Miracle-dz/UniFAR-FTUs huggingface dataset:
Case report of a patient with congenital long QT syndrome Type 2 presenting with electrical storm: do not judge a book by its cover!

Abstract Background Patients with congenital long QT syndrome (LQTS) are at high risk for sudden cardiac death (SCD). Although several triggers can provoke ventricular fibrillation (VF) in patients suffering from LQTS acquired heart disease in addition to LQTS should not be overlooked. Case summary We present a case of a 47-year-old female patient who was diagnosed with congenital LQTS Type 2 at the age of 23 after surviving SCD. At that time, she underwent implantable cardioverter-defibrillator (ICD) implantation and was free of events for 24 years. Recently, the patient was referred to our institution after suffering from an ICD shock during sleep. Upon arrival she developed electrical storm and received overall six ICD shocks. The initial electrocardiogram (ECG) showed atrially triggered ventricular pacing. However, distinct ST segment elevations in the inferior leads could be observed. Thus, coronary angiography was immediately performed and showed subtotal occlusion of the right coronary artery, which was treated by drug-eluting stent implantation. Atrioventricular conduction immediately resumed after revascularization and the following non-paced ECG revealed a prolonged QT interval. Laboratory measurements confirmed acute myocardial infarction with elevated cardiac enzymes. The patient was put on betablockers, dual antiplatelet therapy, and statins and discharged in good condition. Discussion This case report highlights that diagnostic work-up in patients with LQTS presenting with VF should always include the search for additional acquired heart disease such as myocardial infarction, as a potential trigger for electrical storm. Moreover, signs of ischaemia can be discerned even in a paced ECG which should lead to immediate cardiac catheterization.
Adaptive synchronous strategy for distributed machine learning

In distributed machine learning training, bulk synchronous parallel (BSP) and asynchronous parallel (ASP) are two main synchronization methods to help achieve gradient aggregation. However, BSP needs longer training time due to “stragglers” problem, while ASP sacrifices the accuracy due to “gradient staleness” problem. In this article, we propose a distributed training paradigm on parameter server framework called adaptive synchronous strategy (A2S) which improves the BSP and ASP paradigms by adaptively adopting different parallel training schemes for workers with different training speeds. Based on the stale value between the fastest and slowest worker, A2S adaptively adds a relaxed synchronous barrier for fast workers to alleviate gradient staleness, where a differentiated weighting gradient aggregation method is used to reduce the impact of slow gradients. Simultaneously, A2S adopts ASP training for slow workers to eliminate stragglers. Hence, A2S not only improves the “gradient staleness” and “stragglers” problems, but also obtains convergence stability and synchronous gain through synchronous and asynchronous parallel, respectively. Specially, we theoretically proved the convergence of A2S by deriving the regret bound. Moreover, experiment results show that A2S improves accuracy by up to 2.64% and accelerates training by up to 41% more than the state‐of‐the‐art synchronization methods BSP, ASP, stale synchronous parallel (SSP), dynamic SSP, and Sync‐switch.
Trigger Properties of an Ejected-Plasma-Triggered SF Gas Gap for 10-kV Smart Distribution Network

Aimed at developing a rapid control and protection switch for a 10-kV smart distribution network, a gas switch triggered by ejected plasma was designed and tested. The switch met the requirements of fast and reliable triggering at an extremely low operating coefficient. The gas switch employed sulfur hexafluoride (SF6) as its insulating medium for miniaturization requirements and was triggered by capillary discharge excited by a pulse transformer for high potential isolation considerations. The influence of a capillary cavity structure and pulse transformer parameters on the switch trigger characteristics was investigated. The results showed that the plasma ejection was enhanced by increasing trigger energy, but was also saturated with a limited cross section of the magnetic core of the pulse transformer, which determined the maximum transferred trigger energy. Employing a long capillary, shrinking nozzle, and small transformer ratio promoted plasma ejection, resulting in an increase in the triggering reliability and lowering the trigger threshold voltage. A 4-mm capillary cavity with a shrinking nozzle driven by a 37/2 pulse transformer was used to trigger an 80-kV SF6 gas switch at a 4.7% operating coefficient, and 1200 times successive and successful triggering was performed, with the trigger delay ranging from 62.5 to $73~\mu \text{s}$ , which met the technical requirements of rapid control and protection for a 10-kV smart distribution network.
The Prevalence of Electrolyte Imbalances and Their Relationship with Disease Severity in Hospitalized COVID-19 Patients

: Since the identification of COVID-19, its various manifestations have been reported in numerous studies. However, few studies have specifically examined the electrolyte imbalances seen in this disease. Patients with a definitive diagnosis of COVID-19 admitted to our hospital entered this retrospective cross-sectional study. Upon admission of the patients, a blood sample was sent for the analysis of the electrolytes. The relationship between electrolyte imbalances and disease severity, ICU admission, and mortality was also stated. Of 1072 hospitalized patients studied, 657 were men, and 415 were women. The prevalence of hypocalcemia (47.7%), hypophosphatemia (21.1%), hypomagnesemia (15.8%), and hyponatremia (13%) was higher compared to other electrolyte imbalances in these patients. Lower levels of sodium, calcium, and magnesium were seen in severe cases, while higher serum levels of potassium and phosphorus were detected in severe cases and ICU hospitalized patients. Causes such as albumin decrease in inflammation, the role of PTH, and the effect of vitamin D can play a role in hypocalcemia in these patients. In addition, electrolyte loss from the digestive tract can contribute to electrolyte imbalances. Because of the high prevalence of electrolyte imbalance in these patients, electrolyte monitoring is recommended in COVID-19 patients to ensure better care.
SoRoSim: A MATLAB Toolbox for Hybrid Rigid–Soft Robots Based on the Geometric Variable-Strain Approach

Soft robotics has been a trending topic within the robotics community for almost two decades. However, available tools for the modeling and analysis of soft robots are still limited. This article introduces a user-friendly MATLAB toolbox, Soft Robot Simulator (SoRoSim), that integrates the geometric variable-strain (GVS) model of Cosserat rods to facilitate the static and dynamic analysis of soft, rigid, and hybrid robotic systems. We present a brief overview of the design and structure of the toolbox and validate it by comparing its results with those published in the literature. To highlight the toolbox’s potential to efficiently model, simulate, optimize, and control various robotic systems, we demonstrate four sample applications. The demonstrated applications explore different actuator and external loading conditions of single-, branched-, open-, and closed-chain robotic systems. We think that the soft robotics research community will significantly benefit from the SoRoSim toolbox for a wide variety of applications.
Turán's Theorem for random graphs

For a graph $G$, denote by $t_r(G)$ (resp. $b_r(G)$) the maximum size of a $K_r$-free (resp. $(r-1)$-partite) subgraph of $G$. Of course $t_r(G) \geq b_r(G)$ for any $G$, and Tur\'an's Theorem says that equality holds for complete graphs. With $G_{n,p}$ the usual ("binomial" or "Erd\H{o}s-R\'enyi") random graph, we show: For each fixed r there is a C such that if \[ p=p(n) > Cn^{-\tfrac{2}{r+1}}\log^{\tfrac{2}{(r+1)(r-2)}}n, \] then $\Pr(t_r(G_{n,p})=b_r(G_{n,p}))\rightarrow 1$ as $n\rightarrow\infty$. This is best possible (apart from the value of $C$) and settles a question first considered by Babai, Simonovits and Spencer about 25 years ago.
Superconformal Field Theories

We argue the equivalence between the infrared conformal field theory of the 3d N = 8 supersymmetric Yang-Mills theories of ABCD (U(N), SO(2N + 1), Sp(2N), O(2N)) gauge groups and the ABJ(M) theories of U(N)k × U(Ñ)−k for k = 1, 2. We support this duality by comparing the superconformal index of the IR limit of these super Yang-Mills theories and that of those ABJ(M) models. Especially we find the match between two indices of (mirror dual of) the N = 8 U(N) SYM and of U(N)1×U(N)−1 ABJM model. Also we take large N limit of ABCD super YangMills theories with additional fundamental hyper-multiplets and infer the large N limit of N = 8 ABCD theories themselves, finding the expected gravitational duals. With the additional input on finite N, we argue the equivalence of Yang-Mills and ABJ(M) theories for all N. We further explore similar dualities to Chern-Simons matter theories for N = 4 Yang-Mills theories related by mirror symmetry. ar X iv :1 10 8. 36 47 v2 [ he pth ] 1 S ep 2 01 1
Compression and decompression of ultrasonic echoes by means of parametric wave phase conjugation

The properties of magnetoacoustic Parametric Wave Phase Conjugation (WPC) in presence of multiscatterers and conditions of double pulse pumping are studied for the first time. The analyse of the temporal behaviour of the time reversed echoes from complex scatterers in several iterations of WPC process shows that specific phenomena of compression and decompression of ultrasonic scattered signals can arise. The results are of interest for non destructive testing applications.
The Construction of Conceptual Framework of Enterprise Internal Control Evaluation Report

In practice, although there is no doubt about the role of enterprise internal control, how to evaluate the effect of enterprise internal control and the auditability of internal control has always been a difficult problem that plagues the theoretical and practical circles. The problems existing in the construction and development of enterprise internal control, such as the information content problem in the enterprise internal control evaluation report, are largely due to the lack of the conceptual framework of enterprise internal control to guide the internal control theory of enterprises. Therefore, the establishment of a set of conceptual framework for the evaluation report of internal control of enterprises and a full understanding of its importance play an important role in solving the practical problems faced in the practice of internal control of enterprises and promoting the construction and development of internal control of enterprises. The construction of the conceptual framework of the internal control evaluation report of an enterprise should adopt the viewpoint of the essential starting point theory, learn from the experience in the construction of relevant conceptual frameworks, start from the concept of the conceptual framework, clarify the main users of the report and their common needs, and combine the functions of the internal control evaluation report. Then, determine the objectives of the internal control evaluation report. This paper proposes that the introduction of information quality characteristics, elements of internal control evaluation reports, and cost-benefit measurement concepts can achieve the preset goals of enterprise internal control evaluation reports.
Novel Method for Sidelobe Level Suppression in Multielement Angled Dipole Array Antennas

In this paper, we propose a one-dimensional (1D) array antenna with improved sidelobe level (SLL) and cross-polarization (x-pol) characteristics. The array elements constituting the 1D array antenna comprise different numbers of dipole elements, and each array element has a different gain and E-field phase. The positions of the array elements in the z-axis direction are adjusted to equalize their E-field phases in the far field, and the array elements are arranged symmetrically with respect to the z-axis to obtain a low x-pol. The same amount of power is supplied to all the array elements of the 1D array antenna of the proposed structure. Therefore, a complexly structured feeding network is not required to achieve a low SLL and low x-pol. The gain of the proposed array antenna with a corporate feeding network is 15.2 dBi, and its SLL and x-pol level are–21.3 dB and 20.3 dB, respectively. The–10 dB impedance bandwidth of the proposed array antenna is 35.6% (8.3–11.9 GHz).
Attribution Theory Revisited: Probing the Link Among Locus of Causality Theory, Destination Social Responsibility, Tourism Experience Types, and Tourist Behavior

From a parochial perspective, destination social responsibility (DSR) is crucial in maintaining tourists’ loyalty, trust, and satisfaction. From a broad sense, destination social responsibility could play an essential role as an attribution shifting mechanism inside tourists’ mindsets and differ according to tourism experiences’ nature. To investigate this broad sense, the present study is the first to use locus of causality theory (LOC) to address this issue. By employing a quantitative method, we found that with the presence of DSR, tourists who externally (vs. internally) attribute positive events’ outcomes and have no intention to spread positive word-of-mouth (WOM) changed their attribution toward events with positive WOM. Moreover, adventure, business, and sustainable tourists are likely to perceive DSR advantages compared with leisure and cultural tourists by considering their internal LOC (internal attribution) and external LOC (external attribution). Furthermore, the study provided critical theoretical and managerial implications for tourism managers/scholars.
Physical theory and its interpretation : essays in honor of Jeffrey Bub

Preface A new modal interpretation of quantum mechanics in terms of relational properties Joseph Berkovitz and Meir Hemmo Why special relativity should not be a template for a reformulation of quantum mechanics Harvey Brown and Chris Timpson On symmetries and conserved quantities in classical mechanics Jeremy Butterfield On the notion of a physical theory of an incompletely knowable domain William Demopoulos Markov properties and quantum experiments Clark Glymour Quantum entropy Stan Gudder Symmetry and the scope of scientific realism Richard Healey Is it true or is it false or somewhere in between? The logic of quantum mechanics C.J. Isham Einstein's hole argument and Weyl's field-body relationalism Herbert Korte Quantum mechanics as a theory of probability Itamar Pitowsky John von Neumann on quantum correlations Miklos Redei Kriske, Tupman and quantum logic: The quantum logician's conundrum Allen Stairs Bibliography of the publications of Jeffrey Bub to 2006 Index
GROUNDED COMPUTATIONAL ANALYSIS: A HANDS-ON GROUNDED COMPUTATIONAL ANALYSIS: A HANDS-ON APPROACH TO ANALYSING DIGITAL INNOVATION APPROACH TO ANALYSING DIGITAL INNOVATION

As socio-technical processes related to digital innovation are increasingly connected and distributed across geographical, organisational, and temporal boundaries, the methods we use to study them must be adapted to accommodate the greater detail and scope of the phenomenon. Specifically, there is a need to operationalise meth-ods for generating inductive theory of distributed digital innovation from digital trace data. An emerging stream of IS research on computationally intensive inductive theorising lays the groundwork for such methods. This paper builds on this foundation to develop a hands-on approach to operationalising grounded theorizing in computational analysis of digital trace data. The paper first conceptualises trace data of digital innovation as a new research context before articulating an approach to operationalising grounded theory in computational analysis of digital innovation. The application of the grounded computational analysis approach is then briefly illustrated in the context of digital trace data from an online social network before possible directions for further research are laid out.
Problems in Inverse Scattering - Illposedness, Resolution, Local Minima, and Uniqueness

The shape and the distribution of material construction of the scatterer may be obtained from its scattered fields by the iterative inversion in the spectral domain. The illposedness, the resolution, and the uniqueness of the inversion are the key problems in the inversion and inter-related. The illposedness is shown to be caused by the evanescent modes which carries and amplifies exponentially the measurement errors in the back-propagation of the measured scattered fields. By filtering out all the evanescent modes in the cost functional defined as the squared difference between the measured and the calculated spatial spectrum of the scattered fields from the iteratively chosen medium parameters of the scatterer, one may regularize the illposedness of the inversion in the expense of the resolution. There exist many local minima of the cost functional for the inversion of the large and the high-contrast scatterer and the hybrid algorithm combining the genetic algorithm and the Levenberg-Marquardt algorithm is shown to find efficiently its global minimum. The resolution of reconstruction obtained by keeping all the propating modes and filtering out the evanescent modes for the regularization becomes 0.5 wavelength. The super resolution may be obtained by keeping the evanescent modes when the measurement error and instance, respectively, are small and near.
Efficient approximate Bayesian inference for models with intractable likelihoods

We consider the problem of approximate Bayesian parameter inference in nonlinear state space models with intractable likelihoods. Sequential Monte Carlo with approximate Bayesian computations (SMC-ABC) is an approach to approximate the likelihood in this type of models. However, such approximations can be noisy and computationally costly which hinders efficient implementations using standard methods based on optimisation and statistical simulation. We propose a novel method based on the combination of Gaussian process optimisation (GPO) and SMC-ABC to create a Laplace approximation of the intractable posterior. The properties of the resulting GPO-ABC method are studied using stochastic volatility (SV) models with both synthetic and real-world data. We conclude that the algorithm enjoys: good accuracy comparable to particle Markov chain Monte Carlo with a significant reduction in computational cost and better robustness to noise in the estimates compared with a gradient-based optimisation algorithm. Finally, we make use of GPO-ABC to estimate the Value-at-Risk for a portfolio using a copula model with SV models for the margins.
Orbital Effects in VLT--UVES Spectra of AA Dor and NY Vir

Abstract. We analyse VLT/UVES spectra of two eclipsing subdwarf binary systems NY Vir, a rapidly pulsating subdwarf B primary with an M5 companion and AA Dor, an sdOB primary with a degenerate dwarf companion. We report the detection of the Rossiter-McLaughlin effect in the radial velocity curve of NY Vir, as previously seen in AA Dor. Reexamining the AA Dor spectra and simulating the amplitude of the Rossiter-McLaughlin effect, we find it to be in the accordance with the amplitude seen in the radial velocity residuals. In addition to the Rossiter-McLaughlin effect we observe clear radial velocity deviations in the Balmer lines at phases where the contribution from the secondary is greatest in both AA Dor and NY Vir. After careful subtraction of the contribution from the AA Dor primary we clearly detect both emission and absorption features originating from the superheated surface of the secondary. This allows us for the first time to estimate K2 and the masses of the primary and secondary star in the AA Dor system.
Defining Internal Tissue Closure: High-Resolution Ultrasound Evaluation of Interi—A Novel Internal Tissue Closure System

Abstract Background Seroma remains a leading postsurgical complication in plastic surgery. Conventional drains are ineffective in clearing blood and fluid and closing down surgical spaces. The Interi (Internal Closure System, IC Surgical, Grand Rapids, MI) is comprised of a novel branching internal manifold attached to a self-contained portable pump with a higher, consistent, continuous negative pressure, may reduce this long-standing issue. In addition, high-resolution ultrasound (HRUS) has emerged as an ideal tool to visualize structures, fluid collections, and seromas internally. Objectives This study evaluates Interi in full abdominoplasty patients utilizing HRUS to evaluate Interi's ability to evacuate blood and fluid, hold internal tissues together and document, for the first time, what internal tissue healing actually looks like radiographically. Methods An IRB approved, Contract Research Organization reviewed retrospective study evaluated consecutive patients undergoing full abdominoplasty utilizing Interi from July 2020 through March 2021 by three plastic surgeons. HRUS visualized and confirmed the presence or absence of fluid collections and healing tissue planes during the postoperative process. Study data and all adverse events were recorded, with HRUS images reviewed by investigators and confirmed by an independent radiologist. Results Seventy-one Interi patients were enrolled. Mean age was 43 (range: 21-74) and BMI was 28. Seroma was confirmed clinically and through HRUS in 3/71 patients, and was associated with either clot (2) or failure to activate system (1). Interi's ability to eliminate fluid and approximate/hold surgical tissue planes together was confirmed with HRUS. No other major complications, including abscess, hematomas, or flap necrosis were observed. Conclusions This novel Internal Tissue Closure System effectively evacuated blood and fluid, approximated and maintained closure of internal tissue planes in abdominoplasty patients, allowing for primary tissue healing and internal wound closure to occur. Healing tissue planes and any fluid present are easily identified on HRUS visualizing actual internal tissue healing with a simple, widely available radiographic scan. Level of Evidence: 3
A novel machine learning approach to analyzing geospatial vessel patterns using AIS data

ABSTRACT In the maritime environment, the Automatic Identification System (AIS) contains information related to vessel trajectories that can be used to detect unusual maritime occurrences and maritime traffic patterns. To detect such occurrences with supervised learning methods the AIS messages must be manually annotated, which can be a demanding process. Therefore, unsupervised methods are used to identify anomalous traffic patterns based on vessel trajectories. Typically, dense regions of maritime activity are studied to capture common traffic patterns which help identify trajectories that do not follow the norm. However, these approaches cannot detect anomalous behaviors along common pathways or incorporate time-related events into the analysis. Such challenges motivate the approach taken in this work by using auto-regressive techniques to model vessel trajectories and clustering analyses to explore behavior patterns of vessels. Results confirm that the Auto-regressive Integrated Moving Average (ARIMA) and Ornstein-Uhlenbeck (OU) processes are able to model the trajectories and can be used with density-based spatial clustering of applications with noise (DBSCAN), hierarchical clustering (HC), and spectral clustering (SC) to identify different behavioral patterns.