Danaparoid sodium salt, is the active component of ORGARAN, an anticoagulant and antithrombotic drug constituted of three glycosaminoglycans (GAGs) obtained from porcine intestinal mucosa extracts. Heparan sulfate is the major component, dermatan sulfate and chondroitin sulfate being the minor ones. Currently dermatan sulfate and chondroitin sulfate are quantified by UV detection of their unsaturated disaccharides obtained by enzymatic depolymerization. Due to the complexity of danaparoid biopolymers and the presence of shared components, an orthogonal approach has been applied using more advanced tools and methods. To integrate the analytical profile, 2D heteronuclear single quantum coherence (HSQC) NMR spectroscopy was applied and found effective to identify and quantify GAG component signals as well as those of some process signatures of danaparoid active pharmaceutical ingredient (API) batches. Analyses of components of both API samples and size separated fractions proceeded through the determination and distribution of the molecular weight (Mw) by high performance size exclusion chromatographic triple detector array (HP-SEC-TDA), chain mapping by LC/MS, and mono- (¹H and ¹³C) and bi-dimensional (HSQC) NMR spectroscopy. Finally, large scale chromatographic isolation and depolymerization of each GAG followed by LC/MS and 2D-NMR analysis, allowed the sequences to be defined and components to be evaluated of each GAG including oxidized residues of hexosamines and uronic acids at the reducing ends. Full article

The Internet of Things (IoT) is placing new demands on existing communication systems. The limited orthogonal resources do not meet the demands of massive connectivity of future IoT systems that require efficient multiple access. Interleave-division multiple access (IDMA) is a promising method of improving spectral efficiency and supporting massive connectivity for IoT networks. In a given time, not all sensors signal information to an aggregation node, but each node transmits a short frame on occasion, e.g., time-controlled or event-driven. The sporadic nature of the uplink transmission, low data rates, and massive connectivity in IoT scenarios necessitates minimal control overhead communication schemes. Therefore, sensor activity and data detection should be implemented on the receiver side. However, the current chip-by-chip (CBC) iterative multi-user detection (MUD) assumes that sensor activity is precisely known at the receiver. In this paper, we propose three schemes to solve the MUD problem in a sporadic IDMA uplink transmission system. Firstly, inspired by the observation of sensor sparsity, we incorporate compressed sensing (CS) to MUD in order to jointly perform activity and data detection. Secondly, as CS detection could provide reliable activity detection, we combine CS and CBC and propose a CS-CBC detector. In addition, a CBC-based MUD named CBC-AD is proposed to provide a comparable baseline scheme. Full article

Lichong Shengsui Yin (LCSSY) is an effective and classic compound prescription of Traditional Chinese Medicines (TCMs) used for the treatment of ovarian cancer. To investigate its pharmacodynamic basis for treating ovarian cancer, the multi-dimensional spectrum-effect relationship was determined. Four compositions (I to IV) were obtained by extracting LCSSY successively with supercritical CO₂ fluid extraction, 75% ethanol reflux extraction, and the water extraction-ethanol precipitation method. Nine samples for pharmacological evaluation and fingerprint analysis were prepared by changing the content of the four compositions. The specific proportions of the four compositions were designed according to a four-factor, three-level L₉(3⁴) orthogonal test. The pharmacological evaluation included in vitro tumor inhibition experiments and the survival extension rate in tumor-bearing nude mice. The fingerprint analyzed by chromatographic condition I (high-performance liquid chromatography-photodiode array detec tor，HPLC-PDA) identified 19 common peaks. High-performance liquid chromatography-photodiode array detector-Evaporative Light-scattering Detector (HPLC-PDA-ELSD )hyphenated techniques were used to compensate for the use of a single detector, and the fingerprint analyzed by chromatographic condition II identified 28 common peaks in PDA and 23 common peaks in ELSD. Furthermore, multiple statistical analyses were utilized to calculate the relationships between the peaks and the pharmacological results. The union of the regression and the correlation analysis results were the peaks of X₅, X₉, X₁₁, X₁₂, X₁₆, X₁₈, Y₅, Y₈, Y₁₂, Y₁₄, Y₂₀, Z₄, Z₅, Z₆, and Z₈. The intersection of the regression and the correlation analysis results were the peaks of X₁₁, X₁₂, X₁₆, X₁₈, Y₅, Y₁₂, and Z₅. The correlated peaks were assigned by comparing the fingerprints with the negative control samples and reference standard samples, and identifying the structure using high-performance liquid chromatography-mass spectrometry detector(HPLC-MS). The results suggested that the pharmacodynamic basis of LCSSY on anti-ovarian cancer activities were germacrone, furandiene, β-elemene, calycosin-7-glucoside, ononin, epimedin B, icariin, ginsenoside Rc, astragaloside, ginsenoside Rd, astragaloside II, and some unknown components. Full article

Target detection from hyperspectral images is an important problem but encounters a critical challenge of simultaneously reducing spectral redundancy and preserving the discriminative information. Recently, the joint sparse representation and multi-task learning (JSR-MTL) approach was proposed to address the challenge. However, it does not fully explore the prior class label information of the training samples and the difference between the target dictionary and background dictionary when constructing the model. Besides, there may exist estimation bias for the unknown coefficient matrix with the use of minimization which is usually inconsistent in variable selection. To address these problems, this paper proposes an adaptive joint sparse representation and multi-task learning detector with locality information (JSRMTL-ALI). The proposed method has the following capabilities: (1) it takes full advantage of the prior class label information to construct an adaptive joint sparse representation and multi-task learning model; (2) it explores the great difference between the target dictionary and background dictionary with different regularization strategies in order to better encode the task relatedness; (3) it applies locality information by imposing an iterative weight on the coefficient matrix in order to reduce the estimation bias. Extensive experiments were carried out on three hyperspectral images, and it was found that JSRMTL-ALI generally shows a better detection performance than the other target detection methods. Full article

Wavelength- or polarization-selective thermal infrared (IR) detectors are promising for various novel applications such as fire detection, gas analysis, multi-color imaging, multi-channel detectors, recognition of artificial objects in a natural environment, and facial recognition. However, these functions require additional filters or polarizers, which leads to high cost and technical difficulties related to integration of many different pixels in an array format. Plasmonic metamaterial absorbers (PMAs) can impart wavelength or polarization selectivity to conventional thermal IR detectors simply by controlling the surface geometry of the absorbers to produce surface plasmon resonances at designed wavelengths or polarizations. This enables integration of many different pixels in an array format without any filters or polarizers. We review our recent advances in wavelength- and polarization-selective thermal IR sensors using PMAs for multi-color or polarimetric imaging. The absorption mechanism defined by the surface structures is discussed for three types of PMAs—periodic crystals, metal-insulator-metal and mushroom-type PMAs—to demonstrate appropriate applications. Our wavelength- or polarization-selective uncooled IR sensors using various PMAs and multi-color image sensors are then described. Finally, high-performance mushroom-type PMAs are investigated. These advanced functional thermal IR detectors with wavelength or polarization selectivity will provide great benefits for a wide range of applications. Full article

Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits the gray intensity correlation characteristics by building a two-dimensional (2D) joint log-normal model as the joint distribution (JPDF) of the clutter, so joint CFAR detection is realized. Inspired by the CFAR detection methodology, we design an adaptive threshold-based clutter truncation method to eliminate the high-intensity outliers, such as interfering ship targets, side-lobes, and ghosts in the background window, whereas the real clutter samples are preserved to the largest degree. A 2D joint log-normal model is accurately built using the adaptively-truncated clutter through simple parameter estimation, so the joint CFAR detection performance is greatly improved. Compared with traditional CFAR detectors, the proposed TS-2DLNCFAR detector achieves a high PD and a low false alarm rate (FAR) in multiple target situations. The superiority of the proposed TS-2DLNCFAR detector is validated on the multi-look Envisat-ASAR and TerraSAR-X data. Full article

Detecting the signals of the primary users in the wideband spectrum is a key issue for cognitive radio networks. In this paper, we consider the multi-antenna based signal detection in a wideband spectrum scenario where the noise statistical characteristics are assumed to be unknown. We reason that the covariance matrices of the spectrum subbands have structural constraints and that they describe a manifold in the signal space. Thus, we propose a novel signal detection algorithm based on Riemannian distance and Riemannian mean which is different from the traditional eigenvalue-based detector (EBD) derived with the generalized likelihood ratio criterion. Using the moment matching method, we obtain the closed expression of the decision threshold. From the considered simulation settings, it is shown that the proposed Riemannian distance detector (RDD) has a better performance than the traditional EBD in wideband spectrum sensing. Full article

The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detector design which can offer stereoscopic images, depth estimation of gamma-emitting sources, and simultaneous gamma and fluorescence imaging. Recent improvements to the hybrid camera have been used to produce dual-modality images in both laboratory simulations and in the clinic. Hybrid imaging of a patient who underwent thyroid scintigraphy is reported. In addition, we present data which shows that the hybrid camera concept can be extended to estimate the position and depth of radionuclide distribution within an object and also report the first combined gamma and Near-Infrared (NIR) fluorescence images. Full article

Search for Unidentified Maritime Objects (SUMO) is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR) images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR) and resolutions (from 1–100 m) and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate) detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships) uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed) targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU’s Copernicus program, which includes the Sentinel-1 satellite, has hugely increased the availability of SAR images. This paper aims to cater to the consequently expected wider demand for knowledge about SAR ship detectors. Full article

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter. Full article

This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR) imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction extraction. In this paper, the proposed algorithm integrates the fraction extraction and optimization procedure simultaneously to extract the road network: (1) the Bayesian framework is utilized to transfer the road network extraction to joint reasoning of the likelihood of fraction extraction and the priority of network optimization; (2) the multi-scale linear feature detector (MLFD) and the network optimization beamlet are introduced; (3) the conditional random field (CRF) is used to reason jointly. The result is the global optimum since the fraction extraction and network optimization are exploited at the same time. The proposed algorithm solves the problem that the fractions are bound to reduce in the process of network optimization and has demonstrated effectiveness in real SAR images applications. Full article

This paper presents a novel multi-sensor framework to efficiently identify, track, localise and map every piece of fruit in a commercial mango orchard. A multiple viewpoint approach is used to solve the problem of occlusion, thus avoiding the need for labour-intensive field calibration to estimate actual yield. Fruit are detected in images using a state-of-the-art faster R-CNN detector, and pair-wise correspondences are established between images using trajectory data provided by a navigation system. A novel LiDAR component automatically generates image masks for each canopy, allowing each fruit to be associated with the corresponding tree. The tracked fruit are triangulated to locate them in 3D, enabling a number of spatial statistics per tree, row or orchard block. A total of 522 trees and 71,609 mangoes were scanned on a Calypso mango orchard near Bundaberg, Queensland, Australia, with 16 trees counted by hand for validation, both on the tree and after harvest. The results show that single, dual and multi-view methods can all provide precise yield estimates, but only the proposed multi-view approach can do so without calibration, with an error rate of only 1.36% for individual trees. Full article

Current instruments used to detect specific protein-protein interactions in live cells for applications in high-content screening (HCS) are limited by the time required to measure the lifetime. Here, a 32 × 1 single-photon avalanche diode (SPAD) array was explored as a detector for fluorescence lifetime imaging (FLIM) in HCS. Device parameters and characterization results were interpreted in the context of the application to determine if the SPAD array could satisfy the requirements of HCS-FLIM. Fluorescence lifetime measurements were performed using a known fluorescence standard; and the recovered fluorescence lifetime matched literature reported values. The design of a theoretical 32 × 32 SPAD array was also considered as a detector for a multi-point confocal scanning microscope. Full article

Junction formation in deep trenches is proposed as a new means of creating a built-in drift field in silicon drift detectors (SDDs). The potential performance of this trenched drift detector (TDD) was investigated analytically and through simulations, and compared to simulations of conventional bulk-silicon drift detector (BSDD) configurations. Although the device was not experimentally realized, the manufacturability of the TDDs is estimated to be good on the basis of previously demonstrated photodiodes and detectors fabricated in PureB technology. The pure boron deposition of this technology allows good trench coverage and is known to provide nm-shallow low-noise p⁺n diodes that can be used as radiation-hard light-entrance windows. With this type of diode, the TDDs would be suitable for X-ray radiation detection down to 100 eV and up to tens of keV energy levels. In the TDD, the drift region is formed by varying the geometry and position of the trenches while the reverse biasing of all diodes is kept at the same constant voltage. For a given wafer doping, the drift field is lower for the TDD than for a BSDD and it demands a much higher voltage between the anode and cathode, but also has several advantages: it eliminates the possibility of punch-through and no current flows from the inner to outer perimeter of the cathode because a voltage divider is not needed to set the drift field. In addition, the loss of sensitive area at the outer perimeter of the cathode is much smaller. For example, the simulations predict that an optimized TDD geometry with an active-region radius of 3100 µm could have a drift field of 370 V/cm and a photo-sensitive radius that is 500-µm larger than that of a comparable BSDD structure. The PureB diodes on the front and back of the TDD are continuous, which means low dark currents and high stability with respect to leakage currents that otherwise could be caused by radiation damage. The dark current of the 3100-µm TDD will increase by only 34% if an interface trap concentration of 10¹² cm⁻² is introduced to approximate the oxide interface degradation that could be caused during irradiation. The TDD structure is particularly well-suited for implementation in multi-cell drift detector arrays where it is shown to significantly decrease the cross-talk between segments. The trenches will, however, also present a narrow dead area that can split the energy deposited by high-energy photons traversing this dead area. The count rate within a cell of a radius = 300 µm in a multi-cell TDD array is found to be as high as 10 Mcps. Full article

Traditional detectors for spectrum sensing in cognitive radio networks always become disabled when noise uncertainty is severe. Shannon entropy-based detection methods have aroused widespread attention in recent years due to the characteristics of effective anti-noise uncertainty. However, in existing entropy-based sensing schemes, the uniform quantization method cannot guarantee the maximum entropy distribution when primary users do not exist, and cannot effectively distinguish between two hypotheses, which severely limits the promotion of detection performance. Moreover, the Shannon entropy-based sensing schemes are prone to misconvergence occurring when estimating entropy values, thus causing failure detection, which leads to system detection inefficiency and resource waste. These are the two major serious defects in Shannon entropy-based detectors, which restrict the performance improvement. In this paper, a novel non-uniform quantized exponential entropy-based (NQEE) detector is proposed for local sensing to deal with the problems of maximum entropy distribution and detection failure. To further improve the reliability of the detection, a collaborative spectrum sensing algorithm based on an NQEE detector with multiple fusion rules is presented. Simulation results verify that the detection performance of the improved local entropy-based detector is superior to the existing Shannon entropy-based detectors and is proved to be robust to noise power uncertainty. In addition, the novel collaborative detection algorithm outperforms the traditional collaborative spectrum detection method to a great degree. Full article

Resource-based cities face unique challenges when undergoing urban transitions because their non-renewable resources will eventually be exhausted. In this article, we introduce a new method of evaluating the urban transition performance of resource-based cities from economic, social and eco-environmental perspectives. A total of 19 resource-based cities in Northeast China are studied from 2003 to 2012. The results show that resource-based cities in Jilin and Liaoning provinces performed better than those in Heilongjiang province. Liaoyuan, Songyuan and Baishan were ranked as the top three resource-based cities; and Jixi, Yichun and Heihe were ranked last. Multi-resource and petroleum resource-based cities performed better than coal and forestry resource-based cities. We also analyzed the factors influencing urban transition performance using the method of the geographic detector. We found that capital input, road density and location advantage had the greatest effects on urban transition performance, followed by urban scale, remaining resources and the level of sustainable development; supporting policies and labor input had the smallest effects. Based on these insights, we have formulated several recommendations to facilitate urban transitions in China’s resource-based cities. Full article

A powerful chromatographic method coupled to a fluorescence detector was developed to determine the phenolic compounds present in virgin olive oil (VOO), with the aim to propose an appropriate alternative to liquid chromatography-mass spectrometry. An excitation wavelength of 285 nm was selected and four different emission wavelengths (316, 328, 350 and 450 nm) were simultaneously recorded, working therefore on “multi-emission” detection mode. With the use of commercially available standards and other standards obtained by semipreparative high performance liquid chromatography, it was possible to identify simple phenols, lignans, several complex phenols, and other phenolic compounds present in the matrix under study. A total of 26 phenolic compounds belonging to different chemical families were identified (23 of them were susceptible of being quantified). The proposed methodology provided detection and quantification limits within the ranges of 0.004–7.143 μg·mL⁻¹ and 0.013–23.810 μg·mL⁻¹, respectively. As far as the repeatability is concerned, the relative standard deviation values were below 0.43% for retention time, and 9.05% for peak area. The developed methodology was applied for the determination of phenolic compounds in ten VOOs, both monovarietals and blends. Secoiridoids were the most abundant fraction in all the samples, followed by simple phenolic alcohols, lignans, flavonoids, and phenolic acids (being the abundance order of the latter chemical classes logically depending on the variety and origin of the VOOs). Full article

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from $0.807$ to $0.838$ for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit. Full article

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows. Full article

Poly(l-glutamate) (PGlu) was modified with a second-generation dendron to obtain the dendronized polyglutamate, P(Glu-D). Synthesized P(Glu-D) exhibited a degree of polymerization (DP_n) of 46 and a 43% degree of dendronization. Perfect agreement was found between the P(Glu-D) expected structure and the results of nuclear magnetic resonance spectroscopy (NMR) and size-exclusion chromatography coupled to a multi-angle light-scattering detector (SEC-MALS) analysis. The PGlu precursor was modified by coupling with a bifunctional building block (N₃-Pr-NH₂) in the presence of 4-(4,6-dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride (DMTMM) coupling reagent. The second-generation polyamide dendron was prepared by a stepwise procedure involving the coupling of propargylamine to the l-lysine carboxyl group, followed by attaching the protected 2,2-bis(methylol)propionic acid (bis-MPA) building block to the l-lysine amino groups. The hydroxyl groups of the resulting second-generation dendron were quantitatively deprotected under mild acidic conditions. The deprotected dendron with an acetylene focal group was coupled to the pendant azide groups of the modified linear copolypeptide, P(Glu-N₃), in a Cu(I) catalyzed azide-alkyne cycloaddition reaction to form a 1,4-disubstituted triazole. The dendronization reaction proceeded quantitatively in 48 hours in aqueous medium as confirmed by ¹H NMR and Fourier transform infrared spectroscopy (FT-IR) spectroscopy. Full article

Background: Inflammatory mechanisms are key to the pathogenesis of atherosclerosis. Functional polymorphisms of TLR-4, Asp299Gly and Thr399Ile, CD14 promoter area C260T polymorphism and plasma levels of soluble CD14 are studied in subjects with Coronary Artery Disease (CAD). Methods: DNA was obtained from 100 human paraffin-embedded aortic specimens, from cadavers with known coronary atheromatosis (Group A) and 100 blood samples from patients with CAD, as detected by cardiac Multi-Detector-row-Computed-Tomography (MDCT) (Group B). Our control group consisted of 100 healthy individuals (Group C). Genotyping was performed by Restriction Fragment Length Polymorphism-Polymerase Chain Reaction (RFLP-PCR). Plasma levels of sCD14 were measured with ELISA. Results: For TLR-4 Asp299Gly and Thr399Ile polymorphisms, no statistically significant differences were observed. Regarding the C260T polymorphism, frequencies of T allele were significantly higher in the control group compared to the case group (p = 0.05). The Odds Ratio (OR) showed statistically significant association of TT genotype with healthy individuals (OR 0.25, 95% Confidence Interval CI 0.10–0.62, p = 0.0017). Plasma levels of sCD14 in patients with CAD (mean value = 1.35 μg/mL) were reduced when compared to reference value. Conclusions: The studied polymorphisms ofTLR-4 showed no association with CAD. Conversely, the functional polymorphism of CD14 has a statistically significant difference in expression between healthy and affected by CAD individuals. Full article

XiaoyanLidan tablets (XYLDTs) are traditional Chinese medicines frequently used for syndromes of the liver and gallbladder, cholecystitis and cholangitis. To evaluate the consistency of the quality of commercial XYLDT preparations, we established a simple and reliable ultra-performance liquid chromatography (UPLC) method with a photodiode array (PDA) detector and mass spectrometry (MS), including a fingerprint analysis and quantification of the main pharmacologically-active markers. In the UPLC-PDA detection-based fingerprint analysis of XYLDTs, approximately 39 peaks were found in the XYLDT chromatogram, 26 of which were attributed to Picrasmaquassioides, nine to Andrographis and four to Isodonserra. Subsequently, the structures of these bioactive markers were identified through ESI-MS analyses. Using the chemometricmethods of similarity analysis and principal component analysis, the five significant herbal componentswere determined as 4-methoxy-5-hydroxycanthin-6-one, andrographolide, dehydroandrographolide, neoandrographolide and rosmarinic acid, and these components were qualitatively assessed. Our experimental results demonstrated that combining the fingerprint analysis with UPLC-MS and multi-ingredient determination is useful for rapid pharmaceutical quality evaluation. Moreover, the combined approach can potentially differentiate the origin, determine the authenticity and assess the overall quality of the formulae. Full article

Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) radiometers, flown onboard Terra/Aqua and Suomi National Polar-orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) satellites, are capable of providing superior sea surface temperature (SST) imagery. However, the swath data of these multi-detector sensors are subject to several artifacts including bow-tie distortions and striping, and require special pre-processing steps. VIIRS additionally does two irreversible data reduction steps onboard: pixel aggregation (to reduce resolution changes across the swath) and pixel deletion, which complicate both bow-tie correction and destriping. While destriping was addressed elsewhere, this paper describes an algorithm, adopted in the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear-Sky Processor for Oceans (ACSPO) SST system, to minimize the bow-tie artifacts in the SST imagery and facilitate application of the pattern recognition algorithms for improved separation of ocean from cloud and mapping fine SST structure, especially in the dynamic, coastal and high-latitude regions of the ocean. The algorithm is based on a computationally fast re-sampling procedure that ensures a continuity of corresponding latitude and longitude arrays. Potentially, Level 1.5 products may be generated to benefit a wide range of MODIS and VIIRS users in land, ocean, cryosphere, and atmosphere remote sensing. Full article

Magnetic nanoparticles (MNPs) exhibit unique magnetic properties making them ideally suited for a variety of biomedical applications. Depending on the desired magnetic effect, MNPs must meet special magnetic requirements which are mainly determined by their structural properties (e.g., size distribution). The hyphenation of chromatographic separation techniques with complementary detectors is capable of providing multidimensional information of submicron particles. Although various methods have already been combined for this approach, so far, no detector for the online magnetic analysis was used. Magnetic particle spectroscopy (MPS) has been proven a straightforward technique for specific quantification and characterization of MNPs. It combines high sensitivity with high temporal resolution; both of these are prerequisites for a successful hyphenation with chromatographic separation. We demonstrate the capability of MPS to specifically detect and characterize MNPs under usually applied asymmetric flow field-flow fractionation (A4F) conditions (flow rates, MNP concentration, different MNP types). To this end MPS has been successfully integrated into an A4F multidetector platform including dynamic ligth scattering (DLS), multi-angle light scattering (MALS) and ultraviolet (UV) detection. Our system allows for rapid and comprehensive characterization of typical MNP samples for the systematic investigation of structure-dependent magnetic properties. This has been demonstrated by magnetic analysis of the commercial magnetic resonance imaging (MRI) contrast agent Ferucarbotran (FER) during hydrodynamic A4F fractionation. Full article

The goal of data hiding techniques usually considers two issues, embedding capacity and image quality. Consequently, in order to achieve high embedding capacity and good image quality, a data hiding scheme combining run-length encoding (RLE) with multi-bit embedding is proposed in this paper. This work has three major contributions. First, the embedding capacity is increased 62% because the secret message is compressed before embedding into the cover image. Secondly, the proposed scheme keeps the multi-bit generalized exploiting modification direction (MGEMD) characteristics, which are effective to reduce modified pixels in the cover image and to maintain good stego image quality. Finally, the proposed scheme can prevent modern steganalysis methods, such as RS steganalysis and SPAM (subtractive pixel adjacency matrix), and is compared to MiPOD (minimizing the power of the optimal detector) scheme. From our simulation results and security discussions, we have the following results: First, there are no perceivable differences between the cover images and stego images from human inspection. For example, the average PSNR of stego images is about 44.61 dB when the secret message (80,000 bits) is embedded for test cover images (such as airplane, baboon, Lena) of size 512×512. Secondly, Appl. Sci. 2015, 5 1034 on average, 222,087 pixels were not modified after embedding for the cover image. That is to say, 12% less pixels are modified as compared to the MGEMD method. From the performance discussions, the proposed scheme achieves high embedding capacity and good image quality, but also maintains stego image security. Full article

Multi-user detection is an effective method to reduce multiple access interference in code division multiple access (CDMA) systems. This paper discusses a signal subspace based blind adaptive multiuser detector and a Kalman filtering blind adaptive multiuser detector. Combining them together, a new Kalman filtering blind adaptive multiuser detector based on a tracking algorithm of the signal subspace is proposed. Analysis and simulation show that the proposed blind multiuser detector achieves better suppression of multiple access interference and has a higher convergence rate. Full article

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. Full article

One of the most important goals in proteomics is to detect the real-time kinetics of diverse biomolecular interactions. Fluorescence, which requires extrinsic tags, is a commonly and widely used method because of its high convenience and sensitivity. However, in order to maintain the conformational and functional integrality of biomolecules, label-free detection methods are highly under demand. We have developed the oblique-incidence reflectivity difference (OI-RD) technique for label-free, kinetic measurements of protein-biomolecule interactions. Incorporating the total internal refection geometry into the OI-RD technique, we are able to detect as low as 0.1% of a protein monolayer, and this sensitivity is comparable with other label-free techniques such as surface plasmon resonance (SPR). The unique advantage of OI-RD over SPR is no need for dielectric layers. Moreover, using a photodiode array as the detector enables multi-channel detection and also eliminates the over-time signal drift. In this paper, we demonstrate the applicability and feasibility of the OI-RD technique by measuring the kinetics of protein-protein and protein-small molecule interactions in sandwich assays. Full article

The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO₂). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. Therefore, the development of a wearable pulse oximeter, such as a finger base-type pulse oximeter, can effectively solve the above issue. However, the tissue structure of the finger base is complex, and there is lack of detailed information on the effect of the light source and detector placement on measuring SPO₂. In this study, the practicability of a ring-type pulse oximeter with a multi-detector was investigated by optical human tissue simulation. The optimal design of a ring-type pulse oximeter that can provide the best efficiency of measuring SPO₂ was discussed. The efficiency of ring-type pulse oximeters with a single detector and a multi-detector was also discussed. Finally, a wearable and wireless ring-type pulse oximeter was also implemented to validate the simulation results and was compared with the commercial fingertip-type pulse oximeter. Full article

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources. Full article

This paper describes the requirements for the devices of detection, chemical reconnaissance and field analyses of chemical warfare agents (CWA) and divides them into simple devices of detection, universal detectors, selective analyzers, multi-component analyzers and mobile laboratories. It also describes the devices of detection available within the Fire and Rescue Service of the Czech Republic (FRS CR) and compares them with some prospective trends of further development. Full article

A miniature fiber-optic dosimeter (FOD) system was fabricated using a plastic scintillating fiber, a plastic optical fiber, and a multi-pixel photon counter to measure real-time entrance surface dose (ESD) during radiation diagnosis. Under varying exposure parameters of a digital radiography (DR) system, we measured the scintillating light related to the ESD using the sensing probe of the FOD, which was placed at the center of the beam field on an anthropomorphic thorax phantom. Also, we obtained DR images using a flat panel detector of the DR system to evaluate the effects of the dosimeter on image artifacts during posteroanterior (PA) chest radiography. From the experimental results, the scintillation output signals of the FOD were similar to the ESDs including backscatter simultaneously obtained using a semiconductor dosimeter. We demonstrated that the proposed miniature FOD can be used to measure real-time ESDs with minimization of DR image artifacts in the X-ray energy range of diagnostic radiology. Full article

The paper presents a set of tests carried out in order to evaluate the design characteristics and the operating performance of a set of six X-ray extrinsic optical fiber sensors. The extrinsic sensor we developed is intended to be used as a low energy X-ray detector for monitoring radiation levels in radiotherapy, industrial applications and for personnel dosimetry. The reproducibility of the manufacturing process and the characteristics of the sensors were assessed. The sensors dynamic range, linearity, sensitivity, and reproducibility are evaluated through radioluminescence measurements, X-ray fluorescence and X-ray imaging investigations. Their response to the operating conditions of the excitation source was estimated. The effect of the sensors design and implementation, on the collecting efficiency of the radioluminescence signal was measured. The study indicated that the sensors are efficient only in the first 5 mm of the tip, and that a reflective coating can improve their response. Additional tests were done to investigate the concentricity of the sensors tip against the core of the optical fiber guiding the optical signal. The influence of the active material concentration on the sensor response to X-ray was studied. The tests were carried out by measuring the radioluminescence signal with an optical fiber spectrometer and with a Multi-Pixel Photon Counter. Full article

This study aimed to investigate the associations of the serial changes of serum levels of various growth factors with liver regeneration after hepatectomy in healthy liver donors. Sixteen healthy liver donors who underwent conventional liver resection were included. Serum levels of various growth factors before hepatectomy and on postoperative day (POD) 1, 3, 5 and 7 were measured. Liver volume data calculated by multi-detector computed tomography using workstation. The ratio of remnant liver volume on POD 0 to liver volume before the operation was 51% ± 20%. The ratio of liver volume on POD 14 to liver volume on POD 0 were inversely correlated with remnant liver volume on POD 0 (r = −0.91). The ratio of liver volume on POD 14 to liver volume on POD 0 were significantly correlated with serum hepatocyte growth factor (HGF) levels on POD 1 (r = 0.54), serum leptin levels on POD 1 (r = 0.54), and serum macrophage colony-stimulating factor (M-CSF) levels on POD 5 (r = 0.76) and POD 7 (r = 0.80). These results suggest that early-phase elevation of serum levels of HGF, leptin and M-CSF may be associated with the acceleration of liver regeneration after hepatectomy in humans. Full article

This paper presents the concept, structural design and implementation of components of a multifunctional sensory network, consisting of a Mobile Robotic Platform (MRP) and stationary multifunctional sensors, which are wirelessly communicating with the MRP. Each section provides the review of the principles of operation and the network components’ practical implementation. The analysis is focused on the structure of the robotic platform, sensory network and electronics and on the methods of the environment monitoring and data processing algorithms that provide maximal reliability, flexibility and stable operability of the system. The main aim of this project is the development of the Robotic Nurse (RN)—a 24/7 robotic helper for the hospital nurse personnel. To support long-lasting autonomic operation of the platform, all mechanical, electronic and photonic components were designed to provide minimal weight, size and power consumption, while still providing high operational efficiency, accuracy of measurements and adequateness of the sensor response. The stationary sensors serve as the remote “eyes, ears and noses” of the main MRP. After data acquisition, processing and analysing, the robot activates the mobile platform or specific sensors and cameras. The cross-use of data received from sensors of different types provides high reliability of the system. The key RN capabilities are simultaneous monitoring of physical conditions of a large number of patients and alarming in case of an emergency. The robotic platform Nav-2 exploits innovative principles of any-direction motion with omni-wheels, navigation and environment analysis. It includes an innovative mini-laser, the absorption spectrum analyser and a portable, extremely high signal-to-noise ratio spectrometer with two-dimensional detector array. Full article

The main objective of this study was the screening of some selected aromatic plants very popular in Greece, with respect to their total phenolic content, antioxidant capacity, reducing activity, and oxidative stability. All plants were extracted with the conventional method, reflux with methanol. The essential oils of the plants were also analyzed for their antioxidant properties. The total phenolic content was determined by the Folin-Ciocalteu method using gallic acid as the standard, while the phenolic substances were identified and quantified by High Performance Liquid Chromatography (HPLC) coupled with a multi-wavelength ultraviolet-visible (UV-vis) detector. The antioxidant capacity of the plant extracts was measured by their ability to scavenge free radicals such as (a) DPPH (2,2-diphenyl-1-picrylhydrazyl) and, (b) ABTS (2,2′-azinobis-(3-ethylbenzothiaziline-6- sulfonate). The Folin-Ciocalteu method proved the existence of antioxidants in the aromatic plant extracts. Taking into account the results of the DPPH and ABTS methods, the free radical scavenging capacity was confirmed. Eventually, all plants exhibited low but noticeable protection levels against lipid oxidation, as determined by the Rancimat test. Full article

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available. Full article

This paper describes the characteristics of optical fiber sensors with surface plasmon resonance (SPR) at 1,310 nm in which the scattering loss of silica optical fiber is low. SPR operation in the infrared wavelength range is achieved by coating a thin tantalum pentaoxide (Ta₂O₅) film. The novelty of this paper lies in the verification of how the hetero-core scheme could be operated as a commercial base candidate in the sense of easy fabrication, sufficient mechanical strength, and significant sensitivity as a liquid detector under the basis of a low loss transmission network in the near infrared wavelength region. The effect of Ta₂O₅ layer thickness has been experimentally revealed in the wavelength region extending to 1,800 nm by using the hetero-core structured optical fiber. SPR characterizations have been made in the wavelength region 1,000–1,300 nm, showing the feasible operation at the near infrared wavelength and the possible practical applications. In addition, the technique developed in this work has been interestingly applied to a multi-point water-detection and a water-level gauge in which tandem-connected SPR sensors system using hetero-core structured fibers were incorporated. The detailed performance characteristics are also shown on these applications. Full article

“Green” and energy-efficient wireless communication schemes have recently experienced rapid development and garnered much interest. One such scheme is visible light communication (VLC) which is being touted as one of the next generation wireless communication systems. VLC allows communication using multi-color channels that provide high data rates and illumination simultaneously. Even though VLC has many advantageous features compared with RF technologies, including visibility, ubiquitousness, high speed, high security, harmlessness for the human body and freedom of RF interference, it suffers from some problems on the receiver side, one of them being photo sensitivity dissimilarity of the receiver. The photo sensitivity characteristics of a VLC receiver such as Si photo-detector depend on the wavelength variation. The performance of the VLC receiver is not uniform towards all channel colors, but it is desirable for receivers to have the same performance on each color channel. In this paper, we propose a mitigation technique for reducing the performance variation of the receiver on multi-color channels. We show received power, SNR, BER, output current, and outage probability in our simulation for different color channels. Simulation results show that, the proposed scheme can reduce the performance variation of the VLC receiver on multi-color channels. Full article

With the current increased widespread interest in the development and applications of micro/nanosatellites, it was found that we needed to design a small high accuracy satellite attitude determination system, because the star trackers widely used in large satellites are large and heavy, and therefore not suitable for installation on micro/nanosatellites. A Sun sensor + magnetometer is proven to be a better alternative, but the conventional sun sensor has low accuracy, and cannot meet the requirements of the attitude determination systems of micro/nanosatellites, so the development of a small high accuracy sun sensor with high reliability is very significant. This paper presents a multi-aperture based sun sensor, which is composed of a micro-electro-mechanical system (MEMS) mask with 36 apertures and an active pixels sensor (APS) CMOS placed below the mask at a certain distance. A novel fast multi-point MEANSHIFT (FMMS) algorithm is proposed to improve the accuracy and reliability, the two key performance features, of an APS sun sensor. When the sunlight illuminates the sensor, a sun spot array image is formed on the APS detector. Then the sun angles can be derived by analyzing the aperture image location on the detector via the FMMS algorithm. With this system, the centroid accuracy of the sun image can reach 0.01 pixels, without increasing the weight and power consumption, even when some missing apertures and bad pixels appear on the detector due to aging of the devices and operation in a harsh space environment, while the pointing accuracy of the single-aperture sun sensor using the conventional correlation algorithm is only 0.05 pixels. Full article

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset. Full article

A novel needle-type biosensor based on carbon nanotubes is reported. Thebiosensor was prepared by packing a mixture of multi-wall carbon nanotubes (MWCNTs),graphite powder and glucose oxidase (G_ox) freeze-dried powder into a glass capillary of 0.5mm inner diameter. The resulting amperometric biosensor was characterizedelectrochemically using amperometry in the presence of hydrogen peroxide and in thepresence of glucose. The glucose biosensor sensitivity was influenced by the glucoseoxidase concentration within the MWCNTs mixture. The optimized glucose needle-typebiosensor displayed better sensitivity and stability, and a detected range of up to 20 mM.Based on its favorable stability, the needle biosensor was first time used in real-timemonitoring system as a kind of online glucose detector. The decay of current response isless than 10% after 24-hour continuous observation. Full article