Abstract: Nonlinear spectrum distortions are caused by the peculiarities of the operation of charge-coupled device elements (CCD), in which the signal exposition time (TINT) is one of the significant parameters. A change of TINT on a CCD leads to a nonlinear distortion of the resulting spectrum. Nonlinear distortion of the spectrum, in its turn, leads to errors in determining the central wavelength of Fiber Bragg Gratings (FBG) and spectrally sensitive sensors, which, in general, negatively affects the accuracy of measuring systems. The paper proposes an algorithm for correcting nonlinear distortions of the spectrum obtained on a spectrum analyzer using CCD as a receiver. It is shown that preliminary calibration of the optical spectrum analyzer with subsequent mathematical processing of the signal makes it possible to make corrections in the resulting spectrum, thereby leveling the errors caused by measurements at different TINT.

We found an important fact that the beam footprint line of Ping will intersect with the real water depth when the initial incidence angle is about 45°, and sound velocity error hardly has an effect on it. This is contrary to our previous experience that the soundings of the central beam of multi-beam bathymetric system (MBS) is the most accurate. Firstly, the influence of sound velocity errors on central beam and seafloor topography distortion was analyzed. Secondly, the process of proving this fact was given, and the topography correction method was proposed by compensating the sound velocity profile area (SVP area). Finally, we showed in the first simulation of four type errors in SVPs that this fact is verified. The topography correction method used in the second simulation to correct the topography distortion of the first simulation is also verified.

Helical (frontier) molecular orbitals [Chem. Sci. 2013, 4, 4278] have been reported almost a decade ago. Yet, helical molecular spin densities [Mol. Phys. 2022, e2157774] have been observed by us only very recently. In this work, we have observed that some chiral boron clusters (B–16, B–20, B–24, and B–28) can simultaneously have helical molecular orbitals and helical spin densities. To our best knowledge, it is the first time we have discovered that inorganic boron clusters assume such an unprecedented property. We have unambiguously unraveled that it is chiral Jahn-Teller distortion of quasi-planar boron clusters that drives the formation of helical molecular spin densities. More interestingly, we have shown that elongation/enhancement of helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity properties of these boron clusters are also discussed. Implication of this work is straightforward that boron clusters may find potential applications in spintronics, such as molecular magnets.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

Climate simulations in West Africa have been attributed with large uncertainties. Global climate projections are not consistent with changes in observations at the regional or local level of the Niger basin, making management of hydrological projects in the basin uncertain. This study evaluates the potential of using the quantile mapping bias correction to improve the Coupled Model Intercomparison Project (CMIP5) outputs for use in hydrology impact studies. Rainfall and temperature projections from 8 CMIP5 Global Climate Models (GCM) were bias corrected using the quantile mapping approach. Impacts of climate change was evaluated with bias corrected rainfall, temperature and potential evapotranspiration (PET). The IHACRES hydrological model was adapted to the Niger basin and used to simulate impacts of climate change on discharge under present and future conditions. Bias correction significantly improved the accuracy of rainfall and temperature simulations compared to observations. Nash coefficient (NSE) for monthly rainfall comparisons of 8 GCMs to the observed was improved by bias correction from 0.69 to 0.84. The standard deviations among the 8 GCM rainfall data were significantly reduced from 0.13 to 0.03. Increasing rainfall, temperature, PET and river discharge were projected for all GCMs used in this study under the RCP8.5 scenario. These results will help improving projections and contribute to the development of sustainable climate change adaptation strategies.

Natural polluted insulator surfaces are always coated with various kinds of soluble constituents, and those constituents affect flashover performance differentially. Currently this fact is not considered either in laboratory experiments or field pollution degree measurements, causing the existing insulation selection method to be deficient. In this paper a systematical research on insulator flashover voltage gradient correction involving types of soluble pollution constituents was presented. Taking typical type glass insulator as the sample, its flashover tests polluted by typical soluble chemicals NaCl, NaNO₃, KNO₃, NH₄NO₃, MgSO₄, Ca(NO₃)₂ and CaSO₄ were carried out. Then the flashover gradient correction was made combining the flashover performance of each soluble constituent, the ESDD contribution of the seven constituents, as well as the saturation performance of CaSO₄. The correction was well verified with the flashover test results of insulator polluted by three types of soluble mixture. Research results indicate that the flashover gradient correction method proposed by this paper performs well in reducing the calculating error. It is recommended to carry out component measurements and flashover gradient correction to better select outdoor insulation configuration.

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases that include invertible and partially-invertible functions, and degraded measurement channels, exact lossless and lossy rate regions are characterized, and one exact region is evaluated for an example scenario.

Accurate image registration is essential for eye movement compensation in optical coherence tomography (OCT) and OCT angiography (OCTA). The spatial resolution of an OCT instrument is typically anisotropic, i.e., different resolutions in the lateral and axial dimensions. When OCT images have anisotropic pixel resolution, residual distortion (RD) and false translation (FT) were always observed after image registration for rotational movement. In this study, RD and FT were quantitively analyzed over different degrees of rotational movement and various lateral and axial pixel resolution ratio (RL/RA) values. The theoretical analysis confirmed that the RD and FT increase significantly with the rotation degree and RL/RA. An image resizing assisting registration (RAR) strategy was proposed for accurate image registration. The performance of direct registration (DR) and RAR for retinal OCT and OCTA images were quantitatively compared. Experimental results confirmed that unnormalized RL/RA causes RD and FT, RAR can effectively improve the performance of OCT and OCTA image registration and distortion compensation.

The purpose of this study is to show an automated laser vision correction (LVC) with the transep-ithelial refractive keratectomy (TransPRK) surgery technique. Since more surgical steps have been automated over the years, we have standardized the TransPRK technique. We have been using it since 2010. This paper aims to illustrate the processes that are readily applicable to automation. To meet the patient's expectations and ensure that the patient has uncorrected visual acuity at least equal to the preoperative corrected vision with glasses, patient selection is crucial in refractive surgical procedures. One major benefit of automating the surgery is that it can be performed in a similar way by each surgeon or laser correction centre, so once the standard and results are good, these can be per-formed by different surgeons.

In the present paper, we introduced and study a new class of harmonic univalent functions on unit disc U. also we obtain coefficient conditions, extreme points, convolution condition for the above class of harmonic univalent functions.

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to prevent malfunctions and faults in electric assets and in connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic, the supraharmonic 2kHz–150kHz range. This range is not populated by the harmonic components of the 50-60 Hz mains fundamental, but a combination of intentional emissions, switching and non-linearity by-products and various types of resonances. This paper aims to provide a detailed analysis of the impact of SH on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference to equipment and to power line communication (PLC) technology in particular. Under some shareable assumptions limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with specific focus on their accuracy.

Atmospheric correction is the processes of converting radiance measured at a spectral 1 sensor to the reflectance of the materials in a multispectral or hyperspectral image. This is an 2 important step for detecting or identifying the materials present in the pixel spectra. We present 3 two machine learning models for atmospheric correction trained and tested on 100,000 batches of 40 4 reflectance spectra converted to radiance using MODTRAN, so the machine learning model learns 5 the radiative transfer physics from MODTRAN. We created a theoretically interpretable Bayesian 6 Gaussian process model and a deep learning autoencoder treating the atmosphere as noise. We 7 compare both methods for estimating gain in the correction model to the well-know QUAC method 8 of assuming a constant mean endmember reflectance. Prediction of reflectance using the Gaussian 9 process model outperforms the other methods in terms of both accuracy and reliability.

Heme is located in the active site of proteins and has diverse and important biological functions, such as electron transfer and oxygen transport and/or storage. The distortion of heme porphyrin is considered an important factor for the diverse functions of heme because it correlates with the physical properties of heme, such as oxygen affinity and redox potential. Therefore, clarification of the relationship between heme distortion and the protein environment is crucial in protein science. Here, we analyzed the fluctuation in heme distortion in the protein environment for hemoglobin and myoglobin using molecular dynamics (MD) simulations and quantum mechanical (QM) calculations. We also investigated the protein structures of hemoglobin and myoglobin stored in Protein Data Bank and found that heme is distorted along the doming mode, which correlates with its oxygen affinity, more prominently in the protein environment than in the isolated state, and the magnitude of distortion is different between hemoglobin and myoglobin. This tendency was also observed in the results of MD simulations and QM calculations. These results suggest that heme distortion is affected by its protein environment and fluctuates around its fitted conformation, leading to physical properties that are appropriate for protein functions.

Although the similarity laws were widely used in impact fields, the scaling relations of anisotropic elastic structures often were broken when the geometric distortion (not equal scaling in different spatial directions) and the material distortion (different materials used for scaled model and full-size prototype) were considered. To overcome the difficulty of geometric and material distortion, a directional framework of similarity laws, termed as oriented-density-length-velocity (ODLV) system, is proposed for the anisotropic elastic structure under impact loads. Different from previous similarity law systems using scalar dimensional analysis, the directional similarity law framework mainly considers spatial anisotropy for structural geometry and material parameters. Based on the oriented dimensional analysis and the orthotropic Hooke's law, directional dimensionless numbers and directional scaling relations with geometric power properties for the elastic modulus and the Poisson's ratio are presented systematically. By selecting the dominant material parameters controlling similarity, three important scaling techniques with correction of geometric width and thickness are proposed to compensate for the difficulty of distortion. A clamped square plate with different anisotropic and isotropic elastic materials subjected to dynamic pressure pulse is verified numerically and discussed in detail. The results show that the thin square plate prototype must be scaled to be the thinner/thicker rectangular plate, and the components of displacement, stress and strain between scaled model and full-scale prototype behave good consistency in both spatial and temporal fields.

In this paper, industrial structure distortion, two-way FDI and carbon emission intensity are brought into a unified research framework, and based on China's panel data from 2011 to 2020, empirical tests are conducted employing Exploratory Spatial Data Analysis (ESDA), spatial econometric model and intermediary effect test. The results show the following. Firstly, China's industrial structure distortion index shows a downward trend. The industrial structure distortion index is the highest in the west, followed by the middle, and the lowest in the East. Secondly, the relationship between carbon emission intensity and economic development shows a "decoupling" effect and keeps decreasing year by year. The spatial disparity is remarkable, showing the pattern of "the east leading, the middle catching up and the west lagging ". At the provincial level, except in Xinjiang province, the carbon emission intensity of other provinces showed different degrees of decline. In terms of spatial distribution, the polarization characteristics of carbon emission intensity are significant, and the traditional spatial distribution pattern has been broken. Thirdly, there is a positive spatial correlation between China's industrial structure distortion, two-way FDI and carbon emission intensity. The distortion of industrial structure will not only lead to the increase of local carbon emission intensity but also produce reverse spillover to adjacent areas. IFDI and OFDI provide a strong driving force for the decline of carbon emission intensity. IFDI promotes the decline of carbon emission intensity in adjacent areas, while OFDI will increase the carbon emission intensity in surrounding areas. The interaction of IFDI and OFDI can significantly reduce the carbon emission intensity of local and adjacent areas. Fourthly, the results of intermediary effect analysis show that two-way FDI is the two channels of industrial structure distortion affecting carbon emission intensity. Industrial structure distortion can affect the transmission mechanism of carbon emission intensity by affecting two-way FDI.

We describe quantum correction to the accreting hot plasma onto black holes. The accreting black holes are surrounded by the very hot ionized plasma. This plasma is heated inevitably by the outgoing photons of the quantum Hawking radiation. It is demonstrated that Hawking radiation prevails over the Compton scattering of hot electrons in the accreting flow onto the small enough evaporating black holes.

In this paper, we study the relativistic correction to Bekenstein-Hawking entropy in the canonical ensemble and isothermal-isobaric ensemble and apply it to the cases of non-rotating BTZ and AdS-Schwarzschild black holes. This is realized by generalizing the equations obtained using Boltzmann-Gibbs(BG) statistics with its relativistic generalization, Kaniadakis statistics, or κ-statistics. The relativistic corrections are found to be logarithmic in nature and it is observed that their effect becomes appreciable only in the high-temperature limit suggesting that the entropy corrections must include these relativistically corrected terms while taking the aforementioned limit. The non-relativistic corrections are recovered in the κ → 0 limit.

For a long time, physicists always directly use mathematical tools to deal with physical problems, and few people pay attention to the difference between mathematical theory and physical theory. Just like the dilemma that physicists once faced when dealing with the problem of blackbody radiation function.By analyzing the difference between the theoretical basis of mathematics and the theoretical basis of physics, this paper draws the following conclusions: (1) The theoretical basis of mathematics and the theoretical basis of physics are different, so when we use mathematical tools for physics research, we need to be very careful. (2) Finiteness and discreteness should be the basis of the whole physical theory; This paper points out that it is not advisable to use infinite " " and infinitesimal "0" without restriction and demonstration in physics, as well as the continuity of functions, which will bring a lot of trouble to physical theory.At the same time, through the analysis of Banach-Tarski paradox and Bertrand paradox, this paper proposes that if we revise the basic assumptions of probability theory: assuming that "points" have quantized sizes, and "lines" also have quantized widths. After the correction, we can not only avoid the troubles caused by Bertrand paradox, but also make probability theory better for practical application.

The present study compared the contralateral suppression and the amplitude of distortion product otoacoutsic emissions (DPOAEs) between smokers and non-smokers to determine the influence of smoking. Thirty smokers and thirty non-smokers within the age range of 18-40 years with a normal hearing sensitivity were considered for the study. For both the groups, DPOAEs were measured and the efferent auditory system functioning was measured by presenting the white noise of 50 dB HL to the contralateral side, while recording the DPOAEs. There was no significant effect of age on the amplitude of DPOAEs in both the groups. However, there were significant differences in the amplitude of DPOAEs between smokers and non-smokers. The amount of suppression and DPOAE amplitude were reduced in smokers when compared to non-smokers. The study found no significant correlation between the amount of smoking and amount of suppression between smokers and non-smokers. However, there were significant correlations between the amount of smoking and DPOAE at low and mid frequencies between smokers and non-smokers. Therefore, the present study highlights the increased damage to the efferent auditory system risk and the smoking ill-effects on the efferent auditory system.

A description of the motion in Non-Inertial Reference Frames by means of the inclusion of high time derivatives is studied. It is noted that incompleteness of the description of physical reality is a problem of any theory: both quantum mechanics and classical physics. The "stability principle" is put forward. We also provide macroscopic examples of Non-Inertial Mechanics and verify the use of high-order derivatives as non-local hidden variables based the equivalence principle when acceleration is equal to the gravitational field. Acceleration in this case is a function of the higher derivatives with respect to time. The definition of Dark Metrics for matter and energy is presented to replace the standard notions of Dark Matter and Dark Energy.

Atmospheric correction is a necessary step in image processing data and spectra recorded by spaceborne sensors for pure cloudless atmosphere, primarily in the visible and near-IR spectral range. We have present a fast and sufficiently accurate method of atmospheric correction based on the proposed analytical solutions describing with high accuracy the spectrum of outgoing radiation at the top boundary of the cloudless atmosphere. This technique includes the model of the atmosphere and its optical parameters that are important in terms of radiation transfer. The solution of the inverse problem for finding unknown parameters of the model is carried out by the method of non-linear least squares (Levenberg-Marquardt algorithm) for an individual selected pixel of the image (its spectrum), taking into account the adjacency effects. Using the found parameters of the atmosphere and the average surface albedo, assuming homogeneity of the atmosphere within a certain area of the hyperspectral image (or the whole frame), the spectral albedo at the Earth's surface is calculated for all other pixels. It is essential that the procedure of the numerical simulation with non-linear least squares of the direct transfer problem is based on using analytical solutions, which provides a very short calculation time of the atmospheric parameters (seconds or less) and the ability to perform atmospheric correction "on-fly." Testing methods of atmospheric correction was performed using the synthetic outgoing radiation spectra at the top of the atmosphere (TOA), obtained by numerical simulation in the LibRadTran code, as well as spectra of real space images of the Hyperion hyperspectrometer. A comparison with the results of atmospheric correction in module FLAASH of ENVI package has been performed. Finally, to validate our data obtained by the SHARK method, a comparative analysis with ground-based measurements of Radiometric Calibration Network (RadCalNet) was carried out.

The rapid growth of Earth's global geospatial data necessitates an efficient system for organizing the data, facilitating data fusion from diverse sources, and promoting interoperability. Mapping the spheroidal surface of the planet presents significant challenges, as it involves balancing distortion and splitting the surface into multiple partitions. The distortion decreases as the number of partitions increases, but at the same time the complexity of data processing increases, since each partition represents a separate data set and is defined in its own local coordinate system. In this paper, we propose the dual orthogonal equidistant cylindrical projection method to mitigate distortion and reduce the number of partitions. Additionally, we use the rotation of projection cylinders to effectively minimize average angular and areal distortions of the Earth’s landmass and reduce the interruption of continental plates caused by partition edges. By incorporating auxiliary latitudes and proposing an approximate authalic latitude, we further enhance the mapping of the ellipsoid onto the sphere, simplifying calculations. Experimental results demonstrate a substantial reduction in distortion and interruption of continental plates. With only two partitions, an average landmass angular distortion of less than 3.56 degrees and an average normalized surface distortion of less than 1.07 were achieved.

Road intersections are made of asphalt pavement, a popular road surface material used worldwide. The pavement may suffer deformities and deterioration, resulting in higher maintenance expenses and an elevated likelihood of road accidents, due to factors such as heavy vehicles and environmental variables like temperature and rainfall. To tackle these obstacles, researchers have devised several machine-learning algorithms and optimization techniques. These tools aim to forecast and scrutinize pavement deformation, with the goal of refining pavement design and maintenance approaches, as well as obtaining a more comprehensive comprehension of the factors that impact pavement effectiveness. This paper shows that heavy vehicles contribute significantly more to road erosion, and the retention and braking of vehicles greatly impact roadways. We also emphasize the statistical errors computed on the actual data range and demonstrate the results of the multilayer perceptron (MLP) model. The MLP model used the lath erosion standard to simulate future impact. Even though the model given is based on a small sample of data from one intersection, its estimates for road erosion in a year were found to be accurate when contrasted to real data. Controlling traffic flow can significantly improve road conditions, reducing erosion decay by reducing the time spent at intersections and other parameters. We conclude that machine learning can help control traffic flow, which can significantly improve road conditions, reducing vehicle time stretches at intersections.

Recently, deep learning-based image quality enhancement models have been proposed to improve the perceptual quality of distorted synthesized views impaired by compression and Depth Image Based Rendering (DIBR) process in multiview video systems. However, due to the lack of multi-view video plus depth data, the training data for quality enhancement models is small, which limits the performance and progress of these models. Augmenting the training data to enhance the Synthesized View Quality Enhancement (SVQE) models is a feasible solution. In this paper, we suggest a deep learning-based SVQE model using more synthetic Synthesized View Images (SVIs). To simulate the irregular geometric displacement of DIBR distortion, a random irregular polygon-based SVI synthesis method is proposed based on existing massive RGB/RGBD data, and a synthetic synthesized view database is constructed, which includes synthetic SVIs and DIBR distortion masks. Moreover, to further guide the SVQE models to focus more precisely on DIBR distortion, the DIBR distortion mask prediction network which could predict the position and variance of DIBR distortion is embedded into the SVQE models. The experimental results demonstrate that by pretraining on the synthetic SVI database, the performance of the existing SVQE models could be greatly promoted. In addition, by introducing the DIBR distortion mask prediction network, the SVI quality could be further enhanced.

In this paper, I present a comprehensive theoretical framework for understanding surface-enhanced Raman scattering (SERS) measurements in both solution and thin film setups, focusing on electromagnetic enhancement principles. Two prevalent types of SERS substrates found in the literature are investigated: plasmonic colloidal particles, including spherical and spheroid nanoparticles, nanoparticle diameters, and thin-film-based SERS substrates like ultra-thin substrates, bundled nanorods, plasmonic, and porous thin films. The investigation explores the impact of analyte adsorption, orientation, and the polarization of the excitation laser on effective SERS enhancement factors. Notably, it considers the impact of analyte size on the SERS spectrum, by examining scenarios where the analyte is significantly smaller or larger than the hot-spot dimensions. The analysis also incorporates optical attenuations arising from the optical properties of the analyte and the SERS substrates. The findings provide possible explanations for many observations made in SERS measurements, such as variations in relative peak intensities during SERS assessments, reductions in SERS intensity at high analyte concentrations, and the occurrence of significant baseline fluctuations. The study offers valuable guidance for optimizing SERS substrate design, enhancing SERS measurements, and improving the quantification of SERS detection.

This study investigates the nonlinearities in three-phase inverters for SiC-based systems and compares their performance to IGBT-based systems. An analytical model of inverter voltage distortion is developed, which accounts not only for dead time (td), switching delay time, switching frequency (fs), and voltage drops of power devices, but also for output parasitic capacitance (Cout). Experimental tests validate the model, which provides a more accurate estimate of the inverter’s output phase voltage distortion. The power device characteristics are obtained from datasheets, while Cout is determined through experimentation. Three-phase inverters with varying switching frequencies, fundamental frequencies, and dead-time values are used in simulations and experiments to determine the influence of nonlinearity on phase voltage deviation and current distortion. The results show that, due to SiC devices’ faster switching time, the phase voltage deviation and phase current distortion are lower in SiC-based inverters than in IGBT-based ones for high-frequency applications, as the dead time can be reduced.

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

Smallsats are becoming the predominant electro-optical Earth observation (EO) imaging platforms. While atmospheric correction of smallsat data enhances its utility, an established pathway to do so may constrain accuracy and utility. The alternative, Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with Land Surface Reflectance Code (LaSRC) software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC error was well constrained from 0.01% (NIR) to 0.98% (blue) sustaining the null hypothesis for reliability.

Tropical cyclones (TC) are dangerous weather events and accurate monitoring and forecasting can provide significant early warning to reduce loss of life and property. However, the study of tropical cyclone intensity remains challenging, both in terms of theory and forecasting. ERA5 reanalysis is benchmark data set for tropical cyclone studies, yet the maximum wind speed error is very large (68 kts) and still 19 kts after simple linear correction even in the better sampled North Atlantic. Here, we develop an adaptive learning approach to correct the intensity in the ERA5 reanalysis, by optimising the inputs to overcome the problems because of the poor data quality and updating the features to improve the generalisability of the deep learning-based model. Specifically, we use TC knowledge to increase the representativeness of the inputs so that the general features can be learned with deep neural networks in the sample space, and then use domain adaptation to update the general features from the known domain with historical storms to the specific features for the unknown domain of new storms. This approach can reduce the error to only 6 kts which is within the uncertainty of the best track data in IBTrACS in the North Atlantic. The method may have wide applicability, such as extending it to the correction of intensity estimation from satellite imagery and intensity prediction from dynamical models.

Two-dimensional mass spectrometry (2D MS) is a method for tandem mass spectrometry that relies on manipulating ion motions to correlate precursor and fragment ion signals. 2D mass spectra are obtained by performing a Fourier transform in both the precursor ion mass-to-charge ratio (m/z) dimension and the fragment ion m/z dimension. The phase of the ion signals evolves linearly in the precursor m/z dimension and quadratically in the fragment m/z dimension. This study demonstrates that phase-corrected absorption mode 2D mass spectrometry improves signal-to-noise ratios by a factor of 2 and resolving power by a factor of 2 in each dimension compared to magnitude mode. Furthermore, phase correction leads to an easier differentiation between ion signals and artefacts, and therefore easier data interpretation.

Gesture-based recognition is one of the most intuitive methods for inputting information and is not subject to cumbersome operations. Recognition is performed on human's consecutive motion without reference to retrial or alternation by user. We propose a gesture recognition model with a mechanism for correcting recognition errors that operates interactively and is practical. We applied the model to a setting involving a manual grading task in order to verify its effectiveness. Our system, named GERMIC, consists of two major modules, namely, handwritten recognition and interactive correction. Recognition is materialized with image feature extraction and convolutional neural network. A mechanism for interactive correction is called on-demand by a user-based trigger. GERMIC monitors, track, and stores information on the user's grading task and generates output based on the recognition information collected. In contrast to conventional grading done manually, GERMIC significantly shortens the total time for completing the task by 24.7% and demonstrates the effectiveness of the model with interactive correction in two real world user environments.

Heme proteins serve diverse and pivotal biological functions. Therefore, clarifying the mechanisms of these diverse functions of heme is a crucial scientific topic. Distortion of heme porphyrin is one of the key factors regulating the chemical properties of heme. Here, we constructed convolutional neural network models for predicting heme distortion from the tertiary structure of the heme-binding pocket to examine their correlation. For saddling, ruffling, doming, and waving distortions, the experimental structure and predicted values were closely correlated. Furthermore, we assessed the correlation between the cavity shape and molecular structure of heme and demonstrated that hemes in protein pockets with similar structures exhibit near-identical structures, indicating the regulation of heme distortion through the protein environment. These findings indicate that the tertiary structure of the heme-binding pocket regulates the distortion of heme porphyrin, thereby controlling the chemical properties of heme relevant to the protein function; this implies a structure–function correlation in heme proteins.

Academic publishing is undergoing a highly transformative process, and many rules and value systems that were in place for years are being challenged in unprecedented forms leading to the evolution of novel ways of dealing with new pressures. One of the most important aspects of an integrated and valid academic literature is the ability to screen publications for errors during peer review to weed out mistakes, fraud and inconsistencies, such that the final published product represents a product that has value, intellectually, and otherwise. It is difficult to claim the existence of perfect manuscripts. The level of errors that exist in a manuscript will depend on the rigor of the research group and of the peer review process that was used to screen that paper. When errors slip into a final published paper, either through honest error or misconduct, and are not detected during peer review and editorial screening, but are spotted during post-publication peer review, an opportunity is created to set the record straight, and to correct it. To date, the most common forms of correcting the literature have been errata, corrigenda, expressions of concern, and retractions. Despite this range of corrective measures, which represent artificially created corrals around pockets of imperfect literature, certain cases do not quite fit this mold, and new suggested measures for correcting the literature have been proposed, including manuscript versioning, amendments, partial retractions and retract and replace. In this commentary, a discussion of the evolving correction of the literature is provided, as are perspectives of the risks and benefits of such new measures to improve it.

Long-term, high-accuracy mapping of built-up land dynamics is essential for understanding urbanization and its consequences for the environment. Despite advances in remote sensing and classification algorithms, built-up land mapping using early satellite imagery (e.g., from the 2000s and earlier) remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-year intervals. Using dense time-stack Landsat data, we applied discrete Fourier transformation to create temporal predictors and reduce mapping uncertainties for early years. We improved overall accuracy by 8% compared to using spectral and indices predictors alone. We implemented a temporal correction algorithm to remove inconsistent pixel classifications, further improving accuracy to a consistently high level (>94%) across years. A cross-product comparison showed that our study achieved the highest levels of accuracy across years. Total built-up land in the North China Plain increased from 37,941 km² in 1990–1992 to 131,578 km² in 2017–2019. Consistent, high-accuracy built-up land mapping provides a reliable basis for policy planning in one of the most rapidly urbanizing regions of the planet.

The development of anti-pain technologies in the complex treatment of pain syndromes is one of the most urgent tasks of modern medicine. We have undertaken a placebo-controlled experimental study of the therapeutic potential of low-intensity laser radiation when applied to acupuncture points, which are directly related to the autonomic nervous system. The adaptation effect of puncture photobiomodulation on the induction of stress-mediated autonomic reactions, oxidative metabolism and microcirculation in animals during the acute phase of pain stress was revealed. The data obtained are of interest for use in the complex rehabilitation of patients with pain syndrome.

An easier method for the calibration of differential drive robots is presented. Most of the calibration is done on-board and it is not necessary to expend too much time taking note of the robot's position. The calibration method does not need a big free space to perform the tests. The bigger space is just in a straight line, which is easy to find. Results with the proposed method are compared with those from UMB as a reference, and they show very little deviation while the proposed calibration is much simpler.

Advances in remote sensing have led to use of satellite-derived rainfall products to complement the sparse rain gauge data. Although globally derived and some regional bias corrected, these products often show large discrepancies with ground measurements attributed to local and external factors that require systematic consideration. Decreasing rain gauge network however inhibits continuous validation of these products. We propose to deal with this problem by the use of Bayesian approach to merge the existing historical rain gauge information to create a consistent satellite rainfall data that can be used for climate studies. Monthly Bayesian bias correction is applied to the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS v2) data to reduce systematic errors using a corresponding gridded (0.05°) rain gauge data over East Africa for a period of 33 (1981–2013) years of which 22 years are utilized to derive error fields which are then applied to an independent CHIRPS data for 11 years for validation. The bias correction is spatially and temporally assessed during the rainfall wet months of March-May (MAM), June-August (JJA) and October–December (OND) in East Africa. Results show significant reduction of systematic errors at both monthly and yearly scales and harmonization of their cumulative distributions. Monthly statistics showed a reduction of RMSD (29–56)% and MAE (28–60)% and an increase of correlations (2–32) %, while yearly ones showed reductions of RMSD (9-23)%, and MAE (7–27)% and increase of correlations (4–77)% for MAM months, reduction of RMSD (15–35)% and MAE (16–41)% and increase in correlations (5–16)% for JJA months, and reduction of RMSD (3–35)% and MAE (9–32)% and increase of correlations (3–65)% for OND months. Systematic errors of corrected data were influenced by local processes especially over Lake Victoria and high elevated areas. Large-scale circulations induced errors were mainly during JJA and OND rainfall seasons and were reduced by the separation of anomalous years during training. The proposed approach is recommended for generating long-term data for climate studies where consistencies of errors can be assumed.

Vector-borne disease (VBD) accounts for more than 17% of the global infectious disease burden, disproportionately affecting developing nations within tropical and subtropical areas. As Aedes aegypti mosquitoes are the principal vector for the transmission of many Public Health pathogens, our study examined their population dynamics within the seasonal context of tropical dry biomes in El Salvador as incidence of VBD in this region has increased in recent years. Species that rely on sexual reproduction must maintain a balanced sex ratio (1:1) to support their population dynamics, however, our phenological analysis of field-collected A. aegypti specimens revealed significant sex ratio variations during dry and wet seasons. Interestingly, we detected a seasonal shift that favored female mosquitoes during the dry season, highlighting the dynamic nature of mosquito populations in highly urbanized environments like El Salvador. By linking sex ratio distortions to anthropogenic factors, our study underscores the importance of comprehensively characterizing the urban ecology of vectors for the development of effective biocontrol strategies. As such, we advocate for more nuanced vector control approaches that consider ecological factors as well as the human behaviors that influence mosquito breeding habitats to effectively combat the rise of VBDs amid global climate changes.

Atmospheric propagational phase variations are the dominant source of error for InSAR timeseries analysis, generally exceeding uncertainties from poor SNR or signal correlation. The spatial properties of these errors have been well studied, but their temporal dependence and correction have received much less attention to date. We present here an evaluation of the magnitude of tropospheric artifacts in derived time series after compensation using an algorithm that requires only the InSAR data themselves. The level of artifact reduction equals or exceeds that from many weather model based methods, while avoiding the need to access fine-scale atmosphere parameters globally at all times. Our method consists of identifying all points in an InSAR stack with consistently high correlation, and computing, then removing, a fit of the phase at each of these points with respect to elevation. Comparison with GPS truth yields a reduction of 3, from an rms misfit of 5-6 cm to ~2 cm over time. This algorithm can be readily incorporated into InSAR processing flows without need for outside information.

Since the discovery of the first reported case with Zinc-deficiency in Iran¹ by Prasad et al. in 1961, the knowledge on Zinc has increased significantly. Zinc is the second most abundant common trace mineral in the human body, responsible for vital biological functions from cell growth and development to cell homeostasis and immune response ^2,3. Up to a fifth of the global population is estimated to suffer from different degrees of Zinc deficiency⁴. In the western world, Zinc deficiency is more prevalent among the geriatric population³, vegans/vegetarians, and people with certain underlying conditions⁴such as liver cirrhosis, inflammatory bowel disease, and various auto-immune disorders^4,5. Zinc and Zinc deficiency has been associated with several infectious diseases ^2,3. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is responsible for the ongoing pandemic belongs to the family of coronaviruses. SARS-CoV-2 has a high genetic similarity to another family member, SARS-CoV, which caused the first major epidemic of the 21^st century^6,7. Currently, there is no evidence linking the anti- SARS-CoV-2 response and the element Zinc. Herein and in light of the SARS-CoV-2 pandemic, we marshal the evidence associating the element Zinc with the anti-viral and antibacterial immune response as well as the cytokine storm and lung injury. Such a revisit of the precedent evidence may inspire further investigation assessing the relationship between Zincemia status and the anti-viral response in SARS-CoV-2 patients.

Document deskewing is a fundamental problem in document image processing. While existing methods have limitations, such as Hough Line Transformation that can deskew images upside down, and Deep Learning models that require huge amounts of human labour and computational resources and still fail to deskew while taking care of orientation, OCR-based methods also struggle to read text when it is tilted. In this paper, we propose a novel, simple, cost-effective deep learning method for fixing the skew and orientation of documents. Our approach reduces the search space for the machine learning model to predict whether an image is upside down or not, avoiding the huge search space of predicting an angle between 0 and 360. We finetuned a MobileNetV2 model, which was pre-trained on imagenet, using only 200 images and achieve good results. This method is useful for automation-based tasks, such as data extraction using OCR technology, and can greatly reduce manual labour.

Meteorological observations over the last four decades are of paramount importance to investigate the ongoing climate change. The assessment of the reliability of any climatic time series is thus mandatory to draw correct conclusions. This evaluation involves homogeneity tests to detect artificial discontinuities whose identification is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are examined. Hourly observations began in 1993 and since the aim is to study long term behavior of the temperature, the focus is on daily averages and extremes. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. The homogeneity tests applied must be able to identify change-points both in the middle and at the extremes of the series. Some well-known absolute tests have been applied to investigate shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, STARS. Some relative tests have been applied too, which are generally more reliable than absolute tests, because they consider the information from neighboring stations. As relative tests rely on the homogeneity and quality of the reference series, several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or location of the station have occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained splitting the observations in correspondence of these change-points have been homogenized with respect a selected period; corrections must be applied also to future measurements to extend the time series properly.

Fiber coupling efficiency is one of the key technical indicators of atmospheric laser communication, which directly affects the communication system BER. According to the optical fiber coupling efficiency model, the optical fiber coupling model under atmospheric slant link is established, and the relationship between wavelength, zenith angle, receiving aperture, altitude and coupling efficiency is studied through numerical simulation. Based on the principle of adaptive optics turbulence correction, the relationship between fiber coupling efficiency and adaptive optics order is established. A fast method for estimating the coupling efficiency based on Strehl ratio is proposed. According to the principle of laser communication system, the semi-physical simulation experimental system of atmospheric slant-range channel coupling efficiency is constructed, and the coupling efficiency test and analysis are completed.

The CRISPR/Cas9 gene editing system has enormous potential in the treatment of multiple genetic disorders. To fully harness this potential, it is essential to deliver CRISPR-Cas9 components safely and effectively into the nuclei of target cells. In this study, we tested the amphipathic cell-penetrating peptide LAH5, previously used for DNA delivery, to intracellularly deliver spCas9: sgRNA ribonucleoprotein (RNP) and RNP/single-stranded homology-directed repair (HDR) template. We discovered that the LAH5 peptide effectively formed nanocomplexes with both RNP and RNP/HDR cargo, and that these nanocomplexes were taken up by cells effectively. Peptide/RNP nanocomplexes were characterized for size and charge, and nanocomplexation with RNP and RNP/HDR cargo was demonstrated via an electrophoretic mobility shift assay. Various ratios of peptide/RNP nanocomplexes were functionally screened on fluorescent reporter cell lines for gene editing and HDR-mediated gene correction. Additionally, targeted gene editing of the CCR5 gene was demonstrated in various cell lines. This LAH5-based delivery strategy paves the way for the development of therapeutic delivery systems for CRISPR/Cas-based genomic engineering.

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

The purpose of this study is to propose a consecutive manufacturing process system to secure the productivity of excellent STKN540B steel tube in the respect of economy and safety as the supporting material for mega structures such as building, bridge and ship. The components of consecutive manufacturing are press-bending, orbital auto welding and steel tube correction. By using STKN540B a high-strength steel material with low yield point that requires a special manufacturing process unlike other steel materials, an actual tube manufacturing is carried out at each stage in this experimental study. With this, the quality of steel tube and the efficiency of the manufacturing process are analyzed to draw out some points to improve in the future.

Satellite measurements are one of the main sources of data on the state of the marine environment. To obtain information about the sea brightness coefficient , it is needed to correctly carry out atmospheric correction. In the presence of dust aerosol over the Black Sea, physically incorrect values of the spectral brightness coefficient often occur, and specifically negative values in the IR region of the spectrum. The main objective of the study is to evaluate the influence of dust aerosol on the spectral dependence of sea brightness, based on analytical calculations from the transfer theory using the principle of plane-parallel layers and results of validation of AERONET-OC field and remote sensing data. The work analyzes spectral dependence of the first error eigenvector of the standard atmospheric correction in the presence of dust aerosol. As result it is given that with an absorbing aerosol, the atmospheric correction error is described by the spectral course of molecular scattering, i.e. close to

With the development of designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system becomes a key point to determine their internal performances. Nevertheless, phase delay of electron components may result in some serious hazards. This paper describes a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis is provided to clarify the influences of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and zero rate output (ZRO) utilizing force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between amplitude-frequency, phase-frequency of MEMS gyroscope and the phase relationship of the whole control loop, a real-time correction system is proposed to automatically adjust the phase reference value of phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results show that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO is decreased by 755% to 0.095°/s. This correction system realizes a small angle random walk of 0.978°/√h, and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. Besides, the thermal drift of ZRO is reduced to 0.0034°/s/°C at a temperature range from -20°C to 70°C.

UAS-based multi-spectral imagery is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate BRDF correction. Future UAS based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

A computational methodology for the hydrodynamic analysis of horizontal axis marine current turbines is presented. The approach is based on a boundary integral equation method for inviscid flows originally developed for marine propellers and adapted here to describe the flow features that characterize hydrokinetic turbines. To this purpose, semi-analytical trailing wake and viscous-flow correction models are introduced. A validation study is performed by comparing hydrodynamic performance predictions with two experimental test cases and with results from other numerical models in the literature. The capability of the proposed methodology to correctly describe turbine thrust and power over a wide range of operating conditions is discussed. Viscosity effects associated to blade flow separation and stall are taken into account and predicted thrust and power are comparable with results of blade element methods that are largely used in the design of marine current turbines. The accuracy of numerical predictions tend to reduce in cases where turbine blades operate in off-design conditions.

Spectral photon counting cone-beam CT imaging is challenged by individual pixel response behaviour, which leads to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform post-processing ring artefact correction of sinogram data or scan reconstructions, without taking the pixel response explicitly into account. Here we present a novel post-processing method (DAC-shifting), which explicitly measures the current pixel response using flat field images, and subsequently corrects the projection data. The DAC-shifting method was evaluated with a repeat series of spectral photon counting imaging (Medipix3) of a phantom with different density inserts, and in iodine K-edge imaging. The method was also compared against PMMA based STC. The DAC-shifting method was shown to be effective in correcting individual pixel response, and was robust against detector instability. On the contrary, STC correction showed varying results, which was almost as good as DAC-shifting when data was acquired just after STC calibration, but worse with larger time differences. In K-edge imaging, DAC-shifting provides a sharper attenuation peak, and more uniform CT values, which is expected to benefit iodine concentration quantification.

Vein segmentation and projection correction constitute the core algorithms of auxiliary venipuncture device, responding to the accurate venous positioning to assist puncture and reduce the number of punctures and pain of patients. This paper proposes an improved U-Net for segmenting vein and a coaxial correction for image alignment in the self-build vein projection system. The proposed U-Net is embedded by Gabor convolution kernels in the shallow layers to enhance segmentation accuracy. Additionally, to mitigate the semantic information loss caused by channel reduction, the network model is lightweighted by the mean of replacing conventional convolutions with inverted residual blocks. During the visualization process, a method that combining coaxial correction and homography matrix is proposed to address the non-planarity of the dorsal hand in this paper. First, use a hot mirror to adjust the light paths of both projector and camera to be coaxial, and then align the projected image with dorsal hand using a homography matrix. Using this approach, the device requires only a single calibration before use. With the implementation of the improved segmentation method, an accuracy rate of 95.12% is achieved by the dataset. The intersection over union ratio between the segmented and original images is reached at 90.07%. The entire segmentation process is completed in a 0.09 second, and the largest distance error of vein projection onto dorsal hand is 0.53mm. Experiments show that the device has reached practical accuracy and has the value of research and application.

In view of the limitations of the existing optimization method of suspender cable force, in order to improve the stress of suspender under completion state and avoid frequent adjustment of cable force and grid beam elevation during construction, a new method of cable force optimization is proposed. The article takes the longest large span arch bridge in the world, Pingnan Third Bridge, a Concrete-filled steel tube (CFST) arch bridge with a span of 575m as the engineering background combined with the finite element analysis and multi-objective optimization method. One cable force optimization method that suspender “Real-time correction during construction, in the process variable optimal and results reliable” during panel girder lifting of long span CFST arch bridges is clarified. Taking the panel girder weight and displacement during the construction as parameter variables, the displacement and unevenness of the panel girder under completion state as constraint conditions, the displacement and cable force during the hoisting construction as the objective equation, through the optimization of the objective equation, the suspender cable force and dis-placement of each hoisting section are calculated. The results show that it is feasible to introduce the optimization theory into the cable force optimization when lifting the panel girder. the segment displacement variation is minimized to meet the destination. The cable force distributed evenly under completion state of the bridge that further making sure the completion state satisfies the requirements. No repeating iteration is needed, thus avoiding cumberso me calculation, getting cable force once. With higher optimization efficiency and better effects, the method provides high value for the cable force calculation of same type bridge suspender construction and for guiding construction.

Precipitation gauges are critical for measuring precipitation rates at regional and global scales and are often used to calibrate precipitation rates estimated from other instruments such as satellites. However, precipitation measured at the gauges is affected by gauge-undercatch that is often larger for solid precipitation. In the present work, two popular gauge-undercatch correction factors are assessed: one utilizes a dynamic correction model and is used in the Global Precipitation Climatology Centre (GPCC) Monitoring product and the other one employs a fixed climatology and is used in the Global Precipitation Climatology Project (GPCP) product. How much the choice of correction factors can impact the total estimate of precipitation was quantified over land at seasonal, annual, regional, and global scales. The correction factors are also compared as a function of the environmental variables used in their development, among those are near-surface air temperature, relative humidity, wind speed, elevation, and precipitation intensity. Results show that correction factors can increase the annual precipitation rate based on the gauges by ~9.5 % over the global land (excluding Antarctica), although this amount can vary from ~6.3% (in boreal summer) to more than 10% (in boreal winter), depending on the season and the method used for gauge-undercatch correction. Annual variations of correction factors can also be large, so the use of the fixed climatology correction factors requires caution. Given their magnitudes and differences, selection of appropriate correction factors can have important implications in refining the water and energy budget calculations.

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions, (ii) in order to specify and operate the simplified radiative transfer equation (RTE), (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need (i) for formal atmospheric correction, (ii) nor for conversion of relative radiance into calibrated reflectance , (iii) nor for existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

A distinction is made between data rescue (i.e., copying, digitizing and archiving) and data recovery that implies deciphering, interpreting and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern units. This requires a multidisciplinary approach that includes: palaeography and knowledge of Latin and other languages to read the handwritten logs and additional documents; history of science to interpret the original text, data e metadata within the cultural frame of the 17th, 18th and early 19th century; physics and technology to recognize bias of early instruments or calibrations, or to correct for observational bias; astronomy to calculate and transform the original time in canonical hours that started from twilight. The liquid-in-glass thermometer was invented in 1641 and the earliest temperature records started in 1654. Since then, different types of thermometers were invented, based on the thermal expansion of air or selected thermometric liquids with deviation from linearity. Reference points, thermometric scales, calibration methodologies were not comparable, and not always adequately described. Thermometers had various locations and exposures, e.g., indoor, outdoor, on windows, gardens or roofs, facing different directions. Readings were made only one or a few times a day, not necessarily respecting a precise time schedule: this bias is analysed for the most popular combinations of reading times. The time was based on sundials and local Sun, but the hours were counted starting from twilight. In 1789-90 Italy changed system and all cities counted hours from their lower culmination (i.e., local midnight), so that every city had its local time; in 1866, all the Italian cities followed the local time of Rome; in 1893, the whole Italy adopted the present-day system, based on the Coordinated Universal Time and the time zones. In 1873, when the International Meteorological Committee (IMO) was founded, later transformed in World Meteorological Organization (WMO), a standardization of instruments and observational protocols was established, and all data became fully comparable. In the early instrumental period, from 1654 to 1873, the comparison, correction and homogenization of records is quite difficult, mainly because of the scarcity or even absence of metadata. This paper deals about this confused situation, discussing the main problems, but also the methodologies to recognize missing metadata, distinguish indoor from outdoor readings; correct and transform early datasets in unknown or arbitrary units into modern units; finally, in which cases it is possible to reach the quality level required by WMO. The focus is to explain the methodology needed to recover early instrumental records, i.e., the operations that should be performed to interpret, correct, and transform the original raw data into a high-quality dataset of temperature, usable for climate studies.

Background: Eukaryotes whole-genome sequencing is crucial for species identification, gene detection and protein-annotation. Oxford Nanopore sequencing serves as an affordable and rapid platform for sequencing eukaryotes, however the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryotes genome completeness, gene detection and protein-annotation. Methods: Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively. Results: genome completeness was dependent on assembly method rather than read correction tool, however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation. Conclusion: We show that three rounds of read correction significantly affects gene detection and protein-annotation which are dependent on assembly quality in preference to assembly completeness.

The Korean Pathfinder Lunar Orbiter (KPLO)-MAGnetometer (KMAG) consists of three triaxial fluxgate sensors (MAG1, MAG2, and MAG3) to measure the magnetic field around the Moon. The three sensors are mounted in the order of MAG3, MAG2, and MAG1 inside a 1.2 m long boom away from the satellite body. Before it arrived on the Moon, we compared the magnetic field measurements taken by DSCOVR and KPLO in the solar wind to verify the measurement performance of the KMAG instrument. We found that there were artificial disturbances in the KMAG measurement data, such as step-like and spike-like disturbances, which were produced by the spacecraft body. To remove spacecraft-generated disturbances, we applied a multi-sensor method, employing the gradiometer technique and principal component analysis and using KMAG magnetic field data and confirmed the successful elimination of spacecraft-generated disturbances. This indicates that the multi-sensor method is able to clean the magnetic field data measured onboard the KPLO.

We report on the study of the temperature dependence of the response of a BSO crystal based polarimetric current sensor with spectral interrogation. Two possible interrogation schemes are discussed. The spectral dependence of the optical rotation along the crystal caused by temperature and current changes has been investigated and approximate dependences for the sensitivities to current SI and temperature ST have been derived. A mixed term in the response with spectral interrogation has been revealed, the elimination of which is done by tracking wavelength shifts of two distinct extrema in the polarimetric response. A temperature independent second degree equation for the current changes as a function of the spectral shifts has been derived and tested.

To overcome the temperature effect of NaI(Tl) detectors for energy spectrometry without additional hardware, a new correction method was put forward based on pulse deconvolution, trapezoidal shaping and amplitude correction, named DTSAC. To verify this method, actual pulses from a NaI(Tl)-PMT detector were measured at different temperatures from -20℃ to 50℃. Pulse processing and spectrum synthesis showed that the position drift of the 662 keV peak was less than 3 keV, and the corresponding resolution at 662 keV of the sum spectra ranges from 6.9% to 10.60% with trapezoidal width set as 1000 ns to 100 ns. The DTSAC method corrects temperature effect by pulse processing, and need no reference peak, reference spectrum and additional circuits. The method solves the problem of correction of pulse shape and pulse amplitude at the same time, and can be used even at high counting rate.

An exact solution is obtained for the kinetic energy in the general case of the spatial motion of solids with arbitrary rotation, which differs from the Koenig formula by three additional terms with centrifugal moments of inertia. The description of motion in the Lagrange form and the superposition principle are used, which provides a geometric summation of the velocities and accelerations of the joint motions in the Lagrange form for any particle at any time. The integrand function in the equation for kinetic energy is represented by the sum of the identical velocity components of the joint plane-parallel motions. The moments of inertia in the Koenig formula do not change during movement and can be calculated from the current or initial state of the body. The centrifugal moments change and turn to 0 when rotating relative to the main central axes only for bodies with equal main moments of inertia, for example, for a ball. In other cases, the difference in the main moments of inertia leads to cyclic changes in the kinetic energy with the possible manifestation of precession and nutation, the amplitude of which depends on the angular velocities of rotation of the body. An example of using equations for a robot with one helical and two rotational kinematic pairs is given.

Bohrnstedt’s (1969) attempt to derive a formula to compute the partial correlation coefficient and simultaneously correct for attenuation sought to simplify the process of performing each task separately. He suggested that his formula, developed from algebraic and psychometric manipulations of the partial correlation coefficient, produces a corrected partial correlation value. However, an algebraic error exists within his derivations. Consequently, the formula proposed by Bohrnstedt does not appropriately represent the value he intended it to estimate. By correcting the erroneous step and continuing the derivation based upon his proposed procedure, the steps outlined in this paper ultimately produce the formula that Bohrnstedt desired.

We present a simplified atmospheric correction algorithm for the snow/ice albedo retrieval using single view satellite measurements. The validation of the technique is performed using Ocean and Land Colour Instrument (OLCI) on board Copernicus Sentinel - 3 satellite and ground spectral or broadband albedo measurements from locations on the Greenland ice sheet and in the French Alps. Through comparison with independent ground observations, the technique is shown to perform accurately in a range of conditions from a 2100 m elevation mid-latitude location in the French Alps to a network of 15 locations across a 2390 m elevation range in seven regions across the Greenland ice sheet. Retrieved broadband albedo is accurate within 5% over a wide (0.5) broadband albedo range of the (N = 4,155) Greenland observations and with no apparent bias.

The purpose of our study is to determine the effectiveness of various types of psychocorrection measures: social and psychological training, a method of biological feedback and Sandplay for the indicators of childhood anxiety among younger schoolchildren. The study was conducted in the school of Magadan, North East of Russia (9-10 year old students, n = 43). We used a standardized method of Multidimensional Assessment of Child Anxiety which included 10 scales. The correction methods were used: socio-psychological training (SPT), biofeedback method (BFB), individual and group Sandplay. Students of group I (n = 12) participated only in the SPT. Students of group II (n = 11) participated in the SPT and underwent a course of training in self-regulation using the BFB method. In correction work with the students of group III (n = 20), the SPT, BFB, individual and group Sandplay were used. In group I, after the correction activities, a significant decrease in anxiety was observed in 3 of 10 scales (2, 6, 7; (p <0.05). In group II it was seen in 5 scales (1, 3, 6, 7, 8; p <0.05). In group III, a significant improvements took place in 7 scales (1, 2, 5, 6, 7, 9, 10; p <0.01–p <0.05). The present study has shown the different efficacy of applying the remedial techniques separately and in combination. The use of methods in the complex enhances the impact on the types of the child anxiety.

The node position information is critical in the wireless sensor network (WSN). However, the existing positioning algorithms commonly have low positioning accuracy because of noise interferences in communication. To solve this problem, this paper presents an iterative positioning model based on distance correction to improve the positioning accuracy of the target node in WSN. First, the log-distance distribution model of received signal strength indication (RSSI) ranging is built and the noise impact factor is derived based on the model. Second, the initial position coordinates of the target node are obtained based on the triangle centroid localization algorithm, thereby calculating the distance deviation coefficient under the influence of noise. Then, the ratio of the distance measured by the log-normal distribution model to the median distance deviation coefficient is taken as the new distance between the anchor node and the target node. Based on the new distance, the triangular centroid positioning algorithm is used again to calculate the target node coordinates. Finally, the iterative positioning model is constructed, and the distance deviation coefficient is updated repeatedly to update the positioning result until the set number of iterations is reached. Experiment results show that the proposed iterative positioning model can improve positioning accuracy effectively.

This study employed the Fully Modified Ordinary Least Squares (FMOLS) and the Error Correction Model (ECM) to investigate the long-run and short-run determinants of unemployment rate in Nigeria. To achieve this annual data on unemployment rate, inflation rate, interest rate, exchange rate and population growth from 1981 to 2016 was collected from Central Bank Statistical Bulletins and the World Bank website. The ADF test revealed that the macroeconomic variables are stationary at first difference while the Cointegration test revealed that the variables are cointegrated. Using unemployment rate as dependent variable, the FMOLS model revealed that exchange rate and population growth are positively significantly related to unemployment rate, interest rate and inflation rate were negatively related to unemployment rate but only interest rate was significant. The short run relationship revealed that the coefficient of the ecm(-1) is negative and statistically significant at 5% level indicating that the system corrects its previous period disequilibrium at the speed of 48.93% yearly. This study concludes that high exchange rate and population growth can lead to increase in unemployment rate in Nigeria while the government should develop the industrial sector and non-oil sector in order to generate employment and boost export in Nigeria.

The Microwave Humidity and Temperature sounder (MWHTS) on board the Fengyun (FY)-3C satellite measure the outgoing radiance form the Earth surface and atmospheric constituents. MWHTS makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of strong water vapor line around 183 GHz, can provide fine vertical distribution structure of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by the physical retrieval method, bias between the observed radiance and those simulated by radiative transfer model from the background or first guess profiles must be correct. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion, one is the linear regression correction (LRC) and the other is neural networks correction (NNC), representing the linear and nonlinear nature between MWHTS measurements and air mass, respectively. Both correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180° W-180° E, 60° S-60° N). The corrected results are evaluated by the probability density function of the difference between corrected observations and simulated values and the root mean square error (RMSE) with respect to simulated observations. The numerical results show that the NNC method perform better, especially in MWHTS channels 1 and 7-9 whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS uncorrected and corrected brightness temperatures to estimated atmospheric temperature and humidity profiles, The retrieval results show that the NNC has better performance which is to be expected. An indication of the stability and robustness of NNC method is given which suggests that the NNC method has promising application perspectives in the physical retrieval.

Chest X-ray (CXR) is the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field-of-view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep learning-based models to estimate and correct the scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NN. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained with the MC code from chest CTs of patients affected by COVID-19. The results showed that the NN models were able to estimate and correct the scatter contribution to CXRs with an error &lt;5%, being robust to variations in the simulation setup and improving the contrast in soft tissue. The single-energy model was tested with real CXRs, providing robust estimations of the scatter-corrected CXRs.

This report elucidates the first surgical correction of an infundibular muscular ventricular septal defect (VSD) in a one-year-old Ragdoll cat via cardiac arrest using cardiopulmonary bypass, a method that is rarely used in feline cardiac surgery. VSDs can lead to congestive heart failure and pulmonary hypertension, particularly in patients with large shunts. This case involved a VSD that was atypically located and classified under the Soto classification instead of the standard Kirklin classification. Detailed echocardiography revealed that the defect required intervention owing to left heart and main pulmonary artery enlargement. Despite the VSD being located on the contralateral side, as anticipated in the preoperative examinations, the choice of median sternotomy allowed for successful closure of the defect. Conversely, the insertion of two cannulas into the ascending aorta resulted in damage to the adjacent thoracic duct, causing transient chylothorax, which resolved with conservative treatment. Cardiac arrest induced by a cardioplegic solution facilitated the surgical procedure, although it has led to anemia in cats. However, on postoperative day 490, the patient exhibited only minor residual shunting with normalized heart size, and remained healthy. This technique appears to be a viable treatment option for congenital heart disease in cats.

An analysis of the features of measurements and correction of phase distortions in optical waves propagating in the atmosphere at various levels of turbulence was performed. It is shown that with increasing intensity fluctuations, the limiting capabilities of phase correction decrease, and the phase of an optical wave that has passed through a turbulence layer consists of two components: potential and vortex. It was found that even in the region of weak fluctuations there is an overlap of spectral filtering functions for intensity and phase fluctuations. Areas of turbulence inhomogeneities have been identified that will have mutual influence and negatively affect the operation of the phase meter. It is noted that correlation functions, both phase and intensity, are less susceptible to this compared to structural functions. The results of experimental studies of the reconstruction of the wavefront of laser radiation distorted by atmospheric turbulence using a Shack-Hartmann wavefront sensor during vignetting and central screening of the entrance pupil of the optical system are presented. Studies have been carried out on the propagation of laser radiation along a horizontal atmospheric path for various levels of turbulence. The results are analyzed in terms of Zernike polynomials.

Stray light is a critical aspect for high performance optical instruments. When stray light control by design is insufficient to reach the performance requirement, correction by post-processing must be considered. This situation is encountered for example in the case of the Earth observation in-strument 3MI, whose stray light properties are complex due to the presence of many ghosts dis-tributed on the detector array. We implement an iterative correction method and discuss its con-vergence properties. Spatial and field binning can be employed to reduce the computation time but at the cost of a decreased performance. Interpolation of the stray light properties is required to achieve high performance correction. For that, two methods are proposed and tested. The first interpolate the stray light in the field domain while the second applies a scaling operation based on a local symmetry assumption. Ultimately, the scaling method is selected and a stray light reduction by a factor of 58 is obtained at 2σ (129 at 1σ) for an extended scene illumination.

In the study, a new correction method was applied to reduce error during detection on mixed pesticide residue in apples by using Raman spectra. Combined with self-built pesticide residues detection system by Raman spectroscopy and the application of surface enhancement technology, rapid real-time qualitative and quantitative analysis of deltamethrin and acetamiprid residues in apples can be applied effectively. In quantitative analysis, compared with the intensity value of characteristic peaks of single pesticide with same concentration, the intensity value of characteristic peaks of the two pesticides decreased after mixing the pesticides, which interferes the results severely. By comparing the difference in the intensity of characteristic peaks of single and mixed pesticides, a correction method is proposed to eliminate the influence of pesticides mixture. Characteristic peak intensity values of gradient concentration pesticide from 10-1 g•kg-1 to 10-6 g•kg-1 and Lagrangian interpolation are applied in the correction method. And a smooth surface is applied to describe the correction ratio of characteristic peak intensity. Through detecting the characteristic peak intensity values of the mixed pesticide, correction ratio will be obtained. Then real values of the peak intensity of pesticides and the content of each component of the mixed pesticide will be acquired by the correction method. Correlation coefficient of model validation exceeds 0.88 generally and Root Mean Square Error also decreases obviously after correction, which proved the reliability of the method.

This article introduces new method using ANN to control SVC in order to correct the source power factor of low voltage network. Two ANN approaches are investigated to design accurate and fast power factor correction (PFC) controller. First approach uses simple ANN (SANNA). Second approach uses cascaded ANN (CANNA). ANN regression, performance and the calculated error for both approaches are investigated to select between the two approaches. CANNA is selected as a better solution and it used to build the ANN PFFC controller using database, generated by MATLAB-Simulink, for standard three low voltage levels (240V, 220V and 110V). Nine test cases are carried out to validate the performance of proposed ANN PFC controller with a network has variable loads and low power factor (0.6 approximately). In order to extend the use of the controller to other voltage levels not included in the training process of the cascaded ANN, only the SVC is resized. Another nine cases are carried out with the same loads using the same ANN controller, as it is, to test its performance with the extended voltage level range (415V, 230V and 120V). The results show accurate and fast response in all test cases.

The transmission and analysis of data is one of the challenges of the 21st century. In the field of environmental measurement technology, existing broadband and wireless technologies have not been able to transmit data reliably and cost-effectively over long distances and in hard-to-reach places. LoRaWAN, an IoT technology, could be an energy-efficient, cost-effective and secure alternative as a narrowband technology in combination with battery-powered sensors and thus make an important contribution to the intelligent, largely wireless networking of objects, plants and machines (IoT), for example in the municipal sector. In addition to ecological and economic benefits, the quality of life in modern, intelligently networked cities can be enhanced by real time data acquisition. However, the prerequisite is that the quality of the data acquired via this method is sufficiently good. This paper therefore addresses the question of the quality of particulate matter data collected by low-cost sensors. To determine this, an SDS011 particulate matter sensor from Nova Fitness was ported to LoRaWAN. The sensor was installed next to a governmental measurement station. In a test that lasted five weeks, data from the SDS011 sensor were compared with those from the governmental station. Differences were identified and a correction approach was developed and applied. The efficiency of the approach was verified. Based on the results, it can be seen that the use of the low cost sensors has weaknesses. Problems can only be partially reduced. Nevertheless, the use of the low-cost sensors can be helpful for a flexible and cost effective collection of environmental data.

The CRISPR-Cas9 system is an emerging therapeutic tool with the potential to correct diverse ge-netic disorders. However, for gene therapy applications an efficient delivery vehicle is required, capable of delivering the CRISPR-Cas9 components into the cytosol of the intended target cell population. Once there, the ribonucleoprotein complex (RNP) can be transported into the nucleus. Lipid nanoparticles (LNP) serve as promising candidates for delivery of CRISPR-Cas9 RNP. These delivery vehicles have been optimized for the delivery of nucleic acids, such as mRNA. Co-delivery of Cas9 encoding mRNA with the accompanying sgRNA leads to translation of the Cas9 protein and formation of the Cas9 RNP inside the cell. Only recently, direct delivery of the CRISPR-Cas9 RNP complexes has been explored, which requires adjustments to the LNP formulation. In this study, the importance of buffer composition and cationic charge during RNP and ssDNA en-trapment in LNP are demonstrated. After optimizing several formulation parameters, LNP were prepared that were colloidally stable in human plasma and efficiently deliver the SpCas9 RNP and ssDNA for HDR-correction in reporter cells. Under optimal formulation conditions, gene knock-out and gene correction efficiencies as high as 80% and 20%, respectively were achieved at nanomolar CRISPR-Cas9 RNP concentrations.

Tuning nonlinearity of the laser is the main source which will deteriorate the spatial resolution in optical frequency domain reflectometry system. We develop methods for tuning nonlinearity correction in the OFDR system from the aspects of data acquisition and also the posting-processing. A zero-crossing detection scheme is researched and implemented by a customized circuit. Equal-spacing frequency sampling is therefore achieved in real-time. The maximum sensing distance can reach to the same length of the auxiliary interferometer. The zero-crossing detection for the beating frequency of 20MHz is achieved. Then, a nonlinearity correction method based on the self-reference method is proposed. The auxiliary interferometer is no longer necessary in this scheme. The tuning information of the laser is extracted by a strong reflectivity point at the end of the sensing arm in the main interferometer. The tuning information can then be used to resample the raw signal and the nonlinearity correction can be achieved. The spatial resolution test and the distributed sensing experiments are both performed based on this nonlinearity correction method. The results validated the feasibility of the proposed method. The method reduces the hardware and data burden for the system and has a potential value on the system integration and miniaturization.

Background: To rigorously derive easy to use formulae for the inclination angle for single cut rotation osteotomy that can be used for tibia deformity correction. Method: Three theorems were proven using trigonometric identities and concepts of linear algebra. These were rigorously shown. The three concepts were how to convert deformities in an AP/Lateral plane to an oblique plane deformity with a true angular magnitude of deformity; how to project an angular quantity from one plane to another; and the calculation of the inclination angle for the oblique osteotomy plane. All figures in this article were created by the authors of this paper. Results: From the formula derived, a statistical t-test was performed that showed no significant difference between the formula derived in this paper and the original Sangeorzan paper charts (p=0.0079). Conclusions: The formulae described in this article are a method to accurately calculate the inclination angle of the osteotomy for a single cut rotational osteotomy for tibial deformity correction. Clinical Relevance: The article gives a deeper understanding of fundamental concepts behind deformity correction and provides an easy-to-use mathematical formula to calculate the osteotomy inclination for single cut rotational osteotomies.

Crouch gait is a motor complication commonly associated with cerebral palsy, spastic diplegia, stroke, and motor-neurological pathologies, broadly defined as knee flexion in excess of 20° in the gait cycle. Uncorrected crouch gait results in fatigue, joint degradation, and loss of ambulation. Torsion springs have been used in cycling to store energy in knee flexion to reduce fatigue in the quadriceps during knee extension. SolidWorks was used to design a passive exoskeleton for the knee, incorporating torsion springs of stiffnesses 20,000 N/mm and 30,000 N/mm at the knee joint to correct four different crouch gaits. OpenSim was used to gather data from moments produced and knee angles from each crouch gait and the normal gait. Motion analysis of the exoskeleton was simulated using knee angles for each crouch gait and compared with moments produced with the normal gait moments in the stance phase of the gait cycle. All crouch gait moments were significantly reduced, and the correction of peak crouch moments was achieved corresponding to the normal gait cycle during the stance phase. These results offer significant potential for nonsurgical and less invasive options for wearable exoskeletons in crouch gait correction.

An improved FSM method is used in geophysical and environmental corrections to enhance the final product of the along track Jason-2 SLA data and extend it near the Red Sea borders. In this study the ionospheric correction range, wet tropospheric correction range, sea state bias correction range and dry tropospheric correction range are enhanced and improved using FSM01, which helped to retrieve three more tracks (106, 170 and 234), earlier neglected by the distribution centers, and extend the tracks towards the coast. The FSM01 SLA is compared with Jason-2 SLA and AVISO SLA for the available 5 tracks, in which the FSM01 SLA show a good agreement and higher correlation with the Jason-2 SLA compared with that of AVISO, in addition to that it fills the gaps in the times series of all tracks. The new retrieved tracks also compared with those retrieved by AVISO, both data show similar variability, with FSM01 SLA show no gaps in the time series. The FSM01 SLA also extended towards the coast and show high correlation with the coastal tide measurements.

Abstract: The EMU(electric multiple units) traction motors are powered by converters. The PWM(pulse width modulation) voltage increases the voltage stress borne by the motor insulation system, making the ITSC(inter-turn short-circuit) fault more prominent. An index based on short-circuit thermal power was proposed in the article to evaluate the non-metallic ITSC faults degree. The apFFT(all phase FFT) time-shift phase difference correction with double Hanning-windows is used to calculate the fundamental frequency of the traction motor's ZSVC（zero se-quence voltage component）, the fundamental amplitudes of ZSVC and three-phase current. The five parameters are used as fault features to train the SVM (support vector machine)fault diagnosis model. The SVM hyper-parameters C and g are optimized by K-CV (K fold cross-validation) and grid search methods. The experimental verification was carried out by the EMU electric traction simulation experimental platform. According to the non-metallic degree index proposed in this article, the experimental samples were divided into three categories, normal, incipient and serious fault samples. The ITSC fault diagnosis accuracy was 100% on the training data set and 93.33 % on the test data set. There was no misclassification between normal and serious ITSC fault samples.

Nonlinear electrodynamics is known as the generalizations of Maxwell electrodynamics at strong fields and presents interesting features such as curing the classical divergences present in the linear theory when coupled to general relativity. In this paper, we consider the asymptotically flat Reissner-Nordstr\"om black hole solution with higher-order magnetic correction in Einstein-nonlinear-Maxwell fields. We study the effect of the magnetic charge parameters on the black hole, viz. weak deflection angle of photons and massive particles using Gauss-bonnet theorem. Moreover, we apply the Keeton-Petters formalism to confirm our results of the weak deflection angle. Apart from vacuum, their influence in the presence of different media such as plasma and dark matter are probed as well. Finally, We examine the black hole shadow cast using the null-geodesics method and investigate its spherically in-falling thin accretion disk. Our inferences show how the magnetic charge parameter $p$ affects the other physical quantities; so, we impose some constraints on this parameter using the observations from the Event Horizon Telescope.

Satellite-derived soil moisture observations typically rely on bias-correction (BC) prior to assimilation in land surface models. Current techniques include rescaling or machine learning approaches to map the observations to the modelled soil moisture climatology. However, these approaches do not allow for non-stationary biases and recalibrations require a long training period, which is not always feasible. In this study we evaluate a two-stage filter to dynamically correct soil moisture biases from satellite-derived active ASCAT C-band and passive L-band SMOS surface soil moisture observations in the European Centre for Medium Range Weather Forecasts (ECMWF) land data assimilation system. This adaptive soil moisture BC approach is designed to complement the operational seasonal rescaling of the ASCAT observations and the SMOS neural network retrieval used at ECMWF, while allowing the assimilation to correct sub-seasonal scale errors. Over a 3-year test period, the adaptive BC reduces the seasonal-scale first guess-observation departures by 20-30% for ASCAT and SMOS. The adaptive BC leads to (i) slight improvements in soil moisture performance against in situ data; and (ii) moderate but statistically significant reductions in the 1-5 day relative humidity forecast errors in the boundary layer of the northern hemisphere midlatitudes.

We report the first correction by Prime editing of a mutation in the RYR1 gene, paving the way to gene therapies for RYR1-related myopathies. The RYR1 gene codes for a calcium channel named Ryanodine receptor 1, which is expressed in skeletal muscle fibers. The failure of this channel causes muscle weakness in patients, which degenerates into motor disabilities. Currently, there are no effective treatments for these diseases, which are mainly caused by point mutations. Prime editing allows the modification of precise nucleotides in the DNA. Our results showed a 59% correction rate of the T4709M mutation in the RYR1 gene in human myoblasts by RNA delivery of the Prime editing components. It is to be noted that the T4709M is recessive, and thus, persons having a heterozygous mutation are healthy. These results are the first demonstration that it is possible to correct mutations in the RYR1 gene.

The main objective of this study is to develop a Hapke photometric model that is suited for Chang’E-1 (CE-1) Interference Imaging Spectrometer (IIM) data. We first divided the moon into three areas including ‘maria’, ‘new highland’ and old ‘highland’ with similar photometry characteristic based on the Hapke parameters of the moon derived from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) multispectral data. Then, we selected the sample data in the ‘maria’ area and obtained a new set of Hapke model’s parameters that can best fit these data. Result shows that photometric correction using Hapke model with these new derived parameters can eliminate the effect of variations in viewing and luminating geometry, especially ‘opposition surge’, more efficiently than the empirical model. The corrected mosaic shows no significant artifacts along the tile boundaries, and more detailed information of the image can be exhibited due to a better correction of ‘opposition surge’ at small phase angle (g <15°).

This paper presents the experimental implementations of the mathematical models and algorithms developed in Part I. Two experiments are carried out. The first experiment aims at the determinations of the correction coefficients of the mathematical model. The dot grid target is measured and the measurement data are processed by our developed and validated algorithms introduced in Part I. The values of the coefficients are indicated and analysed. Uncertainties are evaluated with implementation of the Monte Carlo method. The second experiment measures a different area of the dot grid target. The measurement results are corrected according to the coefficients determined in the first experiment. The mean residual between the measured points and their corresponding certified values reduced 29.6% after the correction. The sum of squared errors reduced 47.7%. The methods and the algorithms for raw data processing, such as data partition, fittings of dots’ centres, K-means clustering, etc., are the same for both two experiments. The experimental results demonstrate that our method for the correction of the errors produced by the movement of lateral stage of confocal microscope is meaningful and practicable.

The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, guided by observed flows and available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT- simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.

This study describes the characteristics of women who contacted an active program performing uterus transplantation (UTx) in the US expressing interest in becoming a uterus transplant recipient or a living donor. Basic demographic and self-reported clinical information was collected from women who contacted any of the three US UTx programs from 2015 to July 2022. The three centers received 5194 inquiries about becoming a UTx recipient during the study timeframe. Among those reporting a cause of infertility, almost all (4066/4331, 94%) were absence of a uterus, either congenitally (794/4066, 20%) or secondary to hysterectomy (3272/4066, 80%). The mean age was 34 years, and 49% (2545/5194) had at least one child at the time of application. The two centers using living donors received 2217 inquiries about becoming living donors. The mean age was 34 years, and 60% (1330/2217) had given birth to ≥1 child. While most of the UTx clinical trial evidence has focused on young women with congenital absence of the uterus, these results show interest from a much broader patient population in terms of age, cause of infertility, and parity. These results raise questions about whether and to what extent the indications and eligibility criteria for UTx should be expanded as the procedure transitions from the experimental phase to being offered as a clinical treatment.

This study investigates the application of Unmanned Aerial Vehicles (UAVs) equipped with a Micasense RedEdge-MX multispectral camera for the estimation of Secchi Depth (SD) in inland water bodies. The research analyzed and compared five sun-glint correction methodologies — Hedley, Goodman, Lyzenga, Joyce, and threshold removed glint to model the SD values derived from UAV multispectral imagery, highlighting the role of reflectance accuracy and algorithmic precision in SD modeling. While Goodman's method showed a higher correlation (0.92) with in situ SD measurements, Hedley's method exhibited the smallest average deviation (0.65 m), suggesting its potential in water resource management, environmental monitoring, and ecological modeling. The study also underscored the Quasi-Analytical Algorithm (QAA) potential in estimating SD due to its flexibility to process data from various sensors without requiring in situ measurements, offering scalability for large-scale water quality surveys. The accuracy of SD measures, calculated using QAA, was related to variability in water constituents of coloured dissolved organic matter and the solar zenith angle. A practical workflow for SD acquisition using UAVs and multispectral data was proposed for monitoring inland water bodies.

The objective of this study is to clarify the effect of restoring the lowered masticatory muscle functional pressure and correcting the imbalance of bilateral masticatory muscle functional pressure on jawbone growth during growth and development with quantitative evaluation of the changes in micro/nanostructural characteristics of entheses. Male Wistar rats aged 4 weeks were divided into an experimental group injected with a botulinum toxin serotype A (BoNT/A) formulation to reduce muscle function (BTX group) and a control group (CTRL group). They were euthanized after 6, 8, 10, 12, and 16 weeks after measuring the difference between the midline of the upper and lower incisors. The mandibles were harvested for histological examination, second harmonic generation imaging, and quantitative evaluation of biological apatite (BAp) crystal alignment. The midline difference decreased with age in weeks. In rats from 6 weeks after BoNT/A administration to 12 weeks after administration, collagen fibre bundle diameter was significantly smaller in the BTX group; the difference between the two groups decreased with increasing age. BAp crystal alignment was significantly different on the X-axis and the Y-axis on the BTX group from 6 weeks after BoNT/A administration to 10 weeks after administration. Asymmetry of mandibular bone formation caused by load imbalance during growth could be corrected by adjustment of the function of the masseter muscle on either side.

Growth-preserving instrumentation techniques are utilized in early-onset scoliosis (EOS) cases requiring surgical intervention. Shilla technique corrects the deformity and may reduce the need for surgical treatment with its growth-directing effect. As with other techniques, various prob-lems can be encountered following the administration of the Shilla technique. The aim of this study was to examine the effect of complications encountered with Shilla treatment on correction and growth. Sixteen patients with a follow-up period of at least 1 year who received Shilla growth guidance for EOS were included in the study. No complications occurred in 50% cases and no unplanned surgery was required. Of the remaining 8 patients with postoperative im-plant-related complications (50%), 6 (37.5%) required unplanned surgery; this consequently caused implant failure in the proximal region in 5 cases (31.25%) and deep tissue infection around the implant in 1 case (6.25%). Deformity correction, spine length, and quality-of-life scores significantly improved in EOS through Shilla growth guidance. Although implant-related com-plications were observed and related unplanned surgeries were required with Shilla growth guidance in our patients, these complications did not have a significant negative effect on correc-tion and spine growth.

In this work, we propose simple and robust technique for the retrieval of underlying surface spectral albedo using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi - zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral albedo for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.

Accurate assessment and projections of extreme climate events requires the use of climate datasets with no or minimal error. This study uses quantile mapping bias correction (QMBC) method to correct the bias of five Regional Climate Models (RCMs) from the latest output of Rossby Climate Model Center (RCA4) over Kenya, East Africa. The outputs were validated using various scalar metrics such as Root Mean Square Difference (RMSD), Mean Absolute Error (MAE) and mean Bias. The study found that the QMBC algorithm demonstrate varying performance among the models in the study domain. The results show that most of the models exhibit significant improvement after corrections at seasonal and annual timescales. Specifically, the European community Earth-System (EC-EARTH) and Commonwealth Scientific and Industrial Research Organization (CSIRO) models depict exemplary improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model show little improvement across various timescales (i.e. March-April-May (MAM) and October-November-December (OND)). The projections forced with bias corrected historical simulations tallied observed values demonstrate satisfactory simulations as compared to the uncorrected RCMs output models. This study has demonstrated that using QMBC on outputs from RCA4 is an important intermediate step to improve climate data prior to performing any regional impact analysis. The corrected models can be used for projections of drought and flood extreme events over the study area. This study analysis is crucial from the sustainable planning for adaptation and mitigation of climate change and disaster risk reduction perspective.

The paper presents the design stages of a single-phase Silicon Carbide bidirectional DC-AC converter. This includes the LCL filter design responsible to meet grid connection requirements. A 3kW laboratory prototype of the power converter is built employing a low-cost phase locked loop and its results are presented. The design of the low-cost phase locked loop and its implementation are depicted in some detail.

We present the update of the Snow and Ice (SICE) property retrieval algorithm proposed initially by Kokhanovsky et al. (2019). The algorithm is based on the spectral measurements of Ocean and Land Color Instrument (OLCI) onboard Sentinel-3 satellites combined with the asymptotic radiative transfer theory valid for weakly absorbing turbid media. The main improvements include the introduction of a new atmospheric correction, retrieval of snow impurity load and properties, retrievals for partially snow-covered ground and also accounting for various thresholds to be used to assess the retrieval quality. The algorithm is available as python and Fortran packages at https://github.com/GEUS-SICE/pySICE. The technique can be applied to various optical sensors (satellite and ground-based) operated in the visible and near infrared regions of electromagnetic spectra.

In order to perform multi-degree-of-freedom motion measurements of marine machinery such as ship-borne mechanical platform in an absolute environment without a reference, absolute measurement methods using acceleration sensors and tilt gyroscopes are typically employed. However, due to the influence of wave forces on ship-borne mechanical platform, the coupling between different degrees of freedom can cause mutual interference, resulting in significant sensor measurement disturbances that make efficient computation and real-time analysis challenging. Specifically, when ship-borne mechanical platform swings, the proof mass of the acceleration sensor produces an undesirable signal output in the vertical direction, which leads to imprecise acceleration integration, thereby affecting accurate motion collection and posture estimation. To address these challenges, by analyzing the influence of the inclination angle of the ship-borne mechanical platform on the sensor measurement, and using the working principle of the acceleration sensor and angle sensor, a correction method for the motion measurement of the ship-borne mechanical platform based on multi-sensor fusion is proposed. In this article, we first analyze the influence of inclination angle on the integral effect in the heave direction. Then the configuration using four groups of acceleration sensors to correct the integral effect is proposed. Finally, the optimal inclination angle is determined through Kalman filtering based on the measured value of angle sensors and estimated values from the acceleration sensor sets. Experiments have proved that the average error of the corrected heave displacement signal is 25.34 mm, which is better than the integral displacement signal of a single acceleration sensor. At the same time, the acceleration sensor is used to calculate the roll angle and pitch angle of the ship-borne mechanical platform, and combined with the angle sensor signal to perform Kalman filtering, which filters out the errors caused by the shaking and instability of the mechanical platform, and can more accurately estimate the true inclination of the platform. Therefore, this method can enhance the precision and accuracy of the ship-borne mechanical platform motion signal acquisition, providing more valuable experimental data for research in marine engineering and related fields.

Plant loss in experimental plots occurs occasionally in field experiments with coffee crops. In breeding programmes, such loss can be extremely harmful, especially when the statistical analysis methods used are not consistent with the data generated in the experiments. In this study, we analysed a set of productivity data to determine whether the compensatory effect occurs in coffee crops, analyse the need for correcting the number of failures in experiments, and identify the best stand correction method to use. Productivity data from six harvests of 11 experiments with Coffea arabica plants were used. The experiments were implemented in a randomised block design, with four replications and six plants per plot. The following stand correction methods were evaluated: rule of three, Zuber [1], Vencovsky and Cruz [2]covariance of the average or ideal stands, and Cruz [3] and compared to data without correction adjustments. The most adequate correction methods were chosen based on the existence of genetic variance, selective accuracy, and progeny ordering. The compensatory effect was evident from the analysed data, with stand correction shown to be beneficial in progeny competition experiments. The covariance methods using average or ideal stands presented the best results, followed by the method proposed by Cruz [3]. The rule of three and Zuber [1] methods showed unsatisfactory results and are not recommended for stand correction in progeny competition experiments with coffee crops

X-band dual-polarization phased array radar (XPAR-D) possesses high temporal-spatial resolutions and plays a significant role in detecting meso- and micro-scale convective systems. However, the precipitation attenuation it endures necessitates an effective correction method. This study selected radar data from XPAR-D at the peak of Maofeng Mountain in Guangzhou during May 16-17, 2020 from three precipitation stages after quality control. Attenuation coefficients are calculated for different precipitation types through scattering simulations of raindrop size distribution (RSD) data. Drawing upon this, an attenuation correction algorithm (MZH-KDP method) is proposed for radar reflectivity factor (ZH) according to different raindrop types, and is compared to the ZH-KDP method currently in use. The results indicate that the attenuation amount of XPAR-D echoes depends on the attenuation path and echo intensity. When the attenuation path is shorter and the echo intensity is weaker, the amount of attenuation and correction is smaller. Difficulties arise when there are noticeable deviations in such a situation, which are challenging to solve via attenuation correction methods. Longer attenuation paths and stronger echoes highlight the advantages of the MZH-KDP method, while the ZH-KDP method tends to overcorrect the bias. The MZH-KDP method outperforms the ZH-KDP method for different precipitation types. The superior correction capability of the MZH-KDP method provides a significant advantage in improving the performance of XPAR-D for the detection of extreme weather.

The purpose of this study is to develop a cranial traction therapy program to help correct facial asymmetry of the hard tissues through the means of the treatment of soft tissues—a non-surgical therapeutic method for the correcting of facial asymmetry. We have formed a group of experts who have agreed to the study. In the primary survey, open questions were used. In the second survey, the results of the first survey were summarized and the degree of agreement was presented to the questions in each category. In the third survey, we conducted a statistical analysis of the degree of agreement on each item of question. All surveys also performed email. The distribution was calculated using the SPSS (ver.23.0) program, and the mean difference between the result and X² was calculated. The significance level was set to p&lt;.05. Most of the questions attained a certain level of consensus by the experts (average of 4.0 or higher), it can be said that most are important and suitable questions. the results regarding the degree of importance for each of the points of evaluation made by the groups of experts in both the second and third stage of the cranial traction therapy program were verified using content validity ratio (CVR 77). The ratio for the cranial traction 13 points of evaluation was within the range of 0.40∼1.00, so the Delphi program for the cranial traction therapy verified that the content was valid.

This research work deals hybrid control system based integrated Cuk converter fed brushless DC motor (BLDCM) for power factor correction. In this work, moth-flame optimization (MFO) and fuzzy logic controller (FLC) has been combined and moth –flame fuzzy logic controller (MFOFLC) has been proposed. Firstly, the BLDC motor modelling is composed with power factor correction (PFC) based integrated Cuk converter and BLDC speed is regulated using variable DC-Link inverter voltage which makes low switching operation with less switched losses. Here, with the use of switched inductor, the task and execution of proposed converter is redesigned. The DBR (diode bridge rectifier) trailed by proposed PFC based integrated Cuk converter operates in discontinuous inductor conduction mode(DICM) for achievement of better power factor.MFO is exhibited for gathering of dataset from the input voltage signal. At that point separated datasets is send to FLC to improve the updating function and minimization of torque ripple. However, our main objective is to assess adequacy of proposed method, the power factor is broke down. The execution of the proposed control methodology is executed in MATLAB/Simulink working platform and the display is assessed with the existing techniques.

Neuromonitoring of the efferent nerve impulses transmission in the spinal cord tracts during surgical scoliosis treatment makes it possible to assess whether the functional status is deteriorating, affecting the procedure's safety. Is there any relationship between pre- and intraoperative motor evoked potentials recordings and does idiopathic scoliosis (IS) surgical correction improve directly the spinal efferent transmission? This study aimed to compare the results of surface recorded electromyography (EMG), electroneurography (ENG, M and F-waves), and especially motor evoked potentials (MEP) from tibialis anterior (TA) muscle bilaterally in 353 girls with the right idiopathic scoliosis (types 1A-4C according to Lenke classification). It has not yet been documented whether the results of MEPs recordings induced by transcranial single magnetic stimulus (TMS, pre – and postoperatively) and trains of electrical stimuli (TES; intraoperatively in T0-before surgery, T1 – after pedicle screws implantation, T2 – after scoliosis curvature distraction and derotation following two rods implantation) can be compared for diagnostic verification of improvement of the spinal neural transmission. The study also attempted to determine whether the constant level of optimal anesthesia during the certain surgical steps of scoliosis treatment affects the parameters of MEPs recorded during neuromonitoring procedures. No neurological deficits have been observed postoperatively. Values of amplitudes but not latencies in MEPs recordings evoked with TMS in IS patients compared before and after surgery indicated a slight improvement in the efferent transmission of neural impulses within the fibers of the spinal tracts postoperatively. Results of all neurophysiological studies in IS patients were significantly asymmetrical and recorded worse on the concave side, suggesting greater neurological motor deficits at p=0.04. This asymmetry had been significantly reduced following IS surgery. The surgeries in IS patients brought significant improvement (p=0.04) in parameters of amplitudes of sEMG recordings, however reflecting still the consequences of the neurogenic injury of TA muscle motor units. ENG studies results indicated the symptoms of the axonal type injury in peroneal motor fibers improved only on the concave side at p=0.04 in parallel with the significant improvement of F-waves parameters, which suggests that surgeries might result in the lumbar ventral roots decompression. There were not detected significant differences in amplitudes or latencies of MEPs induced with TMS or TES comparing the parameters recorded preoperatively (one day before surgery) and intraoperatively in T0. The amplitudes of TES evoked MEPs increased gradually at p=0.04 in the subsequent periods (T1 and T2) of observation. The significant reduction of MEPs latency at p=0.05 was observed only at the end of the IS surgery. Studies on the possible connections between the level of anesthesia fluctuations and the required TMS stimulus strength, as well as the MEPs amplitude changes measured in T0-T2 revealed lack of relationships. It is not likely that they could be the factors influencing the efferent transmission in spinal pathways beside the surgical procedures. Considering that MEPs amplitude parameter reflects the number of axons excited from the motor cortex and transmitting the efferent impulses via spinal descending tracts in the white matter, pre- (TMS evoked) and intraoperative (TES evoked) recordings are reliable for evaluating the patient’s neurological status before and during surgical scoliosis correction procedures. The results of this study indicate an agreement between preoperative and early-intraoperative evaluations with these both diagnostic methods. An increase of MEPs amplitude parameters recorded on both sides after scoliosis surgery proves immediate improvement of the total efferent spinal cord transmission. Considering comparative pre- and postoperative sEMG and ENG recordings it can be concluded that surgeries might directly result in the additional lumbar ventral roots decompression. Our results of the tests on the possible variability of the anesthesia level on the parameters of intraoperative recorded MEPs show no clear relationships. We can conclude that MEPs parameters changes are determined by the surgery procedures during neuromonitoring, not the anesthesia conditions if they are kept stable, which influences a decrease in the number of false-positive neuromonitoring warnings. Further studies on a larger population of patients with long-lasting observation postoperatively are required to confirm the presented conclusions on the direct influences of scoliosis surgery on improvement of the motor function in patients with IS.