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In this paper, a current mode physical unclonable function (PUF) based on the winner-take-all (WTA) scheme is presented. By using the process variation of the single transistor in the current mirror array, digital values with superior randomness can be produced. With the proposed WTA scheme, the time needed to acquire the currents' difference is significantly reduced. Meanwhile, the overall power consumption is also greatly lowered with the simplified peripheral circuitry. Moreover, unstable bit replacement circuitry is customized to remove the unstable bit caused by WTA's mismatch, which further improves the reliability of our proposed PUF. According to the simulation results using standard 65nm CMOS process, the proposed unstable replacement circuitry can replace up to 12.07% of the unstable bits. In addition, the superior averaged temperature reliability of the proposed implementation is 99.53% from −20° C to 100°C, with the overall power consumption as low as 892nW.

Anodic aluminum oxide (AAO) template based gas sensor, is often used due to its large surface reaction area. With longer AAO tube, the effective reaction surface area is widely believed to further increase leading to a higher sensitivity. However, through 3D current density distribution figures generated from the simulation software, a more uniform distribution is found to form at the center of the tube area instead of only top surface, making the tube area more effective for the reaction. This double effect of tube length is thus believed to contribute to the improved sensitivity of AAO template based gas sensor.

Synthesis of high-performance room-sensing materials have attracted lots of attention in the gas sensor area. In this work, ternary sensing material of MoO2-Ni-Graphene composite was synthesized by the hydrothermal method. Through X-ray diffraction, Raman spectroscopy and X-ray photoelectron spectroscopy, the existence of chemisorbed oxygen contents introduced by the annealing processes are validated (the intensity of graphene oxide (GO) peak (C (0 0 2)) at 9.90° is increased, and the oxidation state of Mo is changed from 6+ to 4+ and 5+). The gas sensing performance of composites to ethanol, formaldehyde, and ammonia was then tested and response (Rg/Ra) of the sample annealed at 400 °C towards 1000 ppm ethanol was improved to 105 at room temperature and the minimum detection limit was 15 ppm. Meanwhile, it didn’t show response towards formaldehyde. For the enhanced sensitivity and selectivity of sensor towards ethanol, metallic nature of Ni and MoO2 on graphene surface, interaction of hydroxyl species via hydrogen bonding and lower LUMO energy levels (0.13 eV) value of ethanol were the main factors. Moreover, long term stability of 40 ppm ethanol for 30 days with response 21.61 ± 0.96 suggested that proposed sensor could be an ideal candidate for future commercial ethanol sensing.

Interspecies electron transfer (IET) between syntrophic fatty-acid oxidizing bacteria (SFOBs) and methanogens decided the performance of anaerobic digestion. Electron shuttles, as potential IET accelerators, were controversial concerning their influences on methanogenesis. In this study, concentration-dependent effects of anthraquinone-2-sulfonate (AQS) and cysteine on glucose digestion were firstly demonstrated: low dosage of AQS and cysteine (50 and 100 µM, respectively) had highest methane yield (133.5% and 148.6%, respectively). Using butyrate as substrate, distinct tendencies towards the enrichment of methanogenic community were further revealed. Cysteine just acted as a reductant which lowered ORP quickly and enriched most methanogens. It benefited methanogenesis right until methanogenic substrates accumulated. AQS, however, showed characteristic features of electron shuttles: it was firstly oxidized by SFOBs and then reduced by hydrogenotrophic methanogens, which accelerated methanogenic butyrate degradation. This study showed wide spectrum of SFOBs and methanogens benefited from the addition of electron shuttles, which laid foundation for future application.

Growing environment problem and emphasis of environmental protection motivate intense research efforts in exploring technology to improve treatment efficiency on refractory organic pollutants. Hence, finding a method to make up for the deficiency of anaerobic digestion (AD) is very attractive and challenging tasks. The recent spark in the interest for the usage of some nanomaterials as an additive to strengthen AD system. The adoption of iron compounds can influence the performance and stability in AD system. However, different iron species and compounds can influence AD system in significantly different ways, both positive and negative. Therefore, strengthening mechanism, treatment efficiency, microbial community changes in Nanoscale Zero Valent Iron (nZVI) and Fe3O4 nanoparticles (Fe3O4 NPs) added AD systems were summarized by this review. The strengthening effects of nZVI and Fe3O4 NPs in different pollutants treatment system were analyzed. Previous study on the effects of nZVI and Fe3O4 NPs addition on AD have reported the concentration of nZVI and Fe3O4 NPs, and the types and biodegradability of pollutants might be the key factors that determine the direction and extent of effect in AD system. This review provides a summary on the nZVI and Fe3O4 NPs added AD system to establish experiment systems and conduct follow-up experiments in future study.

Anaerobic methane production from paddy soils plays an important role in global methane emissions. Syntrophic-methanogenic associations have been viewed as a key regulator of methane generation in paddy fields. However, the effects of rice phenology on the diversity and abundance of syntrophic and methanogenic communities remain largely unknown. This study investigated the changes in syntrophic-methanogenic associations at different rice growth by comparing the 16S RNA sequences of total (DNA-based) and active (RNA-based) microbial communities in rhizosphere and bulk soils. Moreover, the concentrations of specific syntrophs and methanogens were quantified using qPCR assay. Statistical significant differences in the alpha and beta diversities were observed between DNA-based and RNA-based syntrophic communities. The relative abundance of syntrophs in rhizosphere soil was significantly higher at RNA level compared to that at DNA level, indicating that syntrophs display considerably high specific activities. Syntrophic bacteria accounted for 6.23–6.81% of the active communities in rhizosphere soil and 6.12–6.71% in bulk soil. Besides, the quantities of methanogens increased over the entire period of rice growth, and peaked at flowering stage. Such changing pattern was consistent with the total number of short-chain fatty acids-degrading syntrophs at flowering stage, suggesting that rice phenology can affect both syntrophic and methanogenic activities. Furthermore, not only environmental factors (e.g., pH and SOC), but also organic acids (e.g., citrate and succinate), shaped the composition and abundance of syntrophic and methanogenic communities in paddy soils.

For evaluating the methanogenesis from typical methanogenic precursors (formate, acetate and H2/CO2), CH4 production kinetics were investigated at 37±1°C in batch anaerobic digestion tests and stimulated by modified Gompertz model. The results showed that maximum methanation rate from formate, acetate and H2/CO2 were 19.58±0.49, 42.65±1.17 and 314.64±3.58NmL/gVS/d in digested manure system and 6.53±0.31, 132.04±3.96 and 640.16±19.92NmL/gVS/d in sewage sludge system during second generation incubation. Meanwhile the model could not fit well in granular sludge system, while the rate of formate methanation was faster than from H2/CO2 and acetate. Considering both the kinetic results and microbial assay we could conclude that H2/CO2 methanation was the fastest methanogenic step in digested manure and sewage sludge system with Methanomicrobiales as dominant methanogens, while granular sludge with Methanobacteriales as dominant methanogens contributed to the fastest formate methanation.

Nowadays featuring outstanding eco-friendliness, the phytochemical fabrication method of nanostructures is very popular. Here, we propose to utilize the Astragalus membranaceus extract as the reducing and capping agent to stabilize the metal and to avoid the aggregations of nanoparticles during ZnO nanoflowers synthesis procedure. As a result, the whole fabrication procedure was highly efficient and cost-effective without requiring a special environment of high pressure or elevated temperature and without chemical hazards used or produced. After the fabrication, detailed characterization about material morphology and crystal structure was carried out, including scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscope (FTIR). Moreover, the ZnO nanoflowers demonstrated distinctive antibacterial, antioxidant and electrochemical sensing effect. Specifically, ZnO nanoflowers had an antibacterial inhibition zone of 19(±0.7) and 15(±0.8) mm in diameter against the concentration of 50 μL (1 mg/mL) Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), which is greatly improved compared to the reference drug (Kanamycin). Besides, antioxidant activity was also tested using H2O2 free radical scavenging assay and 60% 2,2-diphenyl-1-picrylhydrazyl (DPPH) inhibition of 0.5 mg/mL was reported. Finally, controlled by the diffusion process during the charge transfer procedure, 4-nitorphenol was dramatically reduced and a limit of detection of 0.08 μM by ZnO nanoflowers modified electrode was observed during the cyclic voltammetry (CV) experiment. Because the phenolic compounds originating from Astragalus membranaceus helped to facilitate the electron transfer, the limit of detection was lower compared to other materials, such as copper oxide nanoparticles (Cu2O-NPs), silicon dioxide/silver nanoparticles (SiO2/Ag-NPs), zinc oxide nanoparticles (ZnO-NPs), activated carbon (AC) and cobalt oxide nanocubes (Co3O4). Therefore, featuring easy operation, low-cost and eco-friendliness, our proposed ZnO nanoflowers fabrication method will have a great potential in biomedical and electro-catalytic fields.

Aiming at relieving acid accumulation in anaerobic digestion (AD), syntrophic associations of syntrophic fatty acid-oxidation bacteria and H2/formate-scavenging methanogens were enriched by feeding propionate, butyrate and formate in an up-flow anaerobic sludge blanket (UASB) reactor. Results showed that methane yield increased by 50% with increasing formate concentration (0–2000 mg COD/L). In addition, the abundance and quantity of SFOB (Syntrophobacter, Smithella and Syntrophomonas) and H2/formate-scavenging methanogens (Methanobacteriales and Methanomicrobiales) were increased after microbial acclimation. The enriched syntrophic associations showed higher propionate and butyrate removal efficiencies of 98.48 ± 1.14% and 99.71 ± 0.71%, respectively. Furthermore, encoding genes of formate dehydrogenase and hydrogenases presented higher abundances after microbial enrichment, which suggested that the enhancements of interspecies formate transfer and interspecies hydrogen transfer between syntrophic associations benefited volatile fatty acids (VFAs) conversion. This research provided an effective strategy to relieve acid accumulation.

The increasing production of waste activated sludge (WAS) from wastewater treatment plants presents an inherent environmental burden. In this study, Free nitrous acid combined with potassium ferrate (FNA + PF) pretreatment was used to enhance solubilization and biochemical methane potential of WAS. Results indicated that the maximum removal rates of total suspended solid by PF, FNA, and PF + FNA pretreatment were 21.84%, 38.09%, and 56.17%, respectively. The biochemical methane potential of WAS without pretreatment reached 61.22 L CH4/kg VSS added while this value increased to 147.07 L CH4/kg VSS added after FNA + PF pretreatment (0.06 g/g TSS NaNO2 and 0.25 g/g TSS K2FeO4). Shotgun metagenomic analysis revealed that FNA + PF pretreatment could increase the diversity and stability of microbial communities by shifting methanogenic pathways from strictly acetoclastic to acetoclastic/hydrogenotrophic, thereby enhancing methane production. This study suggested that FNA + PF pretreatment is a promising technology to reduce WAS and enhance methane production by pretreated WAS during anaerobic digestion.

In this paper, we present four denoising algorithms dedicated to the division of focal plane (DoFP) polarization image sensors, including the average filtering, median filtering, Wiener filtering and wavelet threshold denoising algorithms. Compared with the previous implementations solely based on the Gaussian noise model, this paper, for the first time, covers the non-Gaussian noises, such as the salt & pepper noise and Poisson noise. According to our extensive experimental results, the wavelet threshold denoising outperforms for suppressing the Gaussian noise; while the median filtering and the Wiener filtering outperform for suppressing the low-density salt & pepper noise and Poisson noise, respectively.

In this paper, we present a novel one-dimensional deep convolutional neural network (1D-DCNN) based algorithm for classifying mixture gases. Compared with the previously reported electronic nose system that can only recognize pure gas, the proposed implementation is capable of distinguishing the individual component of binary mixture gases composed of Ethylene, CO and Methane. To the best of our knowledge, the proposed 1D-DCNN algorithm is firstly applied in the mixture gases recognition. Compared with the conventional pattern recognition algorithms including support vector machine (SVM) and artificial neural network (ANN), the proposed 1D-DCNN exhibits higher average accuracy (96.15%) based on extensive experimental results using 10-fold cross validation.

In this paper, we present a novel fast gas recognition algorithm based on convolutional recurrent neural network. Rectangular kernels and long short-term memory (LSTM) are adopted to calculate the gas-label distribution from relationship between sensors and relationship among time as well. Compared with the widely adopted algorithms, such as support vector machine (SVM), K nearest neighbor (KNN), random forest (RF), the proposed implementation features an ultra-short detection time of 4 seconds. Moreover, according to our extensive experimental results, a high accuracy of 98.28% is achieved, which greatly outperforms the abovementioned algorithms.

This paper presents a novel K times singular value decomposition (K-SVD) based denoising algorithm for the division-of-focal-plane (DoFP) polarization image sensors. In the proposed implementation, the input DoFP image can be expressed by the optimum sparse combination of the dictionary elements via K-SVD and orthogonal matching pursuit (OMP) algorithms. As a result, this implementation is capable of eliminating the Gaussian noise significantly and well-preserving the details and edges of the target DoFP image. Our extensive experimental results on various test images show that the proposed algorithm yields better visual quality and maintains a lower PSNR value while compared with a wide range of previous implementations.

Gas sensors based on semiconductor–metal–oxide nanomaterial have recently emerged due to their advantages of offering large surface to volume ratio. Unfortunately, these sensors are vulnerable to environmental humidity and lack of selectivity when exposed to common gases in air. In this letter, a novel morphology of ZnO nanomaterial is proposed for fabricating NO2 gas sensor through our customized vapor trapping chemical vapor deposition process. By operating the fabricated gas sensors at the room temperature, high sensing performance, including a large output response of 11.06 and a short response/recovery time of 107/124 s, is achieved for 20-ppm NO2. Moreover, the sensor response remains stable under humid environment up to 76%RH. In addition, the extensive experimental results indicate that our fabricated NO2 gas sensors exhibit high selectivities of 61.7, 42.8, and 54.4 dB for different target gases of H2, CH2O, and C6H6, respectively. These features will enable the mass fabrication of miniaturized, cost-effective, and highly robust gas sensor suitable for real-life application.

In this paper, we present a novel on-chip relaxation oscillator (RO) with high temperature stability. By employing delay compensation circuit (DCC) in the delay loop, the transmission delay, which is highly sensitive to the temperature variation, is well-suppressed, leading to significantly elevated temperature stability of the RO's period. In addition, the proposed RO implementation features a low power consumption of 0.11μW at 25° C, using 65nm 1.2V standard CMOS process. Moreover, according to our extensive simulation results, the variation of our proposed RO's output frequency is reduced to ±0.18% with the working temperature ranged from −55° C to 125° C, outperforming the other state of art RO designs.

Support vector machine (SVM) now attracts increasing attention in gas classification due to its high performance towards small samples and nonlinearity problems of the dataset. Previously, the probable mismatch between the dataset and the training parameters determined by trial and error or grid search may hinder the exploration of the best result. In this paper, we propose a novel approach to estimate the most suitable training parameters, based on the inbreeding prevention of genetic algorithm (GA) by assigning the training model parameters of SVM as its chromosome. Treating the k-fold cross validation of SVM training as the objective function, our new method makes the population on the whole evolve towards the values that are more appropriate for the dataset. The inbreeding prevention mechanism (IPM) can protect the population from converging over-rapidly before reaching the optimum value. Compared with the standard SVM, the proposed method has greatly improved the prediction accuracy in both training data and testing data.

Much greater surface-to-volume ratio of hierarchical nanostructures renders them with promising potential for high performance chemical sensing. In this work, crystalline nanocombs were synthesized via chemical vapor deposition and fabricated into resistive gas sensors. Particularly, NO2 sensing performance of these devices has been systematically characterized, showing higher sensitivity as compared to their nanobelt counterparts. Through device simulation, it was discovered that the teeth part of a nanocomb could serve as a "negative-potential gate" after accumulating electrons captured by surface adsorbed NO2 molecules. This self-gating effect eventually results in a greater reduction of nanocomb device channel conductance upon NO2 exposure, as compared to a nanobelt device, leading to a much higher NO2 detection sensitivity. This study not only sheds light on the mechanism of performance enhancement with hierarchical nanostructures, but also proposes a rational approach and a simulation platform to design nanostructure based chemical sensors with desirable performance.

In this paper, we present a novel on-chip physical unclonable function (PUF) based on the cascode current mirrors. It exploits the process variation of a single transistor as the load of the current mirror to generate a reliable digital signature for the chip. By employing a cascode NMOS transistor in the current-mode PUF architecture, the proposed PUF greatly boosts the output impedance. As a result, the tiny mismatch current can be amplified to a large output voltage swing. In addition, the area overhead per bit is only two minimum-sized NMOS transistors: one for the load of the current mirror, the other one for the selecting switch. Moreover, the proposed PUF design is validated by our extensive post-layout simulation using UMC 65nm CMOS technology, with a power consumption per bit as low as 0.13μW. The average area for each response bit extracted from the design layout is 5.47μm2.

Short-term intensive insulin therapy is effective for type 2 diabetes because it offers the potential to achieve excellent glycemic control and improve β-cell function. We observed that the time to glycemic goal (TGG) was adjustable. Original data of 138 newly diagnosed type 2 diabetic patients received intensive insulin therapy by continuous subcutaneous insulin infusion for 2-3 weeks were retrospectively collected. Subjects underwent an intravenous glucose tolerance test (IVGTT) and an oral glucose tolerance test (OGTT) pre and post treatment. The glycemic goal was achieved within 6 (4-8) days. Patients were divided into two groups by TGG above (TGG-slow) and below (TGG-fast) the median value. Patients in both groups had significantly better glycemic control. Compared with TGG-fast, TGG-slow required a few more total insulin and performed more improvement of HOMA-β and IVGTT-AUCIns, but less improvement of HOMA-IR and QUICKI. Multiple linear regression analysis revealed that TGG was always an explanatory variable for the changes (HOMA-β, IVGTT-AUCIns, HOMA-IR and QUICKI). The hypoglycemia prevalence was lower in TGG-slow (1.48% vs. 3.40%, P

In this paper, we present a novel physical unclonable function (PUF) based on time-domain current difference measurement. By employing the aforesaid simplified current-mode PUF architecture, the proposed implementation completely removes the need of complex error correction circuitry, which is widely adopted in the previously demonstrated implementations. This leads to significant reduction of both the overall power consumption and the required chip area. In addition, the proposed implementation exhibits a superior bit error rate (BER) as low as 0 for the typical case scenario and 1.56% for the worst case scenario, respectively. Featuring an ultra-low power consumption of 11.29μW and an averaged silicon area of 13310μm2, the proposed implementation is validated by our reported extensive post-layout simulation results with UMC 0.18μm standard complementary-metal-oxide-semiconductor (CMOS) technology.

Correction for ‘Impact of physical structure of granular sludge on methanogenesis and methanogenic community structure’ by Xiaofang Pan et al., RSC Adv., 2019, 9, 29570–29578.

SummaryIn this paper, we present a novel spatial-domain denoising algorithm and directly apply it to the mosaicked Stokes sub-images generated by the division-of-focal-plane (DoFP) polarimetric image sensors. Compared to the previous implementations with the generated raw polarization images directly interpolated and demosaicked, the proposed method not only leads to significant noise reduction, but also effectively decreases the interpolated pixels' mean square error (MSE) after the interpolation process. In addition, regarding the sequence of the proposed denoising and interpolation, the polarization image quality and the interpolation MSE can be further improved by conducting the denoising before the interpolation, which has been validated by our intensive simulation results.MotivationPolarimetric image sensors enable a wide range of applications that are infeasible with traditional intensity/color image sensors, such as microscopy for tumor margin detection, 3-D shape reconstruction from a single image, material classification, and cancer diagnosis. By mimicking the mature Bayer-pattern-based color imaging, polarizers with different orientations are first scaled-down to micron level then mosaicked to have the full Stokes sub-images generated simultaneously in one single frame, namely division of focal plane (DoFP) (Fig. 1). However, this single-frame solution is at the expense of temporal noise and spatial resolution loss. As shown in Fig. 2, the temporal noise issue can be well-addressed by averaging multiple image frames of same micro-polarizer, which is not feasible in the aforesaid single-frame-based DoFP. In addition, interpolation algorithms are necessary to compensate the spatial resolution loss. In this paper, we propose a non-local-mean-based spatial-domain noise reduction scheme to denoise the DoFP polarization images and minimize the mean-square-error (MSE) caused by the interpolation process. Moreover, the exploration is extended to the sequence of the denoising and the interpolation as well.ResultsWe compared the overall MSE of the two different sequences for different test polarization images, and it is indicated by the intensive simulation results that denoising before the interpolation can bring lower MSE [Fig. 3 (A)]. In addition, as shown in Fig. 3 (B), we compared the MSE of traditional single-frame solution, 4-frame-averaging and the proposed implementation with spatial-domain denoising, and it is indicated the proposed scheme can achieve an MSE reduction effect similar to 4-frame-averaging by spatial-domain denoising.AcknowledgmentsThis work was supported by the National Natural Science Foundation of China (Grant No. 61504087), the Kongque Technology Innovation Foundation of Shenzhen (Grant No. KQCX20120807153227588), the Fundamental Research Foundation of Shenzhen (Grant No. JCYJ20140418095735624, and JCYJ20150324141711677).

SummaryIn this paper, we present a novel interpolation-based Stokes image reconstruction scheme for the division-of-focal-plane (DoFP) polarization image sensors. Different from the previous implementations, our proposed method first demosaics the raw image by mainstream interpolation algorithms then converts the up-sampled images to Stokes images with much richer polarization-related physical information. This not only leads to significant resolution improvement to the captured raw image, but also greatly reduces the caused pixel mean square error (MSE). Experimental data from the test images have validated the effectiveness of this proposed scheme.MotivationSolid-state image sensors, which are capable of extracting the incident light's polarization information in addition to intensity and color (i.e. wavelength), take great advantages in a wide range of applications [1]. By looking through a layer of patterned micrometer-scale pixelated polarizing elements, a set of mosaicked polarization raw sub-images can be generated simultaneously, namely DoFP polarization imaging. As shown in Fig. 1 (a), similar to the widely-exploited Bayer pattern of color imaging, the mosaicked polarization raw sub-images down-sample each polarization channel by 75%, leading to significant spatial resolution loss. Meanwhile, in order to make the raw sub-images physically meaningful, they are typically translated to Stokes sub-images, which correspond to first three Stokes parameters representing the unpolarized and linearly polarized components of the incident light. In the previously reported implementations, the neighboring four sub-pixels (i.e. I0, I90, I45, I135) are directly substituted to the Stokes parameters' classical expressions. As a result, a 75% down-sampled Stokes images are acquired. In order to compensate this resolution loss, we propose a new Stokes image reconstruction scheme: before the Stokes image conversion, interpolate the mosaicked polarization raw sub-images with mainstream algorithms, including linear, cubic and spline.ResultsFigure 1 (c) illustrates the proposed detailed image reconstruction flow. In addition, we have also compared our proposed method to the traditional implementation of directly applying the same interpolation algorithm to the aforesaid 75% down-sampled Stokes images [Fig. 1 (b)]. For the extracted down-sampled Stokes images in the previous implementations, even with the same interpolation algorithms applied, our proposed method still outperforms by almost 10 folds in term of Stokes parameter S2's MSE (Fig. 2), which well-balances the spatial resolution compensation and the Stokes image generation by minimizing the caused overall MSE. Figure 3 illustrates the real images with different Stokes image reconstruction schemes applied.AcknowledgmentsThis work was supported by the National Natural Science Foundation of China (Grant No. 61504087), the Kongque Technology Innovation Foundation of Shenzhen (Grant No. KQCX20120807153227588), the Fundamental Research Foundation of Shenzhen (Grant No. JCYJ20140418095735624, and JCYJ20150324141711677).Reference[1] M. Kulkarni, V. Gruev, “Integrated spectral-polarization imaging sensor with aluminum nanowire polarization filters”, Optics Express, vol. 20, no. 21, pp. 22997–23012, 2012.

In this paper, a common-source-amplifier-based physical unclonable function (PUF) is presented with ultra-low power consumption, which is verified with 0.18μm standard complementary-metal-oxide-semiconductor (CMOS) technology. Compared with the previous implementations, the proposed PUF circuitry features an averaged reliability as high as 98.83% with the operating temperature ranging from −20°C to 150°C. In addition, an average power consumption as low as 2.72μW is achieved with a supply voltage of 1.8V. Moreover, the reported superior uniqueness of 0.4999 and standard deviation of uniqueness of 0.0172 further validate the excellent security of the proposed circuitry.

In this paper, we present a liquid-crystal-polymer (LCP)-based dual-layer micro-quarter-wave-retarder (MQWR) array for active polarization image sensors. The proposed MQWRs, for the first time, enable the extraction of the incident light’s circularly polarized components in the whole visible regime, which correspond to the fourth parameter of Stokes vector. Compared with the previous implementations, our proposed MQWRs feature high achromaticity, making their applications no longer limited to monochromatic illumination. In addition, the presented thin structure exhibits an overall thickness of 2.43μm, leading to greatly alleviated optical cross-talk between adjacent photo-sensing pixels. Moreover, the reported superior optical performance (e.g. minor transmittance, extinction ratio) validates our optical design and optimization of the proposed MQWRs. Furthermore, the demonstrated simple fabrication recipe offers a cost-effective solution for the monolithic integration between the proposed MQWR array and the commercial solid-state image sensors, which makes the multi-spectral full Stokes polarization imaging system on a single chip feasible.

For probe into the application of Azotobacter on Eucalypt plantation, the method of dip roots was used for Azotobacter inoculation to the seedling roots of GL09 Clone of Eucalyptus urophylla×E.grandis. The experiment result show that there were distinct effects of Azotobacter on Seedlings Growth and chlorophll content and nitric acid deoxidize enzyme activity of GL09 Clone of Eucalyptus urophylla×E.grandis, and produced distinct differece on Eucalypt seedling by different species or different strain of Azotobacter.

In this paper, a research model of the impact of family business culture dimensions on control modes is built, based on the theory of cultural and on the main structure of the impact of family culture on control mode, combined with the reality of control mode of Chinese domestic business. What's more, the paper proposes a detailed analysis of how the family cultural dimensions affect the control mode, and verification that the relationship between the family cultural dimensions and the control mode with a sample of 190 family businesses, obtaining the required data by research and testing empirical hypothesis.

SummaryBackgroundPost-ischemic myocardial diastolic stunning persists for a long time after transient ischemia even after systolic function has recovered. We sought to identify coronary artery stenosis in clinical patients using strain imaging diastolic index (SI-DI) at rest.MethodsWe retrospectively examined 85 patients with suspected coronary artery disease and preserved ejection fraction (EF; >50%) who underwent both echocardiography and coronary angiography. Speckle tracking strains were measured in 3 apical views and parasternal left ventricular (LV) short-axis views at the papillary muscle level. LV segments with inadequate image quality and deficit segments in the movie were excluded by the blinded observer. After strain analysis, LV segments were classified into no stenosis (≤50%), mild stenosis (51–75%), and severe stenosis (>75%) groups on the bases of the coronary angiogram.ResultsSI-DI decreased significantly in severe stenosis segments (p

Path planning, as the core module of navigation GIS, its efficiency and accuracy has a crucial impact on the navigation system. General shortest-path algorithm is based on the classic node label-setting algorithm, which does not consider the situation of including circuitous road sections. Therefore, sometimes it will neglect the closer circuitous path at hand but find the farther path or even failed to find any path in the real road network with complicated traffic restrictions. For the sake of finding more accurate path, this paper presents a circuitous shortest path algorithm labeled by previous-arc vector group. Firstly, we generate incremental network topological relationships according to two random positions travelers are interested in. Secondly, we construct a vector group including previous arc, and seek the way by labeling the previous-arc vector group. Finally, the shortest path in the sense of mathematics which may contain circuitous road sections can be acquired. An experimental work has been done with this algorithm using the map of Beijing, which showed that the algorithm not only well improved the accuracy of the shortest path result between the two random positions in the road network, but also kept the efficiency of the classic node labeled algorithm.