Methodology For Quantification Research Articles

Quality by Design Approach Driven Development and Validation of Reverse Phase‐High‐Performance Liquid Chromatography Methodology for Dual Quantification of Aspirin and Rivaroxaban

ABSTRACTClinical trials have shown that combining a modest dose of Rivaroxaban (RIV) with Aspirin (ASP) is more effective than ASP alone in reducing cardiovascular mortality, myocardial infarction, and stroke. A high‐performance liquid chromatography method developed using Quality by Design (QbD) effectively estimates ASP and RIV for routine pharmaceutical analysis. The Plackett‐Burman design assessed key factors including organic phase volume, mobile phase pH, flow rate, temperature, and injection volume using an Ishikawa fish‐bone diagram for risk assessment. These parameters were then optimized via Box‐Behnken design in 15 trials. The method meets the International Council For Harmonization standards with a mobile phase ratio of 45:55 (v/v) acetonitrile: buffer (pH 3, adjusted with orthophosphoric acid), a flow rate of 1 mL/min, a column temperature of 30°C, and an injection volume of 20 µL. A Phenomenex Luna C18 column (250 × 4.6 mm, 5 µm particle size) with detection at 251 nm ultra‐violet wavelength. The retention times of 4.54 min for ASP and 5.81 min for RIV were obtained. Validation confirmed linear ranges: 40–200 µg/mL for ASP and 2–10 µg/mL for RIV, with excellent recovery rates (ASP: 99.30%–101.9%; RIV: 98.52%–101.84%). Developed using QbD principles, the method proved specific, accurate, precise, sensitive, and robust for routine quality control of both compounds in pharmaceutical formulations.

Optimizing on-site testing for post-tensioned concrete bridges

The decreasing structural reliability of key infrastructure due to aging and degradation represents a significant challenge for engineers, infrastructure managers, and society in general. The concealed nature of tendons in post-tensioned concrete bridges makes the assessment of their structural health a crucial point of several national bridge inspection guidelines. This assessment is commonly performed by means of direct and/or indirect tendon testing. A widely spread approach to the design and quantification of the number of tests is the American FHWA method, also adopted by the Italian guidelines. Unfortunately, in light of its frequentist nature and the consequent negligence of the prior knowledge on the health state of the structure, this one can lead to test campaigns with redundant and non-optimized allocation of resources and time. The present article proposes a novel Bayesian perspective of the FHWA test quantification methodology that accounts for: (i) the prior knowledge in an explicit manner by means of Bayes’ theorem; (ii) the test uncertainties, as in the case of Nondestructive Testing. By means of a demonstrative application, this article displays how this novel methodology leads to an optimized number of tests whilst guaranteeing the required structural reliability and user safety levels.

Paucity of gastrointestinal plasma cells in common variable immunodeficiency.

Common variable immunodeficiency enteropathy (CVID-E) is a noninfectious complication of CVID caused by chronic inflammation of the gastrointestinal (GI) tract. Based on literature, a paucity or lack of plasma cells, although not obligatory for diagnosis, is a pathognomonic feature of CVID and more frequent in CVID-E. However, there is no consensus on standardized histopathological analysis of this feature in biopsies. In this systematic review, we highlight methods of reproducible plasma cell quantification of biopsies in CVID and describe the plasma cell counts and classes as presented in the literature. Reduced plasma cell counts are commonly found over the entire GI tract, except for in the oesophagus. Immunoglobulin A+ (IgA+) plasma cells appear to be the most commonly reduced plasma cell class in CVID, yet there is scarce literature on the predictive value of low IgA+ plasma cell counts in CVID-E. We propose two optimized methodologies of quantification using a cut-of value of <10 plasma cells per HPF at 40× magnification, or a proportion of ≥1-5% of total mononuclear cells, recorded over ≥3 sections, and in ≥2 biopsies, as the most conservative agreeable definitions for a paucity of plasma cells to be used in diagnostics and further research.

Quantitative 13C-IS pyrolysis-GC-MS lignin analysis: Overcoming matrix effects in animal feed and faeces

Recently, a pyrolysis-GC-MS methodology for specific lignin quantification and structural characterisation was developed, relying on the use of uniformly 13C-labeled polymeric lignin isolate as internal standard (IS). The 13C-IS py-GC-MS method has been validated for grasses, woods, and applied in various showcases. To study the fate of lignin in animals, this method still requires careful validation in animal feeds and, especially complex faecal samples, hence the aim of this work. Hereto, faecal material was collected from pigs fed with wheat straw as lignin source and subjected to the py-GC-MS analytical platform for thorough examination of IS pyrolysis behaviour in terms of response and structural features. Next, 13C-ISpy-lignin contents and corrected Klason lignin contents were compared. Most importantly, we revealed that pyrolysis behaviour of 13C-IS lignin and 12C-sample lignin was differently affected in the faecal matrix, resulting in the ultimate underestimation of 13C-ISpy-lignin contents. In-depth examination and evaluation of matrix constituents showed that predominantly matrix ash was responsible for the effects observed. We further demonstrated that said matrix effects can be overcome by water extraction of the samples prior to analysis. Our validation and approach extend the use of the specific 13C-IS py-GC-MS methodology for accurate quantitative lignin analysis to biomass samples with complex matrices like pig faeces, and now call for application in future digestibility studies.

Beyond hinges and spires: A critical examination of archaeomalacological quantification methodologies using coral reef molluscan assemblages from Jiigurru (Lizard Island Group), northern Great Barrier Reef

Quantification, as one of the pillars of the zooarchaeological subdiscipline, is an invaluable component of the toolkit researchers use to study past people-animal interactions. Despite being the subject of rigorous (zoo)archaeological debate, the calculation of Minimum Number of Individuals (MNI) values remains one of the main methods of quantifying the relative abundance of taxa within faunal assemblages. Choosing the appropriate quantification protocol to calculate the MNI of archaeological invertebrate assemblages can be challenging due to regional taxonomic considerations and the myriad of quantification methodologies and frameworks available in the global archaeomalacological literature. In an Australian context, methodologies for quantifying coral reef molluscan assemblages have not been explicitly evaluated. Using archaeological molluscan assemblages from two midden sites (Freshwater Bay Midden and Mangrove Beach Headland Midden) on the northern Great Barrier Reef island group of Jiigurru (the Lizard Island Group), we critically examine two commonly adopted archaeomalacological quantification methodologies: the NRE MNI and tMNI protocols. The NRE MNI methodology uses one to two non-repetitive elements (NREs) of molluscs, whilst the tMNI protocol includes a wider range of elements akin to vertebrate MNI quantification methodologies. Through a comparison of taxa abundances and statistical analyses, results show that the tMNI protocol, with some modification, is best suited for the Jiigurru assemblages. Higher MNI values and an increased assemblage diversity, evenness, and richness were recorded for the molluscan assemblages at both midden sites when the tMNI protocol was applied. This study foregrounds the importance of data transparency when reporting quantification protocols and outcomes to ensure the highest degree of data quality, replicability, and usability.

Optimized HPLC-UV Methodology for the Simultaneous Quantification of Multiple Preservatives in Jordanian Yogurt Products

A method based on high-performance liquid chromatography with a UV detector (HPLC-UV) was developed for the simultaneous determination of sorbic acid, benzoic acid, and natamycin in yogurt. The method does not require time-consuming, labor-intensive pre-treatment processes or complicated procedures. Using a C18 150 mm × 4.6 mm, 3.0 µm column (Roc) at 25 °C, the target analytes were separated within 5 minutes with high sensitivity and selectivity. The mobile phase consisted of trifluoroacetic acid (0.1%) in water containing 100 mM sodium acetate, trifluoroacetic acid (0.1%) in acetonitrile, and trifluoroacetic acid (0.1%) in tetrahydrofuran, in a ratio of 70:20:10 (v/v). Using this mobile phase as an extraction mixture, recoveries ranged from 83.0% to 110.2% at spike levels between 2.5 µg/kg and 80.0 µg/kg. The relative standard deviations (RSDs) for these recoveries were below 10%. Intra-day precision and inter-day precision varied from 5.3% to 6.7% and 7.6% to 9.2%, respectively. Additionally, the limits of detection (LOD) were between 0.24 and 0.61 mg/L, and the limits of quantification (LOQ) ranged from 0.80 to 2.0 mg/L for sorbic acid, benzoic acid, and natamycin. Principal component analysis revealed that yogurt type had the greatest positive influence on preservative concentration, while the weight or volume of the yogurt package had the greatest negative influence.

Extracellular RNAs from Whole Urine to Distinguish Prostate Cancer from Benign Prostatic Hyperplasia.

RNAs, especially non-coding RNAs (ncRNAs), are crucial players in regulating cellular mechanisms due to their ability to interact with and regulate other molecules. Altered expression patterns of ncRNAs have been observed in prostate cancer (PCa), contributing to the disease's initiation, progression, and treatment response. This study aimed to evaluate the ability of a specific set of RNAs, including long ncRNAs (lncRNAs), microRNAs (miRNAs), and mRNAs, to discriminate between PCa and the non-neoplastic condition benign prostatic hyperplasia (BPH). After selecting by literature mining the most relevant RNAs differentially expressed in biofluids from PCa patients, we evaluated their discriminatory power in samples of unfiltered urine from 50 PCa and 50 BPH patients using both real-time PCR and droplet digital PCR (ddPCR). Additionally, we also optimized a protocol for urine sample manipulation and RNA extraction. This two-way validation study allowed us to establish that miRNAs (i.e., miR-27b-3p, miR-574-3p, miR-30a-5p, and miR-125b-5p) are more efficient biomarkers for PCa compared to long RNAs (mRNAs and lncRNAs) (e.g., PCA3, PCAT18, and KLK3), as their dysregulation was consistently reported in the whole urine of patients with PCa compared to those with BPH in a statistically significant manner regardless of the quantification methodology performed. Moreover, a significant increase in diagnostic performance was observed when molecular signatures composed of different miRNAs were considered. Hence, the abovementioned circulating ncRNAs represent excellent potential non-invasive biomarkers in urine capable of effectively distinguishing individuals with PCa from those with BPH, potentially reducing cancer overdiagnosis.

Automated quantification of crack length and width in asphalt pavements

AbstractRapid, accurate, and fully automated estimation of both length and width of asphalt pavement cracks, essential for achieving a proactive asset management, presents a significant challenge, primarily due to limitations in the effectiveness of automatic image segmentation and the accuracy of crack width and length estimation algorithms. To address this challenge, this paper introduces the Branch Growing (BG) algorithm, specifically designed for crack length estimation in asphalt pavements, along with an optimized OrthoBoundary algorithm tailored for crack width estimation. Leveraging four widely adopted deep learning models for asphalt pavement crack segmentation, four distinct sets of image segmentation results have been produced. Subsequently, a comprehensive evaluation has been conducted to assess the effectiveness of both crack dimensions estimation algorithms. The findings demonstrate that the integration of the BG algorithm, the optimized OrthoBoundary algorithm, and the fully convolutional network with the HRNet backbone achieve a prediction accuracy of 80.21% for crack length estimation and 84.32% for average width estimation. Moreover, the image processing speed, at a resolution of 3024 × 3024, can be maintained at approximately 5 s, with average width estimation observed to be up to 9.1‐fold faster than the unoptimized OrthoBoundary algorithm. These results signify advancements in automated crack quantification methodologies, with implications for enhancing civil infrastructure maintenance practices.

Microcystins are present in water treatment plant residuals and are impacted by extraction and quantification methodology

ABSTRACT Microcystins (MCs), a toxin produced by some species of the photosynthetic autotrophic cyanobacteria, are the most studied and monitored cyanotoxin in water. Water treatment plant (WTP) residuals are the byproduct of water treatment consisting of solids removed from WTP processes and have been shown to contain cyanobacterial cells. However, the presence of MCs in WTP residuals has not been systematically demonstrated. Samples from four different WTPs across the United States were used to quantify MCs in residuals while assessing extraction and quantification methods adapted from water samples for solid matrices. MCs were present in 100% of samples. MC-LA was the most prevalent variant in these samples (70.05% of MCs quantified by UPLC-PDA). Natural degradation observed in a WTP storage lagoon was also investigated to determine the impact of physical, chemical, and biological processes on MC concentrations in high-biomass residuals. This study demonstrates that residuals of various characteristics across the United States contain MCs, and no one method was found to maximize results consistently across all samples. Cyanotoxins accumulating in WTP residuals are a growing concern. Implications of this work can help regulations and future studies of potential reuse applications and understanding of potential ecological significance of MCs accumulating in WTP residuals.

Electrical Bioimpedance in Milk Adulterated with Water: Measurement Methodology for Quantification, Influence of Temperature, and Mathematical Modelling

Milk has a high nutritional value and is also one of the most versatile products in the food industry. Unfortunately, fraud involving the product is constant and needs to be combated. This work presents a measurement methodology to perform the electrical impedance analysis in food. The influence of temperature on the measurements has been evaluated through mathematical models specially developed for identifying the fraudulent activity of adding water to milk. The bioimpedance measurements have been performed in a sample container with a four-electrode measurement system and a digital oscilloscope. Samples of 150 mL were analysed, prepared using whole UHT milk adulterated with distilled water in different % by volume (V/V), at temperatures of 16, 28, and 37 °C. The proposed measurement methodology has been validated and showed sensitivity for analysis in milk, revealing the influence of temperature on the impedance values; from the results mathematical models were proposed for investigating adulteration in milk. This work deals with the design of a device capable of measuring bioimpedance in milk with a view to its application in physicochemical analyses. The influence of temperature on the impedance values was also evaluated to propose mathematical models to facilitate analysis with complex factors and matrices.

Chromatographic fingerprinting of ipratropium and fenoterol in their novel co-formulated inhaler treating major respiratory disorders; application to delivered dose uniformity testing along with greenness and whiteness assessment

Ipratropium bromide (IPR) and fenoterol hydrobromide (FEN) have recently been combined in a promising inhaler to treat two prevalent inflammatory illnesses of the airways: bronchial asthma and chronic obstructive pulmonary disease (COPD). The necessity for a single, sensitive, and trustworthy analytical approach to cover the diverse and necessary tests of in-vitro and in-vivo studies is greatly grown with the rising production of new fixed combinations. Two novel, selective and environmentally friendly LC techniques were developed in order to guarantee precise measurement of IPR and FEN in their challenging formulation. The initial technique involved high-performance thin-layer chromatography (HPTLC) in conjunction with densitometric quantification. Chromatographic separation was attained on HPTLC plates utilizing ethyl acetate - ethanol - acetic acid (5.0:5.0:0.1, by volume) as a developing system. Densitometric quantification of the separated bands was carried out at 220.0 nm over concentration ranges of 0.50–15.0 µg/band for IPR and 0.50–12.0 µg/band for FEN. High-performance liquid chromatography (HPLC) paired with diode array detection (DAD) was the core of the second technique. The optimized separation was achieved on a Zorbax SB C18 (150 × 4.6 mm, 5 μm) column with a combination of 10.0 mM potassium dihydrogen orthophosphate, pH 5.0 ± 0.1, adjusted with o-phosphoric acid and methanol (70:30, v/v) as the mobile phase and pumped at flow rate of 1.0 mL/min. The peaks were monitored at 220.0 nm using diode array detection, achieving linearity range of 5.0–200.0 µg/mL for both drugs. The ICH criteria have been verified and both methods have been confirmed to be valid, and successfully applied for assay the cited drugs in the Atrovent® comp HFA metered dose inhaler as well as delivered dose uniformity testing of the final product. Finally, whiteness appraisal and several state-of-the-art green evaluation metrics were applied to evaluate the sustainability of the proposed methods. The suggested approaches produced promising results and are the first simple and sustainable methodologies for the simultaneous quantification of both drugs in different real samples, all of which strongly suggest their application in quality control laboratories.

Free radical quantification in chemical systems: Challenges and future perspectives

The importance of free radicals in several chemical and biological systems has been extensively documented in the literature. Free radical detection is possible through techniques such as electron spin resonance (ESR), chemically induced dynamic nuclear polarization (CIDNP), and biochemiluminescence. Herein, we provide a comprehensive review of free radical detection, with an emphasis on free radical quantification. The ability to control free radical reactions of various matrices necessitates measuring free radical concentration, which can be obtained by quantifying free radicals. In the current work, we provide a review of various methods and procedures employed for free radical quantification in chemical systems. Procedures were discussed in detail and then grouped based on the instrument used, the operating conditions, and the methodology employed to convert the ESR signal obtained to free radical spins per unit mass of sample. We also provide a comparison with free radical quantification in biological systems. It was found that there is a notable dearth of work focused on quantification in chemical systems despite its potential to enhance control over free radicals. In the last part of this manuscript, we provide a summary and suggested methodology for free radical quantification in chemical systems using ESR focusing on factors affecting quantification.

Methodology for Quantification of Technological Processes in Passenger Railway Transport Using Alternatively Powered Vehicles

Due to the reduction in diesel propulsion on railway networks across the world, it is essential to consider the introduction of an alternative propulsion where electrification would not be feasible. The introduction of alternative propulsions may influence the technological processes of train processing and interrupt its quantification methodology, due to their specific operational requirements. The problem of the quantification of technological processes of train processing is not sufficiently solved even in the field of conventional propulsions; therefore, the aim of this paper is to propose a unique methodological procedure for the quantification of selected processes of train processing operated by multiple units with a conventional or alternative propulsion. The new process quantification methodology enables the duration determination of a specific process, which can be simply determined for multiple units of different length and propulsion under local conditions. The duration determination is based on the final formula or its graphical representation. The function is based on data obtained by analysing the evaluated workflow of a model and multiple units using the PERT network analysis method. The proposed methodological procedure is verified by different types of propulsions through a case study using real values. The application of the methodology can prevent the risks related to non-compliance of the required technological times and at the same time increase the sustainability of the operation stability of railway passenger transport.

Uncertainty Quantification in Mineral Resource Estimation

AbstractMineral resources are estimated to establish potential orebody with acceptable quality (grade) and quantity (tonnage) to validate investment. Estimating mineral resources is associated with uncertainty from sampling, geological heterogeneity, shortage of knowledge and application of mathematical models at sampled and unsampled locations. The uncertainty causes overestimation or underestimation of mineral deposit quality and/or quantity, affecting the anticipated value of a mining project. Therefore, uncertainty is assessed to avoid any likely risks, establish areas more prone to uncertainty and allocate resources to scale down potential consequences. Kriging, probabilistic, geostatistical simulation and machine learning methods are used to estimate mineral resources and assess uncertainty, and their applicability depends on deposit characteristics, amount of data available and expertise of technical personnel. These methods are scattered in the literature making them challenging to access when needed for uncertainty quantification. Therefore, this review aims to compile information about uncertainties in mineral resource estimation scatted in the literature and develop a knowledge base of methodologies for uncertainty quantification. In addition, mineral resource estimation comprises different interdependent steps, in and through which uncertainty accumulates and propagates toward the final estimate. Hence, this review demonstrates stepwise uncertainty propagation and assessment through various phases of the estimation process. This can broaden knowledge about mineral resource estimation and uncertainty assessment in each step and increase the accuracy of mineral resource estimates and mining project viability.

Identification by HSQC and quantification by qHNMR innovate pharmaceutical amino acid analysis

This study introduces a new NMR-based methodology for identification (ID) and quantification (purity, strength) assays of widely used amino acids. A detailed analysis of four amino acids and their available salts was performed with both a high-field (600 MHz) and a benchtop (60 MHz) NMR instrument. To assess sensitivity constraints, samples for 1H NMR analysis were initially prepared using only 10 mg of analyte and 1 mg of maleic acid (MA) as an internal calibrant (IC) and secondary chemical shift reference. The characteristic dispersion of the peak patterns indicating the presence or absence of a counterion (mostly chloride) was conserved at both high and low-field strength instruments, showing that the underlying NMR spectroscopic parameters, i.e., chemical shifts and coupling constants, are independent of the magnetic field strength. However, as the verbal descriptions of 1H NMR spectra are challenging in the context of reference materials and pharmaceutical monographs, an alternative method for the identification (ID) of amino acids is proposed that uses 13C NMR patterns from multiplicity-edited HSQC (ed-HSQC), which are both compound-specific and straightforward to document. For ed-HSQC measurements, the sample amount was increased to 30 mg of the analyte and several acquisition parameters were tested, including t1 increments used in the pulse program, number of scans, and repetition time. Excellent congruence with deviations <0.1 ppm was achieved for the 13C chemical shifts from 1D 13C NMR spectra (150 MHz) vs. those extracted from ed-HSQC (15 MHz traces). Finally, all samples of amino acid candidate reference materials were quantified by 1H qNMR (abs-qHNMR) at both 600 and 60 MHz. At high field, both IC and relative quantitations were performed, however, with the low-field instrument, only the IC method was used. The results showed that the analyzed reference material candidates were generally highly pure compounds. To achieve adequately low levels of uncertainty for such high-purity materials, the sample amounts were increased to 100 mg of analytes and 10 mg of the IC and replicates were analyzed for selected amino acids.

Global Sensitivity Analysis for Segmented Inverse Uncertainty Quantification in the Safety Analysis of Nuclear Power Plants

Within the Best Estimate Plus Uncertainty framework for the safety analysis of Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal-Hydraulics (T-H) codes used is crucial. For this, Inverse Uncertainty Quantification (IUQ) methodologies are being developed for determining the probability density functions of relevant T-H codes input parameters, based on experimental data from Separate Effect Tests (SETs) experimental facilities. In practice, IUQ is challenged by the large range of variability of the experimental data in terms of Initial and Boundary Conditions (ICs & BCs), because the experimental campaigns are designed to cover the widest possible domain of conditions with the smallest number of experiments, so that same or similar ICs and BCs are seldomly repeated. To address this issue, we propose to use global sensitivity analysis, to tailor the IUQ on specific sub-regions described by segmented ICs & BCs domains. The methodology proposed is exemplified on two SETs, namely Sozzi-Sutherland and Super Moby Dick, whose experimental databases have been made available in the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the OECD/NEA/CSNI. The results obtained are superior to those of traditional IUQ methodologies for models highly sensitive to ICs & BCs.

Design and Evaluation of Packaging Art Based on Sentimental Value Calculation and Clustering

This paper introduces the cultural dimension of product packaging, elucidates the quantification principle and methodology governing customer aesthetic experiences, propounds an innovative packaging style design approach, and presents an evaluation model based on an enhanced neural network. Using tea packaging design as an illustrative case, the methodology initially aligns adjectives, subsequently computes the emotional depth value, and ultimately derives the corresponding correlation between customer emotional experiences and design elements through a neural network. Subsequently, the designed model is validated using tea packaging design as a practical example. The outcomes demonstrate the model's accuracy and efficacy in establishing the mapping between design elements and aesthetic experiences, offering novel insights for the evolution of packaging design in the contemporary market landscape.

Quantifying the influence of BIM adoption: An in-depth methodology and practical case studies in construction

This research presents a comprehensive framework for quantifying the benefits of Building Information Modelling in construction. Through industry insights and surveys, the study validates formulated equations and integrates case studies from the Swedish construction sector. Results reveal increased costs in the design phase but indicate time and cost savings during design and construction. Operational benefits, notably in maintenance planning and energy efficiency, constitute a substantial portion of the total estimated benefits. The study introduces a unified quantification methodology, demonstrating an investment rate of 16.1 % and 10.17 % for cases A and B, respectively. This research contributes to the ongoing discourse on BIM adoption, offering valuable insights and methodological advancements for industry practitioners.

Smartphone-Based Colourimetric Detection of Methyl Red, Co(II), Uric Acid, and Topotecan after Pre-concentration onto a Hectorite Clay-Hydroxyethylcellulose Hybrid

Objective:: This paper describes a new, digital image colourimetry-based format for the quantification of analytes in an aqueous solution. Method:: The proposed method is based on analyte pre-concentration by adsorption onto Bentone LT. Bentone LT pellet isolation comes after adsorption, followed by in-situ application of an analyteselective chromogenic reaction. The resulting pellet colouration is captured by the phone’s integrated camera and assessed using the free open-source image processing software, ImageJ. Responses are calibrated and quantified. Results:: We tested the applicability of the proposed methodology for the quantification of specific model analytes which are of concern in environmental matrices (methyl red, Co(II), uric acid, topotecan). The smartphone-based assay was proven reliable in quantifying the model analytes (standard recovery of 82-116%), alone or in mixture, from dilute aqueous solutions and was found to depict accurately the adsorption behaviour followed photometrically in solution. Lower limit of linearity was calculated at 0.05, 0.11, 0.85 and 0.20 μg/mL for methyl red, Co(II), uric acid, and topotecan, respectively. The proposed format was found superior when compared to alternative published photometric/ colourimetric assays in terms of the lower limit of linearity. In the presence of possible adsorption interferents, the lower limit of linear response was shifted to slightly higher concentrations for topotecan i.e. from 0.2 μg/mL to 0.5 μg/mL. Conclusion:: We here demonstrate the extended applicability of the proposed methodology for the smartphone-based quantification of the specific model analytes. The applicability of this analysis format likely extends to other analytes, where analyte-specific colour formation is feasible.

Towards Carbon Footprint Management in Hybrid Multicloud

Enterprises today aspire to optimize the operating costs and carbon footprint (CFP) of their IT operations jointly without compromising their business imperatives. This has given rise to a hybrid approach in which enterprises retain the dynamic choice to leverage private data centers and one or more public clouds in conjunction. While cloud service providers (CSPs) have long provided APIs for estimating, reconciling, and optimizing operating costs, they have only recently started exposing APIs related to CFP. Indeed, this is a step in the right direction. Nevertheless, our analyses of these APIs reveals many gaps that need to be addressed to facilitate sizing and placement decisions that can factor in carbon. First, there is a lack of standardized, transparent methodology for CFP quantification across different CSPs. Second, the coarse granularity of the CFP data provided today can help with post-facto reporting but is not suitable for proactive fine-grained optimization. Last, enterprises themselves are unable to independently compute the current CFP or estimate potential CFP savings since CSPs do not share the required power usage data. To address these gaps, enterprises have started developing their own carbon assessment methodologies and tools to estimate the CFP of workloads running on public clouds using the available user-facing APIs. These systems hold the promise for an independent and unbiased evaluation and estimation of relative savings between different deployment options by cloud users. We describe and analyze the details of CSP-native carbon-reporting tools and their quantification methodology, and the "outside-of-the-cloud" estimation approaches. Finally, we present opportunities for future research in the direction of trustworthy, fine-grained, public cloud workload CFP estimation, which is a prerequisite for meaningful realization of carbon optimization.