Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic hypothermia after cardiac arrest: an advisory statement by the advanced life support task force of the International Liaison Committee on Resuscitation.

On the basis of the published evidence to date, the Advanced Life Support (ALS) Task Force of the International Liaison Committee on Resuscitation (ILCOR) made the following recommendations in October 2002: Induction of moderate hypothermia (28°C to 32°C) before cardiac arrest has been used successfully since the 1950s to protect the brain against the global ischemia that occurs during some open-heart surgeries. Successful use of therapeutic hypothermia after cardiac arrest in humans was also described in the late 1950s1–3 but was subsequently abandoned because of uncertain benefit and difficulties with its use.4 Since then, induction of hypothermia after return of spontaneous circulation (ROSC) has been associated with improved functional recovery and reduced cerebral histological deficits in various animal models of cardiac arrest.5–8 Additional promising preliminary human studies have been completed.9–16 At the time of publication of the Guidelines 2000 for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care , the evidence was insufficient to recommend use of therapeutic hypothermia after resuscitation from cardiac arrest.17 In 2002 the results of 2 prospective randomized trials were published that compared mild hypothermia with normothermia in comatose survivors of out-of-hospital cardiac arrest.18,19 One study was undertaken in 9 centers in 5 European countries19; the other was conducted in 4 hospitals in Melbourne, Australia.18 The criteria for entry into these trials were similar: ROSC, patients remaining intubated and ventilated, with persistent coma after out-of-hospital cardiac arrest due to VF. In the European study, the median Glasgow Coma Scale score on hospital admission in both groups …
Input/Output Curves to Tone Bursts and Clicks in Extratympanic and Transtympanic Electrocochleography

Objectiue The aim of this study is to explore the applicability of two specific methods in extratympanic (ET) electrocochleography that have rarely been used there, but are more commonly applied in transtympanic (TT) approaches. These two methods are the use of tone burst stimulation in addition to clicks, and the analysis of amplitude input/output curves as a measure of cochlear recruitment due to a pathological spread of excitation. Design Simultaneous extratympanic and transtympanic recordings were made in 30 patients with various types and degrees of cochlear hearing loss. ET recordings were also made in a group of normal subjects. Stimuli were tone bursts at octave frequencies from 500 to 8000 Hz and clicks, at intensity levels of about 90 dB down to response threshold in 10 dB steps. First, a general comparison is made of ET versus TT response properties, then the initial slopes of YO curves in both sets of data are evaluated. Results ET responses are reduced in amplitude with respect to TT responses by a factor of 0.43 on average. Within each subject this factor is independent of stimulus type or level, but it has a substantial intersubject variation. ET and TT latencies are identical. From the normal data a criterion for abnormality of the slope of the I/O curve is derived in a similar way as available for TT data. Using this criterion ET YO curves appear to be significantly steeper than normal in recruiting ears, albeit with a lesser sensitivity than for the associated TT data. Conclusions Extratympanically recorded responses to tone burst stimuli provide basically the same information as transtympanic recordings. However, for a reliable interpretation of responses to low-intensity stimuli a larger amount of signal averaging is required. The analysis of YO curves is a useful extension of current ET methods as a contribution to assessing a pathological spread of excitation in the cochlea.
Neuropathic Pain Questionnaire—Short Form

Neuropathic pain is a frequent clinical challenge, particularly given the difficulties frequently encountered in diagnosis. As a result, development of a clinical tool that can discriminate it from non-neuropathic pain is an important step in assessment and treatment planning for patients with these chronic pain disorders. A study addressing the ability of patients’ pain descriptors to differentiate neuropathic from non-neuropathic pain has been conducted and yielded a Neuropathic Pain Questionnaire (NPQ). This measure consists of a relatively comprehensive groups of twelve descriptors that characterize symptoms of neuropathic pain. In the initial development of the NPQ, a discriminant analysis was performed on all 12 predictor items simultaneously, to determine the degree to which these items could collectively predict neuropathic versus nonneuropathic pain. In the current analysis, we sought to determine the minimum number of items sufficient to predict diagnostic group membership, without statistically significant loss of predictive accuracy.
Boosting Accuracy of Classical Machine Learning Antispam Classifiers in Real Scenarios by Applying Rough Set Theory

Nowadays, spam deliveries represent a major problem to benefit from the wide range of Internet-based communication forms. Despite the existence of different well-known intelligent techniques for fighting spam, only some specific implementations of Naı̈ve Bayes algorithm are finally used in real environments for performance reasons. As long as some of these algorithms suffer from a large number of false positive errors, in this work we propose a rough set postprocessing approach able to significantly improve their accuracy. In order to demonstrate the advantages of the proposed method, we carried out a straightforward study based on a publicly available standard corpus (SpamAssassin), which compares the performance of previously successful well-known antispam classifiers (i.e., Support Vector Machines, AdaBoost, Flexible Bayes, and Näıve Bayes) with and without the application of our developed technique. Results clearly evidence the suitability of our rough set postprocessing approach for increasing the accuracy of previous successful antispam classifiers when working in real scenarios.
Three Dimensionally Stacked NAND Flash Memory Technology Using Stacking Single Crystal Si Layers on ILD and TANOS Structure for Beyond 30nm Node

For the first time, the 3 dimensionally stacked NAND Flash memory, is developed by implementing S3 (single-crystal Si layer stacking) technology, which was used to develop S3 SRAM previously. The NAND cell arrays are formed on the ILD as well as on the bulk to double the memory density without increasing the chip size. The feasibility of the technology was proven by the successful operation of 32 bit NAND flash memory cell strings with 63nm dimension and TANOS structures. The novel NAND cell operational scheme, so called SBT (source-body tied) scheme, is presented to maximize the advantages of 3 dimensionally stacked NAND cell structures
Deep Learning for Query Semantic Domains Classification

6 Long Short Term Memory (LSTM), a type of recurrent neural network, has 7 been widely used for Language Model. One of the application is speech query 8 domain classification where LSTM is shown to be more effective than 9 traditional statistic models and feedforward neural networks. Different from 10 speech queries, text queries to search engines are usually shorter and lack of 11 correct grammar, while hold certain patterns. In this project, we demonstrate 12 the models that are capable of carrying information both forward and 13 backward, bi-direction LSTM, outperform forward only LSTM. 14 Convolutional Neural Network which encapsulates words regardless of the 15 order also achieves a comparable result as bi-directional LSTM. 16
Coordinated microgrid control via parametric optimization

Microgrid is a cluster of distributed generation sources, storage units and loads, which, when controlled in an optimal coordinated fashion, can improve both the quality of the local power supply as well as the performance of the overall power distribution system. In this paper we present a coordinated control methodology for microgrids that utilizes parameterized costs of local operation declared by microgrid's constituent sub-systems. The overall control problem is decomposed into smaller decoupled local problems related to individual subsystems and one global coordination problem that describes the coupling of the subsystems. Each local problem is cast as a multi-parametric quadratic optimization problem. When the dimension of the coordination parameter is one, a very efficient algorithm can be used to solve the coordination problem. Performance of the proposed control strategy is illustrated on a simulation case study.
In dementia with Lewy bodies, Braak stage determines phenotype, not Lewy body distribution

We used an autopsy series to determine whether the newest dementia with Lewy bodies (DLB) consensus pathologic classification correlates with premortem diagnosis of DLB. Neocortical sections from a total of 95 cases with Lewy bodies were stained with α-synuclein antibodies. We assigned cases according to the DLB consensus' categories and found a significant association with the premortem clinical diagnosis of DLB. Clinical diagnosis of DLB, however, depended on the presence of low Alzheimer disease pathology (by Braak staging) rather than on Lewy body distribution.
The measurement of cannibalization

Notes that the risk of cannibalization is a very real threat for many new product launches and that the risk becomes even more significant if the new product is launched under the same brand name as an existing product. Points out that, since line extension is by far the most common branding strategy for new products, it is important that managers develop their understanding of the effect and that little empirical work has been published on the subject. Defines cannibalization and examines three techniques which managers might use to measure it. Tests gains loss analysis, duplication of purchase tables and deviations from expected share movements on consumer panel data relating to three line extensions in the UK and German detergent markets. Presents results showing cannibalization of the parent brand by all three extensions and suggesting the need for managers to use multiple methods when evaluating the degree of cannibalization. Emphasizes the need to sample over time, since the extent of cannibalizatio.
An Economic Evaluation of the Moneyball Hypothesis

Michael Lewis's book, Moneyball , describes how an innovative manager working for the Oakland Athletics successfully exploited an inefficiency in baseball's labor market over a prolonged period of time. We evaluate Lewis's claims by applying standard econometric procedures to data on player productivity and compensation from 1999 to 2004. These methods support Lewis's argument that certain baseball skills were valued inefficiently in the early part of this period, and that this inefficiency was profitably exploited by managers with the ability to generate and interpret statistical knowledge. Consistent with Lewis's story and economic reasoning, as knowledge of the inefficiency became increasingly dispersed across baseball teams the market corrected the original mispricing.
A Novel Method for Quantifying Spatial Patterns in Plants

Color patterns are found in a plethora of organisms, from vertebrates to flowering plants. While many studies have examined the mechanisms that produce these diverse patterns in animals, little research has investigated the mechanisms by which plants create color patterns. The conclusions drawn from animal studies may not accurately translate to plants due to early divergence in the evolution of life. Characterization of plant patterning mechanisms would have widespread impacts on developmental and evolutionary biology. To unravel the mystery behind pattern formation, we suggest an experimental framework to understand pattern evolution and development at a phenotypic, genotypic, and quantitative level, creating a holistic model for the evolution of complex traits and phenotypic diversity. Here, we provide a novel protocol for the quantification of pattern morphology, and demonstrate its efficacy in a segregating F2 population of the model organism ​Mimulus luteus ​. By co-opting ArcGIS and FragStats, two landscape ecology softwares, to map petal patterns, we developed a high throughput method for objective phenotype characterization. This protocol is useful for preliminary work in a bulk segregant analysis by separating a population in discrete groups based on morphology. We used this protocol to demonstrate that patterns are distinct between petals within the same flower depending on petal location, and that there is a genetic basis for pattern formation in flowers. Minor tweaks to the genes guiding pattern formation may be responsible for the rapid evolution of angiosperm flower diversity. Future work is required to identify the genes responsible for pattern formation, and to develop a method for modeling these genes to predict how minor mutations would impact phenotypic traits.
Deviance-elicited Changes in Event-related Potentials are Attenuated by Ketamine in Mice

Background: People with schizophrenia exhibit reduced ability to detect change in the auditory environment, which has been linked to abnormalities in N-methyl-D-aspartate (NMDA) receptor-mediated glutamate neurotransmission. This ability to detect changes in stimulus qualities can be measured with electroencephalography using auditory event-related potentials (ERPs). For example, reductions in the N100 and mismatch negativity (MMN), in response to pitch deviance, have been proposed as endophenotypes of schizophrenia. This study examines a novel rodent model of impaired pitch deviance detection in mice using the NMDA receptor antagonist ketamine. Methods: ERPs were recorded from unanesthetized mice during a pitch deviance paradigm prior to and following ketamine administration. First, N40 amplitude was evaluated using stimuli between 4 and 10 kHz to assess the amplitude of responses across the frequency range used. The amplitude and latency of the N40 were analyzed following standard (7 kHz) and deviant (59 kHz) stimuli. Additionally, we examined which portions of the ERP are selectively altered by pitch deviance to define possible regions for the mouse MMN. Results: Mice displayed increased N40 amplitude that was followed by a later negative component between 50 and 75 msec in response to deviant stimuli. Both the increased N40 and the late N40 negativity were attenuated by ketamine. Ketamine increased N40 latency for both standard and deviant stimuli alike. Conclusions: The mouse N40 and a subsequent temporal region have deviance response properties similar to the human N100 and, possibly, MMN. Deviance responses were abolished by ketamine, suggesting that ketamine-induced changes in mice mimic deviance detection deficits in schizophrenia.
Wind Power Smoothing by Controlling the Inertial Energy of Turbines With Optimized Energy Yield

Power fluctuations caused by wind speed variations affect power quality, especially in weak or isolated grids, and degrade the reliability of wind power converters. This paper develops a wind power smoothing scheme by making use of the large inertial energy of a wind turbine system (WTS). The proposed method, which explores the energy storage capability of the WTS shaft, is easy to implement by adding two additional terms into the existing maximum power point tracking (MPPT) control reference. Based on the law of conservation of energy, the new controller includes two parts: one part is to duplicate the original power trajectory under the MPPT control and the other is to compensate the fluctuations of it. In this way, two control objectives, namely, optimized wind power capture and its smoothing can be achieved simultaneously since the rotor rotates around the optimum speed points. Meanwhile, the mechanical stress of a WTS is alleviated with less oscillating torque reference, and the stability of a WTS is maintained by disabling the smoothing function when the rotor speed hits the speed limits. RTDS simulations of double-fed induction generator-and direct-driven permanent magnet synchronous generator-based WTSs are used to demonstrate the effectiveness of the proposed power smoothing control algorithm. The proposed method is validated on both a single WTS and a wind farm. Quantitative analysis is then carried out to evaluate the relationship between the smoothing performance and the efficiency of wind energy capture.
Erectile dysfunction, loss of libido and low sexual frequency increase the risk of cardiovascular disease in men with low testosterone

Abstract Introduction: Testosterone deficiency increases the cardiovascular disease (CVD) risk. Aim: To evaluate the effect of erectile dysfunction (ED), sexual frequency and hypogonadal symptoms on CVD risk. Methods: A total of 395 hypogonadal men aged 45–74 years were surveyed using the Androgen Deficiency in the Aging Male and the International Index of Erectile Function. Main outcome measures: The 10-year CVD risk was measured with the Framingham Risk Score. Logistic regression was performed to obtain the odds ratios of sexual function and hypogonadal symptoms for a 10-year CVD risk ≥20% (high risk). Results: The mean age was 56.1 ± 6.7 years. The mean 10-year CVD risk of the whole cohort was 18.1% ± 11.4%, while 131 subjects (33.2%) were classified as high risk. Logistic regression revealed that ED severity was associated with CVD risk [OR = 2.37 (CI 1.24–4.51) for mild-to-moderate ED, OR = 4.39 (1.78–8.43) for moderate ED and OR = 12.81 (4.65–26.11) for severe ED]. Compared to sexual frequency <1 per month, sexual frequency ≥4 decreased the risk of high CVD risk [OR = 0.35 (0.23–0.780)]. Loss of libido [OR = 2.95 (1.91–4.12)] and less strong erection [OR = 3.87 (CI 2.11–4.95)] increased the risk of high CVD risk. All remained significant after adjustment for age and testosterone. Conclusions: ED, decreased sexual frequency and loss of libido predict a high 10-year CVD risk in hypogonadal men.
Place recognition: An Overview of Vision Perspective

Place recognition is one of the most fundamental topics in the computer-vision and robotics communities, where the task is to accurately and efficiently recognize the location of a given query image. Despite years of knowledge accumulated in this field, place recognition still remains an open problem due to the various ways in which the appearance of real-world places may differ. This paper presents an overview of the place-recognition literature. Since condition-invariant and viewpoint-invariant features are essential factors to long-term robust visual place-recognition systems, we start with traditional image-description methodology developed in the past, which exploits techniques from the image-retrieval field. Recently, the rapid advances of related fields, such as object detection and image classification, have inspired a new technique to improve visual place-recognition systems, that is, convolutional neural networks (CNNs). Thus, we then introduce the recent progress of visual place-recognition systems based on CNNs to automatically learn better image representations for places. Finally, we close with discussions and mention of future work on place recognition.
Temporal Variations of Seismic Velocity at Paradox Valley, Colorado, Using Passive Image Interferometry

In our recent article (Ugalde et al. , 2014), we applied the passive image interferometry technique of Sens‐Schonfelder and Wegler (2006) to monitor seismic velocity changes in Paradox Valley (southwestern Colorado). For this purpose, we computed the autocorrelation …
MOOCs as an intelligent online learning platform in Thailand: Past, present, future challenges and opportunities

Massive Open Online Courses or MOOCs have emerged in the past decade as a powerful platform that proffers quality education and training to a vast pool of learners worldwide. While MOOCs have shown successful in bringing online education up to the next level in developed country such as USA; such realization is barely observed in developing countries such as Thailand. With many failed attempts to establish MOOCs in Thailand, doubts often arise whether MOOCs would be the right platform that would mitigate the problems of the existing educational system in such a nation. In this paper, we first provide the history of MOOCs in Thailand. Then we discuss some of the major challenges that prevent such an online learning platform to thrive in Thailand, compared to those offline classroom-based educational programs. Furthermore, we present a comprehensive investigation of MOOC development in nearby countries such as Japan and Malaysia. Finally, both direct and indirect opportunities that successful MOOCs can offer are discussed, that focuses on the Thailand educational settings.
Distribution of Four HIV Type 1-Resistance Polymorphisms ( CCR 5D 32 , CCR 5m 303 , CCR 2-64 I , and SDF 1-3 0 A ) in the Bahraini Population

Allelic differences of chemokine (C-C motif ) receptor 5 (CCR5) and CCR2, as well as the ligand for the chemokine receptor CXCR4, stromal-derived factor (SDF-1), are known to suppress HIV-1 transmission and to be involved in delay in HIV-1 disease progression. The aim of our study was to investigate the frequencies of four mutations that confer resistance to HIV-1: CCR5-D32, CCR5-m303, CCR2-64I, and SDF1-30A among Bahrainis. We have studied the DNA polymorphisms in 304 unrelated healthy Bahraini individuals without any known history of HIV-1 infection or AIDS symptoms. The CCR5-D32 mutation was detected by PCR analysis, while the CCR5-m303, CCR264I, and SDF1-30A mutations were detected by PCR-restriction fragment length polymorphism (PCR-RFLP) tests. Allele frequencies and the fit to the Hardy–Weinberg equilibrium were evaluated using the Arlequin population genetics application. The frequencies of the CCR5-D32, CCR2-64I, and SDF1-30A alleles were 2.8%, 8.9%, and 26.5%, respectively. No mutant alleles were detected for the CCR5-m303 mutation in 304 individuals. We estimated the risk of AIDS onset (relative hazard), computed from the three-locus genotype data. This is the first report of these four mutations conferring resistance to HIV-1 in the Bahraini population. The presence of the CCR5D32 allele among Bahrainis may be attributed to the admixture with people of European descent. The CCR2-64I allele and especially the SDF1-30A allele are predominant in the Bahraini population and may be associated with resistance to fast HIV-1 infection in Bahrainis, and thus their genotyping can be used for prognosis in HIV-infected individuals.
From Cages to Trapping Sets and Codewords: A Technique to Derive Tight Upper Bounds on the Minimum Size of Trapping Sets and Minimum Distance of LDPC Codes

Cages, defined as regular graphs with minimum number of nodes for a given girth, are well-studied in graph theory. Trapping sets are graphical structures responsible for error floor of low-density parity-check (LDPC) codes, and are well investigated in coding theory. In this paper, we make connections between cages and trapping sets. In particular, starting from a cage (or a modified cage), we construct a trapping set in multiple steps. Based on the connection between cages and trapping sets, we then use the available results in graph theory on cages and derive tight upper bounds on the size of the smallest trapping sets for variable-regular LDPC codes with a given variable degree and girth. The derived upper bounds in many cases meet the best known lower bounds and thus provide the actual size of the smallest trapping sets. Considering that non-zero codewords are a special case of trapping sets, we also derive tight upper bounds on the minimum weight of such codewords, i.e., the minimum distance, of variable-regular LDPC codes as a function of variable degree and girth.