Miracle-dz/UniFAR-FTUs huggingface dataset:
The Rise of Deep Learning in Radiology: An Overview of Recent Research

: This is a consolidated look at the applications of various deep learning techniques in the field of radiology. For the past few years, deep learning has pervaded every field and the deep learning revolution has opened up new frontiers in artificial intelligence. From healthcare to art or from education to business - it has been applied successfully in a range of different domains to attain state-of-the-art, often reporting near human-level performance. Hence, in the field of radiology too, especially for image interpretation tasks, deep learning techniques are being increasingly used in recent times to optimize the medical workflow and to achieve better patient care and efficient medical surveillance. Convolutional neural networks (CNNs) are mostly dominant in the case of image interpretation applications in radiology, because of their unprecedented success in image-related applications in other domains such as computer vision. However, other deep learning techniques like recurrent neural networks (RNNs) and generative adversarial networks (GANs) are also being used in recent research for various image-related tasks in radiology like classification, segmentation and detection. In this paper, the imaging modalities associated with this field and the application of different deep learning techniques to these have been discussed at length. Moreover, deep learning can also be applied to radiology use cases other than image interpretation, such as patient scheduling or the processing of free-text radiology reports to improve healthcare surveillance. Finally, in this study, the practical challenges as well as the future research directions of this domain have been discussed. Some challenges include dearth of annotated data, the fear of AI unseating radiologist professionals, legal and ethical issues, black box behaviour of neural networks and adversarial fooling of deep learning algorithms by reverse engineering. To counter some of these problems, a few trends in applying deep learning to radiology in the future may include improved visualisation techniques, integration of the entire workflow for practical usability, unsupervised methods of deep learning like auto-encoders and improving research on GANs in radiology. This study may prove useful for researchers applying deep learning to various radiology use cases by providing a detailed overview of the state-of-the-art research in the field.
Characterization of Short-Term Strength Properties of Fiber/Cement-Modified Slurry

The recycling of construction waste slurry is an urgent issue that needs to be solved in urban construction. To satisfy the requirements of subgrade filling, mechanical properties of fiber/cement-modified slurry were investigated. Unconfined compression tests were conducted for 7-day-cured specimens with a cement content of 5%, 10%, 15%, 20%, 25%, and 30%, respectively. Moreover, the effects of fiber contents (0.25%, 0.5%, 0.75%, and 1%, respectively) were also investigated for the specimens with a cement content of 20%. A formula satisfying the accuracy requirement was obtained by fitting the stress-strain curves using the back propagation (BP) neural network algorithm. Five parameters, including peak strength, failure strain, initial elastic modulus, residual strength, and energy dissipation, were used to characterize the short-term strength properties of fiber/cement-modified slurry. The analysis revealed that the cement content had a dominant effect on the short-term strength properties of fiber/cement-modified slurry, while the influence of fiber content was insignificant.
Enhancing characteristics of dual‐polarized BTS element antenna using metal director

This article proposes a dual‐polarized antenna with enhanced characteristics using metal director for base transceiver station applications. The proposed antenna consists of a main radiation element, ±45ᴼ dual‐polarized feed structure, a reflector and a metal director. The metal director improves the impedance matching and increases the gain and front to back ratio. A prototype of the antenna is fabricated and the measured results show the wide frequency bandwidths of 63% for port 1 with frequency range 1.6 to 3.1 GHz and 60% for port 2 with frequency range 1.6 to 3 GHz. The obtained experimental isolation between ports is greater than 28 dB. The measured results also represent a gain of >8.4 dBi and the stable radiation patterns with half‐power beam width wider than of 65°. According to mentioned experimental results, the presented antenna can be used in the microcell base stations for Global System for Mobile, Code Division Multiple Access, and Long‐Term Evolution services.
Combined influence of nano‐CaCO3 and polyvinyl alcohol fibers on fresh and mechanical performance of concrete incorporating fly ash

In this investigation, the combined influence of polyvinyl alcohol (PVA) fibers and nano‐CaCO3 particles on fresh and mechanical performance of concrete containing fly ash was assessed. In the concrete, Portland cement was replaced with 1, 2, 3, and 4% (by weight) of nano‐CaCO3. PVA fibers were added to the concrete at a dosage of 0.05, 0.10, 0.15, and 0.2% (by volume). The flowability of the fresh concrete was assessed using slump and slump flow measurements. The mechanical properties of the concrete evaluated included compressive and flexural strength as well as elastic modulus under both compression and flexure conditions. Our results showed that the workability of the concrete decreased with increases in nano‐CaCO3 and PVA fiber content. When the dosage of nano‐CaCO3 was no more than 3%, the flexural and compressive elastic modulus, flexural, and compressive strength of the concrete increased with nano‐CaCO3 content. However, these mechanical property values decreased when the dosage of nano‐CaCO3 increased from 3 to 4%. When the fiber content was less than 0.15%, the compressive and flexural strength and elastic modulus of the concrete increased with fiber content. However, these values began to decrease as the PVA fiber dosage increased from 0.15 to 0.2%.
Droop-Free Distributed Control for AC Microgrids With Precisely Regulated Voltage Variance and Admissible Voltage Profile Guarantees

In this paper, we propose a droop-free distributed cooperative control with precisely regulated voltage variance and admissible voltage profile guarantees for AC microgrids. First a distributed voltage variance observer is proposed and proven to be able to converge to global voltage variance using only local measurements and information from neighboring distributed generators (DGs). A droop-free distributed control with average voltage regulator, voltage variance regulator, and relaxed reactive power regulator is then designed and shown to be able to achieve the regulation of average voltage and voltage variance and relaxed reactive power sharing in steady-state. For relaxed reactive power sharing, one special DG that could be a community-owned or utility-owned DG will not participate in reactive power sharing and this flexibility is utilized to regulate the voltage profile. The small-signal stability of the system with the proposed control is evaluated by measurement-based Prony analysis, which can also guide the control parameter selection. It is also shown that the steady-state solution of the proposed control can be obtained by solving a set of nonlinear equations, which allows more efficient evaluation of the control performance under different operating conditions and various controller settings. To validate the performance of the proposed control, extensive real-time simulation studies are performed in OPAL-RT on a four-DG test microgrid.
The Role of Optical Wireless Communication Technologies in 5G/6G and IoT Solutions: Prospects, Directions, and Challenges

The upcoming fifth- and sixth-generation (5G and 6G, respectively) communication systems are expected to deal with enormous advances compared to the existing fourth-generation communication system. The few important and common issues related to the service quality of 5G and 6G communication systems are high capacity, massive connectivity, low latency, high security, low-energy consumption, high quality of experience, and reliable connectivity. Of course, 6G communication will provide several-fold improved performances compared to the 5G communication regarding these issues. The Internet of Things (IoT) based on the tactile internet will also be an essential part of 5G-and-beyond (5GB) (e.g., 5G and 6G) communication systems. Accordingly, 5GB wireless networks will face numerous challenges in supporting the extensive verities of heterogeneous traffic and in satisfying the mentioned service-quality-related parameters. Optical wireless communication (OWC), along with many other wireless technologies, is a promising candidate for serving the demands of 5GB communication systems. This review paper clearly presents how OWC technologies, such as visible light communication, light fidelity, optical camera communication, and free space optics communication, will be an effective solution for successful deployment of 5G/6G and IoT systems.
Graphene sensing meshes for densely distributed strain field monitoring

The objective of this study is to design and validate distributed strain field monitoring using a patterned nanocomposite “sensing mesh” that is coupled with an electrical impedance tomography (EIT) measurement strategy and algorithm. Although EIT has been used in other studies and in conjunction with a piezoresistive thin film for spatial damage detection, different strain components cannot be directly extracted from reconstructed EIT conductivity maps. Therefore, this study seeks to address this issue by patterning piezoresistive graphene-based thin films to form a mesh-like pattern. The high aspect ratio of each nanocomposite grid interconnect acts as a linear distributed strain sensor, capable of resolving strains along the entire length and direction of the element. This study first began with the design, fabrication, and characterization of the strain sensing response of a graphene-based thin film of high strain sensitivity. Second, the strain-sensitive film was spray-coated onto patterned polymer substrates to form the sensing meshes, which were then subjected to load tests. Upon validating distributed strain field monitoring through EIT, its applicability for field implementation and damage characterization was also demonstrated by instrumenting sensing meshes in the column of a seven-story reinforced-concrete building subjected to shaking table earthquake excitations. The large-scale shaking table test results successfully validated distributed damage detection.
Effect of resistive and aerobic exercise on reducing insulin sensitivity during pregnancy.

Aims: The purpose of this study was to evaluate whether a combined resistive and aerobic training program would improve insulin sensitivity compared with aerobic training alone in pregnant women. Place and Duration of Study: Department of Obstetrics and Gynecology, Out Patient Clinic at El Mataria Teaching Hospital, between January and July 2014. Methodology: This study was carried out upon forty primipara pregnant women, who had insulin resistance, their age ranged from 25 to 35 years and their gestational age ranged from 20 to 24 weeks. They were divided into two groups equal in number, group (A) who performed resistance exercise and aerobic exercise (RE and AE) and group (B) who performed who aerobic exercise only(AE only). Original Research Article Embaby et al.; BJMMR, 9(7): 1-6, 2015; Article no.BJMMR. 16269 2 Assessment of all subjects in both groups (A&B) was carried out at the beginning of the study and at 37 weeks of gestation using HOMA test. Results: There was a highly statistically significance decrease in insulin resistance in both groups where the p value was (0.0001) favoring group (A). Conclusion: Adding resistance exercise to aerobic exercise had a greater effect on improving insulin sensitivity than aerobic exercise only.
Tooth Surface Modelling and Mesh Behaviors for Paralleled Beveloid Gears

This paper proposed a new tooth surface modeling method for beveloid gear based on the real cutter surface using two orthogonal variables. Then, the analytical mesh model with and without misalignments were derived and solved to study the influences of geometry design parameters on contact behaviors for paralleled beveloid gear pair. Loaded tooth contact analysis is used to validate the proposed mesh model by abaqus software, and the error is below 5%. Results suggest that the increase in pressure, cone, and helical angles enlarge the contact area for meshing without misalignments. The addendum coefficient has unsubstantial impacts on the contact behaviors. For meshing with axis error in the horizontal direction, the growth of pressure angle, cone angle, helical angle, and addendum coefficient improves the carrying capacity of single tooth. But the transmission error deteriorates with the increase in pressure, cone, and helical angles. All three types of misalignments have little influence on the size of the contact ellipse. The growth of axis errors in horizontal and vertical directions significantly increases the transmission error, but the center distance error has a little influence on the transmission precision.
An Improved UDE-Based Flux-Weakening Control Strategy for IPMSM

Interior permanent magnet synchronous motors (IPMSMs) are usually used in electric vehicle drives and in other applications. In order to enlarge the speed range of IPMSMs, the flux-weakening control method is adopted. The traditional flux-weakening control strategy degrades the control performance because of parameter mismatches caused by variation of motor parameters. An improved uncertainty and disturbance estimator (UDE)-based flux-weakening control strategy is proposed for IPMSM drives in this paper. The parameter tuning method in the UDE-based control is improved. In addition, a flux-weakening adjusting factor is put forward to reduce the torque fluctuation when the operation point switches between the constant torque region and the flux-weakening region. This factor can be adjusted online by a lookup table. Finally, the validity of proposed method is verified by the simulation and experimental results. The results show that the proposed control strategy can effectively enhance the robustness of the system in the flux-weakening region, and make the system switch more smoothly between the constant torque region and the flux-weakening region.
The Cascaded Resonant Converter: A Hybrid Switched-Capacitor Topology With High Power Density and Efficiency

Resonant switched-capacitor (ReSC) converters have efficient utilization of both active and passive components, and hold the potential to achieve higher efficiency and higher power density than conventional switched-capacitor (SC) and magnetic-based converters. This article presents a new hybrid/resonant SC converter topology, comprising two cascaded 2-to-1 ReSC converters, to address high-conversion-ratio applications. The proposed cascaded resonant converter has a simple structure and operation principle and can achieve one of the best overall metrics among popular ReSC topologies. A 36–60-V input 4:1-fixed-ratio bus converter prototype for data center application is designed and constructed. We present detailed design guidelines and discussions to address practical challenges, such as component variations and interstage decoupling requirements. With 48-V input and operating at the typical zero-current switching mode of ReSC converters, the prototype achieves a peak efficiency of 98.85% (including gate drive loss) and a power density of 2500 W/in$^3$, both of which are significantly higher than the state of the art. Furthermore, we propose a zero-voltage switching method to improve light-load efficiency. Through this control method, which greatly reduces the output capacitance loss, the prototype can maintain an efficiency above 97% starting from 3% of the rated load, with a peak of 99.0%.
The impact of a prescribed journal list of disciplinary publishing

In 2007, the Association for Information Systems created a basket of eight journals that claim to bound the discipline. A review of the literature found 41 studies discussing the impact of the basket on scholarly publishing. While the basket of eight has had a positive impact on the impact factors for Information Systems, an increase that has not appeared in the LIS journal set, a review of citations finds a steady increase in the number of basket of eight journals being cited within the basket of eight. This paper discusses the impact the basket of eight has had on cited references.
The benefits and challenges of student-led clinics within an Irish context

Student-led clinics are being established internationally as a means of practice education within a variety of disciplines. These clinics can provide opportunities for students in health care professions to have ‘real life’ clinic experiences while also providing beneficial outcomes for service users. This paper reviews the preliminary experiences from thirteen uni-disciplinary student-led clinics (thirty two students in total) in the disciplines of Occupational Therapy (OT), Speech and Language Therapy (SLT) and Physiotherapy (PT). These clinics were part of the placement experience of the students in an Irish University between 2011 and 2013. Clinical Education Quality Audit (CEQA) questionnaires (Ladyshewsky & Barrie, 1996) were used to explore the student experience of these placements, and practice educators were given an opportunity to discuss the benefits and challenges of the placements with the University Practice Education team. The data collected was analysed using thematic analysis. A number of themes emerged from the data: Environment, Organisational issues, Professional development / growth, and Relationships. These themes highlighted both positive and challenging features of the placement experiences. This paper will discuss the benefits and challenges of these student-led clinics and outline that overcoming challenges may be an additional important aspect of learning in innovative clinical experiences
Real-time emotion recognition system with multiple physiological signals

Emotion is an internal and subjective experience that plays a significant role in human life. There are several methods of recognizing emotions in people, the most authentic of which is using physiological signals, as they are beyond one’s control and strongly correlated with human emotions. This study aims to develop an emotion recognition system based on three physiological signals, namely, brainwave, heartbeat, and facial muscular activity. It utilizes deep neural network (DNN) and the T method of Mahalanobis-Taguchi system (MTS) to process the multiple physiological signals and further recognize the states of human emotion. As such, nine emotions are effectively recognized on a two-dimensional model through the DNN, then compared against several other algorithms, such as MTS, SVM, Naive Bayes, and K-means, where its superior accuracy is validated. Moreover, although the T method only improves the classification accuracy on the valence state, it rather obtains the intensity of emotion in different states. Furthermore, in this study, the proposed DNN is implemented into a wide range of applications for an accurate understanding of the human emotional states, whereas the T method is utilized to respond to the emotional intensity in different states. Finally, a real-time emotion recognition system is developed with DNN as the classifier; this system can directly monitor the variation of the human emotion through reliable and objective emotion analysis results from the physiological signals. Thus, the method can provide useful treatment effect information for robots or assistive apparatus serving activities of daily living.
Comparison of the Financial Standing of Companies Generating Electricity from Renewable Sources and Fossil Fuels: A New Hybrid Approach

Companies operating in the energy sector are under pressure to boost the level of green energy production. The use of renewable energy sources will have a positive impact on the environment, but the basic question is whether power plants that produce electricity using renewable energy sources are in better financial condition than those that use only traditional energy sources. We address the latter using a new hybrid approach that extends prior research by combining three analyses: ratio analysis with a large set of indicators, the Altman model and cluster analysis. To test the statistical significance of differences between groups, Student’s t-test is applied. The sample concerns companies from the Baltic States and Central Europe in the years 2008–2017. The results indicate that in most cases there is no statistical difference in the financial standing of companies that use renewable energy sources and those that generate only fossil fuel-based energy.
Versión española del CSRI: una entrevista para la evaluación de costes en salud mental

The demands and needs for the cost information in psychiatric contexts have multiplied considerably in recent years, but the methodology of data collection has not been developed in the same way. In order to evaluate the costs of community care, a new, instrument, the CSRI (Client Service Receipt Interview) has been developed through interviews with patients and those who take care of them; the questionnaire collects restrospective information on patients services, room accommodations, community services, hospital income, and miscellaneous care. With this information it is possible to calculate the cost of the care of each individual patient. The CSRI was built up in previous research, from relevant parts of previously-developed instruments in the mental health field, that can be adapted to the specific needs of the study being carried out. Since its introduction, the CSRI has been used in more than 40 evaluation studies in the United Kingdom, and there are international versions specifically developed for several European countries. Due to the need to start projects of cost evaluation in mental health in our country, it is necessary to have questionnaires for data collection. The CSRI has been used with success to obtain this sort of information in different studies. This paper describes the adaptation of the questionnaire to the Spanish scene. After our adaptation and verification of the CSRI, there is a Spanish version of the instrument, perfectly applicable to carry out projects of cost evaluation in mental health in Spanish-speaking settings.
Over-the-Air Testing of 5G Communication Systems: Validation of the Test Environment in Simple-Sectored Multiprobe Anechoic Chamber Setups

Over-the-air (OTA) radiated testing is seen as inevitable for 5G antenna systems. The simple-sectored multiprobe anechoic chamber (SS-MPAC) setup is a potential testing candidate for the evaluation of 5G antenna systems under real-world propagation conditions. Validation of emulated channel models in the practical SS-MPAC setup is essential, since it is important to ensure that the target channel models are correctly emulated. Our objective is to detect the joint-angle delay power profile of the reproduced channels in the SS-MPAC setup. In this article, we discuss two joint-angle delay estimation (JADE) algorithms: 1) an existing algorithm with high computation complexity as the reference method and 2) a novel, low-cost, sequential, 1D algorithm. Both numerical simulations and experimental verification measurements in a preliminary SS-MPAC setup are provided to validate the two discussed algorithms. The proposed sequential 1D search method is demonstrated to be highly accurate and effective and, therefore, is recommended for validation measurements in SS-MPAC setups. Measurement setup and procedures for test-environment validation are considered as well.