A Preliminary Study on Human Resources Management in International Construction

As construction companies continue to exploreforeign construction markets, variousinternational construction projects are beingundertaken in all corners of the world. In aninternational construction project with manyunique and complicated characteristics, humanresource management can playa significant rolein promoting the efficient use of complex humanresources. The aim of this paper is to establish avalid foundation for further research onmeasuring the impact of human resourcemanagement economically for internationalconstruction projects. The paper examineshuman resource management literature andidentifies the application of the relatedmanagement techniques to the constructionindustry. In addition, the paper uses the literatureanalysis to describe the nature of humanresource management with particular referenceto international construction projects. Inparticular, the research described in this paperidentifies economic performance factors in theimplementation human resource management ininternational construction projects. This paperalso identifies the social effects of humanresource management practices

Wildfire Alters Spatial Patterns of Available Soil Nitrogen and Understory Environments in a Valley Boreal Larch Forest

Wildfire, a primary natural disturbance in many forests, affects soil nutrient availability and spatial distributions of forest plants. However, post-fire changes in soil nutrients and spatial patterns of understory environments at fine scales are poorly understood. Here, we characterized spatial patterns of soil nitrogen availability and site characteristics at a 3-year-post-fire and an unburned site in a valley boreal larch forest. We also examined the relationship between soil nitrogen availability and site characteristics. The results showed that the burned site had higher NO3− and lower NH4+ than the control. The herb, litter and coarse wood debris cover was greater at the burned site than at the control site with higher soil pH, depth of the organic horizon (DOH) and shrub cover. Relative variability (coefficient of variation) in soil nitrogen and site characteristic variables at the control site was greater than at the burned site except for shrub and regeneration tree seedling cover. Spatial structure (quantified by semi-variograms) was lacking for soil nitrogen and site characteristic variables except for DOH, herb and shrub cover at the control site, but wildfire created a strong spatial structure for all variables. Shorter spatial autocorrelation ranges of soil nitrogen (1.6–3.5 m) and site characteristic variables (2.6–6.0 m) were detected at the burned site, indicating higher heterogeneity. The spatial scale of soil NH4+ was congruent with those of herb, shrub and regeneration tree seedling cover, indicating local coupling, while that of soil NO3− was not. The number of correlations between soil nitrogen and site characteristic variables in the burned site was greater than in the control. These results indicate that fire could not only create higher heterogeneity patches of soil resources, but also strengthen the local coupling between soil resources and understory vegetation, which may impact the establishment and growth of new individual plants

Single-molecule real-time sequencing of the full-length transcriptome of Portunus pelagicus

Reconstruction and annotation of transcripts, particularly for a species without reference genome, plays a critical role in gene discovery, investigation of genomic signatures, and genome annotation in the pre-genomic era. This is the first study to use Single-molecule real-time (SMRT) sequencing for reporting the full-length transcriptome of Portunus pelagicus. Overall, 16.26 Gb of raw reads were obtained, including 7,068,387 subreads, with average length of 2,300 bp and N50 length of 3,594 bp. In total, 351,870 circular consensus sequences (CCS) reads were extracted, including 255,378 full-length non-chimeric (FLNC) reads with mean length of 3,423 bp.70,407 genes were obtained after eliminating redundant sequences, and 56,557 (80.33%) genes were annotated in at least one database, 17,267 (24.52%) genes were annotated in all of the seven databases. Further, 68,797 coding sequences (CDS) were identified, including 36,848 complete CDS. A total of 1,730 unigenes were predicted to be transcription factors (TFs). Finally, 11,894 long noncoding RNA (lncRNA) transcripts were predicted by different computational approaches and 147,262 single sequence repeat (SSR)s were obtained. The transcriptome data reported herein are bound to serve as a basis for future studies on P. pelagicus

Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

In this paper, we propose a robust 3D detector, named Cross Modal Transformer (CMT), for end-to-end 3D multi-modal detection. Without explicit view transformation, CMT takes the image and point clouds tokens as inputs and directly outputs accurate 3D bounding boxes. The spatial alignment of multi-modal tokens is performed by encoding the 3D points into multi-modal features. The core design of CMT is quite simple while its performance is impressive. It achieves 74.1\% NDS (state-of-the-art with single model) on nuScenes test set while maintaining faster inference speed. Moreover, CMT has a strong robustness even if the LiDAR is missing. Code is released at https://github.com/junjie18/CMT

Monitoring of Fiber-Reinforced Composite Single-Lap Joint with Electromechanical Impedance of Piezoelectric Transducer.

The single-lap joint of fiber-reinforced composites is a common structure in the field of structure repair, which has excellent mechanical properties. To study and monitor its quasi-static response behavior under external load, two methodologies called effective structural mechanical impedance (ESMI) and reduced-ESMI (R-ESMI) are presented in this article. A two-dimensional electromechanical impedance (EMI) model for a surface-bonded square piezoelectric transducer (PZT) is adopted to extract more sensitive signatures from the measured raw signatures. There are two major advantages of the monitoring scheme based on ESMI and R-ESMI signatures: (1) excellent monitoring results with less signatures to process, (2) the ability to monitor the quasi-static behavior of a single-lap joint with previously ignored susceptance signatures. Combining the extracted ESMI signatures with the index of root-mean-square deviation, the quasi-static behavior of single-lap joints can be effectively quantified. To test the effectiveness of ESMI methodology, verifying experiments were conducted. The experimental results convincingly demonstrated that the presented ESMI and R-ESMI methodologies have good feasibility in monitoring the quasi-static behavior of a fiber-reinforced composite single-lap joint. The proposed method has potential application in the field of structural health monitoring (SHM)

Viscosity and Thermal Conductivity of Stable Graphite Suspensions Near Percolation

Nanofluids have received much attention in part due to the range of properties possible with different combinations of nanoparticles and base fluids. In this work, we measure the viscosity of suspensions of graphite particles in ethylene glycol as a function of the volume fraction, shear rate, and temperature below and above the percolation threshold. We also measure and contrast the trends observed in the viscosity with increasing volume fraction to the thermal conductivity behavior of the same suspensions: above the percolation threshold, the slope that describes the rate of thermal conductivity enhancement with concentration reduces compared to below the percolation threshold, whereas that of the viscosity enhancement increases. While the thermal conductivity enhancement is independent of temperature, the viscosity changes show a strong dependence on temperature and exhibit different trends with respect to the temperature at different shear rates above the percolation threshold. Interpretation of the experimental observations is provided within the framework of Stokesian dynamics simulations of the suspension microstructure and suggests that although diffusive contributions are not important for the observed thermal conductivity enhancement, they are important for understanding the variations in the viscosity with changes of temperature and shear rate above the percolation threshold. The experimental results can be collapsed to a single master curve through calculation of a single dimensionless parameter (a Péclet number based on the rotary diffusivity of the graphite particles).United States. Air Force Office of Scientific Research (FA9550-11-1-0174)National Natural Science Foundation (China) (51036003

Xiaoqinglong granules as add-on therapy for asthma: latent class analysis of symptom predictors of response.

Xiaoqinglong granules (XQLG) has been shown to be an effective therapy in asthma animal models. We reviewed the literature and conducted this study to assess the impact of XQLG as an add-on therapy to treatment with fluticasone/salmeterol (seretide) in adult patients with mild-to-moderate, persistent asthma. A total of 178 patients were randomly assigned to receive XQLG and seretide or seretide plus placebo for 90 days. Asthma control was assessed by asthma control test (ACT), symptoms scores, FEV(1), and PEF. Baseline patient-reported Chinese medicine (CM)-specific symptoms were analyzed to determine whether the symptoms may be possible indicators of treatment response by conducting latent class analysis (LCA). There was no statistically significant difference in ACT score between two groups. In the subset of 70 patients with symptoms defined by CM criteria, XQLG add-on therapy was found to significantly increase the levels of asthma control according to global initiative for asthma (GINA) guidelines (P = 0.0329). There was no significant difference in another subset of 100 patients with relatively low levels of the above-mentioned symptoms (P = 0.1291). Results of LCA suggest that patients with the six typical symptoms defined in CM may benefit from XQLG

Regulatory detection of edge engineering structures in unloading zones based on parallel perception

The primary challenge encountered by unmanned technology during the unloading phase in open-pit mines is safety hazards, particularly concerning the stability and normative detection of engineering structures at the edges of unloading area. To tackle this issue, a point cloud model analysis algorithm, driven by parallel perception theory and named AC-VIT, is proposed for the real-time and stable detection of the stability and normativity of engineering structures at the edges of open-pit coal mine unloading areas. Initially, three-dimensional point cloud data are captured using unmanned dump trucks equipped with rearward LiDAR scanning. These data are then processed through grid averaging methods, statistical filtering, and mapping to discrete grid models. Preliminary terrain marking is conducted via height field gradient feature extraction, in conjunction with the improved AC-VIT neural network for normative recognition and classification. The AC-VIT model, leveraging parallel computation solely based on a self-attention mechanism and multi-level attention mechanisms, effectively captures long-distance dependencies. Furthermore, a parallel simulation environment for the unloading area is established based on the actual production environment of the Haerwusu open-pit coal mine in Inner Mongolia, within a simulated artificial scene environment, to gather a vast array of diverse artificial scene data. Utilizing this data, in conjunction with actual scene data, the algorithm undergoes a parallel execution to design and perform parallel perception computing experiments, facilitating the effective training of the detection algorithm and scientific evaluation. Experimental outcomes demonstrate that the AC-VIT algorithm, underpinned by parallel perception theory, attains an accuracy rate of 98%, surpassing the accuracy and efficiency of traditional neural network models. The successful deployment of the AC-VIT algorithm not only elevates the intelligence level in open-pit mine unloading operations, but also furnishes robust technical support for the safety detection of other analogous engineering structures. The algorithm introduced herein presents a more efficient, safe, and intelligent approach for the detection of engineering structures at unloading area edges, bearing significant relevance for achieving high-performance, high-reliability, and high-automation in open-pit mine operations