Mg0.5NixZn0.5-xFe2O4 spinel as a sustainable magnetic nano-photocatalyst with dopant driven band shifting and reduced recombination for visible and solar degradation of Reactive Blue-19

Focussing on visible light active ferrites for high performance removal of noxious pollutants, we report the synthesis of Mg_0.5Ni_xZn_0.5-xFe₂O₄ (x = 0.1, 0.2, 0.3, 0.4, & 0.5) ferrite nanoparticle for degradation of reactive blue-19 (RB-19). Lattice parameters calculated using intense X-ray diffraction (XRD) peaks and Nelson-Riley plots (N-R plot) are in well agreement with each other. The sample Mg_0.5Ni_0.4Zn_0.1Fe₂O₄ (M5N4) exhibits best performance with 99.5% RB-19 degradation in 90 min under visible light. Photoluminescence (PL) results confirm that recombination of charge carriers is highly reduced in the photocatalyst. Scavenging experiments suggest that O₂⁻ radicals were the dominant species responsible for photocatalytic performance. The photocatalytic mechanism was explained in terms of dopant driven shifting of conduction bands and valence bands (calculated by Mott-Schottky plots). The thermodynamic probability of radical generation along with role of redox cycles of metal ions has been discussed in the mechanism. The dye degradation was ascertained by detection of intermediates via mass spectrometry analysis and a possible degradation route was also predicted. The findings in this work provide intriguing opportunities to modify the electronic band structure of spinel ferrites for visible and solar light photocatalytic activity for environmental detoxification.     

Preparation and physical properties of the layered niobate Cu0.5Nb3O8: Application to photocatalytic hydrogen evolution

The new layered niobate Cu_0.5Nb₃O₈ is synthesized by soft chemistry in aqueous electrolyte via Cu²⁺→H⁺ exchange between copper nitrate and HNb₃O₈·H₂O. The characterization of the exchanged product is made by means of thermal gravimetry, chemical analysis, X-ray diffraction and IR spectroscopy. Thermal analysis shows a conversion to anhydrous compound above 500 °C. The oxide displays a semiconductor like behavior; the thermal variation of the conductivity shows that d electrons are strongly localized and the conduction is thermally activated with activation energy of 0.13 eV. The temperature dependence of the thermopower is indicative of an extrinsic conductivity; the electrons are dominant carriers in conformity with an anodic photocurrent. Indeed, the Mott–Schottky plot confirms n-type conduction from which a flat band potential of −0.82 V_SCE, an electronic density of 8.72×10¹⁹ m⁻³ and a depletion width of 4.4 nm are determined. The upper valence band, located at ~5.8 eV below vacuum is made up predominantly of Cu²⁺: 3d with a small admixture of O²⁻: 2p orbitals whereas the conduction band consists of empty Nb⁵⁺: 5s level. The energy band diagram shows the feasibility of the oxide for the photocatalytic hydrogen production upon visible light (29 mW cm⁻²) with a rate evolution of 0.31 mL g⁻¹ min⁻¹.     

Electroactive polymers containing 3-arylcarbazolyl units as hole transporting materials for OLEDs

Monomers and their polymers containing 3-arylcarbazolyl electrophores have been synthesized by the multi-step synthetic route. The materials were characterized by thermo-gravimetric analysis, differential scanning calorimetry and electron photoemission technique. The polymers represent materials of high thermal stability having initial thermal degradation temperatures in the range of 331–411 °C. The glass transition temperatures of the amorphous polymeric materials were in the rage of 148–175 °C. The electron photoemission spectra of thin layers of monomers showed ionization potentials in the range of 5.6–5.65 eV. Hole-transporting properties of the polymers were tested in the structures of organic light emitting diodes with Alq₃ as the green emitter. The device containing hole-transporting layers of polyether with 3-naphthylcarbazolyl groups exhibited the best overall performance with a maximum current efficiency of 3.3 cd/A and maximum brightness of about 1000 cd/m².     

采用信息增益率的混合入侵检测模型设计

针对现有混合入侵检测模型仅定性选取特征而导致检测精度较低的问题，同时为了充分结合误用检测模型和异常检测模型的优势，提出一种采用信息增益率的混合入侵检测模型.首先，利用信息增益率定量地选择特征子集，最大程度地保留样本信息；其次，采用余弦时变粒子群算法确定支持向量机参数构建误用检测模型，使其更好地平衡粒子在全局和局部的搜索能力，然后，选取灰狼算法确定单类支持向量机参数构建异常检测模型，以此来提高对最优参数的搜索效率和精细程度，综合提高混合入侵检测模型对攻击的检测效果；最后，通过两种数据集进行仿真实验，验证了所提混合入侵检测模型具有较好的检测性能.     

Change detection in synthetic aperture radar images based on unsupervised artificial immune systems

In this paper, we propose a novel change detection method for synthetic aperture radar images based on unsupervised artificial immune systems. After generating the difference image from the multitemporal images, we take each pixel as an antigen and build an immune model to deal with the antigens. By continuously stimulating the immune model, the antigens are classified into two groups, changed and unchanged. Firstly, the proposed method incorporates the local information in order to restrain the impact of speckle noise. Secondly, the proposed method simulates the immune response process in a fuzzy way to get an accurate result by retaining more image details. We introduce a fuzzy membership of the antigen and then update the antibodies and memory cells according to the membership. Compared with the clustering algorithms we have proposed in our previous works, the new method inherits immunological properties from immune systems and is robust to speckle noise due to the use of local information as well as fuzzy strategy. Experiments on real synthetic aperture radar images show that the proposed method performs well on several kinds of difference images and engenders more robust result than the other compared methods.     

ECG heart beat classification method based on modified ABC algorithm

Electrocardiogram is the most commonly used tool for the diagnosis of cardiologic diseases. In order to help cardiologists to diagnose the arrhythmias automatically, new methods for automated, computer aided ECG analysis are being developed. In this paper, a Modified Artificial Bee Colony (MABC) algorithm for ECG heart beat classification is introduced. It is applied to ECG data set which is obtained from MITBIH database and the result of MABC is compared with seventeen other classifier's accuracy.In classification problem, some features have higher distinctiveness than others. In this study, in order to find higher distinctive features, a detailed analysis has been done on time domain features. By using the right features in MABC algorithm, high classification success rate (99.30%) is obtained. Other methods generally have high classification accuracy on examined data set, but they have relatively low or even poor sensitivities for some beat types. Different data sets, unbalanced sample numbers in different classes have effect on classification result. When a balanced data set is used, MABC provided the best result as 97.96% among all classifiers.Not only part of the records from examined MITBIH database, but also all data from selected records are used to be able to use developed algorithm on a real time system in the future by using additional software modules and making adaptation on a specific hardware.     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

Using d-limonene as the non-aromatic and non-chlorinated solvent for the fabrications of high performance polymer light-emitting diodes and field-effect transistors

Aiming to environment protection, green solvents are crucial for commercialization of solution-processed optoelectronic devices. In this work, d-limonene, a natural product, was introduced as the non-aromatic and non-chlorinated solvent for processing of polymer light-emitting diodes (PLEDs) and organic field effect transistors (OFETs). It was found that d-limonene could be a good solvent for a blue-emitting polyfluorene-based random copolymer for PLEDs and an alternating copolymer FBT-Th₄(1,4) with high hole mobility (μ_h) for OFETs. In comparisons to routine solvent-casted films of the two conjugated polymers, the resulting d-limonene-deposited films could show comparable film qualities, based on UV–vis absorption spectra and observations by atomic force microscopy (AFM). With d-limonene as the processing solvent, efficient blue PLEDs with CIE coordinates of (0.16, 0.16), maximum external quantum efficiency of 3.57%, and luminous efficiency of 3.66 cd/A, and OFETs with outstanding μ_h of 1.06 cm² (V s)⁻¹ were demonstrated. Our results suggest that d-limonene would be a promising non-aromatic and non-chlorinated solvent for solution processing of conjugated polymers and molecules for optoelectronic device applications.