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Purpose: The growing attention to green supply chain transparency prompts firms to disclose their environmental efforts and manage environmental issues along supply chains. Drawn upon diffusion theory, this study aims to investigate how customers' environmental efforts can be diffused to suppliers for similar actions, as well as how customers' (diffusors') characteristics and suppliers' (followers') capability in digital technology application moderate the relationship. Design/methodology/approach: This study collects secondary data of 1,514 unique customer-supplier dyad year observations of Chinese listed firms and their disclosed environmental efforts from 2009 to 2022. A fixed-effect regression model is used to test the hypotheses. Findings: This study reveals a positive association between customers' disclosed environmental efforts and those of their suppliers. Furthermore, the relationship is strengthened when customers are state-owned or when suppliers possess higher levels of digital technology application capability. These findings remain robust when alternative measures of variables are employed. Originality/value: This study contributes to the supply chain transparency literature by uncovering the diffusion mechanism of environmental efforts from customers to their suppliers. It further identifies moderators for this diffusion, including customers' (diffusors') ownership and suppliers' (followers') capability. Lastly, our study extends the applicability of diffusion theory within a buyer–supplier context. [ABSTRACT FROM AUTHOR]

Effects of relative motion between moving fuel and neutrons are usually not considered in the analysis of Circulating Fuel Reactors (CFRs). In this study, we formulate neutron transport equation for CFRs in a hydrodynamic representation in terms of velocities relative to moving fuel. Using the P1 approximation in the comoving transport equation, the diffusion equation for CFRs is obtained. Mass transport of precursors is considered in the formulations. Comoving frame CFRs equations are analytically solved for critical slab problem and a closed form criticality condition is obtained. Comoving representation has introduced corrections to Eulerian cross sections arising from the acceleration term. Hydrodynamics coupling has posed density modifications to cross sections. A parametric study of corrective terms is carried out to calculate effects of these corrections on a generic MSR and on Molten Salt Breeder Reactor (MSBR).

This compendium review focuses on the spatial distribution of sensitivity to localized absorption changes in optically diffuse media, particularly for measurements relevant to near-infrared spectroscopy. The three temporal domains, continuous wave, frequency domain, and time domain, each obtain different optical data types whose changes may be related to effective homogeneous changes in the absorption coefficient. Sensitivity is the relationship between a localized perturbation and the recovered effective homogeneous absorption change. Therefore, spatial sensitivity maps representing the perturbation location can be generated for the numerous optical data types in the three temporal domains. The review first presents a history of the past 30 years of work investigating this sensitivity in optically diffuse media. These works are experimental and theoretical, presenting one-, two-, and three-dimensional sensitivity maps for different Near-Infrared Spectroscopy methods, domains, and data types. Following this history, we present a compendium of sensitivity maps organized by temporal domain and then data type. This compendium provides a valuable tool to compare the spatial sensitivity of various measurement methods and parameters in one document. Methods for one to generate these maps are provided in Appendix A, including the code. This historical review and comprehensive sensitivity map compendium provides a single source researchers may use to visualize, investigate, compare, and generate sensitivity to localized absorption change maps. [ABSTRACT FROM AUTHOR]

Cemented soft rock is prone to softening when exposed to water, and its mechanical properties deteriorate rapidly, which is an important reason to induce the instability and failure of engineering soft rock mass. The softening mechanism of soft rock is essentially the deterioration of microstructure caused by the change of water-rock interface. Considering the general characteristics of soft rock, the microstructural evolution characteristics and element loss over varying immersion time are then compared and analyzed. The Interfacial Cemented Bonding (ICB) structure is proposed to describe the evolution of water-rock interface. Based on the diffusion theory, the theoretical equation describing the evolution of water-rock interface is derived and compared with the experimental results. The meso-softening damage factor (MSDF) of soft rock is proposed and introduced into a numerical method to establish a strength degradation discrete element method (SD-DEM) model. The results show that the softening process of soft rock is accompanied by the shedding and suspension of particles and the dissolution of soluble substances. Besides, the softening of soft rock has obvious nonlinear dynamic characteristics. The fitting degree between the theoretical values and the experimental results is relatively high, which verifies the reliability and rationality of the dissolution-diffusion interfacial softening model. The numerical results are in good agreement with the experimental ones. This study provides a new idea for understanding the mechanism of water-induced softening characteristics and strength degradation of soft rock.

This compendium review focuses on the spatial distribution of sensitivity to localized absorption changes in optically diffuse media, particularly for measurements relevant to near-infrared spectroscopy. The three temporal domains, continuous wave, frequency domain, and time domain, each obtain different optical data types whose changes may be related to effective homogeneous changes in the absorption coefficient. Sensitivity is the relationship between a localized perturbation and the recovered effective homogeneous absorption change. Therefore, spatial sensitivity maps representing the perturbation location can be generated for the numerous optical data types in the three temporal domains. The review first presents a history of the past 30 years of work investigating this sensitivity in optically diffuse media. These works are experimental and theoretical, presenting one-, two-, and three-dimensional sensitivity maps for different Near-Infrared Spectroscopy methods, domains, and data types. Following this history, we present a compendium of sensitivity maps organized by temporal domain and then data type. This compendium provides a valuable tool to compare the spatial sensitivity of various measurement methods and parameters in one document. Methods for one to generate these maps are provided in Appendix A, including the code. This historical review and comprehensive sensitivity map compendium provides a single source researchers may use to visualize, investigate, compare, and generate sensitivity to localized absorption change maps.

Aim/Purpose This paper aims to investigate and understand the intentions of management undergraduate students in Hangzhou, China, regarding the adoption of Artificial Intelligence (AI) technologies in their education. It addresses the need to explore the factors influencing AI adoption in the educational context and contribute to the ongoing discourse on technology integration in higher education. Background The paper addresses the problem by conducting a comprehensive investigation into the perceptions of management undergraduate students in Hangzhou, China, regarding the adoption of AI in education. The study explores various factors, including Perceived Relative Advantage and Trialability, to shed light on the nuanced dynamics influencing AI technology adoption in the context of higher education. Methodology The study employs a quantitative research approach, utilizing the Confirmatory Tetrad Analysis (CTA) and Partial Least Squares Structural Equation Modeling (PLS-SEM) methodologies. The research sample consists of management undergraduate students in Hangzhou, China, and the methods include data screening, principal component analysis, confirmatory tetrad analysis, and evaluation of the measurement and structural models. We used a random sampling method to distribute 420 online, self-administered questionnaires among management students aged 18 to 21 at universities in Hangzhou. Contribution This paper explores how management students in Hangzhou, China, perceive the adoption of AI in education. It identifies factors that influence AI adoption intention. Furthermore, the study emphasizes the complex nature of technology adoption in the changing educational technology landscape. It offers a thorough comprehension of this process while challenging and expanding the existing literature by revealing the insignificant impacts of certain factors. This highlights the need for an approach to AI integration in education that is context-specific and culturally sensitive. Findings The study highlights students' positive attitudes toward integrating AI in educational settings. Perceived relative advantage and trialability were found to impact AI adoption intention significantly. AI adoption is influenced by social and cultural contexts rather than factors like compatibility, complexity, and observability. Peer influence, instructor guidance, and the university environment were identified as pivotal in shaping students' attitudes toward AI technologies. Recommendations for Practitioners To promote the use of AI among management students in Hangzhou, practitioners should highlight the benefits and the ease of testing these technologies. It is essential to create communication strategies tailored to the student's needs, consider cultural differences, and utilize the influence of peers and instructors. Establishing a supportive environment within the university that encourages innovation through policies and regulations is vital. Additionally, it is recommended that students' attitudes towards AI be monitored constantly, and strategies adjusted accordingly to keep up with the changing technological landscape. Recommendations for Researchers Researchers should conduct cross-disciplinary and cross-cultural studies with qualitative and longitudinal research designs to understand factors affecting AI adoption in education. It is essential to investigate compatibility, complexity, observability, individual attitudes, prior experience, and the evolving role of peers and instructors. Impact on Society The study's insights into the positive attitudes of management students in Hangzhou, China, toward AI adoption in education have broader societal implications. It reflects a readiness for transformative educational experiences in a region known for technological advancements. However, the study also underscores the importance of cautious integration, considering associated risks like data privacy and biases to ensure equitable benefits and uphold educational values. Future Research Future research should delve into AI adoption in various academic disciplines and regions, employing longitudinal designs and qualitative methods to understand cultural influences and the roles of peers and instructors. Investigating moderating factors influencing specific factors' relationship with AI adoption intention is essential for a comprehensive understanding. [ABSTRACT FROM AUTHOR]

To address the ongoing supply-demand gap for permanent supportive housing (PSH), Moving On initiatives (MOIs) provide linkage to affordable housing without embedded support services and rental subsidies, as well as short-term transitional case management to support transitions to independent housing. PSH providers mediate outcomes for individuals moving on from PSH by providing appropriate supports and assistance. Yet, little is known about how providers view these moves. This study explores how providers perceive moves from PSH. Individual interviews were completed with PSH providers from seven U.S. agencies. Data was analyzed via a modified grounded theory approach. The data show that organizational support and prior experience with moving on shape providers’ perceptions of resident capacity. These perceptions were associated with gatekeeping and recovery-oriented approaches, which informed providers’ self-perceived role as following or leading residents towards moving on. System-level support and pressure to adopt a moving on mindset may lead more providers to promote independence and autonomy among individuals with histories of homelessness.

The study investigates the learning curve impact of International Financial Reporting Standards (IFRS) adoption on earnings quality. In other words, the study investigates how IFRS affects the quality of earnings over time. The study also examines the moderating role of firm size and IFRS specialists/experts on the issue. We use firm‐level data of Bombay Stock Exchange listed firms and analyze it through the "Difference in Difference" technique. We find that the association between IFRS and earnings quality changes favorably as the introduction grows longer. In particular, we find that earnings quality is lower during the initial years of IFRS adoption, however, it improves in the later years of adoption, consistent with the notion of diffusion and learning curve theory. Our subsequent tests suggest that small firms are taking more time to percolate through the IFRS system, however, it does not hold when small firms hire IFRS specialists/experts to migrate their older accounts to IFRS, consistent with the notion of resource dependency theory of innovation. Overall, IFRS is found to be a continuous improvement process in emerging nations whose benefit can be derived in the initial years by providing sufficient infrastructural and institutional support, particularly to small firms. Our findings are robust to the problem of endogeneity and offer real‐world ramifications for regulatory authorities, accounting‐standard setters, and investors. [ABSTRACT FROM AUTHOR]

The utilization rate of reclaimed asphalt pavement is significantly low in the sustainable design process of asphalt roads. Numerous researchers have extensively investigated the recycling and utilization of reclaimed asphalt pavements from various perspectives. Molecular dynamics simulations could elucidate the diffusion phenomenon occurring at the molecular scale between virgin and aged asphalt interfaces. This review provides a comprehensive summary of the simulation methods and applications of molecular dynamics simulation in the interface diffusion problem between virgin and aged asphalt. Diffusion theory and model testing methods are discussed. The review proposes the basic steps of molecular dynamics simulation and summarizes the molecular models with the corresponding parameter settings of virgin asphalt and aged asphalt. Moreover, the current influencing factors on the interfacial diffusion problem of virgin and aged asphalt are discussed. The paper explores the validation parameters including density, viscosity, radial distribution function (RDF), glass transition temperature, and solubility parameters based on the existing research. Molecular dynamics simulation could simulate interface diffusion at a micro-scale and clarify the diffusion depth and influence range of different asphalts. The purpose of the study of molecular dynamics is to solve interface issues and advance optimization of reclaimed materials. [ABSTRACT FROM AUTHOR]

According to the predictions outlined in global warming models, Iran, especially the plains of the central plateau, has been dealing with increasing temperatures and decreasing rainfall. These changes have had harmful effects on agricultural production and the overall sustainability of agriculture and the environment due to ongoing drought conditions. This study utilizes a model to estimate the risk of agricultural drought based on the principles of information diffusion theory. The goal is to assess the likelihood of agricultural drought occurring in the plains of Shazand, Khomein, and Saveh. By using agricultural data and meteorological information, three main aspects were taken into consideration: the susceptibility of environments prone to disasters, the ability to withstand risk, and the collective exposure to risk. To measure the risk of agricultural drought, three indicators were selected: the vulnerability of the area to drought, the percentage of abnormal rainfall, and the frequency of disaster occurrences. The results of the investigation revealed that the assessments of risk, when viewed from the perspective of disaster-prone environments, hazards, and the population exposed to risk, were significantly elevated. Concerning the susceptibility of disaster-prone environments, the examined plains show a concentrated range between severe and extremely severe sensitivities, with values ranging from 0.6 to 0.9. When considering the precariousness of the risk, these regions are facing a notably high level of vulnerability to drought. In evaluating the overall risk, the incidence of drought-related disasters in these areas exceeds 0.5 on the scale. Consequently, the associated probability of such risks materializing is estimated at intervals of approximately 4.8, 3.2, and 1.2 years for the Shazand, Khomein, and Saveh plains, respectively. [ABSTRACT FROM AUTHOR]

To address the ongoing supply-demand gap for permanent supportive housing (PSH), Moving On initiatives (MOIs) provide linkage to affordable housing without embedded support services and rental subsidies, as well as short-term transitional case management to support transitions to independent housing. PSH providers mediate outcomes for individuals moving on from PSH by providing appropriate supports and assistance. Yet, little is known about how providers view these moves. This study explores how providers perceive moves from PSH. Individual interviews were completed with PSH providers from seven U.S. agencies. Data was analyzed via a modified grounded theory approach. The data show that organizational support and prior experience with moving on shape providers’ perceptions of resident capacity. These perceptions were associated with gatekeeping and recovery-oriented approaches, which informed providers’ selfperceived role as following or leading residents towards moving on. Systemlevel support and pressure to adopt a moving on mindset may lead more providers to promote independence and autonomy among individuals with histories of homelessness. [ABSTRACT FROM AUTHOR]

The diffusion of liberal economic ideas has been challenged by three global shifts: a bipolar tilt, nationalism, and climate change. One consequence is that policy norms are originating from new places and carry new content. To date, diffusion theory in International Political Economy (IPE) explains how liberal policy norms spread through 'adaptation' to local circumstances, but less why they diffuse from particular origins. The three global shifts make a focus on origins critical. I propose integrating Comparative Political Economy (CPE) into diffusion theory to capture the forces and conditions shaping policy norm 'origination'. Analyzing the global proliferation of green finance policies, I show how China's closed capital account and state-controlled financial system combined with a state-led and experimentation-prone governance system creates a top-down market-steering approach that makes China a pioneer of policy instruments. Second, I show how the EU's global economic position, its independent central bank, and a negotiated and consultative governance system create a bottom-up market-facilitating approach that makes the EU a standard-setter of policy content. Adding origination creates a path forward for diffusion theory, exploring how certain political economy traits create roles in the diffusion process and how this impacts the diffusion mechanisms and adaptation processes emphasized today. [ABSTRACT FROM AUTHOR]

Shifting from a linear to a circular economy (CE) is a path promoted from different national and supranational organizations from many years but how that circularity is put in place by businesses from an empirical perspective is still a research gap in the literature. There is the need to stress the study of empirical cases to better understand what are the success factors, the sustainable challenges and the way forward to achieve the goal of a CE. This paper aims to investigate how the circular economy is spreading at the empirical level and with what evolution and opportunities. The framework of the diffusion theory is used to analyse how the CE, as a business model innovation, is widespread. The Italian scenario is taken as background, and 62 good practices of CE are analysed. The results promote a discussion on the attributes of CE, policy implications and future studies to booster the circular changing in society. [ABSTRACT FROM AUTHOR]

Abstract The adoption of a bioenergy crop is affected by various factors, including but not limited to the characteristics of farmers, farm economics, market forces, and physical environment. This study develops a spatially explicit agent‐based model for ascertaining the adoption rate of carinata (Brassica carinata) among the farmers in the Little River Experimental Watershed located in the southern state of Georgia in the United States. Each farmer's adoption behavior is modeled using the profitability difference between traditional crop rotations (with and without carinata at different contract prices), the adoption rate of neighboring farmers, and their land allocation decisions from managing a risky portfolio of enterprises. Carinata production in the winter season once every 3 years has no conflict with the most profitable and popular traditional row crop rotations, such as cotton‐cotton‐cotton and cotton‐cotton‐peanut, to a larger extent. The results show that 28% and 85% of farmers in the watershed will adopt carinata after 33 years at a contract price of $13/bushel (bu) under two different assumptions of low (2.5%) and high (5%) initial neighborhood adoption rates. The proportions of land allocated to carinata to the total farmland under field crops are 38% and 85% after 33 years under the same low and high neighborhood adoption rates, respectively. Our results suggest that fixing the appropriate contract price of carinata will bring additional profits to farmers without any significant foreseeable agronomic risks, thereby increasing the adoption rate of carinata at a regional level.

We empirically study the diffusion of value-based management (VBM) in small capital markets. Specifically, we analyse the factors that influence VBM adoption in Danish-listed firms. Based on a hand-collected data set covering 665 firm years from 2002 to 2010, we find that the same factors influence the diffusion of VBM in both large and small capital markets. Specifically, we find that large firms with a higher percentage of institutional ownership and with a CEO whose education is business-related are more likely to adopt VBM. Additionally, the control variables reveal a significant positive correlation between VBM adoption and leverage, capital intensity, liquidity, and the characteristics of top executives. Furthermore, we find that manufacturing and utility firms are more likely to adopt VBM than service or trade firms. Contrary to the mainstream opinion, we contribute to the literature that findings from large capital markets appear to be transferable to firms in small capital markets. [ABSTRACT FROM AUTHOR]

Previously applied to REA (Rod Ejection Accident) in several PWR-like cores, the minimalistic Nodal Drift Method (NDM) has recently been generalized to sNDM (super NDM). Both developed and validated on a heat-up transient of the KRUSTY experiment made of a few homogeneous parts, sNDM basically feeds the one-group diffusion approximation with so-called corrective Surface Factors (SF) for internodal currents from MCNP F1 tallies. In order to specify its practical usefulness for exploratory design studies, sNDM at its turn is put to the demanding test of REA in a PWR-like core. The chosen test case is a 600 MW th D 2 O/H 2 O-cooled thorium-fueled Spectral Shift Control Reactor (SSCR) core retrieved from previous studies, whose main results on conversion (by our MC-based tool SMURE) and safety (by NDM) are first summed up. Enhanced MCNP core models at HFP, CZP and HZP (respectively Hot Full, Cold Zero and Hot Zero Power) are detailed that have been specially adapted to a 2D radial-azimuthal mesh of few large nodes towards an even simpler REA calculation by sNDM. Other settings, necessary at BOT (Beginning Of Transient from HZP), include fuel and coolant thermal feedbacks as well as the global conductance of a lumped thermal model. Last but not least, the special cases of a few SF found variable between BOT and EOL (End Of Launch at t = 0.05 s) are addressed by an iterative transient calculation based on their linear interpolation. This method is proven effective at the cost of accepting an irreducible discrepancy for the radial exchange rate of the ejected node, provided that a proper so-called global way of computing all SF is used. Finally, main transient results are given until EOT equilibrium (End Of Transient at t = 300 s), with various sanity checks (including a partial safety one). • D 2 O/H 2 O-cooled SSCR has interesting conversion and safety performance with thorium. • Enhanced PWR-like core is designed at all BOC's states and studied over full cycle. • Main sNDM settings include initial Surface Factors (SF) and a lumped thermal model. • Transient calculation requires two steps for the update of a few SF changed by REA. • Transient results and basic thermal criteria allow to partially assess SSCR safety. [ABSTRACT FROM AUTHOR]

Featured Application: Quantitative and calibration free determination of the absolute optical properties of turbid samples in a standard cuvette with milliliter scale volume. Many applications seek to measure a sample's absorption coefficient spectrum to retrieve the chemical makeup. Many real-world samples are optically turbid, causing scattering confounds which many commercial spectrometers cannot address. Using diffusion theory and considering absorption and reduced scattering coefficients on the order of 0.01   mm − 1 and 1 mm − 1 , respectively, we develop a method which utilizes frequency-domain to measure absolute optical properties of turbid samples in a standard cuvette ( 45   mm × 10   mm × 10   mm ). Inspired by the self-calibrating method, which removes instrumental confounds, the method uses measurements of the diffuse complex transmittance at two sets of two different source-detector distances. We find: this works best for highly scattering samples (reduced scattering coefficient above 1 mm − 1 ); higher relative error in the absorption coefficient compared to the reduced scattering coefficient; accuracy is tied to knowledge of the sample's index of refraction. Noise simulations with 0.1 % amplitude and 0.1 ° = 1.7   m rad phase uncertainty find errors in absorption and reduced scattering coefficients of 4% and 1%, respectively. We expect that higher error in the absorption coefficient can be alleviated with highly scattering samples and that boundary condition confounds may be suppressed by designing a cuvette with high index of refraction. Further work will investigate implementation and reproducibility. [ABSTRACT FROM AUTHOR]

Artificial intelligence applications (AIA) increase innovative interaction, allowing for a more interactive environment in governmental institutions. Artificial intelligence is user-friendly and embraces an effective number of features among the different services it offers. This study aims to investigate users' experiences with AIA for governmental purposes in the Gulf area. The conceptual model comprises the adoption properties (namely trialability, observability, compatibility, and complexity), relative advantage, ease of doing business, and technology export. The novelty of the paper lies in its conceptual model that correlates with both personal characteristics and technology-based features. The results show that the variables of diffusion theory have a positive impact on the two variables of ease of doing business and technology export. The practical implications of the current study are significant. We urge the concerned authorities in the governmental sector to understand the significance of each factor and encourage them to make plans, according to the order of significance of the factors. The managerial implications provide insights into the implementation of AIA in governmental systems to enhance the development of the services they offer and to facilitate their use by all users. [ABSTRACT FROM AUTHOR]

Locally adapted traits can exhibit a wide range of genetic architectures, from pronounced divergence at a few loci to small frequency divergence at many loci. The type of architecture that evolves depends strongly on the migration rate, as weakly selected loci experience swamping and do not make lasting contributions to divergence. Simulations from previous studies showed that even when mutations are strongly selected and should resist migration swamping, the architecture of adaptation can collapse and become transient at high mutation rates. Here, we use an analytical two-population model to study how this transition in genetic architecture depends upon population size, strength of selection, and parameters describing the mutation process. To do this, we develop a mathematical theory based on the diffusion approximation to predict the threshold mutation rate above which the transition occurs. We find that this performs well across a wide range of parameter space, based on comparisons with individual-based simulations. The threshold mutation rate depends most strongly on the average effect size of mutations, weakly on the strength of selection, and marginally on the population size. Across a wide range of the parameter space, we observe that the transition to a transient architecture occurs when the trait-wide mutation rate is 10-3-10-2, suggesting that this phenomenon is potentially relevant to complex traits with a large mutational target. On the other hand, based on the apparent stability of genetic architecture in many classic examples of local adaptation, our theory suggests that per-trait mutation rates are often relatively low., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The article presents the foundation of a novel methodology developed for the solution of the neutron transport equation, named the transport driven-diffusion approach, which can be considered as an evolution of the classic multiple collision method. The idea behind this method is based on the expansion of the full solution in terms of the contributions of the particles emitted by successive collisions plus a residual term, accounting for particles which have undergone more than a predefined number of collisions. In order to determine the contribution at each collision order, a transport equation with a source term is solved, while the estimation of the residue is based on a diffusion theory model. The physical rationale for the choice of the diffusion model for the residue is discussed and justified, as physics suggests that the diffusion assumptions become more applicable for the description of the particles having suffered a certain number of collisions rather than to the original transport problem. Some results are presented for a set of steady-state and time-dependent test cases. Their analysis shows the remarkable advantage of the method proposed in terms of accuracy and computational time, when compared to standard diffusion and multiple collision at the same order. [ABSTRACT FROM AUTHOR]

The adoption of a bioenergy crop is affected by various factors, including but not limited to the characteristics of farmers, farm economics, market forces, and physical environment. This study develops a spatially explicit agent‐based model for ascertaining the adoption rate of carinata (Brassica carinata) among the farmers in the Little River Experimental Watershed located in the southern state of Georgia in the United States. Each farmer's adoption behavior is modeled using the profitability difference between traditional crop rotations (with and without carinata at different contract prices), the adoption rate of neighboring farmers, and their land allocation decisions from managing a risky portfolio of enterprises. Carinata production in the winter season once every 3 years has no conflict with the most profitable and popular traditional row crop rotations, such as cotton‐cotton‐cotton and cotton‐cotton‐peanut, to a larger extent. The results show that 28% and 85% of farmers in the watershed will adopt carinata after 33 years at a contract price of $13/bushel (bu) under two different assumptions of low (2.5%) and high (5%) initial neighborhood adoption rates. The proportions of land allocated to carinata to the total farmland under field crops are 38% and 85% after 33 years under the same low and high neighborhood adoption rates, respectively. Our results suggest that fixing the appropriate contract price of carinata will bring additional profits to farmers without any significant foreseeable agronomic risks, thereby increasing the adoption rate of carinata at a regional level. [ABSTRACT FROM AUTHOR]

The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24-1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.

Deploying a transnational approach, the article follows the explanatory framework of diffusion theories in aiming to provide a new perspective on the rise of national-populist actors across different sociopolitical and national-historical settings, in the context of ever-increasing interdependence and transfers of ideas. Thus, it focuses on reconceiving national-populist units not as evolving detached from one another, but rather influencing and providing discursive frames for each other, even in the context of non-institutionalized, indirect connections. For demonstrating the theoretical claims about diffusing ideas and transnational modes of borrowing in the European context, the article discusses the evolution of national-populist discourses in post-communist Georgia through an example of the emergence and exclusionary agenda of a social movement, "Georgian March." Locating the case within diffusion models, the analysis scrutinizes discursive strategies and incorporation of "the West" in the movement's discourse over the process of its collective identity construction. Thus, the article focuses on mediated experiences as providing models for certain behaviors; new roles and uses of social media as direct political platforms and channels for diffusions and borrowings; the factor of mutual references as tools for self-legitimization and mutual identification; and the relevance of borrowings and emulation among national-populist actors. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of four key transnational factors (i.e., cultural, educational, legal and political factors) on the diffusion and early adoption of International Standards on Auditing (ISAs). Using data for 162 countries over 1995–2014 (i.e., 3240 observations) and drawing on distinctive insights from diffusion theory, we found that common law countries tend to adopt ISAs faster than civil law countries. Our findings also show that vigorous legal enforcement and shareholder protection regimes promote the early adoption of ISAs, whereas robust judicial efficiency systems constrain the early adoption of ISAs. In addition, our results show that higher literacy rates and educational attainment simulate the earlier diffusion of ISAs. We also find that higher levels of individualism and uncertainty avoidance, but low levels of power distance cultural values, boost the early adoption of ISAs. Finally, our results report that countries with strong political stability and control of corruption tend to adopt ISAs faster than those with solid government effectiveness. [ABSTRACT FROM AUTHOR]

Accurate simulation and calculation of the deposition of outgassing molecule can shorten the cycle and reduce the cost of vacuum tests on satellites. It also provides a reference for contamination protection design by systems engineers. In this study, the molecular outgassing, transport and deposition processes were simulated by diffusion theory, the angle coefficient method, and the first-order desorption equation, respectively. The simulation results were consistent with the test data trends, but deviated from the test values. Given the effect of initial molecular outgassing rate, diffusion coefficient and residence time on the deposition mass, it was surmised that considering the molecular species and the weight mass rate would improve the calculation result. These considerations indeed improved the numerical simulations of high-vacuum contamination.

The advent of accessible ancient DNA technology now allows the direct ascertainment of allele frequencies in ancestral populations, thereby enabling the use of allele frequency time series to detect and estimate natural selection. Such direct observations of allele frequency dynamics are expected to be more powerful than inferences made using patterns of linked neutral variation obtained from modern individuals. We developed a Bayesian method to make use of allele frequency time series data and infer the parameters of general diploid selection, along with allele age, in nonequilibrium populations. We introduce a novel path augmentation approach, in which we use Markov chain Monte Carlo to integrate over the space of allele frequency trajectories consistent with the observed data. Using simulations, we show that this approach has good power to estimate selection coefficients and allele age. Moreover, when applying our approach to data on horse coat color, we find that ignoring a relevant demographic history can significantly bias the results of inference. Our approach is made available in a C++ software package.

The victory of the Islamic Revolution of Iran has had widespread reflections in the region and in the world. Despite the fact that the greatest impact of the Islamic Revolution took place in the region and in Iran's neighbors, some evidence implying that the extent of the impact of the Iranian revolution on Central Asia countries has been limited. This research seeks to answer the question why the Islamic Revolution failed to have an outstanding effect on the region? The hypothesis of the research points to the existence of problems in the political structure of the Central Asian countries in accepting the revolution, as well as the problems inside Iran to export the revolution. For this purpose, causative method and diffusion theory have been used. The findings of the research show that Some problems in the Origin and destination of the diffusion, including the lack of proper attention of Iran to the region of Central Asia, the pragmatic approach of Iran's foreign policy, the existence of authoritarian governments in the above region, the existence of regional and transnational rivals and etc. have been the most important reasons for Iran's failure to export its revolution to the central Asian countries.

Many applications seek to measure a sample’s absorption coefficient spectrum to retrieve the chemical makeup. Many real-world samples are optically turbid, causing scattering confounds which many commercial spectrometers cannot address. Using diffusion theory and considering absorption and reduced scattering coefficients on the order of 0.01 mm−1 and 1mm−1, respectively, we develop a method which utilizes frequency-domain to measure absolute optical properties of turbid samples in a standard cuvette (45 mm×10 mm×10 mm). Inspired by the self-calibrating method, which removes instrumental confounds, the method uses measurements of the diffuse complex transmittance at two sets of two different source-detector distances. We find: this works best for highly scattering samples (reduced scattering coefficient above 1 mm−1); higher relative error in the absorption coefficient compared to the reduced scattering coefficient; accuracy is tied to knowledge of the sample’s index of refraction. Noise simulations with 0.1% amplitude and 0.1°=1.7 mrad phase uncertainty find errors in absorption and reduced scattering coefficients of 4% and 1%, respectively. We expect that higher error in the absorption coefficient can be alleviated with highly scattering samples and that boundary condition confounds may be suppressed by designing a cuvette with high index of refraction. Further work will investigate implementation and reproducibility.

We predict the magnitude and estimate the uncertainties of the spread, growth and maximum expected long-term infection rates that affect emergency policies and plans. For the COVID-19 and 1918 viral pandemics, large second or successive peaks, waves or plateaux of increased infections occur long after the initial rapid onset. The key question is what physical model can explain and predict their occurrence trends and timing? We establish the principal that the timing and magnitude of such increases can be based on the well-known physics of classical diffusion theory, so is fundamentally different from the commonly used multi-parameter epidemiological methods. This physical model illuminates our understanding of the societal viral progress, providing quantitative predictions, estimates and uncertainties supporting risk decision-making and resilient medical planning. We obtain an approximate relation for predicting the risk of the observed magnitudes, timing and uncertainties of second and more waves, as needed for proactive emergency pandemic planning, bed count and decision-making purposes. The dynamic results and characteristics are compared and fitted to data using just two physical parameters for a number of countries and regions, and the concept shown to apply for both entire national and local regional populations. The present analysis quantitatively shows how much the timing and magnitude are reduced by more learning and effective countermeasures. The medical system and health policy must recognize and pro-actively plan for such inexorable diffusive spread and large residual infection waves.

Accurately identifying the source of coalbed methane is of great practical significance in preventing gas concentration overruns and improving extraction efficiency. At present, it is widely believed that underground gas mainly comes from coal desorption, and the mechanism of gas flow inside the coal seam is explored in depth, while the gas released inside the rock is often neglected, and there is insufficient understanding of its internal transportation law. In this study, the density gradient theory (FGDGD) in the coal matrix was used as a guide to characterize the adsorption and transport properties of gases within the rock. The anthracite and mudstone from the same roadway in Yuxi mine were selected for the experiments, and coal rock samples with particle sizes of 0.425 mm–0.25 mm were ground. The adsorption constant test and adsorption process experiments were carried out under the constant volume condition, and the transport behavior of gas within the rock was simulated and numerically solved, and the content and flow behavior of gas in the rock were discussed in detail. The results are as follows: (i) The simulation curves based on the density gradient model fit well with the experimental data for both coal and rock downholes, indicating that the gas transport law inside the rock downhole is also in accordance with the density gradient theory, which broadens the scope of application of the theory. (ii) The free gas diffusion coefficients D ks (rock) are smaller than D ks (coal) for the gases in the rock matrix and coal matrix, which may be due to the difference in the pore structure of the rock matrix, resulting in lower adsorption sites than those of the coal. (iii) Although the gas content inside the rock is relatively low compared with that of coal, it is significant for reducing the prediction error of gas influx in engineering practice. Therefore, it is necessary to consider the storage of gas in rocks and its migration behavior when studying the sources of gas emissions in engineering fields. • Theoretical model of gas density gradient in roof mudstone matrix based on coal matrix. • Inversion of diffusion coefficient in roof mudstone based on empirical model. • In engineering practice, we cannot ignore the gas existing in the roof rock. [ABSTRACT FROM AUTHOR]

Online social movements have taken root and flourished in the last decade due to online communication networks attributed to Social media. In this paper, the mixed-method approach is utilized for qualitative and quantitative analysis to investigate the efficacy of social media in propounding the outcome of online social movements in India. Further, several factors which have a definite impact on the outcomes of such online social movements are highlighted. This study concludes that online social media campaigns can be viewed as an extension of 'social norms media campaigns'. Further, it establishes that the internet penetration in India coupled with 'online peer pressure' accompanying such movements has effectively aroused the consciousness of users towards such campaigns. It also highlights the alteration in the process of diffusion of ideas in society due to the advent of social media platforms. [ABSTRACT FROM AUTHOR]

The turnover of sex-determining loci has repeatedly occurred in a number of species, rather than having a diverged pair of sex chromosomes. We model the turnover process by considering a linked locus under sexually antagonistic selection. The entire process of a turnover may be divided into two phases, which are referred to as the stochastic and deterministic phases. The stochastic phase is when a new sex-determining allele just arises and is still rare and random genetic drift plays an important role. In the deterministic phase, the new allele further increases in frequency by positive selection. The theoretical results currently available are for the deterministic phase, which demonstrated that a turnover of a newly arisen sex-determining locus could benefit from selection at a linked locus under sexually antagonistic selection, by assuming that sexually antagonistic selection works in a form of balancing selection. In this work, we provide a comprehensive theoretical description of the entire process from the stochastic phase to the deterministic phase. In addition to balancing selection, we explore several other modes of selection on the linked locus. Our theory allows us make a quantitative argument on the rate of turnover and the effect of the mode of selection at the linked locus. We also performed simulations to explore the pattern of polymorphism around the new sex-determining locus. We find that the pattern of polymorphism is informative to infer how selection worked through the turnover process. [ABSTRACT FROM AUTHOR]

The unexpected long lifetime of nanobubble against the large Laplace pressure is one of the important issues in nanobubble research and a few models have been proposed to explain it. Most studies, however, have been focused on the observation of relatively large nanobubbles over 100 nm and are limited to the equilibrium state phenomena. The study on the sub-100 nm sized nanobubble is still lacking due to the limitation of imaging methods which overcomes the optical resolution limit. Here, we demonstrate the observation of growth dynamics of 10 nm nanobubbles confined in the graphene liquid cell using transmission electron microscopy (TEM). We modified the classical diffusion theory by considering the finite size of the confined system of graphene liquid cell (GLC), successfully describing the temporal growth of nanobubble. Our study shows that the growth of nanobubble is determined by the gas oversaturation, which is affected by the size of GLC. [ABSTRACT FROM AUTHOR]

Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic diffusion approximation, Monte Carlo simulations, and an algorithm we developed based on novel application of the diffusion dipole model (DDM). Phantoms simulated a range of breast-mimicking optical properties and contained channels filled with chromophore solutions (ink, hemoglobin, or copper sulfate) or connected to a previously developed blood flow circuit providing tunable oxygen saturation (SO2). The DDM algorithm achieved similar spectral recovery and SO2 measurement accuracy to Monte Carlo-based corrections with lower computational cost, potentially providing an accurate, real-time correction approach. Algorithms were sensitive to optical property uncertainty, but error was minimized by matching phantom albedo. The developed test methods may provide a foundation for standardized assessment of MPAI fluence correction algorithm performance.

This paper proposes a dynamic approach for inventory management, which can be used for a definitely non stationary demand whose rate evolves both in mean and in variance. Specifically, the stock consumption is modelled as a Markov process with a slow diffusion term and the Fokker Planck equation is used to derive the probability distribution of the stock consumption and that of the reorder time. The knowledge of these distributions makes it possible to manage the inventory in a dynamical way and to keep the safety stock to a minimum level. To test the model, some typical demand patterns are used: results demonstrate its ability to capture both the evolution of the mean and that of the variance of the demand. [ABSTRACT FROM AUTHOR]

Truth commissions (TCs) are increasingly common after conflict and authoritarian rule, yet we know little about the different ways they are being used. Despite recent efforts to bridge conceptual gaps and resolve disagreement over the universe of cases, TCs are notoriously undertheorised and proponents have yet to answer why their record is so inconsistent. Through developing a typological approach to TCs, the article lays the groundwork for exploring the forms they need to take to have an impact. It argues for a more nuanced understanding of the term that captures both the breadth of current practice and recasts conceptual debates on the spectrum of design options that are available to policymakers but are often overlooked. The findings are important as they offer a first set of impressions on emerging spatial and temporal patterns and trends that are developing due to the purported transnational diffusion and social learning of ideas about TCs. [ABSTRACT FROM AUTHOR]

• A novel method is proposed for solubility prediction. • An improved PSO algorithm based on the diffusion theory is proposed. • RBF ANN trained by improved APSO is proposed. • Proposed method has a broad application perspective. Solubility is as a key chemical and physical property. Solubility prediction methods are applied in diverse fields including preparation synthesis and modifications of materials. To overcome the shortcomings of existing solubility prediction methods, taking the mass transfer of two-phase system as an example, a solubility prediction model based on the diffusion theory and hybrid artificial intelligence method was proposed in this paper. An improved double-population chaotic accelerated particle swarm optimization (APSO) algorithm combined diffusion theory was developed according to the particle evolution utilizing diffusion energy. The developed algorithm was applied in the training of parameters of the radial basis function artificial neural network and then a model for predicting solubility was developed. The experimental results of supercritical carbon dioxide solubility in 8 polymers were consistent with the predicted values by the model, indicating the high prediction accuracy. The average relative deviation, squared correlation coefficient, and root mean square error were respectively 0.0036, 0.9970, and 0.0152, displaying its higher comprehensive performance. The model may also be applied in other physicochemical fields. [ABSTRACT FROM AUTHOR]

This study compares fertility-related behaviour in the adjacent regions of West Bengal (a state in eastern India) and Bangladesh. The starting premise of the paper is that common history and language has led to diffusion of fertility practices from West Bengal to Bangladesh. This is hypothesised to create a homogenous pattern of fertility behaviour in the bordering districts of both political regions. The study uses Demographic Health Survey (DHS) and District level Household Survey data for 1992, 2002, and 2012. Despite some reservations – as DHS is directed to produce state-level estimates, while DLHS is geared to yield district-level estimates – the similarity in sampling strategies and coverage of all districts (in West Bengal) and divisions (in Bangladesh) implies that the two data sets may be pooled, particularly in the absence of any alternatives. We tested whether fertility behaviour in (i) bordering districts differs from non-border districts in both countries, and (ii) bordering districts of both countries are similar using multi-level linear and logistic models. Outcome variables are contraceptive prevalence rate, and number of ever born children. The results reveal similarities in fertility behaviour between border divisions of Bangladesh and West Bengal, indicating possible cross-border diffusion of fertility practices. [ABSTRACT FROM AUTHOR]

In order to establish a kiln drying schedule for Iranian Beech (Fagus orientalis) lumbers of 5.5 cm thickness, commercially cut from Shast Kola region , 5 km distance from Gorgan. They were then dried under the program based on diffusion theory (from Malmquist's relations) were adopted to dry the lumbers to the final moisture content of 12±2 %. This program for three separate kiln charges and initial moisture content 66.6, 58 and 45 percent was developed. Initial drying bulb temperature (first step) 46 °C and wet-bulb temperature 45 °C was calculated and in three schedules were same. The severity of surface, end checks and warp (bowing, crooking, twisting) in the lumbers were measured before and after the drying process and quality control methods were used to analyze the wood defects. Results indicated that drying of beech lumber using this new schedule was satisfactory. Also intensity changes of defect in all three repeats were about acceptable quality and quantity. Superior characteristics of this program was no surface checks in samples because the moisture content was reduced slowly.