Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single Session of Straight Line and Change-of-Direction Sprinting per Week Does Not Lead to Different Fitness Improvements in Elite Young Soccer Players

Abstract Beato, M, Bianchi, M, Coratella, G, Merlini, M, and Drust, B. A single session of straight line and change-of-direction sprinting per week does not lead to different fitness improvements in elite young soccer players. J Strength Cond Res 36(2): 518–524, 2022—Effective prescription is especially important in elite soccer players, who have a very limited time to dedicate to specific physical development as a consequence of factors such as congested match schedules and travel. The aim of this study was to compare the effectiveness of one repeated-sprint training (RST) session per week over an 8-week period on physical performance. A second aim was to compare the effect of RST involving straight sprints (RST-SS) or changes of direction (RST-COD). This study used a randomized pre-post parallel group trial design. The elite soccer players were randomly assigned to either an RST-SS (10 players) or RST-COD (10 players). RST-SS was 3 sets of 7 × 30-m sprints with 20-second and 4-minute recovery between sprints and sets, respectively. RST-COD was 3 sets of 7 × 20 + 20 m (one COD of 180°) shuttle sprints with 20-second and 4-minute recovery between sprints and sets, respectively. The physical tests selected were long jump, repeated-sprint ability (RSA) best, RSA mean, 505 agility test, Yo-Yo recovery level 1, 10, 30, and 40 m sprints. RST-SS reported unclear variations in long jump, sprint 30 m, sprint 40 m, RSA best, and RSA mean, whereas RST-COD showed unclear and trivial variations in sprint 10 m, sprint 30 m, sprint 40 m, RSA best, and RSA mean. The between-group analysis did not report any statistical difference. In conclusion, a single session of RST-SS and RST-COD do not improve soccer-specific fitness indicators in elite youth players during the season.
A retrospective study

At present, intravesical Bacillus Calmette-Guerin (BCG) immunotherapy is recommended for prophylaxis purposes after transurethral resectionofbladder tumor,but haschancesof recurrence.Radical cystectomy reduces the riskof recurrence inbladdercancerpatients, butmay have chances of postoperative complications. The objective of the studywas to test the hypothesis that radical cystectomy has overtreatment and definitive BCG immunotherapy has undertreatment in intermediate or high-risk nonmuscle invasive bladder cancer patients. Data regarding biopsies, ultrasound, the computed tomography scan, adopted treatment strategy, treatment-emergent adverse effect, and a follow-up period of 312 patients with confirmed nonmuscle invasive bladder cancer (pTa, pTis, or pT1 stage; intermediate or high-risk cancer) were reviewed. Patientswho had received definitive intravesical BCG immunotherapywere included in BCG group (n=210) and those who underwent radical cystectomy were included in RXC group (n=87). Clinical decision-making for treatment strategies was evaluated for both groups. Cystitis was frequently observed in all patients who receivedBCG immunotherapy. In RXC group, ileus was frequently observed in all patients in early days after the operation. During 2 years of the follow-up period, biopsies, ultrasound, and the computed tomography scan reported that BCG group had fewer numbers of negative cancer patients after treatment than the RXC group after surgery (P< .0001). Total expenditure for BCG immunotherapy was higher than radical cystectomy (22,945±945</patient vs 17,985±545</patient; P< .0001). Definitive BCG immunotherapy had undertreatment and radical cystectomy had overtreatment for intermediate or high-risk invasive bladder cancer patients (level of evidence III). Abbreviations: AUA = The American Urological Association, BCG = Bacillus Calmette-Guerin, CTCAE = Common Terminology Criteria for Adverse Events, DICOM=Digital Imaging and Communications in Medicine, EAU= The European Association of Urology, NCCN = The National Comprehensive Cancer Network, NICE = The National Institute for Health and Care Excellence, SUO = The Society of Urologic Oncology, USFDA = The United States Food Drug and Administration.
Polarization-Insensitive and Angularly Stable Compact Ultrawide Stop-Band Frequency Selective Surface

In this letter, a compact ultrawide stop-band frequency selective surface (FSS) with polarization-insensitive and higher level of angular stability property is presented. It consists of a very simple modified square-ring unit cell that exhibits excellent wideband rejection over the entire ultrawideband (UWB) 2.72–13 GHz range. For TE incident wave, the <−20 dB bandwidth is 67.41% (5.01–10.1 GHz), which is 18.38% more compared to the simple square-ring-type FSS. This structure with the smallest unit cell dimension (0.066λ0 × 0.066λ0 × 0.013λ0) compared to the earlier reported UWB FSSs is printed on a single-layer single-sided FR4 substrate. The design is flexible enough to tune the desired resonant frequency and the operating band by changing the length and width of the resonators. The design concept has been validated through proper measurement. This FSS can be used as a good reflector to enhance the gain of UWB antennas.
When Wireless Charging Meets Fresnel Zones: Even Obstacles Can Enhance Charging Efficiency

Benefitting from the discovery of wireless power transfer (WPT) technology, the wireless rechargeable sensor network (WRSN) becomes a promising way for lifetime extension for wireless sensor networks. However, in practical applications, obstacles can be found almost everywhere throughout the WRSN system. Most prior arts believe that obstacles will always degrade signal strength, they omit such influences for computation simplicity, which contradicts to the instincts of signal propagation, yielding their methods unsuitable for realistic adoptions. In this paper, we explore the wireless signal propagation process and provide a theoretical charging model to enhance charging efficiency by leveraging obstacles. Through utilizing the concept of the Fresnel Zones (FZs), we re-formalize the wireless charging model and discretize charging power to determine the best charging spots as well as charging durations. We model such charging efficiency maximization with obstacles (EMO) problem as a submodular function maximization problem and propose a cost-efficient algorithm with approximation ratio $\frac{{(e - 1)}}{e}(1 - \in )$ to solve it. Finally, test-bed experiments and simulations are conducted to verify that our schemes outperform comparison algorithms by at least 10% in charging efficiency improvement.
A Deep Decomposition of MRI to Explore Neurodegeneration in Alzheimer’s Disease

Deep learning has revolutionized data analysis and particularly medical imaging, providing unprecedented insight to non-linear features. Image decomposition techniques such as Principal Component Analysis have been used for a long time, evolving towards complex non-linear decomposition algorithms. Convolutional networks, and particularly convolutional autoen-coders are known for providing high-level abstract features that describe the internal distribution of data in high-dimensional manifolds. In this work, we aim at gaining a deeper understanding the progression of the disease by predicting neuropsycho-logical test outcomes based solely on MRI data. In order to do so, we perform a self-supervised decomposition of the MRI data using a deep convolutional autoencoder. The distribution of features in the z-layer is then used within a neural network based regression, in order to test whether these imaging-derived biomarkers are related to several neuropsychological tests. The prediction of neuropsychological test outcomes achieved R2 rates up to more than 0.3, with correlations higher than 0.5 in the case of variables heavily linked to neurogedeneration and cognitive state such as the MMSE or the ADAS11 scores.
Maximum-likelihood estimation of emission and attenuation images in 3D PET from multiple energy window measurements

This study explores the feasibility of incorporating energy information into a maximum-likelihood reconstruction of activity and attenuation (MLAA) framework. The attenuation and activity distributions were reconstructed from multiple energy window data, and a scatter function was added to the system model of the algorithm. The proposed energy-based method (MLAA-EB) was evaluated with simulated 3D phantom data, using the geometry and characteristics of a Siemens mMR PET-MR scanner. Results showed that the proposed algorithm is able to compensate for errors in the activity image caused by the incorrect assignment of attenuation values to the segmented MR. This is effective for small objects only, for large objects further solutions need to be found.
An Investigation of Nontraditional Phased Array Components

In this paper, the topologies of the two-channel dual-band terminal-fed printed dipole antenna equipped with a ring coupler, dual-band dipole antenna with the stepped-width conductors, and dipole antenna array equipped with Butler matrix are reported. In this initial design, a coupler and the radiators are placed above an integrated balancing unit (balun) so that a balun transforms terminal-fed dipole input impedance and impedance of a coupler. A ring power coupler is used for allowing feeding dipoles from different ports. So if it is done, then it is possible to form sum and difference radiation patterns (RP) in one integrated module so that it could be used when constructing more complex antenna systems.The realized isolation between sum and difference channels is better than -20 dB over 350 MHz frequency band. The frequency bands of the sum and difference channels overlap frequency band of a ring coupler.The proposed in the second section printed arrangement increases the frequency distance between the lower and higher working bands in comparison with the dual-band antenna on a base of classical center-fed dipoles which was described in Russian Patent no. 2 432 646 published 27.10. 2011.The eight-element dipole antenna array, presented in the last section, comprise Butler matrix in order to form eight independent beams.
A Handheld Olfactory Display For Smell-Enabled VR Games

We describe a class of olfactory displays located at the hand, well-suited to support exploratory and active smelling behavior. We have developed a handheld olfactory display for the HTC Vive VR environment, and validated it in a two-step method that combines qualitative user evaluation with an empirical task-based study. The results of our qualitative study suggest that handheld olfactory displays may enhance a sense of presence in virtual environments. Our validation method is suitable for testing instruments that engage novel forms of smell interaction, and seek to provide clear and consistent output for empirically-validated olfactory research.
Pre-trained Contextualized Representation for Chinese Conversation Topic Classification

Topic classification plays an important role in facilitating security-related applications, which can help people reduce data scope and acquire key information quickly. Conversation is one of the important ways of communication between people. The utterances in a conversation may contain vital clues, such as people’s opinions, emotions and political slants. To explore more effective approaches for Chinese conversational topic classification, in this paper, we propose a neural network architecture with pre-trained contextualized representation. We firstly apply pretrained BERT model to fine-tune and generate the conversational embeddings, which are the inputs of our neural network models. Then we design several models based on neural networks to extract task-oriented advanced features for topic classification. Experimental results indicate that the models based on our neural network architecture all outperform the baseline only fine-tuned with the pre-trained BERT model. It demonstrates that the pretrained representations are effective to Chinese conversational topic classification, and the proposed architecture can further capture the salient features from the representations. And we release the code and dataset of this paper that can be obtained from https://github.com/njoe9/pretrained_representation.
A Detailed Numerical Analysis of the Electric Field Distribution in Rod Antenna Radiated Emission Setups

The measurement of electric field for frequency below 30 MHz is requested by standards applicable both for civil and military applications. All the related measurement setups request the use of a rod antenna placed vertically at an electrically short distance from the equipment under test. The measurements, done placing the rod antenna in the near field of the radio disturbance sources, provide results that depend in a rather complex way from the height of the antenna and from other additional boundary conditions, i.e. different bonding of the counterpoise of the rod antenna to other parts of the setup. In the paper a detailed analysis of the field distribution in the different setups is reported in order to understand which are the optimal conditions to adopt in order to obtain measurement results which provide a real representation of the disturbance field generated by the equipment under test in undisturbed conditions.
Impact of social media marketing efforts on Destination’s brand equity: A study among International Tourists arriving to Sri Lanka

The aim of the study is to investigate the impact of social media marketing efforts on the creation of brand equity of Sri Lanka as a destination for international tourists. The other specific objectives are; to explore the social media marketing efforts of Sri Lanka as destination brand, to investigate the brand equity of Sri Lanka as destination and to recommend suggestions to improve the social media marketing efforts for Sri Lanka as destination brand. Results reveal that all factors under the social media marketing efforts namely entertainment, customization and eWOM are positively contributing to the brand equity of Sri Lanka as a destination. However, the other two factors of social media marketing efforts such as interaction and trendiness are negatively impacting on the brand equity of Sri Lanka as destination. Therefore, it is recommended that destination marketers of Sri Lanka need to give moreattention on the interaction and trendiness of the social media marketing efforts.
Towards total-body modular PET for positronium and quantum entanglement imaging

The purpose of the reported research is (i) the elaboration of the new imaging method based on the in-vivo measurement of properties of positronium produced inside patient during positron emission tomography, and determination of correlations between properties of positronium inside the cancer tissues and histopathological characteristics of cancers, as well as (ii) exploration of possibilities of the determination of the linear polarization of annihilation photons and development of novel prognostic indicators for cancer diagnostics based on the quantum information from (multipartite) entanglement of photons originating from the positronium decay.During PET diagnosis positronium may be trapped inside free volumes between and within molecules of the examined patient. Currently, in the PET technique, the phenomenon of positronium production is neither recorded nor used for imaging. Yet in about 40% cases, the electron-positron annihilation proceeds in the tissue via creation of positronium. The properties of positronium (such as e.g. mean lifetime or ratio of decay rates into two and three photons) depend on the size of the free volumes between atoms and there are indications that they are correlated with the stage of the development of metabolic disorders of the human tissues. Therefore, an image of properties of positronium formed inside the human body may deliver new information complementary to SUV index and useful for the diagnosis.Moreover, recent theoretical studies have proven that the entanglement in the three-photon state from the decay of ortho-positronium survives surprisingly also for mixed scenarios expected in human tissues. Hence, detecting entanglement of photons originating from positronium may enable the extraction of quantum properties of the surrounding tissue environment.We discuss (i) results of the feasibility studies of the positronium mean-lifetime image reconstruction with the total-body PET scanner from plastic scintillators, as well as (ii) results of pilot studies of the mean lifetime of positronium in the healthy and tumorous tissues operated from the patients. Performed experiments show that properties of positronium atoms in uterine tissues operated from human patients reveals meaningful differences between healthy and tumorous tissues. We also discuss results of the feasibility studies of the polarization of annihilation photons with the J-PET tomograph in which annihilation photons interact predominantly via Compton scattering. Registration of both primary and scattered photons enables to determinate the linear polarization of the primary photon on the event by event basis and hence enables to witness the entanglement of annihilation photons in polarization based on Mutually Unbiased Bases. The performed simulations indicate that in the future with the total-body PET and improved time resolution it shall be feasible to reconstruct images of positronium properties in-vivo during the routine PET diagnosis.
Compensation Topologies in IPT Systems: Standards, Requirements, Classification, Analysis, Comparison and Application

Wireless power transfer devices are becoming more relevant and widespread. Therefore, an article is devoted to a review, analysis and comparison of compensation topologies for an inductive power transfer. A new classification of topologies is developed. A lot of attention is paid to the problems of the physical fundamentals of compensation work, standards, safety, and five main topology requirements. It is determined, that topologies with the series primary compensating are the most effective in the IPT for charging devices among the four classical schemes. The series-parallel solution is recommended in case of the low output voltage, minimum size of a secondary side coil is achievable. The series-series solution does not depend on the magnetic coupling coefficient and the load on the resonance frequency. For the convenience of displaying and understanding the information, the comparison results are listed in the tables, graphs and dependencies. The main suitable topologies for a certain application are defined. The given conclusions provide a “one-stop” information source and a selection guide on the application of compensation topologies both in terms of devices and in terms of power level that is the main value of this paper. During literature analysis and recent trends in the market for wireless power transmission devices, the main possible further ways of developing topologies are underlined. First of all, it concerns increasing the frequency of resonance of compensation topologies, the use of multilevel / multi-pulse / multicoils structures, the study of existing high-frequency semiconductors and the development of the semiconductor and magnetic materials.
Molecular Diagnostic and Using Deep Learning Techniques for Predict Functional Recovery of Patients Treated of Cardiovascular Disease

Today, with the development of industry and mechanized life style, the prevalence of the disease is rising steadily as well. Observing at the trend and lifecycle style, its predict that after ten years around 23.6 million people die because of Cardiovascular Disease (CVD). For that reason, aim to use Deep Learning Techniques (DLTs), to analysis stable CVD that would give valuable awareness to decrease misdiagnosis in the Robust Healthcare Industry (RHI). An objective of this paper is first, Molecular diagnosis (MD), and second using Deep Learning Techniques DLTs, to synthesis and characterize to accumulate (raw information) from CVD patients, those who admitted the emergency section between January (2018 to December 2019). We are using Artificial Neural Network (ANN), model characterize to predict CVD patients and configuration, Feature selection (FS), Mean Square Error (MSE), accuracy, sensitivity. The ANN accuracy is 98.4, K-nearest neighbor (KNN) accuracy is 98.01%, Naïve Bayes (NB), accuracy is 96.99%. Decision tree (DT), accuracy is 87.81%. Our robust data driven model explore the efficient accuracy rate to predict CVD patients. The ANN model in term of their efficient in disease analysis, and prognosis of the RHI.
Image Quality Enhancement of Digital Breast Tomosynthesis Images by Deblurring with Deep Residual Convolutional Neural Network

Digital Breast Tomosynthesis (DBT) is widely used for early diagnosis of breast cancer due to its higher detectability compared to mammography. However, since the DBT acquires projection data within a limited angular range, blurring artifact occurs in reconstructed images. In this work, we proposed a method to reduce the blurring artifact in DBT images by applying Deep Residual Convolutional Neural Network (DRCNN), which was shown to be very effective for deblurring caused by camera motion. To evaluate the performance of the proposed method, we calculated Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) and structural similarity index (SSIM) between reference and output image from the proposed network. The results show that the DRCNN reduces the blurring artifact effectively, producing the improved image quality.
3De Interactive Lenses for Visualization in Virtual Environments

We present 3De lens, a technique for focus + context visualization of multi-geometry data. It fuses two categories of lenses (3D and Decal) to become a versatile lens for seamlessly working on multiple geometric representations that commonly coexist in 3D visualizations. In addition, we incorporate our lens into virtual reality as it enables a natural style of direct spatial manipulation for exploratory 3D data analysis. To demonstrate its potential use, we discuss two domain examples in which our lens technique creates customized visualizations of both surfaces and streamlines.
Resource-Bounded Intruders in Denial of Service Attacks

Denial of Service (DoS) attacks have been a serious security concern, as no service is, in principle, protected against them. Although a Dolev-Yao intruder with unlimited resources can trivially render any service unavailable, DoS attacks do not necessarily have to be carried out by such (extremely) powerful intruders. It is useful in practice and more challenging for formal protocol verification to determine whether a service is vulnerable even to resource-bounded intruders that cannot generate or intercept arbitrary large volumes of traffic. This paper proposes a novel, more refined intruder model where the intruder can only consume at most some specified amount of resources in any given time window. Additionally, we propose protocol theories that may contain timeouts and specify service resource usage during protocol execution. In contrast to the existing resource-conscious protocol verification models, our model allows finer and more subtle analysis of DoS problems. We illustrate the power of our approach by representing a number of classes of DoS attacks, such as, Slow, Asymmetric and Amplification DoS attacks, exhausting different types of resources of the target, such as, number of workers, processing power, memory, and network bandwidth. We show that the proposed DoS problem is undecidable in general and is PSPACE-complete for the class of resource-bounded, balanced systems. Finally, we implemented our formal verification model in the rewriting logic tool Maude and analyzed a number of DoS attacks in Maude using Rewriting Modulo SMT in an automated fashion.