Calibration Measurements Research Articles

Measurement Technique for the Absolute Acoustic Nonlinearity Parameter Employing Only a Narrowband Pulser

In the nonlinear ultrasonic technique, the measurement of the absolute acoustic nonlinearity parameter is employed to obtain quantitative material nonlinearity. In the piezoelectric method, this measurement involves two processes: calibration and harmonic measurements. In the calibration process, a transfer function is obtained, and distortion of the propagating wave is measured in the harmonic measurement. In the conventional method for this measurement, a narrowband pulser is typically used for the harmonic measurement, while a broadband pulser is used for the calibration measurement. In this study, we propose a technique that utilizes a narrowband pulser for both harmonic and calibration measurements. First, we introduced the proposed method to measure the transfer function in the calibration measurement employing the narrowband pulser. Then, we compared the results of the transfer functions and the absolute acoustic nonlinearity parameters obtained using both a narrowband and broadband pulser in the calibration. Based on the experimental results, we found that the results obtained using both the proposed and conventional methods are highly similar, confirming the validity of the proposed measurement technique. In conclusion, even though we exclusively employ the narrowband pulser, we can accurately measure the absolute nonlinearity parameter, leading to a reduction in the required measurement equipment.

External validation and calibration of the HoLISTIC Consortium's advanced-stage Hodgkin lymphoma international prognostic index (A-HIPI) in the Brazilian Hodgkin lymphoma registry.

The Hodgkin lymphoma International Study for Individual Care (HoLISTIC) Consortium's A-HIPI model, developed in 2022 for advanced-stage classical Hodgkin lymphoma (cHL), predicts survival within 5 years amongst newly diagnosed patients. This study validates its performance in the Brazilian Hodgkin lymphoma registry. By 2022, the Brazilian HL registry included 1357 cHL patients, with a median 5-year follow-up. Probabilities for 5-year progression-free survival (PFS) and overall survival (OS) were calculated using A-HIPI-model equations. Discrimination (Harrell C-statistic/Uno C-statistic) and calibration measures assessed external validation and calibration. Lab values beyond the allowed range were excluded, mirroring the initial A-HIPI analysis. A total of 694 advanced-stage cHL patients met the original inclusion criteria (age 18-65 years, Stage IIB-IV). Median age was 31 years; 46.3% were females. Stage distribution was IIB (33.1%), III (27.4%), IV (39.5%). Bulky disease in 32.6%. Five-year PFS and OS were 68.4% and 86.0%, respectively. Harrell C-statistics were 0.60 for PFS and 0.69 for OS, and Uno C-statistics were 0.63 for PFS and 0.72 for OS. Calibration plots demonstrated well-calibrated predictions with calibration slopes of 0.91 and 1.03 for 5-year OS and PFS, respectively. Despite differing patient, clinical characteristics, and socioeconomic factors, the baseline prediction tool performed well in the Brazilian cohort, demonstrating adequate discrimination and calibration. This supports its reliability in diverse settings.

In-situ calibration for real-time infrasound station monitoring and improved wave parameter determination

Infrasound signals can be detected using a time-delay of arrival approach to derive the back azimuth and trace velocity of the coherent wave. For these calculations, it is necessary to have a calibrated measure of the pressure. Although the calibration of microbarometers can be performed in a laboratory setting and in the field with specific metrological means such as those developed by the CEA, it is much more difficult to determine the transfer function of the wind noise reduction systems (WNRS), designed to reduce the wind associated noise. In-situ calibration of these WNRS's can be performed using a co-located, calibrated reference sensor. System defects, such as flooded pipes or blocked inlets, have significant impacts on the response, which in turn would influence the calculated infrasonic wave parameters. These defects can be characterized using in-situ calibration measurements. Experiments were undertaken at the infrasound station IS26 as part of the EMPIR Infra-AUV project, using a temporary detector that was used to simulate defects on the WNRS. This allowed for the effects on real infrasound detections to be quantified and corrected using in-situ calibrations. Additionally, case studies at IMS stations were performed demonstrating the utility of these methods on operational infrasound stations.

In-flight pixel degradation of the Sentinel 5 Precursor TROPOMI-SWIR HgCdTe detector

Abstract The TROPOMI-SWIR HgCdTe detector on the Sentinel-5 Precursor mission has been performing in-orbit measurements of molecular absorption in Earth's atmosphere since its launch in October 2017. In its polar orbit the detector is continuously exposed to potentially harmful energetic particles. Calibration measurements taken during the eclipse are used to inspect the performance of this detector. This paper explores the in-orbit degradation of the HgCdTe detector.
After five years, the detector is still performing within specifications, even though pixels are continuously hit by cosmic radiation. The bulk of the impacts have no lasting effects, and most of the damaged pixels (95%) appear to recover on the order of a few days to several months, attributed to a slow spontaneous recovery of defects in the HgCdTe detector material. This is observed at the operational temperature of 140 K. The distribution of the observed recovery times has a mean around nine days with a significant tail towards several months. Pixels that have degraded have a significant probability to degrade again. The location of faulty pixels follows a Poissonian distribution across the detector. No new clusters have appeared, revealing that impacts are dominated by relatively low energetic protons and electrons. Due to the observed spontaneous recovery of pixels, the fraction of pixels meeting all quality requirements in the nominal operations phase has always been over 98.7%. 
The observed performance of the TROPOMI-SWIR detector in-flight impacts selection criteria of HgCdTe detectors for future space instrumentation.

New guidelines for ISO 9053 based on CFD simulations of the static airflow resistivity of a perforated solid

The acoustic absorption coefficient of the acoustic absorbers is directly impacted by the airflow resistivity. The ISO 9053 explains the measurement procedure and specify the size and mounting of specimens, and the flow velocities. The main constraint of the standard is to maintain a stable linear flow so that the resistance is independent of the velocity. Additionally, it suggests a straight cylindrical pores specimen whose airflow resistivity value can be calculated theoretically. Any other specifications about the calibration specimen design are given. As the flow dynamics inside the perforated low porosity solid behave nonlinearly, it is important to integrate further guidelines in the design of the calibration specimens and measurements. This work presents CFD calculations results using OpenFoam, on the flow resistivity of a cylindrical solid containing a single perforation. The airflow velocity was determined based on the Reynolds number at the pore, which was varied between 0.33 to 2000. Different calibration specimens were tested by varying the length and the perforation diameter. An excellent agreement was observed between CFD and experimental data with an error of 5 %. The results show that the second-order extrapolation of specific resistance should be limited to Reynolds numbers equal to 500.

Multicentre Validation of the RESECT-90 Prediction Model for 90-Day Mortality After Lung Resection

BackgroundThe RESECT-90 model was developed to predict 90-day mortality for patients undergoing lung resection but hasn't been externally validated. The aim of this study was to validate the RESECT-90 clinical prediction model using multicentre patient data from across the United Kingdom (UK). Materials and MethodsData from 12 UK thoracic surgery centers for patients undergoing lung resection between 2016 and 2020 with available 90-day mortality status were used to externally validate the RESECT-90 model. Measures of discrimination (area under the receiving operator characteristic curve [AUC]) and calibration (calibration slope, calibration intercept and flexible calibration plot) were assessed as measures of model performance. Model recalibration was also performed by updating the original model intercept and coefficients. ResultsA total of 12,241 patients were included. Overall 90-day mortality was 2.9% (n = 360). Acceptable model discrimination was demonstrated (AUC 0.74 [0.73, 0.75]). Calibration varied between centers with some evidence of overall model miscalibration (calibration slope 0.80 [0.66, 0.95] and calibration intercept 0.40 [0.29, 0.52]) despite acceptable appearances of the flexible calibration plot. The model was subsequently recalibrated, after which all measures of calibration indicated excellent performance. ConclusionsAfter external validation and recalibration using a large contemporary cohort of patients undergoing surgery in multiple geographical locations across the UK, the RESECT-90 model demonstrated satisfactory statistical performance for the prediction of 90-day mortality after lung resection. Whilst the recalibrated model will require ongoing validation, the results of this study suggest that routine use of the RESECT-90 model in UK thoracic surgery practice should be considered.

Development and internal validation of prehospital prediction models for identifying intracerebral haemorrhage in suspected stroke patients

IntroductionDistinguishing patients with intracerebral haemorrhage (ICH) from other suspected stroke cases in the prehospital setting is crucial for determining the appropriate level of care and minimising the onset-to-treatment time, thereby...

Novel multi-function setup comprising ultra-bright uniform source for spectral and radiometric calibrations of digital imaging sensors and multiple spectrometric applications

Abstract A new setup is being developed for calibrating CCD/CMOS sensors and cameras, and measuring spectrophotometric quantities in both point-wise and imaging modes. The setup includes a laser-driven light source (LDLS), double-grating monochromator, and an integrating sphere with specific design for two-dimensional (2D) spectrophotometric measurements of complex samples and spectral responsivity calibration of digital imaging sensors and cameras in the visible to near infrared (VIS-NIR) region. The setup can cover a spectral range from 250 nm to 2000 nm with relatively high radiance. The study presents optimization and validation work in the visible through NIR spectral range, up to 1000 nm. Preliminary experiments suggest improved accuracy and lower uncertainties for better metrological performance and sophisticated applications. The developed instrument promises a variety of novel applications while suppressing systematic errors and inaccuracies. The presented measurements results include the validation of 2D spectral reflectance/transmittance measurements in the 360-1000 nm spectral region using selected homogenous standards. Additionally provided are the findings of demonstration measurements for 2D spectral transmittance and the CCD camera’s spectral responsivity within the same spectral range.

An analytical heat transfer model for transient Raman thermometry analysis.

Transient Raman thermometry improves on its steady-state counterpart by eliminating the error-prone steps of temperature calibration and laser absorption measurement. However, the accompanying complex heat transfer process often requires numerical analysis, such as the finite element method, to decipher the measured data. This step can be time-consuming, inconvenient, and difficult to derive a physical understanding of the heat transfer process involved. In this work, the finite element method is replaced by fitting the measured data to an analytical three-dimensional heat transfer model. This process can be completed in a few seconds. Using this approach, the in-plane thermal conductivity of two bulk layered materials and the interfacial thermal conductance between two-dimensional materials and quartz have been successfully measured. Based on our model, we performed an analytical quantitative sensitivity analysis for transient Raman thermometry to discover new physical insights. The sensitivity of the in-plane thermal conductivity of bulk layered materials is dictated by the ratio between the spot radius and heat spreading distance. The sensitivity of the interfacial thermal conductance between two-dimensional materials and quartz is determined by its conductance value. In addition, the uncertainty of the measured value contributed by the uncertainty of the input parameters can be efficiently estimated using our model. Our model provides an efficient data and sensitivity analysis method for the transient Raman thermometry technique to enable high throughput measurements, facilitate designing experiments, and derive physical interpretations of the heat transfer process.

Calibration of MAJIS (Moons and Jupiter Imaging Spectrometer): V. Validation with mineral samples and reference materials.

MAJIS (Moons and Jupiter Imaging Spectrometer) is the imaging spectrometer onboard ESA's JUICE (JUpiter and ICy Moons Explorer) spacecraft that operates in the visible and near/mid-infrared between 0.5 and 5.54μm. Before the launch of JUICE in April 2023, MAJIS underwent a comprehensive on-ground calibration campaign in between August and September 2021 in the IAS (Institut d'Astrophysique Spatiale, Université Paris-Saclay) calibration facilities. Among all the operations, calibration sequences using a set of natural mineral samples and synthetic reference materials were acquired in order to characterize MAJIS performances under conditions assumed to be close to certain future observation configurations. Here, we analyze these calibration measurements using comparison with laboratory reference spectra to quantify MAJIS spectral and spatial performances while observing these solid surfaces. We first assess the MAJIS absolute spectral calibration of the visible and near-infrared channel covering half of the wavelength range. We then quantify spectral performances in terms of global spectral slopes, band detection, band shape, and depth retrievals, over most of the spectral range using six mineral samples. We conclude that for most configurations, the MAJIS instrument demonstrates excellent spectral performances compliant with the requirements. MAJIS can, however, be affected by stray light contributions, notably for wavelengths lower than about 1.2μm, and some performances of the instrument may then be significantly impacted depending on viewing conditions. In particular, we have identified cases of spectral contrast reduction up to 40%, absolute spectral shifts up to 2-3nm, and spectral smile variability by +/1nm. Finally, we used the MAJIS internal scanning mirror to test its ability to construct hyperspectral images of a few samples: we present the first band depth maps derived with MAJIS while observing a serpentine/carbonate sample, as well as an evaluation of MAJIS spatial point spread function. Overall, the analysis of MAJIS behavior while observing samples confirms most MAJIS expected performance requirements, while revealing subtle spectral perturbations that may be related to stray light and viewing conditions. These differences will be further investigated in-flight during the cruise, with a solar reflected target such as the Moon, as well as Jupiter before the JUICE orbital insertion.

Nonlinear Calibration and Temperature Sensitivity of Makrofol Solid-State Nuclear Track Detectors for Radon Measurement

A key characteristic of a solid-state nuclear track detector (SSNTD) is that as more alpha tracks accumulate on the detector, the likelihood of track overlap will increase, making it difficult to distinguish individual events. This article presents the calibration of an in-house SSNTD using a Makrofol polycarbonate detector and electrochemical etching. The calibration employs a nonlinear log-logistic quantile function, which is nearly linear at low exposures but accounts for the reduced efficiency at high exposures due to overlapping alpha tracks. The function can be fitted to calibration measurements very accurately, eliminating systematic errors previously associated with the method at certain radon exposures. This article explores the uncertainties and detection limits associated with the calibration and outlines methods for their evaluation. Additionally, it includes a preliminary discussion on the method’s sensitivity to temperature.

Development of an affordable light emitting diode spectrophotometer paired with a Python program for calibration and linearity testing and the measurement of uranium(VI).

Uranium (U) is a radiologically and chemically toxic element that occurs naturally in water, soil, and rock at generally low levels. However, anthropogenic uranium can also leach into groundwater sources due to mining, ore refining, and improper nuclear waste management. Over the last few decades, various methods for measuring uranium have emerged; however, most of these techniques require skilled scientists to run samples on expensive instrumentation for detection or require the pretreatment of samples in complex procedures. In this work, a Schiff base ligand (P1) is used to develop a simple spectrophotometric method for measuring the concentration of uranium (VI) with an accurate and affordable light-emitting diode (LED) spectrophotometer. A test for a higher-order polynomial relationship was used to objectively determine the calibration data's linearity. This test was done with a Python program on a Raspberry Pi computer that captured the spectrophotometer's calibration and sample measurement data.

Eigenbin compression for reducing photon-counting CT data size.

Photon-counting CT (PCCT) systems acquire multiple spectral measurements at high spatial resolution, providing numerous image quality benefits while also increasing the amount of data that must be transferred through the gantry slip ring. This study proposes a lossy method to compress photon-counting CT data using eigenvector analysis, with the goal of providing image quality sufficient for applications that require a rapid initial reconstruction, such as to confirm anatomical coverage, scan quality, and to support automated advanced applications. The eigenbin compression method was experimentally evaluated on a clinical silicon PCCT prototype system. The proposed eigenbin method performs principal component analysis (PCA) on a set of PCCT calibration measurements. PCA finds the orthogonal axes or eigenvectors, which capture the maximum variance in the N dimensional photon-count data space, where N is the number of acquired energy bins. To reduce the dimensionality of the PCCT data, the data are linearly transformed into a lower dimensional space spanned by the M<N eigenvectors with highest eigenvalues (i.e., the vectors that account for most of the information in the data). Only M coefficients are then transferred per measurement, which we term eigenbin values. After transmission, the original N energy-bin measurements are estimated as a linear combination of the M eigenvectors. Two versions of the eigenbin method were investigated: pixel-specific and pixel-general. The pixel-specific eigenbin method determines eigenvectors for each individual detector pixel, while the more practically realizable pixel-general eigenbin method finds one set of eigenvectors for the entire detector array. The eigenbin method was experimentally evaluated by scanning a 20cm diameter Gammex Multienergy phantom with different material inserts on a clinical silicon-based PCCT prototype. The method was evaluated with the number of eigenbins varied between two and four. In each case, the eigenbins were used to estimate the original 8-bin data, after which material decomposition was performed. The mean, standard deviation, and contrast-to-noise ratio (CNR) of values in the reconstructed basis and virtual monoenergetic images (VMI) were compared for the original 8-bin data and for the eigenbin data. The pixel-specific eigenbin method reduced photon-counting CT data size by a factor of four with<5% change in mean values and a small noise penalty (mean change in noise of<12%, maximum change in noise of 20% for basis images). The pixel-general eigenbin compression method reduced data size by a factor of 2.67 with<5% change in mean values and a less than 10% noise penalty in the basis images (average noise penalty≤5%). The noise penalty and errors were less for the VMIs than for the basis images, resulting in<5% change in CNR in the VMIs. The eigenbin compression method reduced photon-counting CT data size by a factor of two to four with less than 5% change in mean values, noise penalty of less than 10%-20%, and change in CNR ranging from 15% decrease to 24% increase. Eigenbin compression reduces the data transfer time and storage space of photon-counting CT data for applications that require rapid initial reconstructions.

Montane peatland response to drought: Evidence from multispectral and thermal UAS monitoring

This paper investigates the response of mid-latitude montane peatlands to climate warming, focusing on changes occurring in a montane peat bog during a drought period. Unmanned Aerial Systems (UAS) equipped with multispectral and thermal sensors were used for high-resolution monitoring to analyze qualitative changes within the peat bog and their spatial distribution. The study was conducted in the Rokytka mountain peat bog in Šumava National Park, Czech Republic, which is one of the largest mountain peat bog complexes in Central Europe. Monitoring took place during the 2019 vegetation season, coinciding with the peak of the 2015–2019 drought. The recurrent UAS imaging campaigns were complemented by continuous hydrological and hydropedological monitoring and in-situ calibration measurements. The findings revealed diverging responses of montane peatlands to climate change across different functional zones of the peat bog. UAS thermal mapping identified distinct land surface temperature variations across various vegetation categories under different conditions. Notably, ponds and waterlogged areas displayed a stabilizing effect on land surface temperature variability, though they exhibited different absolute temperatures. In contrast, shallow waterlogged areas exhibited surface temperatures akin to dry open peat areas. Multispectral UAS monitoring demonstrated significant transitions among the peat bog zones in response to heat and drought propagation. The most pronounced changes occurred in shallow waterlogged areas, which shrank notably from 22.8% to 4.5%, while bare peat expanded from 26.8% to 45.5% during the 2019 drought season. High-resolution thermal and multispectral monitoring has revealed the scope and magnitude of the intra-peatland responses to drought and heat waves and serves as a sensible indicator of environmental changes of peatlands. It has disclosed a large cumulative effect of change in an environment composed of highly heterogeneous and subtle structures. The results highlighted the effectiveness of UAS monitoring in understanding the extent of change in montane peatlands as a fragile environment exposed to the effects of climate change.

Predicting treatment resistance in positive and negative symptom domains from first episode psychosis: Development of a clinical prediction model

BackgroundTreatment resistance (TR) in schizophrenia may be defined by the persistence of positive and/or negative symptoms despite adequate treatment. Whilst previous investigations have focused on positive symptoms, negative symptoms are highly prevalent, impactful, and difficult to treat. In the current study we aimed to develop easily employable prediction models to predict TR in positive and negative symptom domains from first episode psychosis (FEP). MethodsLongitudinal cohort data from 1027 individuals with FEP was utilised. Using a robust definition of TR, n = 51 (4.97 %) participants were treatment resistant in the positive domain and n = 56 (5.46 %) treatment resistant in the negative domain 12 months after first presentation. 20 predictor variables, selected by existing evidence and availability in clinical practice, were entered into two LASSO regression models. We estimated the models using repeated nested cross-validation (NCV) and assessed performance using discrimination and calibration measures. ResultsThe prediction model for TR in the positive domain showed good discrimination (AUC = 0.72). Twelve predictor variables (male gender, cannabis use, age, positive symptom severity, depression and academic and social functioning) were retained by each outer fold of the NCV procedure, indicating importance in prediction of the outcome. However, our negative domain model failed to discriminate those with and without TR, with results only just over chance (AUC = 0.56). ConclusionsTreatment resistance of positive symptoms can be accurately predicted from FEP using routinely collected baseline data, however prediction of negative domain-TR remains a challenge. Detailed negative symptom domains, clinical data, and biomarkers should be considered in future longitudinal studies.

The sensitivity of powder characterization tool measurements to particle properties

Calibration of Discrete Element Method (DEM) simulations is challenging and non-standardised. A common approach involves deducing particle properties from bulk measurements obtained through powder characterisation instruments. However, choosing the best bulk measurements for calibrating DEM simulations depends on the specific material and system. This paper presents a detailed sensitivity analysis of four commonly used bulk measurements to aid in selecting the best measurements for DEM calibration: Beverloo C fitting term (flowing density), angle of repose, dynamic angle of repose, and cohesive index. Rolling friction and cohesion significantly impact these measurements, with systems showing higher sensitivity to frictional properties in faster flow conditions, while the coefficient of restitution has low sensitivity. The cubic term of a polynomial fit to the free surface of a rotating drum was investigated for measuring the coefficient of restitution. This method demonstrated better sensitivity, particularly at lower rotational speeds.

O38 A SOCIAL DETERMINANT AND SIMPLE CLINICAL VARIABLES AS THE BEST PREDICTORS OF ESRD BY AN XGBOOST MACHINE LEARNING MODEL IN CKD

Background and Objective: Chronic Kidney Disease (CKD) is a complex disease that affects approximately 13% of the world's population and is growing rapidly due to the increase in aging and the prevalence of type 2 diabetes mellitus, obesity and hypertension. It is difficult to predict who will develop End-Stage Renal Disease (ESRD) and, so far, no prediction model is applied in clinical practice. Our aim was to develop and externally validate an ESRD prediction model with potential utility in clinical decision making. Methods: A longitudinal study was conducted with an 8-year follow-up of sociodemographic, biological, and clinical variables. Individuals with a diagnosis of CKD belonging to the cardiovascular risk program were recruited in two cohorts for derivation and external validation of the model. Classical and machine learning models on an imputed data matrix and sub-databases were explored by bootstrapping and cross-validation, as well as the change in GFR between measurements that predicted ESRD. Measures of calibration, discrimination, and overall predictive performance were presented. Models were trained and tested in sub cohorts and the best performing model was validated in an independent cohort and its uncertainty established. Results: A total of 2514 patients were included, 1650 in the derivation cohort, mean age of 74 years, 40.4% were women. A machine learning xgboost model identified previous GFR, creatinine, blood glucose, HbA1c, HDL cholesterol, BUN and income level as the main predictors of ESRD. Likewise, an inter-measurement GFR delta of 3.09 ml/kg/min was associated with a significant increase of ESRD. In the external validation cohort, with 864 patients, the model maintained an accuracy of 0.98, an AUC of 0.776, a recall of 1.00 and an F1-score of 0.99. The uncertainty of the AUC given by the 95%CI was 0.68-0.826. Conclusions: A machine learning xgboost model identified the most important predictors of ESRD, maintaining adequate predictive performance when cross-validated in an independent cohort of patients. The model could be applied in real clinical practice.

An application and discussion of wide-band signal processing technology in the primary calibration for hydrophones

Abstract Wide-band signals are potentially available in the measurement of transducers, which can obtain wide-band responses of electroacoustic parameters of them directly. The hydrophone of B&amp;K 8103 is calibrated in a Φ 1.2 m×1.8 m small water vessel by wide-band signal processing technology in the frequency range of 3.15 kHz to 100 kHz. A thin pellicle co-vibrates with acoustic particle in the free-field, and its oscillation can be detected by a laser Doppler vibrometer, which can estimate the acoustic pressure distribution. The transfer function model is established in a small water vessel, and the wide-band frequency responses of the transfer impedance of transducer and hydrophone as well as the transfer impedance of transducer and pellicle in the small water vessel are calculated respectively. The wide-band signal processing technology of frequency domain filter process are used, which can isolate the reflecting acoustic wave from the boundaries and the surface of the water vessel. To verify the accuracy of the wide-band calibration measurements, the calibration results are compared with that using tone-burst signals in the water vessel and using free-field reciprocity method in the large water tank. The comparisons show that their calibration results are in a good agreement with each other, and the maximum deviation is 0.7 dB. All these demonstrate that the wide-band signal processing technology described is accurate and stable.

Evaluation of Freezanz automated misting system against mosquitoes

Automated misting systems are a convenient way for homeowners or small businesses to control adult mosquitoes. One such system was presented to the Anastasia Mosquito Control District (AMCD) for evaluation to control caged Aedes aegypti. The system consisted of 3 spray tanks, 2 pumps, water level sensors, and flow meters, and was controlled through an Android tablet loaded with dedicated control software. The evaluation of the system included calibration tests, droplet characterization, spray dispersion in the open field, and effectiveness testing using bio-assay cages for mortality assessment. For these tests, a loop of 14 nozzles 4 m apart was connected and held at 1 m height utilizing a total of 120 m tube. All nozzles were arranged in a 16 × 12 m rectangle laid in the East-West direction. Water was sprayed for calibration and droplet size measurements at pressures of 13.0, 15.5, and 18 bar; water and 10 % red dye solution for spray dispersion at 18 bar pressure, and 0.17 % solution of equalizer 20–20 was sprayed at 18 bar pressure for mortality tests. All 3 replicated tests were conducted in the morning between 9:00 and 11:30am. During this time, temperature ranged from 21 to 26 °C, relative humidity from 54 to 95%, and wind speed from 0 – 2 km/hr.The combined flow rate from all 14 nozzles was significantly affected by pressure and was in agreement with the machine-calculated flow rate. There was a similar flow rate from all nozzles, indicated by a standard error of 0.82 mL/min. The droplet characteristics represented by DV0.1, DV0.5, and DV0.9 were not affected by nozzles but decreased with an increase in pressure as expected. The percentage of coverage on the cards, an indicator of spray dispersion, ranged from 20 -100%, and it was found to increase in the direction of the wind. Mosquito mortality showed a similar trend of increasing in the wind direction and ranged from 30 to 100 %. There was no effect of the location of cages on mosquito mortality. These results indicate that the effectiveness of this spray depends upon wind direction. The results, however, may be different when there is no wind, which may be the case during the times these applications are made.

Diagnosis of perimenopausal coronary heart disease patients using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography

To assess whether the radiomics signature of pericoronary adipose tissue (PCAT) from coronary computed tomography angiography (CCTA) can distinguish between perimenopausal women with coronary heart disease (CHD) and those without coronary artery disease (CAD). This single-center retrospective case–control study comprised 140 perimenopausal women with CHD presenting with chest pain who underwent CCTA within 48 h of admission. They were matched with 140 control patients presenting with chest pain but without CAD, based on age, risk factors, radiation dose and CT tube voltage. For all participants, PCAT around the proximal right coronary artery was segmented, from which radiomics features and the fat attenuation index (FAI) were extracted and analyzed. Subsequently, corresponding models were developed and internally validated using Bootstrap methods. Model performance was assessed through measures of identification, calibration, and clinical utility. Using logistic regression analysis, an integrated model that combines clinical features, fat attenuation index and radiomics parameters demonstrated enhanced discrimination ability for perimenopausal CHD (area under the curve [AUC]: 0.80, 95% confidence interval [CI]:0.740–0.845). This model outperformed both the combination of clinical features and PCAT attenuation (AUC 0.67, 95% CI 0.602–0.727) and the use of clinical features alone (AUC 0.66, 95% CI 0.603–0.732). Calibration curves for the three predictive models indicated satisfactory fit (all p > 0.05). Moreover, decision curve analysis demonstrated that the integrated model offered greater clinical benefit compared to the other two models. The CCTA-based radiomics signature derived from the PCAT model outperforms the FAI model in differentiating perimenopausal CHD patients from non-CAD individuals. Integrating PCAT radiomics with the FAI could enhance the diagnostic accuracy for perimenopausal CHD.