Miracle-dz/UniFAR-FTUs huggingface dataset:
Reply to: Predictors of coronary artery disease in cardiac arrest survivors: coronary angiography for everyone? A single-center retrospective analysis

We thank doctors Barriuso, Irigaray, Rivera and Fernández-Rodríguez for their interest in our paper entitled “Predictors of coronary artery disease in cardiac arrest survivors: coronary angiography for everyone? A single-center retrospective analysis”, which aimed to identify predictors of coronary artery disease in survivors of cardiac arrest (CA), to define the best timing for coronary angiography, and to establish the relationship between coronary artery disease (CAD) and mortality. (1) The authors of this letter raised three important questions regarding our paper. First, regarding the definition of significant CAD being based solely on angiographic assessments. In our paper, the cutoffs for significant CAD were a lumen reduction of at least 50% in the left main artery and of at least 70% in the remaining vessels, as recommended in the recently published American Heart Association (AHA) guidelines. (2) In our center, we routinely perform multiple angiographic views to reduce the error of visual estimation of the degree of coronary stenosis. However, we understand the authors’ point, and herein, it is important to differentiate the concept of intermediate stenosis that might not cause ischemia and unstable plaque that might be the culprit for the event. Intermediate stenosis is classically defined by a lumen reduction of 40 69%(2) in non-left main vessels, although a higher range can be found in some studies. To evaluate whether such lesions cause ischemia, a noninvasive stress test or invasive evaluation with fractional flow reserve (FFR) or instantaneous wave-free ratio (iFR) is recommended. However, recent CA is usually a contraindication for noninvasive stress tests. With regard to coronary physiology, there is very limited evidence for FFR, iFR or other indices in this clinical context, mainly because unstable patients (such as patients after CA) have been excluded from the main trials assessing these techniques, while most studies have focused on chronic coronary syndrome or non-culprit lesions of acute coronary syndrome (ACS), such as in the iFR-Swedeheart trial. (3) In addition, there are no strong data to suggest that FFR guidance improves clinical outcomes in ACS. In fact, there is some evidence suggesting that microvascular dysfunction during ACS might compromise the achievement of maximal hyperemia, increasing the number of false negatives with FFR. (4) Additionally, the recent FLOWER-MI study,(5) the only trial directly comparing FFR versus angiography for non-culprit lesions in the ACS setting, did not show superiority of an FFR-based strategy. Thus, there is no evidence that supports invasive physiology to identify the culprit lesion in ACS or after CA. Joana Rigueira1 , Inês Aguiar-Ricardo1 , Pedro Carrilho-Ferreira1 , Miguel Nobre Menezes1 , Sara Pereira1, Pedro S. Morais1, Pedro Canas da Silva1 , Fausto J. Pinto1
High-Intensity Focused Ultrasound Surgery Based on KUKA Robot: A Computer-Assisted Platform for Noninvasive Surgical Treatments on Static and Moving Organs

High-intensity focused ultrasound surgery based on a KUKA robot (HIFUSK) can address unmet clinical needs in the treatment of pathological tissues, such as cancerous tissues. HIFUSK is the marriage of two technologies: robotics and focused ultrasound (FUS). Such a combination results in a surgical treatment that is precise and noninvasive (no incisions, no anesthesia, and no ionizing energy) thanks to robotics and FUS, respectively. Robotic control and machine learning algorithms ensure safety even in case of target motions during therapy. The platform has been validated in dry lab/ex vivo scenarios, and it was preliminarily tested in terms of safety and efficacy during an in vivo test on a large animal model.
Review on the Application of Machine Learning Methods in Landslide Susceptibility Mapping

: Machine learning is a very important in computer science field which has gained attention in numerous applications. This paper reviewed various machine learning methods including supervised and unsupervised learning and highlighted their applications, advantages and disadvantages in landslide susceptibility mapping. The review has also mentioned the challenges of machine learning algorithms for achieving higher performance accuracy from the supervised and unsupervised learning algorithms during landslide susceptibility. Moreover, highlights on the application of deep learning methods as the current research in landslide susceptibility mapping has also been reported. Finally, this paper argued the necessity of thorough preparation of relevant and enough data being significant important to obtain high performance results from the review methods.
Data-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels

The prevailing trend of increasing urbanization and habitat fragmentation makes knowledge of species’ habitat requirements and distribution a crucial factor in conservation and urban planning. Species distribution models (SDMs) offer powerful toolboxes for discriminating the underlying environmental factors driving habitat suitability. Nevertheless, challenges in SDMs emerge if multiple data sets - often sampled with different intention and therefore sampling scheme – can complement each other and increase predictive accuracy. Here, we investigate the potential of using recent data integration techniques to model potential habitat and movement corridors for Eurasian red squirrels (Sciurus vulgaris), in an urban area. We constructed hierarchical models integrating data sets of different quality stemming from unstructured on one side and semi-structured wildlife observation campaigns on the other side in a combined likelihood approach and compared the results to modeling techniques based on only one data source - wherein all models were fit with the same selection of environmental variables. Our study highlights the increasing importance of considering multiple data sets for SDMs to enhance their predictive performance. We finally used Circuitscape (version 4.0.5) on the most robust SDM to delineate suitable movement corridors for red squirrels as a basis for planning road mortality mitigation measures. Our results indicate that even though red squirrels are common, urban habitats are rather small and partially lack connectivity along natural connectivity corridors in Berlin. Thus, additional fragmentation could bring the species closer to its limit to persist in urban environments, where our results can act as a template for conservation and management implications.
PCQNet: A Trainable Feedback Scheme of Precoder for the Uplink Multi-User MIMO Systems

Multi-user multiple-input multiple-output (MU-MIMO) technology can significantly improve the spectral and energy efficiencies of wireless networks. In the uplink MU-MIMO systems, the optimal precoder design at the base station utilizes the Lagrange multipliers method and the centralized iterative algorithm to minimize the mean squared error (MSE) of all users under the power constraint. The precoding matrices need to be fed back to the user equipment to explore the potential benefits of the joint transceiver design. We propose a CNN-based compression network named PCQNet to minimize the feedback overhead. We first illustrate the effect of the trainable compression ratios and feedback bits on the MSE between the original precoding matrices and the recovered ones. We then evaluate the block error rates as the performance measure of the centralized implementation with an optimal minimum mean-squared error (MMSE) transceiver. Numerical results show that the proposed PCQNet achieves near-optimal performance compared with other quantized feedback schemes and significantly reduces the feedback overhead with negligible performance degradation.
Sources of Information about Suppliers Used in Purchasing Processes on the B2B Market

: Purpose: The purpose of this article was to identify the sources of information regarding suppliers most often used by manufacturing companies and to define their importance. Design/Methodology/Approach: The considerations based on the analysis of the literature and the results of empirical research indicate that enterprises use both direct forms (such as sales representatives, recommendations of other clients, fairs and exhibitions) and on-line forms (such as suppliers' websites). Specialized industry as sources of information about suppliers. portals as a source of information about suppliers. The thesis is confirmed by the results of empirical research conducted with the computer-assisted telephone interviewing (CATI) technique in medium and large manufacturing companies operating in Poland. Findings: The results of the conducted research indicate that the sources of information concerning new suppliers most frequently indicated by the surveyed companies are visits of sales representatives of suppliers sending the offer by suppliers, suppliers' websites, direct contacts of the management/specialists employed in the enterprise with suppliers, recommendations of other companies and fairs and exhibitions. The results of the conducted research also indicate that for manufacturers the most important sources of information about suppliers were: suppliers' websites, sending the offer by suppliers, direct contacts of the management / specialists employed in the enterprise with suppliers and the visits of sales representatives of suppliers. Practical Implications: The considerations based on the analysis of the literature and the results of empirical research indicate that both direct forms (such as sales representatives, recommendations of other clients, fairs and exhibitions) and electronic on-line forms of contact (such as suppliers' websites, specialized industry portals) play an important role in the B2B market as sources of information about suppliers. Originality/Value: Research on sources of information about suppliers used in purchasing processes on the B2B market is undertaken very rarely. Therefore, the results of studies presented in this article fill the research gap.
Comparison of the accuracy of residents, senior physicians and surrogate decision-makers for predicting hospital mortality of critically ill patients

Objective To compare the predictive performance of residents, senior intensive care unit physicians and surrogates early during intensive care unit stays and to evaluate whether different presentations of prognostic data (probability of survival versus probability of death) influenced their performance. Methods We questioned surrogates and physicians in charge of critically ill patients during the first 48 hours of intensive care unit admission on the patient’s probability of hospital outcome. The question framing (i.e., probability of survival versus probability of death during hospitalization) was randomized. To evaluate the predictive performance, we compared the areas under the ROC curves (AUCs) for hospital outcome between surrogates and physicians’ categories. We also stratified the results according to randomized question framing. Results We interviewed surrogates and physicians on the hospital outcomes of 118 patients. The predictive performance of surrogate decisionmakers was significantly lower than that of physicians (AUC of 0.63 for surrogates, 0.82 for residents, 0.80 for intensive care unit fellows and 0.81 for intensive care unit senior physicians). There was no increase in predictive performance related to physicians’ experience (i.e., senior physicians did not predict outcomes better than junior physicians). Surrogate decisionmakers worsened their prediction performance when they were asked about probability of death instead of probability of survival, but there was no difference for physicians. Conclusion Different predictive performance was observed when comparing surrogate decision-makers and physicians, with no effect of experience on health care professionals’ prediction. Question framing affected the predictive performance of surrogates but not of physicians.
The Effect of a Weak Asthenospheric Layer on Surface Kinematics, Subduction Dynamics and Slab Morphology in the Lower Mantle

On Earth, the velocity at which subducting plates are consumed at their trenches (termed “subduction rate” herein) is typically 3 times higher than trench migration velocities. The subduction rate is also 5 times higher than estimated lower mantle slab sinking rates. Using simple kinematic analyses, we show that if this present‐day “kinematic state” operated into the past, the subducting lithosphere should have accumulated and folded beneath near‐stationary trenches. These predictions are consistent with seismic tomography, which images localized and widened lower‐mantle slab piles. They are, however, at odds with most dynamic‐subduction models, which predict rapid trench retreat and inclined slabs in the mantle transition zone. We test the hypothesis that a weak asthenospheric layer (WAL), between the lithosphere‐asthenosphere boundary and 220 km depth, compatible with geophysical constraints, can remedy the discrepancies between numerical models and observations. The WAL lubricates the base of the lithosphere, increases the subduction rate while reducing trench retreat. As a consequence, simulations featuring a WAL predict slab accumulation at the mantle transition zone, and thicker, folded slabs in the lower mantle. A WAL viscosity only 2–5 times lower than that of the adjacent mantle is sufficient to shift subduction regimes toward a mode of vertical slab sinking and folding beneath near‐stationary trenches, across a wide range of model parameters, producing surface and slab velocities close to those observed at the present‐day. These findings provide support for the existence of a weak asthenosphere beneath Earth's lithosphere, complementing independent evidence from various geophysical data.
Recommended Improvements for Online Learning Platforms Based on Users’ Experience in the Sultanate of Oman

The Covid-19 pandemic has seen an increasing use of video conferencing software as e-learning platforms. Students and faculty members face many challenges in using these platforms as part of the teaching and learning process, including technical problems. This paper reviews these challenges and offers solutions to improve the experience. A descriptive-analytical approach was used, with the researchers collecting data from the literature and from questionnaires distributed to 32 faculty members and to 104 students of higher education institutions in the Sultanate of Oman. This paper suggests improvements to enhance the experience of e-learning platforms, from the user perspective in the higher Education Institutions-Sultanate of Oman.
A 5.9 mW E-/W-Band SiGe-HBT LNA With 48 GHz 3-dB Bandwidth and 4.5-dB Noise Figure

The theory, design, and implementation of a millimeter-wave (mm-wave) two-stage common-emitter (CE) low noise amplifier (LNA) using a 130-nm silicon-germanium (SiGe):C Bipolar CMOS technology is presented. The LNA was optimized for wideband performance from 62 to 110 GHz for both mm-wave radar/sensing and wireless communication applications. A two-stage broadband noise and impedance matching technique is used to obtain a relativity flat gain (13.5 dB) and noise figure (NF) (4.5 dB) across the E-/W-band. Low-voltage $(V_{\text {CC}}=0.7\,\,\text {V})$ and low-power (5.9 mW) operation is achieved by forward biasing the base–collector junction, while the wideband capability is further improved by a T-type input matching network utilizing constant quality factor curves. To the best of authors’ knowledge, the presented LNA has the widest 3-dB bandwidth with the lowest power consumption in the literature for silicon-based E-/W-band LNAs.
Learning from/in Middle East and North Africa Writing Centers: Negotiating Access and Diversity

The Middle East and North Africa (MENA) region comprises a vast area among three continents—Europe, Asia, and Africa. While there are no standardized lists of MENA countries, the following countries and territories, in alphabetical order, are most generally included: Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Malta, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, West Bank and Gaza, and Yemen. Afghanistan, Ethiopia, Mauritania, Sudan, and Turkey may also be named. While this lack of standardization makes it difficult to settle on a population size, the Middle East North Africa Regional Architecture project estimates the number at 569 million (McKee, Keulertz, Habibi, Mulligan, & Woertz, 2017). The MENA region is widely diverse economically, encompassing both wealthy, oil-rich states and resource-scarce countries. Although Islam is the dominant religion in most of the MENA countries, Islam itself contains many sects, and a
Coherent X-Ray Optics

1. X-ray wave-fields in free space 2. X-ray interactions with matter 3. X-ray sources, optical elements, and detectors 4. Coherent X-ray imaging 5. Singular X-ray optics Appendix A: Review of Fourier analysis Appendix B: Fresnel scaling theorem Appendix C: Reciprocity theorem for monochromatic sclalar fields
Quasiclassical analysis of the gross-shell structure in a deformed oscillator potential

The quasiclassical approximation for the oscillating component of the single-particle level density and of the shell correction to the nuclear binding energy is derived. The oscillator potential is used as a basis. The results are compared with numerical calculations for an oscillator potential and with the quasiclassical calculations for an ellipsoidal potential well.
NEUTRINO OSCILLATION FROM HIDDEN GRB JETS

Collapsars are the likely progenitors of Long GRBs (lGRBs). lGRBs have been observed to last for thousands to tens of thousands of seconds, thus making unlikely the neutrino-driven engine as the main mechanism for driving the jets. In this context, the Blandford-Znajek mechanism seems likely to explain the production of rotational-axis directed jets with out the need for large accretion rates. These engines, require magnetic fields between 10 12 G < B < 10 15 G threading the innerdisk, Kerr-BH region to exist. We derive the neutrino self-energy and the effective potential up to O(1/M 4 W ) in a weakly and highly magnetized GRB fireball flow which is mad e up of electrons, protons, neutrons and their antiparticles. We consider neutrino energies of 1-100 MeV which are produced during stellar collapse, merger events or in the fireball itself by electron-positron annihilation, inv erse beta decay and nucleonic bremsstrahlung processes. Many of these neutrinos propagate through the fireball and may osc illate resonantly. Using two-neutrino mixing we study the possibility of these oscillations.
Pathways from Exposure to Community Violence to Bullying Victimization among African American Adolescents in Chicago’s Southside

The present study proposes and examines the pathways from exposure to community violence to bullying victimization through the influences of depression, exposure to peer delinquency, and drug use among 638 African American adolescents (aged 12–22) from low-resourced neighborhoods in Chicago’s Southside. The study found that African American adolescents who were exposed to community violence were likely at risk of bullying victimization, depression, exposure to peer delinquency, and drug use. Depression can heighten the risk of bullying victimization. These findings have implications for future research.
“Would You Like to Test Drive the New Library Website?” Implementing Guerrilla Usability Testing at Academic Libraries

Nielsen, J. (1993). Iterative User Interface Design. IEEE Computer, 26(11), 32-41. Nielsen, J. (1994). Estimating the number of subjects needed for a thinking aloud test. International Journal of HumanComputer Studies, 41(3), 385-397. Nielsen, J. (2008). 25 Years in Usability. www.useit. com/alertbox/25-years-usability.html Pirker, M. (2016, March 24). 7 Step Guide to Guerrilla Usability Testing: DIY Usability Testing Method. https://userbrain.net/blog/7-step-guide-guerrilla-usability-testing-diy-usability-testing-method Unger, R. , Warfel, T. Z. (2011, February 15). Getting Guerrilla With It. UX Magazine. https://uxmag.com/articles/getting-guerrilla-with-it Wee, M. , Jovanovich, M. , Humphreys, D. (2015, September 1). The Joy of UXing: The beginners guide to UX design. https://www.peakusability. com.au/articles/the-joy-of-uxing-beginners-guide Redesigning websites based on testing “can substantially improve usability” (Nielsen, 1993). However, many avoid it. • Research seen “expensive and time-consuming” (Unger & Warfel, 2011) • Belief that user tests are for large budgets only • Management hesitant to invest resources into unproven projects Thank you for participating in our Usability Study. We’re trying to get feedback on website we are working on so we can see how it works with real users. We’re going to go through a series of tasks and take notes on your responses to figure out how we can improve the site. It should take around 5 minutes.
Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition

Time-frequency (TF) masks are widely used in speech enhancement (SE). However, accurately estimating TF masks from noisy speech remains a challenge to both statistical or neural network (NN) approaches. Statistical model based mask estimation usually depends on a good parameter initialization, while NN-based method relies on setting proper and stable learning targets. To address these issues, we propose to extract TF speech structure from clean speech and partition noisy speech spectrogram into mutually exclusive regions. We investigate modeling clean speech by utterance-specific narrowband complex Gaussian mixture models to derive the regions, and using the region targets to supervise the training of UNet++, a high-performance NN, for predicting regions from noisy speech. For multichannel SE, we consider two scenarios of using speech regions: 1) integrating the regions with TF masks by constraining the mask values or the model parameter updates, and 2) using the predicted regions in place of TF masks. For single-channel SE, we consider using the region targets to improve TF mask targets. Furthermore, we propose to use UNet++ for TF mask estimation. Our experiment results on speech recognition (CHiME-3) and SE (CHiME-3 and LibriSpeech) have demonstrated the effectiveness of our proposed approach of modeling speech region structure to improve TF masks for speech recognition and enhancement.
FPGA-Based Hardware Accelerator on Portable Equipment for EEG Signal Patterns Recognition

Electroencephalogram (EEG) is a recording of comprehensive reflection of physiological brain activities. Because of many reasons, however, including noises of heartbeat artifacts and muscular movements, there are complex challenges for efficient EEG signal classification. The Convolutional Neural Networks (CNN) is considered a promising tool for extracting data features. A deep neural network can detect the deeper-level features with a multilayer through nonlinear mapping. However, there are few viable deep learning algorithms applied to BCI systems. This study proposes a more effective acquisition and processing HW-SW method for EEG biosignal. First, we use a consumer-grade EEG acquisition device to record EEG signals. Short-time Fourier transform (STFT) and Continuous Wavelet Transform (CWT) methods will be used for data preprocessing. Compared with other algorithms, the CWT-CNN algorithm shows a better classification accuracy. The research result shows that the best classification accuracy of the CWT-CNN algorithm is 91.65%. On the other side, CNN inference requires many convolution operations. We further propose a lightweight CNN inference hardware accelerator framework to speed up inference calculation, and we verify and evaluate its performance. The proposed framework performs network tasks quickly and precisely while using less logical resources on the PYNQ-Z2 FPGA development board.