Measurement Strategies Research Articles

Beyond Lux: methods for species and photoreceptor-specific quantification of ambient light for mammals

Abstract Background Light is a key environmental regulator of physiology and behaviour. Mistimed or insufficient light disrupts circadian rhythms and is associated with impaired health and well-being across mammals. Appropriate lighting is therefore crucial for indoor housed mammals. Light is commonly measured in lux. However, this employs a spectral weighting function for human luminance and is not suitable for ‘non-visual’ effects of light or use across species. In humans, a photoreceptor-specific (α-opic) metrology system has been proposed as a more appropriate way of measuring light. Results Here we establish technology to allow this α-opic measurement approach to be readily extended across mammalian species, accounting for differences in photoreceptor types, photopigment spectral sensitivities, and eye anatomy. We develop a high-throughput method to derive spectral sensitivities for recombinantly expressed mammalian opsins and use it to establish the spectral sensitivity of melanopsin from 13 non-human mammals. We further address the need for simple measurement strategies for species-specific α-opic measures by developing an accessible online toolbox for calculating these units and validating an open hardware multichannel light sensor for ‘point and click’ measurement. We finally demonstrate that species-specific α-opic measurements are superior to photopic lux as predictors of physiological responses to light in mice and allow ecologically relevant comparisons of photosensitivity between species. Conclusions Our study presents methods for measuring light in species-specific α-opic units that are superior to the existing unit of photopic lux and holds the promise of improvements to the health and welfare of animals, scientific research reproducibility, agricultural productivity, and energy usage.

Future Low-Cost Urban Air Quality Monitoring Networks: Insights from the EU’s AirHeritage Project

The last decade has seen a significant growth in the adoption of low-cost air quality monitoring systems (LCAQMSs), mostly driven by the need to overcome the spatial density limitations of traditional regulatory grade networks. However, urban air quality monitoring scenarios have proved extremely challenging for their operative deployment. In fact, these scenarios need pervasive, accurate, personalized monitoring solutions along with powerful data management technologies and targeted communications tools; otherwise, these scenarios can lead to a lack of stakeholder trust, awareness, and, consequently, environmental inequalities. The AirHeritage project, funded by the EU’s Urban Innovative Action (UIA) program, addressed these issues by integrating intelligent LCAQMSs with conventional monitoring systems and engaging the local community in multi-year measurement strategies. Its implementation allowed us to explore the benefits and limitations of citizen science approaches, the logistic and functional impacts of IoT infrastructures and calibration methodologies, and the integration of AI and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements and reporting. Similar research or operative projects have been implemented in the recent past, often focusing on a limited set of the involved challenges. Unfortunately, detailed reports as well as recorded and/or cured data are often not publicly available, thus limiting the development of the field. This work openly reports on the lessons learned and experiences from the AirHeritage project, including device accuracy variance, field recording assessments, and high-resolution mapping outcomes, aiming to guide future implementations in similar contexts and support repeatability as well as further research by delivering an open datalake. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, citizens, public authorities, and agencies, about effective strategies for deploying and utilizing LCAQMSs to enhance air quality monitoring and public awareness on this challenging urban environment issue.

Finding the optimal probe state for multiparameter quantum metrology using conic programming

The ultimate precision in quantum sensing could be achieved using optimal quantum probe states. However, current quantum sensing protocols do not use probe states optimally. Indeed, the calculation of optimal probe states remains an outstanding challenge. Here, we present an algorithm that efficiently calculates a probe state for correlated and uncorrelated measurement strategies. The algorithm involves a conic program, which minimizes a linear objective function subject to conic constraints on a operator-valued variable. Our algorithm outputs a probe state that is a simple function of the optimal variable. We prove that our algorithm finds the optimal probe state for channel estimation problems, even in the multiparameter setting. For many noiseless quantum sensing problems, we prove the optimality of maximally entangled probe states. We also analyze the performance of 3D-field sensing using various probe states. Our work opens the door for a plethora of applications in quantum metrology.

Image reconstruction from compressed measurements for ultrasound NDT

In ultrasound NDT, Delay-and-Sum schemes are commonly used to reconstruct images from the measurement data. For single channel pulse-echo measurements, this is called Synthetic Aperture Focusing Technique (SAFT). In a multi-channel setup, SAFT is extended to the Total Focusing Method (TFM), where the focused image is reconstructed from measurements of all transmit-receive combinations, called Full Matrix Capture (FMC). In previous work, we showed that both SAFT and TFM can be cast as a sparse recovery problem that enables enhancing the Delay-and-Sum scheme to a physically motivated forward model that leads to improved image quality. The reconstruction is performed using l1 minimization. Further, this also allows to perform the reconstruction from compressed/subsampled measurements following compressed sensing theory. This subsampling was achieved by only measuring a subset of the frequency coefficients of the signal. In both the single channel and the multi-channel setup the amount of measurement data is thereby significantly reduced. Additionally, for the TFM, we added a spatial subsampling by only considering a subset of transmit and receive pairs, further reducing the measurement data and at the same time also reducing the measurement time. In our previous work, the frequency and spatial dimensions were considered separately for simplicity, using the same compression strategy for all spatial measurements. In this work we consider joint frequency/spatial compression schemes. We show that a joint multidimensional compression strategy where different Fourier subsets are considered for each channel pair leads to a superior reconstruction performance when the compression rate is fixed. Analysis based on an analytical model for a single defect and a real-world example with multiple defects shows that the approach works in practice.

GHZ protocols enhance frequency metrology despite spontaneous decay.

The use of correlated states and measurements promises improvements in the accuracy of frequency metrology and the stability of atomic clocks. However, developing strategies robust against dominant noise processes remains challenging. We address the issue of decoherence due to spontaneous decay and show that Greenberger-Horne-Zeilinger (GHZ) states, in conjunction with a correlated measurement and nonlinear estimation strategy, achieve gains of up to 2.25 decibel, comparable to fundamental bounds for up to about 80 atoms in the presence of decoherence. This result is unexpected because GHZ states do not provide any enhancement under dephasing due to white frequency noise compared to the standard quantum limit of uncorrelated states. The gain arises from a veto signal, which allows for the detection and mitigation of errors caused by spontaneous emission events. Through comprehensive Monte Carlo simulations of atomic clocks, we demonstrate the robustness of the GHZ protocol.

Molecular survey of certain protozoan agents that cause diarrhea in children in Sudan

Introduction Diarrhea is a significant health problem in the Third World. Identification of the pathogen that causes diarrhea is vital for measures to prevent and control this disease. There are also very few reports of diarrhea in Sudan. Our study aimed to determine the Prevalence of specific protozoan pathogens (Entamoeba histolytica, Cryptosporidium parvum., and Giardia spp) in children in Khartoum, Sudan. Methods We conducted a cross-sectional survey among children under five years of age hospitalized with acute diarrhea between April and December 2014. Diarrheal stool samples were collected, and E. histolytica, C. parvum, and Giardia spp were examined using multiplex real-time PCR. Results Four hundred and thirty-seven children with acute diarrhea were included in this study; the higher prevalence of diarrhea was in the age ≤ 2 years old (403, 92.2%), >2–≤4 years (32, 7.3%), and >4–<5 years (2, 0.5%). The male-to-female ratio in this study was 1:1.7. Infection with intestinal parasite was found in 155 (35.5%) cases, and co-infection was detected in 16 (3.7%) cases. Giardia spp (18.8%) and C. parvum (15.8%) were the most frequently identified parasites, followed by E. histolytica (0.9). The parasite infection rate was highest and lowest in the under 2-year-old group 143 (35.5%) and the 2–4-year-old group 12 (37.5%). The infection rate was higher in boys 104 (37.7%) than in girls 51 (31.7%). The number of positive cases was higher in the rainy season (August to December) 143 (37.4%), corresponding with that in the dry Season (April to June) 12 (21.8%). Discussion Our present study demonstrated the high prevalence of Giardia spp and C. parvum in children with diarrhea in the Khartoum region and the usefulness of the multiplex real-time method in disclosing pathogenic protozoal agents. Our result highlighted the necessity of developing intervention measurement and control strategies to deal with childhood parasitic diarrhea in this region.

Long-Range Three-Dimensional Tracking of Nanoparticles Using Interferometric Scattering Microscopy.

Tracking nanoparticle movement is highly desirable in many scientific areas, and various imaging methods have been employed to achieve this goal. Interferometric scattering (iSCAT) microscopy has been particularly successful in combining very high spatial and temporal resolution for tracking small nanoparticles in all three dimensions. However, previous works have been limited to an axial range of only a few hundred nanometers. Here, we present a robust and efficient measurement and analysis strategy for three-dimensional tracking of nanoparticles at high speed and with nanometer precision. After discussing the principle of our approach using synthetic data, we showcase the performance of the method by tracking gold nanoparticles with diameters ranging from 10 to 80 nm in water, demonstrating an axial tracking range from 4 μm for the smallest particles up to over 30 μm for the larger ones. We point out the limitations and robustness of our system across various noise levels and discuss its promise for applications in cell biology and material science, where the three-dimensional motion of nanoparticles in complex media is of interest.

Intergenerational coparenting and child development outcomes: A systematic review

AbstractGrandparents often serve important childrearing roles. The present study is a systematic review of research that examined the association between intergenerational coparenting and children's development. Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines, 220 records were identified, and 16 studies were included in the final review. The review provided a detailed analysis of the methodological characteristics of research in this area. Findings indicated that better intergenerational coparenting was associated with higher levels of children's social competence, executive functioning, and attachment security. Evidence also suggests parenting mediates the relation between intergenerational coparenting and child development. Several directions for future research emerged from the review including the need (a) for measurement strategies that reflect the multidimensional nature of intergenerational coparenting, (b) to consider the various parent‐grandparent dyads, and (c) to incorporate other family factors and processes (e.g., quality of parent‐grandparent relationships) into studies that focus on intergenerational coparenting.

Light-tracing based surface deformation measurement strategy for large radio telescopes

Light-tracing based surface deformation measurement strategy for large radio telescopes

Partidismo gubernamental en los sistemas presidenciales. Una estrategia de análisis

Objective/context: Based on a definition consistent with the party government model, this article proposes a flexible typology to categorize and classify variants of partisanship in Latin American coalition presidential systems. Methodology: We advance a measurement strategy that, based on the assumptions of governmental partisanship, allows representing the individual-organizational link of cabinet members as committed, eventually consolidated, and hierarchical. This typology enables to measure the concept of governmental partisanship nominally, ordinally, and dichotomously. Conclusions: The measurement strategy makes it possible to observe a significant range of partisanship variation in Latin American coalition presidential systems. Additionally, it provides insights into how presidents decide on the composition of their cabinet. Originality: We propose an innovative approach to categorize and classify variants of partisanship in government.

Who cares? Measuring differences in preference intensity

Abstract How well do existing survey instruments differentiate between opinions that affect individual behavior and opinions that don't? To answer this question, we randomly assigned U.S. respondents to one of three survey instruments: Likert items (Likert), Likert items followed by personal importance items (Likert+) and Quadratic Voting for Survey Research (QVSR), which gives respondents a fixed budget to buy “favor” or “oppose” votes, with the price for each vote increasing quadratically. We find that, relative to Likert, both Likert+ and QVSR better identify people who care enough about an issue to act in opinion-congruent ways, with QVSR offering the most consistent improvement overall. Building on these results, we show how conclusions regarding the relationship between policy opinions and self-interest can differ across measurement strategies.

Three-dimensional spatiotemporal wind field reconstruction based on LiDAR and multi-scale PINN

In this numerical study, we use a multi-scale version of physics-informed neural network (PINN) for wind field reconstruction from LiDAR measurements. The reference velocity field is obtained from high-fidelity large-eddy simulation of neutral atmospheric boundary layer, and the LiDAR measurement strategy is restricted to that of a real LiDAR. The multi-scale PINN reconstructs the velocity field by minimizing a combination of the L2-error with respect to the LiDAR measurements and residuals of the governing equations. Our most significant finding is that adding a multi-scale layer to PINN enables us to: (i) capture wider range of scales, (ii) reconstruct the flow field outside the LiDAR scanning area, and (iii) reach faster convergence. We also find that for volumetric flow reconstruction and to deal with uncertainty in the wind direction, the reconstruction accuracy can be greatly improved by employing multiple LiDAR devices. Overall, our results show that the normalized errors in the reconstructed wind field are lower than 5% for all the experiments conducted in this study and that the errors do not increase even in the presence of measurement noise levels of typical LiDAR. These findings show the feasibility of three-dimensional dynamic wind field reconstruction across large wind farms using LiDAR devices.

Wooden multistorey acoustic test facility for vibration reduction indices measurement on different junctions of floor decking used to reduce flanking transmissions

FCBA, CSTB and Cerqual joint forces together with the French acoustic wood technical commission, to create in 2020, an in-situ measurement mockup: the "Maquette Acoustique Bois". The mockup is a CLT based building of three floors construction, with four rooms on each level. Measurements from junction characterization to air-borne and impact sound insulations can be performed. In this paper the "Maquette Acoustique Bois" is used to measure vibration reductions levels indexes Kij, in different configurations, where smart building systems junctions are implemented to reduce flanking transmissions. Measurement results presented are generated from 4 types of junctions in between 2 rooms. The load bearing structure is Cross Laminated Timber (CLT). The measurement strategy is Statistical Energy Analysis (SEA). SEA involves cutting the structure into subsystems and decomposing the spectrum into third-octaves or octaves. In this way, the exchange of energy flow in the substructures can be analyzed. The parameters that govern vibrational transmission between subsystems are damping and coupling loss factors and can be identified experimentally by reversing the problem. The approach is, first, based on sub-structuring strategy of structure; second, on experimentally measured coupling and damping loss factors; third, on extracting vibration level difference one by one all flanking passes.

A-067 Simultaneous Measurement of Aldosterone and Plasma Renin Activity in Human Serum Using Liquid Chromatography Coupled to Tandem Mass Spectrometry for Clinical Research

Abstract Background The combination of primary aldosteronism (PA) and alterations in plasma renin activity (PRA) is a leading cause of secondary hypertension. An accurate measurement of Renin Angiotensin-Aldosterone System (RAAS) pathway improves the recognition of symptoms related to stroke, coronary disease, heart failure and metabolic syndrome. Methods Previously, surrogate matrices have been used when demonstrating the analytical performance of LC-MS/MS clinical research methods for the measurement of aldosterone and angiotensin I. Here, we have developed an analytically sensitive and reliable analytical strategy for simultaneous measurement of Aldosterone and Angiotensin I in human matrices. In-house calibrators and quality control samples were prepared, containing varying ranges of both aldosterone (20-2000pg/mL; 55-5548pmol/L) and angiotensin 1 (0.6-240ng/mL; 0.46-185nmol/L). The samples were extracted using the Oasis™ MAX 96-well µElution plate and then separated through the ACQUITY™ UPLC™ I-Class FL System using a XBridge™ Premier Peptide BEH™ C18 Column, over a run time of 3 minutes. Samples were then injected to Xevo™ TQ Absolute Mass Spectrometer, using both positive and negative acquisition modes. The downstream LC-MS/MS data analysis was performed using MassLynx™ MS Software. The analytical performance was demonstrated by extracting and quantifying two replicates of samples on two occasions per day over five separate days. Additionally, the stability of aldosterone and angiotensin I over the period of incubation (3-5hr) was evaluated, which is necessary when investigating the plasma renin activity in human Serum/Plasma samples. Results High reproducibility and repeatability were both determined, indicating total precision and repeatability (<15%CV) for both analytes and no significant changes were found in Aldosterone and Angiotensin I concentrations over 3-5hr of incubation. No significant system carryover (<10% of the lowest calibrator) from high concentration samples into subsequent blank injections was observed. In addition, calibration lines in human serum/plasma were linear, with coefficient of determinations (r2) >0.992 for all analyses at different incubation times. The analytical sensitivity of the clinical research method allows for precise quantification at 55 pmol/L for aldosterone and 0.46 nmol/L/hr for angiotensin I, with both analytes providing S/N (PtP) ≥10:1 and %RSD of <15% at these concentrations. Conclusions An analytically sensitive and selective clinical research method has been developed for the analysis of aldosterone and angiotensin I, using the Xevo TQ Absolute Mass Spectrometer. The Xevo TQ Absolute Mass Spectrometer enables the simultaneous analysis of physiologically low levels of aldosterone and plasma renin activity in human samples, (20pg/mL; 55pmol/L), (0.6ng/mL; 0.46nmol/h/L). A single test that improves instrument utilization, reduces cost, and allows the user to expand their existing test menu on the same platform has been established.

A Patient-Relevant Measurement Strategy to Assess Clinical Benefit of Novel Therapies for Non-metastatic Cutaneous Squamous Cell Carcinoma.

Although cutaneous squamous cell carcinoma (CSCC) is the second most common type of skin cancer, research describing the patient experience is limited. This study sought to create a conceptual model of non-metastatic disease, to assess patient-reported outcome (PRO) instruments commonly used in CSCC against this model, and to develop a patient-relevant measurement strategy for evaluating the benefit of new therapies. Researchers conducted a literature review, a review of patient blogs, and interviews with dermatologists to draft the conceptual model. A total of 22 patients with CSCC participated in 60-min phone interviews, which were subsequently transcribed, coded, and analyzed; the conceptual model was thenupdated. PRO instruments used in CSCC were assessed for content validity on the basis of this. The CSCC patient experience includes physical symptoms, psychological impacts, and behavior changes. Existing PRO instruments were assessed against the conceptual model using targeted subdomains considered to be relevant for assessing clinical benefit. Four modules of the FACE-Q® Skin Cancer instrument, plus de novo items developed for concepts not assessed by the FACE-Q® [lesion symptoms, negative treatment effects (including symptomatic), and experience of care], provide the best coverage for the concepts of interest hypothesized to show the benefit of novel treatments. This research provides a comprehensive understanding of the experience of patients with non-metastatic CSCC, and the effects of its treatment. It also identifies unmet needs in a subgroup of patients reporting negative treatment experiences. Further cognitive debriefing and psychometric analysis of de novo items are warranted for applications in clinical research.

Quantifying the uniqueness and divisiveness of presidential discourse

Abstract Do American presidents speak discernibly different from each other? If so, in what ways? And are these differences confined to any single medium of communication? To investigate these questions, this paper introduces a novel metric of uniqueness based on large language models, develops a new lexicon for divisive speech, and presents a framework for assessing the distinctive ways in which presidents speak about their political opponents. Applying these tools to a variety of corpora of presidential speeches, we find considerable evidence that Donald Trump’s speech patterns diverge from those of all major party nominees for the presidency in recent history. Trump is significantly more distinctive than his fellow Republicans, whose uniqueness values appear closer to those of the Democrats. Contributing to these differences is Trump’s employment of divisive and antagonistic language, particularly when targeting his political opponents. These differences hold across a variety of measurement strategies, arise on both the campaign trail and in official presidential addresses, and do not appear to be an artifact of secular changes in presidential communications.

Adaptively remeshed multiphysical modeling of resistance forge welding with experimental validation of residual stress fields and measurement processes

Welding processes used in the production of pressure vessels impart residual stresses in the manufactured component. Computational modeling is critical to predicting these residual stress fields and understanding how they interact with notches and flaws to impact pressure vessel durability. In this work, we present a finite element model for a resistance forge weld and validate it using laboratory measurements. Extensive microstructural changes, near-melt temperatures, and large localized deformations along the weld interface pose significant challenges to Lagrangian finite element modeling. The proposed modeling approach overcomes these roadblocks in order to provide a high-fidelity simulation that can predict the residual stress state in the manufactured pressure vessel; a rich microstructural constitutive model accounts for material recrystallization dynamics, a frictional-to-tied contact model is coordinated with the constitutive model to represent interfacial bonding, and adaptive remeshing is employed to alleviate severe mesh distortion. An interrupted-weld approach is applied to the simulation to facilitate comparison to displacement measures. Several approaches are employed for residual stress measurement in order to validate the finite element model: neutron diffraction, the contour method, and the slitting method. Model-measurement comparisons are supplemented with detailed simulations that reflect the configurations of the residual-stress measurement processes themselves. The model results show general agreement with experimental measurements, and we observe some similarities in the features around the weld region. Factors that contribute to model-measurement differences are identified. Finally, we conclude with some discussion of the model development and residual stress measurement strategies, including how to best leverage the efforts put forth here for other types of related weld problems.

Momentum exchange method for quantum Boltzmann methods

The past years have seen a surge in quantum algorithms for computational fluid dynamics (CFD). These algorithms have in common that whilst promising a speed-up in the performance of the algorithm, no specific method of measurement has been suggested. This means that while the algorithms presented in the literature may be promising methods for creating the quantum state that represents the final flow field, an efficient measurement strategy is not available. This paper marks the first quantum method proposed to efficiently calculate quantities of interest (QoIs) from a state vector representing the flow field. In particular, we propose a method to calculate the force acting on an object immersed in the fluid using a quantum version of the momentum exchange method (MEM) that is commonly used in lattice Boltzmann methods to determine the drag and lift coefficients. In order to achieve this we furthermore give a scheme that implements bounce back boundary conditions on a quantum computer, as those are the boundary conditions the momentum exchange method is designed for.

Adaptive Phase Estimation with Squeezed Vacuum Approaching the Quantum Limit

Phase estimation plays a central role in communications, sensing, and information processing. Quantum correlated states, such as squeezed states, enable phase estimation beyond the shot-noise limit, and in principle approach the ultimate quantum limit in precision, when paired with optimal quantum measurements. However, physical realizations of optimal quantum measurements for optical phase estimation with quantum-correlated states are still unknown. Here we address this problem by introducing an adaptive Gaussian measurement strategy for optical phase estimation with squeezed vacuum states that, by construction, approaches the quantum limit in precision. This strategy builds from a comprehensive set of locally optimal POVMs through rotations and homodyne measurements and uses the Adaptive Quantum State Estimation framework for optimizing the adaptive measurement process, which, under certain regularity conditions, guarantees asymptotic optimality for this quantum parameter estimation problem. As a result, the adaptive phase estimation strategy based on locally-optimal homodyne measurements achieves the quantum limit within the phase interval of [0,π/2). Furthermore, we generalize this strategy by including heterodyne measurements, enabling phase estimation across the full range of phases from [0,π), where squeezed vacuum allows for unambiguous phase encoding. Remarkably, for this phase interval, which is the maximum range of phases that can be encoded in squeezed vacuum, this estimation strategy maintains an asymptotic quantum-optimal performance, representing a significant advancement in quantum metrology.

Identification of malfunctioning quantum devices

We consider the problem of correctly identifying a malfunctioning quantum device that forms part of a network of N such devices, which can be considered as the quantum analog of classical anomaly detection. In the case where the devices in question are sources assumed to prepare identical quantum pure states, with the faulty source producing a different anomalous pure state, we show that the optimal probability of successful identification requires a global quantum measurement. We also put forth several local measurement strategies—both adaptive and nonadaptive—that achieve the same optimal probability of success in the limit where the number of devices to be checked is large. In the case where the faulty device performs a known unitary operation, we show that the use of entangled probes provides an improvement that even allows perfect identification for values of the unitary parameter that surpass a certain threshold. Finally, if the faulty device implements a known qubit channel, we find that the optimal probability for detecting the position of rank-one and rank-two Pauli channels can be achieved by product state inputs and separable measurements for any size of network, whereas for rank-three and general amplitude damping channels, optimal identification requires entanglement with N qubit ancillas. Published by the American Physical Society 2024