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Load of Ag 3 PO 4 Particles on Sulfonated Polyphenylene Sulfide Superfine Fibre with High Visible-light Photocatalytic Activity

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Abstract

Ag3PO4 was loaded on sulfonated polyphenylene sulfide (SPPS) superfine fibre by a facile precipitation method. Both the structure and properties of the as-synthesized Ag3PO4/SPPS composites were characterized via XRD, SEM, EDS, XPS, FTIR, and UV-vis. The photocatalytic performance of Ag3PO4/SPPS composites was investigated via degradation of Methylene blue(MB) solution under visible light irradiation. The degradation results revealed that the photocatalytic activity of Ag3PO4/SPPS composites was greatly enhanced by the incorporation of Ag3PO4 with SPPS superfine fibre. For concentrations of AgNO3 and Na2HPO4 solutions of 0.3 M and 0.06 M in the preparation process, the Ag3PO4/SPPS composite showed higher photocatalytic activity under visible light irradiation.


Characterization and Recovery of Copper from Converter Copper Slag Via Smelting Separation

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Abstract

Converter copper slag can be viewed as an important secondary resource for valuable metals, considering its high commercial value. The current research investigates the recycling of copper by a combination of theoretical and experimental methods. Based on a modified Stokes equation, it was determined that copper droplets in the molten slag exhibited a low terminal settling velocity of 2.140 × 10−6 m/s. The copper particles will collide with each other during settling, resulting in particle growth. The results from high temperature experimentation, scanning electron microscopy, and energy-dispersive spectroscopy confirm that in the absence of reducing agents, copper droplets are encased in magnetite to form composite ‘Cu droplet–magnetite’ particles. Other copper droplets adhere to magnetite particles which are suspended in the slag in a short-range-ordered array. The study also confirms that in the presence of increasing amounts of anthracite as a reducing agent, the magnetite content of the slag is progressively decreased and the recovery of copper from the slag is significantly improved. Based on the findings from this work, a new processing route is proposed to treat copper slag for the recovery of copper.

Kinetics of Reduction of Low-Grade Nickel Laterite Ore Using Carbon Monoxide

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Abstract

Reduction of a low-grade nickel laterite ore with carbon monoxide to produce Fe-Ni alloy was investigated using a thermo-gravimetric analysis (TGA) method. Non-isothermal reduction tests with a fixed heating rate of 10 °C/min from room temperature to 1200 °C were carried out to determine the different reduction stages and reaction products in each state. Combining measured mass losses with theoretically calculated values together with X-ray diffraction analysis, the products of different reduction stages were identified and a reaction path was established. Isothermal reduction tests with temperatures ranging from 500 °C to 1100 °C were performed to evaluate the temperature dependence of the reduction kinetics. Various kinetic models were fitted to the experimental data to further determine the rate-controlling step in the isothermal tests. Then, two groups of TG experiments were carried out to study the effect of CO flow rate and sample mass on the rate of reaction. The results indicated that the reduction rate increases with the increase of the reduction temperature from 500 °C to 1100 °C. More alloy products are formed and the apparent activation energies increase from 8.6 to 14.7 kJ/mol with the increase of the reduction temperature from 700 °C to 1100 °C. Accordingly, it was proposed that diffusion of CO in the gas bulk and through the pores of the laterite ore sample bed are the rate limiting steps.

Sequence-based sparse optimization methods for long-term loop closure detection in visual SLAM

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Abstract

Loop closure detection is one of the most important module in Simultaneously Localization and Mapping (SLAM) because it enables to find the global topology among different places. A loop closure is detected when the current place is recognized to match the previous visited places. When the SLAM is executed throughout a long-term period, there will be additional challenges for the loop closure detection. The illumination, weather, and vegetation conditions can often change significantly during the life-long SLAM, resulting in the critical strong perceptual aliasing and appearance variation problems in loop closure detection. In order to address this problem, we propose a new Robust Multimodal Sequence-based (ROMS) method for robust loop closure detection in long-term visual SLAM. A sequence of images is used as the representation of places in our ROMS method, where each image in the sequence is encoded by multiple feature modalites so that different places can be recognized discriminatively. We formulate the robust place recognition problem as a convex optimization problem with structured sparsity regularization due to the fact that only a small set of template places can match the query place. In addition, we also develop a new algorithm to solve the formulated optimization problem efficiently, which guarantees to converge to the global optima theoretically. Our ROMS method is evaluated through extensive experiments on three large-scale benchmark datasets, which record scenes ranging from different times of the day, months, and seasons. Experimental results demonstrate that our ROMS method outperforms the existing loop closure detection methods in long-term SLAM, and achieves the state-of-the-art performance.

Effect of Iron Phase Evolution on Copper Separation from Slag Via Coal-Based Reduction

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Abstract

Copper slag, a by-product of copper pyrometallurgy, inevitably contains a certain amount of copper. Oxygen-enriched smelting technologies increase the copper content in slag indirectly because of the production of higher-grade matte. The effect of iron phase evolution on the copper content in slag during the slag cleaning process in an electric furnace was investigated using the method of combining theory with experiments. Based on the analysis, the main factors that impede the separation of slag and copper/matte were determined. Subsequently, the properties of slag were analyzed after decreasing the magnetite content within the slag. The experimental results showed that decreases in magnetite content were beneficial for the separation of copper and slag because of the decrease of slag viscosity. Nevertheless, Cu-Fe alloys formed when magnetite was completely reduced to metallic iron, and the foaming slag was formed at 1250 °C. Furthermore, the distribution of copper in the reduced slags was studied in detail.

Secure Localization Algorithms in Wireless Sensor Networks: A Review

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Abstract

Localization plays a vital role in understanding the application context for wireless sensor networks (WSNs). However, it is vulnerable to various threats due to the open arrangement area, the nature of radio broadcasting, and resource constraint. Two kinds of attacks on localization process need to be investigated. On the one hand, adversaries may capture, impersonate, replicate, or fabricate nodes to mislead the target to an incorrect position. On the other hand, adversaries may tamper, interfere, replay, or modify jointly localization information to disturb the localization. This paper describes two kinds of localization attacks and gives a systematic survey of existing secure localization solutions, including the design ideas, application scopes, and limitations. Next, several novel secure localization schemes for special WSNs applications, including Underwater Wireless Sensor Networks (UWSNs), Wireless Body Area Network (WBAN) and three-dimensional (3D), are analyzed. Finally, many open problems for secure localization are presented.

Depression detection from social network data using machine learning techniques

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Abstract

Purpose

Social networks have been developed as a great point for its users to communicate with their interested friends and share their opinions, photos, and videos reflecting their moods, feelings and sentiments. This creates an opportunity to analyze social network data for user’s feelings and sentiments to investigate their moods and attitudes when they are communicating via these online tools.

Methods

Although diagnosis of depression using social networks data has picked an established position globally, there are several dimensions that are yet to be detected. In this study, we aim to perform depression analysis on Facebook data collected from an online public source. To investigate the effect of depression detection, we propose machine learning technique as an efficient and scalable method.

Results

We report an implementation of the proposed method. We have evaluated the efficiency of our proposed method using a set of various psycholinguistic features. We show that our proposed method can significantly improve the accuracy and classification error rate. In addition, the result shows that in different experiments Decision Tree (DT) gives the highest accuracy than other ML approaches to find the depression.

Conclusions

Machine learning techniques identify high quality solutions of mental health problems among Facebook users.

Effects of Acupuncture on Alzheimer's Disease: Evidence from Neuroimaging Studies

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Abstract

As the worldwide population ages, the prevalence of Alzheimer's disease (AD) increases. However, the results of promising medications have been unsatisfactory. Chinese acupuncture has a long history of treating dementia, but lack of evidence from well-designed randomized controlled trials that validate its efficacy and safety, as well as its lack of clear underlying mechanisms, contribute to its limited application in clinical practice. In recent years, brain imaging technologies, such as functional magnetic resonance imaging and positron emission tomography, have been used to assess brain responses to acupuncture in a dynamic, visual, and objective way. These techniques are frequently used to explore neurological mechanisms of responses to acupuncture in AD and provide neuroimaging evidence as well as starting points to elucidate the possible mechanisms. This review summarizes the existing brain imaging evidence that explains the effects of acupuncture for AD and analyzes brain responses to acupuncture at cognitive-related acupoints [Baihui (GV 20), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6), and Taixi (KI 3)] from perspectives of acupoint specificity and acupoint combinations. Key issues and directions to consider in future studies are also put forward. This review should deepen our understanding of how brain imaging studies can be used to explore the underlying mechanisms of acupuncture in AD.


Flexible IC Interconnection and Electrical Continuity Verification

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Abstract

As the device miniaturization, the assembly is becoming more and more dense. The current fine pitch package or micro BGA and other forms of interconnection comes to a certain limit, which hinders the development of packaging and assembly. high-density assembly and packaging is facing a lot of new challenges. Today, even the most of the fine pitch packages’ pitch maintained at around 0.3 mm, it is difficult to continue to shrink, because with the pitch further smaller, there will be serious problems. For example: package reliability to be reduced, such as the emergence of lead bridging, solder ball, cold solder joints and other issues. In order to solve these problems, this paper presents a new way of interconnection. The conductive function is achieved by the conductive silicone rubber between the pad on the PCB and the lead of the packaged device. Due to the presence of pressure, the conductive adhesive is deformed and can be contacted from the top to the bottom and interconnection is formed. This interconnection form may be adapted to all conductive patterns depending on the spacing of the conductive layers. Conductive adhesive in the conductive material is generally carbon, metal, metal oxide, carrying capacity between 800–2800 mA/mm2. The current production of conductive silicone spacing between 0.1–0.05 mm. Through this technology, the size of the packages can be greatly reduced, and the assembly density can be greatly improved.

Paleogene sedimentation changes in Lenghu Area, Qaidam Basin in response to the India–Eurasia collision

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Abstract

The Cenozoic India–Eurasia collision is evidently recorded in the Qaidam Basin, which is located in the north margin of the Tibetan Plateau. The present study describes a dextrorotary phenomenon at the end of the Eocene in Lenghu Area in the northern Qaidam Basin, discovered in sedimentary and tectonic records. This phenomenon is interpreted to have been a result of the levorotatory movement along the Altyn Tagh Fault (ATF) based on the following evidence. First, provenance, as analyzed by heavy mineral assemblages, was slightly deflected from southwestward to the westward by about 45°. Second, paleocurrent inferred from dip logging and seismic reflection changed clockwise by approximately 25°. Third, there is evidence of increases in fault activity in the area, especially in northwest–southeast-trending branches relative to older west–east-trending branches. Increases in faulting coincide with abrupt increases in sediment supply in the Oligocene, after earlier decreases based on total sand content during the Eocene. Our results demonstrate that the northern margin of the Tibetan Plateau synchronously responded to the initiation and termination of the India–Eurasia collision. The levorotatory strike slip of the ATF was immediately triggered by the complete collision at the end of Eocene, and the strike-slip movement caused the dextrorotary phenomenon in the Lenghu Area.

Analysis of lipid adsorption on nanoparticles by nanoflow liquid chromatography-tandem mass spectrometry

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Abstract

Nanoparticles (NPs) tend to adsorb matrix molecules like proteins and lipids incubated with biological fluids, forming a biological corona. While the formation and functions of protein corona have been studied extensively, little attention has been paid to lipid adsorption on NPs. However, lipids are also abundantly present in biological fluids and play important roles in processes like cell signaling and angiogenesis. Therefore, in this study, we established the analytical procedure for study of lipid adsorption on three different types of NPs in two matrices: human serum and heavy cream, using nanoflow liquid chromatography-mass spectrometry (nanoflowLC-MS). Serum was chosen to represent the common environment the NPs would be present once entering human body, and heavy cream was the representative food matrix NPs may be added to improve the color or taste. Steps of liquid-liquid extraction were established and optimized to achieve maximum recovery of the adsorbed, standard lipids from the NPs. Then, the LC-MS/MS method was developed to attain base-line separation of the standard lipids that represent the major lipid classes. At last, the lipid adsorption profiles of the three NPs were compared. We found that the lipid adsorption profile on the same type of NP was significantly different between the two matrices. The established method will help us investigate lipid adsorption on additional NPs and reveal how it could be affected by the physiochemical properties of NPs and the presence of proteins and other components in the biological matrix.

Imbalanced Data Processing Model for Software Defect Prediction

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In the field of software engineering, software defect prediction is the hotspot of the researches which can effectively guarantee the quality during software development. However, the problem of class imbalanced datasets will affect the accuracy of overall classification of software defect prediction, which is the key issue to be solved urgently today. In order to better solve this problem, this paper proposes a model named ASRA which combines attribute selection, sampling technologies and ensemble algorithm. The model adopts the Chi square test of attribute selection and then utilizes the combined sampling technique which includes SMOTE over-sampling and under-sampling to remove the redundant attributes and make the datasets balance. Afterwards, the model ASRA is eventually established by ensemble algorithm named Adaboost with basic classifier J48 decision tree. The data used in the experiments comes from UCI datasets. It can draw the conclusion that the effect of software defect prediction classification which using this model is improved and better than before by comparing the precision P, F-measure and AUC values from the results of the experiments.

Fabrication of superhydrophobic and superoleophilic polybenzoxazine-based cotton fabric for oil–water separation

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Abstract

Superhydrophobic material involves the fabrication of appropriate roughness and low surface energy. Studies concerning enhancing the attachment between substrates and low surface energy material have been reported. Hence, it might also be feasible to make low surface energy material as an interface binder to enhance the attachment. In our work, the simple dip-coating method was used to fabricate polybenzoxazine (PBZ)/SiO2-coating cotton (PBZSC) fabric for rapid oil–water separation. The surface morphology and wettability of the PBZSC fabric as well as the properties of the separation were explored using various methods. These results demonstrated that PBZSC fabric not only had excellent thermal properties, but also maintained excellent superhydrophobicity (WCA > 150°) under various harsh conditions which was mainly attributed to higher surface roughness contributed by SiO2 and lower surface energy, heat resistance as well as acid and alkali resistance from PBZ resin, respectively. More importantly, the separation conducted by the PBZSC fabric not only showed great recycle property, but also separated a series of oil and water mixtures with up to 96% separation efficiency. Therefore, it is anticipated that this low-cost PBZSC fabric will be readily and widely utilized in designing multifunctional membrane for large-area oil-spill cleanup without using fluoropolymers or silicones.

Graphical abstract

The fecal virome of red-crowned cranes

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Abstract

The red-crowned crane is one of the rarest crane species, and its population is decreasing due to loss of habitat, poisoning, and infections. Using a viral metagenomics approach, we analyzed the virome of feces from wild and captive red-crowned cranes, which were pooled separately. Vertebrate viruses belonging to the families Picornaviridae, Parvoviridae, Circoviridae, and Caliciviridae were detected. Among the members of the family Picornaviridae, we found three that appear to represent new genera. Six nearly complete genomes from members of the family Parvoviridae were also obtained, including four new members of the proposed genus “Chapparvovirus”, and two members of the genus Aveparvovirus. Six small circular DNA genomes were also characterized. One nearly complete genome showing a low level of sequence identity to caliciviruses was also characterized. Numerous viruses believed to infect insects, plants, and crustaceans were also identified, which were probably derived from the diet of red-crowned cranes. This study increases our understanding of the enteric virome of red-crowned cranes and provides a baseline for comparison to those of other birds or following disease outbreaks.

Effects of hydrogel injection on borderzone contractility post-myocardial infarction

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Injectable hydrogels are a potential therapy for mitigating adverse left ventricular (LV) remodeling after myocardial infarction (MI). Previous studies using magnetic resonance imaging (MRI) have shown that hydrogel treatment improves systolic strain in the borderzone (BZ) region surrounding the infarct. However, the corresponding contractile properties of the BZ myocardium are still unknown. The goal of the current study was to quantify the in vivo contractile properties of the BZ myocardium post-MI in an ovine model treated with an injectable hydrogel. Contractile properties were determined 8 weeks following posterolateral MI by minimizing the difference between in vivo strains and volume calculated from MRI and finite element model predicted strains and volume. This was accomplished by using a combination of MRI, catheterization, finite element modeling, and numerical optimization. Results show contractility in the BZ of animals treated with hydrogel injection was significantly higher than untreated controls. End-systolic (ES) fiber stress was also greatly reduced in the BZ of treated animals. The passive stiffness of the treated infarct region was found to be greater than the untreated control. Additionally, the wall thickness in the infarct and BZ regions was found to be significantly higher in the treated animals. Treatment with hydrogel injection significantly improved BZ function and reduced LV remodeling, via altered MI properties. These changes are linked to a reduction in the ES fiber stress in the BZ myocardium surrounding the infarct. The current results imply that injectable hydrogels could be a viable therapy for maintaining LV function post-MI.


Financial Management and Decision Based on Decision Tree Algorithm

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In order to make university financial management more scientific, technologies such as data warehouse, data mining technology and decision support system are applied to college affairs decision-making. Aimed at a large amount of financial data generated by the financial management system in colleges and universities, the financial management and decision-making in colleges and universities are realized based on the decision tree algorithm. It provides effective support for the management of colleges and universities. The advantages and disadvantages of clustering algorithm and classification algorithm are analyzed. An improved C4.5 decision tree algorithm based on metric is proposed. Combined with data warehouse, data mining and analysis technology, data-driven thinking is adopted to establish university financial budget and model. Financial management and decision-making in colleges and universities are realized. It is applied to the financial project budget execution progress early warning, and carries on the experiment analysis and the result research. A complete financial data warehouse is built. Data aggregation, data analysis and data mining can reduce the amount of data information of the system. The result shows that this method makes college financial management and decision-making more convenient and effective.

Engraved Character Recognition of Train Wheelset Based on the Total Least Square Method

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According to the characteristics of depth information of the engraved characters and the lack of color difference to the background, a line structured light sensor was applied to acquire train wheelset engraved character point cloud information. The total least square method was proposed for a 3D character point cloud processing method, in which the observation vector error and the coefficient matrix error are taken into account. According to the standard deviation of the point cloud data, abnormal points and engraved character points can be eliminated for plane fitting. A high-quality outline of the character information can be extracted from the character point cloud depth data.

Auto Rack Girders Assembly Holes Measurement Based on Multi-camera Vision

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Since single camera’s visual field is limited, the measurement method for auto rack girders assembly holes based on multi-group of binocular vision is proposed. The measurement area is divided into several subregions, the measurement data of each subregion is obtained from the binocular vision measurement system, and a larger planar target is used to achieve three-dimensional data registration among adjacent subregion. Since the texture information of truck side-member surface is not abundant, it is difficult to seek the match points on the edge of assembly holes. It is proposed that pasting marked points around the edge of assembly holes for seeking match points. Every two marked points can be connected into one line, and the intersections of the lines and assembly holes’ edge are seen as match points. At last, the geometric parameters of spatial circle are fitted according to its geometrical properties. Experimental results show that the matching difficulty will be avoided effectively, the measurement error caused by perspective projection distortion can be reduced, and the method has higher measurement accuracy.

Autophagy plays a protective role against apoptosis induced by toxicarioside N via the Akt/mTOR pathway in human gastric cancer SGC-7901 cells

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Toxicarioside N (Tox N), a natural product extract from Antiaris toxicaria, has been reported to induce apoptosis in human gastric cancer cells. However, the mechanism and actual role of autophagy in Tox N-induced apoptosis of human gastric cancer cells remains poorly understood. In the current study, we demonstrated that Tox N could induce autophagy by inhibiting the Akt/mTOR signaling pathway in SGC-7901 cells. Moreover, we found that the inhibition of autophagy by 3-methyladenine, an autophagy inhibitor, enhanced Tox N-induced apoptotic cell death. However, the stimulation of autophagy by rapamycin, an autophagy activator, remarkably suppressed Tox N-induced apoptosis, suggesting that autophagy plays a protective role in Tox N-induced apoptosis. Thus, the results from this study suggested that Tox N combination with an autophagy inhibitor might be a promising strategy to enhance the anticancer activity of Tox N for the treatment of human gastric cancer.

Excellent optical, dielectric, and ferroelectric properties of Sr(In 0.5 Nb 0.5 )O 3 modified K 0.5 Na 0.5 NbO 3 lead-free transparent ceramics

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Abstract

High visible light transmittance (1 − x)(K0.5Na0.5)NbO3xSr(In0.5Nb0.5)O3 (KNN−xSIN, x = 0.05, 0.10, 0.15, 0.20, 0.25) lead-free ceramics with excellent electrical properties were synthesized by traditional solid-state method. The effects of Sr(In0.5Nb0.5)O3 doping on the optical properties, microstructure, and electrical performance were analyzed. The results showed that light transmission in KNN−xSIN ceramics was induced by the dense and fine-grain microstructure, the high symmetry of the pseudo-cubic structure as well as typical relaxor behavior of KNN−0.25SIN ceramic. Moreover, KNN−xSIN transparent ceramics with relaxor characteristics possessed permittivity stability over a wide temperature range. Ferroelectric properties were deteriorated gradually with increasing SIN content in virtue of the strengthened relaxor behavior. Its energy storage property was also tailored by the increasing relaxor characteristic. The appearance of a non-Debye type of relaxation was detected through an impedance Cole–Cole plots.

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