Modular Design Framework Research Articles

Evaluation of carbon sink and photovoltaic system carbon reduction along roadside space

As China's photovoltaic (PV) sector experiences rapid growth, the availability of land resources has become a pivotal policy focus, driving the need for comprehensive research and strategic planning for roadside PV initiatives. Utilizing a fuzzy multi-criteria decision-making approach, combined with GIS spatial analysis and a modular design framework, our study quantitatively compared the carbon reduction capabilities of PV systems against the carbon sequestration potential of various vegetative arrangements along the roadside space. The roadside space analysis modular considers a range of factors including topography, meteorology, and construction costs. We examined the spatial distribution of suitability for PV installation and vegetation establishment along the provincial expressway network in China. The results revealed that Inner Mongolia stood out as the frontrunner in carbon reduction potential within high-suitability zones for PV construction, achieving an impressive 4.845 million tons of carbon reduction—nearly four times greater than that of Shaanxi Province. In contrast, the carbon sequestration attributed to vegetation greening in areas less suited for PV development revealed a higher propensity in the southeastern provinces. Guangdong led the charge with an impressive annual carbon sequestration of 2.89 million tons. This was closely followed by Yunnan, Sichuan, Hebei, Guizhou, and Henan, each achieving carbon sequestration amounts exceeding 2 million tons. These results offer valuable quantitative support and practical recommendations for achieving low-carbon objectives in the construction of China's expressways.

Engineered poly(A)-surrogates for translational regulation and therapeutic biocomputation in mammalian cells

Here, we present a gene regulation strategy enabling programmable control over eukaryotic translational initiation. By excising the natural poly-adenylation (poly-A) signal of target genes and replacing it with a synthetic control region harboring RNA-binding protein (RBP)-specific aptamers, cap-dependent translation is rendered exclusively dependent on synthetic translation initiation factors (STIFs) containing different RBPs engineered to conditionally associate with different eIF4F-binding proteins (eIFBPs). This modular design framework facilitates the engineering of various gene switches and intracellular sensors responding to many user-defined trigger signals of interest, demonstrating tightly controlled, rapid and reversible regulation of transgene expression in mammalian cells as well as compatibility with various clinically applicable delivery routes of in vivo gene therapy. Therapeutic efficacy was demonstrated in two animal models. To exemplify disease treatments that require on-demand drug secretion, we show that a custom-designed gene switch triggered by the FDA-approved drug grazoprevir can effectively control insulin expression and restore glucose homeostasis in diabetic mice. For diseases that require instantaneous sense-and-response treatment programs, we create highly specific sensors for various subcellularly (mis)localized protein markers (such as cancer-related fusion proteins) and show that translation-based protein sensors can be used either alone or in combination with other cell-state classification strategies to create therapeutic biocomputers driving self-sufficient elimination of tumor cells in mice. This design strategy demonstrates unprecedented flexibility for translational regulation and could form the basis for a novel class of programmable gene therapies in vivo.

Modular design framework of an axisymmetric wrap-around thrust-optimized combined nozzle

This work develops a computational analysis framework of an axisymmetric two-stream nozzle for wrap-around combined cycle engines from the aspects of contour design methodology, design feasibility, and performance augmentation technology. This research proposes a modular design method that combines the inverse design for upstream turbojet/ramjet nozzles and the maximum thrust design for the collective mixing region based on the method of characteristics. An improved algorithm for the inviscid slip line is proposed on requirement to model the inevitable mixing layer between the two streams in mixing region. The validation and verification benchmarks confirm the robustness, accuracy, and effectiveness of the method from theoretical and practical perspective. The influences of the exit flow patterns and geometric conditions on the inverse design reveal its practicability boundaries, and it refines a direct judgment criterion with the verified credibility for the rational flow matching in the combined nozzle. The thrust and economic characteristics in relation to the flow patterns of upstream nozzle exits are further investigated. Results indicate that greater levels of linear exit flow angle distributions benefits both thrust coefficient and thrust–area ratio, with performance increments exceeding 6.35% and 43.76%, respectively, when the flowfield is transformed from the “shock-free” to “shock-induced” state.

PepVAE: Variational Autoencoder Framework for Antimicrobial Peptide Generation and Activity Prediction.

New methods for antimicrobial design are critical for combating pathogenic bacteria in the post-antibiotic era. Fortunately, competition within complex communities has led to the natural evolution of antimicrobial peptide (AMP) sequences that have promising bactericidal properties. Unfortunately, the identification, characterization, and production of AMPs can prove complex and time consuming. Here, we report a peptide generation framework, PepVAE, based around variational autoencoder (VAE) and antimicrobial activity prediction models for designing novel AMPs using only sequences and experimental minimum inhibitory concentration (MIC) data as input. Sampling from distinct regions of the learned latent space allows for controllable generation of new AMP sequences with minimal input parameters. Extensive analysis of the PepVAE-generated sequences paired with antimicrobial activity prediction models supports this modular design framework as a promising system for development of novel AMPs, demonstrating controlled production of AMPs with experimental validation of predicted antimicrobial activity.

Single-master/multi-slave haptic teleoperation: a force control scheme

PurposeThis paper aims to present a novel modular design framework for the haptic teleoperation of single-master/multiple-slave (SM/MS) systems with cooperating manipulators.Design/methodology/approachThe user commands the remote-leader robot and the slave remote robot follows the leader in a leader–follower formation. The remote-slave is purely force-controlled. A virtual model of the remote environment is introduced between the local and remote environments through simulation software. Locally generated motion inputs are transmitted to the remote environment through the virtual model. A haptic coupling is designed in the virtual environment and the haptic feedback is transmitted to the user along with the forces measured in the remote environment. The controllers proposed in this work are experimentally evaluated with experienced and inexperienced users.FindingsThe proposed haptic interaction model contributes to the total force feedback and smoothens the high-frequency signals occurring at the physical interaction in the remote environment. Experimental results show that the implemented controllers including the proposed haptic interaction improve the teleoperation performances in terms of trajectory tracking. Furthermore, pure force control of the remote-slave is shown to enhance the robustness of the teleoperation against external disturbances. Satisfactory teleoperation performances are observed with both experienced and inexperienced users.Originality/valueThe proposed SM/MS teleoperation system involves a multi-purpose virtual simulator and a purely force-controlled remote-slave manipulator in a modular cooperative configuration. The uniquely defined structure of the proposed haptic coupling is used in modeling the interaction between the local and remote manipulators on the one hand, and between cooperating remote manipulators on the other.

Modular Design Optimization using Machine Learning-based Flexibility Analysis

Recent studies on modular and distributed manufacturing have introduced a new angle to the traditional economies of scale that claim that large plants exhibit better efficiencies and lower costs. A modular design has several advantages, including higher flexibility of decisions, lower investment costs, shorter time-to-market, and adaptability to market conditions. While design flexibility is a widely studied concept in the process design, modular design provides an interesting new opportunity to the design optimization problem under demand variability. In this work, a framework for modular design under demand variability is proposed. The framework consists of two steps. First, the feasible region for each module is represented analytically with the help of the historical data or the data from a simulation using a classification technique. In the second step, the optimal design choice is obtained by integrating the classifier models built in the first step as constraints in the design optimization problem. The design optimization problem is first solved considering a single objective, i.e., minimizing the total cost or maximizing the flexibility. These two objectives are then addressed simultaneously using a multiobjective optimization framework that considers the tradeoff between maximizing the flexibility of design and minimizing the cost. Computational studies conducted using a case study of an air separation plant, demonstrate the efficacy of the proposed framework. Several advantages of using a modular design, as well as data-driven methods in the decision-making process in the design step, are discussed.

HILOIS THE APP: A DIGITAL PHOTO FRAME PLATFORM FOR FAMILIES TO SUPPORT A LOVED ONE WITH ALZHEIMER’S

While there are effective, standardized tests to help diagnose Alzheimer's, there is a paucity of effective, “last-mile” tools that can be deployed at the site of residence to collect observational data to monitor rate of cognitive decline.1 The Investigator is part of a team that stemmed from a University of Cincinnati Technology Accelerator program. In 2016, the team was awarded $30,000 to create a beta app focused on the family support issues for people with Alzheimer's. The team was also awarded $100,000 from Ohio's Third Frontier program. HiLois is a ‘smart’ photo frame that creates a closed-loop support framework using inexpensive tablets to share photos and messages from family. This methodology makes it possible for disconnected seniors to stay connected with their family's daily lives and feel more engaged.2 The app is designed to be easily adaptable to varied levels of cognitive functioning including a ‘brain teaser’ mode. HiLois collects observational data on the behavior and level of engagement that can be used for metrics to detect changes in cognitive function.3 The kinesthetic communication measures tabulated discrete responses (e.g. current mood) as well as accuracy and precision based on where the screen is touched in relation to an object. We call this ‘cognitivigilance’. The HiLois app is now available in the App store and Google Play at no cost. The modular design framework allows for customized versions of the app to support data collection in both the home and in facilities on a cohort sadly ignored by the digital revolution.

Modular and High-Resolution Channel State Information and Beam Management for 5G New Radio

This article provides an overview of key features pertaining to CSI reporting and beam management for the 5G New Radio (NR) currently being standardized in 3GPP. For CSI reporting, the modular design framework and high-resolution spatial information feedback offer not only flexibility in a host of use cases and deployment scenarios, but also improved average user throughput over state-of-the-art 4G LTE. To accommodate cellular communications in the milimeter-wave regime where a combination of analog and digital beamforming is typically used at both a base station and user equipment, beam management procedures such as measurement, reporting, and recovery are introduced. The utility and joint usage of these two features are demonstrated along with some potential upgrades for the next phase of 5G NR. Introduction

基于WPF的电机控制系统监控软件的设计与实现

电机控制系统是决定电动汽车性能优劣的核心，为了更加直观方便的观察和分析控制效果的优劣，并方便快捷的实现对控制参数的修改，使控制效果达到最佳，本文设计并实现了基于WPF的电机控制系统监控软件。软件采用C#编程，充分利用了WPF的多线程技术和数据绑定技术，为用户提供了友好的人机界面，实现了对电机控制系统参数的高速实时采样、实时显示、实时保存等功能，保证了对电机控制系统运行状态的实时监控。本文首先给出模块化的设计框架，并在此基础上对各个模块的设计方案进行了具体的介绍，然后详细阐述了软件中用到的多线程和数据绑定这两个关键技术，最后对软件运行效果进行了测试，给出了软件的运行效果图，通过测试，监控软件各部分功能满足设计的要求。 Motor control system is the key to determine the performance of electric vehicles. In order to ob-serve and analyze the effects of control more easily and to realize the modification of control pa-rameters more conveniently and quickly so that the optimal control effect can be reached, the pa-per has designed and realized the motor control system monitoring software based on WPF. The software uses C# programming and makes full use of the multithreading technology and data binding technology of WPF, so that it provides a friendly man-machine interface, and realizes the function of high-speed real-time sampling, real-time display and real-time storage of the parame-ters of the motor control system and ensures the real-time monitoring of the running state of the motor control system. Firstly, the paper gives a modular design framework, and on this basis, the detailed design scheme of each module is introduced. Then the two key technologies containing multithreading and data binding are elaborated in detail. Finally, the running effect of the software is tested and the performance of the test is given. Through the test, it proves that all functions of the monitoring software meet the requirements of the design.

Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages.

This article presents analyses of data from a pilot study in Nepal that was designed to provide an initial examination of the errors and costs associated with an innovative methodology for survey data collection. We embedded a randomized experiment within a long-standing panel survey, collecting data on a small number of items with varying sensitivity from a probability sample of 450 young Nepalese adults. Survey items ranged from simple demographics to indicators of substance abuse and mental health problems. Sampled adults were randomly assigned to one of three different modes of data collection: 1) a standard one-time telephone interview, 2) a "single sitting" back-and-forth interview with an interviewer using text messaging, and 3) an interview using text messages within a modular design framework (which generally involves breaking the survey response task into distinct parts over a short period of time). Respondents in the modular group were asked to respond (via text message exchanges with an interviewer) to only one question on a given day, rather than complete the entire survey. Both bivariate and multivariate analyses demonstrate that the two text messaging modes increased the probability of disclosing sensitive information relative to the telephone mode, and that respondents in the modular design group, while responding less frequently, found the survey to be significantly easier. Further, those who responded in the modular group were not unique in terms of available covariates, suggesting that the reduced item response rates only introduced limited nonresponse bias. Future research should consider enhancing this methodology, applying it with other modes of data collection (e. g., web surveys), and continuously evaluating its effectiveness from a total survey error perspective.

Radar Data Processing Software System Design Based on COM Technology

Radar data processing software is a complex system, which has been implemented with mixed language programming using Visual Studio .Net and Visual C++6.0. COM-based software architecture for radar data processing system is proposed in this paper. It provides modular design framework, and integrates modules developed with different programming language and ready-made modules. Firstly, introduce COM technology in brief, then design radar data processing software system framework, finally show the programming examples to explain how to define and refer the COM interfaces. The results show that using COM-based modular mixed language programming is an effective method to realize the radar data processing software system.

Fuzzy-Based Collaborative Modular Architecture for Medical Device Design and Development

The purpose of this project is to develop a modular architecture framework for the design and manufacture of medical devices. This modular framework aims to incorporate design variables and criteria that are unique to the medical domain to facilitate reliable operation, easier maintenance, and faster product development time. Central to this research effort is the need for inputs from the range of stakeholders. The specific goals for this effort are to determine design criteria by collaborating with users and manufacturers of medical equipment and literature search, to translate user inputs to specific design targets, to develop a preliminary modular design framework using multicriteria optimization methods, and to test a preliminary modular architecture using a simple medical device such as a glucometer. The importance of the research with respect to its application in the medical arena can be very significant. With the product interaction with humans, both on the manufacturing level and the user level, the issue of safety is paramount. Some of the other significant contributions are in the improvement of the following: product quality and reliability, product life cycle issues, and an enabler for the medical community.

Enabling distributed multi-disciplinary design of complex products: a knowledge based engineering approach

In this paper, it is discussed how knowledge based engineering has been exploited to develop a flexible design system, able to integrate a heterogeneous set of distributed discipline-specific design and analysis tools into a modular design framework. This system, called Design and Engineering Engine (DEE), demonstrated its capability to support designers in performing what-if studies and accelerate Multi-disciplinary Design and Optimisation (MDO), through the automation of those lengthy and repetitive activities typically hampering the design process. Design quality and innovation are also supported by enabling the use of high fidelity analysis tools in the early design phase.