Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic Resonance Imaging Versus Computed Tomography for Three‐Dimensional Bone Imaging of Musculoskeletal Pathologies: A Review

Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal pathologies. MR imaging of hard tissues such as cortical bone remains challenging due to their low proton density and short transverse relaxation times, rendering bone tissues as nonspecific low signal structures on MR images obtained from most sequences. Developments in MR image acquisition and post‐processing have opened the path for enhanced MR‐based bone visualization aiming to provide a CT‐like contrast and, as such, ease clinical interpretation. The purpose of this review is to provide an overview of studies comparing MR and CT imaging for diagnostic and treatment planning purposes in orthopedic care, with a special focus on selective bone visualization, bone segmentation, and three‐dimensional (3D) modeling. This review discusses conventional gradient‐echo derived techniques as well as dedicated short echo time acquisition techniques and post‐processing techniques, including the generation of synthetic CT, in the context of 3D and specific bone visualization. Based on the reviewed literature, it may be concluded that the recent developments in MRI‐based bone visualization are promising. MRI alone provides valuable information on both bone and soft tissues for a broad range of applications including diagnostics, 3D modeling, and treatment planning in multiple anatomical regions, including the skull, spine, shoulder, pelvis, and long bones.
Effects of HfO2 Interlayer on Microstructure and Mechanical Property of Al2O3 Thin Film on MgF2 Substrate

Al2O3 thin films with or without HfO2 interlayer between Al2O3 and substrate were deposited on MgF2 substrates by electron-beam evaporation technique. The as-deposited thin films were then annealed at 600°C for 1 h to promote crystallization. The microstructure, IR transmittance and mechanical properties of the as-deposited and annealed samples were investigated by field emission scanning electron microscopy (FE-SEM), grazing incidence X-ray diffraction (GIXRD), Fourier Transform Infrared (FTIR) spectrometer, nanoindentation, and scratch tests, respectively. FE-SEM results show that a new branch-like layer is generated in annealed HfO2/Al2O3 double-layer thin films. The hardness of the newly formed layer is considered to be larger than 17.5 GPa. Because of the high hardness of the new layer, the MgF2 substrate can be protected from being drown out during scratch test. From GIXRD patterns, Al2O3 still remains amorphous while HfO2 interlayer transforms from amorphous to monoclinic phase after annealing process. It could be deduced that it is the phase transformation of HfO2 interlayer that promotes the formation of the harder branch-like layer.
Transformer Health Index Sensitivity Analysis using Neuro- Fuzzy Modelling

Article history: Received 5 June 2017 Received in revised form 10 July 2017 Accepted 4 December 2017 Available online 16 March 2018 In this paper a transformer Health Index (HI) sensitivity analysis study is presented. A HI prediction model is developed using a Self-Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS model is tuned using the Particle Swarm Optimizer (PSO). The utilized measurements are a combination of actual field measurements including Carbon Monoxide (CO), Acetylene (C2H2), Ethane (C2H6), Interfacial Tension (IFT) and Furans content (FFA) for 724 working transformers within a network of an industrial facility. Results show that the PSO based ANFIS model is capable of obtaining good and reliable results. The model response is tested and it is able to predict the HI numerically with high accuracy. Furthermore, it was found that the model yielded a good response in predicting HI change with respect to the change of transformer’s measurement values.
Simulation of Optical Nano-Manipulation with Metallic Single and Dual Probe Irradiated by Polarized Near-Field Laser

Nano-manipulation technology, as a kind of “bottom-up” tool, has exhibited an excellent capacity in the field of measurement and fabrication on the nanoscale. Although variety manipulation methods based on probes and microscopes were proposed and widely used due to locating and imaging with high resolution, the development of non-contacted schemes for these methods is still indispensable to operate small objects without damage. However, optical manipulation, especially near-field trapping, is a perfect candidate for establishing brilliant manipulation systems. This paper reports about simulations on the electric and force fields at the tips of metallic probes irradiated by polarized laser outputted coming from a scanning near-field optical microscope probe. Distributions of electric and force field at the tip of a probe have proven that the polarized laser can induce nanoscale evanescent fields with high intensity, which arouse effective force to move nanoparticles. Moreover, schemes with dual probes are also presented and discussed in this paper. Simulation results indicate that different combinations of metallic probes and polarized lasers will provide diverse near-field and corresponding optical force. With the suitable direction of probes and polarization direction, the dual probe exhibits higher trapping force and wider effective wavelength range than a single probe. So, these results give more novel and promising selections for realizing optical manipulation in experiments, so that distinguished multi-functional manipulation systems can be developed.
Viral Vector-Based Cancer Immunotherapy

Cancer immunotherapy has encountered substantial progress during the last decade. Particularly, the development of novel viral and non-viral vectors has contributed to the development of more efficient subunit vaccines. A large number of viral vectors including adenoviruses, adeno-associated viruses, alphaviruses, flaviviruses, herpes simplex viruses, retroand lentiviruses, measles virus, rhabdoviruses and vaccinia virus have been engineered. Immunization with RNA, especially self-replicative RNA replicons, plasmid DNA and recombinant viral particles and oncolytic viruses have elicited strong antibody responses in different animal models. Virus-based delivery of tumor antigens, immunostimulatory molecules such as cytokines, and antibodies has provided prophylactic protection against tumor challenges in mice and also generated therapeutic efficacy in tumor-bearing animals. Several clinical trials have been conducted and the first herpes simplex virus-based vaccine for treatment of melanoma has been approved. In this review, cancer immunotherapy applications of various viral vectors are discussed.
Optimizing Edge-Cloud Cooperation for Machine Learning Accuracy Considering Transmission Latency and Bandwidth Congestion

Machine learning (ML) has been used for various tasks in network operations in recent years. However, since the scale of networks has grown and the amount of data generated has increased, it has been increasingly difficult for network operators to conduct their tasks with a single server using ML. Thus, ML with edge-cloud cooperation has been attracting attention for efficiently processing and analyzing a large amount of data. In the edge-cloud cooperation setting, although transmission latency, bandwidth congestion, and accuracy of tasks using ML depend on the load balance of processing data with edge servers and a cloud server in edge-cloud cooperation, the relationship is too complex to estimate. In this paper, we focus on monitoring anomalous traffic as an example of ML tasks for network operations and formulate transmission latency, bandwidth congestion, and the accuracy of the task with edge-cloud cooperation considering the ratio of the amount of data preprocessed in edge servers to that in a cloud server. Moreover, we formulate an optimization problem under constraints for transmission latency and bandwidth congestion to select the proper ratio by using our formulation. By solving our optimization problem, the optimal load balance between edge servers and a cloud server can be selected, and the accuracy of anomalous traffic monitoring can be estimated. Our formulation and optimization framework can be used for other ML tasks by considering the generating distribution of data and the type of an ML model. In accordance with our formulation, we simulated the optimal load balance of edge-cloud cooperation in a topology that mimicked a Japanese network and conducted an anomalous traffic detection experiment by using real traffic data to compare the estimated accuracy based on our formulation and the actual accuracy based on the experiment.
Sibyl: a Framework for Evaluating the Implementation of Routing Protocols in Fat-Trees

Several data centers adopt fat-tree topologies, where high bisection bandwidth is achieved by interconnecting commodity hardware and by using specific routing solutions. These solutions, which include protocol implementations and configurations, are difficult to evaluate and test both for the density of fat-trees and for the complexity of the protocols. Also, since most issues show up only when a fault happens, it is unfeasible to perform such tests in a production environment. Additionally, the lack of standard testing procedures motivates an effort in developing solutions for such a critical task. In this paper, we propose a methodology devised for testing fat-tree routing protocol implementations. It adopts a wall-clock independent method to establish metrics, which permits normalizing the results of different routing protocol implementations independently from the execution environment. The methodology is implemented by Sibyl, a software framework developed to perform repeatable tests on arbitrary fat-tree topologies automatically. Sibyl also provides a set of tools to analyze the results and investigate implementation behaviors. We evaluate the methodology and Sibyl in three use cases. Such use cases witness a wide spectrum of situations where Sibyl is effective for analyzing, comparing, developing, and debugging routing protocol implementations.
Digital Twin Technologies for Diesel Generator Sets in Backup and Emergency Power Supply Systems

In the electric power industry, the cost of work required to restore power generation and distribution equipment increases significantly with an increase in the energy intensity of power supply systems. This is determined not only by expensive repairs, but also by contractual relations between the generating company and the consumer. One of the ways to improve the power supply system's reliability is the formation of forecast estimates regarding the signs of the origin and emergency modes development of electrical equipment operation. A modern trend is the development of digital twin technologies for industrial equipment. The mathematical model of the diesel generator digital twin is considered. The possibilities of developing universal control and revision electronic modules with the accumulating information function about the operating modes of generating electrical equipment are analyzed.
B5GEMINI: Digital Twin Network for 5G and Beyond

Digital Twin Network (DTN) is a new technology that builds on the concept of Digital Twins (DT) to create a virtual representation of the physical objects of a telecommunications network. DTN bridges physical and virtual spaces to enable coordination and synchronization of physical parts while eliminating the need to directly interact with them. In this work, we present B5GEMINI a DTN for 5G and beyond networks that makes an extensive use of artificial intelligence (AI). First, we present the infrastructural and architectural components that support B5GEMINI. Next, we explore five paradigmatic use cases where AI can leverage B5GEMINI for building new AI-powered applications. Finally, we identify the main components of the AI ecosystem of B5GEMINI.
Analysis of Controlled Digital Recursive High-Pass Filters Structures with Infinite Non-Negative Impulse Response

Digital signal processing is widely used in modern technology, including robotics, medical technology, etc. Thus, high-pass filters are used to eliminate the constant component of the output signal at the output of an analog-to-digital converter. This also reduces the low-frequency interference level spread out on the frequency axis to the left of the lower boundary of the signal spectrum. In the case of a dynamic change in the signal and interference spectra, controlled digital filters are used, the coefficients of which explicitly depend on the cutoff frequency. A non-negative impulse response, which corresponds to a flat transient response, is required. For example, in the case of determining the presence of a negative signal against the background of a positive pulse of a much larger amplitude. Or, conversely, to determine the presence of a positive signal against the background of a negative pulse. As this takes place, a signal pass is allowed, but a false detection is not allowed. False detection can be caused by undershoot or fluctuations in the step response ($SR$) of the high-pass filter. The paper investigates the structures of high-pass filters based on a parallel connection of a direct pass and a cascade connection of first order low-pass filters, which are obtained by the method of invariant transformation of the impulse response. The disadvantage of some of the studied structures is the presence of an overshoot on the amplitude-frequency response in the vicinity of the cutoff frequency. The conditions under which the negative impact of this emission decreases, are analyzed.
QoS-Aware Inter-Domain Connectivity: Control Plane Design and Operational Considerations

Scenarios related to 5G and beyond give rise to a high degree of heterogeneity in terms of applications, services, and user expectations as well as more demanding QoS requirements with an end-to-end scope that can cover multiple operator domains. In this work, we design an inter-domain component that addresses the control plane challenges of establishing such end-to-end connectivity in a scalable, efficient, and automated way. Furthermore, we provide insights into operational aspects by investigating to which extent different traffic aggregation mechanisms can be used to benefit from economies of scale while meeting QoS constraints.
Stem-FIT: a Microneedle-based Multi-parametric Sensor for In Situ Monitoring of Salicylic Acid and pH Levels in Live Plants

This work reports Stem-FIT: a first-of-its-kind three-dimensional printed microneedle-based electrochemical sensor for real-time monitoring of plants’ primary defense-related phytohormone, salicylic acid. In addition, a pH sensor was integrated on the same chip to enable pH correction of the measured salicylic acid levels based on the variations in sap pH. The sensor was demonstrated to measure the salicylic acid and pH levels in the stem of unstressed and water-stressed cabbage plants in real-time. The sensor was capable of detecting salicylic acid levels down to 37 μM. Real-time measurements of SA levels in plant sap with built-in pH correction capability can help growers act timely against any environmental stress conditions to mitigate crop productivity losses and improve plants’ adaptability to stressors.
Fatigue Analysis and Design Optimization of Aircraft’s Central Fuselage

The centre fuselage of an aircraft plays a very crucial role as most of the important parts such as the front fuselage, aft fuselage and the wings are connected to it. So any load applied on these parts will be transferred to the centre fuselage. Hence it was essential to study the centre fuselage briefly in order to attain high design safety. Fatigue is the process of repeated cyclic loading of a component, which leads to an early failure of the same. The sources of fatigue in an aircraft are the parts connected to it, such as the wings, and the differential pressure between the inside of the fuselage and the outside atmosphere as a result of cabin pressurization. The high pressure inside the fuselage tries to expand the fuselage, whereas the stringers and bulk head prevent it from happening. This change in pressure happens frequently and this results in the fatigue of the centre fuselage. The vibratory loads acting on the other parts are transferred to the centre fuselage, which are also major contributors to the fatigue. The centre fuselage of an aircraft was designed using Pro-E software. The standard aluminium alloy was selected for the material. The various loads acting on the centre fuselage were studied and added to the centre fuselage, along with a differential pressure in a cyclic manner.
Analisis Kriteria Dan Proses Seleksi Kontraktor Chemical Sektor Hulu Migas: Aplikasi Metode Delphi-ahp

With an average production growth of 6-7 percent per year, the performanceof upstream oil and gas company PT Pertamina EP Asset 3 plays a strategic role forenergy security in Indonesia. Chemical material procurement activities is one of thecritical activities in the upstream oil and gas supply chain that supports the corporatestrategy of PT Pertamina because the magnitude of the risk if the chemical materialsupplied does not comply with the specification. The purpose of this study was toanalyze the criteria and the selection process of contractors key chemical material in thecontext of the sustainability of the supply chain of oil and gas PT Pertamina 3 using theDelphi method and Analytical Hierarchy Process (AHP). Consensus on the criteria ofchemical contractor PT Pertamina EP Asset 3 involves 8 experts obtained after goingthrough three rounds. The criteria weights in a row is the safety and the environment,price, quality, delivery, flexibility, and services. Safety and environmental issues in theupstream oil and gas industry is a strategic issue and a top priority in selectingcontractors chemical. Based on the analysis results generated priority contractor wasPT. Elnusa Petrofin, followed by PT. Eonchemicals Putra, PT. Sasfindo Multi Yasa,and PT. Top Birus spacious. PT Elnusa Petrofin superior in safety and delivery criteria,although still weak on service and price criteria.
Low Frequency Ripple Mitigation of the Fuel Cell Inverter System using a Controlled Buck Current Source - Part I: Hysteretic Control

This paper analyzes the possibility of using a nonlinear controller to mitigate the current ripple of an inverter system powered by a Polymer Electrolyte Membrane Fuel Cell (PEMFC) stack. Hybrid and fuel cell technologies need to be merged in Hybrid Power Sources (HPS) to assure high performance regarding the PEMFC energy efficiency and PEMFC life cycle. The nonlinear controller is designed based on inverse gain that gives a constant answer for all levels of current ripple. Its advantages will be showed in comparison with hysteretic current control technique (that was shown in part I). Finally, a fuzzy logic controller is proposed to design the nonlinear control law.
Implementation and evaluation of the Multi-connection Tactile Internet Protocol and API

Tactile Internet defines applications for remotely controlling and manipulating critical devices that require perceived real-time operation with additional demanding requirements like reliability. These use cases with stringent requirements demand adequate transport protocols to take advantage of the underlying possibilities. Traditional transport-layer solutions like TCP and UDP are no longer sufficient, hence novel protocols are being developed to support these applications. In this paper, we present an implementation and evaluation of the Multi-connection Tactile Internet Protocol (MTIP), a transport layer proposal to support these communications. MTIP uses application and network status information to perform an intelligent selection of paths in order to improve reliability and latency. In our evaluations, we study how the different configurations of the MTIP algorithm affect this selection and we see a direct trade-off where, with more restrictive thresholds, MTIP can increase the packets received correctly at the cost of sending extra duplicate packets.
Impact of Aperture on the Performance of AlN Lamb Wave Resonators on SOI substrate

In this paper, we present an experimental study of the impact of aperture on the resonance characteristics of aluminum nitride (AlN) lamb wave resonators (LWR), including quality factor (Q) and electromechanical coupling coefficient $\left( {k_t^2} \right)$. We selected four LWR aperatures-170μm, 220μm, 270μm, and 320μm for comparison. Finite element modeling (FEM) simulation was performed for verification. The admittance parameters of the fabricated devices are fitted numerically by a modified Butterworth-van Dyke (MBVD) model to extract the $k_t^2$ and Q. It is found that when device aperture increases, the Q increases and $k_t^2$ decreases. Measurement results show that $k_t^2$ decreases from 1.075% at 170μm to 0.369% at 320μm, while Q increases from 205.60 at 170μm to 558.69 at 320μm. This work may provide guidance on the design of lamb wave resonators.
Mobile applications for connected cars: Security analysis and risk assessment

As connected vehicles continue to become more advanced and widespread, it is vital to ensure that vehicle to everything (V2X) communications are secure. Connected car mobile applications have become a key feature in the vehicular ecosystem and represent a new attack vector that can be used to compromise vehicles. This paper undertakes a threat analysis and risk assessment (TARA) of connected car mobile applications using known vulnerabilities. The found vulnerabilities are analysed to highlight common weaknesses. This paper thus outlines how a TARA can be adapted in the context of connected car mobile applications with reference to established security models.
A NEAT way to test-driven network management

The increasing softwarization of network infrastructures introduces an important challenge for network configuration. The growth of the network configuration space as a result of new device types and the expanding inter-dependence of network service components increases the network configuration complexity. Compounding this issue, new service deployment architectures lack mechanisms to validate the impact of service configuration on network resilience. Network operators need to adopt new mechanisms to validate and verify network configuration changes, taking inspiration from popular Continuous Integration/Continuous Development (CI/CD) mechanisms. This paper introduces Network Emulation-based Automated Testing (NEAT), an automated testing framework for network configuration. NEAT allows network managers to define network topologies and tests through YAML files, to then be later executed by NEAT within realistic network topologies. Furthermore, network managers can control the fidelity of their network tests and bound the execution time of testing suites, as well as exploit parallelization of modern servers to speedup test execution.