• Investigating effects of silicon nanowire and nanohole arrays on fibroblasts via AFAM

      Liu, Yan; Li, Li; Yang, Yang; Tian, Liguo; Wu, Xiaomin; Weng, Zhankun; Guo, Xudong; Lei, Zecheng; Qu, Kaige; Yan, Jin; et al. (Springer Verlag (Germany), 2020-07-30)
      Understanding the cell–substrate interactions has great significance in tissue regeneration therapies. However, the cell–substrate interactions are not well understood because the interface of cell–substrate is typically buried beneath the cells. This research investigated the subsurfaces of fibroblasts cultured on hybrid nanoarrays using atomic force acoustic microscopy (AFAM). We fabricated hybrid silicon nanowires (SiNWs) and silicon nanoholes (SiNHs) on Si substrates to serve as biomimetic nanoarrays by employing laser interference lithography and the metal-assisted chemical etching (MacEtch) method. After the L929 cells were cultured on the nanoarrays, scanning electron microscopy (SEM) and AFAM were employed to investigate the surface and subsurface of L929 cells. It was suggested that fibroblasts could sense the morphology of the hybrid nanoarrays and membrane damage of fibroblasts on the hybrid nanoarrays were related to the nanostructures. This study can help guide the design of biointerfaces and provide a useful tool for the study of cell subsurfaces in diverse biological fields.
    • Effects of alternating electric field on the imaging of DNA double-helix structure by atomic force microscope

      Wang, Ying; Ma, Ke; Wang, Jiajia; Li, Li; Liu, Ziyu; Hu, Jing; Gao, Mingyan; Wang, Zuobin (Springer, 2020-07-22)
      The effects of alternating electric field on the imaging of DNA double-helix structure were explored by atomic force microscope (AFM). First, the DNA sample was located under an alternating electric field in a fixed direction and dried. Then, AFM was used to obtain the DNA images under different alternating electric fields with the voltage range from 0.5 to 6.0 V and the frequency of 50 kHz. Thus, the DNA double-helix structures with different extensions were observed when the DNA molecules were gradually stretched under different field intensities. The distributions of DNA molecules in solution were random if there were no external forces, and the curved DNA molecules were observed in the AFM image. With the increase in alternating electric voltage (0.5–4.0 V), the DNA structure was shifted from random to oriented conformation and the DNA grooves were further unfolded. While the higher voltage (5.0–6.0 V) resulted in the rupture of DNA chains due to the excessive stretching force. It showed that the optimal voltage was 1.0 V, and the double-helix structure was observed. This method provides an efficient way for monitoring and measuring bio-macromolecules. It may also enable the exploration of the DNA–protein binding and DNA molecular self-assembly processes.
    • Quantitative imaging for early detection of osteoarthritis

      Schetinin, Vitaly; University of Bedfordshire (University of Bedfordshire, 2020-07-09)
      The project supported by European Regional Development Fund is related to Quantitative Imaging for Early Detection of Osteoarthritis. The developed method has been tested on high resolution X-Ray images of knees at early stage when the pathological changes in patient's bones cannot be reliably quantified by using the standard radiologic tests. At early stage the pathology is latently developing and so being diagnosed later becomes untreatable. The proposed method has been developed in collaboration with Fusion Radiology (UK) and with Stavropol regional hospital (Russia). The Fusion Radiology (led by Mr Azizul Ambia) is a contractor of the NHS, providing radiology opinions for multiple UK hospitals. The regional hospital (the Deputy MD Anna Sadovaya) has verified the developed method on 160 patient cases. The new method has provided a statistically significant improvement of diagnostic accuracy on the anonymised patient records. The improvements were between 7% and 9%. The results achieved in the studies will allow radiologists to minimise false negative rate which is critically important for early diagnostics.
    • Battery-assisted electric vehicle charging: data driven performance analysis

      Ali, Junade; Dyo, Vladimir (2020-07-03)
      As the number of electric vehicles rapidly increases, their peak demand on the grid becomes one of the major challenges. A battery-assisted charging concept has emerged recently, which allows to accumulate energy during off-peak hours and in-between charging sessions to boost-charge the vehicle at a higher rate than available from the grid. While prior research focused on the design and implementation aspects of battery- assisted charging, its impact at large geographical scales remains largely unexplored. In this paper we analyse to which extent the battery-assisted charging can replace high-speed chargers using a dataset of over 3 million EV charging sessions in both domestic and public setting in the UK. We first develop a discrete-event EV charge model that takes into account battery capacity, grid supply capacity and power output among other parameters. We then run simulations to evaluate the battery-assisted charging performance in terms of delivered energy, charging time and parity with conventional high-speed chargers. The results indicate that in domestic settings battery-assisted charging provides 98% performance parity of high-speed chargers from a standard 3 kW grid connection with a single battery pack. For non-domestic settings, the battery-assisted chargers can provide 92% and 99% performance parity of high-speed chargers with 10 battery packs using 3kW and 7kW grid supply respectively.
    • Practical hash-based anonymity for MAC addresses

      Ali, Junade; Dyo, Vladimir (ScitePress, 2020-06-18)
      Given that a MAC address can uniquely identify a person or a vehicle, continuous tracking over a large geographical scale has raised serious privacy concerns amongst governments and the general public. Prior work has demonstrated that simple hash-based approaches to anonymization can be easily inverted due to the small search space of MAC addresses. In particular, it is possible to represent the entire allocated MAC address space in 39 bits and that frequency-based attacks allow for 50% of MAC addresses to be enumerated in 31 bits. We present a practical approach to MAC address anonymization using both computationally expensive hash functions and truncating the resulting hashes to allow for k-anonymity. We provide an expression for computing the percentage of expected collisions, demonstrating that for digests of 24 bits it is possible to store up to 168,617 MAC addresses with the rate of collisions less than 1%. We experimentally demonstrate that a rate of collision of 1% or less can be achieved by storing data sets of 100 MAC addresses in 13 bits, 1,000 MAC addresses in 17 bits and 10, 000 MAC addresses in 20 bits.
    • Deep learning for biometric face recognition: experimental study on benchmark data sets

      Selitskaya, Natalya; Sielicki, S.; Jakaite, Livija; Schetinin, Vitaly; Evans, F.; Conrad, Marc; Sant, Paul (Springer International Publishing, 2020-06-09)
      There are still problems in applications of Machine Learning for face recognition. Such factors as lighting conditions, head rotations, emotions, and view angles affect the recognition accuracy. A large number of recognition subjects requires complex class boundaries. Deep Neural Networks have provided efficient solutions, although their implementations require massive computations for evaluation and minimisation of error functions. Gradient algorithms provide iterative minimisation of the error function. A maximal performance is achieved if parameters of gradient algorithms and neural network structures are properly set. The use of pairwise neural network structures often improves the performance because such structures require a small set of optimisation parameters. The experiments have been conducted on some face biometric benchmark data sets, and the main findings are presented in the form of a tutorial.
    • Effect of AFM nanoindentation loading rate on the characterization of mechanical properties of vascular endothelial cell

      Wang, Lei; Tian, Liguo; Zhang, Wenxiao; Wang, Zuobin; Liu, Xianping (MDPI, 2020-05-31)
      Vascular endothelial cells form a barrier that blocks the delivery of drugs entering into brain tissue for central nervous system disease treatment. The mechanical responses of vascular endothelial cells play a key role in the progress of drugs passing through the blood-brain barrier. Although nanoindentation experiment by using AFM (Atomic Force Microscopy) has been widely used to investigate the mechanical properties of cells, the particular mechanism that determines the mechanical response of vascular endothelial cells is still poorly understood. In order to overcome this limitation, nanoindentation experiments were performed at different loading rates during the ramp stage to investigate the loading rate effect on the characterization of the mechanical properties of bEnd.3 cells (mouse brain endothelial cell line). Inverse finite element analysis was implemented to determine the mechanical properties of bEnd.3 cells. The loading rate effect appears to be more significant in short-term peak force than that in long-term force. A higher loading rate results in a larger value of elastic modulus of bEnd.3 cells, while some mechanical parameters show ambiguous regulation to the variation of indentation rate. This study provides new insights into the mechanical responses of vascular endothelial cells, which is important for a deeper understanding of the cell mechanobiological mechanism in the blood-brain barrier.
    • Effects of AC/DC electric fields on stretching DNA molecules

      Wang, Ying; Gao, Mingyan; Qu, Yingmin; Hu, Jun; Xie, Ying; Liu, Ziyu; Song, Zhengxun; Xu, Hongmei; Weng, Zhankun; Wang, Zuobin (World Scientific Publishing Co. Pte Ltd, 2020-05-01)
      The effects of AC/DC electric fields on stretching DNA molecules were discussed in this work. In the experiments of stretching DNA molecules with AC/DC electric fields, the voltage range was changed from 0V to 10V, and the frequency of AC electric field was kept at 50kHz. An atomic force microscope (AFM) was used to obtain DNA distributions under different electric fields. DNA molecules were curved and randomly distributed in solution if there was not any force applied to them. When an AC electric field was applied to the DNA sample, the curvature of DNA molecules was decreased gradually, and the stretching result was more obvious with the increase of voltage from 0.1V to 5V. The DNA molecules were broken when the voltage was increased to 6V. However, under the DC electric field, the stretching result of DNA molecules reached to their optimum state when the voltage was 2V, and they kept their steady state even though larger electric field intensities applied to the electrodes. The results can be used for the study of DNA-DNA, protein-DNA and quantum dot-DNA interactions and for the exploration of DNA biophysical properties.
    • Modeling and correction of image pixel hysteresis in atomic force microscopy

      Sun, Baishun; Cao, Liang; Xie, Chenchen; Song, Zhengxun; Lu, Zhengcheng; Weng, Zhankun; Wang, Zuobin; Changchun University of Science and Technology; Jilin Medical University; University of Bedfordshire (Elsevier B.V., 2020-04-27)
      In an atomic force microscope (AFM) system, the measurement accuracy in the scan images is determined by the displacement accuracy of piezo scanner. The hysteresis model of piezo scanner displacement is complex and difficult to correct, which is the main reason why the output displacement of the piezo scanner does not have high precision. In this study, an image pixel hysteresis model of the piezo scanner displacement in the AFM system was established. An AFM was used to scan a two-dimensional (2D) grating in the 0 ° and 90 ° directions and a polynomial fitting method was employed to obtain the image pixel hysteresis model parameters of the piezo scanner displacement in the X-direction and Y-direction. The image pixel hysteresis model was applied to correct the AFM scan image of regular octagons. The results showed that the relative measurement error in the X-direction was decreased from 12.47% to 0.52% after the correction and that in the Y-direction decreased from 28.57% to 0.35%. The image pixel hysteresis model can be applied in the post-processing software of a commercial AFM system. The model solves the hysteresis problem of the AFM system and improves the measuring accuracy of AFM in 2 degrees of freedom (2 DOF).
    • Survey on health care applications in 5G networks

      Liu, Enjie; Effiok, Emmanuel; Hitchcock, Jonathan James; University of Bedfordshire (IEEE, 2020-04-13)
      In 2019, 5G was introduced and it is being gradually deployed all over the world. 5G introduces new concepts, such as network slicing to better support various applications with different performance requirements on data rate and latency; and edge and cloud computing that will be responsible for the leverage of computational requirements. This study aims to describe the functions and features of the key 5G technologies and conduct a survey on the latest development of driving technologies for 5G. This survey focuses on health care applications that would benefit from the advantages brought by 5G.
    • Finger-drawn signature verification on touch devices using statistical anomaly detectors

      Al-Khafaji, Shawq S.; Al-Jarrah, Mudhafar M.; Amin, Saad; Feng, Xiaohua; University of Bedfordshire; Middle East University; Alkhawarizmi International College (Institute of Electrical and Electronics Engineers Inc., 2020-04-09)
      The use of behavioral biometrics in user authentication has recently moved to new security application areas, one of which is verifying finger-drawn signatures and PIN codes. This paper investigates the design of anomaly detectors and feature sets for graphic signature authentication on touch devices. The work involved a selection of raw data feature sets that are extracted from modern mobile devices, such as finger area, pressure, velocity, acceleration, gyroscope, timestamp and position coordinates. A set of computed authentication features are formulated, derived from the raw features. The proposed anomaly detector is based on the outlier method, using three versions of the Z-Score distance metric. The proposed feature sets and anomaly detectors are implemented as a data collection and dynamic authentication system on an Android tablet. Experimental work resulted in collecting a signature dataset that included genuine and forged signatures. The dataset was analyzed using the Equal-Error-Rate (EER) metric. The results for random forgery and skilled forgery showed that the Z-Score anomaly detector with 3.5 standard deviations distance from the mean produced the lowest error rates. The skilled forgery error rates were close to random forgery error rates, indicating that behavioral biometrics are the key factors in detecting forgeries, regardless of pre-knowledge of the signature's shape.
    • Security and forensics challenges to the MK smart project

      Okai, Ebenezer; Feng, Xiaohua; Sant, Paul; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2020-04-09)
      MK Smart project is a joint initiative which is led by the Open university and supported by Key players such as University of Bedfordshire (Milton Keynes Campus), University of Cambridge, British Telecom (BT), Milton Keynes Council, E. ON, Anglian Water, HR Wallingford Ltd, Satellite Applications Catapult, Community Action MK, Fronesys, Graymatter and Playground Energy. The project is partly funded by HEFCE (the Higher Education Funding Council for England) and led by The Open University with the primarily aim of developing innovative solutions to support the economic growth in Milton Keynes [MK Smart]. MK Data Hub is the central infrastructure to the project which supports the acquisition and management of the big data from various data sources relevant to the city systems. [MK Smart, 2014]. Whilst the data plays crucial part to this project, its forensic value of the data held is also important to the investigation of this project. Data might be required to help in any forensic investigation to be proven in a case of Data integrity. The challenges of security and forensics to this project may be hinderance to its future. Mitigating these challenges can go a long way not only to this project but to other smart cities projects. This paper concentrates on realising the security and forensics challenges of the MK Smart project, primarily looking at the challenges of securing such a huge data on a datahub and concentrating on the best possible way to forensically investigate the large complex data such as the data stored on the Datahub.
    • Challenges in ROS forensics

      Abeykoon, Iroshan; Feng, Xiaohua; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2020-04-09)
      The usage of robot is rapidly growth in our society. The communication link and applications connect the robots to their clients or users. This communication link and applications are normally connected through some kind of network connections. This network system is amenable of being attached and vulnerable to the security threats. It is a critical part for ensuring security and privacy for robotic platforms. The paper, also discusses about several cyber-physical security threats that are only for robotic platforms. The peer to peer applications use in the robotic platforms for threats target integrity, availability and confidential security purposes. A Remote Administration Tool (RAT) was introduced for specific security attacks. An impact oriented process was performed for analyzing the assessment outcomes of the attacks. Tests and experiments of attacks were performed in simulation environment which was based on Gazbo Turtlebot simulator and physically on the robot. A software tool was used for simulating, debugging and experimenting on ROS platform. Integrity attacks performed for modifying commands and manipulated the robot behavior. Availability attacks were affected for Denial-of-Service (DoS) and the robot was not listened to Turtlebot commands. Integrity and availability attacks resulted sensitive information on the robot.
    • Autonomous vehicles' forensics in smart cities

      Feng, Xiaohua; Dawam, Edward Swarlat; Li, Dayou; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2020-04-02)
      Autonomous vehicles (AVs) are capable of sensing their environment and navigating without any human inputs. When accidents occur between AVs, road infrastructures, or human subjects, liability is decided based on accident forensics. This accident forensics is carried out by the acquisition of sensor data generated within the AVs and through its communication between vehicles to a vehicle (V2V) and vehicle to infrastructure (V2I) with a centralised data hub in smart cities that collects and stores this data thereby aiding the relevant authorities in informed decision making. However, practices mostly employed in extracting this information are unprofessional when compared to other areas of digital forensics. In this paper, we designed and implemented a non-invasive mechanism for the collection and storage of forensic data from AVs within smart cities. This mechanism is efficient, secure, and preserves the privacy of data generated by the AV.
    • Controllable patterning of hybrid silicon nanowire and nanohole arrays by laser interference lithography

      Guo, Xudong; Li, Songhao; Lei, Zecheng; Liu, Ri; Li, Li; Wang, Lu; Dong, Litong; Peng, Kuiqing; Wang, Zuobin (Wiley-VCH Verlag, 2020-03-17)
      Metal-assisted chemical etching (MACE) is a cost-effective method to fabricate Si nanostructures including silicon nanowires (SiNWs) and silicon nanoholes (SiNHs). However, the preparation of metallic template for MACE would require complex experimental conditions including strict cleaning process and multiple steps. Herein, superlens-enhanced laser interference lithography is applied to directly fabricate complicated metallic patterns and then MACE is used to obtain hybrid SiNW and SiNH arrays. Ag films are first deposited on Si substrates, and then a 1064 nm high power laser source is utilized to generate two-beam interference electric fields. Because Ag molecules are very sensitive to any input energy change, they tend to break up or aggregate and form different Ag patterns which have a specific energy threshold to lower its free energy. By manipulating the distribution of input electric field, complicated metallic patterns and their corresponding Si nanostructures with feature sizes that range from tens of nanometers to several micrometers are obtained.
    • Fabrication and transfer printing of periodic Pt nanonetwork gratings

      Yu, Miao; Li, Li; Wu, Xiaomin; Song, Yingying; Liu, Jinyun; Wang, Zuobin; Changchun University of Science and Technology; University of Bedfordshire (AIP Publishing, 2020-03-13)
      Metal nanonetworks are applied in various applications, such as biomedicine, bionic materials, optical materials, and new energy materials. Here, periodic variable-sized Pt nanonetwork gratings (PtNGs) are fabricated on the surface of a Pt/Si substrate with single pulse two-beam direct laser interference lithography. The fabricated PtNGs are transferred onto the surface of a glass substrate with polymethyl methacrylate as the transfer mediator. Exposure with different film thicknesses, contrasts, and intensity distributions of the laser interference spot is analyzed, and the formation of nanopatterns is explained. Results show that with the change in the thicknesses of the Pt film, the exposed structures present Pt nanoparticles (PtNPs), Pt gratings, and PtNGs. The morphology and the feature size of the PtNGs are influenced by intensity distributions and the contrast of the laser interference spot significantly.
    • Design of a compact multiband circularly polarized antenna for global navigation satellite systems and 5G/B5G applications

      Falade, Oluyemi Peter; Ur-Rehman, Masood; Yang, Xiaodong; Safdar, Ghazanfar Ali; Parini, Clive G.; Chen, Xiaodong (Wiley, 2020-02-17)
      Design of a multiband circularly polarized antenna is proposed in this article. The antenna has a simple and compact form factor by employing single‐feed stacked patch structure. It exhibits good performance at the global navigation satellite system (GNSS) frequency bands of L1, L2, and L5 and cellular communications frequency band of 2.3 GHz. The antenna has a 3‐dB axial ratio bandwidth of 1.1%, 1.0%, 4.1%, and 1.5% at the four operating bands of L1 (1.575 GHz), L2 (1.227 GHz), L5 (1.176 GHz), and 2.3 GHz. The antenna also achieves a gain of more than 2.2 dBiC and efficiency of more than 70% at the four frequencies. A detailed parametric study is carried out to investigate the importance of different structural elements on the antenna performance. Results are verified through close agreement of simulations and experimental measurements of the fabricated prototype. Good impedance matching, axial ratio bandwidth, and radiation characteristics at the four operating bands along with small profile and mechanically stable structure make this antenna a good candidate for current and future GNSS devices, mobile terminals, and small satellites for 5G/Beyond 5G (5G/B5G) applications.
    • Evidence of power-law behavior in cognitive IoT applications

      Bebortta, Sujit; Senapati, Dilip; Rajput, Nikhil Kumar; Singh, Amit Kumar; Rathi, Vipin Kumar; Pandey, Hari Mohan; Jaiswal, Amit Kumar; Qian, Jia; Tiwari, Prayag; College of Engineering and Technology, Bhubaneshwar; et al. (Springer, 2020-02-03)
      The motivations induced due to the presence of scale-free characteristics of neural systems governed by the well-known power-law distribution of neuronal activities have led to its convergence with the Internet of things (IoT) framework. The IoT is one such framework, where the self-organization of the connected devices is a momentous aspect. The devices involved in these networks inherently relate to the collection of several consolidated devices like the sensory devices, consumer appliances, wearables, and other associated applications, which facilitate a ubiquitous connectivity among the devices. This is one of the most significant prerequisites of IoT systems as several interconnected devices need to be included in the convolution for the uninterrupted execution of the services. Thus, in order to understand the scalability and the heterogeneity of these interconnected devices, the exponent of power-law plays a significant role. In this paper, an analytical framework to illustrate the ubiquitous power-law behavior of the IoT devices is derived. An emphasis regarding the mathematical insights for the characterization of the dynamic behavior of these devices is conceptualized. The observations made in this direction are illustrated through simulation results. Further, the traits of the wireless sensor networks, in context with the contemporary scale-free architecture, are discussed.
    • Imaging quality assessment of different AFM working modes on living cancer cells

      Wang, Guoliang; Sun, Baishun; Wu, Xiaomin; Zhang, Wenxiao; Qu, Yingmin; Song, Zhengxun; Wang, Zuobin; Li, Dayou; Changchun University of Science and Technology; University of Bedfordshire (IEEE, 2020-02-02)
      Since the invention of atomic force microscope (AFM) in 1986, its capabilities in biophysical research, such as living cell imaging, molecule imaging and recognition and drug treatment analysis, have been deeply investigated. Various types of working modes of atomic force microscopy have been employed for imaging and analyzing living cells. The physical properties of living cells can be directly illustrated by its good resolution images. In this paper, the applications of three AFM working modes including contact, tapping and quantitative imaging (QI) modes for the investigation of living lung cancer cells (A549) are presented. Meanwhile, the quality of images of the cells obtained by different working modes is compared through the image quality assessment (IQA) methods.