Joint Genomic and Transcriptomic Analysis Reveals Candidate Genes Associated with Plumage Color Traits in Matahu Ducks.

Plumage color is a key trait for identifying waterfowl breeds with significant economic importance. A white-feathered group has recently emerged within the native Matahu duck population, presenting an opportunity for breeding new lines. However, the genetic basis for this plumage variation is still unknown, necessitating further research.

Massive Point Cloud Processing for Efficient Construction Quality Inspection and Control.

The construction of large-scale civil infrastructures requires massive spatiotemporal data to support the management and control of scheduling, quality control, and safety monitoring. Existing artificial-intelligence-based data processing algorithms rely heavily on experienced engineers to adjust the parameters of data processing, which is inefficient and time-consuming when dealing with huge datasets. Limited studies have compared the performance of different algorithms on a unified dataset.

Long-read sequencing reveals the effect of follicle-stimulating hormone on the mRNA profile of chicken granulosa cells from prehierarchical follicles.

Follicle selection is an important step in the laying process of chicken, which is closely related to the laying performance and fecundity of hens. Follicle selection mainly depends on the regulation of follicle-stimulating hormone (FSH) secreted by pituitary gland and the expression of follicle stimulation hormone receptor. To uncover the role of FSH in chicken follicle selection, in this study, we analyzed the changes in the mRNA transcriptome profiles of FSH-treated chicken granulosa cells from prehierarchical follicles by long-read sequencing Oxford Nanopore Technologies (ONT) approach.

Digital Twin-Based Risk Control during Prefabricated Building Hoisting Operations.

Prefabricated buildings have advantages when it comes to environmental protection. However, the dynamics and complexity of building hoisting operations bring significant safety risks. Existing research on hoisting safety risk lacks a real-time information interaction mechanism and lacks scientific control decision-making tools based on considering the correlation between safety risks.

Digital Twins-Based Impact Response Prediction of Prestressed Steel Structure.

Civil infrastructure O&M requires intelligent monitoring techniques and control methods to ensure safety. Unfortunately, tedious modeling efforts and the rigorous computing requirements of large-scale civil infrastructure have hindered the development of structural research. This study proposes a method for impact response prediction of prestressed steel structures driven by digital twins (DTs) and machine learning (ML).

Simulation of the Urban Space Thermal Environment Based on Computational Fluid Dynamics: A Comprehensive Review.

Rapid urbanization has made urban space thermal environment (USTE) problems increasingly prominent. USTE research is important for improving urban ecological environment and building energy consumption. Most studies on USTE research progress have focused on meteorological observations and remote sensing methods, and few studies on USTE are based on computational fluid dynamics (CFD).

Digital Twin-Based Safety Risk Coupling of Prefabricated Building Hoisting.

Safety management in hoisting is the key issue to determine the development of prefabricated building construction. However, the security management in the hoisting stage lacks a truly effective method of information physical fusion, and the safety risk analysis of hoisting does not consider the interaction of risk factors. In this paper, a hoisting safety risk management framework based on digital twin (DT) is presented.

Intelligent Control Method of Hoisting Prefabricated Components Based on Internet-of-Things.

Prefabricated buildings are widely used because of their green environmental protection and high degree of industrialization. However, in construction process, there are some defects such as small wireless network coverage, high-energy consumption, inaccurate control, and backward blind hoisting methods in the hoisting process of prefabricated components (PC). Internet-of-Things (IoT) technology can be used to collect and transmit data to strengthen the management of construction sites.

Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence.

In this study, to address the problems of multiple dimensions, large scales, complex tension resource scheduling, and strict quality control requirements in the tensioning process of cables in prestressed steel structures, the technical characteristics of digital twins (DTs) and artificial intelligence (AI) are analyzed. An intelligent tensioning of prestressed cables method driven by the integration of DTs and AI is proposed. Based on the current research status of cable tensioning and DTs, combined with the goal of intelligent tensioning, a fusion mechanism for DTs and AI is established and their integration to drive intelligent tensioning of prestressed cables technology is analyzed.

A Framework for an Indoor Safety Management System Based on Digital Twin.

With the development of the next generation of information technology, an increasing amount of attention is being paid to smart residential spaces, including smart cities, smart buildings, and smart homes. Building indoor safety intelligence is an important research topic. However, current indoor safety management methods cannot comprehensively analyse safety data, owing to a poor combination of safety management and building information.

Development of Intelligent Prefabs Using IoT Technology to Improve the Performance of Prefabricated Construction Projects.

Prefabrication (PC) projects have many advantages, such as cost and energy savings and waste reduction. However, some problems still exist that hamper the development of prefabrication projects. To improve PC project performance and advance innovation in construction, this study introduces an innovative method that incorporates Radio Frequency Identification (RFID) and Long Range (LoRa) technologies, sensor networks, the BIM model and cloud computing to automatically collect, analyze and display real-time information about PC components.

Wideband dynamic behavioral modeling of reflective semiconductor optical amplifiers using a tapped-delay multilayer perceptron.

In this paper, we propose a wideband dynamic behavioral model for a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in colorless radio over fiber (RoF) systems using a tapped-delay multilayer perceptron (TDMLP). 64 quadrature amplitude modulation (QAM) signals with 20 Msymbol/s were used to train, validate and test the model. Nonlinear distortion and dynamic effects induced by the RSOA modulator are demonstrated.

Digital predistortion for RSOAs as external modulators in radio over fiber systems.

Reflective semiconductor optical amplifiers (RSOAs) can be used as external modulators in radio over fiber (RoF) links due to their amplification and modulation characteristics and colorless property. The nonlinear distortion of RSOA, however, limits its dynamic range. In this paper we demonstrate digital predistortion (DPD) linearization techniques to improve the linearity of RSOA external modulators.