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Handover authentication protocol is a promising access control technology in the fields of WLANs and mobile wireless sensor networks. In this paper, we firstly review an effcient handover authentication protocol, named PairHand, and its existing security attacks and improvements. Then, we present an improved key recovery attack by using the linearly combining method and reanalyze its feasibility on the improved PairHand protocol. Finally, we present a new handover authentication protocol, which not only achieves the same desirable effciency features of PairHand, but enjoys the provable security in the random oracle model.

A green and efficient process was developed for the conversion of biomass-derived furfuryl alcohol to ethyl levulinate using eco-friendly solid acid catalysts (zeolites and sulfated oxides) in ethanol. Studies for optimizing the reaction conditions such as the substrate concentration, the reaction time, the temperature, and the catalyst loading dosage were performed. With SO42−/TiO2 as the catalyst, a high ethyl levulinate yield of 74.6 mol% was achieved using a catalyst load of 5 wt% at 398 K for 2.0 h. The catalyst recovered through calcination was found to maintain good catalytic activity (47.8 mol%) after three cycles, and it was easily reactivated by re-soaking in H2SO4 solution. Catalyst characterization was based on BET surface area, NH3-TPD, and elemental analysis techniques.

Heteroatom doping is considered to be an efficient strategy to improve the electrochemical performance of carbon-based anode materials for Na-ion batteries (SIBs), due to the introduction of an unbalanced electron atmosphere and increased electrochemical reactive sites of carbon. However, developing green and low-cost approaches to synthesize heteroatom dual-doped carbon with an appropriate porous structure, is still challenging. Here, N/S-co-doped porous carbon sheets, with a main pore size, in the range 1.8−10 nm, has been fabricated through a simple thermal treatment method, using KOH-treated waste bagasse, as a carbon source, and thiourea, as the N and S precursor. The N/S-co-doped carbon sheet electrodes possess significant defects, high specific surface area, enhanced electronic conductivity, improved sodium storage capacity, and long-term cyclability, thereby delivering a high capacity of 223 mA h g−1 at 0.2 A g−1 after 500 cycles and retaining 155 mA h g−1 at 1 A g−1 for 2000 cycles. This work provides a low-cost route to fabricate high-performance dual-doped porous carbonaceous anode materials for SIBs.

Image retrieval or content-based image retrieval (CBIR) can be transformed into the calculation of the distance between image feature vectors. The closer the vectors are, the higher the image similarity will be. In the image retrieval system for large-scale dataset, the approximate nearest-neighbor (ANN) search can quickly obtain the top k images closest to the query image, which is the Top-k problem in the field of information retrieval. With the traditional ANN algorithms, such as KD-Tree, R-Tree, and M-Tree, when the dimension of the image feature vector increases, the computing time will increase exponentially due to the curse of dimensionality. In order to reduce the calculation time and improve the efficiency of image retrieval, we propose an ANN search algorithm based on the Product Quantization Table (PQTable). After quantizing and compressing the image feature vectors by the product quantization algorithm, we can construct the image index structure of the PQTable, which speeds up image retrieval. We also propose a multi-PQTable query strategy for ANN search. Besides, we generate several nearest-neighbor vectors for each sub-compressed vector of the query vector to reduce the failure rate and improve the recall in image retrieval. Through theoretical analysis and experimental verification, it is proved that the multi-PQTable query strategy and the generation of several nearest-neighbor vectors are greatly correct and efficient.

Image similarity measurement is a fundamental problem in the field of computer vision. It is widely used in image classification, object detection, image retrieval, and other fields, mostly through Siamese or triplet networks. These networks consist of two or three identical branches of convolutional neural network (CNN) and share their weights to obtain the high-level image feature representations so that similar images are mapped close to each other in the feature space, and dissimilar image pairs are mapped far from each other. Especially, the triplet network is known as the state-of-the-art method on image similarity measurement. However, the basic CNN can only handle fixed-size images. If we obtain a fixed size image via cutting or scaling, the information of the image will be lost and the recognition accuracy will be reduced. To solve the problem, this paper has proposed the triplet spatial pyramid pooling network (TSPP-Net) through combing the triplet convolution neural network with the spatial pyramid pooling. Additionally, we propose an improved triplet loss function, so that the network model can realize twice distance learning by only inputting three samples at one time. Through the theoretical analysis and experiments, it is proved that the TSPP-Net model and the improved triple loss function can improve the generalization ability and the accuracy of image similarity measurement algorithm.

To improve the accuracy of calibration of C-arm, and overcome the space limitation in surgery, we proposed a new calibrator for online calibration of C-arm. After the image rectification by a polynomial fitting-based global correction method, the C-arm was assumed as an ideal pinhole model. The relationships between two kinds of spatial calibration errors and the distribution of fiducial points were studied: the performance of FRE (Fiducial Registration Error) and TRE (Target Registration Error) were not consistent, but both were best at the 12 marked points; the TRE decreased with the increase of the uniformity of calibration points distribution, and with the decrease of the distance between the target point and the center of calibration points. A calibrator with 12 fiducial points conical helically distributed, which could be placed on the knee, was an attractive option. A total of 10 experiments on C-arm calibration accuracy were conducted and the mean value of mapping error was 0.41 mm. We designed an ACL reconstruction navigation system and carried out specimen experiments on 4 pairs of dry femur and tibia. The mean accuracy of navigation system was 0.85 mm, which is important to the tunnel positioning for ACL reconstruction.

The semigroup properties of the Riemann–Liouville fractional integral have played a key role in dealing with the existence of solutions to differential equations of fractional order. Based on some results of some experts’, we know that the Riemann–Liouville variable order fractional integral does not have semigroup property, thus the transform between the variable order fractional integral and derivative is not clear. These judgments bring us extreme difficulties in considering the existence of solutions of variable order fractional differential equations. In this work, we will introduce the concept of approximate solution to an initial value problem for differential equations of variable order involving the derivative argument on half-axis. Then, by our discussion and analysis, we investigate the unique existence of approximate solution to this initial value problem for differential equation of variable order involving the derivative argument on half-axis. Finally, we give examples to illustrate our results.

The effects of interactions of soil type and soil depth on soil C:N:P stoichiometry and microorganisms are poorly understood. In this study, soil samples (0⁻10, 10⁻20, 20⁻30, 30⁻50, 50⁻100 cm) were collected from two soil types (Haplic luvisols and Eutric cambisols) in Sabina przewalskii Kom. forest of Qinghai-Tibet Plateau. The soil C:N ratio and soil microbial biomass (SMB) measured using phospholipid fatty acid in Eutric cambisols were significantly higher than in Haplic luvisols, while soil C:P and N:P ratios were the opposite. In the two soil types, the soil C:N ratio significantly increased with soil depth, and the soil C:P and N:P ratios declined. Structural equation modelling (SEM) indicated that soil depth directly affected soil C, N and P contents. Soil type and soil depth could directly affect soil fungal and bacterial biomass, and indirectly affect both of them through soil bulk density. Meanwhile soil fungal biomass was influenced by soil depth through Total C. These results highlighted that the vertical distribution of soil bacteria could largely be attributed to changes of soil fungi depending on soil carbon resources.

In the title molecule, C28H33ClN4, the central pyrimidine ring is twisted with respect to the two benzene rings, making dihedral angles of 13.56 (19) and 23.1 (2)°. In the crystal, weak C—H...π interactions link the molecules into supramolecular chains propagating along the c-axis direction.

By Leggett-Williams norm-type theorem for coincidences due to O’Regan and Zima, we discuss the existence of positive solutions to fractional order with periodic boundary conditions at resonance. At last, an example is presented to demonstrate the main results.

The traditional bearing fault diagnosis method is achieved often by sampling the bearing vibration data under the Shannon sampling theorem. Then, the information of the bearing state can be extracted from the vibration data, which will be used in fault diagnosis. A long-term and continuous monitoring needs to sample and store large amounts of raw vibration signals, which will burden the data storage and transmission greatly. For this problem, a new bearing fault diagnosis method based on compressed sensing is presented, which just needs to sample and store a small amount of compressed observation data and uses these data directly to achieve the fault diagnosis. First, several over-complete dictionaries are trained by dictionary learning method using the historical operating data of the bearings. Each of these dictionaries can be effective in signal sparse decomposition for a particular state, while the signals corresponding to other states cannot be decomposed sparsely. According to this difference, the bearing states can be identified finally. The fault diagnosis results of the proposed method with different parameters are analyzed. The effectiveness of the method is validated by experimental tests.

Low-level-laser therapy (LLLT) is an effective complementary treatment, especially for anti-inflammation and wound healing in which dermis or mucus mast cells (MCs) are involved. In periphery, MCs crosstalk with neurons via purinergic signals and participate in various physiological and pathophysiological processes. Whether extracellular ATP, an important purine in purinergic signaling, of MCs and neurons could be modulated by irradiation remains unknown. In this study, effects of red-laser irradiation on extracellular ATP content of MCs and dorsal root ganglia (DRG) neurons were investigated and underlying mechanisms were explored in vitro. Our results show that irradiation led to elevation of extracellular ATP level in the human mast cell line HMC-1 in a dose-dependent manner, which was accompanied by elevation of intracellular ATP content, an indicator for ATP synthesis, together with [Ca2+]i elevation, a trigger signal for exocytotic ATP release. In contrast to MCs, irradiation attenuated the extracellular ATP content of neurons, which could be abolished by ARL 67156, a nonspecific ecto-ATPases inhibitor. Our results suggest that irradiation potentiates extracellular ATP of MCs by promoting ATP synthesis and release and attenuates extracellular ATP of neurons by upregulating ecto-ATPase activity. The opposite responses of these two cell types indicate complex mechanisms underlying LLLT.

We have developed a robot system for closed diaphyseal fracture reduction. Because accuracy is essential for the treatment effects of the robot system and for the safety of both the patients and surgeons, we analysed accuracy in a systematic way. Both the structure of the robot and the operation procedure are described. Using the transfer model of errors in series and the error differential solving method for parallel mechanisms, an error model was established, and the main influencing factors of errors were considered. The Monte Carlo method was used to perform the simulation based on the error model. Experiments of image registration, of the mechanism and of the whole robot system were tested in different aspects to verify that the results of the simulation are correct. The system accuracy was compared with clinical standards to show that the robot system fulfilled the requirements for closed diaphyseal fracture reduction. The accuracy analysis method also provides an efficient path for other medical robots.

We establish the existence results for two-point boundary value problem of fractional differential equations at resonance by means of the coincidence degree theory. Furthermore, a result on the uniqueness of solution is obtained. We give an example to demonstrate our results.

We introduce an extension of the mass-spring model applied to human tissue that can truly reflect the mechanical properties of a living person's tissue under large deformations under pressure by a massage head. The model is used in the force-position control system and helps us to control the massage force more accurately. Parameters of the model were determined according to the experimental results. Simulation results demonstrated that the model succeeded in modeling living tissue under large deformation, and the force-position control system based on the soft tissue model under large deformation achieved higher accuracy than the control system based on the soft tissue model with constant stiffness.

Emerging studies show that long noncoding RNAs (lncRNAs) have important roles in carcinogenesis. lncRNA ZEB1 antisense 1 (ZEB1-AS1) is a novel lncRNA, whose clinical significance, biological function, and underlying mechanism remains unclear in glioma. Here, we found that ZEB1-AS1 was highly expressed in glioma tissues, being closely related to clinical stage of glioma. Moreover, patients with high ZEB1-AS1 levels had poor prognoses, with the evidence provided by multivariate Cox regression analysis indicating that ZEB1-AS1 expression could serve as an independent prognostic factor in glioma patients. Functionally, silencing of ZEB1-AS1 could significantly inhibit cell proliferation, migration, and invasion, as well as promote apoptosis. Knockdown of ZEB1-AS1 significantly induced the G0/G1 phase arrest and correspondingly decreased the percentage of S phase cells. Further analysis indicated that ZEB1-AS1 could regulate the cell cycle by inhibiting the expression of G1/S transition key regulators, such as Cyclin D1 and CDK2. Furthermore, ZEB1-AS1 functioned as an important regulator of migration and invasion via activating epithelial to mesenchymal transition (EMT) through up-regulating the expression of ZEB1, MMP2, MMP9, N-cadherin, and Integrin-β1 as well as decreasing E-cadherin levels in the metastatic progression of glioma. Additionally, forced down-regulation of ZEB1-AS1 could dramatically promote apoptosis by increasing the expression level of Bax and reducing Bcl-2 expression in glioma. Taken together, our data suggest that ZEB1-AS1 may serve as a new prognostic biomarker and therapeutic target of glioma.

The objective of private authentication for Radio Frequency Identification (RFID) systems is to allow valid readers to explicitly authenticate their dominated tags without leaking the private information of tags. In previous designs, the RFID tags issue encrypted authentication messages to the RFID reader, and the reader searches the key space to identify the tags. Without key updating, those schemes are vulnerable to many active attacks, especially the compromising attack. We propose a strong and lightweight RFID private authentication protocol, SPA. By designing a novel key updating method, we achieve the forward secrecy in SPA with an efficient key search algorithm. We also show that, compared with existing designs, (SPA) is able to effectively defend against both passive and active attacks, including compromising attacks. Through prototype implementation, we demonstrate that SPA is practical and scalable for current RFID infrastructures.

To investigate the regulation of K17 expression by the pro-inflammatory cytokine IL-22 in keratinocytes and its important role in our previously hypothesized "K17/T cell/cytokine autoimmune loop" in psoriasis.K17 expression was examined in the IL-22-treated keratinocytes by real-time quantitative PCR, ELISA, Western blot and Immunofluorescence. In addition, the signaling pathways involved in K17 regulation were investigated with related inhibitors and siRNAs. In addition, K17 expression was examined in the epidermis of IL-22-injected mouse skin.IL-22-induced K17 expression was confirmed in keratinocytes and the epidermis of IL-22-injected mouse skin at both mRNA and protein levels, which is an important complement to the autoimmune loop. We further investigated the regulatory mechanisms and found that both STAT3 and ERK1/2 were involved in the up-regulation of K17 expression induced by IL-22.IL-22 up-regulates K17 expression in keratinocytes in a dose-dependent manner through STAT3- and ERK1/2-dependent mechanisms. These findings indicated that IL-22 was also involved in the K17/T cell/cytokine autoimmune loop and may play an important role in the progression of psoriasis.