Scaling Approach Research Articles

Are agroecological cooperative supermarkets an alternative for scaling sustainable food?

The paper attempts to investigate the capacity of agroecological cooperative supermarkets in Spain to promote scaling of food products by means of a double perspective. We first employ a vertical scaling approach to analyze the issues affecting the governance and collective organization of the Cooperative Supermarket Network (CSN), set up in May 2022 and comprising eleven Spanish supermarkets. Secondly, we employ a perspective of horizontal scaling to investigate the potential for increased numbers of members, as well as the geographic and sociodemographic variables at play which limit the abovementioned scaling: to this end we use the case study of the cooperative supermarket La Osa, opened in Madrid in December 2020. We adopt a methodology based on participatory action research throughout the years 2022 and 2023, in which the research team was involved in the real processes of creation and development of the CSN or of La Osa. The study confirms the hypothesis that agroecological cooperative supermarkets constitute a formula for efficient retail distribution for scaling sustainable food in Spain. As opposed to the first-generation options for responsible consumption, these supermarkets appear to contribute to generating significant economies of scale and scope. In terms of vertical scaling, joint provision of services, as well as the gaining of political influence in society, constitute the main advantages in relation to the functioning of the CSN. While the recruitment of new members has heretofore been considered a priority in horizontal scaling, particular emphasis should also be placed on loyalty strategies targeting existing members.

Microplastic accumulation in groundwater: Data-scaled insights and future research

Given that microplastics (MPs) in groundwater have been concerned for risks to humans and ecosystems with increased publications, a Contrasting Analysis of Scales (CAS) approach is developed by this study to synthesize all existing data into a hierarchical understanding of MP accumulation in groundwater. Within the full data of 386 compiled samples, the median abundance of MPs in Open Groundwater (OG) and Closed Groundwater (CG) were 4.4 and 2.5 items/L respectively, with OG exhibiting a greater diversity of MP colors and larger particle sizes. The different pathways of MP entry (i.e., surface runoff and rock interstices) into OG and CG led to this difference. At the regional scale, median MP abundance in nature reserves and landfills were 17.5 and 13.4 items/L, respectively, all the sampling points showed high pollution load risk. MPs in agricultural areas exhibited a high coefficient of variation (716.7%), and a median abundance of 1.0 items/L. Anthropogenic activities at the regional scale are the drivers behind the differentiation in the morphological characteristics of MPs, where groundwater in residential areas with highly toxic polymers (e.g., polyvinylchloride) deserves prolonged attention. At the local scale, the transport of MPs is controlled by groundwater flow paths, with a higher abundance of MP particles downstream than upstream, and MPs with regular surfaces and lower resistance (e.g., pellets) are more likely to be transported over long distances. From the data-scaled insight this study provides on the accumulation of MPs, future research should be directed towards network-based observation for groundwater-rich regions covered with landfills, residences, and agricultural land.

Adsorption of Diffusing Tracers, Apparent Tortuosity, and Application to Mesoporous Silica.

The apparent tortuosity due to adsorption of diffusing tracers in a porous material is determined by a scaling approach and is used to analyze recent data on LiCl and alkane diffusion in mesoporous silica. The slope of the adsorption isotherm at small loadings is written as β = qA/qG, where qA is the adsorption-desorption ratio and qG = ϵ/(as) - 1 is a geometrical factor depending on the range a of the tracer-wall interaction, the porosity ϵ, and the specific surface area s. The adsorption leads to a decrease of effective diffusion coefficient, which is quantified by multiplying the geometrical tortuosity factor τgeom by an apparent tortuosity factor τapp. In wide pores or when the adsorption barrier is high, τapp = β + 1, as obtained in previous works, but in narrow pores there is an additional contribution from frequent adsorption-desorption transitions. These results are obtained in media with parallel pores of constant cross sections, where the ratio between the effective pore width ϵ/s and the actual width is ≈0.25. Applications to mesoporous silica samples are justified by the small deviations from this ideal ratio. In the analysis of alkane self-diffusion data, the fractions of adsorbed molecules predicted in a recent theoretical work are used to estimate τgeom of the silica samples, which is ≫1 only in the sample with the narrowest pores (nominal 3 nm). The application of the model to Li+ ion diffusion leads to similar values of τgeom and to a difference of energy barriers of desorption and adsorption for those ions of ∼0.06 eV. Comparatively, alkane self-diffusion provides the correct order of magnitude of τgeom, with adsorption playing a less important role, whereas adsorption effects on Li+ diffusion are much more important.

Improvement of hydrogen production via aqueous phase reforming of glycerol with Ni-Co catalysts synthesized through controlled urea matrix combustion

The effect of synthesis variable control during the combustion of urea in solution to obtain a Ni-Co/γ-Al2O3 catalyst with a low metallic loads for producting hydrogen by reforming glycerol was studied. Catalysts with the same urea/metal molar ratio but synthesized by controlled or uncontrolled urea matrix combustion were compared. It has been observed that adopting a urea/metal molar ratio between 2 and 6 and a heating rate of 10 °C∙min−1 results in a catalyst with an active surface and high Ni-Co interaction. This leads to significant improvements in H2 yield (from 34 to 50%), glycerol conversion (from 35 to 50%), and H2 selectivity (from 96 to 99%), while maintaining stability during 420 min of reaction. The repeatability of controlled synthesis has shown differences in results of less than 2%. Controlled synthesis is an attractive approach for scaling up the process for treating glycerinous waters, effluents in biodiesel plants.

A Novel Neutrosophic Likert Scale Analysis of Perceptions of Organizational Distributive Justice via a Score Function: A Complete Statistical Study and Symmetry Evidence Using Real-Life Survey Data

In this study, ten questions measuring distributive justice on classical Likert and neutrosophic Likert scales consisting of two subdimensions—distributive and procedural justice—were used. Participants responded to the same questions for both the classical Likert and neutrosophic Likert scales within a single survey, with the neutrosophic method applied, for the first time, to the questions included in the scale. The neutrosophic scale responses were answered in percentages to resemble natural language, and the answers received for each question were reduced to the range [−1, 1] to grade the agreement approach through a score function used in neutrosophic decision-making theory. In this study, the neutrosophic scale, a scaling method with strong theoretical foundations, was compared with the traditional Likert scale. The results of the statistical analyses (exploratory factor analysis, reliability analysis, neural network analysis, correlation analysis, paired samples t-test, and one-way and two-way ANOVAs) and evaluations of the scales were compared to measure organizational justice within a single study. In this article, the symmetric and non-symmetric properties of statistical analysis that are specific to this paper in addition to general symmetric and non-symmetry properties are discussed. These symmetric and non-symmetric features are conceptualized according to the features on which each statistical analysis focuses. Finally, although this study presents a new area of research in the social sciences, we believe that the neutrosophic Likert scale and survey approach will contribute to collecting detailed and sensitive information on many topics, such as economics, health, audience perceptions, advertising responses, and product, market, and service purchase research, through the use of score functions.

Synthesis of recovery patterns in microbial communities across environments

BackgroundDisturbances alter the diversity and composition of microbial communities. Yet a generalized empirical assessment of microbiome responses to disturbance across different environments is needed to understand the factors driving microbiome recovery, and the role of the environment in driving these patterns.ResultsTo this end, we combined null models with Bayesian generalized linear models to examine 86 time series of disturbed mammalian, aquatic, and soil microbiomes up to 50 days following disturbance. Overall, disturbances had the strongest effect on mammalian microbiomes, which lost taxa and later recovered their richness, but not their composition. In contrast, following disturbance, aquatic microbiomes tended away from their pre-disturbance composition over time. Surprisingly, across all environments, we found no evidence of increased compositional dispersion (i.e., variance) following disturbance, in contrast to the expectations of the Anna Karenina Principle.ConclusionsThis is the first study to systematically compare secondary successional dynamics across disturbed microbiomes, using a consistent temporal scale and modeling approach. Our findings show that the recovery of microbiomes is environment-specific, and helps to reconcile existing, environment-specific research into a unified perspective.FPVwQXB65-N4idcpgwJZ6_Video

Comparative analysis of machine learning techniques for predicting drilling rate of penetration (ROP) in geothermal wells: A case study of FORGE site

Enhanced Geothermal Systems (EGS) present a compelling means to unlock the considerable yet largely untapped thermal energy within the earth's crust globally. The EGS drilling cost constitutes a substantial portion, up to 60 %, of the overall expenses. Consequently, streamlining and optimizing the drilling processes for these systems hold immense economic significance, with the potential to substantially lower costs, advance the utilization of geothermal energy, and contribute significantly to the reduction of carbon emissions. This research aims to enhance EGS drilling operations by seeking ways of reducing drilling cost.In this research, we harnessed the predictive power of 10 state-of-the-art machine learning (ML) algorithms to anticipate a crucial drilling parameter: ROP. Using the FORGE dataset, we developed a code tailored for the intensive preprocessing of drilling data. This code offers many options, including various noise-removing techniques and scaling approaches. However, the primary focus of our work extends to quantifying uncertainties intrinsic to the predictions of the 10 algorithms employed. To achieve this, a comprehensive approach involved subjecting each algorithm to 40 runs, utilizing the best model from the tuning process.The results show that unaddressed uncertainties may lead to unstable model behavior, where small changes in the input data or random initialization result in significant prediction variations. Thus, models that do not account for uncertainty may be overfit to the noise in the training data, leading to poor generalization to new, unseen data. Remarkably, the results highlight the superiority of the Extreme Tree, Light Gradient Boost, Random Forest, and Gradient Boosting algorithms, showcasing mean absolute error (MAE) and R2 values within the ranges of 3.5–4.5 and 0.9–0.95, respectively. Conversely, artificial neural networks and support vector machine algorithms demonstrate comparatively lower performance, with MAE ranging from 4.7 to 6.3 and R2 from 0.85 to 0.91.Although the results presented in this work are only based on the drilling parameters from one well of the FORGE site and do not include rock properties or geological parameters, however, the proposed nuanced understanding of algorithmic performance is valuable for refining predictive models in geothermal drilling applications, ensuring robustness and reliability in the face of diverse operational scenarios. Navigating a successful workflow, adeptly processing data, and meticulously quantifying uncertainties linked to each predictive algorithm emerge as formidable yet indispensable tasks. Our research not only sheds light on these complexities but also paves the way for a strategic optimization approach based on data-driven ROP models. Therefore, the potential for substantial savings in real-time drilling operations becomes apparent, unlocking a new realm of possibilities for the geothermal energy sector.

Holistic springback compensation procedure

The elastic springback during the manufacturing process of stamped car body components causes dimensional deviations. To compensate these deviations, the common approach is to modify the tool surfaces in the opposite direction of the deviations – this is called springback compensation. In the procedure of springback compensation various issues must be solved. To achieve the main goal of a dimensionally accurate part, it must be ensured that, on the one hand the distance normal to the sheet surface between the springback part and the target geometry is within a specified dimensional tolerance. On the other hand, it must be ensured that the surface areas and characteristic lengths of the springback part and that of the target geometry match as closely as possible. In the past, approaches/methods, such as the physical compensation method and the physical scaling approach, have been presented which can successfully counteract these problems. Furthermore, in a multi-stage process in subsequent operations a stable part position must be achieved and unwanted plastic deformations must be avoided during blankholder closing. Therefore, different compensation strategies have been presented, which can fulfil these requirements. However, in the publication of these methods, the problems were always considered individually. This paper shows how all the named requirements can be achieved by combining the individual methods in springback compensation.

Achieving Agility through Auto-Scaling: Strategies for Dynamic Resource Allocation in Cloud Computing

Abstract: Auto-scaling is a crucial aspect of cloud computing, allowing for the efficient allocation of computational resources in response to immediate demand. This article delves into the concept of auto-scaling, its key components, and the strategies used to effectively manage resources in cloud environments. This study emphasizes the importance of auto-scaling in the cloud computing landscape by exploring its benefits, including cost efficiency, performance optimization, high availability, and scalability [1]. The article explores the various factors to consider when implementing scaling policies, such as selecting the right approach for scaling, whether it be predictive or reactive and the availability of auto-scaling services provided by major cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure [2, 3]. In addition, the paper addresses the challenges and complexities related to configuring auto-scaling systems, cost management, and latency in resource provisioning [4]. The article also showcases case studies that illustrate the successful implementation of auto-scaling in different industries, along with valuable insights and recommended approaches [5]. Lastly, this paper delves into future trends and research directions in auto-scaling techniques, integration with emerging technologies, and potential research areas [6].

Methane production from sugarcane vinasse: The alkalinizing potential of fermentative-sulfidogenic processes in two-stage anaerobic digestion

The two-stage anaerobic digestion (2st-AD) of sugarcane vinasse is widely studied and well-known for improving the energy recovery potential in sugarcane biorefineries. Maintaining enhanced substrate acidification in a separate (first stage) reactor directly improves the performance of methanogenesis (second stage). However, problems derived from the presence of sulfate (SO42−) and the subsequent sulfide formation in the second stage are not prevented in conventional 2st-AD systems. In addition, high costs related to reactor alkalinization still represent significant drawbacks in that configuration. The energy recovery potential via methanogenesis was assessed from acidified sugarcane vinasse samples collected from different dark fermentative systems, namely: V1 (subjected to NaOH+NaHCO3 dosing), V2 (subjected to NaOH dosing) and V3 (subjected to no pH control). Despite the harmfulness of sulfide, the enhanced production of acetate from the incomplete oxidation of organic matter in sulfidogenesis can benefit methanogens. The highest methane yield (296.3 NmL-CH4 g-COD−1) and global energy recovery potential (354,603 GWh per season) were obtained from the lactate and SO42−rich vinasse (V2). Nevertheless, from a technological perspective, the methanogenesis of vinasses subjected to the fermentative-sulfidogenic process (V1) provided a higher quality biogas due to a higher calorific power (26.4-27.0 MJ Nm−3) and decreased H2S content in the biogas. Finally, the fermentative-sulfidogenic process as an alkalinizing strategy was demonstrated to be the best economic approach for scaling up the 2st-AD of sugarcane vinasse, overcoming the main economic drawback of this configuration.

Strategi Konservasi Daerah Tangkapan Air Danau Singkarak

Land use changes that occur in the upstream areas of the watershed will certainly result in changes in the hydrological characteristics of the watershed. Area expansion in the form of land conversion, whether into residential or agricultural land, in the process often does not pay attention to soil and water conservation principles. Therefore, sustainable water catchment management is needed to reduce increasing land degradation. This research uses the Descriptive Analysis method through the Multidimensional Scaling approach. The sustainability status of the Lake Singkarak catchment area based on the results of the RapDTA analysis is in the moderately sustainable category with an index value of 54.87%. If we look at each dimension that is included in the quite sustainable category, it is the economic dimension with an index value of 55.10% and the social dimension with an index value of 50.37%, while the ecological dimension has an index value of 49.88%.

Electroelastic wave dispersion in the rotary piezoelectric NEMS sensors/actuators via nonlocal strain gradient theory

This article introduces a computational means for investigating the electroelastic nonlinear wave dispersion traits of the nano-dimension sandwich pipe, which is composed of a core formed of a bi-directional functionally graded (Bi-FG) material, together with a piezoelectric sensor/actuator. A combination of Hamilton’s principle, first-order shear deformation, along with Von-Karman nonlinearity, is used for modeling and obtaining the nonlinear governing equations of the nano-sized sandwich pipe connected to a piezoelectric part. The nonlinear governing equations to obtain the nonlinear phase velocity of the current system are determined using a combination of analytical and multiple scales approaches. Due to some computational cost for choosing the precise values of both the nonlocality factor and length scale of the nanopipe in the laboratory, for the first time in this research, with the aid of COMSOL multi-physics finite element simulation, the results are verified, and new outcomes for obtaining the exact functions for nonlocal and length scale factors is presented. In addition, an artificial neural network (ANN) is utilized in this study for the prediction of the results. The mathematical and finite element results were used to train the ANN. A newly presented optimization algorithm is exploited for the first time for optimizing the ANN parameters concluding higher accuracy of the ANN predictions. Consequently, to explore the influences of the location of the piezoelectric patch, nonlocality and length scale factors, and applied voltage parameter on the phase velocity characteristics of the nano-dimension sandwich pipe made of a Bi-FG core and electrically patch, an effort is performed. As an applicable result that can be useful in the related nano-industries, the current work presents exact nonlocal and length scale functions for different conditions.

Gravitational wave turbulence: A multiple time scale approach for quartic wave interactions

Gravitational wave turbulence: A multiple time scale approach for quartic wave interactions

Flowback Rates for Pump-In/Flowback Test

Summary The pump-in/flowback test (PIFT), often referred to as the diagnostic fracture injection test (DFIT) with flowback, offers notable advantages in terms of time efficiency and accuracy, particularly in the context of low-permeability formations. The key to the success of this test lies in the careful selection of an optimal flowback rate to yield meaningful results. The fundamental assumption underlying the pressure analysis of these tests is the uniform closure of fractures during the flowback phase, which is considered the default fracture closure mode in current analyses. In this study, we present evidence that challenges the validity of this assumption, highlighting instances where unsuitable flowback rates can lead to nonuniform fracture closure and result in abnormal pressure data. To address this challenge, we identify different closure modes through the signature of fracture closure in the excessive bottomhole pressure decline curve. Subsequently, we propose an optimal range of flowback rates using a scaling analysis approach to obtain a uniform closure mode in an extended openhole section of a vertical well. Our method has been rigorously validated through 3D numerical simulations and field studies, enhancing its reliability and applicability. This approach helps operators to conduct effective tests in complex situations, overcoming a barrier to widespread test application.

Aeroelastic Scaling of a High-Aspect-Ratio Wing Incorporating a Semi-Aeroelastic Hinge

There has been a growing interest in utilizing flared folding wingtips as an in-flight load alleviation device to enable increased wing spans that meet airport gate limits but with little increase in wing weight. The semi-aeroelastic hinge (SAH) concept is implemented in high-aspect-ratio wings to enable wingtips to be released during severe load cases such as maneuvers and gusts to alleviate the bending moments while maintaining optimum aerodynamic shape for the rest of the flight. In this paper, scaling methods for wings incorporating the SAH are explored, allowing for the development of equivalent scaled unmanned aerial vehicles or wind tunnel models with similar aeroelastic behavior as full-size aircraft. Three scaling approaches are considered in this study, namely, Iso-Froude, Iso-Frequency, and Iso-Strain, where a set of governing nondimensional quantities and scaling factors are determined. Despite the significant nonlinearities resulting from large wingtip fold angles, it is shown that a linear scaling approach can be appropriate for such a wing configuration. Furthermore, the aeroelastic properties of each scaled model are compared to those of the full-scale model, where the best match was obtained from the Iso-Strain model, although it is challenging to meet the required operational conditions.

Experimental investigation of countercurrent flow limitation (CCFL) in a 1/19 scale of VVER-1000 geometry

Countercurrent flow limitation (CCFL) has been experimentally considered in a VVER-1000 hot-leg. The proposed test facility consists of a hot-leg pipe, a reactor vessel simulator (RVs), and a steam generator simulator (SGs). It was designed and constructed based on power-to-volume scaling approach by preserving the Froud number in the hot leg. The scaling ratio was considered 1/19 of the Bushehr NPP (VVER-1000) geometry. The hot leg of the proposed facility provides good optical observation of the gas/liquid interface. The SG simulator has also a side view for optical observation. Experimental results were captured at atmospheric pressure with air/water as fluid. CCFL was obtained by analyzing the pressure differences between RV and SG simulators.This CCFL data was compared with empirical data and correlations available in the literature. With increasing liquid superficial velocity, the gas superficial velocity curve is continuously decreased, which is consistent with Navarro's results. In this study, an experimental correlation is proposed and compared to other correlations. It was very close to the Navarro and Richter correlations.The results of experimental investigations clarified the onset of the CCFL phenomenon in a Bushehr NPP (VVER-1000) hot-leg geometry. Moreover, the achieved patterns and behaviors of the air/water mixture would be used in computational fluid dynamics (CFD) code validations.

The quest for down scale representativeness: how to exploit CFD to design a shear study for vaccines

In this work, we exploit computational fluid dynamics (CFD) to evaluate stirred tank reactor (STR) process engineer parameters (PEP) and design a scale-down system (SDS) to be representative of the formulation and filling process steps for an Aluminum adjuvanted vaccine drug product (DP). To study the shear history in the SDS we used the concept of number of passages, combined with an appropriate stirring speed down scale strategy comprising of either (i) tip speed equivalence, widely used as a scale-up criterion for a shear-sensitive product, or (ii) rotating shear, a shear metric introduced by Metz and Otto in 1957 but never used as scaling criterion. The outcome of the CFD simulations shows that the tip equivalence generates a worst-case SDS in terms of shear, whereas the rotating shear scaling approach could be used to design a more representative SDS. We monitored the trend over time for “In Vitro Relative Potency” as DP Critical Quality Attribute for both scaling approaches, which highlighted the crucial role of choosing the appropriate scaling-down approach to be representative of the manufacturing scale during process characterization studies.

Contribution of strong electron-phonon interaction in the transport properties of La0.8Ca0.2Mn0.5Ni0.5O3 system

La0.8Ca0.2Mn0.5Ni0.5O3 NTC (negative thermal coefficient) thermo-sensitive material was prepared using a conventional solid-state reaction method. From the structural results, we found that the material is pure and crystallizes in the orthorhombic structure with a Pnma space group. It is found that the La0.8Ca0.2Mn0.5Ni0.5O3 ceramic can be used as an NTC thermistor compound in specific temperature sensors and attenuators. Based on Holsten's theory, detailed electrical investigations concerning the nature of the activated small polaron hopping mechanism were reported. The temperature dependence of the DC conductance was used to determine the electrical conduction processes that govern the transport properties of La0.8Ca0.2Mn0.5Ni0.5O3. Hence, the DC mechanisms exhibit changes from the variable range hopping at very low temperatures to the non-adiabatic small polaronic hopping at T = 210 K. In the intermediate temperature range, the semiconductor behavior of La0.8Ca0.2Mn0.5Ni0.5O3 was attributed to the contribution of the tunneling transport process. At various temperatures, the conductance spectra were discussed based on Jonscher and Bruce's laws. Contributions of the overlapping-large-polaron-tunneling, the correlated barrier hopping, the quantum mechanical tunneling, and the non-overlapping small polaron tunneling mechanisms to the transport properties were observed in the dispersive region of the conductance spectra. In addition, Summerfield scaling and corrected Summerfield scaling approaches prove that the charge mobility is temperature-dependent. The positive value of the correction parameter α = 1.2 confirms the presence of interactions in the studied sample.

Designated‐time stabilizing strategy for a class of time‐varying nonlinear systems and its application to pendulum system

AbstractIn this paper, a new scheme is proposed to stabilize a class of nonlinear systems within a designated time, mainly motivated by two unsolved problems: the singularity caused by infinity control magnitudes at the prescribed time instant and the lack of formulating/manipulating state responses after the prescribed time. Under the proposed scheme, an exquisite controller is constructed by entailing both the state scaling approach and a finite‐time stabilizing procedure. It is shown that the obtained control is well defined with bounded magnitude on the whole‐time horizon and ensures the existence of the solutions of the closed‐loop system. Superior to the existing prescribed time stabilization results, the proposed method is capable of ensuring that the states of the closed‐loop system converge to a small compact set within the designated time, stay inside it thereafter and perform finite‐time convergence eventually. Simulation examples are presented to illustrate the effectiveness of the proposed approach.

Scaling approaches and macroecology provide a foundation for assessing ecological resilience in the Anthropocene.

In the Anthropocene, intensifying ecological disturbances pose significant challenges to our predictive capabilities for ecosystem responses. Macroecology-which focuses on emergent statistical patterns in ecological systems-unveils consistent regularities in the organization of biodiversity and ecosystems. These regularities appear in terms of abundance, body size, geographical range, species interaction networks, or the flux of matter and energy. This paper argues for moving beyond qualitative resilience metaphors, such as the 'ball and cup', towards a more quantitative macroecological framework. We suggest a conceptual and theoretical basis for ecological resilience that integrates macroecology with a stochastic diffusion approximation constrained by principles of biological symmetry. This approach provides an alternative novel framework for studying ecological resilience in the Anthropocene. We demonstrate how our framework can effectively quantify the impacts of major disturbances and their extensive ecological ramifications. We further show how biological scaling insights can help quantify the consequences of major disturbances, emphasizing their cascading ecological impacts. The nature of these impacts prompts a re-evaluation of our understanding of resilience. Emphasis on regularities of ecological assemblages can help illuminate resilience dynamics and offer a novel basis to predict and manage the impacts of disturbance in the Anthropocene more efficiently. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.