Linear Correction Research Articles

Statistical Downscaling of Remote Sensing Precipitation Estimates Using MODIS Cloud Properties Data over Northeastern Greece

The aim of this study is to spatially downscale the daily precipitation data from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG), utilizing cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Cloud optical thickness (COT), cloud effective radius (CER), and cloud water path (CWP) are used to statistically downscale IMERG precipitation estimates from 0.1 to 0.01° spatial resolution, using the Multivariate Linear Regression (MLR) and residual correction methods. The downscaled precipitation estimates were subsequently validated using in situ rain gauge measurements. The residual corrected IMERG downscaled precipitation estimates were found to be more accurate than the downscaled predicted precipitation without the implementation of the residual correction algorithm (up to 37%), with a respective decrease of the Root Mean Square Error (RMSE) (up to 75%), Normalized Root Mean Square Error (NRMSE) (up to 79%), and the Percent Bias (PB) (up to 98%). In addition, the final downscaled product after the MLR method implementation with residual correction was better correlated with the rain gauge observations than the initial IMERG product (up to 20%). Thus, the implementation of the MLR method in conjunction with the residual correction algorithm is an efficient tool for downscaling remote sensing products with a coarse spatial resolution.

New models of d-dimensional black holes without inner horizon and with an integrable singularity

Theoretically, it has been proposed that objects traveling radially along regular black holes (RBHs) would not be destroyed because of finite tidal forces and the absence of a singularity. However, the matter source allows the creation of an inner horizon linked to an unstable de Sitter core due to mass inflation instability. This inner horizon also gives rise to the appearance of a remnant, inhibiting complete evaporation. We introduce here a d-dimensional black hole model with Localized Sources of Matter (LSM), characterized by the absence of an inner horizon and featuring a central integrable singularity instead of an unstable de Sitter core. In our model, any object tracing a radial and timelike world-line would not be crushed by the singularity. This is attributed to finite tidal forces, the extendability of radial geodesics, and the weak nature of the singularity. Our LSM model enables the potential complete evaporation down to r h = 0 without forming a remnant. In higher dimensions, complete evaporation occurs through a phase transition, which could occur at Planck scales and be speculatively driven by the Generalized Uncertainty Principle (GUP). Unlike RBHs, our model satisfies the energy conditions. We demonstrate a linear correction to the conventional area law of entropy, distinct from the RBH's correction. Additionally, we investigate the stability of the solutions through the speed of sound.

Off-energy operation for the Extremely Brilliant Source at the European Synchrotron Radiation Facility

The European Synchrotron Radiation Facility Extremely Brilliant Source (ESRF-EBS) is the first fourth generation 6 GeV storage ring (SR) light source making use of the hybrid multibend achromat lattice, reaching a natural horizontal emittance of 140 pm rad. Further, reducing the horizontal emittance would provide a more brilliant and a higher quality photon source for the EBS users. One way of achieving this is to operate the SR off-energy. The first approach reduces the electron beam energy by −1%, which gives a 121 pm rad natural horizontal emittance. To fulfill operation requirements, the full ring had to be rematched, including both the quadrupoles and the sextupoles in the linear optics correction. The off-energy settings are then tested in the SR in terms of lifetime, injection efficiency, and operability. Published by the American Physical Society 2024

Elevation dependent precipitation changes in historical and future times in the Himalayan Upper Ganga Basin, India

This study examines long-term (1991–2092) precipitation trends in the Upper Ganga Basin (UGB) across multiple elevations, using historical data (1991–2022) and future Coupled Model Intercomparison Project Phase 6 (CMIP6) climate model datasets (2022–2092). By identifying the top five best-fit models from 29 climate model datasets, this study assesses historical patterns and project future changes in the Near-Future-Term (NFT) (2023–2056) and Far-Future-Term (FFT) (2061–2092) under moderate and extreme scenarios. Based on the evaluation of 29 CMIP6 climate models precipitation products, five models namely: BCC-CSM2-MR, CMCC-CM2-SR5, INM-CM5–0, KIOST-ESM, and NESM3 were selected as the best models describing precipitation over UGB and future precipitation of these models were bias corrected using linear scaling bias correction approach. Also it was observed that in the UGB region usually the climate models are much more reliable in capturing the precipitation pattern in lower and mid elevation regions as compared to higher-elevation regions. Further analysis of best five climate models' future precipitation indicates a substantial increase in wet spell occurrences in the south-western part of UGB, while the north-western and central regions are expected to see a rise in dry spell counts, although dry spell increase is insignificant. The mid-elevation range from 2200 to 4050 m which historically receives the most precipitation and is expected to continue experiencing the highest volume of precipitation in the future. The lower elevation range (287–1500 m) has anticipated the most substantial increase in future precipitation. Analysis suggests a future rise in low precipitation events (2.5 mm/day to 10 mm/day) at high elevations (4050 m to 7399 m) and an increase in events exceeding 10 mm/day in mid to low elevations (287 m to 4050 m). Although an increase in low precipitation events is expected across the entire UGB, it is particularly noteworthy that the region between 287 m to 4050 m is likely to experience a greater prevalence of these events. Historically, high elevations witnessed most of the years with over 20 days of annual snowfall. However, future scenarios indicate a prominent shift, predominantly anticipating <20 days per year of snowfall, signifying a significant change in snowfall patterns within the UGB. An analysis of snowfall patterns within the UGB indicates that historically, in the elevation range of 1500 m to 2200 m, some years have experienced 3–7 days of snowfall per year, however, under the SSP245 (NFT) scenario, this is projected to decrease to 2–5 days per year. Conversely, in scenarios SSP245 (FFT), SSP585 (NFT), and SSP585 (FFT), it is anticipated that there will be no snowfall in this elevation range in the future.

Evaluation and Optimization of a Microcavity Plate-Based Human Hepatocyte Spheroid Model for Predicting Clearance of Slowly Metabolized Drug Candidates.

In vitro clearance assays are routinely conducted in drug discovery to predict in vivo clearance, but low metabolic turnover compounds are often difficult to evaluate. Hepatocyte spheroids can be cultured for days, achieving higher drug turnover, but have been hindered by limitations on cell number per well. Corning Elplasia microcavity 96-well microplates enable the culture of 79 hepatocyte spheroids per well. In this study, microcavity spheroid properties (size, hepatocyte function, longevity, culturing techniques) were assessed and optimized for clearance assays, which were then compared with microsomes, hepatocyte suspensions, two-dimensional-plated hepatocytes, and macrowell spheroids cultured as one per well. Higher enzyme activity coupled with greater hepatocyte concentrations in microcavity spheroids enabled measurable turnover of all 17 test compounds, unlike the other models that exhibited less drug turnover. Microcavity spheroids also predicted intrinsic clearance (CLint) and blood clearance (CLb) within threefold for 53% [9/17; average absolute fold error (AAFE), 3.9] and 82% (14/17; AAFE, 2.6) of compounds using a linear regression correction model, respectively. An alternate method incorporating mechanistic modeling that accounts for mass transport (permeability and diffusion) within spheroids demonstrated improved predictivity for CLint (12/17; AAFE, 4.0) and CLb (14/17; AAFE, 2.1) without the need for empirical scaling factors. The estimated fraction of drug metabolized by cytochrome P450 3A4 (fm,CYP3A4) using 3 μM itraconazole was within 25% of observed values for 6 of 8 compounds, with 5 of 8 compounds within 10%. In sum, spheroid cultures in microcavity plates permit the ability to test and predict clearance as well as fm,CYP3A4 of low metabolic turnover compounds and represent a valuable complement to conventional in vitro clearance assays. SIGNIFICANCE STATEMENT: Culturing multiple spheroids in ultralow attachment microcavities permits accurate quantitation of metabolically stable compounds in substrate depletion assays, overcoming limitations with singly cultured spheroids. In turn, this permits robust estimates of intrinsic clearance, which is improved with the consideration of mass transport within the spheroid. Incubations with 3 μM itraconazole enabled assessments of CYP3A4 involvement in hepatic clearance.

Probing the universe's expansion dynamics: The linear correction scenario perspective on dark energy

In this study, we investigate the cosmological evolution of the universe, focusing on the KMMS models in a model-independent approach, particularly the scenario involving linear correction, given by E2(z)=A(z)+β(1+γB(z)), where A(z)=Ωm0(1+z)3 and B(z)=z. By analyzing recent Cosmic Chronometers (CC) and the Pantheon+ samples, we determine the best-fit values of model parameters using a Markov chain Monte Carlo analysis. Our models exhibit unique dynamics, transitioning from super-exponential to exponential expansion, with a significant shift at redshift zt=0.83−0.10+0.11 and present deceleration parameter q0=−0.69−0.17+0.17. The jerk parameter exceeds 1, indicating a faster change in acceleration than predicted by ΛCDM. The energy density parameter is consistent with Planck observations, and the dark sector evolution follows the expected thermal history. The EoS parameter approaches ωde=−1 over time, with a current value of ωde0=−1.06±0.12, aligning with the phantom phase. Our model presents a new dark energy alternative, emphasizing the importance of considering models like KMMS in understanding cosmic evolution.

OSLD nanoDot characterization for carbon radiotherapy dosimetry

Objective. This study characterized optically-stimulated luminescent dosimeter (OSLD) nanoDots for use in a therapeutic carbon beam using the Imaging and Radiation Oncology Core (IROC) framework for remote output verification. Approach. The absorbed dose correction factors for OSLD (fading, linearity, beam quality, angularity, and depletion), as defined by AAPM TG 191, were characterized for carbon beams. For the various correction factors, the effect of linear energy transfer (LET) was examined by characterizing in both a low and high LET setting. Main results. Fading was not statistically different between reference photons and carbon, nor between low and high LET beams; thus, the standard IROC-defined exponential function could be used to characterize fading. Dose linearity was characterized with a linear fit; while low and high LET carbon linearity was different, these differences were small and could be rolled into the uncertainty budget if using a single linearity correction. A linear fit between beam quality and dose-averaged LET was determined. The OSLD response at various angles of incidence was not statistically different, thus a correction factor need not be applied. There was a difference in depletion between low and high LET irradiations in a primary carbon beam, but this difference was small over the standard five readings. The largest uncertainty associated with the use of OSLDs in carbon was because of the k Q correction factor, with an uncertainty of 6.0%. The overall uncertainty budget was 6.3% for standard irradiation conditions. Significance. OSLD nanoDot response was characterized in a therapeutic carbon beam. The uncertainty was larger than for traditional photon applications. These findings enable the use of OSLDs for carbon absorbed dose measurements, but with less accuracy than conventional OSLD audit programs.

Can the phase of SNR oscillations in GNSS-IR be used to estimate sea-level height?

In existing global navigation satellite system-interference reflectometry (GNSS-IR) research, only the frequency of signal-to-noise ratio (SNR) oscillations has been used to estimate sea-level height. However, the characteristic parameters of SNR oscillations are not isolated from each other, and a single feature cannot accurately and comprehensively capture the environmental changes of reflecting surface. Our simulation results show that for the nonlinear least squares (NLS), when there is a certain difference between the fitting frequency and the actual frequency of SNR oscillations, the deviation of the phase solution obtained is approximately linear with the frequency difference. Consequently, a linear phase correction GNSS-IR sea-level estimation method is constructed in this study. This method integrates the Lomb–Scargle periodogram (LSP) and NLS to process SNR oscillations, using the phase obtained from NLS to correct the retrieval error of LSP. Through processing SNR data from four sites for nearly half a year, we verified the stability of the relationship between phase and frequency-based retrieval error at different sites in continuous monitoring, and established the relationship model between the two. Then, utilizing the relationship model acquired at different sites, we estimated the sea-level variations for the next 6 months at each site through joint frequency and phase versus reflector height relationships. Experimental results show that the phases acquired from NLS can effectively correct the retrieval error of LSP. Compared with the traditional method using only frequency, the root mean square error and mean absolute error of the retrieval results obtained from the linear phase correction GNSS-IR sea-level estimation method based on LSP-NLS are both reduced by about 60%. This multi-feature fusion technique introduces a new perspective and technical approach for GNSS-IR sea-level estimations.

Improvements in the Quantification of End-Member Vapor Compositions in Fluid Inclusion Boiling Assemblages and Implications for Metal Transport by Low-Density Fluids

Abstract Under conditions typically found in the Earth’s crust, there is a large pressure-temperature-composition range in the H2O-NaCl system where fluids may separate into a low-salinity vapor end member and a high-salinity liquid end member. However, heterogeneous trapping is common during the formation of fluid inclusions in an immiscible fluid system, violating the fundamental assumption of homogeneous entrapment for fluid inclusion microthermometry. This has profound consequences on the composition of these fluid phases and consequently on the formation of ore deposits from hydrothermal systems. At the same time, minor mixture of the high-salinity liquid phase with the low-salinity vapor phase cannot be distinguished from the end-member vapor-rich fluid inclusions by their bubble sizes. Precise determination of the salinities of vapor-rich fluid inclusions using microthermometry is deterred by the very small proportion of the liquid phase and the limitation of the analytical precision. All this will lead to erroneous compositional data from fluid inclusion analysis. We have quantitively calculated the variations of fluid inclusion properties caused by heterogeneous entrapment during phase separation in the H2O-NaCl system and showed that the salinity, and thereby the element contents and element/Na ratios of the vapor-rich fluid inclusions, is significantly changed in heterogeneously trapped fluid inclusions. The addition of 1 vol % of the high-salinity end member to the low-salinity end member results in a salinity change from 0.99 to 4.4 wt % NaCl equiv at the phase separation condition of 800 bar and 750°C. This will have a significant impact when it comes to determining the concentration of elements transported as chlorine complexes and typically leads to an overestimation of the mass transport capability by the vapor phase. Therefore, every effort should be taken during microthermometry to find and measure the least affected vapor-rich fluid inclusions. Our numerical calculations and synthetic fluid inclusions reveal that there is a linear relationship between the salinity and element contents for fluid inclusions at different extents of heterogeneous entrapment. Therefore, linear correction to the measured lowest vapor salinity can obtain a good approximation of the element contents in the end-member vapor phase.

A Modified Frequency Nonlinear Chirp Scaling Algorithm for High-Speed High-Squint Synthetic Aperture Radar with Curved Trajectory

The imaging of high-speed high-squint synthetic aperture radar (HSHS-SAR), which is mounted on maneuvering platforms with curved trajectory, is a challenging task due to the existence of 3-D acceleration and the azimuth spatial variability of range migration and Doppler parameters. Although existing imaging algorithms based on linear range walk correction (LRWC) and nonlinear chirp scaling (NCS) can reduce the range–azimuth coupling of the frequency spectrum (FS) and the spatial variability of the Doppler parameter to some extent, they become invalid as the squint angle, speed, and resolution increase. Additionally, most of them ignore the effect of acceleration phase calibration (APC) on NCS, which should not be neglected as resolution increases. For these issues, a modified frequency nonlinear chirp scaling (MFNCS) algorithm is proposed in this paper. The proposed MFNCS algorithm mainly includes the following aspects. First, a more accurate approximation of range model (MAARM) is established to improve the accuracy of the instantaneous slant range history. Second, a preprocessing of the proposed algorithm based on the first range compression, LRWC, and a spatial-invariant APC (SIVAPC) is implemented to eliminate most of the effects of high-squint angle and 3-D acceleration on the FS. Third, a spatial-variant APC (SVAPC) is performed to remove azimuth spatial variability introduced by 3-D acceleration, and the range focusing is accomplished by the bulk range cell migration correction (BRCMC) and extended secondary range compression (ESRC). Fourth, the azimuth-dependent characteristics evaluation based on LRWC, SIVAPC, and SVAPC is completed to derive the MFNCS algorithm with fifth-order chirp scaling function for azimuth compression. Consequently, the final image is focused on the range time and azimuth frequency domain. The experimental simulation results verify the effectiveness of the proposed algorithm. With a curved trajectory, HSHS-SAR imaging is carried out at a 50° geometric squint angle and 500 m × 500 m imaging width. The integrated sidelobe ratio and peak sidelobe ratio of the point targets at the scenario edges approach the theoretical values, and the range-azimuth resolution is 1.5 m × 3.0 m.

Evaluation of Patient-Centric Sample Collection Technologies for Pharmacokinetic Assessment of Large and Small Molecules.

Low-volume sampling devices offer the promise of lower discomfort and greater convenience for patients, potentially reducing patient burden and enabling decentralized clinical trials. In this study, we determined whether low-volume sampling devices produce pharmacokinetic (PK) data comparable to conventional venipuncture for a diverse set of monoclonal antibodies (mAbs) and small molecules. We adopted an open-label, non-randomized, parallel-group, single-site study design, with four cohorts of 10 healthy subjects per arm. The study drugs, doses, and routes of administration included: crenezumab (15 mg/kg, intravenous infusion), etrolizumab (210 mg, subcutaneous), GDC-X (oral), and hydroxychloroquine (HCQ, 200 mg, oral). Samples were collected after administration of a single dose of each drug using conventional venipuncture and three low-volume capillary devices: TassoOne Plus for liquid blood, Tasso-M20 for dry blood, both applied to the arm, and Neoteryx Mitra® for dry blood obtained from fingertips. Serum/plasma concentrations from venipuncture and TassoOne Plus samples overlapped and PK parameters were comparable for all drugs, except HCQ. After applying a baseline hematocrit value, the dry blood concentrations and PK parameters for the two monoclonal antibodies were comparable to those obtained from venipuncture. For the two small molecules, two bridging strategies were evaluated for converting dry blood concentrations to equivalent plasma concentrations. A baseline hematocrit correction and/or linear regression-based correction was effective for GDC-X, but not for HCQ. Additionally, the study evaluated the bioanalytical data quality and comparability from the various collection methods, as well as patient preference for the devices.

Correction Control Model of L-Index Based on VSC-OPF and BLS Method

With the advancement of artificial intelligence (AI) technology, the real-time measurement and control technology of power systems has also progressed. This paper proposes a correction control model for L-indexes based on voltage stability constrained optimal power flow (VSC-OPF) and a broad learning system (BLS) (BLS-VSC-OPF). This model aims to quickly assess the system’s voltage stability and accurately correct the operation mode when the voltage stability indexes are out of the security range. Firstly, the BLS is used to predict the L-index and to analyze the voltage stability of the power system. Secondly, the approximate first-order sensitivity of the L-index is calculated by the combination of the BLS and the perturbation method. This method solves the problem of the complex sensitivity derivation process in the modeling process of the VSC-OPF model. Meanwhile, when the L-index exceeds the threshold, the BLS and VSC-OPF models are combined to correct this operation mode. The feasibility of the proposed method is verified by the simulation of IEEE-30, IEEE-118, and 1047 bus systems. Finally, the BLS-VSC-OPF model is compared with the linear programming correction model based on BLS (BLS-LPC). The results show that the BLS-VSC-OPF model provides a better correction and control performance.

Resonant detectors of gravitational wave in the linear and quadratic generalized uncertainty principle framework

In this work, we consider a resonant bar detector of gravitational waves in the generalized uncertainty principle (GUP) framework with linear and quadratic momentum uncertainties. The phonon modes in these detectors vibrate due to the interaction with the incoming gravitational wave. In this uncertainty principle framework, we calculate the resonant frequencies and transition rates induced by the incoming gravitational waves on these detectors. We observe that the energy eigenstates and the eigenvalues get modified by the GUP parameters. We also observe non-vanishing transition probabilities between two adjacent energy levels due to the existence of the linear order momentum correction in the generalized uncertainty relation which was not present in the quadratic GUP analysis (Class Quantum Gravity 37:195006, 2020). We finally obtain bounds on the dimensionless GUP parameters using the form of the transition rates obtained during this analysis.

Characterization of the future northeast monsoon rainfall based on the clustered climate zone under CMIP6 in Peninsular Malaysia

The Northeast monsoon (NEM) exerts a significant influence on the climate system of Peninsular Malaysia (PM) and has profound implications for water resource management, flood control, and disaster preparedness in the region. This study employed CHIRPS rainfall data from 1981 to 2022 at a spatial resolution of 0.25° to generate climate zones. The performance of global climate models (GCMs) in replicating monthly rainfall was evaluated using multiple statistical metrics, with the top-ranked ones being used for the generation of future projection downscaled ensemble models. The NEM months (November, December, January, February, and March) were used as input parameters to form clustered homogeneous groups using the Ward hierarchical method. The optimal number of climate zones was determined using the elbow method, silhouette width values, and spatial evaluation. Ultimately, a 7-cluster solution was chosen due to its consistency and meaningful cluster formation. The zones were categorized into two regions: the West Coast and the East Coast, based on their geographical location and distinctive monthly NEM rainfall patterns. The analysis of the probability distribution function (PDF) showed that rainfall in the West Coast region had a more spread-out pattern with varying amounts, while rainfall in the East Coast region was more concentrated and consistent. The Northeast climate zone received the highest rainfall, attributed to its proximity to the South China Sea, mountainous areas, and the NEM convergence zone. In contrast, the Northwest and Lower Central-West climate zones received the lowest rainfall due to the rain shadow effect, limited moisture availability, and distance from major moisture sources. The CMCC-ESM2, CMCC-CM2-SR5, EC-Earth3, and CanESM5 consistently ranked among the highest performing models. After linear scaling bias correction, validated GCMs showed significant improvements, with improvements in MAE, NRMSE, PBIAS, RSR, NSE, MD, CP, R2, and KGE by 11–45%, 15–47%, 96–100%, 15–47%, 10–79%, 5–37%, 68–113%, 11–73%, and 9–51%, respectively. Analysis of NEM season rainfall patterns across climate zones indicated consistent mid-future increases for the Northwest and Lower Central-West zones (12.4–19.8%) and the Upper Central-West and Southwest zones (0.2–5.4%) across all scenarios. In the far-future, the Southeast zone saw an overall increase in rainfall (4.9–11.4%), while the Central-West zone exhibited mixed results (−4.0 to 5.6%). The results also highlighted spatial variability and the need to consider specific climate zones when assessing the impacts of climate change on the NEM, emphasizing the importance of incorporating these projections into long-term planning and decision-making processes.

On possible traversable wormhole solutions supported by Karmarkar condition in [formula omitted]gravity within the [formula omitted]formalism

In their seminal work, Morris and Thorne (1988) introduced the concept of traversable wormholes (WHs), which are geometric structures serving as bridges to connect two distinct spacetimes or different points within the same spacetime. The properties of these WHs are determined by the choice of the shape function. Extensive research has been conducted in the literature on WHs within modified theories of gravity, considering various types of shape functions. In this paper, we focus on deriving the simplest solutions for traversable WHs within the framework of f(R,T) gravity. Our specific focus lies on the functional form f(R,T)=R+αR2+λT, where R represents the Ricci scalar and T denotes the trace of the energy–momentum tensor. By incorporating quadratic geometric and linear material corrections, we demonstrate that the matter content of WHs can obediently conform to the energy conditions (ECs). This study significantly advances our understanding of WHs within the context of modified gravity. Our findings shed new light on the behavior and properties of WHs, highlighting their compatibility with the f(R,T) gravity framework. By unveiling the ability of WHs to adhere to ECs through the inclusion of geometric and material corrections, we provide groundbreaking insights into these intriguing objects. Overall, our research contributes to the broader field of gravitational physics by presenting a unique perspective on WH modeling. By exploring WHs within the f(R,T) gravity framework and demonstrating their conformity to ECs, we expand our knowledge of these fascinating structures and pave the way for further investigations in this area.

Monetary policy, threshold of profitability and dynamics of private investment in the West African Economic and Monetary Union

This study investigates the interactions between optimal monetary policy, investment profitability thresholds, and private sector investment dynamics within the West African Economic and Monetary Union. Analyzing data from 2000 to 2021, it employs advanced econometric models (linear, asymmetric, and threshold effect dynamic panel error correction models) to provide a nuanced understanding of the investment environment in the union. The findings reveal the confluence of low returns and high borrowing costs for private investment. Notably, this study suggests that simply pursuing an expansionary monetary policy does not offer a sufficient solution. Instead, it proposes a more accommodative stance by the Central Bank, featuring lower policy rates, to alleviate the negative impact of high credit costs on private investment and ultimately stimulate economic activity.

A correction method for mitigating absorbance discrepancies between near-infrared spectrometers through the incorporation of blended carbon-titanium dioxide powder

In near-infrared spectroscopy analysis, ensuring the accurate transfer of models between different instruments relies on maintaining the accuracy of instrument wavelengths and absorbance. To mitigate absorbance drift at different wavelength points, this paper proposes a near-infrared spectroscopy point-by-point quadratic polynomial correction method based on carbon-titanium dioxide powder samples. The method establishes a quadratic polynomial relationship model for the absorbance of each wavelength point between the main instrument and slave instruments. The study utilized two S450 grating-based diffuse reflection near-infrared spectroscopy instruments, with one serving as the main instrument and the other as the slave instrument. The point-by-point quadratic polynomial was employed to correct wheat spectra collected by the slave instruments, and a crude protein content prediction model for wheat was established, comparing it with linear regression correction. After correction, the average Euclidean distance of wheat spectra decreased by 66.71%, from 0.0937 to 0.0321, and the average peak-valley Euclidean distance decreased by 72.28%, from 0.0203 to 0.0056. The standard deviation of the predicted results decreased by 90.69%, from 1.4372 to 0.1338. The correction effect of the method combined with traditional preprocessing methods was superior to using preprocessing methods alone. Overall, the near-infrared spectroscopy point-by-point quadratic polynomial correction method based on carbon-titanium dioxide powder samples significantly reduces spectral differences between different instruments, enhances spectral consistency, and diminishes prediction errors, achieving improved model sharing between instruments.

Automated extraction of tunnel leakage location and area from 3D laser scanning point clouds

Water leakage is one of the common tunnel disease problems. Fast and accurate detection is crucial for timely management of leakage disease. This paper introduces a method for automatically extracting the location and area of tunnel leakage from 3D laser scanning point clouds. The method involves three key steps: segmenting the point cloud data along the tunnel axis based on the width of the tube sheet, correcting the intensity of the point cloud using a linear intensity correction model, and binarizing the point cloud data to extract the leakage area and calculate its area. To evaluate the performance of the proposed methodology, water leakage detection software is prepared based on the method, and tests are carried out in the urban subway tunnels in the leakage disease-producing sections. The results show a detection accuracy of 92 % and an improvement in detection efficiency of 7–8 times. The method proposed can be used to quickly and accurately extract the location and area of water leakage from point cloud data.

Environmental Quality bOX (EQ-OX): A Portable Device Embedding Low-Cost Sensors Tailored for Comprehensive Indoor Environmental Quality Monitoring.

The continuous monitoring of indoor environmental quality (IEQ) plays a crucial role in improving our understanding of the prominent parameters affecting building users' health and perception of their environment. In field studies, indoor environment monitoring often does not go beyond the assessment of air temperature, relative humidity, and CO2 concentration, lacking consideration of other important parameters due to budget constraints and the complexity of multi-dimensional signal analyses. In this paper, we introduce the Environmental Quality bOX (EQ-OX) system, which was designed for the simultaneous monitoring of quantities of some of the main IEQs with a low level of uncertainty and an affordable cost. Up to 15 parameters can be acquired at a time. The system embeds only low-cost sensors (LCSs) within a compact case, enabling vast-scale monitoring campaigns in residential and office buildings. The results of our laboratory and field tests show that most of the selected LCSs can match the accuracy required for indoor campaigns. A lightweight data processing algorithm has been used for the benchmark. Our intent is to estimate the correlation achievable between the detected quantities and reference measurements when a linear correction is applied. Such an approach allows for a preliminary assessment of which LCSs are the most suitable for a cost-effective IEQ monitoring system.

Evaluation and Correction of PurpleAir Temperature and Relative Humidity Measurements

The PurpleAir PA-II sensor provides low-cost in situ measurements of meteorological variables including temperature and relative humidity (RH), as well as fine particulate matter (PM2.5) in real time. The sensors have been used in several studies investigating intracity differences in temperature and PM2.5. While the adoption and use of low-cost sensors has many benefits, care must be taken to ensure proper calibration and testing. This is true not only for PM2.5 measurements but also for temperature and RH given the synergistic health impacts from extreme heat and air pollution exposure. Here, we compare continuous temperature and RH measurements from a PA-II sensor to measurements from a Campbell Scientific 107 temperature probe and Vaisala HMP45C RH probe. All three instruments were co-located from December 2021 to June 2023 in Asheville, North Carolina. We found that the PA-II has an overall high temperature bias of 2.6 °C and root mean square error (RMSE) of 2.8 °C. Applying a linear regression correction reduces RMSE to 1.0 °C, while applying the constant 4.4 °C correction suggested by PurpleAir reduces RMSE to only 2.2 °C. Our PA-II RH measurements have a low bias of −17.4% and uncorrected RMSE of 18.5%. A linear regression correction improves the RH RMSE to 4.5%. Applying the constant 4% RH correction suggested by PurpleAir reduces RMSE to only 14.8%. We present new correction factors that differ from those suggested by PurpleAir, which overcorrect the high temperature bias and undercorrect the low RH bias. We also show that our correction factors improve estimates of dewpoint temperature (RMSE of 0.6 °C and 0.9 °C) compared to the corrections suggested by PurpleAir.