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To ensure resistance to attacks with coercion to disclose a secret key by an active adversary, the protocol of deniable encryption includes a procedure for mutual authentication of the sender and receiver of a message with their long-term public keys, which is combined with a hidden exchange of single-use public keys used to generate a single-use shared key, on which the secret message is encrypted. Longterm public keys are used to generate a shared secret key, on which a fake message is encrypted. The produced intermediate ciphertexts are converted into a single ciphertext, which is computationally indistinguishable from the ciphertext obtained by probabilistic encryption of a fake message. This approach allows us to build an encryption protocol that is resistant to bi-sided attacks with coercion, since the disclosure of users' private keys gives access only to the fake message and cannot be used to prove the possibility of alternative decryption of the ciphertext transmitted over a public communication channel. The authentication of the single-use public keys is also used to implement protocols for secure encryption using short shared keys.

Bus Rapid Transit (BRT) is a concept born in the 1970s and developed successfully in many developing countries because of its advantages (e.g., lower required investment, more flexibility, faster establishment, and much larger capacity) over traditional bus services. However, the first BRT system in Hanoi (Vietnam), which runs between the Kim Ma terminal and the Yen Nghia terminal, is flawed evidence with a daily ridership at approximately 13,500 passengers. This patronage is only comparable with that of the conventional bus route. This study aimed to find underlying factors determining the service quality to propose policy implications for improving the Hanoi BRT. The data used were the responses of 243 BRT passengers gathered in a customer satisfaction survey conducted in March 2017. The method was an adapted version of the well-known SERVQUAL model with the use of Exploratory Factor Analysis. As regards the findings, the four factors found were Quickness and Timeliness (beta = 0.278), Safety and Reliability (beta = 0.249), Access (beta = 0.217), and Comfort (beta = 0.188). They explained 62.5% of the variance of passengers' satisfaction. Among the eight policy solutions proposed to enhance the four factors mentioned above, the three most important and feasible ones were the implementations of the prioritized traffic signal for BRT, busway enforcement, and automatic pre-board ticket collection.

Walking plays an essential role in both daily mobility and human health. Unfortunately, measuring walking behavior in self-reported surveys is usually subject to lack of accuracy due to the limit of human memory, the habit of not only rounding travel time but also neglecting short and unimportant trip legs. To cope with such a problem, the use of the Global Positioning System (GPS) is promising. This study aimed at developing an inference model to derive travel modes from 406-day GPS data of 90 respondents living in Lyon city and its suburbs (France). Based on mode detection results, aspects of walking (i.e., purposes, length, duration, speed, the relation between walking and home, the relation between walking and other modes) were estimated. For detecting modes well, particularly walking, a fuzzy logic-based algorithm using average speed, the 95th percentile of speed, and the 95th percentile of acceleration were created. Rules of signal loss were proposed to identify metro segments, while respondents’ reports on the frequency of cycling were utilized to address the confusion between walking and cycling better. As for findings, 951 walking stages were found. Because all of the walking patterns, estimated from prediction results of travel modes, were compatible with previous studies’ findings, the mode detection method adopted in this study has performed satisfactorily, particularly concerning imputing walking. The proposed method may enable better use of GPS to conduct further analyses of walking behaviors thanks to deriving walking segments adequately from spatio-temporal data.

Creation of an effective bus rapid transit (BRT) system has never been an easy task, especially for the first case in a developing country, since a BRT project requires a considerable investment with participation from most walks of life. Hanoi, the capital of Vietnam, has omitted to overcome impediments in the maiden BRT establishment. The Hanoi BRT performs poorly with ridership at only 13,500 passengers per day. In this paper, it is scrutinized based on a series of barriers that are findings in previous works and in the shape of a theoretical framework with seven main categories, namely: (1) institutional and legislative context, (2) political leadership and commitment, (3) physical design and operation, (4) management of competing modes, (5) adequate funding, (6) public participation and (7) image promotion. Results emphasize that the difference in views of the funder and the local authorities on the BRT development is the chief barrier. Enforcement of the BRT lanes from motorcycles is demanding, which is distinct from cities previously creating BRT. The findings from the Hanoi BRT are not unique. Lessons drawn from its failure could be widely informative for the BRT establishment in a number of cities with similar contexts.

Small and uniform bimetallic WMoSx nanoparticles well distributed on surface of thin graphene nanosheets (WMoSx-Gr) was prepared and investigated as an effective electrocatalysts for oxygen reduction reaction (ORR) in alkaline electrolyte. This material exhibited highly catalytic activity relative to a commercial Pt/C product. In this context, the material showed a large limit current density, positive onset potential (−0.05 V) as well as half wave potential (−0.13 V). In particularly, the superior durability and methanol tolerance of the as-synthesized material were also pronounced, as compared to Pt/C. The high ORR activity of the WMoSx-Gr material was assumed to the synergistic effect produced from a unique nanostructure of the WMoSx and the high surface area graphene with its excellent conductivity. The obtained results imply that such hybrid material can open a new type of highly efficient non-Pt catalyst for ORR in alkaline environment.

Objectives This study examined recreational cycling in Hanoi, Vietnam, with a particular focus on changes brought about by the Covid-19 pandemic. The research questions were: (1) Has recreational cycling increased during the Covid-19 pandemic?; (2) If so, what factors have led to the increase?; and (3) What are some of the typical traits and behaviors of recreational cyclists? Method Face-to-face surveys of 356 recreational cyclists were carried out in March–April 2021 in four areas of inner Hanoi. The survey data were modelled through two binary and one ordinal logit regression. Results Recreational cycling has become much more popular in Hanoi during the Covid-19 pandemic, with early morning being the preferred time for this activity (to avoid heavy traffic). A quarter of the participants had starting cycling recreationally since the first lockdown in April 2020, and about three quarters reported having noticed an increase in cycling activity around them. Nearly half of the participants cycled regularly (more than four times per week). The groups that were most likely to have taken up cycling for recreations during the pandemic included men, those living with children in the home, and those not working or studying. Age and income were not significant. People have been embracing cycling as a way to maintain or increase physical activity levels, and to safely socialize at the time when social gatherings are limited, walking is prohibited in some zones, and social distancing rules apply everywhere. Conclusion To sustain the growth in recreational cycling and widen the time-window for this activity while ensuring everyone's safety, Hanoi's planning and public health sectors should join forces to adopt a combination of ‘hard’ and ‘soft’ measures. The authors recommend creating multi-use paths for micromobility modes, launching a public bikesharing scheme, regulating motorised modes, and social marketing that promotes recreational cycling as trendy.

In this paper, we propose two new blind digital signature protocols based on the difficulty of the discrete logarithm problem (DLP) modulo a composite number n = p · q. These are the first protocols of such type that are based on the computational difficulty of the DLP modulo a composite number. The use of the last difficult problem provides increased security of the signature protocols due to reducing the probability of the potential breaking the protocols, which is connected with potential appearance of the breakthrough solutions of the following two computationally difficult problems: (1) finding discrete logarithm modulo prime and (2) factoring composite number n containing two unknown prime divisors. The designed protocols are based on using finite groups possessing two-dimensional cyclicity. When selecting parameters providing 80-bit security, the signature size in the proposed blind protocols is equal to 240 bits.

Change detection between as-planned building information modeling (BIM) and the as-is point cloud requires significant computational overhead because it must deal with every geometric face in the BIM and every point in the point cloud one-to-one. To address this problem, this study presents a high-performance algorithm to detect discrepancies between an as-planned BIM and the as-is point cloud automatically. This method is a data structure approach based on modifiable nested octree indexing of surface meshes and point clouds. The results of experiments showed a significant computation performance improvement: 25.3 and 12.1 times faster than the baseline method for a complex plant facility and a simple indoor building, respectively. Furthermore, it was demonstrated that as the number of meshes in the BIM geometry increased, the time complexity of the proposed approach could be represented as a big O-notation,O(logN), where N is the number of meshes in the BIM geometry.

This is among the first studies to provide empirical evidence on active school travel rates and determinants before and after the first Covid-19 lockdown in spring 2020. We have collected and analyzed primary survey data on the school travel patterns of 472 school-age children in Hanoi, Vietnam. The findings show that the Covid-19 pandemic has been quite detrimental: once schools reopened, the prevalence of active school travel decreased from 53% to less than 31%. Where parents, especially mothers, did not face barriers to motorized travel, they assumed the role of chauffeur. Parents who were more concerned about community infections were more motivated to shift children to motorized modes. Walking was more affected than cycling because it was seen as more likely to lead to physical contact and virus transmission. Active school travel dropped more steeply in urban districts (as opposed to poorer, non-urban districts) and in those areas where home-school distances were the largest. It appears that the most common perceptions around barriers to active school travel have been exacerbated during the pandemic as parents and children adapt to “the new normal”.

Transportation mode detection is one of the major challenges in GPS-based travel surveys. This study presents attempts to impute modes from data collected by smartphone in Hanoi (Vietnam), where the dominant mode is the motorcycle. The inclusion of the motorcycle mode and an imbalance in the modal share of the Hanoi data resulted in the ineffective use of supervised-learning models to detect all modes simultaneously. To gain a high level of accuracy and reasonable interpretability, a hierarchical process was developed. At first, walk, bicycle, and motorized modes were identified by a fuzzy logic-based algorithm. Subsequently, based on the distribution of bus stops and the operation of buses in practice, rules using the average distance between stops that a vehicle passed slowly or stopped at were introduced to detect bus segments. Finally, a random forest model was built to distinguish the modes of motorcycle and car. The proposed hierarchical process achieved an accuracy level of 89.1%. The bus detection, which required coordinates of bus stops solely, achieved a recall of 87.2%. The mode of motorcycle was the main source of misclassification. Including the motorcycle mode has contributed to the diversity of the mode detection field, which has previously focused on walk, bicycle, car, bus/tram, and train. The hierarchy was developed and validated by using a dataset that did not include travel by metro or train and would be biased toward persons working and studying at a university. These limitations emphasize the need to test the process on a more diverse sample with more travel options.

The Global Positioning System (GPS) has motivated rapid advances in mobility data collection. A massive amount of spatio-temporal information has made it possible to know where a person was and when, but not how and why (s)he travelled, creating the need for inference models. Compared with mode detection, purpose imputation has been insufficiently studied. However, the relative lack of attention to purpose identification does not mean that this field has not emerged. For this paper, which is the first review dedicated to inferring trip purposes from GPS data, 1,162 non-duplicate papers from four databases (Scopus, Web of Science, ScienceDirect and TRID) were screened, and a corpus of 25 publications was selected for examination. Based on these papers, the purpose imputation problem is defined in the contexts of the evolution of GPS-based travel surveys and two research domains, Transportation Science (TS) and Human Geography (HG). Subsequently, three steps of the purpose detection process, namely (1) trip end detection, (2) input feature selection and (3) main algorithms and validation, are surveyed. During these procedures, the differences between studies in TS and those in HG are highlighted. Finally, unresolved issues related to data and feature selection, algorithms and assessment are discussed substantially to provide potential research directions. This review may be an informative reference for those newly accessing the GPS-based purpose imputation field and/or intending to develop solutions to this problem.

The advent of Hadoop has inspired many researchers to conduct studies on big data. These studies have covered a wide range of aspects of big spatial data. However, they still face challenges in visualizing big spatial data on a distributed storage model since loading multi-resolution data is inefficient. For this reason, multi-resolution data are usually excluded from the distributed storage model to speed up the loading process. This limitation prompted the introduction of B-EagleV, a novel Hadoop-based solution that enables users to manage and visualize massive point cloud data on Hadoop Distributed File System (HDFS) without moving the multi-resolution data to a local server. This paper presents the achievements of B-EagleV in efforts to discover the values of Hadoop in visualizing massive point cloud data.

Tantalum-doped tin oxide transparent conductive thin films were deposited on glass substrates by radio frequency and direct current reactive magnetron co-sputtering methods in an argon and oxygen environment. Optimization of the thin films for photovoltaic applications was performed using a dimensionless figure of merit by combining electrical and transparency properties. The optimized thin film showed a weight-averaged transmittance of 83%, a band gap value of 3.2 eV, resistivity of 5.2 × 10−3 Ω cm, and bulk carrier concentration of 1.2 × 1020 cm−3. The lowest resistivity among all films was 2.1 × 10−3 Ω cm, corresponding to a weight-averaged transmittance of 62%. The optimized deposition condition was carried out by co-sputtering on heated substrates at 270°C. Thin films deposited under this optimized condition were applied for our perovskite solar cells, and demonstrated promising power conversion efficiency.

This paper presents a method for enhancing purpose imputation from global positioning system data without using geographic information system data via relevant feature selection from six groups: (1) activity time; (2) user characteristics; (3) predicted travel modes; (4) actual travel modes; (5) estimated home location; and (6) estimated location of the most frequently visited non-home place (MFVP). Two datasets were collected in 2019 using TRavelVU, a smartphone application. The first one (the Hanoi dataset) comprised 652 days’ worth of data collected from 63 users in Hanoi, Vietnam, whereas the second one (the Donate dataset) comprised 932 days’ worth of information collected from 65 individuals in Denmark, Sweden, and Norway. The hyperparameters of the random forest models were tuned carefully in accordance with selected features, thereby facilitating a thorough evaluation of the improvement in prediction models. The findings of this study revealed that the addition of either actual or predicted modes resulted in improved imputation performance, albeit the former exhibited a stronger positive effect. This demonstrated the potential benefits of integrating mode detection and purpose identification into a continuous process. The newly adopted MFVP feature contributed to enhanced prediction results (around 2%). The proposed purpose-imputation models, which benefited from all features, demonstrated accuracies of the order of 75% and 85% for the Hanoi and Donate datasets, respectively. The imputation of home and work/education activities demonstrated high success, whereas reasonable prediction results with nearly all F-score levels ranging between 50% and 83% were observed for pick-up/drop-off, shopping/eating, visit/leisure, and business activities.

Tin oxides nanowires were selectively grown on the working electrode of a sensor by using modified chemical vapor deposition technique with supporting shadow mask. Time and distance evolution of Sn mass transport in correlation with carrier gas pressure and flow rates in the chemical vapor deposition system was described by Comsol Multiphysics. The simulated density of SnO2 nanowires was in good agreement with that obtained by scanning electron microscope image. X-ray diffraction, high-resolution transmission electron microscopy, scanning transmission electron microscopy measurements showed that nanowire structure was tetragonal with lattice constants a = 0.474 nm and c = 0.318 nm. The nanowires were around 25 nm in diameter and 3.5 μm in length. A simple immobilization of a DNA sensor was conducted by a surface modification of tin oxide nanowire using 3-amino-propyl-tri-ethoxysilance hydroxylation in vapor phase; creating the amino functional groups to which the phosphate groups of probe ss-DNA (Epstein-Barr virus) bound. Differential voltage measurements were conducted to detect DNA hybridization. The response time was 2.5 s and the limit of detection was 3.2 pM.

Aluminum-doped zinc oxide was deposited on silicon and glass substrates by magnetron sputtering methods with various conditions starting from conventional, then to oxygen reactive technique, and finally to cosputtering of aluminum and 2% Al2O3 in ZnO target. The results showed that the optical transmittance of the thin films in the visible range was above 80%. The direct bandgap of the aluminum-doped zinc oxide thin films, depending on the deposition conditions, was estimated to lie in the range between 3.2 eV and 4.2 eV. Good electrical properties with resistivity of about 2.5 × 10−3 Ω cm were also observed when doping more Al using the cosputtering method. Optimization of the synthesis conditions for aluminum-doped zinc oxide thin films was performed using a newly proposed dimensionless figure of merit based on analysis of the efficiency of solar cells. This study highlights that the optimized deposition condition was to cosputter aluminum during a total additional time of 2 min. The results show that such transparent conductive thin films could be applied in future low-cost heterojunction oxide-based solar cells with CuFeO2 delafossite p-type absorber.

One of the interesting forms of cuprous oxide and ferric oxide based materials is CuFeO2 which can be a delafossite-type compound and is a well known p-type semiconductor. This compound makes up an interesting family of materials for technological applications. CuFeO2 thin films recently gained renewed interest for potential applications in solar cell devices especially as absorption layers. One of the interesting facts is that CuFeO2 is made from cheap materials such as copper and iron. In this study, CuFeO2 thin films are intentionally deposited on corning glass and silicon substrates by the radio-frequency and direct current sputtering method with complicated and well developed co-sputtering recipes. The deposition was performed at room temperature which leads to an amorphous phase with extremely low roughness and high density. The films also were annealed at 500°C in 5% H2 in Ar for the passivation. A detailed optical study was performed on these thin films by spectroscopic ellipsometry and by ultra-violet visible near infrared spectroscopy. Depending on sputtering conditions, the direct band gap was extrapolated to be from 1.96 eV to 2.2 eV and 2.92 eV to 2.96 eV and the indirect band gap is about 1.22 eV to 1.42 eV. A good electrical conduction is also observed which is suitable␣for solar cell applications. In future more study on the structural properties will be carried out in order to fully understand these materials.

CH3NH3PbI3 and CH3NH3PbI2Br crystal powders and thin films with chemical formula CH3NH3PbI3−x Br x have been synthesized by reacting methylammonium bromide/iodide with lead iodide. The films were fabricated by a low-temperature solution process using the spin-coating method followed by thermal annealing, which is an effective means for controlling the composition and morphology of the CH3NH3PbI3−x Br x thin films. The resulting perovskite films exhibit good optical absorption and crystalline structure, being promising for potential application as light absorbers in future solar cells.

More than 165 cities on 6 continents have implemented BRT systems. While most have been successful, some have failed—either to perform at a high level or to expand further. This chapter examines the reasons for failures, which can be as illuminating as the reasons for successes. Five case studies are included: Bangkok, Delhi, Hanoi, Lagos, and Lima. The analysis is structured according to an existing theoretical framework, which considers: (1) institutional and legislative context; (2) political leadership and commitment; (3) management of competing modes; (4) public participation; (5) funding and coordination; (6) physical design; and (7) image promotion.

Organo-lead mixed halide perovskites have been showing remarkable performance for applications in solar cells and are very promising for numerous applications in optoelectronics and nonlinear optics. In this study, we report a room-temperature photoluminescence study of this material by using pulsed excitation laser sources at 1064 nm wavelength. Under our experimental conditions, strong photoluminescence was observed only for bromine-containing perovskites, CH3NH3Pb(I1−xBrx)3, thus suggesting an important role of bromine for photoluminescence of halide perovskites. The experimental results also showed that the photoluminescence peak was blue-shifted from 727 nm to 574 nm when x increased from 1/3 to 1. In particular, the photoluminescence peak featured a third-order dependence on the laser intensity. This direct observation of three-photon absorption-induced photoluminescence of organo-lead mixed halide perovskite materials thus opens up interesting applications in the field of optoelectronics and nonlinear optics.

Skeletonization is a morphological operation that transforms an original object into a subset, which is called a ‘skeleton’. Skeletonization has been intensively studied for decades and is a challenging issue especially for special target objects. This paper proposes a novel approach to the skeletonization of text images based on stroke width detection. First, the preliminary skeleton is detected by using a Canny edge detector with a Tensor Voting framework. Second, the preliminary skeleton is smoothed, and junction points are connected by interpolation compensation. Experimental results show the validity of the proposed approach.

This paper describes the development of a DNA sensor based on polypyrrole nanowire. By using potentiostatic technique, in the presence of gelatin as the soft mold, the polypyrrole nanowires were synthesized on the surface of the micro-sensor. The surface enhanced Raman spectroscopy shows that the N H ends of the polypyrrole nanowires orientate upward from the surface facilitating the DNA probe immobilization through the simple linkage with the phosphate groups of the probe DNA. The label-free signal readout was carried out by lock-in amplifier technique. The response time of the DNA sensor is 10 s and the measurement time was 5 min. The lowest detectable concentration of Escherichia coli DNA was 0.1 nM.

Locating text data in images automatically has been a challenging task. In this approach, we build a three stage system for text detection purpose. This system utilizes tensor voting and Completed Local Binary Pattern (CLBP) to classify text and non-text regions. While tensor voting generates the text line information, which is very useful for localizing candidate text regions, the Nearest Neighbor classifier trained on discriminative features obtained by the CLBP-based operator is used to refine the results. The whole algorithm is implemented in MATLAB and applied to all images of ICDAR 2011 Robust Reading Competition data set. Experiments show the promising performance of this method.

Application developer has trend to take advantage of web as a communication medium environment to reach users because HTTP protocol is mostly allowed in any network environment nowadays. Unfortunately, cyber criminal is also fully exploit HTTP protocol to launch variety of forbidden actions such as application level attacks or spreading malware. Consequently, normal and malicious HTTP automated software (auto-ware) traffic are transparently merged with each other. Clustering and identifying between HTTP communication are raised as serious challenge in order to early investigate internal threats. In this paper, access graph and key features are suggested, based on which HTTP auto-ware communication behavior are recognized. From there, a novelty method in clustering and identifying HTTP auto-ware is presented. Experiment shows promising results since not just malicious communications are detected but also grayware traffic are clustered into groups and identified as their purposes.

Tendon is a specific connective tissue composed of parallel collagen fibers. The effect of this tissue-specific matrix orientation on stem cell differentiation has not been investigated. This study aimed to determine the effects of nanotopography on the differentiation of human tendon stem/progenitor cells (hTSPCs) and develop a biomimetic scaffold for tendon tissue engineering. The immuno-phenotype of fetal hTSPCs was identified by flow cytometry. The multipotency of hTSPCs toward osteogenesis, adipogenesis, and chondrogenesis was confirmed. Then, the hTSPCs were seeded onto aligned or randomly-oriented poly (l-lactic acid) nanofibers. Scanning electron micrographs showed that hTSPCs were spindle-shaped and well orientated on the aligned nanofibers. The expression of tendon-specific genes was significantly higher in hTSPCs growing on aligned nanofibers than those on randomly-oriented nanofibers in both normal and osteogenic media. In addition, alkaline phosphatase activity and alizarin red staining showed that the randomly-oriented fibrous scaffold induced osteogenesis, while the aligned scaffold hindered the process. Moreover, aligned cells expressed significantly higher levels of integrin alpha1, alpha5 and beta1 subunits, and myosin II B. In in vivo experiments, the aligned nanofibers induced the formation of spindle-shaped cells and tendon-like tissue. In conclusion, the aligned electrospun nanofiber structure provides an instructive microenvironment for hTSPC differentiation and may lead to the development of desirable engineered tendons.

Text in images is one of the most important cues for understanding a scene. In this paper, we propose a novel approach based on interest points to localize text in natural scene images. The main ideas of this approach are as follows: first we used interest point detection techniques, which extract the corner points of characters and center points of edge connected components, to select candidate regions. Second, these candidate regions were verified by using tensor voting, which is capable of extracting perceptual structures from noisy data. Finally, area, orientation, and aspect ratio were used to filter out non-text regions. The proposed method was tested on the ICDAR 2003 dataset and images of wine labels. The experiment results show the validity of this approach.

Since born-digital images usually have low resolution, they are distinctly different from natural scene images. Extracting text information from born-digital images has been an increasing interest in document analysis and recognition field. We propose an automatic method to recognize word from low-resolution color image. First, the image is smoothed by using the bilateral filter, which preserves edge information. Then, it is binarized using global thresholding method and cleaned from noise. Finally, the open source Optical Character Recognition engine, with the incorporation of a post-processor trained on knowledge of English language, is applied to obtain meaningful words from the binary image. We experiment the proposed system on ICDAR 2011 and music sheet dataset, and the result shows better performance than several previous works.

There are proposed collective signature, blind signature, and collective blind signature protocols based on the digital signature generation and verification procedures specified by Russian and Belarusian signature standards. The protocols are characterized in computing the randomization parameter of the collective signature depending on the collective public key. Due to this novel feature the proposed protocols provide integrity of the collective signature.

This paper studies the problem of signal-quality-guaranteed connection provisioning in all-optical networks under dynamic traffic. We first improve a model integrated with two main signal quality constraints; then propose an impairment information management framework to adaptively gathering and updating interference among lightpaths. Based on that framework, we developed two impairment-aware routing and wavelength assignment (RWA) algorithms. The network simulator OMNET++ is used to simulate the proposed approach on a typical optical network topology. Simulation results show that the proposed impairment ware RWA algorithms significantly outperform the original conventional scheme while implying a reasonable computational requirement.

This work focuses on the synthesis, functionalization, and application of gold and silver nanoparticles, magnetic nanoparticles Fe3O4, combination of 4-ATP-coated silver nanoparticles and Fe3O4 nanoparticles. The synthesis methods such as chemical reduction, seeding, coprecipitation,and inverse microemulsion will be outlined. Silica- and amino-coated nanoparticles are suitable for several applications in biomedicine and the environment. The applications of the prepared nanoparticles for early detection of breast cancer cells, basal cell carcinoma, antibacterial test, arsenic removal from water, Herpes DNA separation, CD4+ cell separation and isolation of DNA of Hepatitis virus type B (HBV) and Epstein–Barr virus (EBV) are discussed. Finally, some promising perspectives will be pointed out.