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This study was aimed at analyzing data and evaluating the accuracy of a new subcutaneous continuous glucose-monitoring device by referring to finger-pricking measurement. The data were obtained from 7 diabetic patients. An improved implanted flex sensor was used to measure the interstitial glucose concentration every 3 min within 6 days, and five finger-pricking samples were collected every day for comparison. A periodic glucose change happened every day. 2.45% of CGM values were in the hypoglycemic range (180 mg/dl). The interstitial glucose concentrations (n=204) were well linearly correlated with the capillary glucose concentrations (r=0.94, P<0.01), but a delay occurred between 10 and 40 minutes within two measurements (CGM later), and the individual average delay times were relatively close to 24.6 minutes. Clarke’s error grid analysis showed that 86.7% of the points fell in zone A, 12.7% fell in zone B, and only 0.6% fell in zone D. An overall MARD was 10.22%. This study demonstrated that the CGM was accurate and highly reliable; thus, it constituted a new device for continuous glucose monitoring in diabetic patients.

Gold nanorods (Au NRs) have attracted extensive research interest due to their unique optical properties, adjustable aspect ratio, and easy surface modification in the fields of biosensing, bioimaging, and disease diagnosis and detection. In this review, we present a comprehensive review of various methods for preparing gold nanorods including hard template method, electrochemistry method, photochemistry method, seed-mediated growth method, secondary growth method, and amorphous seed method. The unique optical properties of the gold nanorods and its applications in biomedical, detection, catalysis, and information storage will also be discussed in detail.

With the ever-increasing concern in network security and privacy, a major portion of Internet traffic is encrypted now. Recent research shows that more than 70% of Internet content is transmitted using HyperText Transfer Protocol Secure (HTTPS). However, HTTPS encryption eliminates the advantages of many intermediate services like the caching proxy, which can significantly degrade the performance of web content delivery. We argue that these restrictions lead to the need for other mechanisms to access sites quickly and safely. In this paper, we introduce QoS3, which is a protocol that can overcome such limitations by allowing clients to explicitly and securely re-introduce in-network caching proxies using fine-grained trust delegation without compromising the integrity of the HTTPS content and modifying the format of Transport Layer Security (TLS). In QoS3, we classify web page contents into two types: (1) public contents that are common for all users, which can be stored in the caching proxies, and (2) private contents that are specific for each user. Correspondingly, QoS3 establishes two separate TLS connections between the client and the web server for them. Specifically, for private contents, QoS3 just leverages the original HTTPS protocol to deliver them, without involving any middlebox. For public contents, QoS3 allows clients to delegate trust to specific caching proxy along the path, thereby allowing the clients to use the cached contents in the caching proxy via a delegated HTTPS connection. Meanwhile, to prevent Man-in-the-Middle (MitM) attacks on public contents, QoS3 validates the public contents by employing Document object Model (DoM) object-level checksums, which are delivered through the original HTTPS connection. We implement a prototype of QoS3 and evaluate its performance in our testbed. Experimental results show that QoS3 provides acceleration on page load time ranging between 30% and 64% over traditional HTTPS with negligible overhead. Moreover, QoS3 is deployable since it requires just minor software modifications to the server, client, and the middlebox.

Reversible data hiding (RDH) is a method that allows a cover image to be completely recovered from its corresponding stego image without distortion after the embedded secret messages have been extracted. Prediction-error expansion (PEE), as a classic RDH scheme, has been studied extensively due to its high quality of stego images. Based on prediction errors, threshold values, and the relative distances between each bin and zero bin, we present a bidirectional shift and double-way prediction strategy to solve the multiple embedding problem. Compared with the original algorithm, this scheme only takes a little more time and reduces the PSNR slightly, but it improves the embedding capacity significantly and allows for reversible data hiding. When both threshold values of TH and TH∗ are equal to 2, the average ER value of 108 test images is 1.2 bpp which is ideal for medium data payload. At the same time, the PSNR is above 30 dB, making embedded information visually imperceptible. These data, together with other experimental results, show that the method proposed in this paper has obvious advantages in image quality and embedding capacity.

Growth of Cu polyhedral structures with well-defined and controllable shapes faced tremendous synthetic challenges in colloid nanocrystal synthesis in the past few decades. In this article, we report a facile approach for the synthesis of Cu nanocrystals with systematic morphological evolution. Transitional truncated octahedral, edge- and corner-truncated octahedral, all-corner-truncated octahedral, and octahedral structures were obtained in a solution-based reduction reaction by precise tuning reaction time. Four distinct morphologies of nanocrystals have been characterized by SEM technique. The optical properties of these various morphologies of nanocrystals were also investigated, and it indicates that the SPR band shifts red while the shape of nanoparticles evolves from transitional truncated octahedral to octahedral, whose resonant bands are transferred from 590 nm to 620 nm.

We synthesized zinc oxide-reduced graphene oxide (ZnO-rGO) composites using a one-pot chemical deposition method at room temperature. Zinc powder and graphene oxide (GO) of different mass ratios (1 : 1, 1 : 2, 1 : 5, 1 : 10, and 1 : 20 GO to Zn) were used as precursors in a mildly alkaline solution. UV-Vis spectroscopy was used to study the photocatalytic efficiency of the samples through the photodegradation of methylene blue (MB). UV-Vis measurements show the fast decomposition of methylene blue under UV light illumination with the best degradation efficiency of 97.7% within one hour, achieved with sample ZG2 (1 GO : 2 Zn mass ratio). The corresponding degradation rate was kZG2 = 0.1253 min−1, which is at least 5.5 times better than other existing works using hydrothermal methods. We argue that the excellent photodegradation of MB by ZG2 is due to the efficient charge separation brought about by the electronic interaction of the rGO with the ZnO and the formation of a Zn-O-C bond, as supported by XRD and Raman spectroscopy measurements.

The Ga0.25Zn4.67S5.08 catalysts were prepared by ultrasonic spray pyrolysis with thiourea as a precursor. The crystal structure, optical properties, specific surface area, chemical composition, surface morphology, and internal structure of the prepared samples were characterized by XRD, UV-Vis DRS, BET, XPS, SEM, and TEM, respectively. The disinfection performance and the main active species of the synthesized catalysts under visible light irradiation were investigated with E. coli K12. The study results indicate that Ga0.25Zn4.67S5.08 prepared at 400°C exhibited the best antibacterial performance with complete kill of E. coli K12 within 4 h. The antibacterial performance of the prepared sample is also higher than that prepared by the hydrothermal method. The result of the radical trapping experiment indicates that the photogenerated holes play a dominant role in the disinfection process.

In this paper, we synthesized ~105±15 nm cubic phase KMnF3:Yb3+,Er3+ NPs, ~195±10 nm hexagonal phase NaYF4:Yb3+,Tm3+ NPs, and ~200±10 nm hexagonal phase NaYF4:Yb3+,Er3+ NPs. Under the excitation of 980 nm, the strong red upconversion luminescence (4F9/2⟶4I15/2, the peak is located at ~653 nm) of Er3+ ions of KMnF3:Yb3+,Er3+ NPs can be seen, the strong blue upconversion luminescence (1D2⟶3F4, 1G4⟶3H6; the peaks are located at ~451 nm and ~477 nm, respectively) of Tm3+ ions of NaYF4:Yb3+,Tm3+ NPs can be observed, and the strong green upconversion luminescence (4I11/2⟶4I15/2, 4S3/2⟶4I15/2; the peaks are located at ~524 nm and ~541 nm, respectively) of Er3+ ions of NaYF4:Yb3+,Er3+ NPs can be found. The mixed white upconversion luminescent materials can be obtained by adjusting the doping ratio of the above NPs. Cyclohexane solution of red, blue, green, and the mixed white NPs can be used as ink, and “JLNU” is written on paper with a pen. Without 980 nm radiation, nothing could be seen. Under 980 nm irradiation, the colored letters “JLNU” can be seen. Red, blue, green, and the mixed white upconversion NPs can be used in security anticounterfeiting.

Cancer was ranked as the second leading cause of death, and colon cancer has been reported as the third most frequent cancer worldwide. Chemotherapeutic drugs act on normal and cancerous cells similarly; therefore, they have various adverse side effects. Nanoparticles were identified to have a controlled effect on different cancer cell lines. The present study is aimed at studying biosynthesis silver nanoparticles by using aqueous Olea chrysophylla and Lavandula dentata leaf extracts, separately, and evaluating their anticancer potential. Silver nanoparticles were characterized by using SEM, XRD, FTIR, zeta potential, and size distribution mean, and their antiproliferative and apoptotic potentials were evaluated on HCT116 cells. Results show the formation of silver nanoparticles Olea-AgNPs and Lav-AgNPs due to the change of color to dark brown, and characterization revealed their crystalline shape with a mean size of 284.5 nm for Lav-AgNPs and 328.6 nm for Olea-AgNPs. Lav-AgNPs shows more stability than Olea-AgNPs due to its higher negative zeta potential (-14.3 mV) than nanoparticles biosynthesized from Olea leaves (-0.877 mV). Conversely, Lav-AgNPs shows more effective antiproliferative potential on HCT116 with (IC50 = 59.79 μg/ml) than Olea-AgNPs (IC50 = 99.35 μg/ml). However, Olea-AgNPs significantly increased the late stage of apoptotic and necrotic cells in comparison to Lav-AgNPs-treated cells in flow cytometry assay. Silver nanoparticles biosynthesized from Olea and lavender show anticancer potential with a more effective potential reported compared to Lav-AgNPs.

Images, as one of the important carriers for information exchange, play an important role in work and daily life. Image encryption technology has received a lot of attention, and varieties of encryption technologies for images have emerged. Early image encryption technologies have shortcomings such as simple algorithm structure, small key space, and poor resistance to plaintext attacks. These algorithms have been unable to meet the needs of information security at this stage. Based on the wavelet algorithm, chaos algorithm, and cyclic encryption algorithm, combined with frequency domain encryption and spatial domain encryption, a digital image encryption algorithm based on adaptive wavelet is proposed in this paper. In terms of frequency, this paper enhances the adaptive ability of the wavelet algorithm by convex optimization-particle swarm optimization (PSO). At the same time, the chaotic algorithm is used to scramble the low-frequency coefficients. In the aspect of airspace, this paper uses the block-encryption adaptive encryption algorithm to rescramble the wavelet-reconstructed image. And the SHA-1 algorithm is introduced into the plaintext image generation key sequence as a cyclic index value for cyclic encryption. The key composition of the encryption algorithm proposed in this paper is complex, and the idea of a one-time pad is used, which makes the improved algorithm increase the key space and improve the ability to resist the choice of plaintext attack. In each cyclic encryption of the airspace, mutual encryption is performed by image subblocks, and the algorithm adaptability is improved. Through the experimental test of statistical characteristics, key space, and key sensitivity, the encryption performance of the algorithm is verified, and it has strong antiattack and interference ability. It is a relatively secure encryption algorithm.

The simple and practicable intrinsic driving mechanism is of great significance for the design and development of nanoscale devices. This paper proposes a nanosystem that can achieve directional gradientless thermoexcited rotation at a relatively high temperature field (such as 300 K). In the case of a constant temperature field, the difference in atomic van der Waals (VDW) potentials in different regions of the rotor can be achieved by an asymmetric design of the structure, which provides torque for the rotation of the rotor. We studied the rotation and driving mechanism of the designed system through molecular dynamics (MD) simulation and discussed the influence of the chiral combination of carbon nanotubes, the chirality of graphene substrate, the length of graphene substrate, and the system temperature on rotation. At the same time, this paper also makes a qualitative analysis of the feasibility of the designed system from the perspective of molecular mechanics combined with energy. This research provides a new idea of nanoscale driving rotation, which has guiding significance for the design and application of related nanodevices in the future.

The one-dimensional nanoscaled bar is commonly seen in current nanodevices, and it plays a significant role in nanoelectromechanical system (NEMS) and related nanotechnology. Motivated by this, the paper is concerned with the bending and stability of a nanoscaled bar especially a flexible bar subjected to vertical concentrated, vertical linearly distributed, and horizontal concentrated forces simultaneously. The theoretical model is developed by employing Eringen’s nonlocal differential law. Hence, the nonlocal differential constitutions in terms of stress and bending moment at a nanoscale are applied to the classical equilibrium formulation in order to construct the nonlocal constitutive model and then determine the analytical solutions for bending of such a nanoscale bar. Subsequently, the effect of a nonlocal scale on the midpoint deflections and internal forces is shown numerically, and the internal and external characteristic length scales are also examined. It is revealed that the capacity of resisting compression decreases with increasing the nonlocal effect since the internal characteristic scale cannot be neglected by comparing with the external characteristic scale. There exists a threshold value for bending stiffness. Both the midpoint deflection and bending moment vary monotonously when the material bending stiffness exceeds the threshold value, while the mechanical quantities fluctuate when the bending stiffness is less than its threshold value, namely, for a flexible nanoscaled bar. Accordingly, two different kinds of nonlocal predictions and the related disputes are resolved in the context of Eringen’s nonlocal differential law. The work is expected to be useful for the design, application, and optimization of nanoscaled bars sustaining bending with linear vertical and horizontal forces.

Attribute-based signature (ABS) is a promising cryptographic primitive. It allows the signer to generate a signature with attributes satisfying the predicate without leaking more information, so as to provide message authenticity in an anonymous manner. However, drawbacks concerning security and efficiency hinder its applications for authentication in mobile platforms. Here, we present F2P-ABS, an escrow-free and pairing-free attribute-based signature supporting perfect signer privacy for mobile anonymous authentication. To enhance its adaptiveness to mobile platforms, a novel key extraction is proposed so that the key escrow problem is mitigated over the single authority setting. It also helps to remarkably reduce the size of the signing key. Different from existing schemes, F2P-ABS is free from pairing operations. It performs no pairing operation for verification. Without the loss of security, we prove that F2P-ABS achieves signer privacy in perfect sense. It is also proven to guarantee existential unforgeability under corrupted and adaptive chosen predicate and message attack, which is securer than existing schemes.

The effect of the addition of cellulose nanocrystals (CNCs) on the properties of cement pastes is studied herein. The compressive strength of CNC/cement paste was investigated under the curing conditions defined in this study. Two-dimensional micrographs and pore size distributions were obtained by scanning electron microscopy, X-ray computed tomography (XCT), and nitrogen adsorption. The addition of CNCs was found to significantly enhance the mechanical properties of cement pastes with a rapid decrease in temperature and humidity. XCT and nitrogen adsorption analyses show that the addition of CNCs leads to a refinement of the pore structure in the cement matrix. Almost no hydration products, including C-S-H, are formed in the cement matrix without CNCs under extreme conditions. This is in contrast with the results for the cement paste with 0.5% CNCs.

Intercalation and exfoliation are key steps in the preparation of graphene by thermal exfoliation, and they determine the quality of the final product. Therefore, it is important to explore the influence of intercalation agents on the intercalation and exfoliation of graphite. In this article, ammonium bicarbonate is intercalated into graphite with different degrees of oxidation to form a graphite intercalation compound (GIC) by means of ultrasound and stirring. Then, they are exfoliated by being heated at high temperatures. After ammonium bicarbonate intercalation and heating treatment, XRD, TG, and BET show that the intercalation and exfoliation effect of graphite oxide (GO) is better than that of graphite (G) and expanded graphite (EG). The intercalation mechanism is that the ammonia molecule in ammonium bicarbonate solution contains a wedge-shaped structure and active point, which provides empty orbits for graphite electrons and forms edge intercalation through physical interaction at the same time.

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

Carbon dots (CDs) have received significant attention worldwide from the beginning of this century, and recently, it has bloomed in every branch of applied sciences. Because of their outstanding physical and chemical properties together with biocompatibilities, CDs find a wide spectrum of applications in drug delivery, explosive detection, chemical sensing, food safety, bioimaging, energy conversion, photocatalysis, etc. This brief review is focused on the synthesis of CDs and their applications. The photophysical properties of CDs are also discussed herewith.

In this paper, a new application of the optical mouse sensor is presented. The optical mouse is used as a main low-cost infrared vision system of a new proposal of a head-mounted human-computer interaction (HCI) device controlled by eye movements. The default optical mouse sensor lens and illumination source are replaced in order to improve its field of view and capture entire eye images. A complementary 8-bit microcontroller is used to acquire and process these images with two optimized algorithms to detect forced eye blinks and pupil displacements which are translated to computer pointer actions. This proposal introduces an inexpensive and approachable plug and play (PnP) device for people with severe disability in the upper extremities, neck, and head. The presented pointing device performs standard computer mouse actions with no extra software required. It uses the human interface device (HID) standard class of the universal serial bus (USB) increasing its compatibility for most computer platforms. This new device approach is aimed at improving comfortability and portability of the current commercial devices with simple installation and calibration. Several performance tests were done with different volunteer users obtaining an average pupil detection error of 0.34 pixels with a successful detection in 82.6% of all mouse events requested by means of pupil tracking. This research was funded by Indra, Accessibility Chair, 2017. This research also was supported by the Government of Catalonia (Comissionat per a Universitats i Recerca, Departament d’Innovació, Universitats i Empresa) and the European Social Fund.

In this work, the ohmic contact mechanism of Ni electrodes on C-faced 4H-n-SiC was investigated by evaluating the electrical and microstructural properties in the contact interface as a function of annealing temperatures ranging from 950 to 1100°C. We determined that Ni-silicide, especially the NiSi phase, plays a key role in the formation of ohmic contacts rather than an increase in carbon vacancies in the C-faced SiC substrate. A vertically oriented NiSi phase was observed in the thermally annealed sample at the optimized temperature that behaves as a current path. A further increase in annealing temperature leads to the degradation of ohmic behavior due to the formation of horizontal-type NiSi in the Ni-rich Ni-silicide/NiSi/SiC structure.

This paper describes the characterization of the light hole, also known as the lumen, in implanted stents affected by restenosis processes using bioimpedance (BI) as a biomarker. The presented approach will enable real-time monitoring of lumens in implanted stents. The basis of the work hereby reported is the fact that neointimal tissues involved in restenosis can be detected and measured through their impedance properties, namely, conductivity and permittivity. To exploit these properties, a 4-electrode setup for BI measurement is proposed. This setup allows study of the influence of the various tissues involved in restenosis fat, muscle, fibre, and endothelium, together with the blood, on the BI value at several frequencies. In addition, BI simulation tests were performed using the electric physics module available in COMSOL Multiphysics®. Interestingly, fat constitutes the most influential layer on the value of impedance (measured in kΩ/μm—magnitude change per micrometre of lumen occlusion). A case study using a standard stent is also presented. In this study, where the involved tissues and blood were simultaneously considered, we conducted an analysis for stable and vulnerable plaques in restenosis test situations. In this regard, the proposed method is useful to test the stent obstruction and detect potential dangerous cases due to nonstable fat accumulation.

In this paper, g-C3N4-WO3 composite materials were prepared by hydrothermal processing. The composites were characterized by means of X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and N2 adsorption-desorption, respectively. The gas sensing properties of the composites were investigated. The results indicated that the addition of appropriate amount of g-C3N4 to WO3 could improve the response and selectivity to acetone. The sensor based on 2 wt% g-C3N4-WO3 composite showed the best gas sensing performances. When operating at optimum temperature of 310°C, the responses to 1000 ppm and 0.5 ppm acetone were 58.2 and 1.6, respectively, and the ratio of the S1000 ppm acetone to S1000 ppm ethanol reached 3.7.

Application of low-temperature PECVD is a very tempting option for formation of ultrathin silicon layers for nanoelectronic and nanophotonic applications, as followed by annealing of this layer, regardless if executed as individual process performed in controlled ambient or during following high-temperature processes, allows for phase and content changes in the silicon layer. Understanding complex changes that can take place during such process, which depend on its temperature, conditions (e.g., oxygen availability), and timeframe, is a fundamental requirement for conscious application of such technology. It is worth realizing that nanodevices with their unprecedented variety of structures and devices require many different fabrication technologies. Hence, depending on the application in mind, different results of ultrathin silicon layer annealing may appear advantageous. During high-temperature processing (e.g., annealing) of PECVD ultrathin silicon layer, three competing effects have to be taken into account. These are amorphous silicon recrystallization and oxidation of amorphous and crystalline (as-deposited or just recrystallized from as-deposited amorphous phase) silicon (both of which by nature exhibit different kinetics). So far, most of attention has been paid to silicon recrystallization, which was justified by the fact that under experimental conditions studied (silicon multilayers) oxidation was certainly of less importance. In certain applications, the required device structure consists of single (and not multiple) ultrathin silicon layer, and thus, oxidation effects certainly have to be included into considerations. Understanding dynamics and very complex relations between these individual effects is thus mandatory for using consciously this technique and achieving needed properties of the layer. It has to be stated clearly that although the achieved results, presented in this study, refer to the silicon layers fabricated under certain conditions (particular type of PECVD reactor and process parameters), they can, however, be easily extrapolated for similar cases too. The presented below results are, to our knowledge, the first successful attempt to address these issues.

Substitution box (S-box) is a vital nonlinear component for the security of cryptographic schemes. In this paper, a new technique which involves coset diagrams for the action of a quotient of the modular group on the projective line over the finite field is proposed for construction of an S-box. It is constructed by selecting vertices of the coset diagram in a special manner. A useful transformation involving Fibonacci sequence is also used in selecting the vertices of the coset diagram. Finally, all the analyses to examine the security strength are performed. The outcomes of the analyses are encouraging and show that the generated S-box is highly secure.

Rapeseed cleaning loss is an important factor to weigh rapeseed combine harvester performance. With the development of sensor technology, establishing a rapeseed cleaning loss monitoring system can be interesting and necessary. However, the rapeseed combine harvester made in China is always with larger vibration, which is not beneficial for sensor monitoring accuracy. Experiment results indicate that inertia force from vibrating sieve unbalanced motion has the greatest influence on the monitoring accuracy of the sensor in its installation position. To reduce the effect of vibration on monitoring accuracy of the sensor, the vibration absorption and isolation structure for cleaning loss sensor has been designed. Moreover, the vibration isolation design was performed on the basis of vibration suppression. The vibration isolation rubber was designed to isolate the vibration at the joint of the sensor with the frame. The experimental results shown that the above design can reduce the vibration disturbance and highlight the grain collision signal greatly, which is beneficial for improving the sensor discrimination ability.

The dental plaque is an oral microbiome hardly associated to be the etiological agent of dental caries and periodontal disease which are still considered serious health public problems. Silver nanoparticles (AgNPs) have demonstrated to have good antimicrobial properties affecting a wide variety of microorganisms, including oral bacteria; however, there is no scientific information that has evaluated the antimicrobial effect of AgNPs against clinical oral biofilms associated with dental caries and periodontal disease. The aim of this study was to determine the antimicrobial and substantivity effects of AgNPs in oral biofilms isolated clinically from patients with dental caries and periodontal disease. Sixty-seven young and young-adult subjects with dental caries and periodontal disease were clinically sampled through the collection of subgingival dental plaque. The inhibitory effect of AgNPs was performed with standard microbiological assays by triplicate using two sizes of particle. Polymerase chain reaction (PCR) assay was used to identify the presence of specific bacterial species. All AgNPs showed an inhibitory effect for all oral biofilms for any age and, generally, any gender (p>0.05); however, the effectiveness of the antimicrobial and substantivity effects was related to particle size, time, and gender (p<0.05). The identified microorganisms wereS. mutans,S. sobrinus,S. sanguinis,S. gordonii,S. oralis,P. gingivalis,T. forsythia, andP. intermedia. The AgNPs could be considered as a potential antimicrobial agent for the control and prevention of dental caries and periodontal disease.

This paper is an expansion of our previous work on the synthesis of graphene oxides and reduced graphene oxides from different kinds of oil palm waste-based feedstocks, namely, OPL (oil palm leaf), PKS (palm kernel shell), and EFB (empty fruit bunch). Here, the electrochemical measurements of the resulting reduced graphene oxides derived via mild-temperature annealing reduction of the graphene oxides were accomplished using cyclic voltammetry and galvanostatic charge/discharge processes. The findings put forward their promising features for supercapacitor applications. For instance, the reduced graphene oxide derived using EFB precursor (rGOEFB) which has a BET surface area of 117 m2 g-1 exhibits a specific capacitance of 688 F g−1 at an applied current density of 0.8 A g-1. This is higher than that observed for reduced graphene oxides derived from oil palm leaf (rGOOPL), palm kernel shell (rGOPKS), and the commercially acquired graphite (rGOCG), which possessed specific capacitance values of 632, 424, and 220 F g−1, respectively. It can be deduced that the specific capacitance of the reduced graphene oxide samples increases in the following order: (rGOCG)

To overcome huge resource consumption of neural networks training, MLaaS (Machine Learning as a Service) has become an irresistible trend, just like SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service) have been. But it comes with some security issues of untrustworthy third-party services. Especially machine learning providers may deploy trojan backdoors in provided models for the pursuit of extra profit or other illegal purposes. Against the redundant nodes-based trojaning attack on neural networks, we proposed a novel detecting method, which only requires the untrusted model to be tested and a small batch of legitimate dataset. By comparing different processes of neural networks training, we found that the embedding of malicious nodes will make their parameter configuration abnormal. Moreover, by analysing the cost distribution of test dataset on network nodes, we successfully detect the trojaned nodes in the neural networks. As far as we know, the research on the defence against trojaning attack on neural networks is still in its infancy, and our research may shed light on the security of MLaaS in real-life scenarios.

Digestive diseases are one of the common broiler diseases that significantly affect production and animal welfare in broiler breeding. Droppings examination and observation are the most precise techniques to detect the occurrence of digestive disease infections in birds. This study proposes an automated broiler digestive disease detector based on a deep Convolutional Neural Network model to classify fine-grained abnormal broiler droppings images as normal and abnormal (shape, color, water content, and shape&water). Droppings images were collected from 10,000 25-35-day-old Ross broiler birds reared in multilayer cages with automatic droppings conveyor belts. For comparative purposes, Faster R-CNN and YOLO-V3 deep Convolutional Neural Networks were developed. The performance of YOLO-V3 was improved by optimizing the anchor box. Faster R-CNN achieved 99.1% recall and 93.3% mean average precision, while YOLO-V3 achieved 88.7% recall and 84.3% mean average precision on the testing data set. The proposed detector can provide technical support for the detection of digestive diseases in broiler production by automatically and nonintrusively recognizing and classifying chicken droppings.

In this study, a novel spray drying-assisted self-assembly (SDAS) technology was proposed to prepare submicron elemental explosives with good morphology, uniform dispersion, and low sensitivity and spherical submicron RDX, HMX, and CL-20 particles without soft agglomeration were fabricated via such a method. Structural characterizations and thermal stability of the composites were systematically studied by scanning electron microscopy (SEM), X-ray diffraction (XRD), and differential scanning calorimeter (DSC). Moreover, safety performance was analyzed by qualitative testing of impact sensitivity and friction sensitivity. The XRD analysis demonstrated that HMX and CL-20 refined by SDAS maintained the crystal structure of β-HMX and ε-CL-20 before and after refinement, whereas the HMX crystal structure after spray recrystallization refinement was transformed from β-HMX to α-HMX. The DSC results indicated that the thermal decomposition peak temperature of the three particles refined by the SDAS technology had a minimum advancement, and the thermal stability of the particles was relatively superior. More importantly, the H50 of the RDX, HMX, and CL-20 refined by this novel method was increased to 48.3 cm, 44.6 cm, and 31.1 cm, and the probability of friction explosion was decreased to 62%, 62%, and 80%, respectively, thus significantly improving the safety performance as compared with the sample refined by spray recrystallization.

The monitoring of chemical and antibiotic residues like amoxicillin, penicillin, tetracycline, and vancomycin in the food originating from the animal and plant sources can prevent the humans from getting exposed to the antibiotic-induced allergic reactions and also decreased immunity towards the microbial population. By taking into consideration the necessity of developing effective and sensitive techniques for milk containing Penicillin G antibiotics in an easy and cost-effective mode, the present work deals with the electrochemical sensor made up of nickel nanoparticles (NiNPs). In order to enhance the chemical stability and biocompatibility, the NiNPs were crosslinked with (3-aminopropyl)triethoxysilane (APTES) and the formed composite was thoroughly characterized using the physical characterization techniques. In addition, the qualitative analysis results confirmed the nanocomposite’s synergetic effect towards the oxidation of Penicillin G. Further, the quantitative analysis towards the use of a nanocomposite electrode due to the changes in pH, scan rate, accumulation time and potential, nanoparticle (NP) amount, etc. was optimized. The limit of detection and limit of quantitation of Penicillin G with this composite were detected to be 0.00031 μM and 0.00100 μM, respectively. Overall, from the results, it can be indicated that the fabricated NiNP sensor can find its applications as a potential electrode material for the qualitative and quantitative analysis of Penicillin G in liquid samples.

Hilly areas necessitate a field road vehicle with high automation to reduce the amount of labor required to transport agricultural products and to increase productivity. In this paper, an adaptive integrated navigation method (combining global navigation satellite system (GNSS) and inertial navigation system (INS)) and path tracking control strategy of field road vehicles are studied in view of the problems of frequent GNSS outages and high automatic control precision requirement in hilly areas. An indirect Kalman filter (KF) is designed for the GNSS/INS information fusion. A modified method for calculating the KF adaptive factor is proposed to effectively suppress the divergence of the KF and a threshold judgement method to abandon the abnormal GNSS measurement is proposed to deal with GNSS interruptions. To achieve automated driving, a five-layer fuzzy neural network controller, which takes the lateral deviation, heading deviation, and path curvature as input and the steering angle as output, is proposed to control vehicle autonomous tracking of the navigation trajectory accurately. The proposed system was evaluated through simulation and experimental tests on a field road. The simulation results showed that the adjusted KF fusion algorithm can effectively reduce the deviation of a single GNSS measurement and improve the overall accuracy. The test results showed the maximum deviation of the actual travel trajectory from the expected trajectory of the vehicle in the horizontal direction was 12.2 cm and the average deviation was 5.3 cm. During GNSS outages due to obstacles, the maximum deviation in the horizontal direction was 12.7 cm and the average deviation was 6.1 cm. The results show that the designed GNSS/INS integrated navigation system and trajectory tracking control strategy can control a vehicle automatically while driving along a field road in a hilly area.

Vehicular Ad-Hoc Networks (VANETs) aim at enhancing road safety and providing a comfortable driving environment by delivering early warning and infotainment messages to the drivers. Jamming attacks, however, pose a significant threat to their performance. In this paper, we propose a novel Relative Speed Estimation Algorithm (RSEA) of a moving interfering vehicle that approaches a Transmitter ($Tx$) - Receiver ($Rx$) pair, that interferes with their Radio Frequency (RF) communication by conducting a Denial of Service (DoS) attack. Our scheme is completely sensorless and passive and uses a pilot-based received signal without hardware or computational cost in order to, firstly, estimate the combined channel between the transmitter - receiver and jammer - receiver and secondly, to estimate the jamming signal and the relative speed between the jammer - receiver using the RF Doppler shift. Moreover, the relative speed metric exploits the Angle of Projection (AOP) of the speed vector of the jammer in the axis of its motion in order to form a two-dimensional representation of the geographical area. This approach can effectively be applied both for a jamming signal completely unknown to the receiver and for a jamming signal partly known to the receiver. Our speed estimator method is proven to have quite accurate performance, with a Mean Absolute Error (MAE) value of approximately $10\%$ compared to the optimal zero MAE value under different jamming attack scenarios., Comment: 13 pages, 7 figures

Intrusion detection and prevention system detects malicious activities that occur in the real-time SCADA systems. This system has a problem without a profound solution. The challenge of the existing intrusion detection is accuracy in the process of detecting the anomalies. In SCADA, wind turbine data are modified by the intruders and forged details are given to the server. To overcome this, the biased intrusion detection system is used for detecting the intrusion with encrypted date, time, and file location with less false-positive and false-negative rates and thereby preventing the SCADA system from further intrusion. It is done in three phases. First, Modified Grey Wolf Optimization (MGWO) is used to extract the features needed for classification and to find the best weight. Second, Entropy-based Extreme Learning Machine (EELM) is used to extort the features and detect the intruded data with its intruded time, file location, and date. Finally, the data are encrypted using the Hybrid Elliptical Curve Cryptography (HECC) to prevent further attack. Experimental results show better accuracy in both detection as well as prevention.

Attackers upload webshell into a web server to achieve the purpose of stealing data, launching a DDoS attack, modifying files with malicious intentions, etc. Once these objects are accomplished, it will bring huge losses to website managers. With the gradual development of encryption and confusion technology, the most common detection approach using taint analysis and feature matching might become less useful. Instead of applying source file codes, POST contents, or all received traffic, this paper demonstrated an intelligent and efficient framework that employs precise sessions derived from the web logs to detect webshell communication. Features were extracted from the raw sequence data in web logs while a statistical method based on time interval was proposed to identify sessions specifically. Besides, the paper leveraged long short-term memory and hidden Markov model to constitute the framework, respectively. Finally, the framework was evaluated with real data. The experiment shows that the LSTM-based model can achieve a higher accuracy rate of 95.97% with a recall rate of 96.15%, which has a much better performance than the HMM-based model. Moreover, the experiment demonstrated the high efficiency of the proposed approach in terms of the quick detection without source code, especially when it only considers detecting for a period of time, as it takes 98.5% less time than the cited related approach to get the result. As long as the webshell behavior is detected, we can pinpoint the anomaly session and utilize the statistical method to find the webshell file accurately.

Scaffolds have been used as extracellular matrix analogs to promote cell migration, cell attachment, and cell proliferation. The use of aerogels and carbon-based nanomaterials has recently been proposed for tissue engineering due to their properties. The aim of this study is to develop a highly porous collagen-alginate(-graphene oxide) aerogel-based scaffold. The GO synthesis was performed by Hummers method; a collagen-alginate and collagen-alginate-GO hydrogel were synthetized; then, they were treated by a supercritical drying process. The aerogels obtained were evaluated by SEM and FTIR. Osteoblasts were seeded over the scaffolds and evaluated by SEM. According to the characterization, the aerogels showed a highly porous interconnected network covered by a nonporous external wall. According to the FTIR, the chemical functional groups of collagen and GO were maintained after the supercritical process. The SEM images after cell culture showed that a collagen-alginate scaffold promotes cell attachment and proliferation. The alginate-collagen aerogel-based scaffold could be a platform for tissue engineering since it shows adequate properties. Further studies are needed to determine the cell interactions with GO.

ACORN v3 is a lightweight authenticated encryption cipher, which was selected as one of the seven finalists of CAESAR competition in March 2018. It is intended for lightweight applications (resource-constrained environments). By using the technique numeric mapping proposed at CRYPTO 2017, an efficient algorithm for algebraic degree estimation of ACORN v3 is proposed. As a result, new distinguishing attacks on 647, 649, 670, 704, and 721 initialization rounds of ACORN v3 are obtained, respectively. So far, as we know, all of our distinguishing attacks on ACORN v3 are the best. The effectiveness and accuracy of our algorithm is confirmed by the experimental results.

D-S evidence theory is widely used in data fusion. However, the result of Dempster’s combination rule is not efficient and in highly conflicting situation. Though the existing methods have been proved efficient to deal with conflict in some applications, the indirect conflict among evidence is neglected to some degree. To solve this problem, a new method is proposed based on decision-making trial and evaluation laboratory (DEMATEL) and the belief correlation coefficient in this paper. The application in target recognition illustrates the efficiency of the proposed method. Compared with Dempster’s rule, averaging method and weighted averaging method, etc., the results obtained by the proposed method have better performance. The main reason is that the indirect conflict is well addressed in the proposed method.

A novel, efficient, and accurate method to detect gear defects under a complex background during industrial gear production is proposed in this study. Firstly, we first analyzed image filtering and smoothing techniques, which we used as a basis to develop a complex background-weakening algorithm for detecting the microdefects of gears. Subsequently, we discussed the types and characteristics of gear manufacturing defects. Under the complex background of image acquisition, a new model S-YOLO is proposed for online detection of gear defects, and it was validated on our experimental platform for online gear defect detection under a complex background. Results show that S-YOLO has better recognition of microdefects under a complex background than the YOLOv3 target recognition network. The proposed algorithm has good robustness as well. Code and data have been made available.

The efficiency of nanoparticles covered with type A gel and loaded with KH2PO4, as a source of P, was evaluated on growth, phosphorus concentration and accumulation, and photosynthesis-related parameters in rice plants (Oryza sativa L. ssp. indica) cv. Morelos A-2010, under greenhouse conditions. Plants were treated for 14 days with P concentrations equivalent to 50 and 100% of those established in the Yoshida nutrient solution. Sources of P were KH2PO4, nano-KH2PO4, and nano-KH2PO4 with trypsin; control treatments were distilled water and nanoparticles with type A gel. The solutions were renewed every 7 d. Rice plants exhibited differential P absorption in function of the P source tested. P supplied by KH2PO4 had a higher uptake rate than P supplied by nano-KH2PO4, alone or with trypsin. Nevertheless, nano-KH2PO4 promoted higher physiological efficiency for P in both roots and shoots, which consequently induced higher biomass accumulation in these organs. P concentration in shoots, as well as P accumulation in shoots and roots, were positively correlated with the photosynthetic rate. Also, nano-KH2PO4 increased instant water use efficiency in rice plants.

Real-time kinematic (RTK) technique is important for mapping applications requiring short measure time, the distance between rover and base station, and high accuracy. There are several RTK methods used today such as the traditional RTK, long base RTK (LBRTK), network RTK (NRTK), and precise point positioning RTK (PPP-RTK). NRTK and LBRTK are popular with the advantage of the distance, the time, and accuracy. In the present study, the NRTK and LBRTK measurements were compared in terms of accuracy and distance in a test network with 6 sites that was established between 5 and 60 km. Repetitive NRTK and LBRTK measurements were performed on 6 different days in 2015-2017-2018 and additionally 4 campaigns of repetitive static measurements were carried out in this test network. The results of NRTK and LBRTK methods were examined and compared with all relevant aspects by considering the results of the static measurements as real coordinates. The study results showed that the LBRTK and NRTK methods yielded similar results at base lengths up to 40 km with the differences less than 3 cm horizontally and 4 cm vertically.

Using downhole annular electromagnetic flow measurement to obtain annular flow in real-time is a foundation of microflow control drilling technology. The existing annular flow electromagnetic measurement method based on low-frequency rectangular excitation is affected by slurry interference and formation fluid invasion, which results in large noise generated on the electrode output signal. These noise causes the instability of the flow measurement system output and lower accuracy. Double-frequency rectangular wave excitation has the advantages of excellent zero-point stability attributed to low-frequency rectangular wave excitation and fast response speed with great ability to suppress slurry interference. First, the double-frequency rectangular wave excitation for annular flow electromagnetic measurement is researched, and its corresponding electromagnetic induction signal process is investigated. In order to verify the feasibility of downhole annular electromagnetic flow measurement, a flow verification platform for comparison of standard and detected parameters is established for simulation experiment, and the ability to suppress slurry interference and response speed of the technology in downhole slurry flow measurement are analyzed. The test results show that the downhole annular electromagnetic flow measurement based on double-frequency rectangular wave excitation can not only satisfy the requirements of regular electromagnetic flow measurement but also suppress the annular slurry interference effectively.

This study was performed to investigate the biocompatibility (BC), magnetothermal effect, and DNA binding biological characteristics of manganese zinc ferrite nanoparticles (Mn0.6Zn0.4Fe2O4-NPs (MZF-NPs)) coated with pegylated manganese (PEG-MZF-NPs). Their functions as gene transfer carrier for gene therapy and magnetic medium for tumor hyperthermia were also explored. The manganese zinc ferrite nanoparticles were synthesized through high temperature cracking, and their characterizations were discovered. Hemolysis test and MTT assay were performed to evaluate biocompatibility, and their self-heating effects in the alternating magnetic field were investigated. PEG-MZF-NPs with different concentrations were measured by using 7.0 T Micro-MR scanner (MRI) to calculate the T2 value and r2 relaxation rate of each sample. The CD44-shRNA plasmids were constructed, and their ability to bind PEG-MZF-NPs were examined. The DNA release from PEG-MZF-NP/DNA complex and protection of DNA from nuclease digestion were also detected. After CD44-shRNA-EGFP were transfected into the ovarian cancer SK-OV-3 cells by using PEG-MZF-NPs as carriers, the transfection efficiency was detected by a flow cytometer and expression of CD44 mRNA and protein in cells was detected using RT-PCR and Western blot, respectively. We successfully prepared PEG-MZF-NPs with favorable dispersity, magnetic responsiveness, and BC. Typically, the excellent magnetothermal effect can be used for a tumor magnetothermal therapeutic study. In vitro MRI showed the application potential for being magnetic resonance T2 relaxation contrast agents and the possibility to achieve goal of integration of targeting diagnosis and treatment. The CD44-shRNA plasmids have been successfully constructed and concluded that PEG-MZF-NPs may serve as gene transfer carriers for gene therapy.

Zinc oxide nanoparticles (ZnO) have long been utilized as UV-protective sunscreen components due to their high durability and lower skin irritation while maintaining capability for blocking UV rays. However, the dispersal and transparency properties of ZnO need to be enhanced in order to improve the capacity for creating effective sunscreen through control of the physiochemical properties of ZnO. In this study, chitosan or niacinamide, which are suitable functional cosmetic compounds and effective skin lightening agents, are combined with ZnO for the development of better UV-protective products. Each biocompatible coating material is individually attached on its surface after the synthesis of ZnO. The size is 70 nm using the sol-gel method. Their morphology and chemical structure are characterized by FT-IR, XRD, SEM, TEM, TGA, and zeta potential. The results indicate that approximately 50% of chitosan and 5% niacinamide were coated on the ZnO. To confirm the capacity of each surface-coated ZnO with chitosan and niacinamide as a sunscreen, we measured their transmission, reflectance, and sun protection factor (SPF) using a UV spectrophotometer and SPF. As a result, the niacinamide-coated ZnO shows remarkably lower transmission and high reflectance against UV rays than that of bare ZnO and chitosan-coated ZnO. Furthermore, niacinamide-coated ZnO exhibits great lightening effects. Consequently, these results demonstrate that niacinamide coating is highly effective for the production of sunscreen emulsions.

The physical layer security of downlink nonorthogonal multiple access (NOMA) network is analyzed. In order to improve the secrecy probability, friendly jammers are jointed in the NOMA network. Two jammer schemes are proposed in the NOMA network. All the jammers transmit jamming signal without jammer selection in the first scheme (NO JS scheme). Jammers are selected to transmit jamming signal if their interfering power on scheduled users is below a threshold in the second scheme (JS scheme). A stochastic geometry approach is applied to analyze the outage probability and the secrecy probability. Compared with the NO JS scheme and traditional scheme (without jointing jammers), the jammer selection scheme provides a good balance between the user outage probability and secrecy probability. Numerical results demonstrate that the security performance of the two proposed schemes can be improved by jointing the jammers in the NOMA wireless network.

A simple two-step method of growing ZnO nanorod arrays on the surface of BiOI nanosheets was developed under mild environment. The hierarchical structure of ZnO arrays@BiOI nanosheets was characterized by various measurements like X-ray powder diffraction, scanning electron microscopy, transmission electron microscopy, and energy-dispersive X-ray detector. The optical absorption of the ZnO arrays@BiOI nanosheets composite was investigated by UV-Vis diffuse reflectance spectra. The photocatalytic degradation of methanol orange under visible light shows that the obtained ZnO arrays@BiOI nanosheets heterostructures exhibit enhanced photocatalytic activity, contrasting to the sum of BiOI nanosheets and ZnO nanorods. The mechanism of the photocatalytic process was discussed. This method of growing ZnO nanorod arrays on other nanosheets also provides a potential method to fabricating other complex structures.

[EN] Pharmacological agents are often used to induce labor. Failed inductions are associated with unnecessarily long waits and greater maternal-fetal risks, as well as higher costs. No reliable models are currently able to predict the induction outcome from common obstetric data (area under the ROC curve (AUC) between 0.6 and 0.7). The aim of this study was to design an early success-predictor system by extracting temporal, spectral, and complexity parameters from the uterine electromyogram (electrohysterogram (EHG)). Different types of feature sets were used to design and train artificial neural networks: Set_1: obstetrical features, Set_2: EHG features, and Set_3: EHG+obstetrical features. Predictor systems were built to classify three scenarios: (1) induced women who reached active phase of labor (APL) vs. women who did not achieve APL (non-APL), (2) APL and vaginal delivery vs. APL and cesarean section delivery, and (3) vaginal vs. cesarean delivery. For Scenario 3, we also proposed 2-step predictor systems consisting of the cascading predictor systems from Scenarios 1 and 2. EHG features outperformed traditional obstetrical features in all the scenarios. Little improvement was obtained by combining them (Set_3). The results show that the EHG can potentially be used to predict successful labor induction and outperforms the traditional obstetric features. Clinical use of this prediction system would help to improve maternal-fetal well-being and optimize hospital resources., This work received financial support from the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (DPI2015-68397-R and RTI2018-094449-A-I00), Universitat Politècnica de València VLC/Campus (UPV-FE-2018-B02), Generalitat Valenciana (GV/2018/104), and Bial S.A.

Simulated moving bed (SMB) chromatographic separation technology is a new adsorption separation technology with strong separation ability. Based on the principle of the adaptive neural fuzzy inference system (ANFIS), a soft sensing modeling method was proposed for realizing the prediction of the purity of the extract and raffinate components in the SMB chromatographic separation process. The input data space of the established soft sensor model is divided, and the premise parameters are determined by utilizing the meshing partition method, subtractive clustering algorithm, and fuzzy C-means (FCM) clustering algorithm. The gradient, Kalman, Kaczmarz, and PseudoInv algorithms were used to optimize the conclusion parameters of ANFIS soft sensor models so as to predict the purity of the extract and raffinate components in the SMB chromatographic separation process. The simulation results indicate that the proposed ANFIS soft sensor models can effectively predict the key economic and technical indicators of the SMB chromatographic separation process.

In the study, ultrasonic longitudinal mode guided waves were employed to detect defects in elbowed tubes (without welds) with a diameter of 10 mm. Finite element simulation results highlighted that the emitted L(0,1) mode guided waves experienced strong reflection and mode conversion at the elbow region to generate F(1,1) mode, followed by slow and weak F(2,1) mode. The guided wave reflected from the elbow with a through-wall defect was manifested as two overlapped wave packets, which were good indicators of a defective elbow. To conduct L(0,1) mode guided waves inspection on the small-diameter elbowed tubes, a novel tailored squirrel-cage magnetostrictive sensor was employed in the experiment. The new sensor employed the configuration of segmental iron-cobalt strips and small-size permanent magnet arrays. The entire sensor is composed of two identical C-shaped sensor elements and can be recycled and installed conveniently. Experimental results obtained from healthy and defective tubes were consistent with the conclusions obtained from finite element simulations. An artificial through-wall defect at the elbow and a notch defect at the straight part of the tube could be simultaneously detected by L(0,1) mode guided waves through comparing experimental signals with simulation results.

There are a large number of insulators on the transmission line, and insulator damage will have a major impact on power supply security. Image-based segmentation of the insulators in the power transmission lines is a premise and also a critical task for power line inspection. In this paper, a modified conditional generative adversarial network for insulator pixel-level segmentation is proposed. The generator is reconstructed by encoder-decoder layers with asymmetric convolution kernel which can simplify the network complexity and extract more kinds of feature information. The discriminator is composed of a fully convolutional network based on patchGAN and learns the loss to train the generator. It is verified in experiments that the proposed method has better performances on mIoU and computational efficiency than Pix2pix, SegNet, and other state-of-the-art networks.

The recent years have witnessed a growth in the number of users connected to computer networks, due mainly to megatrends such as Internet of Things (IoT), Industry 4.0, and Smart Grids. Simultaneously, service providers started offering vertical services related to a specific business case (e.g., automotive, banking, and e-health) requiring more and more scalability and flexibility for the infrastructures and their management. NFV and SDN technologies are a clear way forward to address these challenges even though they are still in their early stages. Security plays a central role in this scenario, mainly because it must follow the rapid evolution of computer networks and the growing number of devices. The main issue is to protect the end-user from the increasing threats, and for this reason, we propose in this paper a security framework compliant to the Security-as-a-Service paradigm. In order to implement this framework, we leverage NFV and SDN technologies, using a user-centered approach. This allows to customize the security service starting from user preferences. Another goal of our work is to highlight the main relevant challenges encountered in the design and implementation of our solution. In particular, we demonstrate how significant is to choose an efficient way to configure the Virtual Network Security Functions in terms of performance. Furthermore, we also address the nontrivial problem of Service Function Chaining in an NFV MANO platform and we show what are the main challenges with respect to this problem.