Original Article +Gz-induced post-cholecystectomy syndrome in rabbit model by using a telemetric method

Abstract: Aviation-related mechanism may exist in the post-cholecystectomy syndrome (PCS) of aircrew patients. The aim of this study was to test this hypothesis on vivo rabbit model and to explore the mechanism by using a novel telemetric method. We constructed a bile duct-to-intestinal bridge bypass on 30 rabbits, with a telemetry implant attached to the Oddi's sphincter. Then a telemetric recording system was used to record the biliary pressure fluctuation through the subcutaneous bridge and the changes of electromyography of the Oddi's sphincter under different +Gz acceleration. Self-control comparison was made before and after cholecystectomy. The fully implantable device was very well accepted by rabbits and the data could reflect the real experimental environment simultaneously. Biliary pressure in common bile duct increased accordingly with +Gz acceleration increased, but bile secretion didn't change. Although +Gz acceleration could increase the frequency of burst of spike potentials in the Oddi's sphincter, the frequency didn't change with the +Gz acceleration increased, and the spike activity didn't change obviously before cholecystectomy. After cholecystectomy, the biliary pressure in common bile duct remained high in 12 rabbits (40%) under +Gz exposure, and the pressure value didn't change as the +Gz acceleration increased. The long-time changes in electromyography of the Oddi's sphincter were observed in the same 12 rabbits, with symptoms of PCS developed in 9 of them. +Gz exposure is an important external factor leading to the biliary physiology disorder, and it may induce PCS in some aircrew patients with individual susceptibility, which means gallbladder maybe a dominant factor in regulating the biliary physiology in theses aircrew patients

Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

Based on Time-Frequency (TF) analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR) images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR) detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach

DEBRIS DETECTION IN HYDRAULIC OIL USING A MICROFLUIDIC INDUCTIVE PULSE DEVICE

ABSTRACT Metal wear debris is an important component of oil particle contamination and is also an essential information carrier in hydraulic oil. Based on inductive Coulter counting principle, a microfluidic device to detect wear debris in oil is presented. The proposed device has the advantage that in theory the distance between wear particle in oil and an embedded coil is 0, which can greatly improve the sensitivity of detection. The relationship between coil parameters and inductive change of a coil is analyzed through the related experimental statistics. The result indicates it can distinguish effectively ferrous and nonferrous metal particles in oil, and the size of 19μm iron particles and 40μm copper particles can be detected

Security Analysis of a Color Image Encryption Algorithm Using a Fractional-Order Chaos

Fractional-order chaos has complex dynamic behavior characteristics, so its application in secure communication has attracted much attention. Compared with the design of fractional-order chaos-based cipher, there are fewer researches on security analysis. This paper conducts a comprehensive security analysis of a color image encryption algorithm using a fractional-order hyperchaotic system (CIEA-FOHS). Experimental simulation based on excellent numerical statistical results supported that CIEA-FOHS is cryptographically secure. Yet, from the perspective of cryptanalysis, this paper found that CIEA-FOHS can be broken by a chosen-plaintext attack method owing to its some inherent security defects. Firstly, the diffusion part can be eliminated by choosing some special images with all the same pixel values. Secondly, the permutation-only part can be deciphered by some chosen plain images and the corresponding cipher images. Finally, using the equivalent diffusion and permutation keys obtained in the previous two steps, the original plain image can be recovered from a target cipher image. Theoretical analysis and experimental simulations show that the attack method is both effective and efficient. To enhance the security, some suggestions for improvement are given. The reported results would help the designers of chaotic cryptography pay more attention to the gap of complex chaotic system and secure cryptosystem

Security Analysis of a Color Image Encryption Algorithm Using a Fractional-Order Chaos

Fractional-order chaos has complex dynamic behavior characteristics, so its application in secure communication has attracted much attention. Compared with the design of fractional-order chaos-based cipher, there are fewer researches on security analysis. This paper conducts a comprehensive security analysis of a color image encryption algorithm using a fractional-order hyperchaotic system (CIEA-FOHS). Experimental simulation based on excellent numerical statistical results supported that CIEA-FOHS is cryptographically secure. Yet, from the perspective of cryptanalysis, this paper found that CIEA-FOHS can be broken by a chosen-plaintext attack method owing to its some inherent security defects. Firstly, the diffusion part can be eliminated by choosing some special images with all the same pixel values. Secondly, the permutation-only part can be deciphered by some chosen plain images and the corresponding cipher images. Finally, using the equivalent diffusion and permutation keys obtained in the previous two steps, the original plain image can be recovered from a target cipher image. Theoretical analysis and experimental simulations show that the attack method is both effective and efficient. To enhance the security, some suggestions for improvement are given. The reported results would help the designers of chaotic cryptography pay more attention to the gap of complex chaotic system and secure cryptosystem

Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations

High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes. Merging multi-resource observations is one of the ways to improve the accuracy of high spatial resolution SM data in the heterogeneous cropland. In this paper, the Bayesian Maximum Entropy (BME) methodology is implemented to merge the following four types of observed data to obtain the spatial distribution of SM at 100 m scale: soil moisture observed by wireless sensor network (WSN), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-derived soil evaporative efficiency (SEE), irrigation statistics, and Polarimetric L-band Multi-beam Radiometer (PLMR)-derived SM products (~700 m). From the poor BME predictions obtained by merging only WSN and SEE data, we observed that the SM heterogeneity caused by irrigation and the attenuating sensitivity of the SEE data to SM caused by the canopies result in BME prediction errors. By adding irrigation statistics to the merged datasets, the overall RMSD of the BME predictions during the low-vegetated periods can be successively reduced from 0.052 m3·m−3 to 0.033 m3·m−3. The coefficient of determination (R2) and slope between the predicted and in situ measured SM data increased from 0.32 to 0.64 and from 0.38 to 0.82, respectively, but large estimation errors occurred during the moderately vegetated periods (RMSD = 0.041 m3·m−3, R = 0.43 and the slope = 0.41). Further adding the downscaled SM information from PLMR SM products to the merged datasets, the predictions were satisfactorily accurate with an RMSD of 0.034 m3·m−3, R2 of 0.4 and a slope of 0.69 during moderately vegetated periods. Overall, the results demonstrated that merging multi-resource observations into SM estimations can yield improved accuracy in heterogeneous cropland

Effects of different types of neonatal pain on somatosensory and cognitive development in male juvenile rats

Abstract Background Premature infants are inevitably exposed to painful events, including repetitive procedures, inflammation, or mixed stimulation that may induce long‐term behavioral outcomes. Here, we set up three neonatal painful models to investigate their long‐term effect on somatosensation and cognition. Methods Three types of neonatal pain models in rat were set up. Rat pups were randomly assigned to four groups. The needling pain (NP) group received repetitive needle pricks on the paws from the day of birth (PD0) to postnatal day 7 (PD7) to mimic the diagnostic and therapeutic procedures. The inflammatory pain (IP) group received the injection of carrageenan into the left hindpaw at PD3 to induce IP in peripheral tissues. The mixed pain group received a combination of the NP and IP (NIP). The control (CON) group was untreated. We performed behavioral and biochemical testing of juvenile rats (PD21–PD26). Results The NIP group showed a longer hypersensitivity than the NP group, when given a secondary inflammatory stimulation. NP led to insensitivity to anxiety‐causing stimuli and impairment of fear memory both aggravated by NIP. NP reduced the expression of synapse‐related molecules (GluN1/PSD95/GFAP) in the medial prefrontal cortex, and NIP exacerbated this decrease. The corticosterone secretion in the NIP group increased after the behavioral task, compared with those in other three groups. Conclusion A combination of NP with inflammation occurring in the neonatal period might aggravate the adverse effects of each on somatosensory and cognitive development of rats, the mechanism of which might be associated with the increase of corticosterone secretion and the dysregulation of synaptic molecules

Neural aggregation network for video face recognition

This paper presents a Neural Aggregation Network (NAN) for video face recognition. The network takes a face video or face image set of a person with a variable number of face images as its input, and produces a compact, fixed-dimension feature representation for recognition. The whole network is composed of two modules. The feature embedding module is a deep Convolutional Neural Network (CNN) which maps each face image to a feature vector. The aggregation module consists of two attention blocks which adaptively aggregate the feature vectors to form a single feature inside the convex hull spanned by them. Due to the attention mechanism, the aggregation is invariant to the image order. Our NAN is trained with a standard classification or verification loss without any extra supervision signal, and we found that it automatically learns to advocate high-quality face images while repelling low-quality ones such as blurred, occluded and improperly exposed faces. The experiments on IJB-A, YouTube Face, Celebrity-1000 video face recognition benchmarks show that it consistently outperforms naive aggregation methods and achieves the state-of-the-art accuracy.GH was partly supported by NSFC Grant 61629301. HL’s work was supported in part by Australia ARC Centre of Excellence for Robotic Vision (CE140100016) and by CSIRO Data61

Liquid Formation in Sinters and Its Correlation with Softening Behaviour

Modern blast furnaces with extensive operational volume demand better-quality iron agglomerates as feed for stable operation. Sinter is the principal feed used in blast furnaces across Asia. Liquid generated during the sintering process plays an essential role in the coalescence of the sinter blend and in sinter quality. Therefore, an estimation of liquid properties at peak bed conditions during sintering helps manage sintering liquid behaviour, leading to better control of final sinter properties. In this study, three different iron sinters were reheated to sinter bed conditions, followed by quenching. Electron probe X-ray microanalysis (EPMA) was used to identify the resultant phases and quantify their chemical compositions. The impact of sinter bulk compositions was analysed, especially on sintering liquid properties. Furthermore, experiments were conducted to study the softening and melting behaviour of the sinters, and the cohesive range of the sinters was identified. Finally, the effect of the sinter bulk compositions on sintering liquid properties and softening behaviour is detailed