Empirical Measures Research Articles

Modeling and Evaluation of a Rate-Based Transcutaneous Blood Gas Monitor.

Current methods for transcutaneous blood gas monitoring (TBM) - a common health monitoring method in neonatal care - comes with a suite of challenges like limited attachment opportunities, and risks of infections from burning and tearing of the skin, which limits its use. This study presents a novel system and method for rate-based transcutaneous CO2 measurements with a soft, unheated skin-interface that can address many of these problems. Additionally, a theoretical model for the gas transport from the blood to the system's sensor is derived. By simulating CO2 advection and diffusion through the cutaneous microvasculature and epidermis to the system's skin interface, the effect of a wide range of physiological properties on the measurement has been modeled. Following these simulations, a theoretical model for the relationship between the measured CO2 concentration and that in the blood was derived and compared to empirical data. Applying the model on measured blood gas levels, even when the theory was based solely on the simulations, produced blood CO2 concentrations within ∼35% of empirical measurements from a state-of-the-art device. Further calibration of the framework, also using the empirical data, yielded an output with a Pearson correlation of 0.84 between the two methods. Compared to the state-of-the-art device the proposed system measured the partial CO2 pressure in the blood with an average deviation of 0.04 kPa and 1.97σ of ±1.1 kPa. However, the model indicated that this performance could be hampered by different skin properties. Given its soft and gentle skin interface and lack of heating, the proposed system could significantly decrease health risks like, burns, tears, and pain, currently associated with TBM on premature neonates.

Large deviations for mean field model in Erdős–Rényi graph

In this paper, we study a particle systems (or interacting diffusions) on an Erdős–Rényi graph with the parameter pN∈(0,1] that behaves like a mean-field system up to large deviations. Our aim is to establish the large deviations for the empirical measure process of particle systems under the condition NpN4→∞ as N→∞, where N is the number of particles. The result is obtained by proving the exponential equivalence between our systems and general interacting systems without random graphs. The multilinear extensions of Grothendieck inequality play a crucial role in our proof.

Age Structure Eliminates the Impact of Coinfection on Epidemic Dynamics in a Freshwater Zooplankton System.

AbstractParasites often coinfect host populations and, by interacting within hosts, might change the trajectory of multiparasite epidemics. However, host-parasite interactions often change with host age, raising the possibility that within-host interactions between parasites might also change, influencing the spread of disease. We measured how heterospecific parasites interacted within zooplankton hosts and how host age changed these interactions. We then parameterized an epidemiological model to explore how age effects altered the impact of coinfection on epidemic dynamics. In our model, we found that in populations where epidemiologically relevant parameters did not change with age, the presence of a second parasite altered epidemic dynamics. In contrast, when parameters varied with host age (based on our empirical measures), there was no longer a difference in epidemic dynamics between singly infected and coinfected populations, indicating that variable age structure within a population eliminates the impact of coinfection on epidemic dynamics. Moreover, infection prevalence of both parasites was lower in populations where epidemiologically relevant parameters changed with age. Given that host population age structure changes over time and space, these results indicate that age effects are important for understanding epidemiological processes in coinfected systems and that studies focused on a single age group could yield inaccurate insights.

Reconsidering the Empirical Measurement of Trust towards Unknown Others

Trust towards unknown others is a fundamental issue in trust research. Actually, it can be said that this problematization is a generative source for the whole scientific framing of trust, regardless of its specific perspective, whether it is a psychological, situational, institutional or structural-cultural interpretation. This means that the notion of ‘generalized trust’ is definitely a core concept and a reference point for all research agendas in the field of trust studies. However, this status of the notion is heavily criticized both from a theoretical and empirical point of view. The current paper tries to contribute to these academic discourses by proposing an extended reading of the concept of trust towards unknown others. By doing this, the paper suggests that the focus cannot be only on the aspect of how one perceives others’ trustworthiness, which is measured by the so-called ‘standard trust variable’; it should also be considered how the given agent relates herself/himself to other people’s otherness. Therefore, the argument simply claims that trusting people in general means being open to others’ otherness. If this link cannot be explored, then trust in unknown others is constrained and limited. Using data obtained from the last two rounds of the European Social Survey, the paper presents a 31-country-based comparative statistical analysis realized on both macro- and micro-levels in order to find out whether the above-described theoretical linkage is verifiable or not.

VaR Estimation with Quantum Computing Noise Correction Using Neural Networks

In this paper, we present the development of a quantum computing method for calculating the value at risk (VaR) for a portfolio of assets managed by a finance institution. We extend the conventional Monte Carlo algorithm to calculate the VaR of an arbitrary number of assets by employing random variable algebra and Taylor series approximation. The resulting algorithm is suitable to be executed in real quantum computers. However, the noise affecting current quantum computers renders them almost useless for the task. We present a methodology to mitigate the noise impact by using neural networks to compensate for the noise effects. The system combines the output from a real quantum computer with the neural network processing. The feedback is used to fine tune the quantum circuits. The results show that this approach is useful for estimating the VaR in finance institutions, particularly when dealing with a large number of assets. We demonstrate the validity of the proposed method with up to 139 assets. The accuracy of the method is also proven. We achieved an error of less than 1% in the empirical measurements with respect to the parametric model.

Empirical measurements of ammonium excretion in kelp forest fishes: Effects of body size, taxonomy and trophic guild

Fishes and other consumers excrete metabolic waste products, including dissolved nutrients rich in nitrogen, which is an essential nutrient for primary production. Relatively little is known about the magnitude and variability of nutrients excreted by fishes in kelp forest ecosystems and whether consumer-derived nutrients are important for supporting kelp productivity. In this study, the supply of ammonium (NH4+) excreted by the dominant fishes (30 species representing ∼85% of total fish biomass) was investigated on nearshore rocky reefs in California. Using rapid field incubations, the amount of excreted dissolved ammonium was measured as a function of body size (n = 460 individuals) and predictive models were developed relating mass to excretion rates at the family-level. Mass-specific excretion rates ranged from 0.08 to 3.45 μmol·g−1·hr−1, and per capita ammonium excretion rates ranged from 5.9 to 2765 μmol·individual·hr−1. Ammonium excretion scaled with fish body mass to the ¾ power, as predicted by the metabolic theory of ecology; mass-specific excretion rates were higher in smaller fishes, but larger fishes contributed more ammonium per individual. When controlling for body size, ammonium excretion rates were greatest among surfperch (Embiotocidae), damselfish (Pomacentridae), and wrasses (Labridae), and the general trophic groups of planktivores and micro-carnivores. When body size differences were considered, the greatest mean excretion rates per individual were observed in larger-bodied species, such as California Sheephead (Semicossyphus pulcher) and Lingcod (Ophiodon elongatus). Empirical estimates of nutrient excretion by fishes, among the first measured in temperate kelp forests, were consistent with those in other aquatic systems. Ultimately, empirically derived excretion rates are the first step to quantifying the relative importance of consumers to nutrient cycling in kelp forest ecosystems.

Innovative Educational Technologies: European Experience and its Implementation in the Training of Specialists in the Context of War and Global Challenges of the 21st Century

The objective of this article is to dissect the European encounter with pioneering educational technologies in the face of the 21st century's global challenges. The methodologies employed encompass theoretical content analysis and empirical survey techniques. The outcomes underscore the core of the innovation concept in education, along with the theoretical underpinnings guiding the integration of innovations within European pedagogical frameworks. Drawing from empirical measurements, several assertions are substantiated. Notably, the significance of the learning environment emerges, alongside educators' general inclination toward embracing innovative educational approaches in contrast to traditional teaching methods. Worth highlighting is the European Union's provision of specialized programs aimed at honing proficiency in working with groundbreaking technologies via internships. In Germany, the "Promotion an Hochschulen in Deutschland" initiative is exclusively tailored to train research and instructional personnel for the country's higher education establishments. France's Sorbonne University offers dedicated courses to augment digital prowess. Correspondingly, in England, the Centre of Excellence for Teaching and Learning is dedicated to fostering the professional advancement of aspiring educators, guaranteeing their possession of pertinent proficiencies. These mobile internships for European educators have evolved into a standard practice for nurturing digital literacy. Participation in such endeavors is characteristic of contemporary European educational hubs, further propelling educators' preparedness and growth within the digital epoch. The conclusions underscore the assorted array of innovations employed by instructors, encompassing platforms, interactive whiteboards, mobile applications, and cloud services.

A 3D simulation framework with ray-tracing propagation for LoRaWAN communication

The adoption of Low-Power Wide-Area Networks (LP-WAN) for interconnecting remote wireless sensors has become a reality in smart scenarios, covering communications needs of large Internet of Things (IoT) deployments. The correct operation and expected performance of such network scenarios, which can range hundreds or thousands of nodes and tens of squared kilometres, should be assessed before carrying out the deployment to save installation and maintenance costs. Common network planning tools can help to roughly study potential coverage, but network simulation offers fine-grained information about network performance. Nevertheless, current simulation frameworks include limited propagation models based on statistical and empirical measurements that do not consider scenario particularities, such as terrain elevation, buildings or vegetation. This is critical in urban settings. In this line, this paper presents a simulation framework including a network simulator, a 3D engine and a ray-tracing tool, which models realistically the performance of Long-Range Wide-Area Network (LoRaWAN) communication technology. We have evaluated the performance of the solution taking as reference experimental campaigns in the city of Cartagena (Spain), comparing data obtained when simulating with the commonly employed propagation models such as Okumura–Hata or path loss. Results indicate that our framework, set-up with data from open geographical information systems, accurately fits experimental values, reporting improvements between 10% and 50% in the error committed when estimating signal strength in challenging urban streets with signal obstruction, as compared with the better performing classical model, Okumura–Hata.

Bridge-bearing disengagement identification based on flexibility matrix diagonal matrix change rate: an indoor physical simulation experiment

The disengagement of bridge bearings is a pervasive issue encountered in the realm of bridges, which can potentially lead to changes in operational circumstances, diminished longevity, and compromised traffic safety. The current methods employed for detecting such disconnections primarily rely on force sensors, cameras, and acceleration sensors. However, their practical implementation on-site and effectiveness in accurately identifying disengagement require enhancement. To address the challenges associated with the installation and layout of conventional contact sensors, as well as the potential introduction of additional mass, a sophisticated “bridge-bearing disconnection detection system” has been devised. This innovative system is based on laser Doppler vibrometer technology, which eliminates the need for physical contact. The feasibility of employing non-contact laser Doppler vibration measurement technology in the detection of bridge-bearing disconnection has been successfully verified within the framework of this study. Furthermore, a comprehensive analysis of the sensitivity of key dynamic parameters, specifically natural frequencies and vibration modes, to bridge-bearing disengagement has been conducted. The verification process included evaluating the identification effectiveness of regularized combined absolute changes in vibration modes and flexibility matrix diagonal matrix change rate (FDMCR) under diverse working conditions simulating complete disconnection. This assessment involved using both finite element analysis and empirical measurements. The findings unequivocally demonstrate that the disconnection of bridge bearings results in a reduction in the natural frequencies for each mode order, with an observed cumulative effect. In addition, it is noteworthy that the vibration mode indices typically exhibit greater sensitivity toward the disconnection of outer bearings. By contrast, FDMCR demonstrates commendable positioning capabilities and exceptional noise resistance in identifying bridge-bearing disengagement. The empirical insights gleaned from these research findings hold significant value in terms of on-site identification of bridge-bearing disengagement, ultimately contributing to the preservation of bridges’ long-term operational integrity.

Simulation modeling of Zoom traffic on a campus network: A case study

In this paper, we develop a synthetic workload model for the Zoom network application based on empirical Zoom traffic measurements from a campus network. We then use this model in a simulation study of Zoom network traffic at the campus scale. The simulation results show that hybrid learning places a substantial load on the campus network. Additional simulation experiments investigate the potential benefits of locally-hosted Zoom infrastructure, improved load balancing strategies for Zoom servers, and multicast delivery for Zoom network traffic. The simulation results show that the multicast approach offers the greatest potential benefit for improving Zoom performance on our campus network.

Assessing school ventilation strategies from the perspective of health, environment, and energy

The global COVID-19 pandemic has highlighted the importance of indoor air quality and ventilation to mitigate the spread of respiratory viral infections. Schools, in particular, represent a vulnerable environment with high occupancy rates, prolonged exposure times and often inadequately ventilated rooms. This paper evaluates the functionality of different natural and retrofitted mechanical ventilation strategies in this context. An experimental setup, combining empirical measurements with building performance simulation and analytical risk analysis was used to assess key performance characteristics, including the energetic performance, thermal comfort, indoor air quality and the airborne infection risk of SARS-CoV-2. The results of this study underscore the need for a holistic approach to ventilation design in schools, taking into consideration the balance between energy performance, carbon emissions, thermal comfort, indoor air quality and associated health factors. We demonstrate that the risk of one or more long-range airborne infections, with the SARS-CoV-2 Omicron variant, can be reduced by >50% through appropriate use of natural, mechanical or hybrid ventilation in a classroom setting. Analytical modelling demonstrates that this risk can be further reduced, by an order of magnitude, through the use of FFP2 masks.

On the weighting of homo economicus and homo virtus in human behaviour

In economic sciences, most analyses focus on the economic person construct. However, this that formalization does not capture the complex nature of human behaviour. This paper estimates the weight that economic and noneconomic dimensions of human behaviour have on wellbeing. A utility function is considered that models behaviour from a complex standpoint, where the motivations of the economic individual (homo economicus) are analysed in a broad perspective by integrating emotional wellbeing and human virtues into the model (homo virtus). Three empirical measures of wellbeing are used: The Well-Being Index developed by the Boston Consulting Group’s Sustainable Economic Development Assessment (2008–2018), the Index of Economic Well-Being from the Centre for the Study of Living Standards (1980–2014), and the Happiness Score from the World Happiness Report (2005–2018). Depending on data availability, the model is estimated globally for all countries, OECD countries, European countries, and developing countries using linear regression methods. The results indicate that, on average, the homo virtus dimension of behaviour has a weight of 11% in countries’ wellbeing functions, while the economic perspective has a weight of 89%. Additionally, the results show that richer countries value economic factors more than poorer countries. The analyses also show that the maximum level of emotional satisfaction is higher for European and OECD countries than for developing countries.

Understanding the release, migration, and risk of heavy metals in coal gangue: An approach by combining experimental and computational investigations

The lack of understanding on the environmental fate and implications of heavy metals in coal gangue (CG) has restrained its utilization. Conventional extraction methods provide empirical measures of heavy metal speciation, lacking a detailed description of bound strength, which limits long-term risk assessment. In this study, the releasing and migrating behavior of six heavy metals (Cd, As, Pb, Ni, Cu, and Cr) were investigated through an approach by combining experimental and computational investigations. The corresponding mechanisms and risks were understood and discussed on a molecular level. The results suggested that CG is primarily a natural kaolinite α-quartz and anatase mineral. The sequence extraction results showed that heavy metals in CG are mainly distributed in stable silicate and iron manganese oxide-bound states. The toxicity characteristic leaching procedure test advised Cu, Cr, Ni, and Pb had a high toxic level and thus required long-term monitoring and controlling. A quantum chemical calculation demonstrated that the heavy metals were more likely to be embedded in silicate minerals with high binding energy than those binding on the anatase surface. The findings of this research provide a promising approach to comprehensively evaluate the stability mechanism and potential long-term risks of heavy metals in solid waste.

Navigating the integration of biotic interactions in biogeography

AbstractBiotic interactions are widely recognised as the backbone of ecological communities, but how best to study them is a subject of intense debate, especially at macro‐ecological scales. While some researchers claim that biotic interactions need to be observed directly, others use proxies and statistical approaches to infer them. Despite this ambiguity, studying and predicting the influence of biotic interactions on biogeographic patterns is a thriving area of research with crucial implications for conservation. Three distinct approaches are currently being explored. The first approach involves empirical observation and measurement of biotic interactions' effects on species demography in laboratory or field settings. While these findings contribute to theory and to understanding species' demographies, they can be challenging to generalise on a larger scale. The second approach centers on inferring biotic associations from observed co‐occurrences in space and time. The goal is to distinguish the environmental and biotic effects on species distributions. The third approach constructs extensive potential interaction networks, known as metanetworks, by leveraging existing knowledge about species ecology and interactions. This approach analyses local realisations of these networks using occurrence data and allows understanding large distributions of multi‐taxa assemblages. In this piece, we appraise these three approaches, highlighting their respective strengths and limitations. Instead of seeing them as conflicting, we advocate for their integration to enhance our understanding and expand applications in the emerging field of interaction biogeography. This integration shows promise for ecosystem understanding and management in the Anthropocene era.

On eigenvalues of the Brownian sheet matrix

We derive a system of stochastic partial differential equations satisfied by the eigenvalues of the symmetric matrix whose entries are the Brownian sheets. We prove that the sequence Ld(s,t),(s,t)∈[0,S]×[0,T]d∈N of empirical spectral measures of the rescaled matrices is tight on C([0,S]×[0,T],P(R)) and hence is convergent as d goes to infinity by Wigner’s semicircle law. We also obtain PDEs which are satisfied by the high-dimensional limiting measure.

Incorporating Primer Amplification Efficiencies in Quantitative Reverse Transcription Polymerase Chain Reaction Experiments; Considerations for Differential Gene Expression Analyses in Zebrafish.

Quantitative reverse transcription polymerase chain reaction (RT-qPCR) is commonly used to measure the mRNA expression of target genes in zebrafish. Gene expression values from RT-qPCR are typically reported as relative fold-changes, and relative quantification of RT-qPCR data incorporates primer amplification efficiency values for each target gene. We describe the influence of the primer amplification efficiency analysis method on RT-qPCR gene expression fold-change calculations. This report describes (1) a sample analysis demonstrating incorporation of primer amplification efficiency into RT-qPCR analysis for comparing gene expression of a gene of interest between two groups when normalized to multiple reference genes, (2) the influence of differences in primer amplification efficiencies between measured genes on gene expression differences calculated from theoretical delta-Cq (dCq) values, and (3) an empirical comparison of the influence of three methods of defining primer amplification efficiency in gene expression analyses (delta-delta-Cq [ddCq], standard curve, LinRegPCR) using mRNA measurements of a set of genes in zebrafish embryonic development. Given the need to account for the influence of primer amplification efficiency along with the simplicity of using software programs (LinRegPCR) to measure primer amplification efficiency from RT-qPCR data, we encourage using empirical measurements of primer amplification efficiency for RT-qPCR analysis of differential gene expression in zebrafish.

A Working TTFields Therapy Framework for Patient-Specific Segmentation-Based Treatment Planning and Dosimetry

Previously reported data support the notion that patient-specific treatment planning in patients with newly diagnosed glioblastoma (GBM) could positively impact patient outcomes like overall survival and progression free survival and predictably affect imaging progression patterns (Ballo et al 2019; Glas et al 2021). These findings provide the grounds for a TTFields dosimetry and patient-specific segmentation-based treatment planning (SBTP) paradigm. This paradigm allows optimized delivery of TTFields to target regions of interest (ROIs) and ability to adjust the treatment during therapy. In this study, we describe a working framework for TTFields SBTP. The working framework consists of the following process: First, a patient's high-resolution imaging data (MRI with or without a CT) is imported from the institution's PACS. The image is segmented to identify tissue types using a combination of automatic and semi-automatic algorithms. During this stage, the user indicates the target ROI subject to optimization. Then, a computational model of the patient is created in which typical electrical properties are allocated to each tissue type based on empirical measurements and/or literature. At this point, the user can mark avoidance zones on the skin identifying areas where the transducer arrays (TAs) should not be placed. Next, dedicated algorithms identify optimal arrangements of TAs to produce several options of TA layouts. Further, quantitative and qualitative evaluation tools such as color maps, iso-surfaces, and dose volume histogram (DVH) curves, are applied to choose the layouts that achieve the optimal distribution of TTFields therapy for each patient. Finally, each patient receives two SBTP to allow switching between the layouts in order to mitigate the risk of skin irritation. Over 60 image sets from GBM patients were used to test the SBTP system. Our experience demonstrates a viable working framework that has the potential to boost TTFields delivery to target ROIs. This working framework offers qualitative and quantitative tools for SBTP and streamlines the process of personalized treatment, allowing physicians to optimize treatment with TTFields therapy. Additionally, this system provides tools for developing an adaptive patient-specific SBTP in response to any clinical need (e.g., disease progression).

Gaussian Fluctuations for Interacting Particle Systems with Singular Kernels

We consider the asymptotic behaviour of the fluctuations for the empirical measures of interacting particle systems with singular kernels. We prove that the sequence of fluctuation processes converges in distribution to a generalized Ornstein–Uhlenbeck process. Our result considerably extends classical results to singular kernels, including the Biot–Savart law. The result applies to the point vortex model approximating the 2D incompressible Navier–Stokes equation and the 2D Euler equation. We also obtain Gaussianity and optimal regularity of the limiting Ornstein–Uhlenbeck process. The method relies on the martingale approach and the Donsker–Varadhan variational formula, which transfers the uniform estimate to some exponential integrals. Estimation of those exponential integrals follows by cancellations and combinatorics techniques and is of the type of the large deviation principle.

The role and influencing factors of government performance evaluation: A test of Chinese public officials’ perceptions in Gaoming district

Government performance evaluation has a long history. However, major differences of opinion regarding its role still exist both in Western and Chinese academia, from theoretical, and practical perspectives. In this article, we conduct an empirical measurement of the role played by government performance evaluation and construct a regression model to explore the major factors influencing public officials’ perception, relying on survey data from a district government of county level in Guangdong Province. The study reveals that the average value of 14 items measuring government performance evaluation was 3.36 points (out of a possible 5 points). The role of the government in setting annual objectives, tasks, and priorities, as well as strategic planning, and target setting, and strengthening departmental accountability, had the most significant effect on the perception of efficacy of performance evaluation, whereas departmental budget setting, resource allocation, and reduction of operating costs had the least effect. Furthermore, performance communication and feedback, as well as the validity of the performance indicator system, also significantly influence the perception of the role played by government performance evaluation. The article concludes with a discussion of the differences between government performance evaluation in the West and in China.

A site amplification model for Switzerland based on site-condition indicators and incorporating local response as measured at seismic stations

AbstractThe spatial estimation of the soil response is one of the key ingredients for the modelling of earthquake risk. We present a ground motion amplification model for Switzerland, developed as part of a national-scale earthquake risk model. The amplification model is based on local estimates of soil response derived for about 240 instrumented sites in Switzerland using regional seismicity data by means of empirical spectral modelling techniques. These local measures are then correlated to continuous layers of topographic and geological soil condition indicators (multi-scale topographic slopes, a lithological classification of the soil, a national geological model of bedrock depth) and finally mapped at the national scale resorting to regression kriging as geostatistical interpolation technique. The obtained model includes amplification maps for PGV (peak ground velocity), PSA (pseudo-spectral acceleration) at periods of 1.0, 0.6 and 0.3 s; the modelled amplification represents the linear soil response, relative to a reference rock profile with VS30 (time-averaged shear-wave velocity in the uppermost 30 m of soil column) = 1105 m/s. Each of these amplification maps is accompanied by two layers quantifying its site-to-site and single-site, within event variabilities, respectively (epistemic and aleatory uncertainties). The PGV, PSA(1.0 s) and PSA(0.3 s) maps are additionally translated to macroseismic intensity aggravation layers. The national-scale amplification model is validated by comparing it with empirical measurements of soil response at stations not included in the calibration dataset, with existing city-scale amplification models and with macroseismic intensity observations from historical earthquakes. The model is also included in the Swiss ShakeMap workflow.