Search

Street maintenance and improvement are significant missions in ensuring transportation safety, especially at nighttime because the severity of injuries doubles at night. Driving visibility and road surface conditions are key factors behind nighttime traffic accidents, and they must be solved as a major priority. Having an exclusive report representing this issue becomes useful documentation for preparing an effective plan for repairing and upgrading a street at appropriate locations. However, road observations are mostly performed by humans, so reports are imprecise owing to the limitation of human cognition and documentation during observation at night. For this reason, the aim of this work is to create a visualization report for monitoring the risk on a street at nighttime. To achieve this goal, a light sensor for measuring brightness on the road, a gyro sensor and an accelerometer for detecting pavement defects, and a location sensor for marking the current latitude and longitude are placed in a car, and the data obtained are transferred to a cloud database while driving on the road. After that, all data are analyzed by machine learning techniques to identify some critical failures and report on map visualization. The result demonstrates that this approach can visualize the right defect at the correct location, and it will become an important contribution to transport safety. [ABSTRACT FROM AUTHOR]

Device-free localization (DFL) is a technique that can locate targets wearing no devices, and has become an attractive technique for wide applications, such as intrusion detection and gesture recognition. In recent years, research on indoor localization using light sensor mainly focuses on traditional active localization methods, which require photodiodes being attached to targets. In this paper, we explore the visible light-based DFL method. In DFL, shadowed areas caused by different targets may overlap when multiple targets simultaneously exist in a small monitored area, which increases difficulties both in counting target and achieving accuracy localization. This paper presents an accurate geometrical multi-target device-free localization method, which includes a sector ring model and an adaptive multi-target positioning (AMTP) algorithm. The proposed model does well in describing the relationship between the target location and the shadowed area, which provides essential observation information for DFL. The proposed AMTP algorithm improves the accuracy of counting and locating multiple targets through updating weight map of the monitored area in each iteration. Numerous simulation results show that the proposed DFL method effectively achieves multi-target location, and outperforms the traditional geometrical localization method and the fingerprinting localization method both in counting and localization accuracy. [ABSTRACT FROM AUTHOR]

Aiming at the single inclined uniaxial solar tracking system has low tracking precision, tracking accumulated error exists, affected by the weather and poor stability problems, the trajectory and photovoltaic solar array tracking trajectory mathematical model was established, which proposed depending on the day trajectory coarse tracking(error 2°) at this time, then through two quadrant silicon photocell light sensors to realize accurate tracking(error correction to within 0. 5°). A 2. 25 k W diagonal tracking device was used to verify and test the proposed compound tracking model. The results indicate that the proposed composite tracking mode can make the system tracking error within0. 5°, PV array output 26. 2% higher than fixed photovoltaic array output, and it can eliminate the accumulated error, to overcome the weather affect, realize the all-weather reliable operation, which to improve the tracking precision of PV tracking system and photovoltaic power generation is of great significance. [ABSTRACT FROM AUTHOR]

Phytochrome photoreceptors control plant growth, development, and the shade avoidance response that limits crop yield in highdensity agricultural plantings. Cyanobacteriochromes (CBCRs) are distantly related photosensory proteins that control cyanobacterial metabolism and behavior in response to light. Photoreceptors in both families reversibly photoconvert between two photostates via photoisomerization of linear tetrapyrrole (bilin) chromophores. Spectroscopic and biochemical studies have demonstrated heterogeneity in both photostates, but the structural basis for such heterogeneity remains unclear. We report solution NMR structures for both photostates of the red/green CBCR NpR6012g4 from Nostoc punctiforme. In addition to identifying structural changes accompanying photoconversion, these structures reveal structural heterogeneity for residues Trp655 and Asp657 in the red-absorbing NpR6012g4 dark state, yielding two distinct environments for the phycocyanobilin chromophore. We use site-directed mutagenesis and fluorescence and absorbance spectroscopy to assign an orangeabsorbing population in the NpR6012g4 dark state to the minority configuration for Asp657. This population does not undergo full, productive photoconversion, as shown by time-resolved spectroscopy and absorption spectroscopy at cryogenic temperature. Our studies thus elucidate the spectral and photochemical consequences of structural heterogeneity in a member of the phytochrome superfamily, insights that should inform efforts to improve photochemical or fluorescence quantum yields in the phytochrome superfamily. [ABSTRACT FROM AUTHOR]

Cryptochromes (CRYs) entrain the circadian clocks of plants and animals to light. Irradiation of the Drosophila cryptochrome (dCRY) causes reduction of an oxidized flavin cofactor by a chain of conserved tryptophan (Trp) residues. However, it is unclear how redox chemistry within the Trp chain couples to dCRY-mediated signaling. Here, we show that substitutions of four key Trp residues to redox-active tyrosine and redox-inactive phenylalanine tune the light sensitivity of dCRY photoreduction, conformational activation, cellular stability, and targeted degradation of the clock protein timeless (TIM). An essential surface Trp gates electron flow into the flavin cofactor, but can be relocated for enhanced photoactivation. Differential effects of Trp-mediated flavin photoreduction on cellular turnover of TIM and dCRY indicate that these activities are separated in time and space. Overall, the dCRY Trp chain has evolutionary importance for light sensing, and its manipulation has implications for optogenetic applications of CRYs. [ABSTRACT FROM AUTHOR]

We successfully fabricated a planar nanocomposite film that uses a composite of silver nanoparticles and titanium dioxide film (Ag-TiO2) for ultraviolet (UV) and blue light detection and application in ozone gas sensor. Ultraviolet-visible spectra revealed that silver nanoparticles have a strong surface plasmon resonance (SPR) effect. A strong redshift of the plasmonic peak when the silver nanoparticles covered the TiO2 thin film was observed. The value of conductivity change for the Ag-TiO2 composite is 4–8 times greater than that of TiO2 film under UV and blue light irradiation. The Ag-TiO2 nanocomposite film successfully sensed 100 ppb ozone. The gas response of the composite film increased by roughly six and four times under UV and blue light irradiation, respectively. We demonstrated that a Ag-TiO2 composite gas sensor can be used with visible light (blue). The planar composite significantly enhances photo catalysis. The composite films have practical application potential for wearable devices.

The interior space of large-scale buildings, such as hospitals, with a variety of departments, is so complicated that people may easily lose their way while visiting. Difficulties in wayfinding can cause stress, anxiety, frustration and safety issues to patients and families. An indoor navigation system including route planning and localization is utilized to guide people from one place to another. The localization of moving subjects is a critical-function component in an indoor navigation system. Pedestrian dead reckoning (PDR) is a technology that is widely employed for localization due to the advantage of being independent of infrastructure. To improve the accuracy of the localization system, combining different technologies is one of the solutions. In this study, a multi-sensor fusion approach is proposed to improve the accuracy of the PDR system by utilizing a light sensor, Bluetooth and map information. These simple mechanisms are applied to deal with the issue of accumulative error by identifying edge and sub-edge information from both Bluetooth and the light sensor. Overall, the accumulative error of the proposed multi-sensor fusion approach is below 65 cm in different cases of light arrangement. Compared to inertial sensor-based PDR system, the proposed multi-sensor fusion approach can improve 90% of the localization accuracy in an environment with an appropriate density of ceiling-mounted lamps. The results demonstrate that the proposed approach can improve the localization accuracy by utilizing multi-sensor data and fulfill the feasibility requirements of localization in an indoor navigation system.