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Total acid content (TAC) and moisture content (MC) are very important parameters during Solid-State Fermentation (SSF) processes. The feasibility of using hyperspectral imaging (HSI) technology for predicting TAC and MC in vinegar cultures during SSF processes was investigated. Prediction models were constructed using variables selected from spectral and spatial data from associated 3-D hyperspectral datacubes to predict the relative content of TAC and MC for each pixel in the hyperspectral image. Models were developed using genetic algorithm (GA) optimization combined with partial least squares regression (PLS) dependent on the spectral variables yielded good prediction results for both TAC and MC. The determination coefficients ( R p 2 ) for TAC and MC were 0.8565 and 0.8162, respectively. Finally, the distribution maps of TAC and MC for a vinegar culture sample were obtained. These distribution maps could be implemented to estimate the uniformity of fermentation products during SSF.

To improve user’s data rate and network coverage, multi-homing heterogeneous network has been considered as a key technology in recent years. However, traditional power allocation schemes cannot provide good robustness and suppress the impact of parameter perturbation due to the random interference and channel delays. A robust power allocation algorithm is proposed for an orthogonal frequency division multiple access based multi-homing heterogeneous network under energy harvesting. Considering the channel uncertainties from base stations to users, the total data rate of all mobile terminals (MTs) is maximized under the rate outage constraint of MT. Based on the uniform distribution of uncertainty, the originally robust counterpart problem is transformed to a deterministic and convex one. The Lagrange dual decomposition theory is used to solve it. Simulation results demonstrate that the proposed scheme has good convergence and robustness.

Image stitching is one of the branches of computer vision. It combines two or more images for a scene to acquire a high-resolution panoramic image. An invariant local function often uses to stitch two images together. Since the flat plate of a digital radiography (DR) system does not cover all parts of the body, the whole bone structure image cannot seize in a single scan. To solved this problem, image stitching is broadly utilized by medical systems to stitch DR images, which can be helpful for scoliosis or lower extremity deformities in the diagnosis, and pre-operative planning are of great importance. In this paper, the stitching and retrieval of medical images planned. To conquer the background noise in medical images, and improve the recovery of quality and stitching rapidity of medical images, a random sample consensus (RANSAC) algorithm is useful to stitching the images of Chest digital radiography by scale-invariant feature transform (SIFT) and speeded-up robust features (SURF) feature extraction. Down-sampling utilizes to lessen the size of the images and reduction the measure of calculation. In the interim, the phase correlation is engaged to discover the overlapping region. After feature matching and perspective transformation, the stitched image is gotten dependent on the homography. At last, experimentation has finished showing the presentation.

The protection of information security is a very important technique requirement in Body area networks (BANs). According to the limitation of energy, the traditional encryption methods which adopt the complex algorithm and the large consumption are not suitable for BANs. This paper proposes a new encryption method based on the channel model of BANs, which adopts the path loss from the BAN systems to form the initial key, utilizes the LFSR (Linear Feedback Shift Register) circuit to generate the key stream, and then encrypts the data in the coordinator of the BAN system. This new encryption method has the advantages of low energy consumption, simple hardware implementation, and dynamic key updating.

In this work, a wearable, intelligent testing device based on nRF52832 microcontroller is designed to monitor the changes of life signs parameters of patients with depression and cardiovascular disease and determine disease seriousness and mood stability. The proposed device uses the ADS1292R chip and conductive silica gel for collection and preconditioning the electrocardiogram (ECG) and respiratory signals, which and then filtered by nRF52832. Since nRF52832 is a Bluetooth chip, it transmits the life signs signals to the mobile phone APP through Bluetooth to be displayed on a device screen. The wearable, intelligent detection devices have the advantages of small size, low power consumption, low cost, and convenience to be wearable.

Global Navigation Satellite System (GNSS) cannot achieve accurate positioning and navigation in the indoor environment. Bluetooth Beacon positioning is one of the most widely used technology. Because of the time-varying characteristics of the Bluetooth received signal strength indication (RSSI), traditional positioning algorithms have large ranging errors by using fixed path loss models. In this paper, we proposes a RSSI real-time correction method based on Bluetooth gateway, which is used to detect the RSSI fluctuations of surrounding Bluetooth nodes and upload them to the cloud server. The terminal to be located collects the RSSIs of surrounding Bluetooth nodes, and then adjusted by the RSSI fluctuation information stored on the server in real time. The adjusted RSSIs can be used for calculation and obtain a more accurate distance, i.e., smaller positioning error. Finally, the position of blind nodes is estimated by least squares algorithm. The experiment shows that the proposed method improves the positioning accuracy.

The Multiple-Input Multiple-Out (MIMO) technology can improve system capacity by using multiple antenna transceivers with high decode complexity at the receiver. The Integer-Forcing (IF) linear detection algorithm is used to reduce the complexity of implementation in MIMO system, and its performance is close to the ML detection algorithm. However, the decode complexity of the IF detection will increase with the increase of antenna number. In order to further reduce the decode complexity, we propose a new detection algorithm called Group Integer-Forcing detection algorithm in this paper. In this algorithm, the received symbols are divided into groups, then each group will be decoded by the IF detection respectively to recover transmitted codewords in their own group, and those recovered codewords will be gathered to obtain original transmitted information before grouping. The Group Integer-Forcing detection algorithm reduce the decode complexity via grouping, so it has great advantage on complexity compare with the IF detection. It also has better error performance than the ZF detection algorithm according to simulation results, and the error performance gap is more and more obvious with the increased antenna numbers.

The Global Navigation Satellite System (GNSS) cannot achieve accurate positioning and navigation in the indoor environment. Therefore, efficient indoor positioning technology has become a very active research topic. Bluetooth beacon positioning is one of the most widely used technologies. Because of the time-varying characteristics of the Bluetooth received signal strength indication (RSSI), traditional positioning algorithms have large ranging errors because they use fixed path loss models. In this paper, we propose an RSSI real-time correction method based on Bluetooth gateway which is used to detect the RSSI fluctuations of surrounding Bluetooth nodes and upload them to the cloud server. The terminal to be located collects the RSSIs of surrounding Bluetooth nodes, and then adjusts them by the RSSI fluctuation information stored on the server in real-time. The adjusted RSSIs can be used for calculation and achieve smaller positioning error. Moreover, it is difficult to accurately fit the RSSI distance model with the logarithmic distance loss model due to the complex electromagnetic environment in the room. Therefore, the back propagation neural network optimized by particle swarm optimization (PSO-BPNN) is used to train the RSSI distance model to reduce the positioning error. The experiment shows that the proposed method has better positioning accuracy than the traditional method.

Compared with the Multiple-Input Multiple-Output (MIMO) systems coded with Space-Time Block Code (STBC), Spatial Modulation (SM) has high spectral efficiency and low diversity gain. After combined with Space-Time Block Code (STBC), so called STBC-SM is able to obtain higher diversity gain at the same time. In this paper, we propose a new full-diversity STBC-SM scheme for spatial modulation systems with four transmit antennas. The transmitted information is partitioned into two parts for STBC-SM codeword selection and modulation symbol mapping, respectively. The proposed codeword matrices are constructed by simultaneously choosing the transmit antennas of one pair of orthogonal STBC instead of only one. Precoding and symbol-crossing of the modulated symbols are carried out to ensure higher diversity gain. By theoretical analysis, the designed scheme is proved to be full diversity. Finally, simulation results is presented and show that the proposed STBC-SM obviously improves the diversity gain and system performance.

Body area network (BAN) consists of intercommunicating sensors, which are either wearable, or can be implanted into the human body. Being a network that features critical information, BAN requires encryption, however common encryption methods found in computer networks are not ideal due to complex algorithms and high power consumption. The authors propose a new encryption method based on the human body channel. This new encryption method has the advantages of low-power, dynamic updating, rapid operation, and easy implementation, which is suitable for BAN systems.

In this paper, we investigate the robust power allocation problem in a two-tier orthogonal frequency division multiplexing (OFDM) access based heterogeneous networks, where the minimal rate requirement of each femtocell user and interference power constraint of macrocell user are properly controlled under channel uncertainties. We formulate an optimization problem to maximize the sum data rate of the femtocell users under the consideration of channel uncertainties of both cross-tier and intra-tier links while guaranteeing the rate requirement of femtocell users and controlling the interference to the macrocell users in terms of probability. According to the distribution models of estimation errors, we transform the original problem into a deterministic one and solve it by the subgradient method and Karush-Kuhn-Tuchker conditions. Simulation results show that our approach can fast converge to the optimal value and well protect the performance of macrocell users under channel uncertainties.

Heterogeneous wireless networks are a promising technology in next generation wireless communication networks, which has been shown to efficiently reduce the blind area of mobile communication and improve network coverage compared with the traditional wireless communication networks. In this paper, a robust power allocation problem for a two-tier heterogeneous wireless networks is formulated based on orthogonal frequency-division multiplexing technology. Under the consideration of imperfect channel state information (CSI), the robust sum-rate maximization problem is built while avoiding sever cross-tier interference to macrocell user and maintaining the minimum rate requirement of each femtocell user. To be practical, both of channel estimation errors from the femtocells to the macrocell and link uncertainties of each femtocell user are simultaneously considered in terms of outage probabilities of users. The optimization problem is analyzed under no CSI feedback with some cumulative distribution function and partial CSI with Gaussian distribution of channel estimation error. The robust optimization problem is converted into the convex optimization problem which is solved by using Lagrange dual theory and subgradient algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm by the impact of channel uncertainties on the system performance.

Rapid progress of networking technologies leads to an exponential growth in the number of unauthorized or malicious network actions. As a component of defense-in-depth, Network Intrusion Detection System (NIDS) has been expected to detect malicious behaviors. Currently, NIDSs are implemented by various classification techniques, but these techniques are not advanced enough to accurately detect complex or synthetic attacks, especially in the situation of facing massive high-dimensional data. Besides, the inherent defects of NIDSs, namely, high false alarm rate and low detection rate, have not been effectively solved. In order to solve these problems, data fusion (DF) has been applied into network intrusion detection and has achieved good results. However, the literature still lacks thorough analysis and evaluation on data fusion techniques in the field of intrusion detection. Therefore, it is necessary to conduct a comprehensive review on them. In this article, we focus on DF techniques for network intrusion detection and propose a specific definition to describe it. We review the recent advances of DF techniques and propose a series of criteria to compare their performance. Finally, based on the results of the literature review, a number of open issues and future research directions are proposed at the end of this work.

Generalized spatial modulation (GSM) activates more transmit antennas than spatial modulation to increase the spectral efficiency. Although the maximum likelihood (ML) detector is able to achieve the optimal performance, its exhaustive search leads to intractable computational complexity. In this paper, we design a detection scheme based on Integer-Forcing (IF) algorithm, which utilize IF receiver to decode the transmitted symbols for all possible antenna combinations, and then compare the Euclidean distances between the detected symbols and the received signals. Finally, the symbol vector with minimum Euclidean distance and the corresponding antenna combination are detected as the decided symbols and transmit antenna combination. Simulation results shows that the designed detection scheme achieves obviously better performance than the ZF and the MMSE detection with relatively lower complexity.

Mobile ad hoc network (MANET) is a kind of mobile multi-hop network which can transmit data through intermediate nodes, it has been widely used and become important since the growing of the market of Internet of Things (IoT). However, the transmissions on MANET are vulnerable, it usually suffered with many internal or external attacks, and the research on security topics of MANET are becoming more and more hot recently. Blackhole Attack is one of the most famous attacks to MANET. In this paper, we focus on the Blackhole Attack in AODV protocol, and use NS-3 network simulator to study the impact of Blackhole Attack on network performance parameters, such as the Throughput, End-to-End Delay and Packet Loss Rate. We further analyze the changes in network performance by adjusting the number of blackhole nodes and total nodes, and the movement speed of mobile nodes. The experimental results not only reflect the behaviors of the Blackhole Attack and its damage to the network, but also provide the characteristics of Blackhole Attacks clearly. This is helpful to the research of Blackhole Attack feature extraction and MANET security measurement.

Purpose: The chemokine receptor CXCR4 is overexpressed in various types of human cancers. As a specific imaging agent of CXCR4, 68Ga-NOTA-NFB was investigated in this study to assess its safety, biodistribution and dosimetry properties in healthy volunteers, and to preliminarily evaluate its application in glioma patients. Methods: Six healthy volunteers underwent whole-body PET scans at 0, 0.5, 1, 2 and 3 h after 68Ga-NOTA-NFB injection (mean dose, 182.4 ± 3.7 MBq (4.93 ± 0.10 mCi)). For time-activity curve calculations, 1 mL blood samples were obtained at 1, 3, 5, 10, 30, 60, 90, 120, 150 and 180 min after the injection. The estimated radiation doses were calculated by OLINDA/EXM software. Eight patients with glioma were enrolled and underwent both 68Ga-NOTA-NFB and 18F-FDG PET/CT scans before surgery. The expression of CXCR4 on the resected brain tumor tissues was determined by immunohistochemical staining. Results: 68Ga-NOTA-NFB was safe and well tolerated by all subjects. A rapid activity clearance from the blood circulation was observed. The organs with the highest absorbed doses were spleen (193.8 ± 32.5 μSv/MBq) and liver (119.3 ± 25.0 μSv/MBq). The mean effective dose was 25.4 ± 6.1 μSv/MBq. The maximum standardized uptake values (SUVmax) and the maximum target to non-target ratios (T/NTmax) of 68Ga-NOTA-NFB PET/CT in glioma tissues were 4.11 ± 2.90 (range, 0.45-8.21) and 9.21 ± 8.75 (range, 3.66-24.88), respectively, while those of 18F-FDG PET/CT were 7.34 ± 2.90 (range, 3.50-12.27) and 0.86 ± 0.41 (range, 0.35-1.59). The histopathological staining confirmed that CXCR4 was overexpressed on resected tumor tissues with prominent 68Ga-NOTA-NFB uptake. Conclusion: With a favorable radiation dosimetry profile, 68Ga-NOTA-NFB is safe for clinical imaging. Compared to 18F-FDG PET/CT, 68Ga-NOTA-NFB PET/CT is more sensitive in detecting glioma and could have potential in diagnosing and treatment planning for CXCR4 positive patients.

β-elemene, the active component of elemene (1-methyl-1-vinyl-2,4-diisopropenyl-cyclohexane), is a naturally occurring compound isolated from the traditional Chinese medicinal herb Curcuma wenyujin. Studies have confirmed that β-elemene enhances the radiosensitivity of lung cancer cell lines such as A549, by multiple pathways; however, their underlying mechanisms and pathways are yet to be elucidated. In the present study, two-dimensional differential in-gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometry were used to profile the different proteins in A549 cell xenograft models of both treatment groups. The protein/mRNA expression was assessed by reverse transcription-polymerase chain reaction and western blotting techniques in tumor samples from all treatment groups. As a critical player in redox regulation of cancer cells, inhibition of peroxiredoxin-1 (Prx-1) may be an effective option for enhancing the tumor response to radiation. We further verified Prx-1 expression at the transcription and translation levels. β-elemene at a dose of 45 mg/kg had little effect on the Prx-1 protein expression, which was correlated with a moderate antitumor effect. However, a 45 mg/kg dose of β-elemene significantly inhibited the Prx-1 mRNA expression, thereby suggesting a possible influence on the transcriptional process, and radiation significantly increased the Prx-1 mRNA/protein expression compared to the control group (p

In this paper, we present a new global optimization method to solve nonlinear systems of equations. We reformulate given system of nonlinear equations as a global optimization problem and then give a new auxiliary function method to solve the reformulated global optimization problem. The new auxiliary function proposed in this paper can be a filled function, a quasi-filled function or a strict filled function with appropriately chosen parameters. Several numerical examples are presented to illustrate the efficiency of the present approach.

Body area network (BAN) is a key technology of solving remote medical, where protecting security of vital signs information is a very important technique requirement. This paper presents a data security scheme based on ECG characteristics, investigating methods of the circuit-level data encryption and dynamic key refreshment due to the obtained ECG signal characteristic value. The proposed scheme is constructed from the inherent features of the BAN system, adopting vital information from security protection, which has advantages of high strength, low cost, and easy implementation. Therefore, the scheme helps to design low-power sensor nodes and provides theoretical support and engineering implementation.

Spatial modulation (SM) is a promising multiple-input multiple-output (MIMO) transmission technology, which exploits the indices of transmit antennas to encode information into the spatial dimension and needs less radio frequency chains. To detect the transmitted information, the maximum likelihood (ML) algorithm is often adopted which has high computational complexity. Some low-complexity detection algorithms only consider hard-decision cases with no channel coding. In this paper, a low-complexity soft output detection algorithm is proposed for coded spatial modulation systems. Its computational complexity doesn't increase with the modulation order and hence much lower than the soft output ML detection algorithm. Simulation results demonstrate that the bit error rate (BER) performance is near to the ML detection with obvious complexity reduction. By sorting the detection metrics and selecting less transmit antenna indices as search candidates to compute soft bit information, further reduction of computational complexity could be obtained.

With the development of the fifth generation communication technology, how to improve system capacity and spectral efficiency is a key issue, which has attracted more and more attention from industry and academia. Heterogeneous network has been considered as a new promising technique for enhancing the quality of service, energy and spectrum efficiency as well as coverage of network due to different radio access technology (RAT) and different network structures. In this paper, the rate maximization resource allocation problem for multiuser cognitive heterogeneous networks is formulated to flexibly use network resource and improve the overall capacity, which simultaneously considers cross-tier interference constraint and maximum transmit power of cognitive microcell base station. The non-convex optimization problem is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results are given to show the performance of the proposed algorithm in terms of the achievable system capacity and the interference to the macrocell network.

Integrin αThirty-one patients with pathologically confirmed lung cancer were enrolled (21 were NSCLC and 10 were SCLC). PET/CT images were acquired usingTheThe uptake of

Intermodal transport generally concerns a few of fundamental elements such as freight's characteristics, shippers' and forwarder evaluations, etc.. The freight's characteristics decide the relevant potential demands and the possibility to combine different transport means into intermodalism. The evaluations of shippers and forwarders always have an important impact on the selections of transport. This paper comparatively analyzes the critical elements of freight's characteristics, shippers' and forwarder evaluations. Moreover, the possibilities and relevant issues to form the road-rail intermodal freight transport are discussed, and some suggestions are proposed to improve the railway freight services.

CD13 receptor as a tumor vasculature biomarker has attracted great attention in cancer research. Through phage display screening, NGR-containing peptides have been characterized as specific ligands binding to CD13 receptor. In this study, a (64)Cu-labeled dimeric NGR peptide based on sarcophagine cage was synthesized and evaluated for micropositron emission tomography (PET) imaging of CD13 expression in vivo. Macrocyclic chelating agent (sarcophagine cage) was conjugated with two azide moieties, followed by mixing with an alkyne-containing NGR peptide to rapidly provide the Sar-NGR2 peptide by click chemistry. Radiolabeling of Sar-NGR2 with (64)Cu was achieved in >90% decay-corrected yield with radiochemical purity of >99%. The cell uptake study showed that (64)Cu-Sar-NGR2 binds to CD13-positive HT-1080 cells, but not to CD13-negative MCF-7 cells. MicroPET imaging results revealed that (64)Cu-Sar-NGR2 exhibits good tumor uptake in CD13-positive HT-1080 xenografts and significantly lower tumor uptake in CD13-negative MCF-7 xenografts. The CD13-specific binding of (64)Cu-Sar-NGR2 was further verified by significant reduction of tumor uptake in HT-1080 tumor xenografts with coinjection of a nonradiolabeled NGR peptide. The biodistribution results demonstrated good tumor/muscle ratio (8.28 ± 0.37) of (64)Cu-Sar-NGR2 at 24 h pi in HT-1080 tumor xenografts, which is in agreement with the quantitative analysis of microPET imaging. In conclusion, sarcophagine cage has been successfully applied to the construction of a (64)Cu-labeled dimeric NGR-containing peptide. In vitro and in vivo studies demonstrated that (64)Cu-Sar-NGR2 is a promising PET probe for imaging CD13 expression in living mice.

Local public transport is recently re-recognized even in the developed countries, as an available resolution for the social issues in the urbanization, such as traffic congestion and safety, globe warming by CO2 emissions, and the process of low birthrate and aging society, etc. Because of some reasons including conventional management system, actual situations of business operations and motorization, many companies of local public transport are running into the red operation. As experiences and lessons from the developed countries, in this study, the situations of local rail transits are firstly analyzed. And then under the bases of the descriptions of cost compositions of rail companies, the comparative analyses between local rails and railway are performed. Furthermore, the governmental assistances are reviewed and discussed. Finally, the relevant technological innovations and transport policies are suggested as the improvements directions of local rails.

This paper designs a high-gain wide-bandwidth multistage amplifier by employing the dual-miller compensation with nulling-resistor and dual-feedforward compensation (DMCNR-DFC) in 0.35μm BCD process. The designed DMCNR-DFC multistage amplifier achieves well performance including gain-bandwidth product (GBW) and slew rate (SR). Simulation results show that the DMCNR-DFC multistage amplifier achieves a dc gain of about 121.1dB and GBW of about 6.1MHz with 52o phase margin.

The analysis of magnetic coupling resonance based on Mode Coupling theory is often complicated and abstract. Moreover, this theory is inconvenient when it comes to designing the circuits. Based on the mutual inductance in the circuit, we completed theoretical derivation, parameters calculation and circuit simulation for each of the two-coil and the four-coil structure. The received power and the transmission efficiency under different conditions are analyzed and compared. Experimental results show that too high or too low resonant frequency will affect the efficiency of transmission and reception of energy in the two-coil structure, a problem of optimal distance for energy transmission is existed in four-coil structure, the resonant frequency of the system will also affect the distance.

A novel ECG filtering algorithm was researched, which was suitable for the MSP430 platform. Several ECG signal wavelet denoising algorithms were simulated on matlab to compare their filtering effect. The mexican-hat wavelet denoising algorithm can get a better effect on filtering of ECG signal (No. 203 data from the MIT-BIH ECG database). The time complexity of the algorithm is O(n2), and the SNR can also be up to 66%.

Baseline drift is the main noise of ECG signals which affects the detection accuracy so its removal plays a significantrole in the ECG signal preprocessing. Complex calculation and non-optimal signal processing cause problems of ineffective results and low real-time effects in traditional methods. This paper designs a new filter to remove baseline drift based on the theory of mathematical morphology, which is created by the geometric parameters of the ECG signal. Experiments show that the method can effectively remove the noise of baseline drift by simple computation and is helpful to improve the detection accuracy.

In this paper, a low temperature coefficient bandgap voltage (BGR) is designed for A/D converter by adopting piecewise-linear compensation technique. The designed BGR is analyzed and simulated in SMIC 0.18μm CMOS process. Simulation results show that the PSRR of the designed BGR achieves-72.51dB, -72.49dB, and-70.58dB at 10Hz, 100Hz and 1kHz respectively. The designed BGR achieve the temperature coefficient of 1.57 ppm/°C when temperature is in the range from-35°C to 125°C. When power supply voltage VDD changes from 1V to 7V, the deviation of the designed BGR output voltage VREF is only 4.465μV.

CD13 receptor plays a critical role in tumor angiogenesis and metastasis. We therefore aimed to develop (99m)Tc-labeled monomeric and dimeric NGR-containing peptides, namely, NGR1 and NGR2, for SPECT imaging of CD13 expression in HepG2 hepatoma xenografts. Both NGR-containing monomer and dimer were synthesized and labeled with (99m)Tc. In vivo receptor specificity was demonstrated by successful blocking of tumor uptake of (99m)Tc-NGR dimer in the presence of 20 mg/kg NGR2 peptide. Western blot and immunofluorescence staining confirmed the CD13 expression in HepG2 cells. The NGR dimer showed higher binding affinity and cell uptake in vitro than the NGR-containing monomer, presumably due to a multivalency effect. (99m)Tc-Labeled monomeric and dimeric NGR-containing peptides were subjected to SPECT imaging and biodistribution studies. SPECT scans were performed in HepG2 tumor-bearing mice at 1, 4, 12, and 24 h post-injection of ~7.4 MBq tracers. The metabolism of tracers was determined in major organs at different time points after injection which demonstrated rapid, significant tumor uptake and slow tumor washout for both traces. Predominant clearance from renal and hepatic system was also observed in (99m)Tc-NGR1 and (99m)Tc-NGR2. In conclusion, monomeric and dimeric NGR peptide were developed and labeled with (99m)Tc successfully, while the high integrin avidity and long retention in tumor make (99m)Tc-NGR dimer a promising agent for tumor angiogenesis imaging.

Airborne TIR remote sensing can obtain land surface temperature (LST) with high spatial resolution. However, the swath width of airborne stripes is usually limited. Therefore, it is necessary to generate the LSTs for a large area through temporal normalization of LSTs derived from different stripes. By selecting an agricultural oasis as the study area, this study compares the diurnal temperature cycle (DTC) model and polynomial regression (PR) technique in the temporal normalization of the LSTs derived from the Thermal Airborne Spectrographic Imager (TASI) data. The results show that the DTC model has better accuracy in normalizing the LSTs. However, the PR technique is simple and requires less ancillary data. The DTC method can normalize the LST to any specific time and generate temporally continuous LSTs, while the PR method can only do relative normalization. This study is helpful to reduce the temperature differences of different airborne stripes and obtain airborne LSTs with both high spatial and temporal resolutions.

The pulse wave signal contains a variety of noises and has strong nonlinear and non-stationary. According to the previous wavelet transformation method, this paper proposes a PPG signal de-noising algorithm based on dual-tree complex wavelet transform (DTCWT) and morphological filtering. With the advantage of simple construction, clear mathematical implications and low computational complexity, this method overcomes the shift sensitive and the frequency aliasing in the discrete wavelet transform. The simulation results show that this algorithm could remove the power line interference and EMG interference, and the quantitative index of SNR and mean square error is superior to the traditional threshold de-noising algorithm. Therefore, the DTCWT and morphological filtering de-noising algorithm would obtain a clear pulse wave signal.

Elemene (1-methyl-1-vinyl-2,4-diisopropenyl-cyclohexane) is a naturally occurring compound that can be isolated from the traditional Chinese medicinal herb Curcuma wenyujin. β-elemene, its active component, has recently been demonstrated to enhance the radiosensitivity of human cancer cell lines in vitro and of one animal tumor in vivo. The underlying mechanism, however, is still unclear. In this study, we demonstrated for the first time that β-elemene significantly improves the radiosensitivity of A549 lung adenocarcinoma xenograft in vivo as measured by tumor regrowth delay experiments. Our results showed that β-elemene, at 45 mg/kg, significantly inhibited radiation-induced expression of survivin and hypoxia-inducible factor (HIF)-1 α proteins. Because HIF-1 α is known to regulate survivin transcription and acts as upstream regulator of survivin, it is possible that β-elemene regulates the transcription of survivin through HIF-1 α. Our study suggests that β-elemene is a promising drug to enhance tumor radioresponse, and survivin and HIF-1 α are novel targets of β-elemene.

The decoding complexity of the layered Alamouti code with the maximum-likelihood (ML) receiver is high. Partial interference cancellation (PIC) group decoding is an attractive method to reduce the ML decoding complexity. However, different grouping schemes for the PIC group decoding may have different performances. In this letter, by fully taking advantage of the Alamouti code structure, we analytically calculate the power gains of the information symbols after the PIC for a grouping scheme, where the zero-forcing (ZF) operator is used for the PIC. We then propose an optimal grouping scheme for the PIC group decoding by proposing a criterion to choose the grouping schemes adaptively so that the power gains of the information symbols are maximized after the PIC.

This paper investigates the reduction in logistics costs and carbon dioxide (CO2) emissions which can be induced by shifting freight from road to rail, focusing on inter-regional surface freight convoys carrying manufactured goods. The article provides a summary analysis of the areas served by rail freight terminals, the relationships between, regions and a target rail corridor in the light of the rail freight sector's present situation in Japan. Using competitiveness criteria for rail freight based on expense analysis models, the distribution of shipped freight suitable for carriage by rail within the influential area of various terminals in each region is determined for the target corridor. Finally, with the help of a case study we determine the effectiveness of moving freight by rail in terms of reducing logistics costs and CO2 emissions on the target corridor.

In this paper, some verifiable necessary global optimality conditions and sufficient global optimality conditions for some classes of polynomial integer programming problems are established. The relationships between these necessary global optimality conditions and these sufficient global optimality conditions are also discussed. The main theoretical tool for establishing these optimality conditions is abstract convexity.

Cerenkov luminescence imaging offers a new diagnostic alternative to radiation imaging, but lacks intensity and penetration. In this study, a Cerenkov luminescence signal and its image quality were enhanced using rare earth oxide nanoparticles as a basis for Cerenkov luminescence excited fluorescence imaging and Cerenkov luminescence excited fluorescence tomography. The results also provided 3D-imaging and quantitative information. The approach was evaluated using phantom and mice models and 3D reconstruction and quantitative studies were performed in vitro, showing improved optical signal intensity, similarity, accuracy, signal-to-noise ratio, and spatial distribution information. The method offers benefits for both optical imaging research and radiopharmaceutical development.

Background and aim Radionuclide-labeled somatostatin analogues selectively target somatostatin receptor (SSTR)-expressing tumors as a basis for diagnosis and treatment of these tumors. To those tumors without somatostatin receptor expressed, the hSSTR2 gene was transfected. Express of the hSSTR2 receptor was imaging and the radiotherapeutic effect was evaluated with 188 Re-RC-160. Methods The stable hSSTR2 - expressing A549 cells (pcDNA3-hSSTR2 A549) and non-somatostatin receptor expressing A549 cells (pcDNA3 A549) were selected by western blot. Later, a corresponding animal tumor model was established. Expression of the hSSTR2 reporter was imaged using 188 Re-RC-160 recognition. Tumors were evaluated for somatostatin receptor expression using immunohistochemistry. The distribution of 188 Re-RC-160 in the animal tumor model was measured and the inhibitory effects of 188 Re-RC-160 were evaluated by measurement of tumor growth and hematoxylin and eosin and TdT mediated dUTP nick end labeling (TUNEL) staining. Results In vivo radioimaging revealed specific targeting of 188 Re-RC-160 to tumors derived from pcDNA3- hSSTR2 A549 cells, compared to those from pcDNA3 A549 cells. pcDNA3- hSSTR2 A549 tumor growth inhibition was significantly higher in the single 7.4 MBq 188 Re-RC-160 treatment group than in the 2×7.4 MBq rhenium-188, RC-160 group, control group, and pcDNA3 A549 tumors ( P 188 Re-RC-160), induced significantly increased tumor-growth inhibition compare with single 7.4 MBq 188 Re-RC-160 treatment ( P Conclusion These studies showed that 188 Re-RC-160 could be effectively used for targeting therapy the A549-derived tumors exogenously expressing hSSTR2, which will offers a potential therapeutic strategy for the treatment of somatostatin receptor-negative cancers.

The majority of the costs involved in logistics come from freight transport expenses, which are affected by various factors in today's world of economic deregulation. This study seeks to investigate the effectiveness of railway freight as a way of controlling logistics costs under the current conditions faced by major shippers. Models to express the compositive mechanism of truckload freight rates (i.e., transport expenses per ton-kilometer) based on a mileage system are introduced to enable case analysis. The suitability of each model and the availability and explanatory power of each constituent factor are then discussed in details. Finally, the degree of influence on the logistics expenses incurred by shippers using railway freight transport is derived.

Objective To study tumour growth and metastasis in a rabbit metastatic breast cancer (MBC) model and find the most sensitive screening modality in monitoring tumour metastasis. Methods The MBC model was established by injecting a VX2 tumour mass suspension into the mammary glands of 23 rabbits and was monitored by using physical examination, X-ray, MRI and hybrid PET/CT. Results Of all 23 rabbits, axillary lymph node metastasis was detected in 21 (91%) at day 33 after tumour inoculation, mediastinal node metastasis in five (22%) at day 42, abdominal node metastasis in two (9%) at day 48, lung metastasis in six (26%) at day 39, liver metastasis in three (13%) at day 48, and lumbar spine metastasis in one (4%) at day 51. Tumour invasion of pleura was found in one, stomach wall in one, and pleura and stomach concurrently in one rabbit. Sensitivity for detection of lymph node metastases was 78.6% (22/28) and 67.9% (19/28) with MRI and PET/CT, respectively; and sensitivity for detection of metastases in distant organs was 85.7% (12/14) and 71.4% (10/14), respectively. Conclusions The MBC model used here exhibits fast tumour growth and extensive metastasis in a relatively short period. Its metastatic pattern is quite similar to that of human MBC and hence could be potentially used as a model for testing imaging modalities and translational research, e.g., MBC management. MRI is superior to PET/CT in monitoring tumour metastasis.