Miracle-dz/UniFAR-FTUs huggingface dataset:
How Long After Coronary Artery Bypass Surgery Can Patients Have Elective Safer Non-Cardiac Surgery?

Objective To evaluate the complications and mortality after noncardiac surgeries in patients who underwent previous coronary artery bypass grafting (CABG). Methods We used insurance data and identified patients aged ≥20 years undergoing noncardiac surgeries between 2010 and 2017 in Taiwan. Based on propensity-score matching, we selected an adequate number of patients with a previous history of CABG (within preoperative 24 months) and those who did not have a CABG history, and both groups had balanced baseline characteristics. The association of CABG with the risk of postoperative complications and mortality was estimated (odds ratio [OR] and 95% confidence interval [CI]) using multiple logistic regression analysis. Results The matching procedure generated 2327 matched pairs for analyses. CABG significantly increased the risks of 30-day in-hospital mortality (OR 2.28, 95% CI 1.36–3.84), postoperative pneumonia (OR 1.49, 95% CI 1.12–1.98), sepsis (OR 1.49, 95% CI 1.17–1.89), stroke (OR 1.53, 95% CI 1.17–1.99) and admission to the intensive care unit (OR, 1.75, 95% CI 1.50–2.05). The findings were generally consistent across most of the evaluated subgroups. A noncardiac surgery performed within 1 month after CABG was associated with the highest risk for adverse events, which declined over time. Conclusion Prior history of CABG was associated with postoperative pneumonia, sepsis, stroke, and mortality in patients undergoing noncardiac surgeries. Although we raised the possibility regarding deferral of non-critical elective noncardiac surgeries among patients had recent CABG when considering the risks, critical or emergency surgeries were not in the consideration of delay surgery, especially cancer surgery.
Does Foreign-Accented Speech Affect Credibility? Evidence from the Illusory-Truth Paradigm

In a pioneering study, Lev-Ari and Keysar (2010) observed that unknown statements are judged less credible when uttered with foreign accent compared to native accent. This finding was interpreted in terms of processing fluency; when intelligibility is reduced, the credibility of the message decreases. Here, we use the illusory truth paradigm to explore how accent affects credibility. In a between-participant design, participants were exposed to unknown statements uttered by native-accented or foreign-accented speakers. After a distractor task, the same statements were presented with new statements, and participants assessed their truthfulness. Truthfulness ratings were higher for repeated statements than for new statements, replicating the illusory truth effect. Contrary to the processing fluency hypothesis, the effect was similar in both the foreign-accented and native-accented speech groups. A new group of participants rated the speakers’ voices on various social traits. A negative bias against foreign speakers was observed. However, this negative-bias did not affect truth ratings.The impact of foreign-accented speech on message credibility is discussed in the context of two factors, processing fluency and out-group stereotype activation.
ANALYSIS ON FOCAL MECHANISM AND SEISMOGENIC STRUCTURES OF YAOAN EARTHQUAKE WITH M_S6.0,2009

Using joint inversion method with amplitude ratio of P wave、SV wave and SH wave,this paper calculated focal mechanism of aftershock sequence of Yaoan earthquake with MS6.0. According to the space distribution of earthquake sequence,the author analyzed the characteristics of stress field and seismogenic fault.The result showed that:(1) seismogenic fault of Yaoan earthquake was a vertical right-lateral strike-slip fault,striking NWW—SEE.The result was reliable,also consistent with nodal plane of CMT result offered by Harvard and predominant direction of aftershocks;(2) predominant direction of principal compressive stress in NWW—SEE was consistent with regional tectonic stress,and some aftershocks were different from main shock.Stress field of main shock was controlled by regional tectonic stress,indicated diversity and complexity in seismic area;(3) analyzing the distribution of earthquake sequence、focal mechanism and fault structure in seismic area comprehensively,seismogenic structure of Yaoan earthquake belongs to Mawei-jing fault.
Health care utilization, mental disorders and behavioural disorders among perpetrators of intimate partner homicide in 2000–2016: A registry-based case-control study from Sweden

Little is known about intimate partner homicide (IPH) perpetrator´s healthcare contacts and mental health problems before the killing. The aim was to compare male and female IPH perpetrators with matched controls from the general population by analysing differences in healthcare utilization and mental and behavioural disorders. This study includes 48 males and 10 females who perpetrated IPH between 2000 and 2016 in the Västra Götaland Region of Sweden. Controls (n = 458) were randomly selected from the general population and matched for sex, birth year and residential area. Data were retrieved from the Swedish National Patient Register and the Western Swedish Healthcare Register. Mental and behavioural disorders were classified according to ICD-10 (F00-F99). The Mann-Whitney U test was used to test for differences in health care utilization and mental and behavioural disorders. Compared to their controls, male perpetrators had more registered contacts with primary care ≤ 30 (p = < .001) and ≤ 365 days (p = .019), respectively, before the homicide; with specialist outpatient care ≤ 30 (p = < .001) and ≤ 365 days (p = < .001), respectively, before the homicide: and with inpatient care ≤ 30 (p = < .001) and ≤ 365 days (p = .024), respectively, before the homicide. Female perpetrators had more specialized outpatient care (p = .040) and inpatient care (p = .003) contacts ≤ 365 days before the homicide, compared to controls. Male perpetrators had at least one mental or behavioral disorder diagnosed in any studied healthcare setting except in inpatient care ≤ 30 days before homicide. Female perpetrators had more mental health disorders diagnosed in specialized outpatient care ≤ 365 days before the homicide (p < .001). Perpetrators had more healthcare contacts and mental disorders one year and one month prior to the homicide compared to their controls. Health care professionals should obtain necessary skills in routinely enquiring about intimate partner violence perpetration.
Recent advances in light patterned optogenetic photostimulation in freely moving mice

Abstract. Optogenetics opened the door to a new era of neuroscience. New optical developments are under way to enable high-resolution neuronal activity imaging and selective photostimulation of neuronal ensembles in freely moving animals. These advancements could allow researchers to interrogate, with cellular precision, functionally relevant neuronal circuits in the framework of naturalistic brain activity. We provide an overview of the current state-of-the-art of imaging and photostimulation in freely moving rodents and present a road map for future optical and engineering developments toward miniaturized microscopes that could reach beyond the currently existing systems.
The Plumbing System Feeding the Lusi Eruption Revealed by Ambient Noise Tomography

Lusi is a sediment‐hosted hydrothermal system featuring clastic‐dominated geyser‐like eruption behavior in East Java, Indonesia. We use 10 months of ambient seismic noise cross correlations from 30 temporary seismic stations to obtain a 3‐D model of shear wave velocity anomalies beneath Lusi, the neighboring Arjuno‐Welirang volcanic complex, and the Watukosek fault system connecting the two. Our work reveals a hydrothermal plume, rooted at a minimum 6 km depth that reaches the surface at the Lusi site. Furthermore, the inversion shows that this vertical anomaly is connected to the adjacent volcanic complex through a narrow (~3 km wide) low velocity corridor slicing the survey area at a depth of ~4–6 km. The NE‐SW direction of this elongated zone matches the strike of the Watukosek fault system. Distinct magmatic chambers are also inferred below the active volcanoes. The large‐scale tomography features an exceptional example of a subsurface connection between a volcanic complex and a solitary erupting hydrothermal system hosted in a hydrocarbon‐rich back‐arc sedimentary basin. These results are consistent with a scenario where deep‐seated fluids (e.g., magmas and released hydrothermal fluids) flow along a region of enhanced transmissivity (i.e., the Watukosek fault system damage zone) from the volcanic arc toward the back arc basin where Lusi resides. The triggered metamorphic reactions occurring at depth in the organic‐rich sediments generated significant overpressure and fluid upwelling that is today released at the spectacular Lusi eruption site.
CHALLENGES IN SCIENCE OF NOWADAYS

Abstracvt. The tensorflow library capabilities in the python programming environment are huge in getting effective results. It describes how to use open data sets to recognize Arabic graphics and to form datasets for additional letters for old Uzbek and Farsi text letters. The most effective methods of recognizing the given Arabic text are used, and only the results obtained are described, without the algorithms given in the references. CNN created a model for the data set letters, based on which the results were 90% recognizable.
Language Independent Named Entity Classi cation by modi ed Transformation-based Learning and by Decision Tree Induction

We describe our last results at the CoNLL2002 shared task of Named Entity Recognition and Classiication using two approaches that we rst applied to other NLL problems. We have been developing our own modiied TBL learner initially to tackle the Part-of-Speech tagging problem, for integration in a hybrid NLL and rule-based system for information extraction (Ciravegna et al., 1999). After encouraging results in applying decision tree induction to the CoNLL2001 task of chunking, Jones (2002), where we attained an overall F-measure of 92.90 at this task, we have applied the same setup to the NER task.
SOURCES APPORTIONMENT OF FINE AND COARSE AEROSOL IN BANGI, SELANGOR USING POSITIVE MATRIX FACTORIZATION

Samples of fine (PM2.5) and coarse (PM10-2.5) fraction of airborne particulate were collected on weekly basis during the period from May 2012 to July 2014 at Bangi, Selangor. The samples were collected using a Gent Stacked Filter Sampler in two fractions of < 2.5 µm and 2.5 - 10 µm sizes. This research paper aims at establishing the concentration level of PM2.5, PM10-2.5 and PM10 at Bangi area and investigates their possible sources and contribution to the ambient aerosol of the area. The samples were analyzed for their elemental composition and black carbon content by Particle Induced X-ray Emission (PIXE) and Smoke Stain Reflectometer, respectively. The average for PM2.5, PM10-2.5 and PM10 ranged from1.8 µg/m3 to 78.0 µg/m3, 9.6 µg/m3 to 76.8 µg/m3 and 12 µg/m3 to 134 µg/m3, respectively. Positive Matrix Factorization (PMF) technique was also applied to fine and coarse data set in order to identify the possible sources of particulate matter (PM) and their contribution to the ambient particulate matter concentrations in the area. The best solution was found to be five factors for both elemental compositions of fine and coarse PM, respectively. The PMF results show that motor vehicles and secondary sulphate contribute about 40.3% and 33.0% of the fine mass respectively followed by soil, sea salt and smoke/biomass burning with the average contribution of 10.5%, 10.3% and 6.4%, respectively. In case of coarse particles the PMF results show that a large fraction of about more than 50% of the coarse mass comes from motor vehicle. Soil dust including road dust and soil construction contribute about 32.5% of the coarse mass whilst the smoke/biomass burning factor contributes about 6.7% of the coarse mass.
Q-sorting and MIS Research: A Primer

Q-sort offers a powerful, theoretically grounded, and quantitative tool for examining opinions and attitudes. This article provides clear guidelines in an effort to facilitate successful understanding and application of Q-sort. Following a description of the steps of Q-sorting, an example Q-sort of MIS professors on the topic of PhD preparation is presented. The example includes details of Web-based data collection and data analysis using freeware tools. The use of Q-sorting in MIS research and issues surrounding the use of Q-sort are discussed.
Lowering the Barrier to Applying Machine Learning

Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably, and understand the universe. Yet, the data explosion has outstripped our tools to process it, leaving a gap between powerful new algorithms and what real programmers can apply in practice. I examine how data affects the way we program. Specifically, this dissertation focuses on using machine learning algorithms to train a model. I found that the key barrier to adoption is not a poor understanding of the machine learning algorithms themselves, but rather a poor understanding of the process for applying those algorithms and insufficient tool support for that process. I have created new programming and analysis tools that support programmers by helping them (1) implement machine learning systems and analyze results, (2) debug data, and (3) design and track experiments.
Optimization of intervention strategies in epidemic models using deep reinforcement learning techniques

The challenge is to analyze these BIG DATA to answer clinical and biological questions by using appropriate statistical methods. With data on the machinery of a cell to the clinical status of individuals in any circumstances including in clinical trials, new tools are needed to translate information obtained from complex systems into knowledge. This has led to the field of « systems biology » and « systems medicine » by extension, which naturally takes place in the context of translational medicine that links clinical and biological research. The statistical analysis of these data is facing several issues:
Simon: Scriptable Interactive Monitoring for SDNs

Software-Deﬁned Networking helps to simplify network control and conﬁguration. However, understanding and debugging SDN involve some challenges for some set of common operations. Operators of debugging not only can determine behaviors of data-and control-plane, but also need to perform some interactive actions during a fact. We present S IMON (Scriptable Interactive Monitoring), probing SDN behaviors by monitoring networks, ﬁltering events and reusing operators. Debugging with S IMON takes SDN as a black-box, which is independent of controller and network. Since S IMON is scriptable and interactive, users can deﬁne own reactive functions by using the power of Scala to reﬁne the desired goals.
MDG Tools for the Veri(cid:12)cation of RTL Designs (cid:3)

Multiway Decision Graphs (MDGs) [3] have been proposed as a new kind of decision graphs to represent Register-Transfer (RT) level hardware designs. MDG-based veri(cid:12)cation techniques have been developed for combinational and sequential designs. In our presentation, we shall describe the structure of the MDG tools we implemented and demonstrate their applications on a number of benchmarks including the Fairisle 4X4 ATM switch fabric. The MDG Tools comprise an MDG package that contains basic MDG operators and an application layer that implements the veri(cid:12)cation algorithms.
Database Management Systems

From the Publisher: Database Management Systems (DBMS) is a must for any course in database systems or file organization. DBMS provides a hands-on approach to relational database systems, with an emphasis on practical topics such as indexing methods, SQL, and database design. New to this edition are the early coverage of the ER model, new chapters on Internet databases, data mining, and spatial databases, and a new supplement on practical SQL assignments (with solutions for instructors' use). Many other chapters have been reorganized or expanded to provide up-to-date coverage.
Author Identification : Using Text Mining , Feature Engineering & Network Embedding

Authorship analysis is a challenging area that has been developed through centuries and with research done widely scattered across multiple disciples of mainly computational linguistics, text mining, data mining, stylometry and machine learning. Conventional techniques from the past relied heavily on stylometry and text-based content analysis of document text for authorship analysis. More recent developments use network embedding training focus heavily on document attributes to build a network and predict the author. We propose a system that incorporated the strengths of both text mining and network embedding methods and utilizes both the document text and document attributes fully when available. In this paper, we describe the system overview and implementation in detail and discuss how by supporting a more multi-faceted information based network embedding, it can be possible to get improved results. Finally we discuss our results and suggest some future improvements in terms of results, speed and performance for our system to handle larger corpus
Joint compensation of transmitter and receiver IQ imbalance in OFDM systems based on selective coefficient updating

approach at each branch of per-tone equalization (PTEQ) structure has been applied for insufficient cyclic prefix (CP) length. Because of the high amount of adaptive filters and their complex adaption process in PTEQ structure, SCU has been proposed. So using this method leads to reduce the computational complexity while the performance is almost being unchanged. Moreover, using set-membership filtering with variable step size is proposed for sufficient CP case to increase convergence speed and decrease the average of calculations. Simulation results show that these algorithms have similar performance in comparison with conventional algorithms while these reduce the amount of calculations. In addition, compensation of the channel effect, transmitter/ receiver in-phase/quadrature-phase (IQ) imbalance are achievable by these algorithms.
Happy Packets to You!

Previous studies of the Internet control plane examined its quality from a number of different points of view, but very few considered the performance of the data plane as a measure of control plane performance. For example, a large number of routing updates during some period or slow routing convergence, are often cited as an indication of a poorly designed or behaving routing protocol. However, if the customers’ packets are being delivered well, which we term “happy packets”, while routers can handle routing updates without being overloaded, then how significant are these control plane measurements? We believe packet happiness should be the primary metric for measuring control plane performance, especially the quality of routing. Since handling routing changes is the fundamental function of any routing protocol, in this paper we measure packet happiness during controlled routing changes. We obtain results by using established data plane metrics – delay, drop, jitter and reordering (DDJ&R) – in order to evaluate BGP, the de facto standard inter-domain routing protocol. Moreover, we compare the results with routing updates observed by RouteViews, a commonly used resource for studying the control plane. We establish that generally there is no clear correlation between the number and duration of routing updates derived from partial views and the performance of the data plane, further cautioning the usage of metrics from the control plane alone in evaluating control plane quality.
How hard is halfspace range searching?

We investigate the complexity of <italic>halfspace range searching</italic>: Given <italic>n</italic> points in <italic>d</italic>-space, build a data structure that allows us to determine efficiently how many points lie in a query halfspace. We establish a tradeoff between the storage <italic>m</italic> and the worst-case query time <italic>t</italic> in the Fredman/Yao arithmetic model of computation. We show that <italic>t</italic> must be at least on the order of (<italic>n</italic>/log <italic>n</italic>)<supscrpt>1-((<italic>d</italic>-1)/(<italic>d</italic>(<italic>d</italic>+1))</supscrpt><italic>m</italic><supscrpt>1/<italic>d. </italic></supscrpt> To our knowledge, this is the first nontrivial lower bound for halfspace range searching. Although the bound is unlikely to be optimal, it falls reasonably close to the recent <italic>O</italic>(<italic>n</italic>(log <italic>m</italic>/<italic>n</italic>)<supscrpt><italic>d</italic>+1</supscrpt>/<italic>m</italic><supscrpt>1/<italic>d</italic></supscrpt>) upper bound established by Matousˇek. We also show that it is possible to devise a sequence of <italic>n</italic> inserts and halfspace range queries that require a total time of <italic>n</italic><supscrpt>2-&thgr;(1/<italic>d</italic></supscrpt>). Our results imply nontrivial lower bounds for spherical range searching in any fixed dimension. For example they show that, with linear storage, circular range queries in the plane require &OHgr;(<italic>n</italic><supscrpt>1/3</supscrpt>) time (modulo a logarithmic factor).
SUPERVISED NONLINEAR UNMIXING OF HYPERSPECTRAL IMAGES USING A PRE-IMAGE METHODS

Spectral unmixing is an important issue to analyze remotely sensed hyperspectral data. This involves the decomposition of each mixed pixel into its pure endmember spectra, and the estimation of the abundance value for each endmember. Although linear mixture models are often considered because of their simplicity, there are many situations in which they can be advantageously replaced by nonlinear mixture models. In this chapter, we derive a supervised kernel-based unmixing method that relies on a pre-image problem-solving technique. The kernel selection problem is also brieﬂy considered. We show that partially-linear kernels can serve as an appropriate solution, and the nonlinear part of the kernel can be advantageously designed with manifold-learning-based techniques. Finally, we incorporate spatial information into our method in order to improve unmixing performance.
EMBEDDED IMPLEMENTATION OF EEG ANALYSIS USING INDEPENDENT COMPONENT APPROACH

Brain signals are important in diagnosing various disorders and abnormalities in the human body. These signals are recorded by scalp electrodes and are called as EEG signals. EEG signals are a mixture of signals from different brain regions which contain artefacts along with original information. These contaminated mixtures are analysed such that diagnosis of various diseases is possible. One of the effective methods available is Independent Component Analysis (ICA) for removing artefacts and for separation and analysis of the desired sources from within the EEGs. This paper focuses on the analysis of EEG signals using ICA approach. Two ICA algorithmsPearson ICA and JADE ICA are analysed in this paper. Comparison of these ICA algorithms in removing artefacts from EEG has been carried out by simulation using MATLAB. Then the Pearson ICA algorithm simulation is done using Visual C#. The algorithm has been implemented in an Embedded Development Kit (EDK) using . NET Micro Framework and the results are presented. Keywords-Blind source separation, Electroencephalogram, Independent Component Analysis (ICA), Pearson system, Joint Approximate Diagonalization of Eigen Matrices, Embedded Development Kit.
REPORT RAPPORT

Wecombinetype inference and concept analysis in order to gain insight into legacy software systems. Type inference for COBOL yields the types for variables and program parameters. These types are used to perform mathematical concept analysis on legacy systems. We have developed ConceptReﬁnery, a tool for interactively manipulating concepts. We show how this tools facilitates experiments with concept analysis