LLukas22/scidocs huggingface dataset:
Accuracy of diagnosing atrial fibrillation on electrocardiogram by primary care practitioners and interpretative diagnostic software: analysis of data from screening for atrial fibrillation in the elderly (SAFE) trial.

OBJECTIVE
To assess the accuracy of general practitioners, practice nurses, and interpretative software in the use of different types of electrocardiogram to diagnose atrial fibrillation.


DESIGN
Prospective comparison with reference standard of assessment of electrocardiograms by two independent specialists.


SETTING
49 general practices in central England.


PARTICIPANTS
2595 patients aged 65 or over screened for atrial fibrillation as part of the screening for atrial fibrillation in the elderly (SAFE) study; 49 general practitioners and 49 practice nurses.


INTERVENTIONS
All electrocardiograms were read with the Biolog interpretative software, and a random sample of 12 lead, limb lead, and single lead thoracic placement electrocardiograms were assessed by general practitioners and practice nurses independently of each other and of the Biolog assessment.


MAIN OUTCOME MEASURES
Sensitivity, specificity, and positive and negative predictive values.


RESULTS
General practitioners detected 79 out of 99 cases of atrial fibrillation on a 12 lead electrocardiogram (sensitivity 80%, 95% confidence interval 71% to 87%) and misinterpreted 114 out of 1355 cases of sinus rhythm as atrial fibrillation (specificity 92%, 90% to 93%). Practice nurses detected a similar proportion of cases of atrial fibrillation (sensitivity 77%, 67% to 85%), but had a lower specificity (85%, 83% to 87%). The interpretative software was significantly more accurate, with a specificity of 99%, but missed 36 of 215 cases of atrial fibrillation (sensitivity 83%). Combining general practitioners' interpretation with the interpretative software led to a sensitivity of 92% and a specificity of 91%. Use of limb lead or single lead thoracic placement electrocardiograms resulted in some loss of specificity.


CONCLUSIONS
Many primary care professionals cannot accurately detect atrial fibrillation on an electrocardiogram, and interpretative software is not sufficiently accurate to circumvent this problem, even when combined with interpretation by a general practitioner. Diagnosis of atrial fibrillation in the community needs to factor in the reading of electrocardiograms by appropriately trained people.
Consumers Prefer Bundled Add-Ins

Software such as operating systems, word processing, spreadsheets, graphics, and others often serves as a base for a number of third-party add-in products or plug-ins. These add-ins enhance the functionality of the base product. Unless protected by patents, these add-ins can potentially be bundled into the base software. The impact of this bundling on the profits of the base software producer and the consumer depends on the proportion of consumers that value 'the add-in and the penalty that some consumers incur from finding only a bundled product available when they do not desire the add-in. Using a model of the market, we show that the price of the bundle will be less than the sum of the prices of the base and add-in software when they are sold separately. We also show that the total consumer surplus and the social welfare increase if the base software producer's profit increases with bundling.
VOCALOID - commercial singing synthesizer based on sample concatenation

The song submitted here to the “Synthesis of Singing Challenge” is synthesized by the latest version of the singing synthesizer “Vocaloid”, which is commercially available now. In this paper, we would like to present the overview of Vocaloid, its product lineups, description of each component, and the synthesis technique used in Vocaloid.
Complete remission of ovarian cancer induced intractable malignant ascites with intraperitoneal bevacizumab. Immunological observations and a literature review

Malignant ascites resistant to conventional drugs frequently affects ovarian cancer patients at the end of life. Here we report the case of a patient who benefited from complete resolution of ascites after low dose intraperitoneal administration of bevacizumab. Immunological analyses showed an initial increase in proportion and function of CD8+ effector T cells and a reduction of circulating Treg cells. A review of the current literature regarding bevacizumab in ovarian cancer is reported. Bevacizumab has shown a high efficacy in the treatment of ovarian cancer. Intraperitoneal administration induces an immune activation and appears promising in the treatment of malignant ascites.
Arthroscopic Transtibial Pullout Repair for Posterior Medial Meniscus Root Tears: A Systematic Review of Clinical, Radiographic, and Second-Look Arthroscopic Results.

PURPOSE
To systematically review the results of arthroscopic transtibial pullout repair (ATPR) for posterior medial meniscus root tears.


METHODS
A systematic electronic search of the PubMed database and the Cochrane Library was performed in September 2014 to identify studies that reported clinical, radiographic, or second-look arthroscopic outcomes of ATPR for posterior medial meniscus root tears. Included studies were abstracted regarding study characteristics, patient demographic characteristics, surgical technique, rehabilitation, and outcome measures. The methodologic quality of the included studies was assessed with the modified Coleman Methodology Score.


RESULTS
Seven studies with a total of 172 patients met the inclusion criteria. The mean patient age was 55.3 years, and 83% of patients were female patients. Preoperative and postoperative Lysholm scores were reported for all patients. After a mean follow-up period of 30.2 months, the Lysholm score increased from 52.4 preoperatively to 85.9 postoperatively. On conventional radiographs, 64 of 76 patients (84%) showed no progression of Kellgren-Lawrence grading. Magnetic resonance imaging showed no progression of cartilage degeneration in 84 of 103 patients (82%) and showed reduced medial meniscal extrusion in 34 of 61 patients (56%). On the basis of second-look arthroscopy and magnetic resonance imaging in 137 patients, the healing status was rated as complete in 62%, partial in 34%, and failed in 3%. Overall, the methodologic quality of the included studies was fair, with a mean modified Coleman Methodology Score of 63.


CONCLUSIONS
ATPR significantly improves functional outcome scores and seems to prevent the progression of osteoarthritis in most patients, at least during a short-term follow-up. Complete healing of the repaired root and reduction of meniscal extrusion seem to be less predictable, being observed in only about 60% of patients. Conclusions about the progression of osteoarthritis and reduction of meniscal extrusion are limited by the small portion of patients undergoing specific evaluation (44% and 35% of the study group, respectively).


LEVEL OF EVIDENCE
Level IV, systematic review of Level III and IV studies.
Growing Pains with Information Overload

Emotional and cognitive overload with information technology can be caused by more than just too many digital devices.
A 9-GHz 65-nm Intel® Pentium 4 Processor Integer Execution Unit

This paper describes a fourth generation Intel Pentium 4 processor integer execution core operating at 9 GHz in a 1.3-V, 65-nm CMOS technology at 70degC. Low-voltage-swing circuits of the 90-nm design are replaced by: 1) 2times frequency fast clock (FCLK)-optimized domino clocking scheme; 2) segmented arithmetic and logic unit (ALU) front-end multiplexer; 3) sparse-tree ALU adder; 4) merged add/subtract sparse-tree address generation unit (AGU) design; 5) speculative RC-delay-optimized rotator; and 6) single-rail L0 cache and alignment multiplexer, resulting in 8.4% reduction in integer core normalized active power and 42% reduction in normalized leakage power. The use of standard domino/static tools and methodologies lowers design complexity, reducing development cost and time. The redesign also reduces integer core thermal density, resulting in an 8degC reduction in CPU operating temperature
Determinants for Heart Rate Variability in a Normal Korean Population

This study examined the normal ranges and the determinants for various parameters of the short-term heart rate variability (HRV) measurements in a large Korean sample of healthy people. HRV measurements were obtained in 2,748 healthy men and 735 healthy women 18-65 yr of age. The mean total power (TP), low frequency (LF), high frequency (HF), and LF/HF ratio were 1,358.9 ± 1,840.8 ms(2), 417.3 ± 807.6 ms(2), 254.1 ± 414.1 ms(2), and 2.4 ± 20.9 ms(2) in the frequency-domain spectral analysis. The mean standard deviation of the normal-to-normal (NN) interval (SDNN) and the square root of the mean squared differences of successive NN intervals (RMSSD) were 39.6 ± 22.1 ms and 29.7 ± 18.1 ms in the time-domain analysis. The female subjects had significantly higher SDNN, RMSSD, and HF values than the male subjects. After controlling for age, there was no statistically significant difference in the SDNN. Quantile regression analysis showed that age and mean heart rate had a significant impact on short-term HRV measurement. Given that both clinicians and researchers are increasingly relying on short-term HRV assessment in measuring stress, our work suggests that age and gender should be considered as independent determinants for HRV.
Brain-computer interfaces for communication and control

The brain's electrical signals enable people without muscle control to physically interact with the world.
A Dynamic Histogram Equalization for Image Contrast Enhancement

A smart contrast enhancement technique, dynamic histogram equalization (DHE), is proposed. It takes control over traditional histogram equalization for appropriate contrast enhancement of images without introducing any severe side affects such as washed out appearance, over-enhancement of some features and noises, checkerboard effects etc.
Mindfulness-based stress reduction versus pharmacotherapy for chronic primary insomnia: a randomized controlled clinical trial.

OBJECTIVE
The aim of this study was to investigate the potential of mindfulness-based stress reduction (MBSR) as a treatment for chronic primary insomnia.


DESIGN
A randomized controlled trial was conducted.


SETTING
The study was conducted at a university health center.


PATIENTS
Thirty adults with primary chronic insomnia based on criteria of the Diagnostic and Statistical Manual of Mental Disorders, Text Revision, 4th Edition were randomized 2:1 to MBSR or pharmacotherapy (PCT).


INTERVENTIONS
Mindfulness-based stress reduction, a program of mindfulness meditation training consisting of eight weekly 2.5 hour classes and a daylong retreat, was provided, with ongoing home meditation practice expectations during three-month follow-up; PCT, consisting of three milligrams of eszopiclone (LUNESTA) nightly for eight weeks, followed by three months of use as needed. A 10-minute sleep hygiene presentation was included in both interventions.


MAIN OUTCOMES
The Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), sleep diaries, and wrist actigraphy were collected pretreatment, posttreatment (eight weeks), and at five months (self-reports only).


RESULTS
Between baseline and eight weeks, sleep onset latency (SOL) measured by actigraphy decreased 8.9 minutes in the MBSR arm (P < .05). Large, significant improvements were found on the ISI, PSQI, and diary-measured total sleep time, SOL, and sleep efficiency (P < .01, all) from baseline to five-month follow-up in the MBSR arm. Changes of comparable magnitude were found in the PCT arm. Twenty-seven of 30 patients completed their assigned treatment. This study provides initial evidence for the efficacy of MBSR as a viable treatment for chronic insomnia as measured by sleep diary, actigraphy, well-validated sleep scales, and measures of remission and clinical recovery.
Dead time generator for synchronous boost converters with GaN transistors

An analog dynamic dead time generator for synchronous boost converters based on GaN transistors is presented. A prototype was designed to operate at switching frequencies in the MHz range, with wide variations of the output voltage, and experimentally demonstrated its capability to stabilize the dead time duration to a few nanoseconds, independent of wide variations of the switching times of the transistor in use.
Prostate specific antigen decrease and prostate cancer diagnosis: antibiotic versus placebo prospective randomized clinical trial.

PURPOSE
Prostate inflammation can lead to an increase in serum prostate specific antigen concentration and confound the use of prostate specific antigen kinetics. Repeat prostate specific antigen measurements after a period of observation or a course of empirical antibiotics are controversial in terms of the optimal approach to reduce the confounding impact on prostate cancer screening. This issue was analyzed in patients with a diagnosis of type IV or asymptomatic prostatitis (National Institutes of Health classification) and high prostate specific antigen.


MATERIALS AND METHODS
We studied 200 men between 50 and 75 years old with a high prostate specific antigen (between 2.5 and 10 ng/dl). Of these patients 98 (49%) had a diagnosis of type IV prostatitis. In a prospective, double-blind trial they were randomized to receive placebo (49 patients, group 1) or 500 mg ciprofloxacin (49 patients, group 2) twice a day for 4 weeks. Prostate specific antigen was determined after treatment and all patients underwent transrectal ultrasound guided biopsy of the prostate.


RESULTS
In group 1, 29 (59.18%) patients presented with a decrease in prostate specific antigen and 9 (31%) had cancer on biopsy, while in group 2 there were 26 (53.06%) patients with a decrease in prostate specific antigen and 7 (26.9%) with prostate cancer. There was no statistical difference in either group in relation to prostate specific antigen decrease after treatment or the presence of tumor.


CONCLUSIONS
A considerable number of patients (49%) were diagnosed with type IV prostatitis and high prostate specific antigen in agreement with the current literature. Of the patients 26.9% to 31% presented with a decrease in prostate specific antigen after the use of antibiotic or placebo and harbor cancer as demonstrated on prostate biopsy. Prostate specific antigen decreases do not indicate the absence of prostate cancer.
Computational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data Points

Problem statement: Clustering is one of the most important research ar eas in the field of data mining. Clustering means creating groups of ob jects based on their features in such a way that th e objects belonging to the same groups are similar an d those belonging to different groups are dissimila r. Clustering is an unsupervised learning technique. T he main advantage of clustering is that interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. Clustering algorithms can be applied in many domains. Approach: In this research, the most representative algorithms K-Mean s and K-Medoids were examined and analyzed based on their basic approach. The best algorithm i n each category was found out based on their performance. The input data points are generated by two ways, one by using normal distribution and another by applying uniform distribution. Results: The randomly distributed data points were taken as input to these algorithms and clusters are found ou t for each algorithm. The algorithms were implement ed using JAVA language and the performance was analyze d based on their clustering quality. The execution time for the algorithms in each category was compar ed for different runs. The accuracy of the algorith m was investigated during different execution of the program on the input data points. Conclusion: The average time taken by K-Means algorithm is greater than the time taken by K-Medoids algorithm for both the case of normal and uniform distributions. The r esults proved to be satisfactory.
DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings

The paper describes our approach for SemEval-2018 Task 1: Affect Detection in Tweets. We perform experiments with manually compelled sentiment lexicons and word embeddings. We test their performance on twitter affect detection task to determine which features produce the most informative representation of a sentence. We demonstrate that general-purpose word embeddings produces more informative sentence representation than lexicon features. However, combining lexicon features with embeddings yields higher performance than embeddings alone.
Self-View Grounding Given a Narrated 360° Video

Narrated 360◦ videos are typically provided in many touring scenarios to mimic real-world experience. However, previous work has shown that smart assistance (i.e., providing visual guidance) can significantly help users to follow the Normal Field of View (NFoV) corresponding to the narrative. In this project, we aim at automatically grounding the NFoVs of a 360◦ video given subtitles of the narrative (referred to as “NFoV-grounding”). We propose a novel Visual Grounding Model (VGM) to implicitly and efficiently predict the NFoVs given the video content and subtitles. Specifically, at each frame, we efficiently encode the panorama into feature map of candidate NFoVs using a Convolutional Neural Network (CNN) and the subtitles to the same hidden space using an RNN with Gated Recurrent Units (GRU). Then, we apply soft-attention on candidate NFoVs to trigger sentence decoder aiming to minimize the reconstruct loss between the generated and given sentence. Finally, we obtain the NFoV as the candidate NFoV with the maximum attention without any human supervision. To train VGM more robustly, we also generate a reverse sentence conditioning on one minus the soft-attention such that the attention focuses on candidate NFoVs less relevant to the given sentence. The negative log reconstruction loss of the reverse sentence (referred to as “irrelevant loss”) is jointly minimized to encourage the reverse sentence to be different from the given sentence. To evaluate our method, we collect the first narrated 360◦ videos dataset and achieve state-of-the-art NFoV-grounding performance. Introduction Thanks to the availability of consumer-level 360◦ video cameras, many 360◦ videos are shared on websites like YouTube and Facebook. Among these videos, a subset of them is narrated with natural language phrases describing the video content. For instance, many videos consist of the guided tour of real estates (e.g., houses and apartments) or tourist locations. Intuitively, a 360◦ touring video provides viewers the freedom to follow the narrative and select Normal Field of Views (NFoVs) provided by typical video players (see Fig. 1). However, a study in Lin et al. (2017) suggests that visual guidance (i.e., assistance through visual indicator) is preferred to assist viewers to follow the NFoV described by the narrative. In order to provide the visual Copyright c © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. t t-1
Breaking a secure communication scheme based on the phase synchronization of chaotic systems.

A security analysis of a recently proposed secure communication scheme based on the phase synchronization of chaotic systems is presented. It is shown that the system parameters directly determine the cipher text waveform, hence it can be readily broken by system parameter estimation from the cipher text signal.
Interpreting Deep Visual Representations via Network Dissection

The success of recent deep convolutional neural networks (CNNs) depends on learning hidden representations that can summarize the important factors of variation behind the data. In this work, we describe \textit{Network Dissection}, a method that interprets networks by providing meaningful labels to their individual units. The proposed method quantifies the interpretability of CNN representations by evaluating the alignment between individual hidden units and visual semantic concepts. By identifying the best alignments, units are given interpretable labels ranging from colors, materials, textures, parts, objects and scenes. The method reveals that deep representations are more transparent and interpretable than they would be under a random equivalently powerful basis. We apply our approach to interpret and compare the latent representations of several network architectures trained to solve a wide range of supervised and self-supervised tasks. We then examine factors affecting the network interpretability such as the number of the training iterations, regularizations, different initialization parameters, as well as networks depth and width. Finally we show that the interpreted units can be used to provide explicit explanations of a given CNN prediction for an image. Our results highlight that interpretability is an important property of deep neural networks that provides new insights into what hierarchical structures can learn.
Autonomous Vehicle Navigation and MappingSystem

— Autonomous vehicle navigation gains increasing importance in various growing application areas. In this paper we described a system it navigates the vehicle autonomously to its destination. This system provides a communication between vehicle and internet using GPRS modem. This system interfaced with OSRM open source map through internet. So we can decide the robot path from internet. In non-urban Domains such as deserts the problem of successful GPS-based navigation appears to be almost solved, navigation in urban domains particularly in the close vicinity of buildings is still a challenging problem. In such situations GPS accuracy significantly drops down due to unavailability of GPS signal. This project also improves the efficiency in navigation. This system not only relay on GPS. To improve the efficiency it uses location information from inertial sensors also. This system uses rotatable laser range finder for obstacle sensing. This is also designed in such a way that It can be monitored from anywhere through internet. I. INTRODUCTION An autonomous vehicle, also known as a driverless vehicle, self-driving vehicle is an vehicle capable of fulfilling the human transportation capabilities of a traditional vehicle. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input. Autonomous vehicles sense their surroundings with such techniques as radar, lidar, GPS, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Some autonomous vehicles update their maps based on sensory input, allowing the vehicles to keep track of their position even when conditions change or when they enter uncharted environments. For any mobile robot, the ability to