Scale Constraints Research Articles

Systematic Analysis on The Development and Potential Use of Novel Semiconductors

Silicon-based transistors and integrated circuits, crucial for modern technology, are facing limitations due to scaling constraints. As transistors shrink, their performance is capped, affecting advanced technologies like AI, IoT, and 5G. Gallium nitride (GaN), with a melting point 200°C higher than silicon, presents a promising alternative due to its superior high-power and high-frequency performance. This essay reviews silicon’s semiconductor limitations and highlights the advancements in silicon carbide and Gan. The basic theories, such as electron mobility, energy level and covalent bond, are analyzed, and it is found that GaN is better than Sic and Si, but the three examples of semiconductors have different development fields in different fields. It compares the benefits of traditional silicon with these novel semiconductors, focusing on high-frequency and high-temperature performance. The essay also discusses current development, issues, and future predictions in semiconductor technology. Exploring new materials like GaN and silicon carbide addresses the technical challenges of silicon and enhances device performance, broadening technological possibilities.

New Municipalism and the Challenges of Design: Context, Instruments and Implementation

AbstractThis contribution adds a design approach to our understanding of emancipatory epistemologies within new municipalism. So far, the extant research has rarely discussed its specific opportunities and limitations, regarding their context‐bound formulation and real‐world implementation as a policy process. In contrast, the following article situates their emancipatory potential within the place‐specific ways in which multiple stakeholders define problems, set objectives, choose instruments and convert them into actions, intersecting with significant capacity constraints of the municipal scale. The case of participatory budgeting in Vienna illustrates our approach and theoretical reflection. It shows how and to what extent the design of the relational process influences new municipalism in practice and its outcome with respect to agenda‐setting, formulation and implementation. It concludes by highlighting the contribution of a design approach to the production of emancipatory knowledge and practices in democratic transformation and its analytical value added for comparative research on new municipalism.

Decision Support Systems adoption in pesticide management

This paper presents the findings from a survey on factors influencing the adoption of agricultural Decision Support Systems (DSS). Our study focuses on examining the influence of behavioural, socioeconomic and farm specific characteristics on DSS adoption. Using two structural equation models, we investigate how these factors influence the willingness to pay (WTP) and willingness to adopt. Our analysis reveals nuanced insights into the user and farm-specific factors that influence the decision-making process of DSS adoption and WTP. Notably, farm size significantly influences both adoption and WTP, with larger farms more likely to adopt and exhibit higher WTP. To promote adoption, it is important to adapt promotion strategies, with a focus on productivity benefits for large-scale farms and addressing price barriers for smaller ones. Additionally, the main crop type grown impacts WTP and adoption, with arable crop farmers exhibit a lower WTP but more likely to adopt, especially in large-scale operations. Conversely, small-scale arable farmers exhibit higher WTP but lower adoption rates due to scale constraints. Farmer characteristics such as experience and attitudes also play a crucial role, with experienced users and those perceiving productivity improvements due to DSS showing higher WTP. In addition, adoption is also influenced by ease of use and pricing, underpinning the importance of user-friendly designs and clear cost justifications. DSSs with user-centric designs and clear cost justifications can enhance adoption rates.

Effects of public procurement on corporate total-factor carbon productivity: evidence from China

Using balanced panel data for listed Chinese industrial firms from 2016 to 2021, this study examines the effect of public procurement (PP) on corporate total-factor carbon productivity (CTFCP) and the related mechanisms. The results show that (1) there is a positive correlation between PP and CTFCP. (2) PP exerts a more pronounced incentivizing effect on CTFCP for state-owned enterprises, larger corporations, and those with weaker financing constraints. (3) We decompose CTFCP into technological progress (TECH), pure technical efficiency (PTE), and scale efficiency (SE) and find that PP improves TECH and PTE, and the effect differs according to firm ownership, scale, and financing constraints. (4) PP promotes CTFCP through labor productivity (LP), capital productivity (CP), and corporate green innovation (CGI) while the mediating role of environmental productivity (EP) is not significant. This study contributes to theoretical discourse on PP’s influence on CTFCP and has practical implications for PP agencies and enterprises.

Driven by the policy or bent by the market? Cracking the digital transformation code of farmer cooperatives

The digital transformation of farmer cooperatives significantly promotes the digital rural strategy. However, due to funding and scale constraints, the digital transformation of farmer cooperatives requires government and market participation. To explore the roles of the government and market in the digital transformation of farmer cooperatives, this study constructs a tripartite game model involving farmer cooperatives, consumers, and the government, analyzing stakeholders' decisions and effects. The research results show that, first, under certain conditions, the strategies of the government, farmer cooperatives, and consumers can lead the system to evolve into stable states of (1,0,0) or (1,1,1). Second, critical parameters influencing the digital transformation of farmer cooperatives exist, with discernible thresholds. In the context of this study, the digital subsidy coefficient and the degree of propaganda for consumption upgrade should range between 0.4 and 0.45 and between 0.45 and 0.5, respectively. Consumers' high-quality consumption preferences should be between 0.5 and 0.6, whereas high-quality consumption utility should be between 75 % and 80 % of the existing level. Third, in the short term, the digital transformation of farmer cooperatives requires policy-driven initiatives; in the long term, market-bent initiatives become essential.

Segmentation Point Simultaneous Localization and Mapping: A Stereo Vision Simultaneous Localization and Mapping Method for Unmanned Surface Vehicles in Nearshore Environments

Unmanned surface vehicles (USVs) in nearshore areas are prone to environmental occlusion and electromagnetic interference, which can lead to the failure of traditional satellite-positioning methods. This paper utilizes a visual simultaneous localization and mapping (vSLAM) method to achieve USV positioning in nearshore environments. To address the issues of uneven feature distribution, erroneous depth information, and frequent viewpoint jitter in the visual data of USVs operating in nearshore environments, we propose a stereo vision SLAM system tailored for nearshore conditions: SP-SLAM (Segmentation Point-SLAM). This method is based on ORB-SLAM2 and incorporates a distance segmentation module, which filters feature points from different regions and adaptively adjusts the impact of outliers on iterative optimization, reducing the influence of erroneous depth information on motion scale estimation in open environments. Additionally, our method uses the Sum of Absolute Differences (SAD) for matching image blocks and quadric interpolation to obtain more accurate depth information, constructing a complete map. The experimental results on the USVInland dataset show that SP-SLAM solves the scaling constraint failure problem in nearshore environments and significantly improves the robustness of the stereo SLAM system in such environments.

Optimal design of electro-thermo-mechanical microactuators considering minimum length scale constraints

To ensure the manufacturability of compliant mechanisms, this paper presents a new approach for optimal design of electro-thermo-mechanical microactuators by employing minimum length scale constraints. A sequential coupling method is adopted to carry out finite element analysis for electric-thermal-mechanical coupling multiphysics. The inflection point fields of the solid and void phases are identified by structural indicator functions. The minimum length scales of the solid and void phases are adopted as constraints. The optimization objective is designed to maximize the output displacements of electro-thermo-mechanical microactuators. The validity of the proposed optimal design method is demonstrated through several numerical examples. In the optimal designs obtained by the proposed method, the minimum length scales of the two phases can be properly controlled. The electro-thermo-mechanical microactuator’s output displacements decrease when the allowable value of the minimum length scale is increased. The effects of different mesh discretizations and output spring stiffnesses on the optimized designs are discussed.

Energy Management Strategy for Wind Solar Storage Microgrid Based on Improved Ant Lion Optimizer

The energy management of microgrids involves optimizing the capacity configuration, which significantly impacts the economic and stable operation of microgrids. This paper presents a control strategy for microgrid operation that effectively manages distributed power sources and energy storage to optimize capacity configuration. A mathematical optimization model for microgrid energy management is established considering minimum annual cost and optimal scale constraints. The traditional Ant Lion Optimizer (ALO) is improved by using dynamic weight coefficients and chaotic mapping to enhance the diversity of the population and improve the convergence of the algorithm. This can effectively avoid local optimal solutions and premature problems, and improve the convergence speed and search ability of the ALO algorithm. Based on this control strategy and improved ALO algorithm, simulations and tests were conducted using actual data from an independent microgrid, resulting in the optimal solution for the microgrid capacity allocation model. The case study results validate the practicality of the proposed microgrid operation control strategy as well as the superiority of the improved ant colony optimization algorithm.

Decision Support Systems adoption in pesticide management

This paper presents the findings from a survey on factors influencing the adoption of agricultural Decision Support Systems (DSS). Our study focuses on examining the influence of behavioural, socioeconomic and farm specific characteristics on DSS adoption. Using two structural equation models, we investigate how these factors influence the willingness to pay (WTP) and willingness to adopt. Our analysis reveals nuanced insights into the user and farm-specific factors that influence the decision-making process of DSS adoption and WTP. Notably, farm size significantly influences both adoption and WTP, with larger farms more likely to adopt and exhibit higher WTP. To promote adoption, it is important to adapt promotion strategies, with a focus on productivity benefits for large-scale farms and addressing price barriers for smaller ones. Additionally, the main crop type grown impacts WTP and adoption, with arable crop farmers exhibit a lower WTP but more likely to adopt, especially in large-scale operations. Conversely, small-scale arable farmers exhibit higher WTP but lower adoption rates due to scale constraints. Farmer characteristics such as experience and attitudes also play a crucial role, with experienced users and those perceiving productivity improvements due to DSS showing higher WTP. In addition, adoption is also influenced by ease of use and pricing, underpinning the importance of user-friendly designs and clear cost justifications. DSSs with user-centric designs and clear cost justifications can enhance adoption rates.

Stability and transport of gyrokinetic critical pedestals

A gyrokinetic threshold model for pedestal width–height scaling prediction is applied to multiple devices. A shaping and aspect ratio scan is performed on National Spherical Torus Experiment (NSTX) equilibria, finding Δped=0.92A1.04κ−1.240.38δβθ,ped1.05 for the wide-pedestal branch with pedestal width Δped , aspect ratio A, elongation κ, triangularity δ, and normalized pedestal height βθ,ped . The width–transport scaling is found to vary significantly if the pedestal height is varied either with a fixed density or fixed temperature, showing how fueling and heating sources affect the pedestal density and temperature profiles for the kinetic-ballooning-mode (KBM) limited profiles. For an NSTX equilibrium, at fixed density, the wide branch is Δped=0.028(qe/Γe−1.7)1.5∼ηe1.5 and at fixed temperature Δped=0.31(qe/Γe−4.7)0.85 ∼ηe0.85 , where qe and Γe are turbulent electron heat and particle fluxes and ηe=∇ln⁡Te/∇ln⁡ne for an electron temperature Te and density ne . Pedestals close to the KBM limit are shown to have modified turbulent transport coefficients compared to the strongly driven KBMs. The role of flow shear is studied as a width–height scaling constraint and pedestal saturation mechanism for a standard and lithiated wide pedestal discharge. Finally, the stability, transport, and flow shear constraints are combined and examined for an NSTX experiment.

Can Creating an Agro-Product Regional Public Brand Improve the Ability of Farmers to Sustainably Increase Their Revenue?

Through the analysis of various typical cases, this study examines whether the establishment of an agro-product regional public brand (ARPB) can effectively boost the revenue of farmers and increase their share in the supply chain. The findings suggest that an early-stage ARPB can command a price premium for products, yet its overall contribution to farmers’ revenue remains limited due to scale constraints. The premium ability of an ARPB is influenced by product characteristics and sales strategies, underscoring the need to enhance control over terminal sales. Although the revenue of all operators in an ARPB supply chain shows an increase compared to that of a non-ARPB supply chain, the ratios of revenue allocated to farmers diminish. The Shapley value method was utilized to optimize the revenue-sharing in the supply chain, indicating a need to increase the share of revenue for farmers. This optimization necessitates the formation of a community of interests between farmers, processing enterprises, and sellers to facilitate the upstream movement of brand premiums. Furthermore, enhancing the government’s mediation and regulatory functions can provide farmers with more opportunities to partake in brand benefits.

Preferential Hydrologic States and Tipping Characteristics of Global Surface Soil Moisture

AbstractA dynamic transition in soil hydrologic states through meteorological variability and terrestrial feedback governs soil‐vegetation‐climate (SVC) interactions, constrained by critical soil moisture (SM) thresholds. However, observational and scaling constraints limit critical SM threshold estimation at the remote‐sensing (RS) footprint scale. Using global surface SM (θRS) from NASA’s Soil Moisture Active Passive (SMAP) satellite, we characterize the seasonal preferential hydrologic states of θRS and derive three tipping characteristics to estimate the intensity (Mean Tipping Depth, ), frequency (Tipping Count, η), and duration (Mean Tipped Time, ) of the excursion of θRS from wet‐ to dry‐average conditions. The preferential state provides the seasonally dominant hydrological states of θRS, while tipping characteristics capture the ecosystem linkages of the dynamic transition in θRS hydrologic states. Globally, θRS predominantly exhibits a (unimodal) dry‐preferential state, especially over arid/semi‐arid drylands and a unimodal wet‐preferential θRS state in high‐latitude boreal forests and tundra biomes. Prevalence of (bimodal) bistable θRS state overlaps with regions of strong positive SM‐precipitation coupling and monsoonal climate in semi‐arid/subhumid climates. Seasonal preferential hydrologic states co‐vary with the regional variability in plant water stress threshold and land‐atmospheric coupling strength. Tipping characteristics of θRS show sensitivity to intra‐biome variability in SVC coexistence patterns and display high skill in partitioning global ecoregions. While and η are climate‐controlled, is moderated by soil and vegetation through their influence over θRS drydown during water‐limited evapotranspiration. Preferential states and tipping characteristics find applications in quantifying SVC coexistence patterns, climate model diagnosis, and assessing ecosystem sensitivity to climate change.

3D-PCGR: Colored Point Cloud Generation and Reconstruction with Surface and Scale Constraints

In the field of 3D point cloud data, the 3D representation of objects is often affected by factors such as lighting, occlusion, and noise, leading to issues of information loss and incompleteness in the collected point cloud data. Point cloud completion algorithms aim to generate complete object point cloud data using partial or local point cloud data as input. Despite promising results achieved by existing methods, current point cloud completion approaches often lack smooth and structural consistency, resulting in a messy overall structure. To address these shortcomings in point cloud completion, we propose a point cloud generative method based on surface consistency and scale rendering. In addition, to solve the limitation of existing methods that mainly focus on geometric features in 3D point cloud completion and do not make full use of color information, we introduce an object reconstruction method based on texture and geometric features. Extensive experiments demonstrate that our proposed methods exhibit superior performance in terms of local details and overall object structure.

Multi-Level Feature-Refinement Anchor-Free Framework with Consistent Label-Assignment Mechanism for Ship Detection in SAR Imagery

Deep learning-based ship-detection methods have recently achieved impressive results in the synthetic aperture radar (SAR) community. However, numerous challenging issues affecting ship detection, such as multi-scale characteristics of the ship, clutter interference, and densely arranged ships in complex inshore, have not been well solved so far. Therefore, this article puts forward a novel SAR ship-detection method called multi-level feature-refinement anchor-free framework with a consistent label-assignment mechanism, which is capable of boosting ship-detection performance in complex scenes. First, considering that SAR ship detection is susceptible to complex background interference, we develop a stepwise feature-refinement backbone network to refine the position and contour of the ship object. Next, we devise an adjacent feature-refined pyramid network following the backbone network. The adjacent feature-refined pyramid network consists of the sub-pixel sampling-based adjacent feature-fusion sub-module and adjacent feature-localization enhancement sub-module, which can improve the detection capability of multi-scale objects by mitigating multi-scale high-level semantic loss and enhancing low-level localization features. Finally, to solve the problems of unbalanced positive and negative samples and densely arranged ship detection, we propose a consistent label-assignment mechanism based on consistent feature scale constraints to assign more appropriate and consistent labels to samples. Extensive qualitative and quantitative experiments on three public datasets, i.e., SAR Ship-Detection Dataset (SSDD), High-Resolution SAR Image Dataset (HRSID), and SAR-Ship-Dataset illustrate that the proposed method is superior to many state-of-the-art SAR ship-detection methods.

The wake of a large wind turbine in stable atmospheric boundary layer flow, simulated in the EnFlo stratified-flow wind tunnel

The EnFlo stratified-flow wind tunnel is described, and the parameterization of stable atmospheric boundary layers in the context of wind turbines and stability classification is given, as are the scaling constraints for stratified-flow wind tunnel experiments. Wake measurements of mean velocity, Reynolds stresses, and turbulent heat flux were made for three mild stable states, including overlying inversion, and the neutral state. The depth of the atmospheric boundary layer was kept constant, and so the results show the effect of change in stability alone, without the change in scale that would also arise in full scale measurements, an advantage provided by wind tunnel experiments. The simulated boundary-layer wind-speed profile is the same in each case, its height slightly exceeding the blade-tip top height, and the velocity deficit at the turbine is also the same in each, implying a constant thrust coefficient. In the near wake the momentum deficit rises more rapidly in the stable cases, and stays higher further downstream where it is subsequently reduced by turbulent mixing. The wake grows less rapidly in the vertical direction in the stable cases, both above and below the hub height, the height above growing still less rapidly with an imposed inversion, while the height below is unaffected by the inversion. The wake width is largely unaffected by stability. Stability reduces the Reynolds stresses in the wake over and above the reduction in the undisturbed flow; there is not a simple superposition. In the lower part of the wake the stresses are not affected by the inversion, while they are in the upper part. Turbulent heat flux is increased in the bulk of the wake, more so with an inversion, but is reduced to the surface and unaffected by an inversion.

Co-Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction.

Synthetic consortia have emerged as a promising biosynthetic platform that offers new opportunities for biosynthesis. Genome-scale metabolic network models (GEMs) with complex constraints are extensively utilized to guide the synthesis in monocultures. However, few methods are currently available to guide the rational construction of synthetic consortia for predicting the optimal allocation strategy of synthetic pathways aimed at enhancing product synthesis. A standardized method to construct the co-cultivated Enzyme Constraint metabolic network model (CulECpy) is proposed, which integrates enzyme constraints and modular interaction scale constraints based on the research concept of "independent + global". This method is applied to construct several synthetic consortia models, which encompassed different target products, strains, synthetic pathways, and compositional structures. Analyzing the model, the optimal pathway allocation and initial inoculum ratio that enhance the synthesis of target products by synthetic consortia are predicted and verified. When comparing with the constructed co-culture synthesis system, the normalized root mean square error of all optimal theoretical yield simulations is found to be less than or equal to 0.25. The analyses and verifications demonstrate that the method CulECpy can guide the rational construction of synthetic consortia systems to facilitate biochemical synthesis.

Outcrop to petrography scale and new age constraint of the Jatisamit Mélange in the Luk Ulo area, Central Java, Indonesia

To resolve the formation of the Luk Ulo Mélange in the Karangsambung area of Central Java, the matrix-dominated Jatisamit Mélange, which is a member of the Luk Ulo Mélange, was examined. Outcrop and petrographic observations of sandstone boudins and their shale matrix from the Jatisamit Mélange were used to assess deformational mechanisms and formation. We suggest the Jatisamit Mélange underwent three deformation phases: (1) formation of a web structure in the sandstone boudins through a cataclasis mechanism; (2) formation of boudins and cleavage through a ductile deformation; and (3) formation of open fractures and Riedel shears through pressure increasing. These deformations occurred at relatively low to medium temperatures during progressively increasing differential stress. Using illite crystallinity, the matrix of the Jatisamit Mélange has a maximum metamorphic temperature of 150–200 °C (diagenesis zone) at a 4–5 km depth. In addition, calcareous nannofossil assemblages of the Jatisamit Mélange and other related rock units in Karangsambung suggest a depositional matrix age of middle Eocene–early Oligocene. Therefore, the mixing of the Luk Ulo Mélange occurred not earlier than the middle Eocene–early Oligocene at a shallow structural level in the suture zone during the collision of the southeastern margin of Sundaland with the Gondwana micro-continent.

MWDNs: reconstruction in multi-scale feature spaces for lensless imaging.

Lensless cameras, consisting of only a sensor and a mask, are small and flexible enough to be used in many applications with stringent scale constraints. These mask-based imagers encode scenes in caustic patterns. Most existing reconstruction algorithms rely on multiple iterations based on physical model for deconvolution followed by deep learning for perception, among which the main limitation of reconstruction quality is the mismatch between the ideal and the real model. To solve the problem, we in this work learned a class of multi Wiener deconvolution networks (MWDNs), deconvoluting in multi-scale feature spaces with Wiener filters to reduce the information loss and improving the accuracy of the given model by correcting the inputs. A comparison between the proposed and the state-of-the-art algorithms shows that ours achieves much better images and performs well in real-world environments. In addition, our method takes greater advantage of the computational time due to the abandonment of iterations.

Scale in Language.

A central concern of the cognitive science of language since its origins has been the concept of the linguistic system. Recent approaches to the system concept in language point to the exceedingly complex relations that hold between many kinds of interdependent systems, but it can be difficult to know how to proceed when "everything is connected." This paper offers a framework for tackling that challenge by identifying *scale* as a conceptual mooring for the interdisciplinary study of language systems. The paper begins by defining the scale concept-simply, the possibility for a measure to be larger or smaller in different instances of a system, such as a phonemic inventory, a word's frequency value in a corpus, or a speaker population. We review sites of scale difference in and across linguistic subsystems, drawing on findings from linguistic typology, grammatical description, morphosyntactic theory, psycholinguistics, computational corpus work, and social network demography. We consider possible explanations for scaling differences and constraints in language. We then turn to the question of *dependencies between* sites of scale difference in language, reviewing four sample domains of scale dependency: in phonological systems, across levels of grammatical structure (Menzerath's Law), in corpora (Zipf's Law and related issues), and in speaker population size. Finally, we consider the implications of the review, including the utility of a scale framework for generating new questions and inspiring methodological innovations and interdisciplinary collaborations in cognitive-scientific research on language.

Interplay between entanglement and crosslinking in determining mechanical behaviors of polymer networks

ABSTRACT In polymer physics, the concept of entanglement refers to the topological constraints between long polymer chains that are closely packed together. Both theory and experimentation suggest that entanglement has a significant influence on the mechanical properties of polymers. This indicates its promise for materials design across various applications. However, understanding the relationship between entanglement and mechanical properties is complex, especially due to challenges related to length scale constraints and the difficulties of direct experimental observation. This research delves into how the polymer network structure changes when deformed. We specifically examine the relationship between entanglement, crosslinked networks, and their roles in stretching both entangled and unentangled polymer systems. For unentangled polymers, our findings underscore the pivotal role of crosslinking bond strength in determining the system’s overall strength and resistance to deformation. As for entangled polymers, entanglement plays a pivotal role in load bearing during the initial stretching stage, preserving the integrity of the polymer network. As the stretching continues and entanglement diminishes, the responsibility for bearing the load increasingly shifts to the crosslinking network, signifying a critical change in the system’s behavior. We noted a linear correlation between the increase in entanglement and the rise in tensile stress during the initial stretching stage. Conversely, the destruction of the network correlates with a decrease in tensile stress in the later stage. The findings provide vital insights into the complex dynamics between entanglement and crosslinking in the stretching processes of polymer networks, offering valuable guidance for future manipulation and design of polymer materials to achieve desired mechanical properties.