Amplicon-Based Illumina Sequencing and Quantitative PCR Reveals Nanoplankton Diversity and Biomass in Surface Water of Qinhuangdao Coastal Area, China

Aureococcus anophagefferens caused brown tides for three consecutive years from 2009 to 2011 in the coastal waters of Qinhuangdao, China, with numerous, widespread ecological and economic impact on ecosystems. To understand the population dy- namics of nanoplankton during the brown tides, sequences of the V9 region of the 18S rDNA gene, used as a marker, were analyzed by Illumina sequencing to assess nanoplankton biomass, and real-time fluorescence quantitative PCR was performed to analyze spa- tial variation in the 18S rDNA copy concentrations of nanoplankton off the Qinhuangdao coast in July, 2011. The results showed that A. anophagefferens and Minutocellus polymorphus were the dominant species in the local phytoplankton community during the brown tide in July 2011. The highest 18S rDNA copy concentrations of A. anophagefferens and M. polymorphus were detected at stations SHG and FN, respectively. The central area most strongly affected by the brown tide migrated southward from 2011 to 2013. Redundancy analysis (RDA) showed that the decreasing NOx concentration might provide suitable nutrient conditions for the A. anophagefferens outbreak. During the brown tide caused by A. anophagefferens, other phytoplankton, such as diatoms, cryptophytes, chlorophytes, dinoflagellates and other flagellates, could co-occur with it. For zooplankton, due to less selective feeding behavior, Amoebozoa was the most abundant zooplankton at station SHG, while Ciliophora was the most abundant zooplankton at other sta- tions for its more selective feeding.

A Study on the Degradation of Carbamazepine and Ibuprofen by TiO₂&ZnO Photocatalysis upon UV/Visible-Light Irradiation

The degradation of carbamazepine (CBZ) and ibuprofen (IBP) in aqueous matrices was investigated by TiO2 and ZnO photocatalysis initiated by UV-A and visible-light irradiation. Emphasis was given on the effect of operating parameters on the degradation effectiveness, such as catalyst type and loading (50 - 500 mg/L), initial drug concentration (10, 40, 80 mg/L) and wavelength of irradiation (200 - 600 nm). In an effort to understand the photocatalytic pathway for CBZ and IBP removal in terms of primary oxidants, the contribution of HO· was evaluated. With this scope, the radical-mediated process was suppressed by addition of an alcohol scavenger, isopropanol, (i-PrOH), described as the best free hydroxyl radical quencher. The photodegradation rate of the pharmaceuticals was monitored by high performance liquid chromatography (HPLC). According to the results, visible-light exposure, at λexc > 390 nm, takes place as a pure photocatalytic degradation reaction for both compounds. IBP was found to have overall high conversion rates, compared to CBZ. IBP oxidized fast under photocatalytic conditions, regardless the adverse effect of the increase of initial drug concentration, or low catalyst load, irradiation upon visible-light, by either titania or zinc oxide. Finally, addition of isopropanol showed a significant inhibition effect on the CBZ degradation, taken as an evidence of a solution-phase mechanism. In the case though of IBP degradation, the hole mechanism may be prevailing, suggested by the negligible effect upon addition of isopropanol indicating a direct electron transfer between holes (h+) and surface-bound IBP molecules. A plausible mechanism of IBP and CBZ photocatalysis was proposed and described.

Impact of media violence on aggressive attitude for adolescents

The goal of this study was mainly to examine the impact of media violence on aggressive attitude among Chinese adolescents by using a modified STROOP task. 74 adolescents participated in this study, 37 were assigned to violent movie group and 37 were assigned to non-violent movie group. The results showed significant Movie Type and Trait Aggressiveness interaction, and adolescents with high aggressiveness (HA) had a significantly higher aggressive attitude than adolescents with mild aggressiveness (MA) and low aggressiveness (LA) after watching violent movies. Furthermore, the relation between significant Movie Type and Gender interaction was also found, and boys showed a significantly higher aggressive attitude than girls after watching violent movies. This implied that violent movies could effectively affect aggressive attitude for adolescents in China.

Transfer of Rural Surplus Labor and Vocational Education

The paper introduces about the rural surplus labor transfer.According to the paper,the transfer of rural surplus labor in China presents such fundamental characteristics as randomness and non-thoroughness,scope and field constraint,and hysteretic nature of employment and industrial structure conversion.Besides,the causes of the difficulties in the transfer of rural surplus labor lie in the barriers from the system and policy,structural imbalance of industry and low quality of rural labor.The paper studies the correlation between the quality and the transfer of rural surplus labor FORCE in a systematical way from three aspects,which are the correlations between rural labor quality and the transfer difficulty & speed,the transfer scope & field and the employment stability & income after transfer respectively.Moreover,the paper carries out analysis of the special effects of vocational education on the transfer of rural surplus labor in China,which shows that vocational education is a help in the improvement of cultural qualities,labor skills and physical & mental health of rural labor.

Specifying the Global Execution Context of Computer-Mediated Tasks: A Visual Notation and a Supporting Tool

This paper presents the notion of the global execution context of a task as a representational construct for analysing complexity in software evolution. Based on this notion a visual notation and a supporting tool are presented to support specification of a system’s global execution context. A system’s global execution context is conceived as an evolving network of use scenarios depicted by nodes and links designating semantic relationships between scenarios. A node represents either a base or a growth scenario. Directed links characterize the transition from one node to another by means of semantic scenario relationships. Each growth scenario is generated following a critique (or screening) of one or more base or reference scenarios. Subsequently, representative growth scenarios are compiled and consolidated in the global execution context graph. The paper describes the stages of this process, presents the tool designed to facilitate the construction of the global execution context graph and elaborates on recent practice and experience.

The Short-Term Effect of Online Violent Stimuli on Aggression

The significance of this study was to find whether violent stimuli exposure could escalate the following levels of aggression in order to better cultivate aggression education among contemporary undergraduates in China. This study mainly tested the effects of violent stimuli on aggression by employing modified Stroop task. A total of 188 undergraduates participated in this study. Results showed that undergraduates exposing to violent stimuli exhibited high levels of aggression, whereas undergraduates who exposed to non-violent stimuli displayed low levels of aggression. Specifically, males, but not females, manifested high levels of aggression after exposure to violent stimuli. Moreover, viewers with high-aggressiveness (HA), but not with moderate-aggressiveness (MA) and low-aggressiveness (LA), showed high levels of aggression after exposure to violent stimuli via internet.

Erratum to “Impact of Media Violence on Aggressive Attitude for Adolescents” [Health 5 (2013) 2156-2161]

The original online version of this article (Zhang, Q., Xiong, D.Y. and Tian, J.J. (2013) Impact of Media Violence on Aggressive Attitude for Adolescents. Health, 5, 2156-2161. http://dx.doi.org/10.4236/health.2013.512294) was published as some results data reported mistakenly. The author wishes to correct the errors to:

Erratum to “The Short-Term Effect of Online Violent Stimuli on Aggression” [Open Journal of Medical Psychology 5 (2016) 35-42]

The original online version of this article (Tian, J.J., Zhang, Q., Cao, J. and Rodkin, P. (2016) The Short-Term Effect of Online Violent Stimuli on Aggression. Open Journal of Medical Psychology, 5, 35-42. http://dx.doi.org/10.4236/ojmp.2016.52005) was published as some results data reported mistakenly. The author wishes to correct the errors to:

An Active Image Forgery Detection Approach Based on Edge Detection

Recently, digital images have become the most used data, thanks tohigh internet speed and high resolution, cheap and easily accessible digitalcameras. We generate, transmit and store millions of images every second.Most of these images are insignificant images containing only personal information.However, in many fields such as banking, finance, public institutions,and educational institutions, the images of many valuable objects like IDcards, photographs, credit cards, and transaction receipts are stored andtransmitted to the digital environment. These images are very significantand must be secured. A valuable image can be maliciously modified by anattacker. The modification of an image is sometimes imperceptible even by theperson who stored the image. In this paper, an active image forgery detectionmethod that encodes and decodes image edge information is proposed. Theproposed method is implemented by designing an interface and applied on atest image which is frequently used in the literature. Various tampering attacksare simulated to test the fidelity of the method. The method not only notifieswhether the image is forged or not but also marks the tampered region ofthe image. Also, the proposed method successfully detected tampered regionsafter geometric attacks, even on self-copy attacks. Also, it didn’t fail on JPEGcompression.

FEW-NNN: A Fuzzy Entropy Weighted Natural Nearest Neighbor Method for Flow-Based Network Traffic Attack Detection

Attacks such as APT usually hide communication data in massive legitimate network traffic, and mining structurally complex and latent relationships among flow-based network traffic to detect attacks has become the focus of many initiatives. Effectively analyzing massive network security data with high dimensions for suspicious flow diagnosis is a huge challenge. In addition, the uneven distribution of network traffic does not fully reflect the differences of class sample features, resulting in the low accuracy of attack detection. To solve these problems, a novel approach called the fuzzy entropy weighted natural nearest neighbor(FEW-NNN) method is proposed to enhance the accuracy and efficiency of flowbased network traffic attack detection. First, the FEW-NNN method uses the Fisher score and deep graph feature learning algorithm to remove unimportant features and reduce the data dimension. Then, according to the proposed natural nearest neighbor searching algorithm(NNN_Searching), the density of data points, each class center and the smallest enclosing sphere radius are determined correspondingly. Finally, a fuzzy entropy weighted KNN classification method based on affinity is proposed, which mainly includes the following three steps: 1、 the feature weights of samples are calculated based on fuzzy entropy values, 2、 the fuzzy memberships of samples are determined based on affinity among samples, and 3、 K-neighbors are selected according to the class-conditional weighted Euclidean distance, the fuzzy membership value of the testing sample is calculated based on the membership of k-neighbors, and then all testing samples are classified according to the fuzzy membership value of the samples belonging to each class;that is, the attack type is determined. The method has been applied to the problem of attack detection and validated based on the famous KDD99 and CICIDS-2017 datasets. From the experimental results shown in this paper, it is observed that the FEW-NNN method improves the accuracy and efficiency of flow-based network traffic attack detection.

Crustal Thermo-Structure and Geothermal Implication of the Huangshadong Geothermal Field in Guangdong Province

Dense distribution of granites and surrounding hot springs, the high anomalous heating rates of geothermal fluids and the high geothermal gradients in shallow crust in Southeast China are revealed by previous geothermal explorations. However, there have always been debates on the genesis of geothermal anomalies of Southeast China. It is imperative to look into the genesis mechanism of geothermal anomalies through selecting a typical geothermal field, and constructing fine crustal thermostructure. In this study, in-depth excavation is implemented for the previous data of geophysical exploration and deep drilling exploration in the Huangshadong area. We synthetically analyze the results of radioactive heat productions(RHPs), thermophysical properties of rocks and audio-frequency magnetotellurics(AMT) sounding. This study concludes that the coefficient of radioactive heat generation(RHG) of crustal rocks and conduction heat of concealed granites is the main formation mechanism of geothermal anomalies of South China, where occurs a Great Granite Province. There is a regional indicating implication for the genesis of geothermal anomalies, taking the Huangshadong geothermal field as a typical example. It is also an important reference to guide the exploration, evaluation, development and utilization of geothermal resources in this region.

30 glitches in 18 radio pulsars

Pulsar timing is a classic technology of detecting irregularities in pulsar rotation.We carried out this method for 18 young radio pulsars,with long-term timing observations obtained between 2007 and 2015 using the Parkes 64-m radio telescope.As a result,30 glitches were identified,ranging from 0.75 × 10^(-9) to 8.6 × 10^(-6) in the relative glitch sizes Δv/v,where v=1/P is the pulse frequency.These glitches are composed of 26 new glitches and four published glitches with new exponential recoveries.All pulsars exhibit normal glitches,and six pulsars were observed to undergo a glitch event for the first time.We discuss the properties and implications for neutron-star physics of these glitches,and show that they are in agreement with previous work,except that the cumulative probability distributions of the mean waiting times for PSRs J0537-6910,J1341-6220 and J1740-3015 are not in consonance with the Poisson model.

On the Same Floor Building Drainage Technology

The same floor drainage refers to sanitary wares in the washing room, to be specific, the drainage pipe （sewage and branch pipes respectively） which can be into other houses without going through floors! This technology has many advantages, like easy to construct and install at the same floor on one hand; on the other hand, when sewage or waste reach the top compared with the same kind drainage systems and other drainage methods, it can smoothly enter the main pipe （the chief vertical one）. Moreover, once there is any situation needing dredge and cleaning, this problem can be solved at the same floor without interrupting the lives of other families. Last but not the least, it is so convenient to create a clean and tidy washing room. The branch pipe without being through floors is the very reason to solve the problem of surface condensation relative to sewage pipe in the rainy days, which correspondingly increases the hcight of head room indoor, is more favorable for fire prevention and much easier to keep smooth pipe flow.

Proposed numerical and machine learning models for fiber-reinforced polymer concrete-steel hollow and solid elliptical columns

This study employs a hybrid approach,integrating finite element method(FEM)simulations with machine learning(ML)techniques to investigate the structural performance of double-skin tubular columns(DSTCs)reinforced with glass fiber-reinforced polymer(GFRP).The investigation involves a comprehensive examination of critical parameters,including aspect ratio,concrete strength,number of GFRP confinement layers,and dimensions of steel tubes used in DSTCs,through comparative analyses and parametric studies.To ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of the analysis.The present research work examines the use of the columns with elliptical cross-sections and contributes valuable insights into the application of FEM and ML in the design and evaluation of structural systems within the field of structural engineering.

Dynamic Simulation Analysis of Humanoid Robot Walking System Based on ADAMS

Humanoid robots are a hot topic in the field of robotics research. The walking system is the critical part of the humanoid robot, and the dynamic simulation of the walking system is of great importance. In this paper, the stability of the walking system and the rationality of its structural design are considered in the study of dynamics for a humanoid robot. The dynamic model of humanoid robot walking system is established by using the Lagrange dynamics method. Additionally, the three-dimensional model of CATIA is imported into ADAMS. The humanoid robot walking system is added with the movement of the deputy and the driving force in the ADAMS.The torque and angular velocity of the ankle joint and hip joint are analyzed in the process of knee bends. The simulation results show that the overall performance of the humanoid robot walking system is favorable and has a smooth movement, and the specified actions can be completed, which proves the rationality of the humanoid robot walking system design.

A novel combination belief rule base model for mechanical equipment fault diagnosis

Due to the excellent performance in complex systems modeling under small samples and uncertainty,Belief Rule Base(BRB)expert system has been widely applied in fault diagnosis.However,the fault diagnosis process for complex mechanical equipment normally needs multiple attributes,which can lead to the rule number explosion problem in BRB,and limit the efficiency and accuracy.To solve this problem,a novel Combination Belief Rule Base(C-BRB)model based on Directed Acyclic Graph(DAG)structure is proposed in this paper.By dispersing numerous attributes into the parallel structure composed of different sub-BRBs,C-BRB can effectively reduce the amount of calculation with acceptable result.At the same time,a path selection strategy considering the accuracy of child nodes is designed in C-BRB to obtain the most suitable submodels.Finally,a fusion method based on Evidential Reasoning(ER)rule is used to combine the belief rules of C-BRB and generate the final results.To illustrate the effectiveness and reliability of the proposed method,a case study of fault diagnosis of rolling bearing is conducted,and the result is compared with other methods.