height and energy percentiles derived from Tomoradar waveforms correlate well with those from satellite lidar waveforms with the mean correlation coefficients of more than 0.78 and 0.85. The linear regression models for the height and energy percentile produce excellent fits with the mean CODs of 0.95 and 0.90 and the mean RMSEs of 1.25 m and 0.03, respectively. Less than 15% of height percentiles and 87.54% of the energy percentiles in the sixth stratum near the ground derived from Tomoradar waveforms surpass those from satellite lidar waveforms. Hence, the Ku-band microwave can penetrate deeper into the forest than the near-infrared laser at the same spatial scale. In addition, quadratic fitting models are established to describe the differences of the height percentile (DHP) and the energy percentile (DEP) to expound the canopy height and closure contributions numerically. The facts that the CODs of the DHP and DEP individually are more than 0.96 and 0.89 and the fitting residual histograms approximate to normal distributions reveal the reliabilities of the proposed fitting models. Thus, the penetration analyses are valid for the explorations on the FMCW radar applications and the data fusion of the Ku-band radar and near-infrared lidar in the forest investigations.

Urban energetics applications and Geomatic technologies in a Smart City perspective

2015 ◽  
Vol 6 (1) ◽  
pp. 19-29 ◽  
Author(s):  
G. Bitelli ◽  
P. Conte ◽  
T. Csoknyai ◽  
E. Mandanici
Keyword(s):  
Smart City ◽  
Laser Scanning ◽  
Near Infrared ◽  
Three Dimensional ◽  
Energy Sector ◽  
Primary Objective ◽  
Airborne Lidar ◽  
City Management ◽  
Urban Context ◽  
Research Areas

The management of an urban context in a Smart City perspective requires the development of innovative projects, with new applications in multidisciplinary research areas. They can be related to many aspects of city life and urban management: fuel consumption monitoring, energy efficiency issues, environment, social organization, traffic, urban transformations, etc. Geomatics, the modern discipline of gathering, storing, processing, and delivering digital spatially referenced information, can play a fundamental role in many of these areas, providing new efficient and productive methods for a precise mapping of different phenomena by traditional cartographic representation or by new methods of data visualization and manipulation (e.g. three-dimensional modelling, data fusion, etc.). The technologies involved are based on airborne or satellite remote sensing (in visible, near infrared, thermal bands), laser scanning, digital photogrammetry, satellite positioning and, first of all, appropriate sensor integration (online or offline). The aim of this work is to present and analyse some new opportunities offered by Geomatics technologies for a Smart City management, with a specific interest towards the energy sector related to buildings. Reducing consumption and CO2 emissions is a primary objective to be pursued for a sustainable development and, in this direction, an accurate knowledge of energy consumptions and waste for heating of single houses, blocks or districts is needed. A synoptic information regarding a city or a portion of a city can be acquired through sensors on board of airplanes or satellite platforms, operating in the thermal band. A problem to be investigated at the scale A problem to be investigated at the scale of the whole urban context is the Urban Heat Island (UHI), a phenomenon known and studied in the last decades. UHI is related not only to sensible heat released by anthropic activities, but also to land use variations and evapotranspiration reduction. The availability of thermal satellite sensors is fundamental to carry out multi-temporal studies in order to evaluate the dynamic behaviour of the UHI for a city. Working with a greater detail, districts or single buildings can be analysed by specifically designed airborne surveys. The activity has been recently carried out in the EnergyCity project, developed in the framework of the Central Europe programme established by UE. As demonstrated by the project, such data can be successfully integrated in a GIS storing all relevant data about buildings and energy supply, in order to create a powerful geospatial database for a Decision Support System assisting to reduce energy losses and CO2 emissions. Today, aerial thermal mapping could be furthermore integrated by terrestrial 3D surveys realized with Mobile Mapping Systems through multisensor platforms comprising thermal camera/s, laser scanning, GPS, inertial systems, etc. In this way the product can be a true 3D thermal model with good geometric properties, enlarging the possibilities in respect to conventional qualitative 2D images with simple colour palettes. Finally, some applications in the energy sector could benefit from the availability of a true 3D City Model, where the buildings are carefully described through three-dimensional elements. The processing of airborne LiDAR datasets for automated and semi-automated extraction of 3D buildings can provide such new generation of 3D city models.

scholarly journals Digit Variability in Carotenoid Scores Obtained with the Veggie Meter: A Pilot Study (P02-001-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Velarie Ansu ◽  
Stephanie Dickinson ◽  
Alyce Fly
Keyword(s):  
Indiana University ◽  
Left Hand ◽  
Funding Sources ◽  
Right Hand ◽  
Period Data ◽  
The Mean ◽  
The Right ◽  
Post Hoc ◽  
Main Effects ◽  
Mean Square Errors

Abstract Objectives To determine which digit and hand have the highest and lowest skin carotenoid scores, to compare inter-and-intra-hand variability of digits, and to determine if results are consistent with another subject. Methods Two subjects’ first(F1), second(F2), third(F3) and fifth(F5) digits on both hands were measured for skin carotenoids with a Veggie Meter, for 3 times on each of 18 days over a 37-day period. Data were subjected to ANOVA in a factorial treatment design to determine main effects for hand (2 levels), digits (4), and days (18) along with interactions. Differences between digits were determined by Tukey's post hoc test. Results There were significant hand x digit, hand x day, digit x day, and hand x digit x day interactions and significant simple main effects for hand, digit, and day (all P < 0.001). Mean square errors were 143.67 and 195.62 for subject A and B, respectively, which were smaller than mean squares for all main effects and interactions. The mean scores ± SD for F1, F2, F3, and F5 digits for the right vs left hands for subject A were F1:357.13 ± 45.97 vs 363.74 ± 46.94, F2:403.17 ± 44.77 vs. 353.20 ± 44.13, F3:406.76 ± 43.10 vs. 357.11 ± 45.13, and F5:374.95 ± 53.00 vs. 377.90 ± 47.38. For subject B, the mean scores ± SD for digits for the right vs left hands were F1:294.72 ± 61.63 vs 280.71 ± 52.48, F2:285.85 ± 66.92 vs 252.67 ± 67.56, F3:268.56 ± 57.03 vs 283.22 ± 45.87, and F5:288.18 ± 34.46 vs 307.54 ± 40.04. The digits on the right hand of both subjects had higher carotenoid scores than those on the left hands, even though subjects had different dominant hands. Subject A had higher skin carotenoid scores on the F3 and F2 digits for the right hand and F5 on the left hand. Subject B had higher skin carotenoid scores on F5 (right) and F1 (left) digits. Conclusions The variability due to hand, digit, and day were all greater than that of the 3 replicates within the digit-day for both volunteers. This indicates that data were not completely random across the readings when remeasuring the same finger. Different fingers displayed higher carotenoid scores for each volunteer. There is a need to conduct a larger study with more subjects and a range of skin tones to determine whether the reliability of measurements among digits of both hands is similar across the population. Funding Sources Indiana University.

scholarly journals P170 The validity and utility of the SLE-key® rule-out serological test when applied in a selected cohort of patients with SLE and other connective tissue diseases

Rheumatology ◽  
2021 ◽  
Vol 60 (Supplement_1) ◽  
Author(s):  
Sheilla Achieng ◽  
John A Reynolds ◽  
Ian N Bruce ◽  
Marwan Bukhari
Keyword(s):  
Linear Regression ◽  
Connective Tissue ◽  
Connective Tissue Disease ◽  
Negative Correlation ◽  
Connective Tissue Diseases ◽  
Inflammatory Myositis ◽  
The Mean ◽  
Negative Rule ◽  
Spearman’S Correlation ◽  
Rule Out

Abstract Background/Aims  We aimed to establish the validity of the SLE-key® rule-out test and analyse its utility in distinguishing systemic lupus erythematosus (SLE) from other autoimmune rheumatic connective tissue diseases. Methods  We used data from the Lupus Extended Autoimmune Phenotype (LEAP) study, which included a representative cross-sectional sample of patients with a variety of rheumatic connective tissue diseases, including SLE, mixed connective tissue disease (MCTD), inflammatory myositis, systemic sclerosis, primary Sjögren’s syndrome and undifferentiated connective tissue disease (UCTD). The modified 1997 ACR criteria were used to classify patients with SLE. Banked serum samples were sent to Immune-Array’s CLIA- certified laboratory Veracis (Richmond, VA) for testing. Patients were assigned test scores between 0 and 1 where a score of 0 was considered a negative rule-out test (i.e. SLE cannot be excluded) whilst a score of 1 was assigned for a positive rule-out test (i.e. SLE excluded). Performance measures were used to assess the test’s validity and measures of association determined using linear regression and Spearman’s correlation. Results  Our study included a total of 155 patients of whom 66 had SLE. The mean age in the SLE group was 44.2 years (SD 13.04). 146 patients (94.1%) were female. 84 (54.2%) patients from the entire cohort had ACR SLE scores of ≤ 3 whilst 71 (45.8%) had ACR SLE scores ≥ 4. The mean ACR SLE total score for the SLE patients was 4.85 (SD 1.67), ranging from 2 to 8, with mean disease duration of 12.9 years. The Sensitivity of the SLE-Key® Rule-Out test in diagnosing SLE from other connective tissue diseases was 54.5%, specificity was 44.9%, PPV 42.4% and NPV 57.1 %. 45% of the SLE patients had a positive rule-out test. SLE could not be ruled out in 73% of the MCTD patients whilst 51% of the UCTD patients had a positive Rule-Out test and &gt;85% of the inflammatory myositis patients had a negative rule-out test. ROC analysis generated an AUC of 0.525 illustrating weak class separation capacity. Linear regression established a negative correlation between the SLE-key Rule-Out score and ACR SLE total scores. Spearman’s correlation was run to determine the relationship between ACR SLE total scores and SLE-key rule-out score and showed very weak negative correlation (rs = -0.0815, n = 155, p = 0.313). Conclusion  Our findings demonstrate that when applied in clinical practice in a rheumatology CTD clinic setting, the SLE-key® rule-out test does not accurately distinguish SLE from other CTDs. The development of a robust test that could achieve this would be pivotal. It is however important to highlight that the test was designed to distinguish healthy subjects from SLE patients and not for the purpose of differentiating SLE from other connective tissue diseases. Disclosure  S. Achieng: None. J.A. Reynolds: None. I.N. Bruce: Other; I.N.B is a National Institute for Health Research (NIHR) Senior Investigator and is funded by the NIHR Manchester Biomedical Research Centre. M. Bukhari: None.

scholarly journals Tunable near infrared laser

2021 ◽  
Vol 1822 (1) ◽  
pp. 012016
Author(s):  
A.G. Putilov ◽  
A.A. Antipov ◽  
A.E. Shepelev ◽  
S.M. Arakelian
Keyword(s):  
Near Infrared ◽  
Infrared Laser

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

scholarly journals The Relationship between Inflammation Markers (CRP, IL-6, sCD40L) and Colorectal Cancer Stage, Grade, Size and Location

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1382
Author(s):  
Olga Martyna Koper-Lenkiewicz ◽  
Violetta Dymicka-Piekarska ◽  
Anna Justyna Milewska ◽  
Justyna Zińczuk ◽  
Joanna Kamińska
Keyword(s):  
Colorectal Cancer ◽  
Linear Regression ◽  
Tumor Size ◽  
Distal Colon ◽  
Proximal Colon ◽  
Model Parameters ◽  
Grade Group ◽  
Who Grade ◽  
The Mean ◽  
Mean Concentration

The aim of the study was the evaluation whether in primary colorectal cancer (CRC) patients (n = 55): age, sex, TNM classification results, WHO grade, tumor location (proximal colon, distal colon, rectum), tumor size, platelet count (PLT), mean platelet volume (MPV), mean platelet component (MCP), levels of carcinoembryonic antigen (CEA), cancer antigen (CA 19-9), as well as soluble lectin adhesion molecules (L-, E-, and P-selectins) may influence circulating inflammatory biomarkers: IL-6, CRP, and sCD40L. We found that CRP concentration evaluation in routine clinical practice may have an advantage as a prognostic biomarker in CRC patients, as this protein the most comprehensively reflects clinicopathological features of the tumor. Univariate linear regression analysis revealed that in CRC patients: (1) with an increase in PLT by 10 × 103/μL, the mean concentration of CRP increases by 3.4%; (2) with an increase in CA 19-9 of 1 U/mL, the mean concentration of CRP increases by 0.7%; (3) with the WHO 2 grade, the mean CRP concentration increases 3.631 times relative to the WHO 1 grade group; (4) with the WHO 3 grade, the mean CRP concentration increases by 4.916 times relative to the WHO 1 grade group; (5) with metastases (T1-4N+M+) the mean CRP concentration increases 4.183 times compared to non-metastatic patients (T1-4N0M0); (6) with a tumor located in the proximal colon, the mean concentration of CRP increases 2.175 times compared to a tumor located in the distal colon; (7) in patients with tumor size > 3 cm, the CRP concentration is about 2 times higher than in patients with tumor size ≤ 3 cm. In the multivariate linear regression model, the variables that influence the mean CRP value in CRC patients included: WHO grade and tumor localization. R2 for the created model equals 0.50, which indicates that this model explains 50% of the variance in the dependent variable. In CRC subjects: (1) with the WHO 2 grade, the mean CRP concentration rises 3.924 times relative to the WHO 1 grade; (2) with the WHO 3 grade, the mean CRP concentration increases 4.721 times in relation to the WHO 1 grade; (3) with a tumor located in the rectum, the mean CRP concentration rises 2.139 times compared to a tumor located in the distal colon; (4) with a tumor located in the proximal colon, the mean concentration of CRP increases 1.998 times compared to the tumor located in the distal colon; if other model parameters are fixed.

scholarly journals 1412. The utility of respiratory viral panel testing for nosocomial fever in the neonatal intensive care unit

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S713-S713
Author(s):  
Carlo Fopiano Palacios ◽  
Eric Lemmon ◽  
James Campbell
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Linear Regression ◽  
Length Of Stay ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Intensive Care ◽  
P Value ◽  
Fisher Exact Test ◽  
The Mean ◽  
Pcr Test

Abstract Background Patients in the neonatal intensive care unit (NICU) often develop fevers during their inpatient stay. Many neonates are empirically started on antibiotics due to their fragile clinical status. We sought to evaluate whether the respiratory viral panel (RVP) PCR test is associated with use of antibiotics in patients who develop a fever in the NICU. Methods We conducted a retrospective chart review on patients admitted to the Level 4 NICU of the University of Maryland Medical Center from November 2015 to June 2018. We included all neonates who developed a fever 48 hours into their admission. We collected demographic information and data on length of stay, fever work-up and diagnostics (including labs, cultures, RVP), and antibiotic use. Descriptive statistics, Fisher exact test, linear regression, and Welch’s ANOVA were performed. Results Among 347 fever episodes, the mean age of neonates was 72.8 ± 21.6 days, and 45.2% were female. Out of 30 total RVP samples analyzed, 2 were positive (6.7%). The most common causes of fever were post-procedural (5.7%), pneumonia (4.8%), urinary tract infection (3.5%), meningitis (2.6%), bacteremia (2.3%), or due to a viral infection (2.0%). Antibiotics were started in 208 patients (60%), while 61 neonates (17.6%) were already on antibiotics. The mean length of antibiotics was 7.5 ± 0.5 days. Neonates were more likely to get started on antibiotics if they had a negative RVP compared to those without a negative RVP (89% vs. 11%, p-value &lt; 0.0001). Patients with a positive RVP had a decreased length of stay compared to those without a positive RVP (30.3 ± 8.7 vs. 96.8 ± 71.3, p-value 0.01). On multivariate linear regression, a positive RVP was not associated with length of stay. Conclusion Neonates with a negative respiratory viral PCR test were more likely to be started on antibiotics for fevers. Respiratory viral PCR testing can be used as a tool to promote antibiotic stewardship in the NICU. Disclosures All Authors: No reported disclosures

scholarly journals Realizing Near‐Infrared Laser Dyes through a Shift in Excited‐State Absorption

2021 ◽  
pp. 2001947
Author(s):  
Reiko Aoki ◽  
Ryutaro Komatsu ◽  
Kenichi Goushi ◽  
Masashi Mamada ◽  
Soo Young Ko ◽  
...  
Keyword(s):  
Excited State ◽  
Near Infrared ◽  
Excited State Absorption ◽  
Infrared Laser ◽  
Laser Dyes
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