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Objectives: To illustrate in-depth validation of prediction models developed on multicenter data. Methods: For each hospital in a multicenter registry, we evaluated predictive performance of a 30-day mortality prediction model for transcatheter aortic valve implantation (TAVI) using the Netherlands heart registration (NHR) dataset. We measured discrimination and calibration per hospital in a leave-center-out analysis (LCOA). Meta-analysis was used to calculate I2 values per performance metric from the LCOA and to compute mean and confidence interval (CI) estimates. Case mix differences between studies were inspected using the framework of Debray et al. for understanding external validation. We also aimed to discover subgroups (SGs) with high model prediction error (PE) and their distribution over the centers. Results: We studied 16 hospitals with 11,599 TAVI patients with an early mortality of 3.7%. The models’ area under the curve (AUCs) had a wide range between hospitals from 0.59 to 0.79, and miscalibration occurred in seven hospitals. Mean AUC from meta-analysis was 0.68 (95% CI 0.65-0.70). I2 values were 0%, 74%, and 0% for AUC, calibration intercept and slope, respectively. Between-hospital case-mix differences were substantial, and model transportability was low. One SG was discovered with marked global PE and was associated with poor performance on validation centers. Conclusion: The illustrated combination of approaches provides useful insights to inspect multicenter-based prediction models, and it exposes their limitations in transportability and performance variability when applied to different populations.

OBJECTIVES: In biomedical research, spin is the overinterpretation of findings, and it is a growing concern. To date, the presence of spin has not been evaluated in prognostic model research in oncology, including studies developing and validating models for individualized risk prediction. STUDY DESIGN AND SETTING: We conducted a systematic review, searching MEDLINE and EMBASE for oncology-related studies that developed and validated a prognostic model using machine learning published between 1st January, 2019, and 5th September, 2019. We used existing spin frameworks and described areas of highly suggestive spin practices. RESULTS: We included 62 publications (including 152 developed models; 37 validated models). Reporting was inconsistent between methods and the results in 27% of studies due to additional analysis and selective reporting. Thirty-two studies (out of 36 applicable studies) reported comparisons between developed models in their discussion and predominantly used discrimination measures to support their claims (78%). Thirty-five studies (56%) used an overly strong or leading word in their title, abstract, results, discussion, or conclusion. CONCLUSION: The potential for spin needs to be considered when reading, interpreting, and using studies that developed and validated prognostic models in oncology. Researchers should carefully report their prognostic model research using words that reflect their actual results and strength of evidence. ispartof: JOURNAL OF CLINICAL EPIDEMIOLOGY vol:157 pages:120-133 ispartof: location:United States status: published

The Brewer ozone spectrophotometer (the Brewer) is one of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW)'s standard ozone-monitoring instruments since the 1980s. The entire global Brewer ozone-monitoring network is operated and maintained via a hierarchical calibration chain, which started from world reference instruments that are independently calibrated via the primary calibration method (PCM) at a premium site (National Oceanic and Atmospheric Administration's (NOAA) Mauna Loa Observatory, Hawaii). These world reference instruments have been maintained by Environment and Climate Change Canada (ECCC) in Toronto for the last 4 decades. Their calibration is transferred to the travelling standard instrument and then to network (field) Brewer instruments at their monitoring sites (all via the calibration transfer method; CTM). Thus, the measurement accuracy for the entire global network is dependent on the calibration of world reference instruments. In 2003, to coordinate regional calibration needs, the Regional Brewer Calibration Center for Europe (RBCC-E) was formed in Izaña, Spain. From that point, RBCC-E began calibrating regional references also via PCM instead of CTM. The equivalency and consistency of world and regional references are then assured during international calibration campaigns. In practice, these two calibration methods have different physical requirements, e.g., the PCM requires a stable ozone field in the short term (i.e., half-day), while the CTM would benefit from larger changes in slant ozone conditions for the calibration periods. This difference dictates that the PCM can only be implemented on Brewer instruments at certain sites and even in certain months of the year. This work is the first effort to use long-term observation records from 11 Brewer instruments at four sites to reveal the challenges in performing the PCM. By utilizing a new calibration simulation model and reanalysis ozone data, this work also quantifies uncertainties in the PCM due to short-term ozone variability. The results are validated by real-world observations and used to provide scientific advice on where and when the PCM can be performed and how many days of observations are needed to achieve the calibration goal (i.e., ensure the calibration uncertainty is within a determined criterion, i.e., ≤5 R6 units; R6 is a measurement-derived double ratio in the actual Brewer processing algorithm). This work also suggests that even if the PCM cannot be used to deliver final calibration results for mid- or high-latitude sites, the statistics of the long-term PCM fitting results can still provide key information for field Brewer instruments as stability indicators (which would provide performance monitoring and data quality assurance).

A Position Calibration Method (PCM) is proposed for a single cell measurement with Electrochemical Impedance Spectroscopy (EIS). It improves the measurement accuracy by reducing the error induced by position difference. First, the relationship between the impedance and the position is explored with numerical simulation. The impedance is calculated in different positions of the single cell with the finite model. Second, a mathematical model is established based on the relationship between the impedance and the position. Then, the experiments are conducted to verify the valid of the PCM. In the experiments, Na2O∙CaO∙6SiO particles and Zebrafish eggs are used. The result shows that the impedance near the electrode is less than the center of the sensor, while the impedance of the sensor center is less than the sensor boundary, which is the same as the numerical simulation. Finally, a coincidence degree is employed to evaluate the position calibration method. After position calibration, the coincidence degree of numeric simulation could reach to 99.999%, and the experimental coincidence degree reaches to 99.87%. In this paper, the reasons of impedance varying with positions are also explored. The electric field intensity turns out to be the main internal factor that causes the impedance varying with positions. Furthermore, the PCM is expected to realize the detection of a cell structure.

Background: Accurate camera and hand-eye calibration are essential to ensure high-quality results in image-guided surgery applications. The process must also be able to be undertaken by a nonexpert user in a surgical setting. Purpose: This work seeks to identify a suitable method for tracked stereo laparoscope calibration within theater. Methods: A custom calibration rig, to enable rapid calibration in a surgical setting, was designed. The rig was compared against freehand calibration. Stereo reprojection, stereo reconstruction, tracked stereo reprojection, and tracked stereo reconstruction error metrics were used to evaluate calibration quality. Results: Use of the calibration rig reduced mean errors: reprojection (1.47 mm [SD 0.13] vs. 3.14 mm [SD 2.11], p-value 1e−8), reconstruction (1.37 px [SD 0.10] vs. 10.10 px [SD 4.54], p-value 6e−7), and tracked reconstruction (1.38 mm [SD 0.10] vs. 12.64 mm [SD 4.34], p-value 1e−6) compared with freehand calibration. The use of a ChArUco pattern yielded slightly lower reprojection errors, while a dot grid produced lower reconstruction errors and was more robust under strong global illumination. Conclusion: The use of the calibration rig results in a statistically significant decrease in calibration error metrics, versus freehand calibration, and represents the preferred approach for use in the operating theater.

The efficacy of the application of traffic models depends on a successful process of model calibration. Microsimulation models have a significant number of input parameters that can be optimized in the calibration process. This paper presents the optimization of input parameters that are difficult to measure or unmeasurable in real traffic conditions and includes parameters of the driver’s behavior and parameters of Wiedemann’s psychophysical car-following model. Using neural networks, models were generated for predicting travel time and queue parameters and were used in the model calibration procedure. This paper presents the results of a comparison of five different applications of neural networks in calibrating the microsimulation model. The VISSIM microsimulation traffic model was selected for calibration and field measurements were carried out on two roundabouts in a local urban transport network. The applicability of neural networks in the process of calibrating the microsimulation models was confirmed by comparison of the modelled and measured data of traffic indicators in real traffic conditions. Methods of calibration were validated with two sets of new measured data at the same intersection where the calibration of the model was carried out. The third validation was made at the intersection in a different location. The selection of the optimal calibration methodology is based on the model accuracy between the simulated and measured data of traveling time, as well as queue parameters. The microsimulation model provides access to the raw data of observed traffic parameters for each vehicle in the simulation. The dataset of the calibrated model simulation results of all travel times of the selected traffic flow was compared with the dataset of the measured field data to determine whether the data are statistically significantly different or not.

A transfer-learning-based method for accelerating power-only calibration of phased array antennas by combining the conventional array theory with deep learning is presented in this communication. The existing power-only calibration methods either require a significant number of measurement cycles or have restrictive phase shifter resolution requirements. The proposed array calibration method uses a surrogate model to calibrate all the array elements in one pass without restricting phase resolution requirements. We developed a novel feature extraction scheme (FES) that picks out the most important power features resulting in reduced measurement cycles. The burden of data acquisition for model training is further reduced by relational knowledge transfer learning. The surrogate model acquires its general calibration capability from massive theoretical data, which is easily collected by the radiation multiplication theorem, and captures the detailed nonideal response from a small number of simulations. The proposed methodology has been demonstrated and tested on several arrays for validation. The effectiveness and performance of the method have been verified, and hence, it can serve as a complementary tool to accelerate the calibration process of phased antenna arrays.

article describes a method used to calibrate 3-D freehand ultrasound systems based on phantoms with parallel wires forming two perpendicular planes, such as the usual general-purpose commercial phantoms. In our algorithm, the phantom pose is co-optimized with the calibration to avoid the need to precisely track the phantom. We provide a geometrical analysis to explain the proposed acquisition protocol. Finally, we give an estimate of the system accuracy and precision based on measurements acquired on an independent test phantom. We obtained error norms of 1.6 mm up to 6 cm of depth and 3.5 mm between 6 and 14 cm of depth, in total average. In conclusion, it is possible to calibrate ultrasound tracked-probe systems with a reasonable accuracy based on a general-purpose phantom. Contrarily to most calibration methods that imply the construction of the phantom, the present algorithm is based on a standard phantom geometry that is commercially available. (E-mail: sandra. marcadent@epfl.ch) (c) 2022 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

The effect of measurement cables on impulse voltage measurement system signal transmission has been widely ignored by the high-voltage community. During the last years, the cable length effects have been reported, but the results have not been fully consistent. This article characterizes cable effects on a resistive impulse voltage divider system using three different empirical test methods. The used methods are step response analysis using convolution, low-voltage analysis with an impulse calibrator, and high-voltage impulse analysis with an impulse generator. Results show that with reasonable cable lengths up to 25 m, the time parameter errors increase almost linearly with the cable length. The tested divider system was not sensitive to the tolerance of the 50 Ω termination at the cable end. The cable effect seems to be related to the current flowing through the cable, and the related errors can be reduced using a high-impedance termination at the digitizer end of the cable. Either short cable or high-impedance termination at the digitizer end is recommended for this type of divider. In addition, the results show that the three applied methods produce comparable results.

The fast and in situ measurement of the complex magnetic susceptibility stands a potential geological tool for enhanced characterization of rocks and comprehension of the geological context of the landing and exploration sites when used on board planetary rovers. The real part of susceptibility is related to the capability to acquire magnetization and the imaginary part, with resistivity and magnetic energy loss mechanism of rocks. Therefore, the determination of the rocks’ susceptibility provides key information as to the need for the presence of water in the formation of certain minerals, which can be used as one of the rocks selection criteria, in sample return missions. Previous work has been done in the conception of a novel portable instrument, based on magnetic induction, to measure the complex susceptibility of rocks in the context of planetary exploration. The next step is to create a comprehensive calibration procedure to extract magnetic properties information from the direct readings. This work describes a novel instrument calibration methodology. The calibration of the novel instrument comprises a comparative methodology with representative patterns for the real and the imaginary components of the susceptibility. Therefore, the work also includes calibration sample conception, manufacture, and characterization by different techniques. The authors would like to acknowledge INTA staff for the support and Ferroxcube for the ferrite selection and samples.Spanish Program for Research, Development, and Innovation (Grant Number: ESP2017-88930-R and PID2020-119208RB-I00:MagAres) and European Union’s Horizon 2020 Research and Innovation Program (Grant Number: 730041) Peerreview

In this work, we consider the self-calibration problem of joint calibration and direction-of-Arrival (DOA) estimation using acoustic sensor arrays. Unlike many previous iterative approaches, we propose solvers that can be readily used for both linear and non-linear arrays for jointly estimating the sensor gain, phase errors, and the source DOAs. We derive these algorithms for both the conventional element-space and covariance data models. We focus on sparse and regular arrays formed using scalar sensors as well as vector sensors. The developed algorithms are obtained by transforming the underlying non-linear calibration model into a linear model, and subsequently by using convex relaxation techniques to estimate the unknown parameters. We also derive identifiability conditions for the existence of a unique solution to the self-calibration problem. To demonstrate the effectiveness of the developed techniques, numerical experiments, and comparisons to the state-of-The-Art methods are provided. Finally, the results from an experiment that was performed in an anechoic chamber using an acoustic vector sensor array are presented to demonstrate the usefulness of the proposed self-calibration techniques.

An assay using HPLC with fluorescence (FL) detection method for monitoring native FL of tocilizumab (TCZ) in human serum combined with extremely simple and rapid pretreatment without any antigen-antibody reaction was developed. Good separation of TCZ was achieved within 13 min on a Presto FF-C18 column (100 × 4.6 mm i.d., 2 µm). Simple pretreatment with acetonitrile containing primary and secondary alkylamines having longer than C3 in the alkyl chain removed immunoglobulin G subclass 1 and TCZ could be recovered selectively. The spiked calibration curve of TCZ in human serum showed good linearity in the range of 40-1000 µg/mL (r 0.997). The lower limit of quantitation (S/N = 10) of the TCZ was 19.7 µg/mL. The accuracy was within 103.5-114.9%, and the intra- and inter-day precisions as relative standard deviations were less than 5.3 and 7.8% (n = 5), respectively. The recovery of TCZ was 42.2 ± 3.4% (n = 3). The TCZ in pretreated sample was confirmed to be stable for 6 h (95%) at room temperature and 24 h (95%) at 4 °C. The proposed method is considered extremely superior to the previous methods in terms of time requirement for analysis. Therefore, the developed method may be more useful than conventional methods in urgent situations, such as confirming therapeutic efficacy of cytokine-release syndrome by 2019 coronavirus disease.

In recent years, with rapid increases in the number of vehicles in China, the contribution of vehicle exhaust emissions to air pollution has become increasingly prominent. To achieve the precise control of emissions, on-road remote sensing (RS) technology has been developed and applied for law enforcement and supervision. However, data quality is still an existing issue affecting the development and application of RS. In this study, the RS data from a cross-road RS system used at a single site (from 2012 to 2015) were collected, the data screening process was reviewed, the issues with data quality were summarized, a new method of data screening and calibration was proposed, and the effectiveness of the improved data quality control methods was finally evaluated. The results showed that this method reduces the skewness and kurtosis of the data distribution by up to nearly 67%, which restores the actual characteristics of exhaust diffusion and is conducive to the identification of actual clean and high-emission vehicles. The annual variability of emission factors of nitric oxide decreases by 60% - on average - eliminating the annual drift of fleet emissions and improving data reliability.

Autonomous driving can make traffic safer by reducing human errors. Different sensor types in autonomous vehicles could introduce additional technical failures. We offer a target simulator testing LiDAR systems under automotive conditions. Therefore, data are projected over-the-air by laser signals on the LiDAR detector. This work presents a concept of a LiDAR target simulator with regards to LiDAR systems using the direct time-of-flight principle. We develope design considerations for a screen discussing undesired screen reflections, a curved screen form and the positioning of light sources on this screen. As one main solution, we introduce a concept of an antireflective screen. For the scenario simulation, we derive a model delivering the required optical power representing a simulated target, which is combined with the simulated time-of-flight. Considering no prior knowledge of the LiDAR system under test, we discuss the required calibration data and timing resolution. Thereby, we suggest an optimized time-of-flight concept requireing only one optical trigger to determine the LiDAR measurement start. All requirements are supported by calculated example parameters based on real LiDAR systems. Altogether, we discuss main challenges and possible solutions of our LiDAR target simulator, which will allow a safer and more efficient development of LiDAR systems.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

Three-dimensional (3D) microdisplacement monitoring plays a crucial role in the assembly of large aircraft. This paper presents a broadly applicable high-precision online 3D microdisplacement monitoring method and system based on proximity sensors as well as a corresponding in situ calibration method, which can be applied under various extreme working conditions encountered in the aircraft assembly process, such as compact and obstructed spaces. A 3D monitoring model is first established to achieve 3D microdisplacement monitoring based only on the one-dimensional distances measured by proximity sensors, which concerns the extrinsic sensor parameters, such as the probe base point (PBP) and the unit displacement vector (UDV). Then, a calibration method is employed to obtain these extrinsic parameters with high precision by combining spatial transformation principles and weighted optimization. Finally, calibration and monitoring experiments performed for a tailplane assembly process are reported. The calibration precision for the PBP is better than ±10 μm in the X and Y directions and ±2 μm in the Z direction, and the calibration precision for the UDV is better than 0.07°. Moreover, the accuracy of the 3D microdisplacement monitoring system can reach ±15 μm. In general, this paper provides new insights into the modeling and calibration of 3D microdisplacement monitoring based on proximity sensors and a precise, efficient, and low-cost technical means for performing related measurements in compact spaces during the aircraft assembly process.

To enable wireless MRI receive arrays, per-channel power consumption must be reduced by a significant factor. To address this, a low-power SiGe alternative to industry standard MRI pre-amplifier blocks has been proposed and its impact on imaging performance evaluated in a benchtop environment. The SiGe amplifier reduces power consumption 28x, but exhibits increased non-linearity and reduced dynamic range relative to industry standard amplifiers. This distorts the images, causing reduced contrast and a blurring of fine features. In conjunction with the amplifier, a semi-blind calibration and compensation framework has been proposed to remove artifacts caused by this non-linearity. Requiring the knowledge of the calibration signal bandwidth, the associated peak transmit powers, and the distorted baseband signals, a second non-linearity is constructed that when cascaded with the receive chain produces a linear response. This method was evaluated for both knee and phantom image datasets of peak input power -20dBm with a -40dBm peak input power image as reference. In the benchtop environment, industry standard amplifiers produced input normalized RMSEs of 0.0199 and 0.0310 for phantom and knee datasets, respectively. The low-power SiGe amplifier resulted in RMSEs of 0.0869 and 0.1130 which were reduced to 0.0158 and 0.0168 following compensation, for phantom and knee images respectively. The ability to effectively compensate for this reduced dynamic range encourages further investigation of low-power SiGe amplifiers for power limited MRI receive arrays.

The availability of new and improved display, tracking and input devices for Virtual Reality experiences has facilitated the use of partial and full body self-avatars in interaction with virtual objects in the environment. However, scaling the avatar to match the user's body dimensions remains to be a cumbersome process. Moreover, the effect of body-scaled self-avatars on size perception of virtual handheld objects and related action capabilities has been relatively unexplored. To this end, we present an empirical evaluation investigating the effect of the presence or absence of body-scaled self-avatars and visuo-motor calibration on frontal passability affordance judgments when interacting with virtual handheld objects. The self-avatar's dimensions were scaled to match the participant's eyeheight, arms length, shoulder width and body depth along the mid section. The results indicate that the presence of body-scaled self-avatars produce more realistic judgments of passability and aid the calibration process when interacting with virtual objects. Also, participants rely on the visual size of virtual objects to make judgments even though the kinesthetic and proprioceptive feedback of the object is missing or mismatched.

Temperature sensitive electrical parameters (TSEP) provide an indirect and noninvasive method for on-line junction temperature estimation of power semiconductor devices. It is known that the fundamental of TSEP-based methods is to calibrate the relationship between TSEP and junction temperature in advance. However, the calibration methods in the literature need to open the module, require pretesting, or record the operating data of a converter in the entire power rating range, which are inconvenient in field applications. This article proposes an on-line and noninvasive calibration method by measuring the data at three operating states that are already existed in the regular converter operation. It is achieved by measuring the accessible heatsink/case temperature and TSEP during converter regular operation. The concept, implementation, and error analysis of the proposed method are presented in this article. Experimental verification is given to prove the effectiveness, accuracy, and convenience of the proposed method.

With the development of launch vehicles, the number of satellite-based synthetic aperture radar (SAR) has been increasing. Satellite-based SAR can acquire high-resolution images at day and night regardless of the weather. Since SAR resolution is determined by a chirp bandwidth, corresponding a generation technology of wideband chirp is essentially required for high-resolution SAR images under consideration of relatively small and light weight SAR system. Therefore, an ideal chirp waveform generation, which is challenging task in actual hardware, is proposed by modifying a chirp equation for phase calibration, and is verified based on Sentinel-1 satellite SAR parameters. The proposed method is applied to our SAR hardware and we confirm the calibrated waveform. Evaluation results using SAR observation simulation show that the impulse response with the proposed method has better performances.

A major gap between few-shot and many-shot learning is the data distribution empirically oserved by the model during training. In few-shot learning, the learned model can easily become over-fitted based on the biased distribution formed by only a few training examples, while the ground-truth data distribution is more accurately uncovered in many-shot learning to learn a well-generalized model. In this paper, we propose to calibrate the distribution of these few-sample classes to be more unbiased to alleviate such an over-fitting problem. The distribution calibration is achieved by transferring statistics from the classes with sufficient examples to those few-sample classes. After calibration, an adequate number of examples can be sampled from the calibrated distribution to expand the inputs to the classifier. Specifically, we assume every dimension in the feature representation from the same class follows a Gaussian distribution so that the mean and the variance of the distribution can borrow from that of similar classes whose statistics are better estimated with an adequate number of samples. Extensive experiments on three datasets, miniImageNet, tieredImageNet, and CUB, show that a simple linear classifier trained using the features sampled from our calibrated distribution can outperform the state-of-the-art accuracy by a large margin. Besides the favorable performance, the proposed method also exhibits high flexibility by showing consistent accuracy improvement when it is built on top of any off-the-shelf pretrained feature extractors and classification models without extra learnable parameters. The visualization of these generated features demonstrates that our calibrated distribution is an accurate estimation thus the generalization ability gain is convincing. We also establish a generalization error bound for the proposed distribution-calibration-based few-shot learning, which consists of the distribution assumption error, the distribution approximation error, and the estimation error. This generalization error bound theoretically justifies the effectiveness of the proposed method.

The article will be intended to explain the Image Depth Detection System, which in turn should perform all the necessary functions for detecting objects on a 3D scene, obtaining information about the sizes of bodies, and determining distances to certain bodies. Since such systems already exist in the modern world, the main goal was to create a model that meets the requirements regarding price-quality, since systems of this type currently on the market have a high cost price. Also, the improvement of the method of determining the depth of the image in this system was created thanks to the analysis of filtering methods available in the Matlab environment. An analysis of operation in different conditions of use, i.e. in the presence of external disturbances, such as daylight on the street, has been created. У даній статті розглянуто систему визначення глибини зображення, яка в свою чергу повинна виконувати всі необхідні функції для виявлення об’єктів на 3D сцені, отримання інформації про розміри тіл і визначення відстаней до певних об'єктів. Оскільки подібні системи вже існують у сучасному світі, головною метою було створити модель, що відповідає вимогам ціна-якість, оскільки системи такого типу, які зараз представлені на ринку, мають високу собівартість. Також удосконалення методу визначення глибини зображення в цій системі було створено завдяки аналізу методів фільтрації, доступних у середовищі Matlab. Проаналізовано роботу в різних умовах експлуатації, тобто за наявності зовнішніх перешкод, наприклад денне світло на вулиці. У даній статті розглянуто систему визначення глибини зображення, яка в свою чергу повинна виконувати всі необхідні функції для виявлення об’єктів на 3D сцені, отримання інформації про розміри тіл і визначення відстаней до певних об'єктів. Оскільки подібні системи вже існують у сучасному світі, головною метою було створити модель, що відповідає вимогам ціна-якість, оскільки системи такого типу, які зараз представлені на ринку, мають високу собівартість. Також удосконалення методу визначення глибини зображення в цій системі було створено завдяки аналізу методів фільтрації, доступних у середовищі Matlab. Проаналізовано роботу в різних умовах експлуатації, тобто за наявності зовнішніх перешкод, наприклад денне світло на вулиці.

Purpose: The purpose of this article is to explain various types of data collection instruments, and available techniques for checking the calibration, validity, and reliability of the data collection instrument, in turn, guiding Ph.D. scholars to use a well-calibrated, valid, and reliable data collection instrument to ensure high-quality of research output. Design/Methodology/Approach: Postmodernism philosophical paradigm; Inductive research approach; Observation data collection method; Longitudinal data collection time frame; Qualitative data analysis. Findings/Result: As long as the Ph.D. scholars can understand the existing research data collection instruments and realize the need for the development of a new instrument and make mindful choices of instruments in addition to checking their calibration, validity, and reliability before collecting the research data to answer their research question they will be able to determine (on their own) data analysis techniques and appropriate statistical techniques in subsequent stages of the doctoral-level research process to comfortably claim their research findings. Originality/Value: There is a vast literature about research data collection instruments and procedures to check their calibration, validity, and reliability. However, only a few have explained them together comprehensively which is conceivable to Ph.D. scholars. In this article, we have attempted to briefly explain various types of data collection instruments, and available techniques for checking the calibration, validity, and reliability of the data collection instrument. Paper Type: Conceptual.

Measurements of wideband acoustic immittance (WAI) rely on the calibration of an ear probe to obtain its acoustic source parameters. The clinical use of WAI and instruments offering the functionality are steadily growing, however, no international standard exists to ensure a certain reliability of the hardware and methods underlying such measurements. This paper describes a reciprocity method that can evaluate the accuracy of and identify errors in ear-probe source calibrations. By placing the ear probes of two calibrated WAI instruments face-to-face at opposite ends of a short waveguide, the source parameters of each ear probe can be measured using the opposite calibrated ear probe. The calibrated and measured source parameters of each ear probe can then be compared directly, and the influence of possible calibration errors on WAI measurements may be approximated. In various exemplary ear-probe calibrations presented here, the reciprocity method accurately identifies errors that would otherwise remain undetected and result in measurement errors in real ears. The method is likely unsuitable for routine calibration of WAI instruments but may be considered for conformance testing as part of a potential future WAI standard.

Considerable between-subject variability in envelope following response (EFR) amplitude limits its clinical translation. Based on a pattern of lower amplitude and larger variability in the low (8 kHz), relative to mid (1–3 kHz) frequency carriers, we hypothesized that the between-subject variability in external and middle ear (EM) contribute to between-subject variability in EFR amplitude. It is predicted that equalizing the stimulus reaching the cochlea by accounting for EM differences using forward pressure level (FPL) calibration would at least partially improve response amplitude and reduce between-subject variability. In 21 young normal hearing adults, EFRs of four modulation rates (91, 96, 101, and 106 Hz) were measured concurrently from four frequency bands [low (0.091–1.2 kHz), mid (1–3 kHz), high (4–5.4 kHz), and very high (vHigh; 8–9.4 kHz)], respectively, with 12 harmonics each. The results indicate that FPL calibration in-ear and in a coupler leads to larger EFR amplitudes in the low and vHigh frequency bands relative to conventional coupler root-mean-square calibration. However, improvement in variability was modest with FPL calibration. This lack of a statistically significant improvement in variability suggests that the dominant source of variability in EFR amplitude may arise from cochlear and/or neural processing.

Introduction: Federated learning has the potential to perfrom analysis on decentralised data; however, there are some obstacles to survival analyses as there is a risk of data leakage. This study demonstrates how to perform a stratified Cox regression survival analysis specifically designed to avoid data leakage using federated learning on larynx cancer patients from centres in three different countries. Methods: Data were obtained from 1821 larynx cancer patients treated with radiotherapy in three centres. Tumour volume was available for all 786 of the included patients. Parameter selection among eleven clinical and radiotherapy parameters were performed using best subset selection and cross-validation through the federated learning system, AusCAT. After parameter selection, β regression coefficients were estimated using bootstrap. Calibration plots were generated at 2 and 5-years survival, and inner and outer risk groups’ Kaplan-Meier curves were compared to the Cox model prediction. Results: The best performing Cox model included log(GTV), performance status, age, smoking, haemoglobin and N-classification; however, the simplest model with similar statistical prediction power included log(GTV) and performance status only. The Harrell C-indices for the simplest model were for Odense, Christie and Liverpool 0.75[0.71–0.78], 0.65[0.59–0.71], and 0.69[0.59–0.77], respectively. The values are slightly higher for the full model with C-index 0.77[0.74–0.80], 0.67[0.62–0.73] and 0.71[0.61–0.80], respectively. Smoking during treatment has the same hazard as a ten-years older nonsmoking patient. Conclusion: Without any patient-specific data leaving the hospitals, a stratified Cox regression model based on data from centres in three countries was developed without data leakage risks. The overall survival model is primarily driven by tumour volume and performance status.

Among the objectives in treatments with yttrium-90 spheres, is to demonstrate that the tumoricidal dose is achieved and that hepatotoxic doses are avoided, as well as that there is no extrahepatic deposition.We use different amounts of yttrium-90 resin micro-spheres and a NEMA NU2-2007 phantom to check if the scanner maintains a response that allows real dosimetric calculations.The Gemini tomograph responds linearly in a wide range of activities with RThe detection capacity of the PET equipment allows us to carry out standard body studies with dosimetric purposes with times of five minutes per bed. It also make possible to verify the absence of extrahepatic deposition of significant amounts of yttrium 90 spheres.

As the maximum frequency of electronics is rising, on-wafer measurements play an important role in modeling of integrated devices. Most of the time, due to the lack of measurement accuracy beyond 110 GHz, such models are usually extracted at frequencies much below their working frequencies and are subsequently extrapolated. The validity of such models is then mostly verified after fabrication of the complete chip, with a simple pass and fail test. This is stating the necessity of enhancing measurement results by any means possible, i.e., to reduce the overall uncertainty in such measurements. It is widely accepted that one of the main sources of uncertainty in such measurements is probe contact repeatability, since it is difficult to reach position accuracy below a few micrometers. We are presenting in this article a method to model the S -parameter variation with probe position on the pads, which can then be used to either estimate contact repeatability uncertainty or further enhance measurement results. The approach is validated based on the measurements performed at 500 GHz.

Whole-genome sequencing (WGS) is the gold standard for fully characterizing genetic variation but is still prohibitively expensive for large samples. To reduce costs, many studies sequence only a subset of individuals or genomic regions, and genotype imputation is used to infer genotypes for the remaining individuals or regions without sequencing data. However, not all variants can be well imputed, and the current state-of-the-art imputation quality metric, denoted as standard Rsq, is poorly calibrated for lower-frequency variants. Here, we propose MagicalRsq, a machine-learning-based method that integrates variant-level imputation and population genetics statistics, to provide a better calibrated imputation quality metric. Leveraging WGS data from the Cystic Fibrosis Genome Project (CFGP), and whole-exome sequence data from UK BioBank (UKB), we performed comprehensive experiments to evaluate the performance of MagicalRsq compared to standard Rsq for partially sequenced studies. We found that MagicalRsq aligns better with true R

Early visual deprivation typically results in spatial impairments in other sensory modalities. It has been suggested that, since vision provides the most accurate spatial information, it is used for calibrating space in the other senses. Here we investigated whether sight restoration after prolonged early onset visual impairment can lead to the development of more accurate auditory space perception. We tested participants who were surgically treated for congenital dense bilateral cataracts several years after birth. In Experiment 1 we assessed participants' ability to understand spatial relationships among sounds, by asking them to spatially bisect three consecutive, laterally separated sounds. Participants performed better after surgery than participants tested before. However, they still performed worse than sighted controls. In Experiment 2, we demonstrated that single sound localization in the two-dimensional frontal plane improves quickly after surgery, approaching performance levels of sighted controls. Such recovery seems to be mediated by visual acuity, as participants gaining higher post-surgical visual acuity performed better in both experiments. These findings provide strong support for the hypothesis that vision calibrates auditory space perception. Importantly, this also demonstrates that this process can occur even when vision is restored after years of visual deprivation.

Simultaneous elemental detection of F and Cl offers quantitation of fluorinated and chlorinated compounds and their transformation products without compound-specific standards. Despite wide-ranging applications, this capability has been hindered by fundamental and technical shortcomings of current inductively coupled plasma (ICP)-MS methods in ion formation and isobaric interference elimination. These hurdles are alleviated here via a chemical ionization method. Fluorine and chlorine in analytes are first converted to HF and HCl by an ICP with post-plasma recombination and subsequently react with barium-containing ions supplied by a nanospray, yielding BaF

Maize production in low-yielding regions is influenced by climate variability, poor soil fertility, suboptimal agronomic practices, and biotic influences, among other limitations. Therefore, the assessment of yields to various management practices is, among others, critical for advancing site-specific measures for production enhancement. In this study, we conducted a multiseason calibration and evaluation of the DSSAT–CERES-Maize model to assess the maize yield response of two common cultivars grown in Trans Nzoia County in Kenya under various agricultural strategies, such as sowing dates, nitrogen fertilization, and water management. We then applied the Mann–Kendall (MK), and Sen’s Slope Estimator (SSE) tests to establish the yield trends and magnitudes of the different strategies. The evaluated model simulated long-term yields (1984–2021) and characterized production under various weather regimes. The model performed well in simulating the growth and development of the two cultivars, as indicated by the model evaluation results. The RMSE for yield was 333 and 239 kg ha−1 for H614 and KH600-23A, respectively, representing a relative error (RRMSE) of 8.1 and 5.1%. The management strategies assessment demonstrated significant feedback on sowing dates, nitrogen fertilization, and cultivars on maize yield. The sowing date conducted in mid-February under fertilization of 100 kg of nitrogen per hectare proved to be the best strategy for enhancing grain yields in the region. Under the optimum sowing dates and fertilization rate, the average yield for cultivar KH600-23A was 7.1% higher than that for H614. The MK and SSE tests revealed a significant (p

Circular dichroism (CD) measurements help characterize optically active molecules and higher-order biomolecular structures. The harmonization of interlaboratory CD measurements requires minimizing measurement uncertainties and determinate errors. Most CD measurements utilize a single-wavelength intensity measurement at a spectral peak to calibrate the intensities of the ultraviolet wavelength range. However, such a single-wavelength calibration is inherently less precise than using the CD instrument's spectrum over the entire measured spectral range. A more thorough and informative calibration can be achieved by remapping the spectrum into what we call a spectral similarity plot. This process allows a straightforward, quantitative evaluation of the shape congruence between two spectra over the full spectral range. While preliminary analyses suggest spectral similarity plots can be utilized with a variety of different spectrometry methods, here we illustrate the process applied to circular dichroism. Spectral similarity plots are highly sensitive to deviations due to differences in concentration, pathlength, source and detector properties, circular polarization balance, as well as wavelength nonlinearities and shifts. Deviations in these properties can be quantitated by a linear least squares fit of the remapped data. The remapping enables protocols to correct spectra toward congruence between two spectra. The spectra similarity comparison provides an objective, unambiguous test of the CD instrument quality when, for example, compared to a carefully calibrated system as shown in the examples described in the text.

Stable carbon isotope ratio measurements are used to investigate the provenance of vanillin. In this study, a variety of commercial vanillin samples and vanilla products were analyzed to provide a frame of reference for the variability of carbon isotope delta values in various vanillin samples, with the results ranging from −20.6 to −36.7‰ relative to the Vienna Peedee Belemnite (VPDB). We present information on the development of two synthetic vanillin reference materials, VANA-1 and VANB-1, prepared in 0.75 g units in glass vials, to be used for the calibration of carbon isotope delta measurements of vanillin and other easily combustible organic materials. Characterization of 40 vials each of VANA-1 and VANB-1 was performed by three laboratories over several measurement sequences. The certified carbon isotope delta values are −31.30 ± 0.06‰ (VANA-1) and −25.85 ± 0.05‰ (VANB-1). These uncertainties, for the 95% confidence level, include considerations for measurement uncertainty, coherence of the reference materials used for calibration, batch homogeneity, and stability during storage and transportation. The results are traceable to the VPDB through a set of nine reference materials (IAEA-CH-6, USGS65, IAEA-600, NBS22, USGS61, IAEA-603, IAEA-610, IAEA-611, and IAEA-612). For up to date certified values, users should refer to doi.org/10.4224/crm.2022.vana-1 and doi.org/10.4224/crm.2022.vanb-1.

Standard Parshall flumes are widely used as in-line flow measurement structures in open channels and irrigation projects. The calibration of flow measurement structures is an important issue in practical applications. At present, free-flow Parshall flumes have separate empirical discharge equations for each nominal flume size, ranging from 1 inch to 50 ft (0.0254–15.24 m). In this study, using dimensional analysis and 420 data points generated from the original rating equations of 21 standard Parshall flume sizes, different dimensionally homogeneous equations were developed to calculate discharge values in Parshall flumes. The results showed that the throat width, the contraction ratio and the Reynolds number are key parameters for deducing a generic discharge equation. A general calibration discharge equation was developed for free-flow conditions for any Parshall flume in the range of 21 standard sizes and a specified contraction ratio of 0.15–0.82 according to the original design criteria. The proposed equation also enables computation of the discharge of Parshall flumes with custom and intermediate sizes. Compared with the original values, the average error in the discharges estimated using the proposed unified discharge equation for all flume sizes was found to be 0.95%.

In this work, a novel electrochemical biosensor assisted by multivariate calibration methods was developed for simultaneous estimation of rates of DNA damage induced by doxorubicin (DX), daunorubicin (DR) and idarubicin (ID), and also to simultaneous determination of the drugs. A glassy carbon electrode was efficiently modified and used as the biosensing platform. Binding and interactions of DX, DR and ID with DNA were modeled by molecular docking methods, and theoretical information was completed by experimental results. The methylene blue was able to intercalate within the DNA structure and by incubation of the biosensor with DX or DR or ID, the methylene blue was replaced by drug and therefore, the voltammetric signal of the biosensor was changed due to the exposed DNA and repelling the electrochemical probe molecules carrying negative charge. The DNA damage induced by each drug was individually monitored by differential pulse voltammetry and then, rates of DNA damage were calibrated and validated by mixture design and multivariate calibration methods. The developed multivariate calibration model constructed based on vectorization of the data was able to simultaneous detection of the rates of DNA damage induced by all the three drugs. The change in the biosensor response in the presence of the drugs was also modeled by multivariate calibration methods to simultaneous determination of the drugs.

The reliability of molecular mechanics simulations to predict effects of ion binding to proteins depends on their ability to simultaneously describe ion-protein, ion-water, and protein-water interactions. Force fields (FFs) to describe protein-water and ion-water interactions have been constructed carefully and have also been refined routinely to improve accuracy. Descriptions for ion-protein interactions have also been refined, although in an

Asymmetric gradient coils introduce zeroth- and first-order concomitant field terms, in addition to higher-order terms common to both asymmetric and symmetric gradients. Salient to compensation strategies is the accurate calibration of the concomitant field spatial offset parameters for asymmetric coils. A method that allows for one-time calibration of the offset parameters is described.A modified phase contrast pulse sequence with single-sided bipolar flow encoding is proposed to calibrate the offsets for asymmetric, transverse gradient coils. By fitting the measured phase offsets to different gradient amplitudes, the spatial offsets were calculated by fitting the phase variation. This was used for calibrating real-time pre-emphasis compensation of the zeroth- and first-order concomitant fields.Image quality improvement with the proposed corrections was demonstrated in phantom and healthy volunteers with non-Cartesian and Cartesian trajectory acquisitions. Concomitant field compensation using the calibrated offsets resulted in a residual phase errorlt;3% at the highest gradient amplitude and demonstrated substantial reduction of image blur and slice position/selection artifacts.The proposed implementation provides an accurate method for calibrating spatial offsets that can be used for real-time concomitant field compensation of zeroth and first-order terms, substantially reducing artifacts without retrospective correction or sequence specific waveform modifications.

A new, rapid, highly sensitive, and affordable spectrofluorimetric approach has been constructed and validated for the determination of octreotide in its authentic form and pharmaceutical dosage form. Octreotide is an important synthetic analog of the naturally occurring somatostatin hormone. The developed spectrofluorimetric approach is actually dependent on the measurement of octreotide native fluorescence at emission wavelength of 342 nm after excitation at 218 nm. At optimal reaction conditions, the calibration curve has been constructed over the concentration range 200-2000 ng ml

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN's ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on

To implement a method for real-time field control using rapid FID navigator (FIDnav) measurements and evaluate the efficacy of the proposed approach for mitigating dynamic field perturbations and improvingmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miT/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{T}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:math-weighted image quality.FIDnavs were embedded in a gradient echo sequence and a subject-specific linear calibration model was generated on the scanner to facilitate rapid shim updates in response to measured FIDnav signals. To confirm the accuracy of FID-navigated field updates, phantom and volunteer scans were performed with online updates of the scanner Bsub0/subshim settings. To evaluate improvement inmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miT/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{T}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:math-weighted image quality with real-time shimming, 10 volunteers were scanned at 3T while performing deep-breathing and nose-touching tasks designed to modulate the Bsub0/subfield. Quantitative image quality metrics were compared with and without FID-navigated field control. An additional volunteer was scanned at 7T to evaluate performance at ultra-high field.Applying measured FIDnav shim updates successfully compensated for applied global and linear field offsets in phantoms and across all volunteers. FID-navigated real-time shimming led to a substantial reduction in field fluctuations and a consequent improvement inmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miT/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{T}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:math-weighted image quality in volunteers performing deep-breathing and nose-touching tasks, with 7.57% ± 6.01% and 8.21% ± 10.90% improvement in peak SNR and structural similarity, respectively.FIDnavs facilitate rapid measurement and application of field coefficients for slice-wise Bsub0/subshimming. The proposed approach can successfully counteract spatiotemporal field perturbations and substantially improvesmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miT/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{T}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:math-weighted image quality, which is important for a variety of clinical and research applications, particularly at ultra-high field.

Originally developed for use in controlled laboratory settings, potentiometric ion-selective electrode (ISE) sensors have recently been deployed for continuous, in situ measurement of analyte concentration in agricultural (e.g., nitrate), environmental (e.g., ocean acidification), industrial (e.g., wastewater), and health-care sectors (e.g., sweat sensors). However, due to uncontrolled temperature and lack of frequent calibration in these field applications, it has been difficult to achieve accuracy comparable to the laboratory setting. In this paper, we propose a novel temperature self-calibration method where the ISE sensors can serve as their own thermometer and therefore precisely measure the analyte concentration in the field condition by compensating for the temperature variations. We validate the method with controlled experiments using pH and nitrate ISEs, which use the Nernst principle for electrochemical sensing. We show that, using temperature self-calibration, pH and nitrate can be measured within 0.3% and 5% of the true concentration, respectively, under varying concentrations and temperature conditions. Moreover, we perform a field study to continuously monitor the nitrate concentration of an agricultural field over a period of 6 days. Our temperature self-calibration approach determines the nitrate concentration within 4% of the ground truth measured by laboratory-based high-precision nitrate sensors. Our approach is general and would allow battery-free temperature-corrected analyte measurement for all Nernst principle-based sensors being deployed as wearable or implantable sensors.

To facilitate the monitoring and management of modern transportation systems, monocular visual traffic surveillance systems have been widely adopted for speed measurement, accident detection, and accident prediction. Thanks to the recent innovations in computer vision and deep learning research, the performance of visual traffic surveillance systems has been significantly improved. However, despite this success, there is a lack of survey papers that systematically review these new methods. Therefore, we conduct a systematic review of relevant studies to fill this gap and provide guidance to future studies. This paper is structured along the visual information processing pipeline that includes object detection, object tracking, and camera calibration. Moreover, we also include important applications of visual traffic surveillance systems, such as speed measurement, behavior learning, accident detection and prediction. Finally, future research directions of visual traffic surveillance systems are outlined.

Quantitative sensory testing (QST) allows researchers to evaluate associations between noxious stimuli and acute pain in clinical populations and healthy participants. Despite its widespread use, our understanding of QST's reliability is limited, as reliability studies have used small samples and restricted time windows. We examined the reliability of pain ratings in response to noxious thermal stimulation in 171 healthy volunteers (n = 99 female, n = 72 male) who completed QST on multiple visits ranging from 1 day to 952 days between visits. On each visit, participants underwent an adaptive pain calibration in which they experienced 24 heat trials and rated pain intensity after stimulus offset on a 0 to 10 Visual Analog Scale. We used linear regression to determine pain threshold, pain tolerance, and the correlation between temperature and pain for each session and examined the reliability of these measures. Threshold and tolerance were moderately reliable (Intra-class correlation = .66 and .67, respectively; Plt; .001), whereas temperature-pain correlations had low reliability (Intra-class correlation = .23). In addition, pain tolerance was significantly more reliable in female participants than male participants, and we observed similar trends for other pain sensitive measures. Our findings indicate that threshold and tolerance are largely consistent across visits, whereas sensitivity to changes in temperature vary over time and may be influenced by contextual factors. PERSPECTIVE: This article assesses the reliability of an adaptive thermal pain calibration procedure. We find that pain threshold and tolerance are moderately reliable whereas the correlation between pain rating and stimulus temperature has low reliability. Female participants were more reliable than male participants on all pain sensitivity measures.

We propose a new account of calibration according to which calibrating a technique shows that the technique does what it is supposed to do. To motivate our account, we examine an early 20th century debate about chlorophyll chemistry and Mikhail Tswett’s use of chromatographic adsorption analysis to study it. We argue that Tswett’s experiments established that his technique was reliable in the special case of chlorophyll without relying on either a theory or a standard calibration experiment. We suggest that Tswett broke the Experimenters’ Regress by appealing to material facts in the common ground for chemists at the time.

Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures.The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were "calibration," "mass spectrometry," and "regression." Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results.The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling.This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.

The benefit of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) remains unclear. We hypothesized that a new mechanistic mathematical model of chemotherapy and radiation response could predict clinical outcomes a priori, using a previously described baseline measurement of perfusion from computed tomography scans, normalized area under the enhancement curve (nAUC).We simplified an existing mass transport model that predicted cancer cell death by replacing previously unknown variables with averaged direct measurements from randomly selected pathologic sections of untreated PDAC. This allowed using nAUC as the sole model input to approximate tumor perfusion. We then compared the predicted cancer cell death to the actual cell death measured from corresponding resected tumors treated with neoadjuvant chemoradiation in a calibration cohort (n = 80) and prospective cohort (n = 25). After calibration, we applied the model to 2 separate cohorts for pathologic and clinical associations: targeted therapy cohort (n = 101), cetuximab/bevacizumab + radiosensitizing chemotherapy, and standard chemoradiation cohort (n = 81), radiosensitizing chemotherapy to 50.4 Gy in 28 fractions.We established the relationship between pretreatment computed v nAUC to pathologically verified blood volume fraction of the tumor (r = 0.65; P = .009) and fractional tumor cell death (r = 0.97-0.99; P.0001) in the calibration and prospective cohorts. On multivariate analyses, accounting for traditional covariates, nAUC independently associated with overall survival in all cohorts (mean hazard ratios, 0.14-0.31). Receiver operator characteristic analyses revealed discrimination of good and bad prognostic groups in the cohorts with area under the curve values of 0.64 to 0.71.This work presents a new mathematical modeling approach to predict clinical response from chemotherapy and radiation for PDAC. Our findings indicate that oxygen/drug diffusion strongly influences clinical responses and that nAUC is a potential tool to select patients with PDAC for radiation therapy.

Bacteria in the dental biofilm produceacid after consumption of carbohydrates which if left unmonitored leads to caries formation. We present O-pH, a device that can measure dental biofilm acidity and provide quantitative feedback to assist in oral health monitoring.O-pH utilizes a ratiometric pH sensing method by capturing fluorescence of Sodium Fluorescein, an FDA approved chemical dye. The device was calibrated to a lab pH meter using buffered fluorescein solution with a correlation coefficient of 0.97. The calibration was further verified in vitro on additional buffered solution, artificial, and extracted teeth. An in vivo study on 30 pediatric subjects was performed to measure pH before (rest pH) and after (drop pH) a sugar rinse, and the resultant difference in pH (diff pH) was calculated. The study enrolled subjects with low (Post-Cleaning) and heavy (Pre-Cleaning) biofilm load, having both unhealthy/healthy surfaces. Further, we modified point-based O-pH to an image-based device using a multimode-scanning fiber endoscope (mm-SFE) and tested in vivo on one subject.We found significant difference between Post-Cleaning and Pre-Cleaning group using drop pH and diff pH. Additionally, in Pre-Cleaning group, the rest and drop pH is lower at the caries surfaces compared to healthy surfaces. Similar trend was not noticed in the Post-Cleaning group. mm-SFE pH scope recorded image-based pH heatmap of a subject with an average diff pH of 1.5.This work builds an optical pH prototype and presents a pioneering study for non-invasively measuring pH of dental biofilm clinically.

This article proposes a novel validated de-embedding approach to S-parameter measurement. This de-embedding approach benefits from the fully symmetric nature of the designed tapered transmission line test fixture and requires only a Through (THRU) standard. A key point of this approach is solving for a new coefficient Rx, which is defined to take into account the inherent physical properties of the transmission network. Compared to previous thru-only de-embedding methods, the present approach is applicable to a significantly wider range of frequencies and offers more flexibility in the design of the test fixture. In addition, this approach simplifies multi-port configurations compared to traditional complicated calibration methods such as TRL. For validation purposes, symmetric two and four port tapered THRUs were designed and measured. This novel de-embedding approach is verified by comparison measurements with the classic TRL method or the HFSS simulation and shows a very good agreement.