LLukas22/scidocs huggingface dataset:
Clinical classifications of atrial fibrillation poorly reflect its temporal persistence: insights from 1,195 patients continuously monitored with implantable devices.

OBJECTIVES
This study aimed to identify how accurately the current clinical atrial fibrillation (AF) classifications reflect its temporal persistence.


BACKGROUND
Clinical classification of AF is employed to communicate its persistence, to select appropriate therapies, and as inclusion criterion for clinical trials.


METHODS
Cardiac rhythm histories of 1,195 patients (age 73.0 ± 10.1 years, follow-up: 349 ± 40 days) with implantable devices were reconstructed and analyzed. Patients were classified as having paroxysmal or persistent AF by physicians at baseline in accordance with current guidelines. AF burden, measured as the proportion of time spent in AF, was obtained from the device. Additionally we evaluated the agreement between clinical and device-derived AF classifications.


RESULTS
Patients within the same clinical class were highly heterogeneous with regards to AF temporal persistence. Agreement between the clinical AF classification and the objective device-derived assessments of AF temporal persistence was poor (Cohen's kappa: 0.12 [95% CI: 0.05 to 0.18]). Patient characteristics influenced the clinical decision to classify AF as paroxysmal or persistent. Higher ejection fraction (odds ratio: 0.97/per unit [95% CI: 0.95 to 0.98/per unit]; p < 0.0001) and presence of coronary artery disease (odds ratio: 0.53 [95% CI: 0.32 to 0.88]; p = 0.01) were independently associated with a lower probability of being classified as persistent AF for the same AF burden level.


CONCLUSIONS
The currently used clinical AF classifications poorly reflect AF temporal persistence. Patient characteristics significantly influence the physician's classification of AF. Patients classified in identical clinical categories may be inherently heterogeneous with regard to AF temporal persistence. Further study is required to determine if patient selection on the basis of objective criteria derived from rigorous AF monitoring can improve reported outcomes and better identify responders and non-responders to treatments. (OMNI Study-Assessing Therapies in Medtronic Pacemaker, Defibrillator, and Cardiac Resynchronization Therapy Devices; NCT00277524; TRENDS: A Prospective Study of the Clinical Significance of Atrial Arrhythmias Detected by Implanted Device Diagnostics; NCT00279981).
The essential norm of a composition operator on a planar domain

We generalize to nitely connected planar domains the result of Joel Shapiro which gives a formula for the essential norm of a composition operator. In the process, we dene and give some properties of a generalization of the Nevanlinna counting function and prove generalizations of the Littlewood inequality, the Littlewood{Paley identity, and change of variable formulas, as well.
Early detection and counselling intervention of asthma symptoms in preschool children: study design of a cluster randomised controlled trial

BACKGROUND
Prevention of childhood asthma is an important public health objective. This study evaluates the effectiveness of early detection of preschool children with asthma symptoms, followed by a counselling intervention at preventive child health centres. Early detection and counselling is expected to reduce the prevalence of asthma symptoms and improve health-related quality of life at age 6 years.


METHODS/DESIGN
This cluster randomised controlled trial was embedded within the Rotterdam population-based prospective cohort study Generation R in which 7893 children (born between April 2002 and January 2006) participated in the postnatal phase. Sixteen child health centres are involved, randomised into 8 intervention and 8 control centres. Since June 2005, an early detection tool has been applied at age 14, 24, 36 and 45 months at the intervention centres. Children who met the intervention criteria received counselling intervention (personal advice to parents to prevent smoke exposure of the child, and/or referral to the general practitioner or asthma nurse). The primary outcome was asthma diagnosis at age 6 years. Secondary outcomes included frequency and severity of asthma symptoms, health-related quality of life, fractional exhaled nitric oxide and airway resistance at age 6 years. Analysis was according to the intention-to-treat principle. Data collection will be completed end 2011.


DISCUSSION
This study among preschool children provides insight into the effectiveness of early detection of asthma symptoms followed by a counselling intervention at preventive child health centres.


TRIAL REGISTRATION
Current Controlled Trials ISRCTN15790308.
Matrix Multiplication via Arithmetic Progressions

We present a new method for accelerating matrix multiplication asymptotically. This work builds on recent ideas of Volker Strassen, by using a basic trilinear form which is not a matrix product. We make novel use of the Salem-Spencer Theorem, which gives a fairly dense set of integers with no three-term arithmetic progression. Our resulting matrix exponent is 2.376.
A Portable Surveillance Camera Architecture using One-bit Motion Detection

We present a surveillance camera architecture using a one-bit motion detection algorithm for portable applications. The conventional surveillance system requires too many components and is too complicated for portable applications. In this paper, we propose a simple surveillance camera architecture with a motion detector that can detect changes of an object within its surroundings for low-power and low-cost applications. The proposed motion-detection algorithm uses one-bit images which are selected using a binary search algorithm that is decided by varying the reference voltage. We verify all the functions of the motion detector through the use of a user interface program on an FPGA board. Experimental results are also presented1.
Effects of a pharmacotherapy follow-up in community pharmacies on type 2 diabetes patients in Brazil

Objective To evaluate the effects of pharmacotherapy follow-up (PF) on metabolic control and clinical outcomes in type 2 diabetic patients. Setting Six community pharmacies (4 intervention and 2 control) in the Curitiba metropolitan region (Brazil). Main outcome measure Glycosylated Haemoglobin A1 (HbA1) and fasting capillary glycaemia. Methods We conducted a 12-month controlled trial involving a total of 161 patients in six community pharmacies between July 2004 and March 2006. Pharmacotherapy follow-up was applied only to patients in the intervention group. Results Of the 161 patients enrolled, 96 completed the study (50 intervention and 46 control). The administration of 574 consultations with the intervention group patients led to 119 negative clinical outcomes (2.3/patient [SD = 1.6]). The majority of detected problems were related to the ineffectiveness of pharmacotherapy (68.1%). Relative to the control group, the intervention group exhibited greater glycosylated haemoglobin (HbA1) reduction (−2.2% [95%CI −2.8%:−1.6%] vs. −0.3 [95% CI −0.8:0.2]; P < 0.001) and greater fasting capillary glycaemia reduction (−20.1 mg/dl [95% CI −31.9 mg/dl:−8.3 mg/dl] vs. 4.3 mg/dl [95% CI −13.4 mg/dl:22.2 mg/dl]; P = 0.022). These differences persisted after adjustment for baseline values. There were no significant differences in any other clinical measures between the groups. There were also no significant changes in the number of medications and treatment regimens between groups, with the exception of the percentage of patients undergoing lipid lowering treatment, which increased in the intervention group from 16% to 24% (P = 0.018). The initial medication regimen complexity index (MRCI) in the intervention group was 15.5 (SD = 7.8, range 4–40.5), and it decreased by 1.2 units (SD = 5.9) after 12 months (P = 0.149). Conclusions PF of type 2 diabetic patients in community pharmacies can improve the glycaemia control of patients through optimisation of medication profiles without significant changes in either the number of drugs used or the regimen complexity.
Effect of an intervention to improve the cardiovascular health of family members of patients with coronary artery disease: a randomized trial.

BACKGROUND
Family members of patients with coronary artery disease (CAD) have higher risk of vascular events. We conducted a trial to determine if a family heart-health intervention could reduce their risk of CAD.


METHODS
We assessed coronary risk factors and randomized 426 family members of patients with CAD to a family heart-health intervention (n = 211) or control (n = 215). The intervention included feedback about risk factors, assistance with goal setting and counselling from health educators for 12 months. Reports were sent to the primary care physicians of patients whose lipid levels and blood pressure exceeded threshold values. All participants received printed materials about smoking cessation, healthy eating, weight management and physical activity; the control group received only these materials. The main outcomes (ratio of total cholesterol to high-density lipoprotein [HDL] cholesterol; physical activity; fruit and vegetable consumption) were assessed at 3 and 12 months. We examined group and time effects using mixed models analyses with the baseline values as covariates. The secondary outcomes were plasma lipid levels (total cholesterol, low-density lipoprotein cholesterol, HDL cholesterol and triglycerides); glucose level; blood pressure; smoking status; waist circumference; body mass index; and the use of blood pressure, lipid-lowering and smoking cessation medications.


RESULTS
We found no effect of the intervention on the ratio of total cholesterol to HDL cholesterol. However, participants in the intervention group reported consuming more fruit and vegetables (1.2 servings per day more after 3 mo and 0.8 servings at 12 mo; p < 0.001). There was a significant group by time interaction for physical activity (p = 0.03). At 3 months, those in the intervention group reported 65.8 more minutes of physical activity per week (95% confidence interval [CI] 47.0-84.7 min). At 12 months, participants in the intervention group reported 23.9 more minutes each week (95% CI 3.9-44.0 min).


INTERPRETATION
A health educator-led heart-health intervention did not improve the ratio of total cholesterol to HDL cholesterol but did increase reported physical activity and fruit and vegetable consumption among family members of patients with CAD. Hospitalization of a spouse, sibling or parent is an opportunity to improve cardiovascular health among other family members.


TRIAL REGISTRATION
clinicaltrials.gov, no NCT00552591.
Algorithms for rendering depth of field effects in computer graphics

Computer generated images by default render the entire scene in perfect focus. Both camera optics and the human visual system have limited depth of field, due to the finite aperture or pupil of the optical system. For more realistic computer graphics as well as to enable artistic control over what is and what is not in focus, it is desirable to add depth of field blurring. Starting with the work of Potmesil and Chakravarty[33][34], there have been numerous approaches to adding depth of field effects to computer graphics. Published work in depth of field for computer graphics has been previously surveyed by Barsky [2][3]. Later, interactive depth of field techniques were surveyed by Demers [12]. Subsequent to these surveys, however, there have been important developments. This paper surveys depth of field approaches in computer graphics, from its introduction to the current state of the art.
Characterization and detection of noise in clustering

Cluster analysis is an important tool in many scientific disciplines, and many clustering methods are available (see e.g. Everitt (1974) or Jain and Dubes (1988)). A single clustering method or algorithm cannot solve all the possible clustering problems, hence the proliferation of many techniques. Most clustering methods are plagued ~ith the problem of noisy data, i.e., characterization o f good clusters amongst noisy data. In some cases, even a few noisy points or outliers affect the outcome of the method by severely biasing the algorithm. The noise that is just due to the statistical distribution o f the measuring instrument is usually of no concern. On the other hand, the completely arbitrary noise points that just do not belong to the pattern or class being searched for are o f real concern. A good example o f that is in image processing, where one is searching for certain shapes, for instance, amongst all the edge elements detected. An approach that is frequently recommended (for example, Jain and Dubes (1988)) is where one tries to identify such data and removes it before application o f the clustering algorithms. In many cases, however, that may not be possible or it may be extremely difficult. In this paper, a class of algorithms based on the square-error clustering (a sub-class o f partitional clustering) is considered. The performance of the algorithms o f this kind is highly susceptible to outliers or noisy points. The K-meaus type algorithms is one example where each point in the data-set must be assimaed to one o f the dusters. Because of this requirement, even the noise points have to be allotted to one o f the good clusters, and that would deteriorate the performance o f the algorithm. One approach to solve this problem is as proposed by Jolion and Rosenfeld (1989), where each data point is # y en a weight proportional to the density o f data points in its vicinity, thus assigning higher weights to the points belonging to the clusters, while assigning lower weights to the noise or background points. Thus the approach results in preprocessing o f the data in order to reduce the bias due to noise background. The
Building Better Quality Predictors Using "$\epsilon$-Dominance"

Despite extensive research, many methods in software quality prediction still exhibit some degree of uncertainty in their results. Rather than treating this as a problem, this paper asks if this uncertainty is a resource that can simplify software quality prediction. For example, Deb’s principle of ε-dominance states that if there exists some ε value below which it is useless or impossible to distinguish results, then it is superfluous to explore anything less than ε . We say that for “large ε problems”, the results space of learning effectively contains just a few regions. If many learners are then applied to such large ε problems, they would exhibit a “many roads lead to Rome” property; i.e., many different software quality prediction methods would generate a small set of very similar results. This paper explores DART, an algorithm especially selected to succeed for large ε software quality prediction problems. DART is remarkable simple yet, on experimentation, it dramatically outperforms three sets of state-of-the-art defect prediction methods. The success of DART for defect prediction begs the questions: how many other domains in software quality predictors can also be radically simplified? This will be a fruitful direction for future work.
VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

With the advent of affordable depth sensors, 3D capture becomes more and more ubiquitous and already has made its way into commercial products. Yet, capturing the geometry or complete shapes of everyday objects using scanning devices (eg. Kinect) still comes with several challenges that result in noise or even incomplete shapes. Recent success in deep learning has shown how to learn complex shape distributions in a data-driven way from large scale 3D CAD Model collections and to utilize them for 3D processing on volumetric representations and thereby circumventing problems of topology and tessellation. Prior work has shown encouraging results on problems ranging from shape completion to recognition. We provide an analysis of such approaches and discover that training as well as the resulting representation are strongly and unnecessarily tied to the notion of object labels. Furthermore, deep learning research argues [1] that learning representation with over-complete model are more prone to overfitting compared to the approach that learns from noisy data. Thus, we investigate a full convolutional volumetric denoising auto encoder that is trained in a unsupervised fashion. It outperforms prior work on recognition as well as more challenging tasks like denoising and shape completion. In addition, our approach is atleast two order of magnitude faster at test time and thus, provides a path to scaling up 3D deep learning.
Approach to TDT-2 : Segmentation , Detection , and Tracking

This paper reports the results achieved by Carnegie Mellon University on the Topic Detection and Tracking Project’s secondyear evaluation for the segmentation, detection, and tracking tasks. Additional post-evaluation improvements are also
Shared knowledge construction process in an open-source software development community: an investigation of the Gallery community

An investigation was conducted to study shared knowledge construction process in an Open-Source Software Development (OSSD) community. Using a qualitative study approach, we examined the resources, tools, and activities in the Gallery community to create a rich description of the interrelationships among people, activities, and media. Of particular interest was how the individuals contributed to the building of a shared knowledge base through collaborative problemsolving and decision-making processes, mediated with the OSSD environment. The study indicated that the collaboration process was symbolized by multiple rounds of discussions, which were means to pool individuals’ expertise and experiences to obtain quality problem-solving and decision-making outcomes. The study also revealed that the OSSD environment mediated the collaborative efforts through virtual collaboration space, visual organization, and communication tools. The findings have important implications for designing effective instruction specifically for computing disciplines in promoting students’ collaborative problem solving and decision making.
Design of feedback linearization control and reconfigurable control allocation with application to a quadrotor UAV

Based on the developed nonlinear dynamic equations of a quadrotor (named as Qball-X4) UAV (Unmanned Aerial Vehicle), attitude and trajectory tracking control designs based on an inner/outer loop control structure has been proposed in this paper. Feedback linearization is designed to control the attitude stability in inner loop, traditional PID is designed to follow trajectory in accordance with pre-planned paths based on the Qball-X4 nonlinear model. For taking care of faults occurred in the UAV during the flight, reconfigurable control allocation is implemented together with the above controllers. Performance of constrained optimization algorithm for reconfigurable control allocation design — Fixed-point (Fix) algorithm with applications to Qball-X4 is evaluated under different partial-loss fault cases. Various simulation results have been provided to demonstrate the validity of the fault tolerant control system design and the effectiveness of the reconfigurable control allocation design in trajectory tracking control.
Leishmania major lipophosphoglycan: discrepancy in Toll-like receptor signaling.

Lipophosphoglycan (LPG) is structurally characterized by a series of phosphoglycan repeat units. Cellular LPG, isolated from promastigotes, has a very similar structure to culture supernatant LPG, but differs in the average number of phosphorylated oligosaccharide repeat units and in glycan composition. Comparison of these LPGs with capillary electrophoresis and immunoblotting indicate that these molecules are highly conserved structurally and composed of galactosylated Gal-Man repeats but their size and molecular weight are very different which is due to glycan portion. There are 30 and 20 repeat units in sLPG and mLPG, respectively. Both LPGs induced nitric oxide in macrophages cell line while sLPG had the higher stimulatory effect. In the presence of anti-TLR2 nitric oxide stimulated by LPG was reduced to control levels. In addition, in the presence of anti-TLR4, nitric oxide stimulated by LPGs was not affected. We propose that lipophosphoglycan induces nitric oxide production via TLR2 signaling pathway.
Roles of glutamate signaling in preclinical and/or mechanistic models of depression

Accumulating evidence suggests that the glutamatergic system plays important roles in the pathophysiology and treatment of major depressive disorder (MDD). Abnormalities in the glutamatergic system are definitely observed in this disorder, and certain glutamatergic agents exhibit antidepressant effects in patients with MDD. In this review, we summarize the preclinical findings suggesting the involvement of glutamate signaling in the pathophysiology and treatment of MDD. Preclinical animal models for depression are often characterized by changes in molecules related to glutamatergic signaling. Some antidepressants exert their effects by affecting glutamatergic system components in animals. Animals with genetically modified glutamatergic function exhibit depression-like behaviors or anti-depressive behavior. In addition, several types of glutamatergic agents have shown antidepressant-like effects in preclinical models for depression. Many types of glutamate receptors (NMDA, AMPA, and metabotropic glutamate receptors) or transporters appear to be involved in the etiology of depression or in the mechanisms of action of antidepressants. These functional proteins related to glutamate signal transduction are potential targets for a new generation of antidepressants with fast-onset effects, such as the NMDA antagonist ketamine.
Androids as an Experimental Apparatus : Why Is There an Uncanny Valley and Can We Exploit It ?

Abstract. It seems natural to assume that the more It seems natural to assume that the more closely robots come to resemble people, the more likely they are to elicit the kinds of responses people direct toward each other. However, subtle flaws in appearance and movement only seem eerie in very humanlike robots. This uncanny phenomenon may be symptomatic of entities that elicit a model of a human other but do not measure up to it. If so, a very humanlike robot may provide the best means of finding out what kinds of behavior are perceived as human, since deviations from a human other are more obvious. In pursuing this line of inquiry, it is essential to identify the mechanisms involved in evaluations of human likeness. One hypothesis is that an uncanny robot elicits an innate fear of death and culturally-supported defenses for coping with death’s inevitability. An experiment, which borrows from the methods of terror management research, was performed to test this hypothesis. Across all questions subjects who were exposed to a still image of an uncanny humanlike robot had on average a heightened preference for worldview supporters and a diminished preference for worldview threats relative to the control group.