To explore factors that influence the likelihood of committing fraud in the construction industry, this study concentrated on senior executives and tested whether some characteristics at the individual and firm levels have impacts on the likelihood of fraud committed by top management. Based on social network theory, this study first proposes that intrafirm alumni networks may increase the probability of senior executives engaging in corrupt behavior. Then the study explored whether the effect of executives' alumni networks on their wrongdoings is influenced by external and internal corporate governance measures. To verify the hypotheses, this study collected data on 2,017 senior executives from 118 construction companies in China from 2013 to 2021. Because of the multilevel structure of the data, hierarchical linear modeling was used. The results show that alumni networks have a significant positive effect on top management fraud. The effect is weakened by external auditing, altered by board independence, and strengthened by the size of the board of directors and the size of the supervisory board. This multilevel research contributes to advancing the understanding of managers' fraudulent behavior within an organization and extends the literature on social networks and corporate governance in the construction industry.

Dynamic photovoltaic (PV) greenhouses integrate sustainable energy generation with plant cultivation, offering more possibilities of energy production and microclimate control by adjusting the sun-tracking angles. Previous studies on PV greenhouses barely paid attention to the PV partial shading effects, and rarely recorded the performance across the full range of rotation angles. In this study, we first build computer simulation models of typical greenhouses with high-density (1/2 roof area) and low-density (1/3 and 1/4 roof area) PV layouts. Then four special sun-tracking positions are found in the model of equivalent global irradiance, which is defined as the quotient of the total input power divided by the area of PV module under partial diffuse shadows. Simulation models are also built in terms of PV modules and interior irradiance. Simulations are conducted using the climate data of Delft, the Netherlands (52.01°N,4.36°E). Results show that high-density PVs under no-shading sun tracking generate 6.91% more energy than that under conventional (quasi-perpendicular) sun-tracking. Meanwhile, no-shading sun tracking allows more diffuse sunlight to enter the greenhouse mounted with high-density PV panels, resulting in 10.96% and 10.68% improvement on the annual average global irradiance and uniformity on the target plane compared to the fixed PV panels in the closed position. Regarding low-density PV layouts, which barely suffer from partial shading problems, quasi-perpendicular sun tracking improves the annual energy generation by 7.40% relative to the closed position. However, the average global irradiance reaches the minimum in this position because more sunlight is blocked by PVs. Meanwhile, the average uniformity of global irradiance reveals good (but not the best) performance, resulting in up to 9.80% (1/3 coverage) and 4.70% (1/4 coverage) improvement respectively compared to the closed position. The proposed methods and simulation results provide guidelines for the initial design and daily operation of PV greenhouses, aiming to balance the PV power generation and food production.

In this paper, a method to extend the detection range of hydrogen sulfide (H₂S) gas sensor is demonstrated. The sensor is based on AlGaN/GaN high electron mobility transistors (HEMTs) with Pt gate. It is observed that the as-fabricated devices exhibited sensing signal saturation at 30 ppm H₂S exposure in dry air. A pre-treatment using H₂ pulses in dry air ambient at 250 °C was applied to extend the detection range of the sensor. The H₂ treated H₂S gas sensor was able to detect a higher H₂S concentration up to 90 ppm at 250 °C without complete saturation.

As more and more proofs show that fine particles (diameter of 2.5μm and below) pose more risk on human health than coarse particles, an increasing need for monitoring fine particles has emerged. A miniaturized sensor designed for measuring fine particle concentration is presented in this paper. The proposed sensor possesses a compact size of only 15 mm × 10mm × 1mm. A virtual impactor has been integrated as a particle size selector and the design is optimized by simulation-assisted analysis. The sensor is realized by silicon microfabrication and wafer-level packaging. Testing results show that a high measurement accuracy of 2.55 μg/m³ has been achieved.