Design System Research Articles

Deep learning enhancing guide RNA design for CRISPR/Cas12a-based diagnostics.

Rapid and accurate diagnostic tests are fundamental for improving patient outcomes and combating infectious diseases. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) Cas12a-based detection system has emerged as a promising solution for on-site nucleic acid testing. Nonetheless, the effective design of CRISPR RNA (crRNA) for Cas12a-based detection remains challenging and time-consuming. In this study, we propose an enhanced crRNA design system with deep learning for Cas12a-mediated diagnostics, referred to as EasyDesign. This system employs an optimized convolutional neural network (CNN) prediction model, trained on a comprehensive data set comprising 11,496 experimentally validated Cas12a-based detection cases, encompassing a wide spectrum of prevalent pathogens, achieving Spearman's ρ = 0.812. We further assessed the model performance in crRNA design for four pathogens not included in the training data: Monkeypox Virus, Enterovirus 71, Coxsackievirus A16, and Listeria monocytogenes. The results demonstrated superior prediction performance compared to the traditional experiment screening. Furthermore, we have developed an interactive web server (https://crispr.zhejianglab.com/) that integrates EasyDesign with recombinase polymerase amplification (RPA) primer design, enhancing user accessibility. Through this web-based platform, we successfully designed optimal Cas12a crRNAs for six human papillomavirus (HPV) subtypes. Remarkably, all the top five predicted crRNAs for each HPV subtype exhibited robust fluorescent signals in CRISPR assays, thereby suggesting that the platform could effectively facilitate clinical sample testing. In conclusion, EasyDesign offers a rapid and reliable solution for crRNA design in Cas12a-based detection, which could serve as a valuable tool for clinical diagnostics and research applications.

Accelerating the design of lattice structures using machine learning

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

A wide-band high gain beamsteerable variable patch reflectarray antenna for THz applications

This article proposed a compact size, high gain, wideband reflectarray antenna for THz and 6 G applications. To enhance the aperture efficiency and gain, a single layer L-shape delay line-based unit cell with a size of 0.45λ0 is adopted. The λ0 is the free space wavelength at 1.35 THz. The SiO2 substrate is sandwiched between L- shape delay line and the ground plane of gold. The unit cell, equivalent parallel RLC circuit modelled with gap coupled capacitance is also presented which is validated through the Ansys-High Frequency Structure Simulator (HFSS) and Advanced Design System (ADS). The dimension of the RA is 3 mm having 610 elements. It is excited by the pyramidal horn antenna at an optimum distance (F/D =1.21). The optimum ratio (F/D) is calculated with the help of the cosq model at −10 dB edge taper. The operating bandwidth is obtained 46.15 % from 1 to 1.6 THz. The reflection phase and magnitude are 500° and 3.93 dB at 1.35 THz. It is adjusted by varying the length of the delay line. The maximum aperture efficiency and realized gain are 35 % and 28 dBi respectively. The Side lobe level is −15.5 dB and the Co-Cross polarization level is below −30 dB.

Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.

Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size. The Bureau of Communicable Disease's systems have quickly detected outbreaks of salmonellosis, legionellosis, shigellosis, and COVID-19. This tutorial details system design considerations, including geographic and temporal data aggregation, study period length, inclusion criteria, whether to account for population size, network location file setup to account for natural boundaries, probability model (eg, space-time permutation), day-of-week effects, minimum and maximum spatial and temporal cluster sizes, secondary cluster reporting criteria, signaling criteria, and distinguishing new clusters versus ongoing clusters with additional events. We illustrate how to support health equity by minimizing analytic exclusions of patients with reportable diseases (eg, persons experiencing homelessness who are unsheltered) and accounting for purely spatial patterns, such as adjusting nonparametrically for areas with lower access to care and testing for reportable diseases. We describe how to fine-tune the system when the detected clusters are too large to be of interest or when signals of clusters are delayed, missed, too numerous, or false. We demonstrate low-code techniques for automating analyses and interpreting results through built-in features on the user interface (eg, patient line lists, temporal graphs, and dynamic maps), which became newly available with the July 2022 release of SaTScan version 10.1. This tutorial is the first comprehensive resource for health department staff to design and maintain a reportable communicable disease outbreak detection system using SaTScan to catalyze field investigations as well as develop intuition for interpreting results and fine-tuning the system. While our practical experience is limited to monitoring certain reportable diseases in a dense, urban area, we believe that most recommendations are generalizable to other jurisdictions in the United States and internationally. Additional analytic technical support for detecting outbreaks would benefit state, tribal, local, and territorial public health departments and the populations they serve.

Hydraulic characterization of a hybrid aerated vertical and horizontal treatment wetland

Characterizing the performance of any treatment wetland (TW) system requires a fundamental understanding of the hydraulic behavior of the system. In aerated treatment, the air supply increases complexity, and the internal behavior of TWs can vary according to the adopted aeration strategy. Understanding these changes can provide insights into an optimized operation for aerated TWs. In this sense, the present work characterizes the hydraulics of a hybrid vertical and horizontal aerated TW through parallel tracer testing under different aeration strategies (varying aeration duration and aeration between the different compartments). The tracer test was conducted using amino-G acid and salt on a pilot scale system and measured at the outlet and inside the system. These results are subsequently compared to a full-scale system of a similar design to assess the validity of the results on a larger scale. The results allowed a characterization of actual retention time, the estimated number of tanks-in-series (NTIS), the volume of dead zones, and the identification of the hydraulic behavior under different aeration conditions. The results indicated that decreasing aeration duration led to more heterogeneity within the filter, the aeration on the primary filter plays an important role in mixing, and the pilot scale results can be upscaled for a larger scale. It also highlighted the impact of aeration in the different compartments of this hybrid aerated wetland system, which can contribute to an accurate characterization of specific pollutant removal kinetics.

Integrating transformers and many-objective optimization for drug design

BackgroundDrug design is a challenging and important task that requires the generation of novel and effective molecules that can bind to specific protein targets. Artificial intelligence algorithms have recently showed promising potential to expedite the drug design process. However, existing methods adopt multi-objective approaches which limits the number of objectives.ResultsIn this paper, we expand this thread of research from the many-objective perspective, by proposing a novel framework that integrates a latent Transformer-based model for molecular generation, with a drug design system that incorporates absorption, distribution, metabolism, excretion, and toxicity prediction, molecular docking, and many-objective metaheuristics. We compared the performance of two latent Transformer models (ReLSO and FragNet) on a molecular generation task and show that ReLSO outperforms FragNet in terms of reconstruction and latent space organization. We then explored six different many-objective metaheuristics based on evolutionary algorithms and particle swarm optimization on a drug design task involving potential drug candidates to human lysophosphatidic acid receptor 1, a cancer-related protein target.ConclusionWe show that multi-objective evolutionary algorithm based on dominance and decomposition performs the best in terms of finding molecules that satisfy many objectives, such as high binding affinity and low toxicity, and high drug-likeness. Our framework demonstrates the potential of combining Transformers and many-objective computational intelligence for drug design.

From shipwreck to seaworthy: A digital reconstruction of the Ma'agan Mikhael B ship

A digital 3D model of the Ma'agan Mikhael B ship was developed by resourcing excavation data, iconographic representations, and relevant documentation. A computer-aided design system was used to digitally replicate the ship, also yielding 3D prints used to refine the results. The digital model also served to test amphora cargo loading scenarios, considering maritime dictates of ship stability, accessibility, and commerce. A standard maritime-engineering analysis of stability and strength, and computational fluid dynamics analyses were performed on the digital model to evaluate hull resistance and the power of the ship's lateen sail. The simulations demonstrated that the fully loaded merchantman was seaworthy and made satisfactory speed over ground.

Advancing geological modelling and geodata management: a web-based system with AI assessment in Singapore

ABSTRACT This paper outlines the development and deployment of the Geodata Modelling and Management System (GEM2S) in Singapore. GEM2S offers a sophisticated web-based platform for visualising and interacting with 3D geological models of Singapore. Beyond basic visualisation and interaction, GEM2S provides advanced features for geodata management, including the functionality to upload new borehole data with AI assessment and to integrate geophysical results. The paper begins by elucidating the data processing procedures, which involve extracting data from electronic site investigation records. Additionally, common data errors for cleaning and validation purposes are summarised. Subsequently, the paper presents the 3D geological modelling process and results. The architecture of the web-GIS geodata management system is detailed, outlining the data flow and functions for interactive queries. Furthermore, the paper investigates two AI-based prototypes for quality assessment of newly acquired borehole data. Incorporating virtual boreholes generated from the geophysics effectively enhances the quality of the resulting geological model. GEM2S can serve as a comprehensive and user-friendly platform, making it a valuable system for underground project design and a foundational database for future subsurface planning in Singapore.

Design and hydroponic systems

In facing the complexity of the challenge posed by urban growth and increasing world population, design disciplines are called upon to question new strategies to mitigate their impact on biodiversity and the food production system. In this context, hydroponics represents a viable solution to help re-establish a connection with nature and to create productive greenery within the most diverse contexts. Although the potential of these systems is widely discussed from various perspectives, there is a lack of comparative and evaluative studies illustrating their potential for designers. Through the analysis of literature and case studies focusing on hydroponic crops, we intend to investigate the possibilities and criticalities offered not only for food production but also as a means to improve degraded contexts, trigger social innovation movements and restore identity and livelihood to people and territories. By comparing projects implemented at different latitudes and the transfer of solutions from one context to another, we intend to provide Design with virtuous models, integrating perspectives from the Global North and South, for a better understanding and new project management of these systems.

Satisfaction with Rooftop Photovoltaic Systems and Feed-in-Tariffs Effects on Energy and Environmental Goals in Jordan

Rooftop photovoltaic (RPV) systems are valuable clean-energy-efficient technology that facilitates the transition toward energy sustainability in residential buildings. Hence, the government in Jordan implemented the feed-in-tariffs (FiT) policy to motivate residents’ willingness to install RPV systems. However, the quality of RPV products and services is a key determinant of social acceptance to install RPV systems. Hence, manufacturers and suppliers are working closely with adopters to design and manufacture RPV systems that meet or exceed their expectations. Still, there is a need to develop a quantitative assessment to examine the effects of this FiT policy and the quality of RPV systems on energy security. This study, therefore, develops a system dynamics model to examine the effects of the FiT policy and the quality of RPV products and services on social acceptance to install RPV systems. To achieve this objective, several hypotheses were established related to the main model factors, including the quality of services, complaint reduction, performance ratio, payback period and warranty, and FiT price, with a willingness to install RPV systems. Then, a system dynamics model was constructed. The simulation results reveal the significant factor that impacts energy goals. Moreover, from the end of the year 2030 to the end of 2050, RPV installations, generated power, and CO2 emission reductions are expected to increase from 0.681 GW to 72.83 GW, from 1.07 to 125.74 TWh, and from 0.680 to 79.59 million tons of CO2, respectively. Optimization was performed to maximize the three objectives under the uncertainty of key model variables. The optimal factor values can significantly increase the current energy goals by about 20%. In conclusion, collecting, analyzing, and evaluating adopter input and feedback on RPV systems regarding their design and technology and manufacturing and the post-services of RPV systems significantly influence energy sustainability in residential buildings. In addition, government support through investing in the FiT policy can boost RPV installations in residential buildings.

Logistics Network Design System in Eu Through Modern Modelling Techniques: Establishing Strong Transport Links to Improve Foreign Economic Relations

Logistics Network Design System in Eu Through Modern Modelling Techniques: Establishing Strong Transport Links to Improve Foreign Economic Relations

Economics of Various Treatments of Vermicompost on Growth and Yield Attributes of Pea (Pisum sativum L.) Based Intercropping System

Intercropping is an ecologically friendly technique that can increase the sustainability of farming systems, whilst considered as low input systems. An experiment was conducted at the vegetable farm, Department of Vegetable Science, College of Horticulture and Forestry, Jhalrapatan City, Jhalawar during the rabi season from November, 2022 to April 2023. The experiment comprised fifteen treatment combinations having three levels each of vermicompost (0, 2.5, and 5 ton/ha) and five levels of different intercropping system (Sole Pea, Sole Garlic, Pea + Garlic 1:1, 2:1, 2:2) in Factorial Randomized Block Design with three replications. The result of the present investigation showed that the effect of vermicompost and intercropping system on individually and combined had significant effect on the economic related attributes. The interaction effect of the Vermicompost and Intercropping system significantly increased the economic attributes such as maximum gross return (361172 ₹ ha-1), net profit (272244 ₹ ha-1) and B:C ratio (4.06) was recorded under treatment V2I5 (Vermicompost @5ton/ha+ Pea+ Garlic 2:2) as compared to other treatment, respectively. The interaction effect of vermicompost and Intercropping system also significantly increased pea equivalent yield (166.040 q/ha), land equivalent ratio (1.25) under treatment V2I5 (Vermicompost@5ton/ha+ Pea+ Garlic 2:2), respectively.

Application of innovative mechatronic systems in product design, development and production

The application of mechatronic systems is very topical today. Today, mechatronic systems are applied in all areas, so today systems are also being developed that enable fast and simple production of products. Today's mechatronic systems that are supported by computers enable the development, easy and fast production of prototypes and products. Two technologies that are widely used are 3D printers and scanners. 3D printers allow a virtually developed product to be turned into a physical model, while the application of a 3D scanner allows a physical model to be turned into a virtual model on a computer. In this paper, a comparative analysis of two types of printers and their software was performed. They differ according to their working principle. In addition to the working principle, an example of the difference between the software used to write the G code to drive the printing process of 3D printer.

Approach to automating the construction and completion of ontologies in a scientific subject field

Domain ontologies facilitate the organization, sharing, and reuse of subject areas. Building a software ontology is labor-intensive and time-consuming. In the process of obtaining a software ontology, it is required to analyze a huge number of scientific publications relevant to the software being modeled. The process of ontology replenishing with information from a huge number of scientific publications can be facilitated and accelerated through the use of lexical-syntactic patterns of ontological design. In this paper, we consider the possibility of automated construction of scientific subject area ontologies based on a heterogeneous patterns system of ontological design. This system includes ontological design patterns and is intended for ontology developers. System also includes automatically built lexical and syntactic patterns, which help to automatic replenishment of the ontology with information extracted from natural language texts.

Protein engineering enables a soakable crystal form of human CDK7 primed for high-throughput crystallography and structure-based drug design

Cyclin dependent kinase 7 (CDK7) is an important therapeutic kinase best known for its dual role in cell cycle regulation and gene transcription. Here, we describe the application of protein engineering to generate constructs leading to high resolution crystal structures of human CDK7 in both active and inactive conformations. The active state of the kinase was crystallized by incorporation of an additional surface residue mutation (W132R) onto the double phosphomimetic mutant background (S164D and T170E) that yielded the inactive kinase structure. A novel back-soaking approach was developed to determine crystal structures of several clinical and pre-clinical inhibitors of this kinase, demonstrating the potential utility of the crystal system for structure-based drug design (SBDD). The crystal structures help to rationalize the mode of inhibition and the ligand selectivity profiles versus key anti-targets. The protein engineering approach described here illustrates a generally applicable strategy for structural enablement of challenging molecular targets.

Base Isolation and Energy Dissipating System in Earthquake Resistant Building Design

The utilization of base isolation is a crucial strategy for enhancing seismic resilience in structures. The method involves installing isolators and energy-absorbing devices beneath a building's superstructure to mitigate the destructive effects of earthquakes. When base isolation is implemented in a building, it not only makes the structure stronger and more stable, but also helps to safeguard lives and properties. This technique is particularly valuable for seismic retrofitting of historical buildings. In the present study, software called simulation of seismic isolation systems in structural analysis is employed, considering isolator characteristics, whether they exhibit nonlinear or equivalent linear behavior. Adhering to the IS 1893:2016 Code, the analysis utilized the SAP 2000 software package. A study was carried out to compare the effectiveness of base isolation systems versus fixed-base buildings in dealing with seismic activity. The study focused on analyzing various seismic indicators such as joint displacement, shear force, bending moment, building torsion, and the period of natural frequency. Results showed that models utilizing base isolation systems had significantly higher base shear values than those with a fixed-base building configuration. However, there was a significant 35% reduction in story shear values for the rubber isolation system and a 40% decrease for the friction pendulum model. Additionally, there was a 25% reduction in story drift for the rubber base model and a 30% decrease for the friction pendulum model. The friction pendulum model demonstrated the most effective control of these parameters across various seismic zone conditions. Key words: The topic of discussion pertains to Seismic Isolation with Rubber Bearing System and the Friction Pendulum Technique. Additionally, it includes SAP2000 Analysis, Story Drift Measurement, and Shear Force Evaluation in relation to these techniques.

System-Level Magnetic Interference Modeling in Electrified Monorail System for Track-Side Safety Design

System-Level Magnetic Interference Modeling in Electrified Monorail System for Track-Side Safety Design

Innovation and Digital Transformation in the Business Environment: A Case Study on Analyzing the Impact on Organizational Performance in a CAD Company

Abstract This article makes an exploratory attempt to study the impact of implementing a computer-aided design (CAD) system on a Romanian company. The firm has been established in 1998 and it is based on Baia Mare (Maramures), Romania. It is the commercial administrator of the CAD/CAM Technology Support Center. This center was a project initiated within the Maramureş Center for the Development of Small and Medium Enterprises (SMEs), and it received funding from the PHARE FIDEL program, an European Funded program that supported at that time the development of SMEs). Using a multifaced approach encompassing semi-structural interviews and financial analysis data, the results show integration of innovative CAD technologies yields substantial gains for operational efficiency. For instance, most of the KPIs associated with production have improved: the time required to complete one cycle of production has decreased by 15%, from an average of 20 hours to 17 hours per unit and the efficient use of materials has increased by 10% resulting in cost savings. This research shows how Romanian companies can adopt CAD technologies and improve their activities.

Integrated floating wind farm layout design and mooring system optimization to increase annual energy production

As we cluster wind turbines in wind farms to gain energy from sites with high wind speeds, wake losses occur within the wind farm. Wake loss is a term used to describe the lower energy production of a downwind turbine that is totally or partially in the wake of an upwind turbine. To decrease wake losses inside the wind farm, the wind farm’s layout is optimized. However, a variety of factors constrain the wind farm layout optimization, such as the size of the lease area relative to the number of turbines to be placed, or the shape of the lease area. Therefore, many wind farms end up with a regular grid layout, such as the Horns Rev 1 wind farm in the North Sea. The ability of a floating offshore wind turbine (FOWT) to change its position based on the wind direction and its mooring system design presents an opportunity to further decrease wake losses in floating wind farms. In this work, we integrate the design of the FOWT mooring systems with the floating wind farm layout design with the goal of increasing the farm’s annual energy production. We use the Horns Rev 1 wind farm as a case study to demonstrate our method. The results show that allowing the FOWT to relocate can decrease wake losses up to 18%. Moreover, the newly developed mooring systems are less stiff and therefore allow larger motion of the FOWT; hence, the material cost of the mooring system decreases by an estimated 17%.

Analisis Regulasi Manajemen Sistem Keselamatan Instalasi Nuklir dalam Mewujudkan Ketahanan Energi Indonesia

The rising energy demand in Indonesia has led to the planning of Nuclear Power Plants (NPP) as a sustainable solution, with implementation targeted around 2030. The government has emphasized the need for strict regulations, especially in safety management, reinforced by lessons from the Fukushima incident in Japan. This study underscores the critical role of regulatory analysis in the safety management of nuclear installations, which is essential for achieving energy security in Indonesia. By evaluating regulatory design and management system implementation, the research aims to identify key steps to support a safety culture in nuclear installations. Adopting a qualitative approach focused on policy analysis, this study evaluates aspects of Safety Management System Regulations in Nuclear Installations for Indonesia's Energy Security. The findings highlight the importance of structured management systems to enhance nuclear safety, providing a solid foundation for energy security. Strengthening regulations and implementing a systematic approach will ensure that Indonesia’s nuclear installations meet high safety standards, contributing positively to the country’s energy security.