Empirical Measures Research Articles

Larval dispersal predictions are highly sensitive to hydrodynamic modelling choices

AbstractLarval dispersal is a critical ecological process in marine ecosystems, responsible for connecting and replenishing populations in patchy habitat. Because empirical measurements of larval dispersal are very challenging, coupled biological and oceanographic simulations (“biophysical models”) of larval dispersal are commonly used to answer ecological questions and support conservation management decisions. In the process of creating biophysical models, a series of choices must be made that do not have a single correct answer—sometimes because the oceanographic or ecological processes are uncertain; sometimes because trade-offs are required between different goals (e.g. computational time versus spatial resolution). In this paper, we demonstrate that larval dispersal estimates at management scales are strongly affected by these choices. Using three different hydrodynamic models of the Great Barrier Reef, we estimated the dispersal of crown-of-thorns starfish larvae in the spawning seasons between 2018 and 2021. Despite sharing similar physical forcings and using similar models of larval behaviour, we find that the different hydrodynamic models produce divergent predictions of larval dispersal between the reefs. If used to support crown-of-thorns starfish control decisions, these different predictions would recommend different priority reefs. Our results caution against the use of single models of larval dispersal, and suggest that multi-model ensembles may offer a valuable new perspective on dispersal patterns in marine environments.

Exploring prosocial behaviors in times of a pandemic: Individuals’ lay perspective versus scientific measurements

AbstractHumanitarian crises like the Covid‐19 pandemic pose significant challenges to society, prompting scientific debate on whether such situations elicit more prosocial or more selfish behavior. Despite the restrictions imposed by the pandemic, current evidence indicates a continued display of various prosocial behaviors. This research aims to enhance the understanding of what constitutes prosocial behavior from both individuals’ lay and scientific perspectives. For this purpose, we analyzed lay perspectives via an open question in a representative survey (N = 446) and qualitatively categorized the reported prosocial behaviors inductively with content analysis. The qualitative content analysis revealed three clusters of prosocial behaviors: promoting the welfare of others, health‐protective measures, and supporting society. Additionally, we conducted a systematic literature review to identify the scientific perspective view (i.e., focusing on the empirical measurements) on prosocial behaviors studied during the pandemic. Although behaviors promoting the welfare of others (e.g., donations) were the most commonly studied in the literature review, participants reported more health‐protective behavior, such as hand‐washing, which was not traditionally considered to be prosocial before the pandemic. The comparison between individuals’ lay and scientific perspectives highlighted some prosocial behaviors that warrant future investigation (e.g., supporting the economy, home office).

Study on Shape Optimization of Air-Supported Membrane Gymnasiums in Cold Regions Based on Indoor Daylight Simulation

ABSTRACT Air-supported membrane gymnasiums are gaining popularity in cold regions due to their rapid construction, low energy consumption, and cost-effectiveness. However, their natural translucency leads to excessive indoor daylight and discomfort, posing challenges compared to traditional structures. This study investigates the indoor daylight performance of air-supported membrane gymnasiums in cold regions. Through computer simulation, key daylight indicators were identified, a typical model was developed, and its accuracy was verified through empirical measurements. Based on these findings, shape optimization suggestions are proposed to enhance indoor daylight quality, promoting a healthier sports environment. The insights from this study are expected to inform future design practices for similar facilities.

Trade liberalization and export performance in China: Export-margin approach with firm-level data in 1995–2019

A key challenge facing developing countries is how to promote export performance through trade liberalization (TL). Using large and highly disaggregate firm-level data with 6-digit HS categories for 1995–2019, we investigate the issue for China based on the recent literature of export margins (XM). Export growth is decomposed into extensive and intensive margins (EM and IM), and IM further into price and quantity margins (PM and QM). We develop three empirical hypotheses based on a theoretical model that includes external economies of scale (EES) and industrial agglomeration (IA) as well as TL-XM links. Then we take China's entry to World Trade Organization (WTO) in 2001 as a quasi-natural experiment in difference-in-difference (DID) regressions. The estimate results suggest that TL increases both EM and IM (and QM) but reduces PM after China's entry to TWO in 2001. The finding is robust to various specifications of the empirical model and measurements of the variables. The further estimations show significantly positive effects of EES, IA, and their interactive terms with TL on EM, IM, and QM. The positive effects are larger for medium-tech industries than low-tech and high-tech industries.

A new method for conductivity prediction in polymer carbon nanofiber system by the interphase size and total conductivity of constituents

Current modeling approaches for the conductivity of polymer composites containing carbon nanofiber (CNF) called as PCNFs exhibit limitations. Herein, we introduce an enhanced Ouali model to accurately forecast the PCNF conductivity by incorporating the operative CNF amount and the conductivity contributions of CNFs, interphase region, and tunneling zones. The effective CNF volume fraction is derived from the dimensions of both CNFs and interphase, while the overall conductivity calculation integrates the resistances of interphase region and tunnels. The model's accuracy is validated through empirical conductivity measurements of various PCNF samples and extensive parametric analyses. An interphase depth (t) of less than 8 nm renders the composite insulative, whereas peak conductivity of 0.04 S/m is achieved at an interphase depth of 40 nm and interphase conductivity of 400 S/m. These results underscore the significant influence of interphase depth and conductivity on the overall electrical performance of the composites. Furthermore, a CNF length (l) below 13 μm or a contact diameter (d) under 10 nm also results in an insulative composite. Conversely, maximum values of CNF length (80 μm) and contact diameter (40 nm) enhance the composite's conductivity to 0.1 S/m. These findings illustrate the advantageous impact of longer nanofibers and wider tunnels on the electrical conductivity of PCNFs.

Big Data in Leadership Studies: Automated Machine Learning Model to Predict Preferred Leader Behavior Across Cultures

With global leadership as the new norm, discussion about followers’ preferred leader behaviors across cultures is growing in significance. This study proposes a comprehensive predictive model to explore significant preferred leadership factors, drawn from the Leader Behavior Description Questionnaire (LBDQXII), across cultures using automated machine learning (AML). We offer a robust empirical measurement of culturally contingent leader behavior and entrepreneurship behaviors and provide a tool for assessing the cultural predictors of preferred leader behavior to minimize predictive errors, explore patterns in the data and make predictions in an empirically robust way. Hence, our approach fills a gap in the literature relating to applications of AML in leadership studies and contributes a novel empirical method to better predict leadership preferences. Cultural indicators from Global Leadership and Organizational Behavior (GLOBE) predict the likelihood of the preferred leader behaviors of “Role Assumption”, “Production Emphasis” and “Initiation of Structure”. Hofstede’s Long-Term/Short-Term Orientation is the most critical predictor of preferences for “Tolerance of Uncertainty” and “Initiation of Structure”, whereas the value of restraint impacts the likelihood of preferring leaders with skills in “Integration” and “Consideration”. Significant entrepreneurial values indicators have a significant impact on preferences for leaders focused on “Initiation of Structure”, “Production Emphasis” and “Predictive Accuracy”. Findings also support earlier studies that reveal age and gender significantly impact our preferences for specific leader behaviors. We discuss and offer conclusions to support our findings that foster development of global business managers and practitioners.

Social protection for inclusive growth: a tale of two countries Pakistan and Bangladesh

PurposeThis paper examines and compares the role of social protection to promote inclusive growth in two countries (once related), Pakistan and Bangladesh, from 1984 to 2020, using annual time series data.Design/methodology/approachThe study used principal component analysis to develop the index of social protection, inclusive growth and macroeconomic stability. It also employed co-integration with impulse response function and fully modified ordinary least squares test for long-run cointegration.FindingsThe key results highlighted that social protection positively promotes inclusive growth in both countries. However, Bangladesh attains a high position in achieving inclusive growth through the mechanism of welfare programs. Findings show that institutional quality, macroeconomic stability and globalization are the positive and significant drivers of inclusive growth in both countries. It also confirms that macroeconomic stability and globalization are contributing more to achieving inclusive growth in Bangladesh as compared to Pakistan.Practical implicationsInstitutions and macroeconomic stability in both countries are critical toward providing a transparent system of welfare schemes to achieve inclusive growth. Shocks to social protection schemes in Pakistan are inconsistent for achieving inclusive growth as compared to Bangladesh.Originality/valueThe study extends the empirical measurement of social protection and inclusive growth while using protracted dimensions and indicators. It further examines and compares the dynamics of social protection programs for inclusive growth in two countries once related. For further originality and reliability, this study checks the robustness of long-run estimates by disaggregating the institutional quality and globalization into their key dimensions.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0548

Measuring characteristics of wild and cultivated food environments: a scoping review

BackgroundGlobal food systems are essential to sustain life; however, unhealthy diets are the leading cause of poor health and death worldwide. Natural food environments are a critical source of healthful food such as fresh fruit and vegetables, lean meat and aquatic foods, particularly in low- and middle-income countries (LMICs) and Indigenous food systems. Understanding and monitoring natural food environments is critical to protecting the supply of healthy food, and the land and water it comes from, for current and future generations.MethodsA scoping review was applied to classify and summarise empirical methods and measures used for characterising natural food environments. The ways in which food environment characteristics are conceptualised and measured for natural (wild and cultivated) food environments were explored. Data were extracted from the included studies using the following fields: study country, aim/objective(s), type of natural food environment (wild vs. cultivated), method or measure used to measure the food environment, key food environment characteristic/s (up to four) measured and key findings in relation to the food environment measurement.ResultsOne hundred forty seven studies were found to be relevant in this review. Most studies investigated food environments in LMICs, with almost two-thirds of all studies focussing on middle-income countries (n = 89, 61%). There was a strong focus on food security and home-based agriculture from studies that measured the cultivated food environment in LMICs, while the majority of studies on the cultivated food environment from high-income countries focussed on urban and community gardening. In addition to the most common survey-based methodological approaches, our review yielded a broad range of both qualitative and quantitative methods for measuring natural food environments, such as geospatial analysis; biochemical analysis of food, soil and water; citizen science; photovoice and food availability calendars.ConclusionsOur review demonstrated that the concept and characteristics of the food environment are a promising conceptualization for measuring natural food environments, particularly in relation to food availability, healthiness and food security. Mapping the currently used methods and measures to assess natural food environments is important to help identify critical leverage points for strengthening policy interventions, and monitoring and evaluation of progress.

Quantifying uncertainty in the contribution of mesopelagic fishes to the biological carbon pump in the Northeast Atlantic Ocean

Abstract Mesopelagic fishes may contribute substantially to marine carbon export and sequestration. However, uncertainty in this contribution due to limited precision of mesopelagic biomass and bioenergetic rate estimates has not been thoroughly quantified for any study site. Datasets that can confront these challenges are rare, particularly for comparing fish-mediated carbon flux to other biological carbon pump pathways. Using data from a unique three-ship expedition in spring 2021 in the subarctic Northeast Atlantic Ocean, we compare carbon transported by adult fish, zooplankton, and sinking particles, and calculate uncertainty in the relative contribution of fishes. Results indicate biomass- and bioenergetic-based uncertainty contributed roughly equally to variance in estimated carbon transport. The plausible range of mesopelagic fish carbon flux spans an order of magnitude: 1.6–21 mg C m−2 d−1 to 200 m depth and 0.52–9.6 mg C m−2 d−1 to 500 m. Fishes contributed ∼0.52%–18% at 200 m to the total biological carbon pump, and ∼0.43%–13% at 500 m. Of the fish-mediated carbon transport to 200 m, ∼8%–30% is sequestered on climate-relevant time scales (>100 years). This reinforces that carbon transport should not be conflated with carbon sequestration. These findings have implications for prioritizing future empirical measurements, evaluating trade-offs in fisheries management, and understanding the role of fishes in the biological carbon pump.

Quantifying and reducing the cost of tagging: combining computational fluid dynamics and diving experiments to reduce impact from animal-borne tags.

Animal-borne instruments are essential research tools for ecologists and physiologists. An increasing number of studies have shown impacts of carrying a tag on behaviour and energetics, which can have implications for animal welfare and data validity. Such impacts are a result of the additional mass and/or drag loads, with the latter requiring empirical measurements or computational fluid dynamics (CFD) to estimate. To quantify and effectively minimize tag impacts from drag, a novel combined empirical and CFD approach is required. Here, we demonstrate such an approach using captive phocid seals and the widely used Sea Mammal Research Unit (SMRU) Instrumentation Group GPS/GSM tag. We (i) show a significant change in the behaviour of grey seals when carrying a tag (gen 1; associated with 16.4% additional drag); (ii) redesigned the tag (gen 2) resulting in a lower additional drag of 8.6%; (iii) show significant differences in behaviour when carrying a gen 2 compared to gen 1 tag, demonstrating that the redesign successfully reduced impact; and (iv) observed changes in the swim speed of seals that were consistent with predictions from CFD estimates of drag. The gen 2 instrument is now commercially available. This non-trivial case study should pave the way for similar studies in other taxa and species.

Beyond the Event Window: Earnings Horizon and the Informativeness of Earnings Announcements

ABSTRACT The impact of earnings announcements (EAs) on investor uncertainty depends not only on how much new information they contain but also on how long it would take comparable information to arrive in the future through alternative sources, which I term “earnings horizon.” Using a structural model of periodic EAs, I show that earnings horizon is not captured by standard empirical measures of earnings informativeness or timeliness based on the event-study approach. However, earnings horizon can be estimated using patterns in return volatility over firms’ reporting cycles, which indicate that EAs have a short horizon and thus reduce investor uncertainty by one-third the amount suggested by event studies. Moreover, these patterns indicate that it takes investors considerably longer than the three- to five-day windows commonly applied in event studies to fully process EAs and that more frequent financial reporting may significantly enhance EAs’ informativeness. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: C58; D82; D84; G10; G12; G14; G30.

Bounding Seed Loss from Isolated Habitat Patches

Dispersal of propagules (seeds, spores) from a geographically isolated habitat into an uninhabitable matrix can play a decisive role in driving population dynamics. ODE and integrodifference models of these dynamics commonly feature a “dispersal success” parameter representing the average proportion of dispersing propagules that remain in viable habitat. While dispersal success can be estimated by empirical measurements or by integration of dispersal kernels, one may lack resources for fieldwork or details on dispersal kernels for numerical computation. Here we derive simple upper bounds on the proportion of propagule loss—the complement of dispersal success—that require only habitat area, habitat perimeter, and the mean dispersal distance of a propagule. Using vector calculus in a probabilistic framework, we rigorously prove bounds for the cases of both symmetric and asymmetric dispersal. We compare the bounds to simulations of integral models for the population of Asclepias syriaca (common milkweed) at McKnight Prairie—a 14 hectare reserve surrounded by agricultural fields in Goodhue County, Minnesota—and identify conditions under which the bounds closely estimate propagule loss.

The Sonora Substellar Atmosphere Models. III. Diamondback: Atmospheric Properties, Spectra, and Evolution for Warm Cloudy Substellar Objects

We present a new grid of cloudy atmosphere and evolution models for substellar objects. These models include the effect of refractory cloud species, including silicate clouds, on the spectra and evolution. We include effective temperatures from 900 to 2400 K and surface gravities from log g = 3.5 to 5.5, appropriate for a broad range of objects with masses between 1 and 84 M J. Model pressure–temperature structures are calculated assuming radiative–convective and chemical equilibrium. We consider the effect of both clouds and metallicity on the atmospheric structure, resulting spectra, and thermal evolution of substellar worlds. We parameterize clouds using the A. S. Ackerman & M. S. Marley cloud model, including cloud parameter f sed values from 1 to 8; we include three metallicities (−0.5, 0.0, and +0.5). Refractory clouds and metallicity both alter the evolution of substellar objects, changing the inferred temperature at a given age by up to 100–200 K. For solar-metallicity evolution models including clouds in warm objects, we find a hydrogen-burning minimum mass of 70.2 M J, close to empirical measurements; we find a deuterium-burning minimum mass of 12.05 M J (50% of initial D burned). We compare to the observed photometry of brown dwarfs, finding broad agreement with the measured photometry. We publish the spectra, evolution, and other data products online with open access on Zenodo (doi:10.5281/zenodo.12735103).

The power of play: uncovering the hidden impact of sport events on communities

ABSTRACT Sport tourism, despite being recognized as an effective activity for facilitating recovery from the COVID-19 pandemic, primarily emphasizes benefits related to economic aspects based on current research findings. However, the impacts of sports events extend beyond financial benefits, to various community benefits such as building community cohesion, fostering civic pride, and promoting progressive values. The perceptions of residents within hosting communities also significantly impact the success of these events, yet there are limited empirical studies. To address this research gap, this study aims to investigate the socio-psychological impacts of sports event hosting to address this gap. By introducing a theoretical framework and validating it empirically using 589 responses from a survey conducted among residents in the City of London, Canada, this study sheds light on the indirect relationship between psychic income and quality of life through an SEM analysis. Additionally, psychic income was found to have a significant influence on active support, indicating that residents who possess a strong emotional connection to the sports event are more likely to offer robust support. Ultimately, this study supports managers in the sport-hosting communities to obtain better resources and provide empirical measurements for the social impacts of the sport hosting, guiding hosts to engage fully with their communities.

The Role of Hydrogen in ReRAM.

Previous research on transistor gate oxides reveals a clear link between hydrogen content and oxide breakdown. This has implications for redox-based resistive random access memory (ReRAM) devices, which exploit soft, reversible, dielectric breakdown, as hydrogen is often not considered in modeling or measured experimentally. Here quantitative measurements, corroborated across multiple techniques are reported, that reveal ReRAM devices, whether manufactured in a university setting or research foundry, contain concentrations of hydrogen at levels likely to impact resistance switching behavior. To the knowledge this is the first empirical measurement depth profiling hydrogen concentration through a ReRAM device. Applying a recently-developed Secondary Ion Mass Spectrometry analysis technique enables to measure hydrogen diffusion across the interfaces of SiOx ReRAM devices as a result of operation. These techniques can be applied to a broad range of devices to further understand ReRAM operation. Careful control of temperatures, precursors, and exposure to ambient during fabrication should limit hydrogen concentration. Additionally, using thin oxynitride or TiO2 capping layers should prevent diffusion of hydrogen and other contaminants into devices during operation. Applying these principles to ReRAM devices will enable considerable, informed, improvements in performance.

Dyslexic Learners Appropriated in the South African Schooling Environment: A Legal and Philosophical Analysis

Learning is more difficult for students with dyslexia, a learning disability that affects 10% of the population. South African dyslexic students face various challenges, including inadequate help and limited access to assistive technology. Their challenges highlight the key laws and regulations protecting dyslexic learners. The goal of laws and regulations is to ensure that these learners receive the necessary accommodations and support. This article addresses these concerns by offering solutions and outlining helpful tools. It has been proven that these tools help dyslexic learners enhance their reading and writing skills and promote their independence. Creating an inclusive learning environment is crucial for fostering positive attitudes toward dyslexia. Increased awareness of this learning problem is needed among educators, parents, and policymakers. This theoretical study was based on the theory of successful intelligence, which made it possible to investigate how students characterise their mastery of the process of becoming teachers and immersing themselves in a curriculum that promotes inclusivity with a psychological-spectrum disease such as dyslexia. The study emphasizes the significance of multi-stakeholder collaboration in improving educational practices for dyslexic learners, despite its theoretical limitations that prevent empirical measurement of tools' impact on learning. This way, dyslexic learners can receive the necessary help and adaptations to succeed.

A Novel Wearable Sensor for Measuring Respiration Continuously and in Real Time.

In this work, a flexible textile-based capacitive respiratory sensor, based on a capacitive sensor structure, that does not require direct skin contact is designed, optimised, and evaluated using both computational modelling and empirical measurements. In the computational study, the geometry of the sensor was examined. This analysis involved observing the capacitance and frequency variations using a cylindrical model that mimicked the human body. Four designs were selected which were then manufactured by screen printing multiple functional layers on top of a polyester/cotton fabric. The printed sensors were characterised to detect the performance against phantoms and impacts from artefacts, normally present whilst wearing the device. A sensor that has an electrode ratio of 1:3:1 (sensor, reflector, and ground) was shown to be the most sensitive design, as it exhibits the highest sensitivity of 6.2% frequency change when exposed to phantoms. To ensure the replicability of the sensors, several batches of identical sensors were developed and tested using the same physical parameters, which resulted in the same percentage frequency change. The sensor was further tested on volunteers, showing that the sensor measures respiration with 98.68% accuracy compared to manual breath counting.

Application of Experimental Studies of Humidity and Temperature in the Time Domain to Determine the Physical Characteristics of a Perlite Concrete Partition

These days, the use of natural materials is required for sustainable and consequently plus-, zero- and low-energy construction. One of the main objectives of this research was to demonstrate that pelite concrete block masonry can be a structural and thermal insulation material. In order to determine the actual thermal insulation parameters of the building partition, in situ experimental research was carried out in real conditions, taking into account the temperature distribution at different heights of the partition. Empirical measurements were made at five designated heights of the partition with temperature and humidity parameters varying over time. The described experiment was intended to verify the technical parameters of perlite concrete in terms of its thermal insulation properties as a construction material used for vertical partitions. It was shown on the basis of the results obtained that the masonry made of perlite concrete blocks with dimensions of 24 × 24.5 × 37.5 cm laid on the mounting foam can be treated as a building element that meets both the structural and thermal insulation requirements of vertical single-layer partitions. However, it is important for the material to work in a dry environment, since, as shown, a wet perlite block has twice the thermal conductivity coefficient. The results of the measurements were confirmed, for they were known from the physics of buildings, the general principles of the formation of heat and the moisture flow in the analysed masonry of a perlite block. Illustrating this regularity is shown from the course of temperature and moisture in the walls. The proposed new building material is an alternative to walls with a layer of thermal insulation made of materials such as polystyrene or wool and fits into the concept of sustainable construction, acting against climate change, reducing building operating costs, improving living and working conditions as well as fulfilling international obligations regarding environmental goals.

Forest Restoration Thinning Has Minimal Impacts on Surface Soil Carbon in a Second-Growth Temperate Rainforest

Forest restoration thinning may accelerate the development of structural complexity toward old-growth conditions faster than a natural forest, yet associated changes in forest carbon (C) are poorly understood. Old-growth forests are characterized by high levels of sequestered C in aboveground biomass and soil C pools, yet active management has well-recognized negative impacts on stored C. Effects of forest restoration thinning on forest C can be determined using longitudinal measurements and modeling based on stand conditions and tree growth. At Ellsworth Creek Preserve in Southwest Washington, forest restoration efforts in a second-growth temperate rainforest have been monitored using permanent plots since 2007. Here, we compare repeat measurements from 2020, modeled forest C, and measurements of O-horizon C pools from 2022 to determine C impacts of silvicultural treatments for old-growth restoration. We found good general agreement between empirical measurements and models of forest C using the Forest Vegetation Simulator (FVS). However, treatment alone was not a strong indicator for C conditions; rather, forest age and age–treatment interactions better predicted soil C responses to restoration treatments. These data may indicate that “light” forest restoration thinning can accelerate old-growth development with minimal effects on soil carbon—a win-win conservation strategy for old-growth forests and the climate.

The empirical measurement of competition and digitalization for the banking sector of Kyrgyzstan: Impacts of efficiency, profitability, and stability

This study investigates the competitive dynamics and digitalization within Kyrgyzstan's banking sector. The study analyzes the interplay between bank competition, digitalization, profitability, and stability using the two-step Generalized Method of Moments. Banking competition is assessed from 2012 to 2022 via the Lerner Index and the Boone Indicator. Furthermore, a novel method is employed to estimate the bank digitalization index based on the System Dynamics Approach. Findings indicate a competitive landscape marked by monopolistic competition, where digitalization enhances operational efficiency and competitive advantage. However, increased market power inversely affects digital adoption, suggesting monopolistic banks innovate less than their competitive peers. Further, the study highlights that intensified competition and digital adoption may encourage riskier bank behaviors, aligning with competition-fragility theory. Digitalization improves profitability, advocating for banks to adopt innovations to surpass competitors and improve financial performance. Policymakers are advised to foster a balanced competitive environment that encourages innovation without compromising bank stability.