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As an emerging type of large commercial building, commercial complexes play an increasingly important role in contemporary urban development and construction trends. In order to better study the organization of public space relations in commercial complex buildings, this paper selects eight commercial complexes as sample cases to analyze their spatial design in terms of both content public space and external public space based on big data technology. Regarding the design of the commercial complexes’ internal public space movement, the highest accessibility degree reached 95.3%, while the average was 82.5%. Regarding visibility, the highest level was 96.0%, and the average was 83.3%. For large complexes, better spatial relationships can be designed to improve the circulation degree and thus enhance customers’ consumption experience. Regarding the convenience of traffic connection to the external space of commercial complexes, an average of 41.4% of customers consider it very convenient, 23.1% consider it relatively convenient, 27.9% consider it somewhat inconvenient, and 18.0% consider it very inconvenient. Commercial complexes can effectively attract more repeat customers if they can improve the convenient design of transportation connections. The study of public relations of commercial complexes based on big data helps to discover the defects of their public space design and plays a significant role in optimizing spatial design and relationship organization and strengthening their integrated functions.

Integrated opto-mechanical analysis (IOA) for Photoelectric detection and tracking systems (PDTS) is crucial both in the early design phase and during later operation and maintenance. The movements of PDTS typically generate unbalanced momentum, resulting in noticeable line-of-sight jitters (LOSJs) and wavefront aberrations (WFAs) of the beam. However, the characteristics of multidisciplinary coupling and multibody system dynamics bring challenges to the measurement of LOSJ and WFA. To address this challenge, this paper proposes a modeling method for the opto-mechanical coupling problems of PDTS during dynamic processes. Firstly, a flexible multibody system dynamics model of PDTS is constructed to assess its kinematics, dynamics, and mechanics performance. The reaction moments and their effect on deformation and equivalent stress are obtained. Secondly, an optical model is developed to make the mechanical data available in optical analysis. The LOSJ and WFA are computed by using homogeneous coordinate transformation and ray tracing. Then, an engineering experiment and a numerical experiment are carried out to validate the accuracy of the model. The results show that the average relative error of LOSJ is 4.452%, the R 2 of WFA is greater than 0.991, and the RMSE is less than 6.921 × 10 –3 , which verifies the accuracy and reliability of the proposed method. Finally, the multidisciplinary performance of PDTS under a dynamic condition is analyzed and discussed. The causes of LOSJ and WFA are clarified, and mitigation strategies for these phenomena are proposed. The proposed method and coupling analysis results have reference significance for the multidisciplinary design optimization and optoelectronic control of PDTS.

Supramolecular chemistry offers an exciting opportunity to assemble materials with molecular precision. However, there remains an unmet need to turn molecular self-assembly into functional materials and devices. Harnessing the inherent properties of both disordered proteins and graphene oxide (GO), we report a disordered protein-GO co-assembling system that through a diffusion-reaction process and disorder-to-order transitions generates hierarchically organized materials that exhibit high stability and access to non-equilibrium on demand. We use experimental approaches and molecular dynamics simulations to describe the underlying molecular mechanism of formation and establish key rules for its design and regulation. Through rapid prototyping techniques, we demonstrate the system’s capacity to be controlled with spatio-temporal precision into well-defined capillary-like fluidic microstructures with a high level of biocompatibility and, importantly, the capacity to withstand flow. Our study presents an innovative approach to transform rational supramolecular design into functional engineering with potential widespread use in microfluidic systems and organ-on-a-chip platforms. Self-organising systems have huge potential in device design and fabrication; however, demonstrations of this are limited. Here, the authors report on a combination of disordered proteins and graphene oxide which allows spatio-temporal patterning and demonstrate the fabrication of microfluidic devices.

Earthquake swarms attributed to subsurface fluid injection are usually assumed to occur on faults destabilized by increased pore-fluid pressures. However, fluid injection could also activate aseismic slip, which might outpace pore-fluid migration and transmit earthquake-triggering stress changes beyond the fluid-pressurized region. We tested this theoretical prediction against data derived from fluid-injection experiments that activated and measured slow, aseismic slip on preexisting, shallow faults. We found that the pore pressure and slip history imply a fault whose strength is the product of a slip-weakening friction coefficient and the local effective normal stress. Using a coupled shear-rupture model, we derived constraints on the hydromechanical parameters of the actively deforming fault. The inferred aseismic rupture front propagates faster and to larger distances than the diffusion of pressurized pore fluid.

Which products should a firm offer based on its customers’ preferences? This is the question posed in the problem of product line design, a well-studied and notoriously difficult problem that is central in marketing science. In “Exact First-Choice Product Line Optimization” by Dimitris Bertsimas and Velibor V. Mišić, the authors propose a new approach for solving this problem when segments of customers choose products according to a ranking. They propose a new mixed-integer optimization model of the problem, which they show to be tighter than prior formulations, and a solution approach based on Benders decomposition, which exploits the surprising fact that the subproblem can be solved efficiently for both integer and fractional master solutions. A well-known product line instance based on a conjoint data set of over 3,000 products and 300 respondents, which required a week of computation time to solve in prior work, is solved by the authors’ approach in just over 10 minutes. A fundamental problem faced by firms is that of product line design: given a set of candidate products that may be offered to a collection of customers, what subset of those products should be offered to maximize the profit that is realized when customers make purchases according to their preferences? In this paper, we consider the product line design problem when customers choose according to a first-choice rule and present a new mixed-integer optimization formulation of the problem. We theoretically analyze the strength of our formulation and show that it is stronger than alternative formulations that have been proposed in the literature, thus contributing to a unified understanding of the different formulations for this problem. We also present a novel solution approach for solving our formulation at scale, based on Benders decomposition, which exploits the surprising fact that Benders cuts for both the relaxation and the integer problem can be generated in a computationally efficient manner. We demonstrate the value of our formulation and Benders decomposition approach through two sets of experiments. In the first, we use synthetic instances to show that our formulation is computationally tractable and can be solved an order of magnitude faster for small- to medium-scale instances than the alternate, previously proposed formulations. In the second, we consider a previously studied product line design instance based on a real conjoint data set, involving over 3,000 candidate products and over 300 respondents. We show that this problem, which required a week of computation time to solve in prior work, is solved by our approach to full optimality in approximately 10 minutes. The e-companion is available at https://doi.org/10.1287/opre.2018.1825 .

The operational stability of power transmission line inspection robots (PTLIRs) is severely challenged by wind-induced structural sway, while conventional vibration suppression methods are difficult to apply due to strict weight constraints. This study proposes and validates a novel zero-additional-mass vibration suppression strategy based on an integrated dynamic vibration absorber (DVA). Its key innovation lies in repurposing the robot’s existing batteries and electrical components as the DVA mass, eliminating the extra weight of traditional absorbers. First, a wind disturbance model was developed to provide dynamic loading. Then, a dynamic model of the PTLIR with the integrated DVA was established using Lagrange’s equations, and the DVA parameters were optimized via fixed-point theory. Subsequently, the effectiveness of the design was evaluated through numerical simulations and laboratory experiments. Results show that the DVA significantly suppresses vibrations under all conditions, reducing the root mean square (RMS) of wind-induced swing angles by up to 34.13% in simulations. Comparative analysis confirms that this lightweight design achieves higher intrinsic vibration suppression efficiency than heavier conventional DVAs. By effectively balancing vibration control and lightweight design, this study provides a practical, robust, and experimentally validated solution for enhancing the operational stability of PTLIRs and other weight-sensitive mobile robots.

The majority of approaches to product line design that have been proposed by marketing scientists assume that the underlying choice model that describes how the customer population will respond to a new product line is known precisely. In reality, however, marketers do not precisely know how the customer population will respond and can only obtain an estimate of the choice model from limited conjoint data. In this paper, we propose a new type of optimization approach for product line design under uncertainty. Our approach is based on the paradigm of robust optimization where, rather than optimizing the expected revenue with respect to a single model, one optimizes the worst-case expected revenue with respect to an uncertainty set of models. This framework allows us to account for parameter uncertainty, when we may be confident about the type of model structure but not about the values of the parameters, and structural uncertainty, when we may not even be confident about the right model structure to use to describe the customer population. Through computational experiments with a real conjoint data set, we demonstrate the benefits of our approach in addressing parameter and structural uncertainty. With regard to parameter uncertainty, we show that product lines designed without accounting for parameter uncertainty are fragile and can experience worst-case revenue losses as high as 23%, and that the robust product line can significantly outperform the nominal product line in the worst case, with relative improvements of up to 14%. With regard to structural uncertainty, we similarly show that product lines that are designed for a single model structure can be highly suboptimal under other structures (worst-case losses of up to 37%), while a product line that optimizes against the worst of a set of structurally distinct models can outperform single model product lines by as much as 55% in the worst case and can guarantee good aggregate performance over structurally distinct models.

By means of two supramolecular systems—peptide amphiphiles engaged in hydrogen-bonded β-sheets, and chromophore amphiphiles driven to assemble by π -orbital overlaps—we show that the minima in the energy landscapes of supramolecular systems are defined by electrostatic repulsion and the ability of the dominant attractive forces to trap molecules in thermodynamically unfavourable configurations. These competing interactions can be selectively switched on and off, with the order of doing so determining the position of the final product in the energy landscape. Within the same energy landscape, the peptide-amphiphile system forms a thermodynamically favoured product characterized by long bundled fibres that promote biological cell adhesion and survival, and a metastable product characterized by short monodisperse fibres that interfere with adhesion and can lead to cell death. Our findings suggest that, in supramolecular systems, functions and energy landscapes are linked, superseding the more traditional connection between molecular design and function. The energy landscapes of supramolecular systems are linked to their functions, as demonstrated by the switching of the balance of competing interactions in self-assembling amphiphiles.

Dynamic response characteristics of the passive heave compensator with auxiliary gas bottles are investigated in this paper. A mathematical model of the passive heave compensator is developed which includes mechanics, hydraulics and pneumatics. The key innovation of the proposed model is that the thermodynamic model of gas exchange between the piston accumulator and the gas bottles is derived and discussed. Meanwhile, a one-dimensional model of the pipeline resistance effect is established to calculate the pressure drop across the oil pipeline. The proposed model is used to evaluate the different design parameters of the passive heave compensator for heavy lifting cranes. A study was conducted to investigate the influence of the design parameters on the effectiveness of the passive compensator to reduce the payload displacement. The simulation results indicated that substantial improvement may be possible by careful design parameter selection and optimization.

With an extreme load condition, the mooring system of a floating offshore wind turbine (FOWT) will be led to failure, such as mooring line breakage. However, the induced FOWT mooring line breakage in extreme gust still requires further study for design optimization in the future. In this paper, an aero-hydro-cable-servo time domain coupled simulation have been carried out of a NREL’s 5 MW OC4-DeepCwind semi-submersible type FOWT for investigate the mooring system response under extreme coherent gust with direction change (ECD) condition. The platform is assumed to be installed at 50 m depth location in the South China Sea. The practical ECD is simulated by a fast conversion between two wind conditions with different mean wind speeds and wind direction. In addition, the gust characteristics that can generate snap tension of mooring lines were identified, and the consequence of the induced ECD accident is investigated. ECD condition with rise time of 10 s is prone to cause a snap tension of the mooring line, and it may eventually lead to cascading mooring line breakage and potential catastrophic collision events.