Miracle-dz/UniFAR-FTUs huggingface dataset:
Big Data for a Big Problem: Precision Medicine of Stroke in Neurocritical Care.

Critical Care Medicine www.ccmjournal. org 1189 6. Waikar SS, Bonventre JV: Creatinine kinetics and the definition of acute kidney injury. J Am Soc Nephrol 2009; 20:672–679 7. Levin A, Stevens PE: Summary of KDIGO 2012 CKD Guideline: Behind the scenes, need for guidance, and a framework for moving forward. Kidney Int 2014; 85:49–61 8. Zeng X, McMahon GM, Brunelli SM, et al: Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol 2014; 9:12–20 9. Libório AB, Leite TT, Neves FM, et al: AKI complications in critically ill patients: Association with mortality rates and RRT. Clin J Am Soc Nephrol 2015; 10:21–28 10. Chawla LS, Amdur RL, Amodeo S, et al: The severity of acute kidney injury predicts progression to chronic kidney disease. Kidney Int 2011; 79:1361–1369 11. Torio CM, Andrews RM: National Inpatient Hospital Costs: The Most Expensive Conditions by Payer, 2011. Statistical Brief #160, August 2013. Available at: https://hcup-us.ahrq. gov/reports/statbriefs/ sb160.jsp. Accessed March 19, 2018 12. Koyner JL, Carey KA, Edelson DP, et al: The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model. Crit Care Med 2018; 46:1070–1077 13. Thottakkara P, Ozrazgat-Baslanti T, Hupf BB, et al: Application of machine learning techniques to high-dimensional clinical data to forecast postoperative complications. PLoS One 2016; 11:e0155705 14. Davis SE, Lasko TA, Chen G, et al: Calibration drift in regression and machine learning models for acute kidney injury. J Am Med Inform Assoc 2017; 24:1052–1061 15. Kate RJ, Perez RM, Mazumdar D, et al: Prediction and detection models for acute kidney injury in hospitalized older adults. BMC Med Inform Decis Mak 2016; 16:39 16. Singer JD, Willett JB: It’s about time: Using discrete-time survival analysis to study duration and the timing of events. J Educ Stat 1993; 18:155–195 17. Moran SM, Myers BD: Course of acute renal failure studied by a model of creatinine kinetics. Kidney Int 1985; 27:928–937 18. Star RA: Treatment of acute renal failure. Kidney Int 1998; 54:1817–1831 19. Moore PK, Hsu RK, Liu KD: Management of acute kidney injury: Core curriculum 2018. Am J Kidney Dis 2018 Feb 22. [Epub ahead of print] 20. Haines RW, Lin SP, Hewson R, et al: Acute kidney injury in trauma patients admitted to critical care: Development and validation of a diagnostic prediction model. Sci Rep 2018; 8:3665
Patch Angioplasty or Primary Closure Following Carotid Endarterectomy for Symptomatic Carotid Artery Stenosis

Abstract Objectives Guidelines recommend routine patching to prevent restenosis following carotid endarterectomy, mainly based on studies performed many years ago with different perioperative care and medical treatment compared with current standards. Aim of the present study was to compare primary closure (PRC) versus patch closure (PAC) in a contemporary cohort of patients. Methods Consecutive patients treated by carotid endarterectomy for symptomatic stenosis between January 2006 and April 2016 were retrospectively analyzed. Primary outcome was restenosis at 6 weeks and 1 year and occurrence of ipsilateral stroke. Secondary outcomes were mortality, complications, and reintervention rates. Results Five hundred carotid artery endarterectomies were performed. Fifty-nine patients were excluded because eversion endarterectomy was performed or because they were asymptomatic. PRC was performed in 349 and PAC in 92 patients. Restenosis at 6 weeks was 6.0% in the PAC group versus 3.0% in the PRC group (p = 0.200). Restenosis at 1 year was 31.6 versus 14.1%, respectively (p = 0.104). No difference was found for stroke (3.4 vs 1.1%, p = 0.319), death (1.1 vs 0.0%, p = 0.584), or other complications (1.1 vs 0.0%, p = 0.584), respectively. Conclusions It remains unclear whether routine patching should be recommended for all patients. A strategy of selective patching compared with routine patching, based on internal carotid artery diameter and other patient characteristics, deserves further investigation.
Sparse Gradient Based Structured Matrix Decomposition for Salient Object Detection

In the salient object detection, the given image can be decomposed into background regions (low-rank part) and salient regions (sparse part). In this paper, we present a novel sparse gradient-based structured matrix decomposition model for salient object detection. We use the ${l_{1}}$ norm of logistic function on the singular values to approximate the rank function, which avoid over-penalized problem of the nuclear norm. And a group sparsity induced norm regularization is imposed on the salient part to explore the relationship among superpixels. In order to widen the gap between salient regions and background regions in feature space, we suggest a sparse gradient regularization to replace the conventional Laplacian regularization. Finally, the model is solved through an augmented Lagrange multipliers method, and high-level priors are embedded into our model to promote the performance. Experiments indicate that the proposed method performs better in terms of various evaluation metrics than the state-of-the-art methods.
Triple-Mode and Triple-Band Cavity Bandpass Filter on Triplet Topology With Controllable Transmission Zeros

On the basis of triplet and its properties, a class of triple-mode and triple-band narrow-band bandpass filters is presented and designed by simultaneously exploiting the three resonant modes in a single rectangular cavity: TE101, TE011, and TM110 modes. The input/output ports of the proposed filter are formed by coupling a waveguide feed to a slot on the side wall of a rectangular cavity. These resonant modes are excited by making use of the position and shape of the slots at input/output of the rectangular cavity without any intra-cavity coupling structure. Besides three poles within the desired passband, a pair of transmission zeros (TZs) can be produced and controlled to appear at the inner or outer sides of this passband. Due to emergence of the three resonant modes and realization of a pair of TZs, a highly attenuated and sharpened filtering selectivity is achieved. In order to verify the proposed approach, two filter prototypes are in final fabricated and measured.
A Novel Physical Layer Security Scheme in OFDM-Based Cognitive Radio Networks

In this paper, a physical-layer-security scheme for an underlay relay-based cognitive radio network (CRN) that uses orthogonal frequency-division multiplexing (OFDM) as the medium access technique is proposed. Resource allocation in relay-aided CRNs becomes a hard problem especially if it is under security threat. Different from conventional relay-based OFDM schemes, in the paper, we consider the relay network which has two dedicated relay nodes; one relay which is capable of subcarrier mapping forward the received signal to the destination and the other sends a jamming signal to add noise to the signal received by the eavesdropper. Optimization is performed under a unified framework where power allocation at the source node, power allocation, and subcarrier mapping in the relay network are optimized to maximize the secrecy rate of the CRN while satisfying the maximum transmission power constraints and the interference threshold of the PU. The power allocation problem at the forwarding relaying node is a non-convex optimization problem. Therefore, at first, the optimization problem is simplified and a closed-form solution is obtained which satisfies the maximum PU interference constraint. Afterward, the optimization problem is solved for satisfying the maximum transmission power constraint. An algorithm is also proposed for subcarrier mapping at the forwarding relaying node. The proposed power allocation method and a subcarrier mapping scheme have low complexity, compared with the baseline schemes. Finally, simulation results are provided for different parameters to show the performance improvement of the proposed scheme in terms of secrecy rate.
A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendered machine analysis of facial micro-expressions possible today, in contrast to decades ago when it was primarily the domain of psychiatrists where analysis was largely manual. Indeed, although the study of facial micro-expressions is a well-established field in psychology, it is still relatively new from the computational perspective with many interesting problems. In this survey, we present a comprehensive review of state-of-the-art databases and methods for micro-expressions spotting and recognition. Individual stages involved in the automation of these tasks are also described and reviewed at length. In addition, we also deliberate on the challenges and future directions in this growing field of automatic facial micro-expression analysis.
The need for an alternative method to determine intravascular volumes

Abstract It is well described that numerous environmental factors, including exercise, modulate plasma volume (PV). These modulations prove problematic when a number of haematological markers are measured as a concentration in blood plasma. A primary example is haemoglobin concentration ([Hb]), a marker of erythropoiesis commonly used within medicine and also used to detect blood doping. Natural changes in PV can confound [Hb] values when a volume change is detected rather than a true change in haemoglobin mass (Hbmass) (e.g. volume expansion resulting in a [Hb] decrease and pseudo-anemia vs. Hbmass decline resulting in anaemia). Currently, there is no simple solution to correct for PV shifts, and this has proven problematic when monitoring volumetric health markers in clinical and anti-doping settings. This narrative review explores the influence that PV shifts have on volumetric biomarkers, such as [Hb]. The progressive expansion in PV observed during multi-day endurance events will be summarised, and the observed impact PV variance has on concentration-based markers will be quantified. From this, the need for alternative methods to correct [Hb] for volume fluctuations is highlighted. Available methods for calculating intravascular volumes are then discussed, with a focus on a recently developed approach using a panel of ‘volume descriptive’ biomarkers from a standard blood test. Finally, the practical applications of this novel PV blood test within both anti-doping and clinical settings will be examined.
A comparison of power system signal detrending algorithms

Wide Area Measurement Systems (WAMS) have facilitated tracking of oscillations in power system response signals. This has provided an impetus for application of signal measurement-based modal detection methods such as matrix pencil and Prony analysis. Detrending, which means removal of trend in a signal, is a pre-requisite for effective functioning of these modal detection methods. In this work, performance of three methods of detrending viz., Center-of-Inertia (COI)-based detrending, MATLAB function-based detrending and ‘Zhou’ detrending are compared with particular reference to power system signals. It is indicated that COI-based detrending is better suited to detection of modes from slip signals of generators.
Is a Bimodal Force-Time Curve Related to Countermovement Jump Performance?

A countermovement jump (CMJ) represents one of the most frequently used performance tests for monitoring neuromuscular function in athletes. An often-overlooked feature that may provide some useful diagnostic information is the actual shape of the force-time curve. The aim of this study was therefore to consider how the shape of the force-time curve influences jump performance. Thirty-three male rugby union players performed two CMJs on a force plate, with discrete variables and continuous curve analysis used. The subjects were dichotomized based on shape of the force-time curve during the propulsion phase and by jump height. The differences between the unimodal and bimodal groups were unclear for jump height (ES = 0.28, ±0.58) and reactive strength index-modified (ES = −0.30, ±0.59). A substantial difference between high (40.2 ± 2.9 cm) and low (31.2 ± 3.2 cm) jumpers only existed in the late propulsion phase by 79.0% to 97.0% of the normalized force-time curve. A bimodal force-time curve is not representative of an optimal pattern of performance and simply reflects an inefficient stretch-shortening cycle. The inter-individual variability that exists in braking COM displacement renders temporal phase analysis impractical in cross-sectional type studies.
Seasonal variations of the gravity wave momentum flux in the Antarctic mesosphere and lower thermosphere

Airglow imager and dynasonde/imaging Doppler interferometer (IDI) radar wind measurements at Halley Station, Antarctica (75.6degreesS, 26.6degreesW) have been used to estimate the seasonal variation of the vertical fluxes of horizontal momentum carried by high-frequency atmospheric gravity waves. The cross-correlation coefficients between the vertical and horizontal wind perturbations were calculated from sodium (Na) airglow imager data collected during the austral winter seasons of 2000 and 2001. These were combined with wind velocity variances from coincident radar measurements to estimate the daily averaged upper limit of the vertical flux of horizontal momentum due to gravity waves. The resulting momentum flux at the Na airglow altitudes, while displaying a large day-to-day variability, showed a marked rotation from the northwest to the southeast throughout the winter season. Calculations show that this rotation is consistent with seasonal changes in the wind field filtering of gravity waves below the Na airglow region. The calculations also indicate that while the magnitude of the meridional wind is small, this filtering leads to the observed seasonal changes in the meridional momentum flux.
SCR-Based ESD Protection Using a Penta-Well for 5 V Applications

This paper proposes a new structure of silicon controlled rectifier (SCR)-based ESD protection circuit using a penta-well for ESD protection in 5 V applications. The proposed circuit exhibits higher holding voltage and current-driving capability than low Ron SCR (LRSCR) ESD protection circuits. The existing LRSCR ESD protection circuit and the proposed ESD protection circuit were fabricated using the 0.18 <inline-formula> <tex-math notation="LaTeX">$\mu$ </tex-math></inline-formula>m BCD process. The electrical and latch-up characteristics were compared and analyzed using transmission line pulse measurement and a transient-induced latch-up test.
Flexible and Printed PPG Sensors for Estimation of Drowsiness

We report printed flexible optoelectronic sensors composed of red organic light-emitting diodes (OLEDs) and organic photodiodes (OPDs) for detection of various biological signals in a photoplethysmograph (PPG) device. Fabricated flexible OLEDs achieved maximum luminance >1000 cd/m<sup>2</sup> at 9 V, with peak at 640 nm. Maximum flexible OPD photosensitivity for the poly(3-hexylthiophene-2, 5-diyl) and phenyl-C61-butyric acid methyl ester (PCBM) heterojunction is <inline-formula> <tex-math notation="LaTeX">$ {2} \times {10}^{{2}}$ </tex-math></inline-formula> at 0 V and 1.76 at −1 V, irradiated with 1.2 mW/cm<sup>2</sup> at 660 nm. The diketopyrrolopyrrole thieno [3,2-b]thiophene blended with PCBM OPDs with poly (3,4-ethylenedioxythiophene):polystyrene sulfonate anode showed photosensitivity = 84 at −1 V bias to almost <inline-formula> <tex-math notation="LaTeX">${6} \times {10}^{{4}}$ </tex-math></inline-formula> at 0 V accompanied by low dark current (<inline-formula> <tex-math notation="LaTeX">${9.5} \times {10}^{-{8}}$ </tex-math></inline-formula> A/cm<sup>2</sup> at −1 V). PPG signals were successfully detected using the developed flexible PPG sensor and the conventional driving circuit. Human studies were conducted to evaluate the flexible PPG sensor performance in practical applications. Subject drowsiness was estimated from heart rate variability, extracted from the PPG signals, using machine learning algorithms. The flexible PPG sensor achieved 79.2% accuracy and 72.1% area under the receiver (AUC) to predict drowsiness (60-s window), which are meaningful results compared with conventional PPG sensors (83.3% accuracy and 69% AUC). Drowsiness estimation experiments using two PPG signals showed that the flexible PPG sensor achieved similar or better performance compared to conventional PPG sensors.
Supervised learning with generalized tensor networks

Tensor networks have found a wide use in a variety of applications in physics and computer science, recently leading to both theoretical insights as well as practical algorithms in machine learning. In this work we explore the connection between tensor networks and probabilistic graphical models, and show that it motivates the definition of generalized tensor networks where information from a tensor can be copied and reused in other parts of the network. We discuss the relationship between generalized tensor network architectures used in quantum physics, such as String-Bond States and Entangled Plaquette States, and architectures commonly used in machine learning. We provide an algorithm to train these networks in a supervised learning context and show that they overcome the limitations of regular tensor networks in higher dimensions, while keeping the computation efficient. A method to combine neural networks and tensor networks as part of a common deep learning architecture is also introduced. We benchmark our algorithm for several generalized tensor network architectures on the task of classifying images and sounds, and show that they outperform previously introduced tensor network algorithms. Some of the models we consider can be realized on a quantum computer and may guide the development of near-term quantum machine learning architectures.
Toward Blockchains for Health-Care Systems: Applying the Bilinear Pairing Technology to Ensure Privacy Protection and Accuracy in Data Sharing

A health-care system gathers comprehensive physiological information and medical records, making its data more important than ever. For example, for years now, the National Health Insurance Administration (https://www.nhi.gov.tw/English/) of Taiwan has requested every doctor, whether in a medical center or private clinic, to upload the diagnosis result, treatment, and prescription. These anamneses have also been stored in the National Health Insurance Research Database (http://nhird.nhri.org.tw/en/index.html) since 1 March 1995, and 99.9% of the Taiwanese population have been enrolled since 2014. With this comprehensive database, analytics tools can be run to uncover useful information to further understand the etiological factors for rare disorders. This database is successful primarily because Taiwan is a small but densely populated island, making it relatively easy for the government to collect most, if not all, the anamneses.
Determinants of parasite distribution in Arctic charr populations: catchment structure versus dispersal potential

Abstract Parasite distribution patterns in lotic catchments are driven by the combined influences of unidirectional water flow and the mobility of the most mobile host. However, the importance of such drivers in catchments dominated by lentic habitats are poorly understood. We examined parasite populations of Arctic charr Salvelinus alpinus from a series of linear-connected lakes in northern Norway to assess the generality of lotic-derived catchment-scale parasite assemblage patterns. Our results demonstrated that the abundance of most parasite taxa increased from the upper to lower catchment. Allogenic taxa (piscivorous birds as final host) were present throughout the entire catchment, whereas their autogenic counterparts (charr as final hosts) demonstrated restricted distributions, thus supporting the theory that the mobility of the most mobile host determines taxa-specific parasite distribution patterns. Overall, catchment-wide parasite abundance and distribution patterns in this lentic-dominated system were in accordance with those reported for lotic systems. Additionally, our study highlighted that upper catchment regions may be inadequate reservoirs to facilitate recolonization of parasite communities in the event of downstream environmental perturbations.
Human Depotentiation following Induction of Spike Timing Dependent Plasticity

Depotentiation (DP) is a crucial mechanism for the tuning of memory traces once LTP (Long Term Potentiation) has been induced via learning, artificial procedures, or other activities. Putative unuseful LTP might be abolished via this process. Its deficiency is thought to play a role in pathologies, such as drug induced dyskinesia. However, since it is thought that it represents a mechanism that is linked to the susceptibility to interference during consolidation of a memory trace, it is an important process to consider when therapeutic interventions, such as psychotherapy, are administered. Perhaps a person with an abnormal depotentiation is prone to lose learned effects very easily or on the other end of the spectrum is prone to overload with previously generated unuseful LTP. Perhaps this process partly explains why some disorders and patients are extremely resistant to therapy. The present study seeks to quantify the relationship between LTP and depotentiation in the human brain by using transcranial magnetic stimulation (TMS) over the cortex of healthy participants. The results provide further evidence that depotentiation can be quantified in humans by use of noninvasive brain stimulation techniques. They provide evidence that a nonfocal rhythmic on its own inefficient stimulation, such as a modified thetaburst stimulation, can depotentiate an associative, focal spike timing-dependent PAS (paired associative stimulation)-induced LTP. Therefore, the depotentiation-like process does not seem to be restricted to specific subgroups of synapses that have undergone LTP before. Most importantly, the induced LTP seems highly correlated with the amount of generated depotentiation in healthy individuals. This might be a phenomenon typical of health and might be distorted in brain pathologies, such as dystonia, or dyskinesias. The ratio of LTP/DP might be a valuable marker for potential distortions of persistence versus deletion of memory traces represented by LTP-like plasticity.
Alfvén wave dispersion behavior in single- and multicomponent plasmas

Dispersion relations of driven Alfven waves (AWs) are measured in single- and multicomponent plasmas consisting of mixtures of argon, helium, and oxygen in a magnetized linear cylindrical plasma device VINETA [C. Franck, O. Grulke, and T. Klinger, Phys. Plasmas 9, 3254 (2002)]. The decomposition of the measured three-dimensional magnetic field fluctuations and the corresponding parallel current pattern reveals that the wave field is a superposition of L- and R-wave components. The dispersion relation measurements agree well with calculations based on a multifluid Hall-magnetohydrodynamic model if the plasma resistivity is correctly taken into account.