Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.     

Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANN_FCM-GRN. In MANN_FCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANN_FCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANN_FCM-GRN and show that MANN_FCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANN_FCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

     

烟道流量计量标准装置

为了解决我国烟道流量计的量值溯源问题,中国计量科学研究院建立了烟道流量计量标准装置。装置使用可溯源至标准转盘的激光多普勒测速仪作为原级标准器,采用激光多普勒流速剖面扫描和超声流量计波动修正的方式测量标准流量,经校准的8声道超声流量计为工作级标准表,具备了908~104840m3/h的测量能力,扩展不确定度为0.62%(k=2),可对最大口径为1m的流量计进行校准。装置下游测试段包括圆形管段和矩形管段,能够开展烟道流量计测量性能的研究。     

Epidemic contact tracing with smartphone sensors

ABSTRACT

Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.     

Fabrication of tungsten oxide photoanode by doctor blade technique and investigation on its photocatalytic operation mechanism

WO₃ is a potential material candidate for construction of photoanode for solar driven water splitting. In this work, μm-thick porous WO₃ photoanode is prepared by depositing a stable ink made of WO₃ nanoparticles and Aristoflex velvet polymer in water using the doctor blade technique, followed by a sintering in air. The nature of WO₃ nanoparticles, its loading mass on F-doped tin oxide electrode as well as sintering temperature are examined in order to optimize the photocatalytic activity of the resultant WO₃ photoanode. The operation of WO₃ photoanode is investigated by varying the light illumination direction and light incident intensity as well as changing the nature of the electrolyte. Dissolved tungsten in electrolyte is quantified by ICP-MS providing insights into the influences of electrolyte nature and operating conditions to the corrosion of WO₃. It is proposed that the H₂O₂ and OH^. radical generated as by-products of the photo-driven water oxidation on the photoanode surface are harmful species that accelerate the dissolution of WO₃.     

Controlling thickness to tune performance of high-mobility transparent conducting films deposited from Ga-doped ZnO ceramic target

Structure modification has been found to tune significantly the transparent-conducting performance, especially mobility and conductivity of hydrogenated Ga-doped ZnO (HGZO) films. The strong correlation between film thickness and mobility of the films is revealed. The mobility increases quickly with increasing the thickness from 350 to 900 nm, and then tends to be saturated at further thicknesses. A higher mobility than 50 cm²/Vs can be achieved, which is an extra-high value for polycrystalline ZnO films deposited by using the sputtering technique. The thickness-dependent mobility originates from scatterings on grain boundaries and dislocation-induced defects controlled by thin-film growth. Based on the Volmer-Weber model, an expansion model is built up to describe the thickness-dependent crystal growth of the HGZO films, especially at the thick films. As a result, the 800 nm-thick HGZO film obtains the highest performance with high mobility of 51.5 cm²/Vs, low resistivity of 5.3 × 10^?4 Ωcm, and good transmittance of 83.3 %.