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Although consumers often value minimalist aesthetics, little work has examined why and when simple packaging designs of consumable products enhance consumer outcomes. The authors theorize that simple packaging evokes a symbolic association whereby minimizing design complexity signals that the product contains few ingredients, which increases perceived product purity and willingness to pay (WTP). A field study examining a supermarket chain's product packages (N = 1,353) provided preliminary support for this increase in WTP and two boundary conditions. Six preregistered studies replicated these effects and tested the underlying process. Studies 1a and 1b showed that the increase in WTP for simple packaging is driven by few-ingredients inferences increasing perceived product purity. Study 2 demonstrated the increase in WTP using an incentive-compatible design. Study 3 reinforced the proposed process via moderated mediation. Lastly, Studies 4 and 5 tested the boundary conditions in the field study, showing that WTP for simple packaging decreases when the product is from a store (vs. nonstore) brand and when consumers have an indulgence (vs. health) goal. These findings offer theoretical and managerial insight into minimalist aesthetics. [ABSTRACT FROM AUTHOR]

Minimal neighbor designs are useful to balance out neighbor effects economically. The method of cyclic shifts provides the construction of these minimal designs in circular blocks only for v odd, where v is the number of treatments to be compared. Minimal circular weakly balanced neighbor designs are used for v even. In this article, two classes of minimal circular weakly balanced neighbor designs are constructed for v even. In class I, v/2 of all unordered pairs of two distinct treatments appear twice as neighbors while the remaining ones appear once. In class II, 3v/2 of all unordered pairs appear twice as neighbors. [ABSTRACT FROM AUTHOR]

The variable-sweep wing, as an important morphing wing technology, has received widespread attention because it can change the sweep angle according to different flight conditions. It has the advantage of simultaneously utilizing a large sweep angle to reduce shock wave drag at high speeds and improving lift characteristics at small sweep angles. However, it has always been the case that the variable-sweep wing will bring about a rearward shift of the center of gravity when the sweep angle increases, leading to a decrease in aircraft stability. This paper focuses on a structural design of a variable-sweep wing based on a four-bar planar linkage. The novel variable-sweep wing structure containing a four-bar planar linkage and an outer wing section is proposed, and key parameters are extracted to establish a mathematical model of the mechanism. Through parametric analysis, main parameters have been identified, and the structure is optimized: the longitudinal position (direction of the fuselage) of the wing's center of gravity is designed to maintain minimal change during the morphing process, but remain the same at both the beginning and ending states of the transformation. The structural design of the variable-sweep wing is carried out based on this. Then, the finite-element model is established to validate the load-bearing capacity of the variable-sweep wing and derive the driving force. Finally, as one of the main novelties, a full-size prototype is successfully manufactured for load testing. The results of finite-element simulation and load testing show that this variable-sweep wing structure can achieve movement from 30° to 70° under an aerodynamic load that is up to 460 kg/m2. The present study demonstrates the effectiveness and potential of the proposed morphing trailing edge concept for real application on aircraft. [ABSTRACT FROM AUTHOR]

Medical image semantic segmentation is a crucial technique in medical imaging processing, providing essential diagnostic support by precisely delineating different tissue structures and pathological areas within an image. However, the pursuit of higher accuracy has led to increasingly complex architectures in existing networks, resulting in significant training overhead. In response, this study introduces a flattened, minimalist design philosophy and constructs the shallow super convolution U-shaped Net (SSCU-Net) based on this concept. Compared to the traditional four-layer U-shaped networks, SSCU-Net has a simplified two-layer structure, adhering to a lightweight research objective. On one hand, to address the issue of insufficient semantic feature extraction caused by the shallow network architecture, a parallel multi-branch feature extraction module called the super convolution block is designed to thoroughly extract diverse semantic information. On the other hand, to facilitate the transfer of critical semantic information between encoding and decoding, as well as across layers, the spatial convolution path, along with feature enhanced downsample and feature resolution upsample, are constructed. The performance of SSCU-Net was validated against 18 comparison models across seven metrics on five datasets. Results from metric analysis, image comparisons, and ablation tests collectively demonstrate that SSCU-Net achieves an average improvement of 15.9792% in the Dice coefficient compared to other models, confirming the model's advantages in both lightweight design and accuracy. The network code is available at https://github.com/YF-W/SSCU-Net. [ABSTRACT FROM AUTHOR]

To maximize the performance of rotating machines, it is essential to establish a design method with minimal arbitrariness. This paper proposes a self‐assembling method to design stator slots for alternating current (AC) rotating machines. First, we develop a line‐current approximation model of the stator winding using pulse‐width modulation technique and realize an ideal spatial magnetic flux density distribution. Subsequently, we design the realistic stator with an acceptable current density of the winding by forming unique slot shapes in a self‐assembling manner under two synthetic conditions using the developed line‐current approximation model as the starting model. The designed stator realizes a rotating magnetic field similar to the conventional design results. Additionally, we perform an analysis of motor rotation characteristics by combining the self‐assembled stator with a surface‐mounted permanent magnet rotor to determine the possibility of a higher output compared to that when using a conventional stator. The self‐assembled motor without relying on empirical rules shows a possibility of further improving the torque characteristics, thereby contributing to designing the AC rotating machines. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) and topology optimization (TO) emerge as vital processes in modern industries, with broad adoption driven by reduced expenses and the desire for lightweight and complex designs. However, iterative topology optimization can be inefficient and time-consuming for individual products with a large set of parameters. To address this shortcoming, machine learning (ML), primarily neural networks, is considered a viable tool to enhance topology optimization and streamline AM processes. In this work, a machine learning (ML) model that generates a parameterized optimized topology is presented, capable of eliminating the conventional iterative steps of TO, which shortens the development cycle and decreases overall development costs. The ML algorithm used, a conditional generative adversarial network (cGAN) known as Pix2Pix-GAN, is adopted to train using a variety of training data pairs consisting of color-coded images and is applied to an example of cantilever optimization, significantly enhancing model accuracy and operational efficiency. The analysis of training data numbers in relation to the model's accuracy shows that as data volume increases, the accuracy of the model improves. Various ML models are developed and validated in this study; however, some artefacts are still present in the generated designs. Structures that are free from these artefacts achieve 91% reliability successfully. On the other hand, the images generated with artefacts may still serve as suitable design templates with minimal adjustments. Furthermore, this research also assesses compliance with two manufacturing constraints: the limitations on build space and passive elements (voids). Incorporating manufacturing constraints into model design ensures that the generated designs are not only optimized for performance but also feasible for production. By adhering to these constraints, the models can deliver superior performance in future use while maintaining practicality in real-world applications. [ABSTRACT FROM AUTHOR]

While there have been notable advancements in Si-based optical integration, achieving compact and efficient continuous-wave (CW) III-V semiconductor nanolasers on Si at room temperature remains a substantial challenge. This study presents an innovative approach: the on-demand minimal-gain-printed Si nanolaser. By using a carefully designed minimal III-V optical gain structure and a precise on-demand gain-printing technique, we achieve lasing operation with superior spectral stability under pulsed conditions and observe a strong signature of CW operation at room temperature. These achievements are attributed to addressing both fundamental and technological issues, including carrier diffusion, absorption loss, and inefficient thermal dissipation, through minimal-gain printing in the nanolaser. Moreover, our demonstration of the laser-on-waveguide structure emphasizes the integration benefits of this on-demand gain-printed Si nanolaser, highlighting its potential significance in the fields of Si photonics and photonic integrated circuits. [ABSTRACT FROM AUTHOR]

Featured Application: Following straightforward guidelines, feedforward neural networks enable to design an accurate model-free control structure for the fast trajectory tracking of robotic arms. This paper designs a minimal neural network (NN)-based model-free control structure for the fast, accurate trajectory tracking of robotic arms, crucial for large movements, velocities, and accelerations. Trajectory tracking requires an accurate dynamic model or aggressive feedback. However, such models are hard to obtain due to nonlinearities and uncertainties, especially in low-cost, 3D-printed robotic arms. A recently proposed model-free architecture has used an NN for the dynamic compensation of a proportional derivative controller, but the minimal requirements and optimal conditions remain unclear, leading to overly complex architectures. This study aims to identify these requirements and design a minimal NN-based model-free control structure for trajectory tracking. Two architectures are compared, one NN per joint (INN) and one global NN (GNN), each tested on two serial robotic arms in simulations and real scenarios. The results show that the architecture reduces tracking errors (RMSE < 2°). The INN is accurate for decoupled joint dynamics and requires fewer training data than the GNN. A table summarizes the design process. Future works will apply this control structure to low-cost robotic arms and micro-movements. [ABSTRACT FROM AUTHOR]

This paper presents a novel three-dimensional (3D) minimally actuated serial robot (MASR) and its unique kinematic analysis. Unlike traditional robots, the 3D MASR features a passive arm devoid of wires or motors, comprising passive rotational and prismatic joints. A single mobile actuator (MA) traverses the arm, engages designated joints for operation, and locks them in place with a worm gear setup. A gripper is attached to the MA, enabling object transportation along the arm, reducing joint actuation, and optimizing task completion time. Our key contributions include the mechanical design, and in particular the robot's passive joints with their automated actuation mechanism, and a novel optimization algorithm leveraging neural networks (NNs) to minimize task completion time through advanced kinematic analysis. Experiments with a physical prototype of the 3D MASR demonstrate its major advantages: it is remarkably lightweight (2.3 kg for a 1 m long arm and a 1 kg payload) compared to similar robots; it is highly modular (five joints R and P actuated by a single MA); and part replacement is effortless due to the absence of wiring along the arm. These features are visually depicted in the accompanying video. [ABSTRACT FROM AUTHOR]

Topology optimization is a mathematical method used to determine the optimal design of a structure to achieve desirable functional performance. Traditional single-material topology optimization can be extended to include multiple materials, offering greater design freedom, and the potential for superior layouts. Additive manufacturing technologies have become powerful tools to build up such multi-material solutions. However, inherent limitations in these processes must be considered in the optimal design. One significant challenge in additive manufacturing is the trapping of either unmelted or non-solidified powder, or in some cases, support structures in enclosed voids. This study investigates a gradient-based 3D bi-material topology optimization method that considers not only the volume fraction of each material and total mass constraints but also an additional virtual temperature constraint to avoid enclosed voids. To this end, the virtual temperature method is extended to identify and mitigate enclosed voids in bi-material structures. An efficient and straightforward technique is proposed for interpolating the elemental virtual heat conduction matrix and the elemental thermal load. Additionally, a discrete material optimization approach is employed to interpolate the elemental stiffness matrix. The problem formulation and sensitivities are thoroughly discussed. The method of moving asymptotes is used to update the design variables, which are the element densities of each material. 3D numerical results are presented to demonstrate the capability and feasibility of the proposed implementation, thereby providing superior performing designs with minimal impact on the structural performance. [ABSTRACT FROM AUTHOR]

We present a complete classification of minimal problems for generic arrangements of points and lines in space observed partially by three calibrated perspective cameras when each line is incident to at most one point. This is a large class of interesting minimal problems that allows missing observations in images due to occlusions and missed detections. There is an infinite number of such minimal problems; however, we show that they can be reduced to 140,616 equivalence classes by removing superfluous features and relabeling the cameras. We also introduce camera-minimal problems, which are practical for designing minimal solvers, and show how to pick a simplest camera-minimal problem for each minimal problem. This simplification results in 74,575 equivalence classes. Only 76 of these were known; the rest are new. To identify problems having potential for practical solving of image matching and 3D reconstruction, we present several natural subfamilies of camera-minimal problems as well as compute solution counts for all camera-minimal problems which have fewer than 300 solutions for generic data. [ABSTRACT FROM AUTHOR]

During 2005–2007, the Securities and Exchange Commission conducted a randomized trial in which it removed short-sale restrictions from one third of the Russell 3000 firms. Early studies found modest market microstructure effects of removing the restrictions but no effect on short interest, stock returns, volatility, or price efficiency. More recently, many studies have attributed a wide range of indirect outcomes to this experiment, mostly without assessing the causal channels for those outcomes. We examine the three most often cited causal channels for these indirect effects: short interest, returns, and managerial fear. We find no evidence to support these channels. We then reexamine the principal findings in four recent studies using a sample that closely matches the actual experiment and a common research design and find minimal support for the reported indirect effects. Our findings highlight the importance of confirming a causal channel or an economic mechanism and show that sample selection and specification choices can produce statistical significance even without an underlying economic mechanism. This paper was accepted by David Sraer, finance. Supplemental Material: The internet appendix and data are available at https://doi.org/10.1287/mnsc.2023.4918. [ABSTRACT FROM AUTHOR]

The burgeoning field of fog computing introduces a transformative computing paradigm with extensive applications across diverse sectors. At the heart of this paradigm lies the pivotal role of edge servers, which are entrusted with critical computing and storage functions. The optimization of these servers' storage capacities emerges as a crucial factor in augmenting the efficacy of fog computing infrastructures. This paper presents a novel storage optimization algorithm, dubbed LIRU (Low Interference Recently Used), which synthesizes the strengths of the LIRS (Low Interference Recency Set) and LRU (Least Recently Used) replacement algorithms. Set against the backdrop of constrained storage resources, this research endeavours to formulate an algorithm that optimizes storage space utilization, elevates data access efficiency, and diminishes access latencies. The investigation initiates a comprehensive analysis of the storage resources available on edge servers, pinpointing the essential considerations for optimization algorithms: storage resource utilization and data access frequency. The study then constructs an optimization model that harmonizes data frequency with cache capacity, employing optimization theory to discern the optimal solution for storage maximization. Subsequent experimental validations of the LIRU algorithm underscore its superiority over conventional replacement algorithms, showcasing significant improvements in storage utilization, data access efficiency, and reduced access delays. Notably, the LIRU algorithm registers a 5% increment in one-hop hit ratio relative to the LFU algorithm, a 66% enhancement over the LRU algorithm, and a 14% elevation in system hit ratio against the LRU algorithm. Moreover, it curtails the average system response time by 2.4% and 16.5% compared to the LRU and LFU algorithms, respectively, particularly in scenarios involving large cache sizes. This research not only sheds light on the intricacies of edge server storage optimization but also significantly propels the performance and efficiency of the broader fog computing ecosystem. Through these insights, the study contributes a valuable framework for enhancing data management strategies within fog computing architectures, marking a noteworthy advancement in the field. [ABSTRACT FROM AUTHOR]

This paper provides a specific analysis strategy for tensegrity prism units with different complexities and connectivity. Through the nodal coordinate matrix and connectivity matrix, we can establish the equilibrium equation of the structure in the self-equilibrium state, and the equilibrium matrix can be obtained. The Singular Value Decomposition (SVD) method can find the self-equilibrium configuration. The torsional angle formula between the upper and bottom surfaces of the prismatic tensegrity structure, which includes complexity and connectivity, can be obtained through the SVD form-finding method. According to the torsional angle formula of the self-equilibrium configuration, we carry out the mechanical analysis of the single node, and the force density relationship between elements is gained. As one of the standards, the mass is used to evaluate the light structure. This paper also studied the minimal mass of the self-equilibrium tensegrity structure with the same complexity in different connectivity and got the minimal mass calculation formula. A six-bar tensegrity prism unit is investigated in this paper, which shows the feasibility of systematic analysis of prismatic structures. This paper provides a theoretical reference for prismatic tensegrity units. [ABSTRACT FROM AUTHOR]

The experiments where response of a treatment (direct effect) is affected by the treatment(s) applied in neighboring units, neighbor designs are used to balance the neighbor effects. Being the economical, minimal neighbor designs are preferred by the experimenters. Minimal circular neighbor designs could not be constructed for almost every case of v even, where v is number of treatments. For v even, minimal circular generalized neighbor designs are preferred. In this article, algorithms are developed to obtain minimal circular generalized neighbor designs in which (a) v/2 of the unordered pairs, and (b) 3v/2 of the unordered pairs, do not appear as neighbor whereas the remaining ones appear once. These algorithms are also coded with R-language. [ABSTRACT FROM AUTHOR]

The development of precision agriculture requires unmanned aerial vehicles (UAVs) to collect diverse data, such as RGB images, 3D point clouds, and hyperspectral images. Recently, convolutional networks have made remarkable progress in downstream visual tasks, while often disregarding the trade-off between accuracy and speed in UAV-based segmentation tasks. The study aims to provide further valuable insights using an efficient model named Taoism-Net. The findings include the following: (1) Prescription maps in agricultural UAVs requires pixel-level precise segmentation, with many focusing solely on accuracy at the expense of real-time processing capabilities, being incapable of satisfying the expectations of practical tasks. (2) Taoism-Net is a refreshingly segmented model, overcoming the challenges of complexity in deep learning, based on minimalist design, which is used to generate prescription maps through pixel level classification mapping of geodetic coordinates (the lychee tree aerial dataset in Guangdong is used for experiments). (3) Compared with mainstream lightweight models or mature segmentation algorithms, Taoism-Net achieves significant improvements, including an improvement of at least 4.8% in mIoU, and manifested a superior performance in the accuracy–latency curve. (4) "The greatest truths are concise" is a saying widely spread by ancient Taoism, indicating that the most fundamental approach is reflected through the utmost minimalism; moreover, Taoism-Net expects to a build bridge between academic research and industrial deployment, for example, UAVs in precision agriculture. [ABSTRACT FROM AUTHOR]

In this essay I suggest that we view design principles in systems biology as minimal models, for a design principle usually exhibits universal behaviors that are common to a whole range of heterogeneous (living and nonliving) systems with different underlying mechanisms. A well-known design principle in systems biology, integral feedback control , is discussed, showing that it satisfies all the conditions for a model to be a minimal model. This approach has significant philosophical implications: it not only accounts for how design principles explain, but also helps clarify one dispute over design principles, e.g., whether design principles provide mechanistic explanations or a distinct kind of explanations called design explanations. [ABSTRACT FROM AUTHOR]

A priority system has traditionally been the protocol of choice for the allocation of scarce life-saving resources during public health emergencies. COVID-19 revealed the limitations of this allocation rule. Many argue that priority systems abandon ethical values, such as equity, by discriminating against disadvantaged communities. We show that a restrictive feature of the traditional priority system largely drives these limitations. Following minimalist market design, an institution design paradigm that integrates research and policy efforts, we formulate pandemic allocation of scarce life-saving resources as a new application of market design. Interfering only with the restrictive feature of the priority system to address its shortcomings, we formulate a reserve system as an alternative allocation rule. Our theoretical analysis develops a general theory of reserve design. We relate our analysis to debates during COVID-19 and describe the impact of our paper on policy and practice. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome. [ABSTRACT FROM AUTHOR]

The research is a theoretical analysis of the relationships between minimalism in Western and Eastern design. The research purpose is to identify the influence of oriental minimalist design on the development of design in the West. The scientific value of the research is the comparative analysis of Eastern and Western minimalist design that may be of interest to teachers and students learning art, design, and architecture. The research methodology used the philosophical principles of Determinism, the Interdependence of Being and Consciousness, the Harmony of Man and Nature, the Unity of External and Internal, form and content, style and meaning. The scholars followed different methods of analysis, reviewed scientific literature, and applied the method of theoretical modeling to the research framework. The results helped to identify key characteristics, commonalities, and distinctive features of minimalist design in the East and the West. [ABSTRACT FROM AUTHOR]

Residual effects in repeated measurements design (RMDs) leads to wrong estimation of direct treatment effects. Minimal strongly balanced RMDs are preferred to balance out the residual effects. The partially strongly balanced designs form an important family of RMDs which provide designs where minimal strongly balanced RMDs do not exist. In this article, a general construction of efficieint circular partially strongly-balanced RMDs is given in periods of k different sizes which produces these designs in periods of equal sizes, two different sizes, three different sizes, ..., by putting k = 1, 2, 3, ..., respectively. [ABSTRACT FROM AUTHOR]

Background: Simulation‐based procedural practice is crucial to emergency medicine skills training and maintenance. However, many commercial procedural models are either nonexistent or lacking in key elements. Simulationists often create their own novel models with minimal framework for designing, building, and validation. We propose two interlinked frameworks with the goal to systematically build and validate models for the desired educational outcomes. Methods: Simulation Academy Research Committee and members with novel model development expertise assembled as the MIDAS (Model Innovation, Development and Assessment for Simulation) working group. This working group focused on improving novel model creation and validation beginning with a preconference workshop at 2023 Society for Academic Emergency Medicine Annual Meeting. The MIDAS group sought to (1) assess the current state of novel model validation and (2) develop frameworks for the broader simulation community to create, improve, and validate procedural models. Findings: Workshop participants completed 17 surveys for a response rate of 100%. Many simulationists have created models but few have validated them. The most common barriers to validation were lack of standardized guidelines and familiarity with the validation process. We have combined principles from education and engineering fields into two interlinked frameworks. The first is centered on steps involved with model creation and refinement. The second is a framework for novel model validation processes. Implications: These frameworks emphasize development of models through a deliberate, form‐follows‐function methodology, aimed at ensuring training quality through novel models. Following a blueprint of how to create, test, and improve models can save innovators time and energy, which in turn can yield greater and more plentiful innovation at lower time and financial cost. This guideline allows for more standardized approaches to model creation, thus improving future scholarship on novel models. [ABSTRACT FROM AUTHOR]

Evolutionarily conserved structural folds can give rise to diverse biological functions, yet predicting atomic-scale interactions that contribute to the emergence of novel activities within such folds remains challenging. Pancreatic-type ribonucleases illustrate this complexity, sharing a core structure that has evolved to accommodate varied functions. In this study, we used ancestral sequence reconstruction to probe evolutionary and molecular determinants that distinguish biological activities within eosinophil members of the RNase 2/ 3 subfamily. Our investigation unveils functional, structural, and dynamical behaviors that differentiate the evolved ancestral ribonuclease (AncRNase) from its contemporary eosinophil RNase orthologs. Leveraging the potential of ancestral reconstruction for protein engineering, we used AncRNase predictions to design a minimal 4-residue variant that transforms human RNase 2 into a chimeric enzyme endowed with the antimicrobial and cytotoxic activities of RNase 3 members. This work provides unique insights into mutational and evolutionary pathways governing structure, function, and conformational states within the eosinophil RNase subfamily, offering potential for targeted modulation of RNase-associated functions. [ABSTRACT FROM AUTHOR]

The relationship between social factors and the formation of exported mug designs is blurred. This study addresses how they influence material design. Based on a quantitative typological analysis, this paper interprets the cultural relationships underlying the evolution of mug designs exported during the Ming and Qing dynasties. The study reveals: (1) the typology and handle styles of mugs can be categorized into six types, with a predominance of Cylindrical bodies and Ear-shaped handles. Notably, artistic emphasis is concentrated on Bulbous cup bodies and Tail outward curved handles; (2) the design of mugs in the eighteenth century exhibited diversity, morphological similarities, and feature continuity, evolving from representational (Ming Dynasty) to abstract and then to minimalistic styles (Qing Dynasty), particularly evident in the three-dimensional modeling of handles for ergonomic comfort (transitioning from a singular Outward curved form to Ear-shaped form, and then to Entwined branch form); (3) the body shape of mugs transformed from Arc-barrel bodies to Bulbous bodies (focusing on heat retention), and eventually to Cylindrical bodies (prioritizing heat retention, practicality, and cost-efficiency).; (4) the volume of mugs steadily increased from the early eighteenth century, generally classified into large volume (≥ 500 ml), medium volume (200-499 ml), and small volume (< 200 ml); (5) considering the extreme range of volume (11090 ml) and height (25 cm), it indicates that these two variables do not necessarily have a direct positive correlation; (6) the low center of gravity in handle design (average width of 3.4 cm against an average height of 9.9 cm for the body) reflects considerations for the distribution of liquid weight and operational convenience. The volume of sample-10 (11127 ml) notably exceeds the typical range for tea-drinking utensils, revealing the mechanism of wealth and status symbolism. Market demand orientation emerged as the primary driver for the evolution of export mug designs during the Ming and Qing Dynasties, with adjustments in the merchant system playing a secondary role. The transformation in mug design reflects the interplay of multiple factors, with the trend toward minimalist design being a response to market demands. [ABSTRACT FROM AUTHOR]

The morphology of crystalline active pharmaceutical ingredients (APIs) can significantly affect their product properties, so that its control during manufacturing is crucial. To address this, a newly augmented commercial milliliter‐scale facility and knowledge‐based workflow were developed with the aim of identifying optimal process conditions for producing more equant‐shaped crystals. The design includes minimal material usage, inline imaging, and independent temperature and supersaturation control through evaporative crystallization. The methodology enables the identification of process conditions for equant‐shaped crystals across diverse APIs. These findings contribute to advancing pharmaceutical research and development by providing a reliable approach to optimize crystal morphology. [ABSTRACT FROM AUTHOR]

In an era marked by the rapid growth of digital media and increasingly limited attention spans, advertisements employing minimalist aesthetics have emerged as a compelling approach. Yet, the specific conditions under which consumers favor minimalist ads remain underexplored. Through a comprehensive series of studies, including a field study and five scenario‐based experiments, this research unveils new insights into how busyness shapes consumer preferences for minimalist ad designs. This research found that busyness notably steers preferences toward minimalist over complex ads, both in real‐world (Study 1) and experimental environments (Study 2). Notably, we revealed a serial mediation, with busyness affecting ad preference through the desire for relaxation (distal mediator) followed by the intent to avoid processing disfluency (proximal mediator) (Study 3). Furthermore, two boundary conditions were identified in which this effect is attenuated or intensified. When consumers place a high (vs. low) price on time, the busyness effect on minimalism preference is undermined (Study 4). In addition, this effect is more pronounced when a temporal landmark that designates an end (vs. start) is made salient (Studies 5 and 6). These insights not only illuminate consumer behavior in visual marketing but also carry significant practical implications for advertisers, marketing professionals, and policymakers. [ABSTRACT FROM AUTHOR]

We present a proof-of-concept for minimalist market design (Sönmez 2023) as an effective methodology to enhance an institution based on stakeholders' desiderata with minimal interference. Four objectives--respecting merit, increasing retention, aligning talent, and enhancing trust--guided reforms to the US Army's centralized branching process of cadets to military specialties since 2006. USMA's mechanism for the class of 2020 exacerbated challenges in implementing these objectives. Formulating the Army's desiderata as rigorous axioms, we analyze their implications. Under our minimalist approach to institution redesign, the Army's objectives uniquely identify a branching mechanism. Our design is now adopted at USMA and ROTC. [ABSTRACT FROM AUTHOR]

Recently, performance development related to noise, vibration, and harshness in sunroof systems has attracted significant research attention. However, research thus far has been limited to analytical and experimental studies relating to structural improvement of the individual parts, rather than considering vehicle driving conditions. This study compared the experimental data from actual driving tests with simulation results to examine sunroof vibration characteristics under realistic conditions. Firstly, the characteristics of sunroof vibrations were investigated theoretically in order to derive equations of motion and the natural frequencies of the sunroof. Sunroof vibrations occurring during driving were analyzed through experimental modal analysis and operational deflection shape. A parametric study was conducted adapting design parameters such as the Young's modulus, glass thickness, and bracket location. The vibration characteristics of the sunroof glass could be improved by changing the support points of the front and rear brackets, which represent the design elements that can achieve the greatest efficiency with minimal design changes. [ABSTRACT FROM AUTHOR]

The essential guidelines are presented of a postgraduate course on electrochemistry for master studies at the University of Valencia (Spain). This course has been designed for students with a minimal knowledge of electrochemistry. It is based on laboratory experiments that, starting from an initial theoretical core, promotes the in-laboratory discussion of concepts, operations, functional relations, etc. The course, although focused on voltammetric techniques, covers the main concepts and experimental aspects of electrochemistry and particular attention is put to erroneous conceptions regarding fundamental physicochemical concepts and operations (misconceptions) as well as on general aspects of the scientific methodology (meta-conceptions) around this discipline. [ABSTRACT FROM AUTHOR]

The primary aim of this study was to optimize 3D-printed sandwich beams incorporating auxetic cores. Four key design variables were considered: core thickness, width, and two specific geometric parameters related to the auxetic core–the cell's wall thickness-to-length ratio and the cell angle. Initially, sixteen sandwich samples, each varying in geometric parameters, were printed following Taguchi's experimental design. These samples underwent a three-point bending test, and the resulting data were used to train a deep neural network (DNN). The trained DNN proficiently predicted the bending response of the structures. Another network, using a similar architecture, was trained to precisely predict the structure's mass. These trained networks were then integrated into the imperialist competitive algorithm (ICA) to optimize the sandwich beams design for minimal mass. A contour plot was subsequently generated to visually illustrate the minimum required mass distribution for sandwich beams under various conditions and constraints, considering applied bending forces and maximum allowable deflection. The optimization results underscored the importance of fabricating and testing an adequate number of sandwich samples, aligning with the number of design parameters. The results provide a valuable reference for future research on designing advanced 3D-printed lightweight structures, including integrating machine learning techniques and metaheuristic algorithms. [ABSTRACT FROM AUTHOR]

The advent of additive manufacturing also referred to as 3D printing, has brought about substantial changes in the industrial domain, as it possesses the capability to fabricate intricate items with enhanced cost‐efficiency and productivity. Fused Filament Fabrication (FFF) is a 3D printing process that has gained significant popularity due to its versatile capabilities and cost‐effectiveness. This paper investigates the impact of the printing parameters on the tensile characteristics of Triply Periodic Minimal Surface (TPMS) manufactured using FFF 3D printing. TPMS patterns have unique geometric properties and potential applications, making them an intriguing subject of study. The behavior of three different TPMS lattices with three printing parameters is investigated. Finding the best testing settings is done with the Taguchi method, and the data is analyzed with the Analysis of Variance (ANOVA) test. TPMS pattern was found to be the most effective parameter with 83.78%. While the highest strength was obtained in Schwarz diamond, the highest energy absorption was observed in the Gyroid structure. The contributions of printing parameters to tensile strength are line thickness, printing speed, and layer height, respectively. As line width and printing speed increase, both energy absorption and strength increase. Therefore, 0.40 mm line width and 60 mm/s printing speed give optimum values. When considered for energy absorption, the optimum value is 0.20 mm layer height, while when considered for strength, 0.10 mm layer height is the optimum value. The findings emphasize the importance of optimizing printing parameters for desired mechanical characteristics in 3D printed components and highlight the potential of TPMS structures in various applications. This research contributes to the growing knowledge in additive manufacturing and provides insights into optimizing FFF 3D printing for improved mechanical performance. [ABSTRACT FROM AUTHOR]

Minimalism in consumption can be expressed in various forms, such as monochromatic home design, wardrobe capsules, tiny home living, and decluttering. This research offers a unified understanding of the variegated displays of minimalism by establishing a conceptual definition of consumer minimalism and developing the 12-item Minimalist Consumer Scale to measure the construct. Three distinct dimensions of consumer minimalism are identified: number of possessions (reflecting the ownership of few possessions), sparse aesthetic (reflecting the preference for simple and uncomplicated designs), and mindfully curated consumption (reflecting the thoughtful selection of possessions). A series of studies, using samples from a variety of populations (N = 3,735) demonstrates the validity and reliability of the tridimensional Minimalist Consumer Scale, situates the measure conceptually and empirically within a broader nomological network of related constructs (e.g. voluntary simplicity, frugality, green values, materialism), and documents the scale's ability to predict relevant consumer preferences and behaviors. [ABSTRACT FROM AUTHOR]

Complex envelope and reduced phase simulation models describing the dynamical behaviour of an optoelectronic oscillator (OEO) under injection by an external source are described. The models build on the foundations of a previously reported delay integral/differential equation (DDE) theory of injection locking of time delay oscillators (TDO) such as the OEO. The DDE formulation is particularly amenable to high precision simulation using the Simulink™ block diagram environment. The correspondence between the blocks and the oscillator components offers intuition and considerable freedom to explore different circuit architectures and design variations with minimal coding effort. The simulations facilitate the study of the profound effect the multimode nature of a TDO has on its dynamical behavior. The reduced phase models that make use of the Leeson approximation are generally successful in reproducing the results of complex envelope models for established oscillations except for spiking phenomena for which the Leeson approximation fails. Simulation results demonstrating phenomena not captured by classical injection theory are presented, including multimode oscillation, the appearance of sidemodes in the RF and phase noise spectrum, and persistent spike trains redolent of recent experimental observations of 2 π phase pulse trains in a broadband OEO under injection. [ABSTRACT FROM AUTHOR]

Residual effects in repeated measurements design leads to wrong estimation of direct treatment effects. Due to that minimal balanced repeated measurement designs and strongly balanced repeated measurements designs are preferred to balance the residual effects. When these minimal designs could not be constructed then minimal partially balanced repeated measurement designs and generalized strongly balanced RMDs are used. In this article, some new generators are developed to obtain the generalized classes of minimal circular strongly balanced RMDs which can be converted directly into minimal circular balanced and strongly balanced RMDs. [ABSTRACT FROM AUTHOR]

The combination of bioactive Zn‐2Mg alloy and additively manufactured porous scaffold is expected to achieve customizable biodegradable performance and enhanced bone regeneration. Herein, Zn‐2Mg alloy scaffolds with different porosities, including 40% (G‐40‐2), 60% (G‐60‐2), and 80% (G‐80‐2), and different unit sizes, including 1.5 mm (G‐60‐1.5), 2 mm (G‐60‐2), and 2.5 mm (G‐60‐2.5), are manufactured by a triply periodic minimal surface design and a reliable laser powder bed fusion process. With the same unit size, compressive strength (CS) and elastic modulus (EM) of scaffolds substantially decrease with increasing porosities. With the same porosity, CS and EM just slightly decrease with increasing unit sizes. The weight loss after degradation increases with increasing porosities and decreasing unit sizes. In vivo tests indicate that Zn‐2Mg alloy scaffolds exhibit satisfactory biocompatibility and osteogenic ability. The osteogenic ability of scaffolds is mainly determined by their physical and chemical characteristics. Scaffolds with lower porosities and smaller unit sizes show better osteogenesis due to their suitable pore size and larger surface area. The results indicate that the biodegradable performance of scaffolds can be accurately regulated on a large scale by structure design and the additively manufactured Zn‐2Mg alloy scaffolds have improved osteogenic ability for treating bone defects. [ABSTRACT FROM AUTHOR]

Extreme limited entry (XLE) method can enhance hydraulic fracture uniformity by elevating wellbore pressure to overcome reservoir heterogeneity. However, it increases surface pressure and decreases hydraulic fracturing efficiency. In this paper, the effects of stress shadow and heterogeneity of the lateral breakdown pressure on fracture propagation are numerically studied, from which an optimization method is proposed for the XLE design with the minimal requirement of fracturing pressure. Initially, the unconventional fracture model is applied to analyze fracture propagation in formations with homogeneous geomechanical parameters and various perforation designs. Fracture length distribution is correlated with perforation friction, revealing insights into the influence of geomechanical parameters and fracture spacing. Then, the uniformity of fracture propagation is assessed for different XLE designs by varying lateral breakdown pressures. Simulation results are utilized to develop a cross-plot of fracture length distributions vs normalized perforation frictions for optimizing an XLE design. In homogeneous reservoirs, decreasing perforation spacing and increasing perforation hole erosion rate slow down the reduction in the fracture length distribution span with perforation friction, necessitating a higher perforation friction for uniform fractures. In all simulated cases, a similar trend is observed when the distribution of fracture lengths is plotted vs the normalized perforation friction to the difference of breakdown pressure within one fracturing stage. It is recommended that this normalized value be maintained above 2 in an XLE design. This new plot makes the conventional horn-shaped plot more applicable to reservoirs with heterogeneous lateral breakdown pressures. [ABSTRACT FROM AUTHOR]

Devising genetic interventions for desired cellular phenotypes remains challenging regarding time and resources. Kinetic models can accelerate this task by simulating metabolic responses to genetic perturbations. However, exhaustive design evaluations with kinetic models are computationally impractical, especially when targeting multiple enzymes. Here, we introduce a framework for efficiently scouting the design space while respecting cellular physiological requirements. The framework employs mixed-integer linear programming and nonlinear simulations with large-scale nonlinear kinetic models to devise genetic interventions while accounting for the network effects of these perturbations. Importantly, it ensures the engineered strain's robustness by maintaining its phenotype close to that of the reference strain. The framework, applied to improve the anthranilate production in E. coli, devises designs for experimental implementation, including eight previously experimentally validated targets. We expect this framework to play a crucial role in future design-build-test-learn cycles, significantly expediting the strain design compared to exhaustive design enumeration. No consensus exists on the computationally tractable use of dynamic models for strain design. To tackle this, the authors report a framework, nonlinear-dynamic-model-assisted rational metabolic engineering design, for efficiently designing robust, artificially engineered cellular organisms. [ABSTRACT FROM AUTHOR]

In the present study, a 100 kW organic Rankine cycle is suggested to recover heat energy from commercial ships. A radial-type turbine is employed with R1233zd(E) and back-to-back layout. To improve the performance of an organic Rankine power system, the efficiency of the turbine is significant. With the conventional approach, the optimization of a turbine requires a considerable amount of time and involves substantial costs. By combining design of experiments, an artificial neural network, and Latin hypercube sampling, it becomes possible to reduce costs and achieve rapid optimization. A radial basis neural network with machine learning technique, known for its advantages of being fast and easily applicable, has been implemented. Using such an approach, an increase in efficiency greater than 1% was achieved with minimal design changes at the first and second turbines. [ABSTRACT FROM AUTHOR]

Arithmetic Logic Unit is the brain of all processors, is composed of an Adder circuit. The main component of multiplier circuits is the adder, which performs subtraction (by 2's complement arithmetic). Since the most fundamental operation in mathematics is addition, and the adder is the most essential part of the processor, the study of VLSI arithmetic has required many digital VLSI researchers. When designing digital systems employing the VLSI approach, the digital adder plays a major role. Low power VLSI based adder designs perform poorly because of the propagation delay issue. With the aid of the PPA design, an assessment of adders' availability for low power VLSI designs with minimal propagation delay is conducted. Using these performance measures, this study compares and evaluates the performance of several parallel prefix adders, allowing readers to select the optimum adder architecture for their application Specific Integrated Circuits implementations. The three adder topologies taken into considered in this Article include the Han carlson adder, Brent kung, Kogge stone adders. Xilinx ZYNQ XC7Z020 (7000 series) SoC is used to implement the adders using the Vivado Design Suite 2014 and Verilog. [ABSTRACT FROM AUTHOR]

• It is vital to incorporate patient views into trial design. • We used complex experimental design to find out what pwCF value most when deciding whether to take part in trials. • Location of trial and distance travelled to site were the most important attributes when deciding whether to participate. • Post-trial medicine access, type of medicine, stipend provision and washouts were moderately influential. • Trial design had minimal influence and pwCF do not seem to find placebo-controlled trials off putting. Patient-centred trial design optimises recruitment and retention, reduces trial failure rates and increases the diversity of trial cohorts. This allows safe and effective treatments to reach clinic more quickly. To achieve this, patients' views must be incorporated into trial design. A discrete choice experiment was used to quantify preferences of pwCF for trials features; medicine type, trial location, stipend, washout, drug access on trial completion and trial design. Respondents were presented pairs of hypothetical trial scenarios with different level combinations assigned through experimental design. Respondents were asked to pick their preferred option or decline both. The cross-sectional data were explored using a Random Parameters Logit model. We received 207 eligible responses between Oct2020-Jan2021. The strongest influence on the decision to participate was trial location; pwCF favour participation at their usual clinical centre. Greater travel distances made respondents less willing to participate. Post-trial drug access ranked second. pwCF would rather participate in modulator trials than trials of other drugs. In general, pwCF did not favour a washout period, but were more prepared to washout non-modulators than modulators. Stipend provision was not ranked highly, but higher stipends increased intention to participate. Trial design (placebo vs open-label) had minimal influence on the decision to participate. There are complex interactions between placebos and washouts. We used quantitative methods to systematically elicit preferences of pwCF for clinical trials' features. We explore the relevance of our findings to trial design and delivery in the current CF trials landscape. [ABSTRACT FROM AUTHOR]

We show that the eigenpolytopes of graphs are universal in the sense that every polytope, up to affine equivalence, appears as the eigenpolytope of some positively weighted graph. We next extend the theory of graphical designs, which are quadrature rules for graphs, to positively weighted graphs. Through Gale duality for polytopes, we show a bijection between graphical designs and the faces of eigenpolytopes. This bijection proves the existence of graphical designs with positive quadrature weights and upper bounds the size of a minimal graphical design. Connecting this bijection with the universality of eigenpolytopes, we establish three complexity results: It is strongly NP-complete to determine if there is a graphical design smaller than the mentioned upper bound, it is NP-hard to find a smallest graphical design, and it is \#P-complete to count the number of minimal graphical designs. [ABSTRACT FROM AUTHOR]

Minimal circular balanced and strongly balanced neighbor designs (MCBNDs & MCSBNDs) are popular to control neighbor effects and to estimate neighbor and direct effects independently. In this article, an R-coded algorithm is presented to obtain efficient MCBNDs and MCSBNDs for odd v (number of treatments), and its four generalized classes for v even. Developed algorithm has made the construction of the efficient circular designs robust to neighbor effects so easy in blocks of equal and unequal sizes. [ABSTRACT FROM AUTHOR]

In this work, we introduce a novel technique that optimizes the design and properties of support structures for Powder Bed Fusion–Laser-Based Metal (PBF-LB/M) processes. The goal is to significantly ease support removal during post-processing without compromising print quality. We propose an additive manufacturing (AM) workflow that streamlines the end-to-end AM process through the creation and integration of innovative support systems, modeling software, and efficient support removal techniques. This approach enhances productivity and minimizes trial and error between design and 3D printing. Our key concept revolves around developing a "soft" support system, which can be easily removed using sandblasting. Compared to manual or machining removal, this method substantially reduces cost and time, particularly in areas with limited or no access. For locations with steep overhangs and large cross-sectional areas, the traditional strong support system can be implemented as a "hard" support. The proposed workflow allows for the development of a hybrid system combining hard and soft supports, effectively manufacturing parts with minimal design constraints. The workflow begins from a standard operating procedure (SOP) for evaluating the appropriate printing parameters to achieve a support that can be soft enough to be sandblasted for removal, yet sufficient strong to support the overhang part structure and prevent distortion. A simulation platform is developed to assess the ideal placement and combination of the hybrid support design, achieving a balance between post-processing cost and effort, and print quality. The development of this solution truly reflects the advantage of metal 3D printing technology, i.e., design freedom. [ABSTRACT FROM AUTHOR]

The aim of this article is to contribute in two respects to the evolving research agenda focused on the problem of democratic resilience. First, we attempt to provide several clarifications regarding the general concept of 'democratic resilience', in the course of which we both assess a number of accounts offered thus far and discuss some difficulties raised by elements of its most attractive articulation. Second, we outline a specific conception of democratic resilience framed on minimalist grounds and designed so as to be compatible with a wide range of descriptive and normative models of democracy. Aside from the conceptual and analytical value of these contributions, we also point to their practical relevance for both empirical assessments and for the normative and applied-level evaluation of democratic institutions and their performance. [ABSTRACT FROM AUTHOR]

Repeated measurements designs (RMDs) are very useful and economical but unfortunately, with the use of RMDs, a major source of bias is arisen, that is the carry over effect. Minimal designs which are strongly and nearly strongly balanced, are preferred to estimate the direct and carry over effects independently. In this article, some new classes of minimal circular nearly strongly balanced RMDs are constructed in periods of two and three different sizes which can be converted directly into minimal circular balanced and minimal strongly balanced which are highly efficient. [ABSTRACT FROM AUTHOR]