Piezoelectric materials are capable of transforming mechanical strain and vibration energy into electrical energy. This property allows opportunities for implementing renewable and sustainable energy ...through power harvesting and self-sustained smart sensing in buildings. As the most common construction material, plain cement paste lacks satisfactory piezoelectricity and is not efficient at harvesting the electrical energy from the ambient vibrations of a building system. In recent years, many techniques have been proposed and applied to improve the piezoelectric capacity of cement-based composite, namely admixture incorporation (e.g. lead zirconate titanate, barium zirconate titanate, carbon particles, and steel fibers) and physical treatments (e.g. thermal heating and electrical field application). The successful application of piezoelectric materials for sustainable building development not only relies on understanding the mechanism of the piezoelectric properties of various building components, but also the latest developments and implementations in the building industry. Therefore, this review systematically illustrates research efforts to develop new construction materials with high piezoelectricity and energy storage capacity. In addition, this article discusses the latest techniques for utilizing the piezoelectric materials in energy harvesters, sensors, and actuators for various building systems. With advanced methods for improving the cementitious piezoelectricity and applying the material piezoelectricity for different building functions, more renewable and sustainable building systems are anticipated.
Awkward postures in construction activities pose substantial hazards in both instantaneous injuries and long-term work-related musculoskeletal disorders (WMSDs). Posture recognition using motion ...capturing systems shows promising potential in avoiding and minimizing workers' exposure to awkward postures. However, current motion capturing systems require huge computational resources and complicated processes to recognize postures in construction tasks. To address this issue, we proposed an abstract and efficient motion tensor decomposition approach to compress and reorganize the motion data. Together with a multi-classification algorithm, the proposed approach is able to efficiently and accurately differentiate various postures. To validate the approach, we employed a system based on inertial measurement units (IMUs) to examine two sample activities composed of sequencing postures. The results indicate the proposed approach is able to provide sufficient recognition accuracy with less computation power and memory. Also, the idea of tensorization and tensor decomposition in this paper is extendable to other studies in the construction industry.
•A supervised motion tensor decomposition approach•Six postures and two activities were examined.•Motion tensor was developed to compress motion matrices.•A wearable wireless motion capture system was used.•The proposed posture identification method can help improve construction safety.
•Social network analysis is a valid approach to assess green spaces connectivity.•Case studies suggest more green spaces not necessarily mean higher accessibility.•Accessibility and connectivity can ...be improved through network optimization.
In the construction environment with high attention requirements, distraction is the main cause of unsafe behavior and safety performance degradation. However, few studies have focused on ...distraction's cognitive features and how to monitor it objectively in the construction workplace. To fill the research gap, the present study examined the correlation between distraction and brain activity using an Electroencephalography (EEG) device, intending to provide an approach for objectively monitoring worker distraction. In the simulated hazards identification activity, sustained attention to response task and dual-task paradigms have been employed to induce distraction combined with noise interference. Twenty-seven subjects participated in the experiment to identify whether a hazardous opening exists or not in the workplace in the shown images. The EEG waves were recorded and divided into two groups according to task performance: focused and distracted. Through feature calculation and extraction, it was found that beta and gamma powers in the left temporal and right pre-frontal cortex can distinguish these two statuses, particularly in channels T7 and AF4. The indicators can be considered as an objective evaluation of an individual's sustained attention and attention failures. The developed indicators located in specified brain zones can also be used as a reference for attention training. By providing safety managers with attention status about the workers in high-risk workplaces, distraction detection contributes to control and regulate work error and improper operation, which can extend to apply in other attentive jobs like drivers, pilots, surgeons, and lifeguards.
•An objective distraction monitoring method is proposed.•EEG frequency features can distinguish focused and distracted state.•Feasibility of distraction monitoring method is validated by SVM classification.•Classification performance of channel T7 and AF4 outperformed other electrodes.
•We examine the validity of Wi-Fi events as an indicator of energy load changes.•The Wi-Fi connection events have a positive relationship with energy load increase.•The number of Wi-Fi connections ...has no direct correlation to building energy load.
Providing energy-consumption feedback has proven to be an effective approach for changing people's behavior and has led to significant energy-consumption reductions in residential buildings. However, providing feedback in commercial and educational buildings is challenging because of the difficulty in tracking occupants’ behaviors and their corresponding energy usage – especially for temporary occupants. To make providing such feedback possible in commercial and educational buildings, this paper presents the framework for a coupled system that uses residents’ wireless devices’ Wi-Fi connection and disconnection events to detect occupancy and then benchmarks energy loads against these events to monitor the energy use of occupants. A preliminary experiment implemented the proposed approach in a small-scale educational building to ascertain whether Wi-Fi network connection/disconnection events can be an effective indicator of energy load variation. The experiment's results confirmed the positive relationship between the Wi-Fi connection events and energy load increase; these results also indicated that the number of Wi-Fi connections cannot directly represent the magnitude of the energy load. A validation test was also conducted to assess the robustness of the coupled system in terms of the impact of users’ schedules (AM/PM), their length of stay (long-term/temporary), and the locations of access points.
Histone modifications have critical roles in regulating the expression of developmental genes during embryo development in mammals. However, genome-wide analyses of histone modifications in ...pre-implantation embryos have been impeded by the scarcity of the required materials. Here, by using a small-scale chromatin immunoprecipitation followed by sequencing (ChIP-seq) method, we map the genome-wide profiles of histone H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 trimethylation (H3K27me3), which are associated with gene activation and repression, respectively, in mouse pre-implantation embryos. We find that the re-establishment of H3K4me3, especially on promoter regions, occurs much more rapidly than that of H3K27me3 following fertilization, which is consistent with the major wave of zygotic genome activation at the two-cell stage. Furthermore, H3K4me3 and H3K27me3 possess distinct features of sequence preference and dynamics in pre-implantation embryos. Although H3K4me3 modifications occur consistently at transcription start sites, the breadth of the H3K4me3 domain is a highly dynamic feature. Notably, the broad H3K4me3 domain (wider than 5 kb) is associated with higher transcription activity and cell identity not only in pre-implantation development but also in the process of deriving embryonic stem cells from the inner cell mass and trophoblast stem cells from the trophectoderm. Compared to embryonic stem cells, we found that the bivalency (that is, co-occurrence of H3K4me3 and H3K27me3) in early embryos is relatively infrequent and unstable. Taken together, our results provide a genome-wide map of H3K4me3 and H3K27me3 modifications in pre-implantation embryos, facilitating further exploration of the mechanism for epigenetic regulation in early embryos.
In this work, the hot deformation behaviors of Udimet 720Li superalloy with the microstructures of coarse grain, fine grain and mixed grain were studied contrastively by means of various ...microstructural analysis approaches. Based on the experimental results, in single-phase region, dynamic recrystallization (DRX) mainly occurs along the boundaries, while a decrease in the grain size accelerates the DRX kinetics. In two-phase region, the DRX on grain boundaries of coarse grain is limited, but intragranular continuous sub-grain rotation and accumulation takes effect remarkably; no DRX occurs in fine grain, but local migration of grain boundaries and deformation of γ′ independently occur. The coarse-grain and fine-grain portions of mixed grain perform in a similar way of the coarse grain and fine grain respectively.
As a sector associated with high injury and fatality rates, the construction industry requires constant caution with regard to construction laborers during project execution. Different from people in ...other industries, construction workers are less sensitive to hazards because of their long-term exposure to risks. Therefore, maintaining construction workers' vigilance and monitoring their attention levels are critical to successful safety management practices. However, current attention-assessing approaches are post hoc and subjective and difficult to implement in construction practice. To address these issues, we propose a wireless and wearable electroencephalography (EEG) system to quantitatively and automatically assess construction workers' attention level through processing human brain signals. To validate the proposed system, we conducted an on-site experiment to analyze the EEG signal patterns when construction workers avoid different obstacles in their tasks. The results suggest EEG signal properties such as frequency, power spectrum density, and spatial distribution can effectively reflect and quantify the construction workers' perceived risk level. Especially, lower gamma frequency bands and the frontal left EEG cluster provide the most direct and observable indications of their vigilance states. These conclusions could facilitate the future implementation of wearable EEG devices through data filtering and channel optimization.
•Wearable EEG sensors were used to monitor construction workers' perceived risk.•Topographical maps show the signal patterns at various vigilance levels.•On site experiment was conducted to validate the results.•Vigilance states can be assessed through EEG band powers.
► A comprehensive survey of 7 multivariate methods applied in multimodal fusion. ► Comparison of the assumptions, goals, data reduction, data input for each model. ► Classifying methods in two ways: ...(1) the need of priori/input data. (2) optimization priority. ► Providing examples in brain imaging data application for each method. ► Offer a reference that helps readers understand the trade-offs of various methods.
The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multi-modal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous multimodal fusion reports, mostly fMRI with other modality, which were performed with or without prior information. A table for comparing optimization assumptions, purpose of the analysis, the need of priors, dimension reduction strategies and input data types is provided, which may serve as a valuable reference that helps readers understand the trade-offs of the 7 methods comprehensively. Finally, we evaluate 3 representative methods via simulation and give some suggestions on how to select an appropriate method based on a given research.
It has been nearly 60 years since Dr John Gurdon achieved the first cloning of Xenopus by somatic cell nuclear transfer (SCNT). Later, in 2006, Takahashi and Yamanaka published their landmark study ...demonstrating the application of four transcription factors to induce pluripotency. These two amazing discoveries both clearly established that cell identity can be reprogrammed and that mature cells still contain the information required for lineage specification. Considering that different cell types possess identical genomes, what orchestrates reprogramming has attracted wide interest. Epigenetics, including high-level chromatin structure, might provide some answers. Benefitting from the tremendous progress in high-throughput and multi-omics techniques, we here address the roles and interactions of genome architecture, chromatin modifications, and transcription regulation during somatic cell reprogramming that were previously beyond reach. In addition, we provide perspectives on recent technical advances that might help to overcome certain barriers in the field.
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