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Abstract Background Polygenic risk scores (PRS) quantify an individual’s genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the $$R^2$$ R 2 is a commonly used measure to evaluate prediction accuracy. While the $$R^2$$ R 2 is a well-defined goodness-of-fit measure for statistical linear models, there exist different definitions for its application on test data, which complicates interpretation and comparison of results. Methods Based on large-scale genotype data from the UK Biobank, we compare three definitions of the $$R^2$$ R 2 on test data for evaluating the generalizability of PRS models to different populations. Polygenic models for several phenotypes, including height, BMI and lipoprotein A, are derived based on training data with European ancestry using state-of-the-art regression methods and are evaluated on various test populations with different ancestries. Results Our analysis shows that the choice of the $$R^2$$ R 2 definition can lead to considerably different results on test data, making the comparison of $$R^2$$ R 2 values from the literature problematic. While the definition as the squared correlation between predicted and observed phenotypes solely addresses the discriminative performance and always yields values between 0 and 1, definitions of the $$R^2$$ R 2 based on the mean squared prediction error (MSPE) with reference to intercept-only models assess both discrimination and calibration. These MSPE-based definitions can yield negative values indicating miscalibrated predictions for out-of-target populations. We argue that the choice of the most appropriate definition depends on the aim of PRS analysis — whether it primarily serves for risk stratification or also for individual phenotype prediction. Moreover, both correlation-based and MSPE-based definitions of $$R^2$$ R 2 can provide valuable complementary information. Conclusions Awareness of the different definitions of the $$R^2$$ R 2 on test data is necessary to facilitate the reporting and interpretation of results on PRS generalizability. It is recommended to explicitly state which definition was used when reporting $$R^2$$ R 2 values on test data. Further research is warranted to develop and evaluate well-calibrated polygenic models for diverse populations.

Abstract Automated radio telemetry systems have become a popular and invaluable tool in tracking the activity and movement of wild animals. However, many environmental conditions can hinder accuracy when tracking with this technology. For instance, study sites may contain multiple habitat types, each habitat uniquely affecting the signal strength received from tagged species. To investigate the influence of a structurally diverse study site on an automated radio telemetry system, we conducted this project at a restored and managed pine barren habitat that consisted of a mix of mature pitch pine, treated pitch pine, scrub oak, and hardwood forests. This site, Montague Plains Wildlife Management Area, Montague, Massachusetts, is also a known breeding ground for Eastern whip-poor-will (Antrostomus vociferus). To measure the relationship of radio signal strength with distance across each habitat, we used radio telemetry equipment manufactured by Cellular Tracking Technologies. We produced negative exponential decay functions measuring radio signal strength over distance and tested for differences among habitat types on radio signal strength (RSS). We found that decay function parameters significantly differed by habitat type, prompting us to investigate if accounting for these differences improved location estimate accuracy. To test this, we estimated known locations using trilateration methods with and without habitat calibration. Comparing these tests indicates that habitat-specific adjustments significantly improved location accuracy. Lastly, we visualized estimated RSS-based locations of 1 week of whip-poor-will data and compared them to GPS data generated from the same individual. Previous studies have accounted for types of environmental interference (like elevation) in the field but have avoided incorporating habitat-specific factors by working with node networks covering a relatively small area, but in this study, we examined the potential to scale up for larger areas and in more complex habitats.

Societal Impact Statement Palaeoecological investigations are crucial in understanding millennial to centennial land use and land cover change. By analysing the modern pollen rain from four main vegetation types across Madagascar, this research provides baselines for improving the interpretation of pollen records in palaeoecological studies. This study determines the modern pollen‐vegetation relationship in Madagascar and gives a better understanding of the island's landscapes. Despite some spatial limitations, this approach contributes to resolving the debated topic related to the origin of Madagascar's open ecosystems. Knowing the vegetation history prior to and after human settlement would help guide biodiversity management and its associated ecosystem services. Summary Modern pollen rain contributes to calibrating and defining palaeo‐records relative to the current vegetation of diverse landscapes. Quantifying past vegetation change is important to better frame sustainable and resilient management methods of biodiversity considering human needs. In this paper, we aim to assess modern pollen assemblages in different vegetation types in Madagascar and inform how these could contribute to the interpretation of palaeo‐records. We identified modern pollen assemblages from 21 samples across four major vegetation types in Madagascar, including seven (N = 7) newly generated samples from the tropical dry forest in the Northwest region and 14 datasets downloaded from the African Pollen Database website. The downloaded datasets are from core tops representing modern vegetation previously analysed in the tropical dry forests and spiny thickets, the wooded grassland–bushland mosaic and the littoral humid forest. We evaluated the frequency of different taxa in the samples and conducted multivariate analyses to evaluate the similarities and ecological affinities between samples. Pollen rain reflected the main vegetation types across Madagascar and provided information on the current structure and state of the landscape. Regarding the interpretation of pollen records, pollen rain samples revealed that: (i) Open mosaic ecosystems should contain a percentage of at least 40% grass pollen, informing on the origin of the vegetation in older samples and the state of degradation in more recent vegetation reconstructions; and (ii) Anthropogenic vegetation such as plantations are marked by the abundance of pioneer taxa such as Pinus and/or Eucalyptus spp. with a frequency >20%. Our findings improve the interpretations of pollen records and help differentiate past distribution of forest, open and mosaic vegetation, in Madagascar. It will contribute to further research on human practices, land use and into scenarios of conservation planning not only in Madagascar but also across the tropics.

AbstractIn the literature on policy design, the topic of citizen or policy-taker compliance, or the lack thereof, has been understood mainly in terms of economistic motivations responding to incentives and deterrents. That is, until recently. A pronounced turn toward behavioral public policy over the last two decades has diversified the set of possible propositions that are available for policy design scholars to study policy-takers. Consequently, how the diversity of policy-taker motivations and behavioral responses can be considered in the design of policy mixes and their implementation is an emerging area of study. Here, we contribute to this research effort by conceptualizing how the motivations of policy-takers affect their compliance response to the calibration of different types of policy instruments. We first elaborate on the inter-relationships between heterogenous policy-taker motivations, policy instrument calibrations, and heterogenous behavioral responses. Next, we use the example of Singapore’s approach to the management of a cyclical environmental disease (dengue) to illustrate the mix of motivations on the part of policy-takers. We then offer some thoughts on how policy instrument calibrations can be deployed to target heterogenous policy-taker motivations and induce greater policy participation.

This article presents a study carried out on a 2 kN·m torque transducer at the Central Office of Measures (GUM) and the Physikalisch-Technische Bundesanstalt (PTB). The weighted least squares method was used to generate the linear regression equations for this torque transducer. The Monte Carlo method and the law of uncertainty propagation were used to calculate the expanded uncertainty. In addition, a creep study was carried out at eight measurement points ranging from 200 N·m to 2000 N·m. The investigations showed that the highest readings of the torque transducer, expressed in electrical units as mV/V, occur within the initial few seconds of the test after the removal of the maximum reference torque.

Objectives: The aim of the study is to assess the influence of the masticatory muscles on the indices of the occlusion, measured with electromyographic (EMG) device Teethan® (Teethan S.p.A., Milan, Italy). The device is designed to assess the effect of occlusion on muscle balance and thus indirectly guides the clinician to the necessary changes in occlusion. This paper aims to determine whether muscles influence the indices characterizing occlusion. Material and methods: Thirty-three persons aged 13-43 (mean 21.33) years, 15 men and 18 women who fulfilled the criteria, were included in the study. All subjects had a good state of dental and periodontal health and complete permanent dentition. EMG recordings of the masseter and temporalis muscles were performed during maximum voluntary teeth clenching on cotton rolls and in centric occlusion. All values were standardized as a percentage of the maximum clenching on cotton rolls. Results: Most of the results of the test on cotton rolls are below normal reference values provided by the manufacturer. Within the normal range are only the Global index and IMPACT. When compared to MVC in centric occlusion, some of the indices were higher than when biting on cotton rolls (POC MM, BAR, Global index), which pointed out the effect of the occlusal contact on these tests. Conclusions: The calibration of the Teethan® device gives reliable and reproducible results. Test during MVC in centric occlusion will provide information on which of the indices are influenced by occlusal factors. Recording a test MVC on cotton rolls gives valuable information for the muscle balance, excluding the influence of the occlusion.

Controlling a remotely operated underwater vehicle (ROV) is an extremely challenging task that requires precise maneuvering and navigation in complex and often unpredictable environments. The operator faces numerous difficulties, including limited visibility and communication constraints, and the need to interpret data from various sensors. This paper describes a method for calibration of a wearable system equipped with inertial measurement unit (IMU) sensors that control the underwater manipulators. To implement a solution that allows the robot to be controlled by the operator's hand movements, it is necessary to measure the movement of the arm. This task is carried out using the IMU sensors, which are mounted in appropriate places on the ROV operator's suit to allow mapping the movement of his/her upper limbs. These movements are transferred to the manipulator's arms on the ROV, making it possible to interact with the environment by - manipulating objects under-water.

Microscopic traffic simulation models offer an effective way to analyze and assess different transportation systems thanks to their efficiency and reliability. As traffic management issues become more prevalent, notably in urban areas, simulation tools enable a significant opportunity to replicate real-world conditions before implementation. Therefore, the calibration of traffic simulation models plays a substantial role in obtaining accurate and confidential results. Nowadays, urban regions are facing the challenge of restricted space for developing traffic solutions. As a consequence of environmental restrictions, the use of mini-roundabouts rather than larger roundabouts is increasing. Based on the given literature review, it is seen that not much attention was given to the complex modeling and calibration of microsimulation models of mini-roundabouts and unsignalized intersections. The objective of this study is to offer the calibration of microscopic traffic simulation of urban road network, including closely located mini-roundabouts and unsignalized intersection. To this end, an open-source tool called SUMO (Simulation of Urban Mobility) was utilized as a simulation environment in this study. The necessary data for developing a microsimulation model in SUMO was gathered using a videography technique. The traffic count data and speed were considered performance measures between field observations and simulation outputs. The routeSampler tool of SUMO, which has recently emerged in the literature, was used to match traffic count data and the corresponding time interval for traffic volume data calibration. The calibration of car-following model parameters using a trial-and-error approach was employed based on mean absolute percent error (MAPE) between simulated speeds and field-measured speeds. According to the findings of the study, the simulation model fulfilled the calibration aims of the FHWA guideline and is suitable for further research.

Abstrak Data hidrologi dalam menentukan besaran debit adalah curah hujan dan klimatologi. Salah satu tempat di sungai Cimanuk yang memiliki pos duga air adalah Cimanuk-Bojongloa. Data debit selain dari hasil observasi, juga bisa menggunakan pemodelan. Model yang digunakan pada penelitian ini adalah model NRECA dan model Sacramento. Data curah hujan untuk kalibrasi dengan empat pos, yaitu Pamegatan, Pangauban, Kapakan, dan Bayongbong dari tahun 2017 sampai 2021. Curah hujan rata-rata dihitung dengan metode Thiessen. Kalibrasi model untuk memperoleh parameter kalibrasi terbaik sehingga debit pemodelan akan mendekati debit observasi. Pemodelan debit menggunakan data harian dari tahun 2012 sampai 2021. Hasil kalibrasi pada model NRECA, yaitu PSUB, GWF, dan Wo adalah masing-masing 0,9; 0,2; 600; dan nilai NSE adalah -1,557. Pada model Sacramento hasil kalibrasi adalah UZTW sebesar 25; UZFW sebesar 400; LZTW sebesar 600; LZFS sebesar 20; dan LZFP sebesar 40. Nilai NSE pada model Sacramento adalah 0,471. Kata kunci: kalibrasi, NRECA, NSE, Sacramento Abstract Hydrological data in determining the amount of discharge is rainfall and climatology. One of the places on the Cimanuk river that has a water observation post is Cimanuk-Bojongloa. Discharge data apart from measurement results, can also use modeling. The models used in this research are the NRECA model and the Sacramento model. Rainfall data for calibration with four station namely Pamegatan, Pangauban, Kapakan, and Bayongbong from 2017 to 2021. Average rainfall is calculated using the Thiessen method. Calibrate the model to obtain the best calibration parameters so that the modeled discharge will be close to the observed discharge. Discharge modeling uses daily data from 2012 to 2021. The calibration results for the NRECA model, namely PSUB, GWF, and Wo are 0.9 each; 0.2; 600; and the NSE value is -1.557. In the Sacramento model the calibration results are UZTW 25; UZFW 400; LZTW 600; LZFS 20; and LZFP 40. The NSE value in the Sacramento model is 0.471. Keywords: calibration, NRECA, NSE, Sacramento

Measurements of the fair-weather electric field in mountainous areas are affected by the terrain, and therefore need additional calibration to be included in the global field picture. To do this, it is proposed to solve the three-dimensional electric current continuity problem of the atmosphere in the region between the Earth's surface and the ionosphere. As an example, the neighborhood of Klyuchevskaya Sopka is considered. With an increase in the height of the plateaus, the fair-weather electric current density above them increases, and the electric field strength decreases. A one-dimensional model of atmosphere conductivity is not applicable for terrain with steep slopes. A comparison of the daily-seasonal diagrams constructed according to the data of the Carnegie Cruise VII and according to the Tomsk Observatory showed the similarity of variations of the fair-weather electric field strength in such different places on the Earth. The field over the sea is about half as small as over low-lying land at the same time.

Across the world best practice, the flood hazard and risk maps are core instruments used for the development and implementation of flood management policies. These maps sit as base information for developing flood management strategies and plans, designing of new flood defence schemes and assessment of the existing flood scheme performance, elaboration of emergency and action plans, territorial planning (zoning and permissions), land use control, climate changes impacts evaluation, insurance industry etc. Romania did remarkable steps in developing high quality flood hazard and risk maps as core action for an integrated flood risk management. In the second cycle of Floods Directive 2007/60/EC implementation, Romania developed and reported to European Commission (EC) the hazard and risk maps for 526 APSFRs (Areas with Potential Significant Flood Risk). The hazard maps built in second cycle are the result of detailed models developed based on high resolution Lidar (0.5m), calibrated hydrological data and advanced modelling technics. Crasna River is one of the watercourses from the Somes-Tisa Basin which benefited from advanced 2D hydraulic modelling having in-place all the existing infrastructure and which has been well - calibrated on the flood event recorded in 2015. The calibration of the model on 2015 flood event was performed both for flows and levels. The article aims to explicitly present the performance of the existing defence system of Crasna river during extreme flood events with different magnitudes having in hand these high-quality hydraulic model and hazard maps.

Methods of evaluation of interlaboratory comparison results are prescribed by ISO standards. Ruler is probably one of the most widely used length measuring instrument in the world. For laboratories that plan to be accredited for the calibration of Ruler, the acquisition of a specialized Measuring bench is not economically feasible. Confidence in the measured result depends on the measurement uncertainty, and where deficiencies are observed, the values that contribute to the measurement uncertainty should be investigated. This paper describes an interlaboratory comparison for a small number of laboratories on the example of a Measuring bench for calibrating Ruler and indicates the procedure for problem identification; diagnosis of causes; consideration of solutions; initiation of action for improvement and monitoring of the results of applied solutions. The authors documented the problem and listed the elements that contributed to "Unsatisfactory" result in interlaboratory comparisons. They described the actions they took to overcome the "Unsatisfactory" result, analyzed whether the proposed solutions led to "Satisfactory" result and took actions accordingly. The paper presents the results of the international interlaboratory comparison, which are a confirmation of the competence of the personnel, measuring calibration equipment and calibration method.

The accuracy of microwave remote sensing relies on the calibration of the radar measurement. It is important to estimate the radar cross-section (RCS) using a passive corner reflector (CR) or active transponder to evaluate the quality of imaging radar data. A strong and consistent RCS can be achieved by the acquisition of radar signals concentrated at specific angles during the CR calibration procedure. There are several types of CR depending on the shape and size such as triangular trihedrals, square trihedrals, dihedrals, spheres, or cylinders. In this study, we examine the RCSs using three types of CR with Ku-band ground-based real aperture radar equipment, the Gamma Portable Radar Interferometer-II. It can be easily deployed to acquire fully polarimetric radar observations. The initial experiment was conducted at Busan Sam-nak Auto Camping Site on November 1, 2023. The amplitude images show much higher backscattered radar signals at the CR location, whereas relatively lower power has been captured in the surrounding areas. The attenuation factors in the radar receivers could be useful to prevent saturation around the CR location at the line-of-sight direction. The experiment indicates that the different levels of the RCS measurements from three types of CRs could be utilized for calibration study with fully polarimetric radar observations.

This comprehensive study delves deeply into the intricate domain of optimizing Micro-electromechanical Systems (MEMS)-based navigation sensors for aerospace vehicles. It entails a meticulous examination of MEMS sensors, focusing on their role in guidance, navigation, and control, with particular emphasis on MEMS inertial sensors and crucial performance metrics. The study investigates a spectrum of techniques for sensor optimization, including strategies for enhancing fabrication and production through smart structures and mathematical modeling. Additionally, it explores methodologies and mechanisms for improving navigation sensor fabrication, along with the incorporation of optimizer techniques to manage computational complexities effectively. The key findings underscore the challenges tied to material selection and structural intricacies in optimizing these sensors for aerospace applications. Integration of sensors into integrated circuits, development of advanced mathematical models, and harmonization with artificial intelligence algorithms are vital for boosting sensor performance, while calibration and error mitigation during user deployment are essential. Furthermore, the study underscores the imperative for addressing limitations in sensor accuracy and precision through refined calibration mechanisms and error correction processes. The trajectory for future research involves advancing material selection, mathematical models, and innovative calibration techniques to comprehensively enhance sensor performance and reliability in aerospace applications.

A calibration system was designed to evaluate the accuracy of linear optical encoders at the micron level in a fast and economical manner. The system uses a commercial interferometer and motor stage as the calibrator and moving platform. Error analysis is necessary to prove the effectiveness and identify areas for optimization. A fixture was designed for the scale and interferometer target to meet the Abbe principle. A five-degree-of-freedom manual stage was utilized to adjust the reading head in optimal or suboptimal working conditions, such as working distance, offset, and angular misalignment. The results indicate that the calibration system has an accuracy of ±2.2 μm. The geometric errors of the calibration system, including mounting errors and non-ideal motions, are analyzed in detail. The system could be an inexpensive solution for encoder manufacturers and customers to calibrate a linear optical encoder or test its performance.

Abstract Background In southern central rift valley of Ethiopia, maize is an important crop because of its adaptation to wider agro-ecologies and higher yield potential. However, most cultivars were not parameterized to include in the database of Decision Support System for Agro-technology Transfer (DSSAT). As a result simulation of growth and yield of those cultivars was not possible under changing climate. Methods Two set of independent crop, management and soil data were used for calibration and validation of genetic coefficients of maize cultivars (BH-540, BH-546, BH-547, Shala and Shone) under condition of historic weather (1990–2020). Later, we simulated the growth and yield of maize using twenty multimodel climate ensembles across RCP 4.5 and 8.5 during early, medium and late century across Shamana, Bilate, Hawassa and Dilla clusters using DSSATv4.8 model. Results Cultivars BH-540, BH-546, BH-547, Shala and Shone produced yields of 5.7, 5.4, 5.2, 6.9 and 7.4 t ha−1 with the corresponding error percentage of − 0.1, − 0.8, − 1.0, − 6.1 and 2.6%. The results of normalized root mean square were 1.14–4.2 and 3.0–3.9%, for grain yield during calibration and validation, respectively showing an excellent rating. The simulation experiment produced 5.4–9.2 t ha−1 for grain yield of maize cultivars across the study areas, which is likely to fall close to 63.3% by 2070 if right adaptation options are not introduced necessitating switch in cultivars and production areas. Conclusions There is critical need for reduction of GHGs emissions, generation of innovative adaptation strategies, and development of drought and heat stress tolerant maize cultivars. Hence, researchers and policy makers shall act with utmost urgency to embark with breeding programs that target climate change adaptation traits in maize crop.

Weather radar calibration is a crucial factor to be considered for quantitative applications, such as QPE (Quantitative Precipitation Estimation), which is used as input for weather risks management. The present work proposes a novel approach to the end-to-end radar calibration method through the characterization of the radar weighting functions. These are Gaussian functions that model an additional attenuation factor to the radar received power. This approach, based on the inclusion these parameters, allow the obtainment of a calibrated equivalent reflectivity factor expression for a Doppler dual-polarization weather radar that operates in the X band. To calculate these parameters, a UAS (Unmanned Aircraft System) was implemented for suspending the calibration target with a well-defined cross-section and for measuring its inclination due to wind using an IMU (Inertial Measurement Unit). From its measurements, the position of the target can be estimated, which is essential to the characterization of the weighting functions. Their inclusion within the radar equation, alongside the implementation of the angular measurement system highlight the innovation to the traditional radar calibration methodology that does not contemplate them from the explored state-of-the-art. The reflectivity was compared with the measurements from a disdrometer for a moderate rain event. An average reflectivity difference of 0.75 dBZ and a percent bias of 3.3 % were obtained between the expected and estimated measurements when including these functions compared to the 1.51 dBZ and –62.7 % obtained when disregarding them. These experimental results point out that the proposed method can deliver superior accuracy in the reflectivity estimation.

The traditional method of joint calibration of fixed baseline interferometer with multiple errors requires more than three calibration emitters to achieve real-time calibration of the interferometer in orbit, but the performance of the traditional method will be reduced or even failed when the number of calibration emitters is insufficient. For the situation that the number of calibration emitters is insufficient, a single or double emitters calibration method for fixed baseline interferometer is proposed. Under the condition of relative motion between the interferometer and the calibration emitters, a set of phase differences of calibration signals is obtained firstly by multiple measurements, and a set of equations about the systematic errors of the interferometer is listed by using the obtained phase differences, finally the systematic errors are solved by the Penrose inverse matrix assisted iterative least squares method. The simulation results verify the feasibility of the proposed method. On this basis, the influence of the emitter selection on the positioning performance of the interferometer after calibration is analyzed qualitatively by means of numerical simulation, decomposing the parameters of the emitter selection. The analysis results show that the calibration emitter located near the sub-star in the single emitter case or two calibration emitters located far apart both can make the interferometer obtain better positioning performance after calibration.

Recent investigations have noted that using a hybrid arrangement of Soil and Water Assessment Tool (SWAT) and multi-layer perceptron (MLP) has high efficiency in runoff prediction. In this research, in addition to using the SWAT and MLP models, an optimized algorithm called Mutated SunFlower Optimization (MSFO) algorithm has been proposed to predict better runoff, which improves the results of prediction runoff by decreasing the error percentage in the MLP model. For this purpose, first, runoff modeling is used to assess the efficiency of the SWAT system. The model's verification and calibration have been performed using data from the previous 30 years of statistics. Then, the flow stream simulated by the SWAT method is evaluated with the observational data and applied as the inputs to the MLP model, and finally, runoff is predicted through the MLP model, and MSFO is used in the MLP model to obtain better results for runoff prediction. The results show that the values of statistical indices R2, RMSE, NSE, and RE give satisfying agreement for runoff forecast in the SWAT–MLP/MSFO model with values of 0.83, 1.68, 0.51, and −0.1. HIGHLIGHTS Two versions of the SWAT model are utilized for forecasting runoff.; The SWAT–MLP model is based on Multi-Layer Perceptron networks.; The SWAT–MLP is optimized based on an improved metaheuristic.; Modified SunFlower Optimization algorithm is used for optimizing SWAT–MLP.; The SWAT–MLP\MSFO model simulates the runoff more accurately.;

Abstract To date, publications have shown that compositions of oral microbiota differ depending on their habitats (e.g. tongue, tonsils, pharynx). The absence of set standards for the choice of the areas and conditions of material collection makes the oral microbiome one of the most difficult environments for a comparative analysis with other researchers, which is a meaningful limitation during an assessment of the potential effects of microorganisms as biomarkers in the courses of various human diseases. Therefore, standardisation of basic conditions of a dental examination and collection of material for the next generation sequencing (NGS) is worth attempting. The standardisation of the dental exam and collection of the clinical materials: saliva, swab from the tongue ridge, hard palate, palatine tonsils and oropharynx, supragingival plaque and subgingival plaque. Protocol involved the patients (n = 60), assigned to 3 groups: I—COVID-19 convalescents who received antibiotics, n = 17, II—COVID-19 convalescents, n = 23 and III—healthy individuals, n = 20. The collected biological samples were used to conduct NGS (16S rRNA). The conditions of patient preparation for collecting biological materials as well as the schedule of dental examination, were proposed. Based on the research conducted, we have indicated the dental indicators that best differentiate the group of COVID-19 patients (groups I and II) from healthy people (group III). These include the DMFT, D and BOP indices. The use of alpha and beta diversity analysis provided an overall insight into the diversity of microbial communities between specific niches and patient groups. The most different diversity between the studied group of patients (group II) and healthy people (group III) was noted in relation to the supragingival plaque. The order of activities during the dental exam as well as while collecting and securing clinical materials is particularly important to avoid technical errors and material contamination which may result in erroneous conclusions from the analyses of the results of sensitive tests such as the NGS. It has been shown that the dental indices: DMFT, D number, PI and BOP are the best prognostic parameters to assess the oral health. Based on beta diversity the most sensitive niche and susceptible to changes in the composition of the microbiota is the supragingival plaque. The procedures developed by our team can be applied as ready-to-use forms in studies conducted by other researchers.

Abstract Background Since color measurements are relative, the discrepancy among different instruments is alarmingly high. This multicenter study evaluated the effectiveness of instrument calibration and inter-instrument harmonization of different spectrophotometers with the same optical geometry using tooth-colored, translucent dental materials. Methods The coordinating center (CC) spectrophotometer was calibrated using the NPL Ceram Series II set. Two sets of 10 specimens, labeled 1 to 10 and I to X (10 mm in diameter and 1 mm thick), were tested at CC and three research sites (RS1, RS2, and RS3) using the same d/8° optical geometry spectrophotometers. Calibration factors were calculated for each material and site to obtain the average calibration factors for sets 1–10, set I-X, and the combination of both. The differences among the non-corrected and corrected reflection values were calculated using CIEDE2000 (DeltaE00) and CIELAB (DeltaEab) color difference formulas and were submitted to ANOVA and Tukey test (α = 0.05). Results A significant decrease of color differences between non-corrected as compared to corrected measurements was recorded for all CC-RS and RS-RS comparisons. The reduction of DeltaE00 values between non-corrected and corrected for CC-RS1, CC-RS2, and CC-RS3 were 83.1%, 77.2%, and 73.6%, respectively. The corresponding DeltaE00 values for RS1-RS2, RS1-RS3, and RS2-RS3 comparisons, indirectly compared in the experiment, were 84.2%, 82.8%, and 68.5%, respectively. There was a significant reduction of DeltaE00 and DeltaEab color difference for all combined RS pairs and each of three RS pairs, corrected with one of two specimen sets calibration factors separately. Conclusions Calibration and harmonization of color measurements in dentistry using tooth-colored, translucent restorative materials significantly decreased measurement discrepancies between the coordinating center and research sites and among pairs of research sites.

To prevent severe safety accidents caused by primary coolant leakage in pressurized water reactors (PWRs), it is necessary to monitor the leakage rate of key parts of the reactor coolant pressure boundary (RCPB) in order to take timely countermeasures. The primary coolant of PWRs is usually high-pressure supercritical water containing boron, which can produce 18F in the high neutron flux environment of the reactor. The leak rate of the RCPB can be inferred by measuring the activity concentration of the radioactive 18F aerosol produced by the coolant leaking into the containment. A measurable sample source is usually obtained by extracting sample gas containing 18F aerosol from the containment and filtering it in the monitor. The measurement method used by the monitor is to screen the γ signal by using the β signal as the gate signal, which is actually a γ relative measurement method using the coincidence method to reduce the background. The electronic design of the monitor prevents the β-channel signal from being recorded, which makes it impossible to achieve the absolute measurement as with conventional coincidence methods. To ensure the accuracy of the monitoring results, the 18F aerosol monitor needs to be calibrated. In this paper the monitor was calibrated using a standard 18F surface source produced by the intermittent spot method on a filter paper base. By means of the decay of the 18F source and the automatic recording function of the monitor, the indication number of the monitor was measured at six source activities of different orders of magnitude, i.e. the count of the energy spectrum at the position of the 511 keV γ-window. The data were used to obtain the activity response and uncertainty of the monitor's readings and to verify the feasibility of such a calibration scheme on the monitor. Two standard point sources of 22Na and 68Ge/68Ga were also used to calibrate the monitor to verify the feasibility of using long-lived nuclides to make alternative sources for calibration. Sets of 511 keV γ-window count data from γ and coincidence channels were recorded to investigate the effect of the γ coincidence additive effect and different β emission spectra on the activity response, and to determine which long-lived positron nuclides should be used in the field calibration. Calibration with a standard 18F surface source shows that the monitor can give stable and reliable readings of this type of standard source over different orders of magnitude within the range. The extended uncertainty (k=2) of the displayed activity response is 6.0%, which meets manufacturing requirements. And the calibration of the long-lived positron nuclide standard point sources shows that the positron spectrum has a great influence on the activity response of the monitor, and the γ coincidence additive effect is not very significant. Therefore, it is recommended to use 22Na with β energy close to 18F to make point sources or surface sources for field calibration.

A circuit-based calibration system is presented for active phased arrays. In particular, to achieve the desired (and corrected) consecutive phase differences and relative magnitudes between RF channels, a computer controlled circuit system was developed for dynamic adjustment. The proof-of-concept demonstrator uses a phase sensor, phase shifters (PSs), and variable gain amplifiers, along with other active hardware, to realize a self-calibrating circuit system which achieves the required magnitude and phase for each array element. In addition, measured magnitude and phase imbalances are less than 0.10 dB and 3$^\circ$, respectively. The computer-controlled feed network is then used to demonstrate that the system can automatically calibrate an active antenna array for various beam steering examples. Also, the S-band feed system can self-calibrate due to any monitored magnitude and phase drifts due to temperature changes and practical component ageing, or, other general channel offsets. This can be considered advantageous and simpler when compared to more established approaches which characterize the coupling between elements or the response of the entire array in the near- or far-field for example.

For this study, a substitution principle-based impedance bridge has been developed to calibrate AC resistors in a four-terminal-pair (4TP) configuration. The calibration is performed in the full complex plane for resistances ranging from 100 mΩ to 400 Ω and frequencies of between 50 Hz and 20 kHz. The automated bridge is based on four resistors associated with two high-impedance stages. The balancing of the bridge is achieved by means of PXI modules. The bridge is automatically balanced via a simplex top-down algorithm. The new bridge is primarily used for the measurement chain of AC standard resistors defined in a 4TP configuration at LNE, which are used for routine customer calibrations. The traceability of LNE’s standard resistors when defined in a 4TP configuration is ensured by a measurement chain from a 1 kΩ reference resistor using the new bridge. The reference resistor was calibrated previously via comparison with a calculable resistor up to 20 kHz. The bridge was validated via comparison with calibration results obtained in 1983 and 2009. For a resistor of 1 Ω at 1 kHz, the uncertainty of the series resistance variation and the phase shift are less than 6 µΩ/Ω (k = 1) and 6 µrad (k = 1), respectively.

This paper presents a simple, lightweight, automatic calibration method for low-cost triaxial accelerometers, utilizing the Earth’s gravitational constant in various orientations. It can be easily implemented using only fixed-point arithmetic and can run on low-power microcontrollers for real-time measurements, making it practical for scenarios with limited data storage and computational power, such as actigraphy or IoT applications. The method offers ease of use by automatically detecting motionless intervals, eliminating the need for complex positioning techniques. The procedure detects resting states and calculates the corresponding three-dimensional mean acceleration values during the measurement. After appropriately selecting these mean values, a set of calibration points is formed and passed to a gradient-based optimization algorithm for iterative estimation of the calibration coefficients. Different metrics were used for verification and comparison with other methods, which were calculated through simulations and tests based on real measurements. The results show that, despite its lightweight nature, the method performs equally to more complex solutions. This article provides a thorough explanation of a novel method for collecting calibration points, the optimization algorithm, and the methods used for performance evaluation in a reproducible manner.

We present a Vehicle Model (VM) that has 17 degrees of freedom and includes nonlinear tire and powertrain subsystems. Implemented as a relatively small piece of C++ code, the model runs vehicle dynamics 2000 times faster than real time at a simulation time step of $1 \times 10^{-3}, \text {s}$ on a single core of a commodity CPU. When executed on the GPU, one can perform 300000 vehicle simulations in real-time. These properties make the model a good candidate for reinforcement learning, model predictive control, model predictive path integral control, path planning, state estimation, and traffic simulation tasks. The model is expressive in that it can capture the dynamics of vastly different vehicles. This is demonstrated by first calibrating the model to mimic the dynamics of a 1/ $6^{th}$ scale vehicle called the Autonomy Research Testbed (ART) vehicle, which has a mass of approximately 5.8 kg. Subsequently, the model is calibrated to mimic the dynamics of a heavy-duty High Mobility Multipurpose Wheeled Vehicle (HMMWV), which has a mass of 2097 kg. The Bayesian calibration process discussed can $(i)$ handle real-life measurement noise, and $(ii)$ provide model parameter probability distributions. The vehicle model, which is open source and freely available in a public repository, can also be imported into Python owing to SWIG wrapping.

Abstract Most general population web surveys are based on online panels maintained by commercial survey agencies. Many of these panels are based on non-probability samples. However, survey agencies differ in their panel selection and management strategies. Little is known if these different strategies cause differences in survey estimates. This paper presents the results of a systematic study designed to analyze the differences in web survey results between agencies. Six different survey agencies were commissioned with the same web survey using an identical standardized questionnaire covering factual health items. Five surveys were fielded at the same time. A calibration approach was used to control the effect of demographics on the outcome. Overall, the results show differences between probability and non-probability surveys in health estimates, which were reduced but not eliminated by weighting. Furthermore, the differences between non-probability surveys before and after weighting are larger than expected between random samples from the same population.

Abstract Background Tele-rehabilitation, also known as tele-rehab, uses communication technologies to provide rehabilitation services from a distance. The COVID-19 pandemic has highlighted the importance of tele-rehab, where the in-person visits declined and the demand for remote healthcare rises. Tele-rehab offers enhanced accessibility, convenience, cost-effectiveness, flexibility, care quality, continuity, and communication. However, the current systems are often not able to perform a comprehensive movement analysis. To address this, we propose and validate a novel approach using depth technology and skeleton tracking algorithms. Methods Our data involved 14 participants (8 females, 6 males) performing shoulder abduction exercises. We collected depth videos from an LiDAR camera and motion data from a Motion Capture (Mocap) system as our ground truth. The data were collected at distances of 2 m, 2.5 m, and 3.5 m from the LiDAR sensor for both arms. Our innovative approach integrates LiDAR with the Cubemos and Mediapipe skeleton tracking frameworks, enabling the assessment of 3D joint angles. We validated the system by comparing the estimated joint angles versus Mocap outputs. Personalized calibration was applied using various regression models to enhance the accuracy of the joint angle calculations. Results The Cubemos skeleton tracking system outperformed Mediapipe in joint angle estimation with higher accuracy and fewer errors. The proposed system showed a strong correlation with Mocap results, although some deviations were present due to noise. Precision decreased as the distance from the camera increased. Calibration significantly improved performance. Linear regression models consistently outperformed nonlinear models, especially at shorter distances. Conclusion This study showcases the potential of a marker-less system, to proficiently track body joints and upper-limb angles. Signals from the proposed system and the Mocap system exhibited robust correlation, with Mean Absolute Errors (MAEs) consistently below $$10^\circ$$ 10 ∘ . LiDAR’s depth feature enabled accurate computation of in-depth angles beyond the reach of traditional RGB cameras. Altogether, this emphasizes the depth-based system’s potential for precise joint tracking and angle calculation in tele-rehab applications.

Calibration is essential to optimize the performance of any radio transceiver during its development and manufacturing processes. This paper proposes over-the-air (OTA) calibration methods based on measuring and calibrating the phases of phased array transceiver paths. The phase responses of each signal path with all phase shifter states were characterized using an OTA radio link in the transmission and reception modes. Scattering parameter measurements give amplitude and phase responses over the frequency range, which can be converted to the delay domain with the Fourier transform. In this paper, two new delay domain phase calibration methods are presented and compared with a previously presented frequency domain method. The best performance was achieved with the relative phase calibration method in the delay domain which uses all measurement data to find the calibration values. The other two methods, i.e., the absolute phase calibration method in the delay domain and in the frequency domain, use the average phase as the calibration value. OTA radiation pattern measurements from two prototype 5G millimeter wave transceivers were used to compare the RF performances of the calibration methods, and measurements were performed with a 100 MHz 5G new radio waveform. The radiation patterns were analyzed based on direction accuracy, power level, and side lobe level, to give a few examples. The transceiver units were calibrated using the three studied methods, and while having significantly different uncalibrated performances, after calibration, both transceivers were tuned to similar performance levels.

We recently established an impedance standard for the D-band, one of the 6G candidate frequencies. However, primary standards are difficult to use for routine calibration because they require multiple impedance standards and a lot of time to calibrate the vector network analyzer (VNA). Therefore, a transfer standard is needed to efficiently apply the calibration value and to propagate the uncertainty of the primary standard to a device under test (DUT). In this paper, we describe a design method for a transfer standard with small uncertainty even when an arbitrary DUT is measured. This is achieved by propagating the uncertainty of the primary standard to the transfer standard and then propagating it again to the uncertainty of the DUT. We developed a calibration kit that has low uncertainty over a wide frequency band, from 110 GHz to 170 GHz, and consists of waveguide offset shorts for ease of production. We also propose a method to minimize DUT uncertainty and a method to minimize “phase distance” to find the optimal length of the offset short. When using three offset shorts, an uncertainty similar to that of the short-open-load-thru (SOLT) calibration kit was obtained, and when using four offset shorts, an uncertainty comparable to the primary standard was obtained. Lastly, this paper examines the repeatability of measurements and reproducibility during the production process.

This article presents a novel transmission-only calibration technique for free-space quasi-optical material characterization, based on rotating the sample around its axis to vary the angle of incidence under which the sample is illuminated. In contrast to common time domain approaches, each frequency point is evaluated individually. Thus, no minimum bandwidth is required and artifacts due to time gating are prevented. In this article, two methods are presented: the first is based on self-calibration, such that all error terms are obtained by the measured sample itself. The second one, which is tailored for thin samples, requires two known standards. Since plane-wave illumination cannot be assumed for highly-focused beams, an analytical model for the coupling of arbitrary paraxial beams is developed, accounting for the lateral beam shift in case of angled samples. Thus, the presented methods are not restricted to free-space beams with high Gaussicity, allowing to employ a variety of feed antennas. Measurements in the frequency range from 220 GHz to 330 GHz of a well-known alumina sample verify the different calibration methods.

Abstract The de‐embedding calibration method has been proposed to achieve high‐precision calibration for a single port electric field or magnetic field probe, which can effectively eliminate the calibration ripple. However, the method's effectiveness for a four‐port calibration system has not been verified yet. In this paper, a four‐port de‐embedding calibration method with a differential magnetic field probe is proposed, and its effectiveness is proved. Two symmetric grounded coplanar waveguide transmission lines are applied in the proposed method to solve the ABCD‐matrix of the embedded part of the calibrator. The de‐embedded S‐parameter model of the four‐port calibration system for differential magnetic field probe can be obtained. The calibration results indicate that the proposed method can also reduce the calibration ripple and compensate for the attenuation caused by the calibrator. Compared with the traditional calibration method using a microstrip line calibrator, the ripples of the proposed method can be reduced by 34%. The analysis results of the frequency interval of the ripple (FIR) in different methods show that the de‐embedding method can reduce the FIRs (except around 1.2 GHz) caused by the reflection of the calibrator and retain the FIR (about 1.2 GHz) caused by the reflection of the probe itself.

The accuracy of geophysical retrievals from radiometers relies on calibration quality, encompassing both absolute radiometric accuracy and spectral consistency. Radiometers have employed various calibration techniques, including external targets, vicarious sources, and internal calibrators like noise diodes or matched reference loads. Calibration techniques face challenges like frequency dependence, instrumental effects, environmental influences, drift, aging, and radio frequency interference. Recent hardware advancements enable radiometers to collect raw samples containing both temporal and spectral information. Leveraging advanced modeling techniques like deep learning (DL) enables detecting subtle correlations, non-linear dependencies, and higher-order interactions within the data extracting valuable information that may have been challenging with conventional methods. This study utilizes NASA's Soil Moisture Active Passive (SMAP) satellite's level 1A and level 1B data products to develop a DL-based radiometer calibrator to estimate antenna temperature. Spectrograms of second raw moments equivalent to power carrying the 2-D spectral features serve as primary input in a supervised convolutional neural network-based architecture. DL-based calibrator has demonstrated high correlation and low root mean square error when incorporating spectral information from both reference and noise diodes and when not considering this information. Findings suggest that the ancillary features such as internal thermistor temperature and loss elements exhibit sufficient accuracy in estimating antenna temperature to compensate for variations in receiver noise temperature and short-term gain fluctuations in the absence of the reference load and noise diode power. The proposed calibration technique with reduced reference information might enable radiometers for a higher number of antenna scene observations within a footprint.

To measure the distinct interaction of the Earth's materials with solar electromagnetic radiation, field spectroradiometers are commonly utilized. These are used to validate spectroradiometers deployed on various platforms through comparison exercises. Following metrology standards, the inclusion of uncertainties is required. Thus, field spectroradiometers need to be calibrated regularly against traceable radiance sources. In this article, we present a laboratory radiometric calibration protocol for the calibration of a heliosphere integrating sphere to make it traceable to the International System of Units as well as to establish an uncertainty budget. We adopted a transfer radiometer approach including four spectroradiometers that were calibrated at the Deutsches Zentrum für Luft und Raumfahrt Radiometric Standard facility before transferring that calibration to the heliosphere. After considering various sources of uncertainty by employing an uncertainty tree diagram approach, we arrive at an overall propagated uncertainty of approximately 1.5%. In future publications, we will present how to extend the traceability to other attenuations provided by the heliosphere. Its application to the calibration of a field spectroradiometer will be the focus of a future publication.

Land use changes are one of the main factors in the amount of surface runoff changes in watersheds. Therefore, it is necessary to investigate it to reduce the damages (human and financial) caused by floods and to modify watershed management. The watershed of Nahre Azam is located in the north of Shiraz city and a lot of loss of life and money to the residents of Shiraz due to floods has occurred in previous years. The present research was conducted to investigate the relationship between land use change and runoff in the Nahre Azam watershed in Shiraz using the SWAT model in the period of 2004-2020. The model was calibrated using data from 2004 to 2014 and validated for 2015 to 2020. These images were classified into 6 main land uses using the supervised classification method after performing necessary pre-processing, and a land use map was prepared for 2040 using the Markov chain method. Then, the effect of the land use change in 2003 and 2040 on the amount of simulated runoff was evaluated with the recalibrated model. The calibration results of Nahre Azam watershed for the values of statistical parameters in the calibration step for the coefficient of determination, P-Facor and R-Facor are 0.77, 0.72, and 2.43, respectively, and for the validation step we obtained 0.69, 0.65, and 2.3 respectively. The analysis of the land use map showed that the main land use change in the region related to the conversion of pastures to agricultural land and urban land, which caused a decrease in pastures. Also, the results of the model simulation using the land use maps of 2003 and 2040 indicated that the amount of runoff decreased. The results revealed that if all the uncertainties are minimized, the calibrated SWAT model can produce acceptable hydrological simulation results for the user, which is useful for water resource and environmental managers and politicians as well as city managers of Shiraz.

Scanning probe microscopy (SPM) techniques are widely used to study the structure and properties of surfaces and interfaces across a variety of disciplines in chemistry and physics. One of the major artifacts in SPM is (thermal) drift, an unintended movement between sample and probe, which causes a distortion of the recorded SPM data. Literature holds a multitude of strategies to compensate for drift during the measurement (online drift correction) or afterwards (offline drift correction). With the currently available software tools, however, offline drift correction of SPM data is often a tedious and time-consuming task. This is particularly disadvantageous when analyzing long image series. Here, we present unDrift, an easy-to-use scientific software for fast and reliable drift correction of SPM images. unDrift provides three different algorithms to determine the drift velocity based on two consecutive SPM images. All algorithms can drift-correct the input data without any additional reference. The first semi-automatic drift correction algorithm analyzes the different distortion of periodic structures in two consecutive up and down (down and up) images, which enables unDrift to correct SPM images without stationary features or overlapping scan areas. The other two algorithms determine the drift velocity from the apparent movement of stationary features either by automatic evaluation of the cross-correlation image or based on positions identified manually by the user. We demonstrate the performance and reliability of unDrift using three challenging examples, namely images distorted by a very high drift velocity, only partly usable images, and images exhibiting an overall weak contrast. Moreover, we show that the semi-automatic analysis of periodic images can be applied to a long series containing hundreds of images measured at the calcite–water interface.

ObjectiveThis study proposes a design scheme for an underwater magnetic sensor calibration device. The device is composed of an electromagnetic coil and integrated navigation equipment which can be carried on a mobile platform to sail on the water surface, and realize the high-precision calibration of the position and attitude of the underwater magnetic sensor.MethodsAccording to information on the coil's attitude, orientation and trajectory, and the measured values of the magnetic field generated by the coil at the magnetic sensor, the position and attitude of the underwater magnetic sensor can be calculated using a nonlinear optimization algorithm. The mathematical model of the whole system is established and numerical verification tests are carried out, considering the effects of the measuring accuracy of the coil's position and attitude, the magnetic sensor's noise and measuring error, and geomagnetic interference.ResultsWhen the device is used and the magnetic sensor is at a depth of 30 m underwater, the mean value of position error is not more than 0.06 m, and the mean value of attitude error is not more than 0.20°; the accuracy of the magnetic sensor itself is the main factor affecting the calibration accuracy. ConclusionsThe proposed calibration device can achieve the high-precision calibration of the position and attitude of an underwater magnetic sensor at the same time, giving it great application value. It can be widely used in underwater magnetic target detection, resource exploration, medicine and other fields, especially scenarios involving the attitude deviation of underwater magnetic sensors.

To ensure the measuring accuracy of the wall temperature, the outer wall temperature measurement values by using three kinds of thermocouple welding methods were analyzed and evaluated in the paper, including single-point flush-mounted in the wall groove method, single-point insert-mounted in the wall groove, and outer surface direct welding method, based on the application of a tube-in-tube condensing heat exchanger. And the impacts of silver, tin, and thermal resistance adhesive as filling materials on wall temperature measurement were also investigated, and the results were compared to that obtained without filling materials. The results showed that the wall temperatures measured by the three welding methods were lower than the theoretically calculated value. And the wall temperature measured by the outer surface direct welding method was lowest under the same experimental conditions. The wall temperatures measured by single-point flush-mounted and insert-mounted in the wall groove methods were also affected by different welding filling materials. It was found that the greater the thermal resistance of filling materials, the smaller the heat loss. By analyzing the reasons for the low measured value of wall temperature, a new wall temperature measurement method was developed to improve the accuracy of the current measurement method. Meanwhile, the outer wall temperature measurement experiments of vertical and horizontal heat transfer tubes were carried out to validate and calibrate the improved outer wall temperature measurement method. The results showed that the average outer wall temperature deviation measured by the improved wall temperature measurement method ranged from −0.82% to +2.29% for vertical tubes and −4.75% to −1.44% for horizontal tubes, and the improved measurement method had good measurement accuracy.

The Water Erosion Prediction Project (WEPP) model has been widely used for estimating runoff and soil loss. The evaluation of the latest version (version 2021.133) under a range of environmental conditions can provide confidence to its users. The objectives of this study were to evaluate the WEPP model for runoff and soil loss predictions using 1159 plot years of rainfall-runoff events data from field experimental plots with various climates, soils, topographies, and crops. WEPP runoff and soil loss predictions were compared to the observations before and after input parameter calibration. The results showed good predictions of runoff and soil loss were obtained with both the uncalibrated and calibrated WEPP model for all considered scales with Nash-Sutcliffe model efficiencies (NSE) over 0.4. The calibration of input baseline effective hydraulic conductivity (ke), baseline critical shear stress (τc), baseline rill erodibility (kr), and baseline interrill erodibility (ki) improved WEPP model performance with NSE values of 0.98 and 0.91 for average annual runoff and soil loss predictions, respectively. The WEPP model tended to underestimate the runoff and soil loss for large events with runoff over 100 mm and soil loss over 120 t/ha. Good event runoff and soil loss predictions (NSE ≥0.4) were obtained for the most common cropping/management systems considered, including corn, cotton, tilled fallow, and wheat after calibration. This study illustrates the most recent WEPP model's performance for runoff and soil loss predictions, and provides a comprehensive set of results.

AbstractThe current study analyzed the impact of Land Use Land Cover (LULC) change on streamflow and surface water availability in the Akaki catchment of the Awash Basin, Ethiopia. Soil and Water Assessment Tool (SWAT) and Climatic Water Balance (CWB) models were used. The SWAT model calibrated and validated the daily streamflow. The results indicated that from 1993 to 2016, built-up and barren land areas increased by 5.3% and 3.4%, respectively. The SWAT model over-simulated the peak flows and best simulated the medium and low flows. Based on the calibrated daily streamflow, the runoff was 236.01 mm and 272.59 mm under the 1993 and 2016 LULC scenarios. The total water yield of the catchment was 366.7 mm and 382.01 mm for the 1993 and 2016 LULC scenarios, respectively. The seasonal CWB of the catchment depicted decreasing trend except for the Tsedey (SON) season. Based on the current study’s findings, since LULC change enhanced surface runoff and total water yield in the catchment, proactive flood management is recommended to reduce the impact of the flood hazard on life and property.

Recently, several memory-type mean estimators (including ratio, product, and logarithmic) have been developed. These estimators rely on exponentially weighted moving average (EWMA), which incorporate both historical and present sample data. In this article, we propose EWMA type calibrated estimators under single and double stratified random sampling (StRS). Because calibration method enhances the estimates by modifying the stratification weight, taking advantage of supplementary information. To evaluate the performance of estimators, various real-world time-scaled data sets pertaining to stock market and weather are taken into account. Additionally, we also conduct a simulation study using a bivariate symmetric data set. The numerical results show the superiority of proposed estimators (y¯TM,y¯TaM) over the adapted ones (y¯PM,y¯PaM).

Many video-based eye trackers rely on detecting and tracking ocular features, a task that can be negatively affected by a number of individual or environmental factors. In this context, the aim of this study was to practically evaluate how the use of a scleral contact lens with two integrated near-infrared lasers (denoted CLP) could improve the tracking robustness in difficult lighting conditions, particularly outdoor ones. We assessed the ability of the CLP (on a model eye) to detect the lasers and to deduce a gaze position with an accuracy better than 1° under four lighting conditions (1 lx, 250 lx, 50 klux and alternating 1lx /250 lx) on an artificial eye. These results were compared to the ability of a commercial eye tracker (Pupil Core) to detect the pupil on human eyes with a confidence score equal to or greater than 0.9. CLP provided good results in all conditions (tracking accuracy and detection rates). In comparison, the Pupil Core performed well in all indoor conditions (99% detection) but failed in outdoor conditions (9.85% detection). In conclusion, the CLP presents strong potential to improve the reliability of video-based eye-trackers in outdoor conditions by providing easy trackable feature.

Abstract Breaking atmospheric gravity waves (GWs) in the tropical stratosphere are essential in driving the roughly 2‐year oscillation of zonal winds in this region known as the Quasi‐Biennial Oscillation (QBO). As Global Climate Models (GCM)s are not typically able to directly resolve the spectrum of waves required to drive the QBO, parameterizations are necessary. Such parameterizations often require knowledge of poorly constrained physical parameters. In the case of the spectral gravity parameterization used in this work, these parameters are the total equatorial GW stress and the half width of phase speed distribution. Radiosonde observations are used to obtain the period and amplitude of the QBO, which are compared against values obtained from a GCM. We utilize two established calibration techniques to obtain estimates of the range of plausible parameter values: History matching & Ensemble Kalman Inversion (EKI). History matching is found to reduce the size of the initial range of plausible parameters by a factor of 98%, requiring only 60 model integrations. EKI cannot natively provide any uncertainty quantification but is able to produce a single best estimate of the calibrated values in 25 integrations. When directly comparing the approaches using the Calibrate, Emulate, Sample method to produce a posterior estimate from EKI, history matching produces more compact posteriors with fewer model integrations at lower ensemble sizes compared to EKI; however, these differences become less apparent at higher ensemble sizes.

Abstract Global Climate Model tuning (calibration) is a tedious and time‐consuming process, with high‐dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand‐picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere‐only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient‐based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly‐tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high‐dimensional output and operating in a fraction of the time.

Uncrewed aerial vehicles (UAV) have great potential for use in forest inventories, but in practice they can be expensive for relatively small inventory areas as a large number of field measurements are needed for model construction. One proposed solution is to transfer previously constructed models to a new inventory area and to calibrate these with a small number of local field measurements. Our objective was to compare calibration of general models and the construction of new models to determine the best approach for UAV-based forest inventories. Our material included field measurements and UAV-based laser scanning data, from which individual trees were automatically identified. A general mixed-effects model for diameter at breast height (DBH) had been formulated earlier based on data from a geographically wider area. It was calibrated to the study area with field measurements from 2–10 randomly selected calibration trees. The calibrated diameters were used to calculate the diameter of a basal area median tree (DGM), tree volumes, and the volume of all trees at plot-level. Next, new DBH-models were formulated based on the 2–10 randomly selected trees and calibrated with plot-level random effects estimated during model construction. Finally, plot-specific height-diameter regression models were formulated by randomly selecting 10 trees from each plot. Calibration reduced the prediction errors of all variables. An increase in the number of calibration trees decreased error rates by 1–6% depending on the variable. Calibrated predictions from the general mixed-effects model were similar to the separately formulated mixed-effects models and plot-specific regression models.

Precise precipitable water vapor (PWV) observations play a crucially important role in weather and climate research. The Atmospheric Infrared Sounder (AIRS) on-board the Aqua spacecraft is a hyperspectral instrument that offers operational PWV products using infrared (IR) channels. However, the observational accuracy of AIRS-sensed cloudy-sky PWV products is much poorer than that of PWV retrievals under clear sky conditions. We present a new machine learning-based calibration model to improve the observational performance of operational AIRS-derived IR PWV satellite products under all sky conditions, which considers using several dependence elements correlated with remotely sensed IR PWV observations. The first-guess PWV estimates, obtained from the ERA5 reanalysis, are also utilized in the newly developed calibration approach. The ground-based GNSS-sensed PWV observations, collected in 2017 across the world, are used as the expected PWV output for the training of the newly proposed calibration model. The newly calibrated PWV data records considerably outperform operational AIRS-sensed PWV products, compared with independent PWV estimates from radiosonde observations during 2017–2020. The root-mean-square error of operational PWV satellite products decreases 19.05 % from 2.31 mm to 1.87 mm under cloud fraction (CF) = 0 condition (clear sky), 30.71 % from 3.68 mm to 2.55 mm under CF = (0,1] condition (cloudy sky), and 30.14 % from 3.55 mm to 2.48 mm under CF = [0,1] condition (all sky). The calibration method exhibits much higher RMSE reductions than previous approaches that do not utilize the first-guess PWV estimates, illustrating the effectiveness of our calibration approach. This research provides insights into calibrating satellite-sensed PWV estimates based on machine learning by jointly using ground-based and reanalysis-based PWV observations. The newly proposed calibration method has significant potential to calibrate operational PWV products from other satellite-borne sensors, in addition to the AIRS instrument.

Incubator Analyzer is a calibration tool used to measure temperature, mattress temperature, humidity, airflow, and sound level in baby incubators. The purpose of this research is to make a tool "Design of Incu Analyzer for IOT based Baby Incubator Calibration (Chamber Temperature)” with LCD display and Thingspeak. The design of this calibration tool consists of baby incubator chamber temperature parameters consisting of 5 points, namely T1, T2, T3 , T4, T5 using the DS18B20 sensor and using the ESP32 microcontroller to take advantage of the IOT system. Utilization of IOT on ESP32 is using Wi-Fi. The ESP32 microcontroller processes data from the DS18B20 temperature sensor which is then displayed on the LCD display and Thingspeak. Testing of this tool is done by comparing incubator analyzer module with a standard measuring instrument, INCU II. In this study, the temperature parameter obtained the smallest error value of -0,059293% at T5 with a setting temperature of 36°C and the largest error value of -0,0254188% at T2 with a setting temperature of 35°C. Overall the conclusions obtained after carrying out the literature study process, and planning, it can be concluded that the tool "Incu Analyzer Design for IOT based Baby Incubator Calibration" can be used according to the plan, namely Incubator Analyzer with IOT based.

An infusion pump is a tool used to inject a certain amount of fluid into the patient's body through the patient's veins continuously over a certain period of time. A syringe pump is a tool that functions to push the syringe rod so that it can produce a flow ranging from microliters to milliliters per minute periodically with high accuracy. Very often there are problems with blockages or occlusion when using infusion pumps and syringe pumps. The occlusion limit set is ≤20 PSI according to ECRI. The presence of occlusion in the infusion pump and syringe pump can be identified when there is an alarm buzzer which will sound when a blockage is detected. A 1 Channel Portable Infusion Device Analyzer has been designed using the SKU 237545 Sensor, namely by using a 1 channel flowrate and occlusion sensor and making it portable to be efficient. For this reason, it is necessary to analyze the performance of the tools that have been created. How accurate is it? From the results of performance testing, Oclusion was corrected at 0.242 psi and 0.3 Psi. For flow rate, the largest correction was 2.4 ml/hour and the uncertainty was 6,046 ml/hour. This shows that the accuracy of the design is still quite high and the resulting tool is still not stable, this can be seen from the uncertainty value. The uncertainty that occurs is likely due to the sensitivity of the droplet sensor related to the detection time of the droplet

Low-cost sensor arrays are an economical and efficient solution for large-scale networked monitoring of atmospheric pollutants. These sensors need to be calibrated in situ before use, and existing data-driven calibration models have been widely used, but require large amounts of co-location data with reference stations for training, while performing poorly across domains. To address this problem, a meta-learningbased calibration network for air sensors is proposed, which has been tested on ozone datasets. The tests have proved that it outperforms five other conventional methods in important metrics such as mean absolute error, root mean square error and correlation coefficient. Taking Manlleu and Tona as the source domain and Vic as the target domain, the proposed method reduces MAE and RMSE by 17.06% and 6.71% on average, and improves R2 by an average of 4.21%, compared with the suboptimal pre-trained multi-source transfer calibration. The method can provide a new idea and direction to solve the problem of cross-domain and reliance on a large amount of co-location data in the calibration of sensors.

Low-cost automatic irrigation systems require quality calibrated soil moisture sensors. The sensor is an indirect method of soil moisture measurement. The sensor works based on the change in the dielectric constant. So, it requires to be calibrated in terms of the soil water content. Polynomial and linear models are frequently used to calibrate soil moisture sensor data in the gravimetric test method. However, computational effort is required. This study aims to obtain a sensor calibration application that can provide the best model of the available models for model-based capacitive soil moisture sensor. This research was conducted using primary data from gravimetric test experiment on Internet of things (IoT) based soil moisture sensor. Web-based re-calibration application produced best model based on adjusted R Squared. Finally, model-based capacitive soil moisture sensor set up using best model coefficient. The results show that the web-based re-calibration application can provide the best model for model-based capacitive soil moisture sensor. Based on gravimetric test experiments and web applications, the best model is a polynomial regression model order 3 with 0.945 adjusted R Squared. The model predicted value for soil moisture is in the range 0 – 1.2 for raw sensor data values of 100 – 530. When the model coefficient configured in capacitive soil moisture sensor and Blynk application, soil moisture measurement can be done via mobile phone in real time.