Explore the vast range of titles available.

Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) products are essential data sources for global and regional climate change research. Currently, several versions of the MODIS LST product have been released, yet the performance differences and uncertainties they introduce in land surface studies remain insufficiently addressed. To bridge this gap, this study focuses on four distinct versions of the LST product: MxD11A1 Collection 5 (C5), Collection 6 (C6), Collection 6.1 (C6.1), and MxD21A1 Collection 6.1 (MxD21). The spatial resolution of all product generations is 1 km, and the temporal resolution is 0.5 days. This study provides a comprehensive analysis of the errors arising from different generations of these products in various land surface process studies. The error assessment includes cross-comparisons between product versions and evaluations of the absolute errors generated. Absolute errors in evaluation data were collected from 13 surface sites within the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project during the period 2013–2018. Cross-validation results show that the largest difference between C5 and C6.1 occurs over bare land, with an RMSE of approximately 1.45 K, while there is no significant change between C6 and C6.1. MOD21 shows considerable variation compared to C6.1 at night across different land cover types, with RMSE over cropland exceeding 2 K. The temperature difference between MOD21 and C6.1 is more pronounced at night (2.01 K) than during the day (0.30 K). Validation results based on temperature indicate that C5 has greater uncertainty compared to C6, especially over bare land, where errors are 2.06 K and 1.06 K, respectively. Furthermore, MxD21 demonstrates significant day–night performance discrepancies, with an average bias of 0.10 K at night, while daytime errors over bare land can reach 2 K, potentially influenced by atmospheric conditions. Based on the research in this paper, it is possible to clarify the performance of different versions of MODIS products, reflecting the appropriateness of their past applications; on the other hand, it is recommended to prioritize the use of the MxD11A1 C6 and C6.1 products for monitoring and applications in bare soil areas to ensure higher accuracy. Furthermore, for day and night monitoring, it may be beneficial to alternate between the MxD11A1 and MxD21A1 products to fully leverage their respective advantages and enhance overall monitoring effectiveness.

Osteoporosis is a life threatening disease which commonly affects women mostly after their menopause. It primarily causes mild bone fractures, which on advanced stage leads to the death of an individual. The diagnosis of osteoporosis is done based on bone mineral density (BMD) values obtained through various clinical methods experimented from various skeletal regions. The main objective of the authors’ work is to develop a hybrid classifier model that discriminates the osteoporotic patient from healthy person, based on BMD values. In this Letter, the authors propose the monarch butterfly optimisation-based artificial neural network classifier which helps in earlier diagnosis and prevention of osteoporosis. The experiments were conducted using 10-fold cross-validation method for two datasets lumbar spine and femoral neck. The results were compared with other similar hybrid approaches. The proposed method resulted with the accuracy, specificity and sensitivity of 97.9% ± 0.14, 98.33% ± 0.03 and 95.24% ± 0.08, respectively, for lumbar spine dataset and 99.3% ± 0.16%, 99.2% ± 0.13 and 100, respectively, for femoral neck dataset. Further, its performance is compared using receiver operating characteristics analysis and Wilcoxon signed-rank test. The results proved that the proposed classifier is efficient and it outperformed the other approaches in all the cases.

A simple high performance thin layer chromatography (HPTLC) has been developed and validated for determination of sunitinib malate and possible impurities. The samples were applied in forms of bands on an aluminum TLC plate pre-coated with silica gel and were separated using dichloromethane: methanol: toluene: ammonia solution as the mobile phase. Sunitinib malate was thoroughly separated from impurities including E-isomer, sunitinib N-oxide and impurity B with a retention factor (RF) of 0.35±0.02. Quantitative analysis of sunitinib was carried out using a mobile phase consisting of dichloromethane:methanol:ammonia solution, RF value was 0.53±0.02 for Z isomer. Detection was performed densitometrically in absorbance mode at 430 nm. This method was found to produce sharp, symmetrical, and well resolved peaks. Linear relationship with the coefficients of determination > 0.99 was achieved over the concentration range of 27.34 to 437.5 ng/spot. This method provides robust, replicable and accurate results with acceptable sensitivity.

Forced degradation studies of gliquidone were conducted under different stress conditions. Three degradates were observed upon using HPLC and TLC and elucidated by LC-MS and IR. HPLC method was performed on C18 column using methanol-water (85:15 v/v) pH 3.5 as a mobile phase with isocratic mode at 1 mL.min-1 and detection at 225 nm. HPLC analysis was applied in range of 0.5-20 µg.mL-1 (r =1) with limit of detection (LOD) 0.177 µg.mL-1. TLC method was based on the separation of gliquidone from degradation products on silica gel TLC F254 plates using chloroform-cyclohexane-glacial acetic acid (6:3:1v/v) as a developing system with relative retardation 1.15±0.01. Densitometric measurements were achieved in range of 2 -20 µg /band at 254 nm (r = 0.9999) with LOD of 0.26 µg /band. Least squares regression analysis was applied to provide mathematical estimates of the degree of linearity. The analysis revealed a linear calibration for HPLC where a binomial relationship for TLC. Stability testing and methods validation have been evaluated according to International Conference on Harmonization guidelines. Moreover, the proposed methods were applied for the analysis of tablets and the results obtained were statistically compared with those of pharmacopeial method revealing no significant difference about accuracy and precision.

 This study was aimed to development and modification the method of analysis for active ingredient in Tamsulosin drug by using high performance liquid chromatography (HPLC) also determined shelf life and storage conditions for Tamsulosin. Chromatographic conditions utilized stationary phase C18 (250*4.6) mobile phase 0.05Nmixture of  di hydrogen ortho phosphate and Acetonitrile 55:45 , preserve the flow rate near (1ml/min) and length of wave has been 275nm, The retention time found to be 10 minute for the HPLC process . The Tamsulosin assay result was found to be 99.93% . The calibration curve linearity analysis results showed a strong linear relationship in the concentration range (10-200ppm) and the correlation coefficient, slope and intercept value were 0.9933,11796,190017, respectively The percentage recovery was found 99%. LOD value was found to 0.00053 µg/ml  and LOQ value was found to 0.0016 µg/ml , Precision was found to be 99.49% Robustness was found to 99.69%. Our proposed procedure confirmed a group of merits such as  Linear ,accurate ,precise ,and robust , could be recommended for determination of Tamsulosin.

In recent decades, mass spectrometry techniques, particularly when combined with separation methods such as high-performance liquid chromatography, have become increasingly important in pharmaceutical, bio-analytical, environmental, and food science applications because they afford high selectivity and sensitivity. However, mass spectrometry has limitations due to the matrix effects (ME), which can be particularly marked in complex mixes, when the analyte co-elutes together with other molecules, altering analysis results quantitatively. This may be detrimental during method validation, negatively affecting reproducibility, linearity, selectivity, accuracy, and sensitivity. Starting from literature and own experience, this review intends to provide a simple guideline for selecting the best operative conditions to overcome matrix effects in LC-MS techniques, to obtain the best result in the shortest time. The proposed methodology can be of benefit in different sectors, such as pharmaceutical, bio-analytical, environmental, and food sciences. Depending on the required sensitivity, analysts may minimize or compensate for ME. When sensitivity is crucial, analysis must try to minimize ME by adjusting MS parameters, chromatographic conditions, or optimizing clean-up. On the contrary, to compensate for ME analysts should have recourse to calibration approaches depending on the availability of blank matrix. When blank matrices are available, calibration can occur through isotope labeled internal standards and matrix matched calibration standards; conversely, when blank matrices are not available, calibration can be performed through isotope labeled internal standards, background subtraction, or surrogate matrices. In any case, an adjusting of MS parameters, chromatographic conditions, or a clean-up are necessary.

•This is a guideline proposing a protocol for the validation of forensic evaluation methods.•The validation focuses on likelihood ratio methods for the inference at source level.•The guideline is general and can be applied to any forensic evaluation method producing LR values. This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes’ inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of the evidence for a trace specimen, e.g. a fingermark, and a reference specimen, e.g. a fingerprint, to originate from common or different sources. Some theoretical aspects of probabilities necessary for this Guideline were discussed prior to its elaboration, which started after a workshop of forensic researchers and practitioners involved in this topic. In the workshop, the following questions were addressed: “which aspects of a forensic evaluation scenario need to be validated?”, “what is the role of the LR as part of a decision process?” and “how to deal with uncertainty in the LR calculation?”. The questions: “what to validate?” focuses on the validation methods and criteria and “how to validate?” deals with the implementation of the validation protocol. Answers to these questions were deemed necessary with several objectives. First, concepts typical for validation standards [1], such as performance characteristics, performance metrics and validation criteria, will be adapted or applied by analogy to the LR framework. Second, a validation strategy will be defined. Third, validation methods will be described. Finally, a validation protocol and an example of validation report will be proposed, which can be applied to the forensic fields developing and validating LR methods for the evaluation of the strength of evidence at source level under the following propositions:H1/Hss: The trace and reference originate from the same source.H2/Hds: The trace and reference originate from different sources.

Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided. This article is part of the themed issue ‘Quantitative mass spectrometry’.

Wine, as a high-value product, is vulnerable to counterfeiting. To tackle increasingly sophisticated fraud, innovative analytical approaches are required. However, they must undergo rigorous validation. Proton nuclear magnetic resonance spectroscopy ([sup.1]H-NMR) is intrinsically quantitative, reproducible, and fast, making it a promising tool for official control. This study presents the development and validation of a standardised and fully automated workflow for the quantification of 20 oenologically relevant compounds, including organic acids, sugars, alcohols, esters, phenolics, and an alkaloid. The method combines optimised sample preparation, external quantification standards, spectrometer calibration, and a dedicated R package (RnmrQuant1D) for fully automated spectral processing, enabling high-throughput and operator-independent analysis. Validation was performed under intermediate precision according to OIV metrological standards, evaluating accuracy, precision, robustness, limits of quantification, and measurement uncertainty. The results demonstrated excellent linearity, trueness, and reproducibility, matching the targeted analytical performance. Measurement uncertainties were estimated both by conventional linear modelling and by a dynamic approach better suited to detection limits. The workflow is easy to implement, requires minimal sample consumption, and substantially reduces operator bias. Beyond validating a robust method, this study provides a framework for harmonised, transferable [sup.1]H-NMR workflows that could support large-scale databases, integration with chemometric models, and ultimately, [sup.1]H-NMR’s recognition as a relevant method for wine authentication and quality control. This work fills a crucial gap in wine analysis by uniting practical application and rigorous methods, enabling broader adoption in control laboratories worldwide.

Background The theoretical framework of acceptability (TFA) was developed in response to recommendations that acceptability should be assessed in the design, evaluation and implementation phases of healthcare interventions. The TFA consists of seven component constructs (affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy) that can help to identify characteristics of interventions that may be improved. The aim of this study was to develop a generic TFA questionnaire that can be adapted to assess acceptability of any healthcare intervention. Methods Two intervention-specific acceptability questionnaires based on the TFA were developed using a 5-step pre-validation method for developing patient-reported outcome instruments: 1) item generation; 2) item de-duplication; 3) item reduction and creation; 4) assessment of discriminant content validity against a pre-specified framework (TFA); 5) feedback from key stakeholders. Next, a generic TFA-based questionnaire was developed and applied to assess prospective and retrospective acceptability of the COVID-19 vaccine. A think-aloud method was employed with two samples: 10 participants who self-reported intention to have the COVID-19 vaccine, and 10 participants who self-reported receiving a first dose of the vaccine. Results 1) The item pool contained 138 items, identified from primary papers included in an overview of reviews. 2) There were no duplicate items. 3) 107 items were discarded; 35 new items were created to maximise coverage of the seven TFA constructs. 4) 33 items met criteria for discriminant content validity and were reduced to two intervention-specific acceptability questionnaires, each with eight items. 5) Feedback from key stakeholders resulted in refinement of item wording, which was then adapted to develop a generic TFA-based questionnaire. For prospective and retrospective versions of the questionnaire, no participants identified problems with understanding and answering items reflecting four TFA constructs: affective attitude, burden, perceived effectiveness, opportunity costs. Some participants encountered problems with items reflecting three constructs: ethicality, intervention coherence, self-efficacy. Conclusions A generic questionnaire for assessing intervention acceptability from the perspectives of intervention recipients was developed using methods for creating participant-reported outcome measures, informed by theory, previous research, and stakeholder input. The questionnaire provides researchers with an adaptable tool to measure acceptability across a range of healthcare interventions.