Single Instrument Research Articles

Optimizing policy mixes for promoting prefabricated construction in developing countries: an fsQCA approach

PurposePrefabricated construction (PC) is increasingly recognized for its sustainability and is being vigorously promoted worldwide. However, its adoption in developing countries remains suboptimal, with existing studies predominantly focusing on policy frameworks or the impact of a single policy instrument. This study addresses this research gap by optimizing the path of PC promotion from the perspective of policy mixes.Design/methodology/approachThe study employs fuzzy-set qualitative comparative analysis (fsQCA) in conjunction with necessary condition analysis, to explore effective policy configurations for PC promotion. A comprehensive collection of 171 PC-related policies issued by the Chinese government was analyzed using text mining to identify antecedent conditions of configuration. Data were further obtained through a questionnaire survey involving 263 valid responses, with fsQCA used to derive the optimal policy configurations.FindingsThe analysis identified six distinct combination paths for effective policy configurations. Land supply and governmental procurement were found to be core conditions, while fiscal and taxation financial measures emerged as marginal conditions prevalent across all paths. These findings suggest that land supply policies are particularly suitable for regions with limited land resources, such as Shanghai, while government procurement is more effective in regions like Xinjiang, where PC awareness is still developing.Practical implicationsIn practice, the conclusions enable policymakers to clearly understand policy instruments, thereby finding differentiated pathways for promoting PC with comparable effects. The proposed recommendations help advance PC development effectively while reducing financial burden and minimizing resource waste. This provides important guidance for PC development across different regions or stages, helps address regional imbalances in PC development, and ultimately contributes to the broader goal of sustainable urban development.Originality/valueThis study significantly enriches the research on PC policy combinations by utilizing more comprehensive and robust data, thereby enhancing the universal applicability of the findings. The results provide valuable references for policymakers in different regions, helping to address regional imbalances in PC development and facilitating the construction industry’s transition towards greater intelligence and sustainability.

Development of a revised version of the SCRAM questionnaire to evaluate sleep, circadian rhythms, and mood characteristics

ABSTRACT Sleep quality, chronotype, and mood may be closely interconnected processes. Typically, such constructs are measured independently, leaving out important information regarding their intrinsic relationships. The Sleep, Circadian Rhythms, and Mood (SCRAM) questionnaire is a promising tool for measuring sleep, chronotype, understood as diurnal preference, and depressive symptomatology, and the interrelationships between them. Anxiety has also been linked to sleep quality, chronotype, and depression, but there is currently no scale that measures these constructs together. This study aims to validate a revised version of the SCRAM questionnaire (rSCRAM), incorporating items to measure anxious mood. 486 Italian participants were involved in two studies. In Study 1, principal component analysis (PCA) identified representative anxiety elements from validated questionnaires. In Study 2, after adding the anxiety elements, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) established a 4-factor, 16-item model. The rSCRAM demonstrated excellent psychometric properties: high internal consistency (α = 0.72–0.90) and a strong test-retest reliability of the scales over 2 weeks (r = 0.73–0.82), a high correlation for convergent validity, and low correlations for divergent validity. The rSCRAM questionnaire measures the constructs for which it was created and revised. Including the anxiety scale enhances its utility in assessing mental health constructs within a single instrument.

Research on single-point fast three-dimensional concentration reconstruction of a smoke plume based on the static interference infrared imaging spectroscopy system

To meet the requirements of real-time and effectiveness of three-dimensional concentration telemetry of gas clouds and address the difficulty of fast three-dimensional concentration reconstruction of single instrument smoke plumes, the paper proposes a single-point fast three-dimensional concentration reconstruction of the smoke plume based on a static interference infrared Fourier transform imaging spectrometer (ISIFTS) by using the advantages of high throughput, large field of view, high stability, and rapid detection. Based on the scanning field switching characteristics of ISIFTS, a single instrument quickly scans the dual-field map data to obtain the three-dimensional point cloud of the target scene. Combined with the three-dimensional spatial parameters of the scene, a multi-dimensional re-projection algorithm is constructed based on the Gaussian plume continuous diffusion model to simulate the concentration-path-length product (CL) image, and the measured CL image is solved by analyzing the smoke plume image spectra data. The normalized cross-correlation fitting algorithm is used to perform the optimal matching of simulated-measured CL images, and then the three-dimensional concentration distribution of the plume scene is reconstructed based on the dimension mapping relationship. The field smoke plume telemetry experiment was designed and carried out, and the three-dimensional concentration distribution of plume gas at three emission points in the scene was obtained. The CO2 emission rates were calculated to be 13.572 kg / s, 12.225 kg / s, and 14.114 kg / s, respectively. The data are consistent with the emission rate of the coal-fired thermal power plant, which verifies the effectiveness of the single-point fast three-dimensional concentration reconstruction of the smoke plume method based on the ISIFTS system.

Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+)

ABSTRACT Background: Prolonged Grief Disorder (PGD) has been recognized as a mental health disorder and was added to the ICD-11 and DSM-5-TR. Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. The study aimed to evaluate the psychometric properties of the German version of the Traumatic Grief Inventory Self-Report Plus (TGI-SR+), a self-report measure to assess PGDICD-11 and PGDDSM-5-TR symptoms. Methods: Out of a representative sample of the German general population (N = 2509), 1062 reported a significant loss and completed questions about sociodemographic and loss-related variables, the TGI-SR+, and a measure of health-related quality of life. Results: Item analyses demonstrated good item characteristics. Confirmatory factor analyses showed a good fit for two-factor models for PGDICD-11 and PGDDSM-5-TR. Omega values demonstrated good internal consistency. In support of concurrent validity, symptoms of PGDICD-11 and PGDDSM-5-TR were associated with worse health-related quality of life. In support of known-groups validity, symptoms of PGDICD-11 and PGDDSM-5-TR were significantly higher among women, people with a lower educational level, more recently bereaved, those who lost a spouse or child (vs. other person), and those who lost someone due to unnatural causes (vs. natural causes). ROC analyses showed optimal cut-off scores of ≥60 and ≥65 to screen for probable caseness for PGDICD-11 and PGDDSM-5-TR, respectively. Limitations: The analyses were based on a cross-sectional design, and data on retest-reliability and predictive validity is missing. Conclusion: Results support the reliability and validity of the German TGI-SR+ as a screening instrument for PGD in research.

Mid‐Infrared Sensing Using a Hollow–Core Fiber in a Nonlinear Interferometer

AbstractIncreasing the interaction path length is a well‐known method for enhancing the sensitivity of the optical detection system. Hollow–core fibers (HCFs) represent a viable alternative to the traditional multi‐path cells offering low optical losses and strong confinement of the optical field. Here, the incorporation of an Antiresonant Hollow–core Fiber (AR‐HCF) section into a nonlinear interferometer, where the AR‐HCF section serves as a gas‐sensing cell operating in the IR range is presented. By exploiting the effect of nonlinear interference, the detection is brought into the more operation‐friendly visible range. The detection of methane (CH4) gas at mid‐IR wavelengths within a half‐meter section of AR‐HCF, with an estimated concentration accuracy of 200 ppm·m is demonstrated. These results represent the combination of two research fields within a single instrument and pave the way for further advancement of quantum‐inspired gas sensing techniques.

Research on Whether Quality Policies Can Promote the High-Quality Development of China’s Manufacturing Industry and Its Configuration Paths in the Context of Sustainable Development

High-quality development enhances economic quality and resource allocation efficiency through various effective and sustainable means, with particularly notable results in the manufacturing sector. Quality policies, through establishing standards, norms, and incentive measures, aim to foster technological innovation, efficient resource utilization, and quality improvement in manufacturing, thereby supporting its high-quality development. This study explores the impact of quality policies on high-quality development in manufacturing and their configurational pathways, providing theoretical foundations and practical guidance for optimizing policy combinations and promoting sustainable development. This analysis is based on quality policies released from 2013 to 2022 and sample data from 30 Chinese provinces. The findings reveal that quality policies significantly promote high-quality development in manufacturing, particularly through incentive, capacity building, and system changing instruments, while command instruments may exert certain pressures on high-quality development. Configuration analysis further indicates that a single instrument is insufficient to support high-quality development in manufacturing fully; the synergistic effect of multiple policy instruments is essential, and regions should optimize policy combinations according to their characteristics. This study provides valuable insights for sustainable development, offering a deeper understanding of the complex causal relationship between quality policies and high-quality development in manufacturing.

The Dark Energy Survey Supernova Program: Light Curves and 5 Yr Data Release

We present griz photometric light curves for the full 5 yr of the Dark Energy Survey Supernova (DES-SN) program, obtained with both forced point-spread function photometry on difference images (DiffImg) performed during survey operations, and scene modelling photometry (SMP) on search images processed after the survey. This release contains 31,636 DiffImg and 19,706 high-quality SMP light curves, the latter of which contain 1635 photometrically classified SNe that pass cosmology quality cuts. This sample spans the largest redshift (z) range ever covered by a single SN survey (0.1 < z < 1.13) and is the largest single sample from a single instrument of SNe ever used for cosmological constraints. We describe in detail the improvements made to obtain the final DES-SN photometry and provide a comparison to what was used in the 3 yr DES-SN spectroscopically confirmed Type Ia SN sample. We also include a comparative analysis of the performance of the SMP photometry with respect to the real-time DiffImg forced photometry and find that SMP photometry is more precise, more accurate, and less sensitive to the host-galaxy surface brightness anomaly. The public release of the light curves and ancillary data can be found at github.com/des-science/DES-SN5YR and doi:10.5281/zenodo.12720777.

Regulatory Effects of the Combinations of Aggregate and Structural Monetary Policy Instruments: an application of New Keynesian DSGE model to China

This paper selects Chinese macroeconomic data from the first quarter of 2009 to the first quarter of 2020 and employs a New Keynesian dynamic stochastic general equilibrium model that incorporates the financial accelerator mechanism, price stickiness, and invisible government guarantees. The regulatory effects of different combinations of monetary policy instruments are compared from five perspectives: the shock effect of monetary policy, the magnitude of economic volatility of non-monetary policy shocks, the Central Bank loss function, the gap in the distribution of household income, and the heterogeneous firm external financing premium. Our findings indicate that the regulatory effects of the aggregate price-based and structural quantity-based monetary policy instrument combination are optimal, a conclusion that is further supported by the robustness test. It is therefore recommended that the Central Bank consider the potential benefits of a combined approach to aggregate and structural monetary policy instruments, with a view to enhancing credit availability for the real economy. This paper represents a significant contribution to the field, as it is the first to explicitly propose four distinct monetary policy instrument combinations, thereby overcoming the limitations of previous studies that have focused on a single instrument or a narrow range of instruments. The paper also contributes to the theoretical understanding of monetary policy instruments.

Deriving the PedsUtil health state classification system to measure health utilities for pediatric populations based on the PedsQL: a confirmatory factor analysis.

An important methodological challenge in conducting pediatric economic evaluations is estimating the preference-based health-related quality of life (HRQoL) of children. Current methods are highly variable and there is no single instrument available to value HRQoL consistently across multiple pediatric age groups. The Pediatric Quality of Life Inventory (PedsQL) is a non-preference-based generic HRQoL instrument validated for children 2-18 years, but it cannot be directly used in economic evaluations. The aim of this study was to establish the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis, which is the first step of deriving a preference-based measure of HRQoL based on the PedsQL. Four competing dimension structures of the PedsUtil health state classification system were developed based on published literature and expert opinion. Using data from the Longitudinal Study of Australian Children (LSAC) (n = 45,207), the 4 dimension structures were evaluated using the robust weighted least squares estimation method. The analyses were stratified by 2-year age intervals (from 2 to 17 years) to reflect the study design of the LSAC, as well as special healthcare needs status of the child. Model fit was evaluated by examining standardized factor loadings and various fit indices including the comparative fit index (CFI), Tucker-Lewis Index (TLI), and the root mean square error of approximation (RMSEA). Modification indices and residual correlations were examined to re-specify the models to improve model fit when necessary. The findings supported a 7-dimension structure (i.e., Physical Functioning, Pain, Fatigue, Emotional Functioning, Social Functioning, School Functioning, and School Absence) of the PedsUtil health state classification system. The 7-dimension model exhibited adequate fit across subgroups with CFI values that ranged from 0.929 to 0.954, TLI values from 0.916 to 0.946, and RMSEA values from 0.058 to 0.102. This study established the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis. The 7-dimension structure was found to be applicable across diverse pediatric populations. Research is currently ongoing to select the most representative item within each dimension of the PedsUtil health state classification system and valuation surveys will be fielded to estimate the PedsUtil scoring system.

A-367 Development of a Multimodal Point-of-Care Diagnostic Platform to Perform Rapid, Accurate, and Cost-Effective Molecular, Immunochemistry, Clinical Chemistry, and Cytometry Tests

Abstract Background Access to point-of-care (POC) testing can make a significant impact on the quality of care. However, because POC diagnostic platforms available today are expensive and only perform one type of test, clinicians are unable to implement all the POC tests they wish to perform. Fluxergy is developing a multimodal POC diagnostic platform that consolidates diverse diagnostic modalities into a single, compact platform to minimize the cost of POC testing and standardize testing workflow for the most common clinical chemistry, hematology, immunochemistry and molecular tests. This study describes feasibility studies performed to benchmark these assay modalities on the Fluxergy Analyzer. Methods Fluxergy Analyzer: The Fluxergy Analyzer integrates conventional detection systems—colorimetric, fluorometric, and electrochemical—into a singular POC platform. This unique design expands -omics testing capabilities, including molecular, immunochemistry, clinical chemistry, and hematology within a single instrument. Benchmarking Feasibility Studies: Molecular benchmarking was performed using a multiplex respiratory panel on contrived samples in UTM/VTM. Immunochemistry benchmarking was performed using a procalcitonin assay on spiked sodium citrate plasma samples. Cytometry benchmarking was performed using a white blood cell count (WBC) assay and testing contrived samples whole blood samples. Results For molecular testing, the Fluxergy Analyzer was able to accurately detect flu A, flu B, SARS-CoV-2, and RSV with agreements with the Luminex ARIES® Flu A/B &amp; RSV Assay and Cepheid Xpert® SARS-CoV-2 test results. For immunochemistry testing, the Fluxergy Analyzer accurate quantified PCT levels at 0.3, 0.6, 1.25 and 2.5 ng/mL. For hematology testing, the Fluxergy Analyzer demonstrated a strong correlation across the reportable range against the standard of care HemoCue analyzer. For clinical chemistry testing, the Fluxergy Analyzer demonstrated a strong correlation against the Siemen’s epoc® Blood Analysis System. Conclusions The Fluxergy Analyzer is uniquely suited to offer a comprehensive menu of the most common POC tests on a single, cost-effective platform.

A-368 Feasibility of a Five-Minute Sample-to-Answer Basic Metabolic Panel for Point-of-Care Testing on the Fluxergy Analyzer

Abstract Background Adoption of point-of-care (POC) platforms has been limited by their high cost and limited menu (e.g., molecular only). Fluxergy has developed a cost-effective multimodal POC platform capable of performing the most common clinical chemistry, immunochemistry, hematology, molecular tests in CLIA-waived settings. This method comparison study describes the performance of the Fluxergy’s feasibility stage basic metabolic panel (BMP) with contrived samples compared to the Siemen’s epoc® Blood Analysis System. Methods Fluxergy Analyzer: The Fluxergy Analyzer is a rapid and cost-effective multimodality platform that can perform lab-quality PCR, clinical chemistry, immunochemistry, and cytometry in a single instrument and if required, in a single cartridge. Fluxergy BMP: Fluxergy BMP rapidly quantifies key electrolytes (K+, Na+, Ca2+, Cl-) and metabolites (glucose, creatinine, and BUN) from whole blood in under five minutes on the Fluxergy Analyzer, utilizing the Fluxergy test cards with screen-printed electrochemical sensor. Feasibility Study: A method comparison study was conducted to assess the performance of the feasibility stage Fluxergy BMP using contrived samples generated by spiking known concentrations of K+, Na+, Ca2+, Cl-, and glucose into buffer solutions. Samples were tested in triplicate with both the Fluxergy BMP and Siemen’s epoc® Blood Analysis System at three different concentrations across the reportable range of the epoc® Blood Analysis System. Results The feasibility stage Fluxergy BMP demonstrated strong correlation across the reportable range for K+, Na+, Ca2+, Cl-, and glucose versus the epoc® Blood Analysis System (Table 1). The error percentage for all samples tested except one glucose sample (9.5 mM) was less than 10%. The coefficient of variance for all samples tested except one Ca2+ sample (0.44 mM) was less than ten percent. Conclusions This feasibility data demonstrates the Fluxergy Analyzer is well-suited to perform rapid and accurate metabolic testing from whole blood samples at the POC.

A-103 Analytical Performance Evaluation of Plasma NfL in a Clinical Diagnostic Laboratory

Abstract Background Neurofilament light chain (NfL) is a neuron-specific intermediate filament that is released at a consistent low level in normal individuals and increases with age and axonal injuries. NfL is a neurodegeneration biomarker in Alzheimer’s disease (AD), multiple sclerosis, stroke, traumatic brain injury and other neurodegenerative diseases (NDD). Here, we report the analytical performance of plasma NfL using high-sensitivity methodology in a clinical diagnostic laboratory. Methods The analytical performance, encompassing precision, detection limits, interference, and linearity, was evaluated. Plasma NfL levels were measured between July and October 2023 at Neurocode USA in Bellingham, WA, using a single Lumipulse G1200 instrument following CLSI guidelines, particularly for the utilization of the Fujirebio NfL Blood RUO assay as a laboratory-developed test for clinical analysis. A total of 100 healthy control samples, near the age of AD onset, were used to validate the reference ranges. Results The average plasma NfL concentrations varied from ≤ 8.4 to ≤ 37.9 ng/L among healthy individuals aged 20 to 80 years. The Plasma NfL assay exhibits analytical measurements, including a limit of blank (LoB) of 0.75 ng/L, a limit of detection (LoD) of 1.99 ng/ml, and a limit of quantification (LoQ) of 3.96 ng/L. Its linearity ranges from 11.08 to 741.58 ng/L, with intra-laboratory precision ≤ 9% CV. Stability is maintained at 4⁰C for ≤ 72 hours, at room temperature for ≤ 4 hours, at -20⁰C for ≤ 4 weeks, and at -80⁰C for ≤ 7 days, with freeze/thaw cycles tolerated within the specified time frame. Additionally, no interference was observed at the maximum concentrations tested for bilirubin, hemoglobin, and intralipid. Conclusions With a reference range between ≤ 8.4 to ≤ 37.9 ng/L and exceptional analytical performance, the measurement of plasma NfL on a state-of-the-art instrument using CLSI guidelines, can be useful in the diagnosis and monitoring of AD and other NDD.

Observing System Simulation Experiments Exploring Potential Spaceborne Deployment Options for a Differential Absorption Radar Measuring Marine Surface Pressures

AbstractA new technology for remote measurements of marine surface pressure has been proposed, employing a V‐band differential absorption radar and a radiometric temperature sounder to calculate the total column atmospheric mass. Observing System Simulation Experiments (OSSEs) are performed to evaluate the potential impact of Spaceborne Marine Surface Pressure (SMSP) on Numerical Weather Prediction. These experiments build on prior efforts (Privé, McLinden, et al., 2023, https://doi.org/10.16993/tellusa.3254), but with an updated version of the OSSE framework and with more sophisticated simulation of the SMSP observations and a longer experiment period. Several different instrument configurations are compared, including both scanning and non‐scanning orbits. SMSP impacts are calculated for analysis quality and forecast skill, and a forecast sensitivity observation impact tool is employed to place SMSP observations in context with the global observing network. The effects of rain contamination on observation quality are explored. Different magnitudes of simulated SMSP observation error are tested in the context of data assimilation to show the range of potential behaviors. Overall, SMSP observations are found to be most beneficial in the southern hemisphere extratropics, with statistically significant forecast improvements for the first 72 hr of the forecast. A constellation of four non‐scanning SMSP satellites is found to outperform a single scanning instrument with a 250 km wide swath.

Assessment of anxiety symptoms in children and adolescents: Italian validation of the short version of the spence children's anxiety scale for parents.

The assessment of anxiety symptoms in children and adolescents requires a valid and reliable single instrument able to detect various anxiety symptoms early and systematically collect data from other informant such as parents. The present study aimed to test the one-factor structure of the SCAS-P-8 and to examine its psychometric properties and invariance across sex and age in an Italian sample of 769 parents of children and adolescents aged 3-18years (50.8% females). Confirmatory factor analysis confirmed the one-factor structure of the SCAS-P-8, which showed good reliability and invariance by sex and age. When examining mean differences by sex and age, results showed that female schoolchildren had higher anxiety scores than males and other age groups. A strong correlation with emotional problems demonstrated convergent validity, while discriminant validity resulted from the weak correlations with externalizing symptoms and relationship problems with peers. Overall, findings support the SCAS-P-8 as a valid brief instrument to assess anxiety symptoms in children and adolescents for clinical and research purposes and demonstrate its invariance across sex and age.

Hats Off to Modeling! Profiling Early Synthetic Dyes on Historic Woolen Samples with ATR-FTIR Spectroscopy and Multivariate Curve Resolution-Alternating Least Square Algorithm.

This research focuses on analyzing wool samples dyed with synthetic dyes from the early 20th century. A methodology to identify and distinguish wool fibers dyed with azo, triphenylmethane, and xanthene dyes, which are no longer in use, using the ATR-FTIR spectra, is presented. Firstly, the dataset was subjected to PCA, which revealed the similarities and differences among the samples, illustrating a distribution pattern based on dye classes. MCR-ALS was employed to extract the spectral profiles of the dyed fibers, thereby enhancing the efficacy of the analytical techniques and extracting the comprehensive information from a single instrument. The combination of ATR-FTIR spectroscopy with chemometric methods, such as PCA and MCR-ALS, has proven to be an effective strategy for identifying and differentiating wool fibers dyed with early azo, triphenylmethane, and xanthene dyes. This approach has demonstrated particular effectiveness in enabling rapid analysis without requiring sampling or pretreatment. Moreover, the analysis is supported by thorough bibliographic research on these no longer used colorants. In order to maximize the potential of non-destructive spectroscopic techniques, such as ATR-FTIR, the approach used has proven to be crucial. This study underscores how chemometric techniques expand the capabilities of spectroscopy, extracting extensive information from a single instrument and aligning with the goals of cultural heritage analysis.

Novelties in the regulatory practice of reporting on sustainable development in the Russian Federation

Subject. The article analyzes the latest changes and trends in the regulation of sustainable development reporting in the Russian Federation. Objectives. The study is aimed to review the Russian regulatory framework for organizing and reporting on sustainable development in the context of expanding the agenda of the Sustainable Development Goals, consider the key aspects of sustainable development reporting in the Russian jurisdiction, including new requirements, methods of measuring effectiveness reflected in guidance documents of Russian regulators. Methods. The study employs general scientific research methods, like detailing, generalization, analysis, synthesis, and description. Results. The regulation of the process of reports on sustainable development preparation is being transformed in response to the changing market conditions and emergence of global reporting standards. The current state of regulatory practice is characterized by the lack of legislative consolidation of the obligation to prepare reports, which complicates the process of data comparability of these organizations demonstrating a responsible approach to business. I analyzed the approaches of the Bank of Russia and the Ministry of Economic Development of the Russian Federation to take into account ESG factors in the formation of the reports. Conclusions. The fragmented regulation of the preparation process of reports on sustainable development is caused by the absence of a single legal instrument of mandatory application, the existence of internal initiatives of regulatory authorities aimed at improving the reporting practices of economic actors who chose a sustainable development vector.

A practical HPLC-MS method for the analysis of nitrosamine drug substance related impurities using an inexpensive single quadrupole mass spectrometer

Nitrosamine drug substance related impurities (NDSRIs) are often analyzed using high performance liquid chromatography (HPLC) with mass spectrometry (MS) detection. Due to high sensitivity requirements, high resolution MS or MS/MS is commonly used. However, it is difficult to implement this type of method for routine analysis at a supply site. Herein, we report a systematic approach to develop and validate a practical, robust, and user-friendly method for the analysis of NDSRIs using an inexpensive single quadrupole MS instrument such as QDa. We used 7-nitroso-3-(trifluoromethyl)-5,6,7,8-tetrahydro- [1,2,4] triazolo [4,3-a] pyrazine (NTTP) as an example to demonstrate the method development process. By optimizing the HPLC and MS parameters, we were able to develop a simple HPLC-MS method that provides the desired specificity and sensitivity for the analysis of NTTP and can be easily implemented in an analytical lab. The limit of quantitation is 0.5 ng/mL, corresponding to 0.1 ppm with respect to 5 mg/mL sitagliptin. The method has been successfully validated per ICH guidelines.

Beyond transfer learning: Leveraging ancillary images in automated classification of plankton

AbstractWe assess whether a supervised machine learning algorithm, specifically a convolutional neural network (CNN), achieves higher accuracy on planktonic image classification when including non‐plankton and ancillary plankton during the training procedure. We focus on the case of optimizing the CNN for a single planktonic image source, while considering ancillary images to be plankton images from other instruments. We conducted two sets of experiments with three different types of plankton images (from a Zooglider, Underwater Vision Profiler 5, and Zooscan), and our results held across all three image types. First, we considered whether single‐stage transfer learning using non‐plankton images was beneficial. For this assessment, we used ImageNet images and the 2015 ImageNet contest‐winning model, ResNet‐152. We found increased accuracy using a ResNet‐152 model pretrained on ImageNet, provided the entire network was retrained rather than retraining only the fully connected layers. Next, we combined all three plankton image types into a single dataset with 3.3 million images (despite their differences in contrast, resolution, and pixel pitch) and conducted a multistage transfer learning assessment. We executed a transfer learning stage from ImageNet to the merged ancillary plankton dataset, then a second transfer learning stage from that merged plankton model to a single instrument dataset. We found that multistage transfer learning resulted in additional accuracy gains. These results should have generality for other image classification tasks.

A new neuropsychological tool for simultaneous reading and executive functions assessment: initial psychometric properties.

The development of reading and complex executive functions is fundamental for achieving social, academic, and professional success. So far, there is no single neuropsychological instrument that comprehensively assesses the domains of inhibitory control, cognitive flexibility, working memory, and reading comprehension. To assess executive functions related to reading, the "Assessment of Reading and Executive Functions" (AREF) was developed. In this study, we show initial evidence of validity and reliability for four subtests - Graphophonological-Semantic Flexibility, Inhibitory Control, Flexibility, and Working Memory. A total of 93 students from 4th to 9th grade, aged 8-14, in public (n = 61) and private (n = 32) schools were evaluated. Tasks from the AREF instrument, as well as measures of reading comprehension, inhibitory control, cognitive flexibility, working memory, and intelligence, were administered. Correlations between AREF scores and the other measures were performed to assess external construct validity. Performance differences between school groups on AREF subtests were analyzed using ANOVA, t-test, and Mann-Whitney tests, and the internal consistency of the instrument's tasks was evaluated using Cronbach's alpha coefficient. The scores of the AREF subtests demonstrated significant positive correlations with reading measures (ranging from 0.339 to 0.367) and executive functions (ranging from 0.209 to 0.396). Significant differences were found in the performance of some AREF tasks when comparing individuals from public and private schools, as well as between 4th and 5th graders compared to students in higher grades. The internal consistency of the tasks was low for Graphophonological-Semantic Flexibility (Cronbach's α = 0.566), moderate for Inhibitory Control and Flexibility (Cronbach's α = 0.768), and high for Working Memory (Cronbach's α = 0.881). The results provide initial evidence of construct validity and reliability for the AREF subtests. It is expected that this new neuropsychological test will contribute to the assessment of reading skills and executive functions, assisting in guiding clinical and educational interventions for individuals with and without neurodevelopmental disorders.

Item response theory validation of the Oxford knee score and Activity and Participation Questionnaire: a step toward a common metric

ObjectivesThe Oxford knee score (OKS) and OKS Activity and Participation Questionnaire (OKS-APQ) are patient-reported outcome measures used to assess people undergoing knee replacement surgery. They have not explicitly been tested for unidimensionality (whether they measure one underlying trait such as ‘knee health’). This study applied item response theory (IRT) to improve the validity of the instruments to optimize for ongoing use. Study Design and SettingParticipants undergoing primary total knee replacement (TKR) provided preoperative and postoperative responses for OKS and OKS-APQ. Confirmatory factor analysis (CFA) were performed on the OKS and OKS-APQ separately and then on both when pooled into one. An IRT model was fitted to the data. Results2972 individual response patterns were analyzed. CFA demonstrated that when combining OKS and OKS-APQ as one instrument, they measure one latent health trait. A user-friendly, free-to-use, web app has been developed to allow clinicians to upload raw data and instantly receive IRT scores. ConclusionsThe OKS and OKS-APQ can be combined to use effectively as a single instrument (producing a single score). For the separate OKS and OKS-APQ the original items and response options can continue to be posed to patients, and this study has confirmed the suitability of IRT-weighted scoring. Applying IRT to existing responses converts traditional sum scores into continuous measurements with greater granularity, including individual measurement error.