Most of the molybdenum (Mo) bilayer films are deposited by direct current (DC) magnetron sputtering at the bottom and the top layer (DC/DC). However, the deposition of Mo bilayer film by radio frequency (RF) Mo bottom layer and DC Mo top layer magnetron sputtering has been less studied by researchers. In this paper, the bottom layer of Mo bilayer film was deposited by RF magnetron sputtering to maintain its good adhesion and high reflectance, and the top layer was deposited by DC magnetron sputtering to obtain good conductivity (RF/DC). Generally, the bottom layer sputtering pressure is relatively random, in this paper, the effects of the bottom layer RF sputtering pressures on the microstructures and properties of Mo bilayer films were first studied in detail. Next, in order to further improve their properties, the as-prepared Mo bilayer films at 0.4 Pa bottom layer RF sputtering pressure were annealed at different temperatures and then investigated. Specifically, Mo bilayer films were deposited on soda-lime glass substrates by RF/DC magnetron sputtering at different bottom layer RF sputtering pressures in the range of 0.4–1.2 Pa, the powers of bottom layer RF sputtering and top layer DC sputtering were 120 W and 100 W, respectively. Then, Mo bilayer films, prepared at a bottom layer sputtering pressure of 0.4 Pa and top layer sputtering pressure of 0.3 Pa, were annealed for 30 min at various temperatures in the range of 100–400 °C. The effects of bottom layer sputtering pressures and the annealing temperatures on the microstructures, electrical and optical properties of Mo bilayer films were clarified by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), atomic-force microscopy (AFM), and ultraviolet (UV)-visible spectra, respectively. It is shown that with decreasing bottom layer sputtering pressure from 1.2 to 0.4 Pa and increasing annealing temperature from 100 to 400 °C, the crystallinity, electrical and optical properties of Mo bilayer films were improved correspondingly. The optimized Mo bilayer film was prepared at the top layer sputtering pressure of 0.3 Pa, the bottom layer sputtering pressure of 0.4 Pa and the annealing temperature of 400 °C. The extremely low resistivity of 0.92 × 10⁻⁵ Ω.cm was obtained. The photo-conversion efficiency of copper indium gallium selenium (CIGS) solar cell with the optimized Mo bilayer film as electrode was up to as high as 13.5%. Full article

This paper presents an experimental study on detecting and monitoring of evolution of fatigue damage in composites under cyclic loads by using guided waves. Composite specimens fabricated by glass fiber/epoxy laminates and surface mounted with piezoelectric wafers are fatigued under tension–tension loads. A laser extensometer is used to obtain the degradation of longitudinal stiffness of the specimens under fatigue states to reflect the accumulation of internal fatigue damage. Meanwhile, at different fatigue cycles, one wafer acts as actuator to excite diagnostic guided waves, and the other acts as sensor to receive corresponding response waves. These guided wave signals are then processed by wavelet packet transform to extract characteristic features of energies in multiple frequency bands. A statistical multivariate outlier analysis is then performed to determine the existence of fatigue damage and to characterize their evolution using Mahalanobis squared distance. Experimental results have demonstrated the potential applicability and effectiveness of guided waves for continuous monitoring of fatigue damage in composite structures. Full article

Angiogenesis plays a fundamental role in tumor growth and progression. It is regulated by several growth factors, including vascular endothelial growth factor protein family (VEGF) and its receptors, which are probably the most important factors responsible for the development of new vessels. The VEGF family includes several members: VEGF-A, VEGF-B, VEGF-C, VEGF-D, VEGF-E, placental growth factor (PlGF), and their receptors VEGFR-1, VEGFR-2 and VEGFR-3. Other relevant factors are represented by angiopoietins, thrombospondin-1, and endothelins. However, since the therapeutic benefit associated with VEGF-targeted therapy is really complex, a better understanding of these pathways will lead to future advances in the use of these agents for clinic management of tumors. Here we present a review regarding the role of angiogenic factors in cholangiocarcinoma, which arise from cholangiocytes, the epithelial cells of bile ducts. They are rare and aggressive neoplasms with a poor prognosis and limited treatment options, classified as intrahepatic, perihilar, and distal cholangiocarcinoma based on their anatomical location. Therefore, the identification of specific signaling pathways or new tumor biomarkers is crucial in order to develop more effective anti-angiogenic therapies. Full article

The recent increase in hacks and computer network attacks around the world has intensified the need to develop better intrusion detection and prevention systems. The intrusion detection system (IDS) plays a vital role in detecting anomalies and attacks on the network which have become larger and more pervasive in nature. However, most anomaly-based intrusion detection systems are plagued by high false positives. Furthermore, Remote-to-Local (R2L) and User-to-Root (U2R) are two kinds of attack which have low predicted accuracy scores in advance IDS methods. Therefore, this paper proposes a novel IDS framework to overcome these IDS problems. The proposed framework including three main parts. The first part is to build SFSDT model which is the feature selection model. SFSDT is to generate the best feature subset from the original feature set. This model is a hybrid Sequence Forward Selection (SFS) algorithm and Decision Tree (DT) model. The second part is to build various IDS models to train on the best-selected feature subset. The various Recurrent Neural Networks (RNN) are traditional RNN, Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). Two IDS datasets are used for the learned models in experiments including NSL-KDD in 2010 and ISCX in 2012. The final part is to evaluate the proposed model by comparing the proposed models to other IDS models. The experimental results show the proposed models achieve significantly improved accuracy detection rate as well as attack types classification. Furthermore, this approach can reduce the computation time by memory profilers measurement. Full article

In this paper, a low-complexity multi-cell resource allocation algorithm with a near-optimal system throughput is proposed to resolve the conflict between the high system throughput and low complexity of indoor visible light communication ultra-dense networks (VLC-UDNs). First, by establishing the optimal model of the resource allocation problem in each cell, we concluded that the problem is a convex optimization problem. After this, the analytic formula of the normalized scaling factor of each terminal for resource allocation is derived after reasonable approximate treatment. The resource allocation algorithm is subsequently proposed. Finally, the complexity analysis shows that the proposed algorithm has polynomial complexity, which is lower than the classical optimal inter-point method. The simulation results show that the proposed method achieves a improvement of 57% in performance in terms of the average system throughput and improvement of 67% in performance in terms of the quality of service (QoS) guarantee against the required data rate proportion allocation (RDR-PA) method. Full article

To improve the adsorption and separation efficiency of lead-containing wastewater by graphene oxide (GO), attapulgite (ATP) was used through a simple hydrothermal reaction. The prepared GO was characterized by SEM, TEM, FTIR, and XPS. The adsorption properties of the prepared GO were investigated. The maximum adsorption capacity of Pb²⁺ on as-prepared GO at pH 5 and 25 °C was 450.9 mg/g. It is concluded that the as-prepared GO can be used as a high-efficiency adsorbent for lead-containing wastewater. Full article

Climate conditions affect buildings’ performance and durability. The purpose of this paper is to examine the influence of climate conditions on roof deficiencies. 763 cases of such deficiencies were analyzed in this regard. Once the construction deficiencies were quantified, they were characterized from a climatological point of view and their ‘climate location segments’ were studied to obtain ‘ranges of concentration of anomalies’ according to the obtained percentage. A direct relation is shown to exist between the location of the building (latitude, situation, type of climate, precipitation, thermal demands, and average wind speed) and a greater or smaller concentration of deficiencies found in both flat and pitched buildings. It was also found that an annual average wind speed greater than 3 m/s increases the appearance of deficiencies in roofs. A higher prevalence of deficiencies was also found in those geographical zones with a thermal demand of 1800–2800 heating degree days or 450–700 cooling degree days. It was found that a higher percentage of construction deficiencies are concentrated in buildings located in the northern coastal climate segments of Spain. With these results, technicians will be able to take more appropriate precautions during both the building process and the use and maintenance phase. Full article

This paper describes an underwater acoustic sensor network consisting of a heterogeneous robotic swarm used for long-term monitoring of underwater environments. The swarm consists of a large number of underwater robots acting as sensor nodes with limited movement capabilities, and a few surface robots aiding them in accomplishing underwater monitoring scenarios. Main interactions between two types of robots include underwater sensor deployment and relocation, energy and data exchange, and acoustic localisation aiding. Hardware capabilities of each vehicle are described in detail. Inter-agent communication is split into two layers: surface and underwater communication. Surface communication utilises wireless communication using WiFi routers configured for decentralised routing. Underwater communication mainly uses acoustic communication which, when used within a large swarm, poses a challenging task because of high probability of interference and data loss. The acoustic communication protocol used to prevent these issues is presented in detail. Finally, more complex functionalities of the robotic swarm are presented, including several results from real-life experiments. Full article

Surface-enhanced Raman scattering (SERS) spectroscopy stands out due to its sensitivity, selectivity, and multiplex ability. The development of ready-to-use, simple, and low-cost SERS substrates is one of the main challenges of the field. In this paper, the intrinsic reproducibility of microfluidics technology was used for the fabrication of self-assembled nanoparticle structures over a paper film. The paper SERS substrates were fabricated by assembling anisotropic particles, gold nanostars (GNSs), and nanorods (NRs) onto paper to offer an extra enhancement to reach ultra-sensitive detection limits. A polydimethylsiloxane PDMS-paper hybrid device was used to control the drying kinetics of the nanoparticles over the paper substrate. This method allowed a high reproducibility and homogeneity of the fabrication of SERS substrates that reach limits of detection down to the picomolar range. This simple and low-cost fabrication of a paper-based sensing device was tested for the discrimination of different cell lineages. Full article

The service capacity of each station has a direct impact on the capacity of a subway line and also the whole subway network. Therefore, it is critically important to keep the station capacity above a certain level in its full life cycle. This paper aims at keeping subway station capacity in a certain level range. In consideration of key equipment failure, the expected station capacity model is established. After that the lower bound of equipment reliability is determined by sensitivity analysis based on the equipment reliability-expected station capacity curve. Finally, the maintenance schedule optimization model is also proposed. The validity and practicability of the proposed method are demonstrated by a simulation case study. Full article

Visual classification of commercial products is a branch of the wider fields of object detection and feature extraction in computer vision, and, in particular, it is an important step in the creative workflow in fashion industries. Automatically classifying garment features makes both designers and data experts aware of their overall production, which is fundamental in order to organize marketing campaigns, avoid duplicates, categorize apparel products for e-commerce purposes, and so on. There are many different techniques for visual classification, ranging from standard image processing to machine learning approaches: this work, made by using and testing the aforementioned approaches in collaboration with Adidas AG™, describes a real-world study aimed at automatically recognizing and classifying logos, stripes, colors, and other features of clothing, solely from final rendering images of their products. Specifically, both deep learning and image processing techniques, such as template matching, were used. The result is a novel system for image recognition and feature extraction that has a high classification accuracy and which is reliable and robust enough to be used by a company like Adidas. This paper shows the main problems and proposed solutions in the development of this system, and the experimental results on the Adidas AG™ dataset. Full article

Since an individual approach can hardly navigate robots through complex environments, we present a novel two-level hierarchical framework called JPS-IA3C (Jump Point Search improved Asynchronous Advantage Actor-Critic) in this paper for robot navigation in dynamic environments through continuous controlling signals. Its global planner JPS+ (P) is a variant of JPS (Jump Point Search), which efficiently computes an abstract path of neighboring jump points. These nodes, which are seen as subgoals, completely rid Deep Reinforcement Learning (DRL)-based controllers of notorious local minima. To satisfy the kinetic constraints and be adaptive to changing environments, we propose an improved A3C (IA3C) algorithm to learn the control policies of the robots’ local motion. Moreover, the combination of modified curriculum learning and reward shaping helps IA3C build a novel reward function framework to avoid learning inefficiency because of sparse reward. We additionally strengthen the robots’ temporal reasoning of the environments by a memory-based network. These improvements make the IA3C controller converge faster and become more adaptive to incomplete, noisy information caused by partial observability. Simulated experiments show that compared with existing methods, this JPS-IA3C hierarchy successfully outputs continuous commands to accomplish large-range navigation tasks at shorter paths and less time through reasonable subgoal selection and rational motions. Full article

Modular multilevel converters (MMCs) are quickly emerging as a suitable technology for a voltage-source converter-based high-voltage direct-current (VSC-HVDC) transmission systems due to its numerous advantages as reported in literature. However, for a large DC-network, MMCs require large numbers of sub-modules (SMs) and switches, which makes its modeling very challenging and computationally complex using electromagnetic transient (EMT) programs. Average Value Model (AVM) provides a relatively better solution to model MMCs by combining cells as an arm equivalent circuit. Circulating current is an important issue related to the performance and stability of MMCs. Due to circulating currents, power loss in a converter increases as root mean square (RMS) values of the arm current increases. The traditional method for inserting SMs in each arm is based on direct modulation, which does not compensate for the arm voltage oscillations, and generates circulating current in each leg of a three-phase MMC. This paper presents a new method for reducing the circulating current by adding 2nd and 4th harmonics in the upper and lower arm currents of an MMC. Less capacitor energy variations are obtained by the proposed method compared to traditional direct modulation methods. The proposed method is tested on a common symmetrical monopole (point-to-point) MMC-HVDC system using vector current control strategy in PSCAD/EMTDC software. Analytical and simulation results show the effectiveness of the new method in minimizing the circulating current and arm voltage oscillation reductions as compared to the direct modulation approach. Full article

A reliable and economic utilization of textile-reinforced concrete in construction requires appropriate design concepts. Unlike designs for bending, the development of models for shear is still the subject of current research. Especially for thin slabs, systematic experimental investigations are lacking. In this paper, the results of an experimental campaign on 27 carbon-textile reinforced slab segments tested in three-point bending are presented. The shear-span to depth ratio and member size were key variation parameters in this study. Increasing the structural depth of members led to a reduction in relative shear strength, while variation of shear slenderness controlled the efficiency of direct stress fields between load introduction and support. Interestingly, direct load transfer was activated up to a shear slenderness ratio of 4, which is significantly higher than in reinforced concrete (a/d < 2.5–3) and may result from the bond characteristics of the textile reinforcement. The experimental shear strengths were compared to predictions from existing models for shear of fiber-reinforced polymer (FRP)-reinforced concrete. The study shows that these FRP calculation models also predict the ultimate shear force for textile-reinforced concrete (TRC) tests presented in this paper with sufficient accuracy. Existing approaches for the size effect seem transferable as well. In order to validate the models for general use in TRC shear design, a compilation and comparison with larger experimental databases is required in future works. Full article

The study involved research related to the selection of the material with improved functional properties that can be used for dental prostheses. An innovative system of nanofillers, that differ in shape, by means of gelatin-modified halloysite nanotubes (HNTs-g) along with silane-coupled aluminum trihydrate (ATH-sil) was prepared, in order to observe a synergistic improvement of acrylic material (methyl methacrylate with methyl methacrylate monomer (MM/mMM)). Selected mechanical properties of manufactured nanocomposites, along with utilitarian properties, like hardness, buffer solution absorption, and abrasion resistance, along with a fall test from the height of finished products have been discussed. Moreover, the study of the biofilm formation on the surface of dental prostheses confirmed the occurrence of a synergistic improvement of properties and the legitimacy of using modified mineral nanofillers in the form of a hybrid system. Full article