LLukas22/scidocs huggingface dataset:
Rheolytic Pharmacomechanical Thrombectomy for the Management of Acute Limb Ischemia: Results From the PEARL Registry.

PURPOSE
To present the results of rheolytic pharmacomechanical thrombectomy (PMT) for the management of acute limb ischemia (ALI) as reported in the PEARL Registry (PEripheral Use of AngioJet Rheolytic Thrombectomy with a variety of catheter Lengths).


METHODS
A total of 283 patients (mean age 65±13 years; 170 men) presenting with ALI undergoing treatment with the AngioJet System at participating institutions were enrolled in the registry. Rutherford ALI categories included 26% with viable limbs, 38% with marginally threatened limbs, 35% with immediately threatened limbs, and <1% with irreversible damage. Procedure and follow-up data were collected for the calculation of outcomes. To control for patient selection bias, propensity score matching was used to compare outcomes for patients undergoing PMT with or without catheter-directed thrombolysis (CDT).


RESULTS
Procedure success was achieved in 235 (83%) of 283 patients. Half of the procedures (147, 52%) were completed without the need for adjunctive CDT. At 12-month follow-up, amputation-free survival and freedom from mortality were 81% and 91%, respectively; 12-month freedom from bleeding requiring transfusion was 91%, and freedom from renal failure was 95%. Subgroup analysis revealed significantly better outcomes in patients without infrapopliteal involvement and those who underwent PMT without CDT. In the matched cohorts, higher rates of procedure success, 12-month amputation-free survival, and 12-month freedom from amputation were observed in the PMT without CDT group (88% vs 74%, p=0.021; 87% vs 72%, p=0.028; 96% vs 81%, p=0.01, respectively).


CONCLUSIONS
The results support the use of PMT as a first-line treatment for ALI, providing a rapid reperfusion to the extremity, reduced procedure time, and an acceptable risk profile without compromising limb salvage.
Likelihood ratio tests for goodness-of-fit of a nonlinear regression model

We propose likelihood and restricted likelihood ratio tests for goodness-of-fit of nonlinear regression. The first order Taylor approximation around the MLE of the regression parameters is used to approximate the null hypothesis and the alternative is modeled nonparametrically using penalized splines. The exact finite sample distribution of the test statistics is obtained for the linear model approximation and can be easily simulated. We recommend using the restricted likelihood instead of the likelihood ratio test because restricted maximum likelihood estimates are not as severely biased as the maximum likelihood estimates in the penalized splines framework. Short title: LRTs for nonlinear regression
The role of interface organizations in science communication and understanding

www.frontiersinecology.org © The Ecological Society of America S research can provide important and timely insights into environmental issues, but scientists face many personal and institutional challenges to effectively synthesize and transmit their findings to relevant stakeholders. In this paper, we address how “interface” or “boundary” organizations – organizations created to foster the use of science knowledge in environmental policy making and environmental management, as well as to encourage changes in behavior, further learning, inquiry, discovery, or enjoyment – can help scientists improve and facilitate effective communication and the application of scientific information (Gieryn 1999). Interface organizations are synergistic and operate across a range of scales, purposes, and intensities of information flow between scientists and audiences. Considerable attention has focused on how to involve scientists in the decision-making process regarding natural resource management issues related to their area of expertise (Andersson 2004; Roth et al. 2004; Rinaudo and Garin 2005; Bacic et al. 2006; Olsson and Andersson 2007). These efforts have resulted in scientific input to environmental issues, including ecosystem management (Meffe et al. 2002), adaptive collaborative management (Buck et al. 2001; Colfer 2005), and integrated watershed management (Jeffrey and Gearey 2006). A common element of many of these approaches is the use of an organization or group to manage and facilitate the interaction between the scientists and the “users” or “managers” of a natural resource. Cash et al. (2003) identified key functions of successful “boundary management” organizations. These functions include communication, translation, and mediation (convening groups, as well as resolving differences). Successful efforts are characterized by having clear lines of responsibility and accountability on both sides of the boundary, and by providing a forum in which information can be co-produced by scientists and information users. Interface organizations typically: (1) Engage: seeking out scientists with important findings and then building or filling a demand for their insights among different communities and for various niches, contexts, and scales. The organization usually serves as a convener. SCIENCE, COMMUNICATION, AND CONTROVERSIES
Signal-dependent wavelets for electromyogram classification

In the study, an efficient method to perform supervised classification of surface electromyogram (EMG) signals is proposed. The method is based on the choice of a relevant representation space and its optimisation with respect to a training set. As EMG signals are the summation of compact-support waveforms (the motor unit action potentials), a natural tool for their representation is the discrete dyadic wavelet transform. The feature space was thus built from the marginals of a discrete wavelet decomposition. The mother wavelet was designed to minimise the probability of classification error estimated on the learning set (supervised classification). As a representative example, the method was applied to simulate surface EMG signals generated by motor units with different degrees of short-term synchronisation. The proposed approach was able to distinguish surface EMG signals with degrees of synchronisation that differed by 10%, with a misclassification rate of 8%. The performance of a spectral-based classification (error rate approximately 33%) and of the classification with Daubechies wavelet (21%) was significantly poorer than with the proposed wavelet optimisation. The method can be used for a number of different application fields of surface EMG classification, as the feature space is adapted to the characteristics of the signal that discriminate between classes.
Low miR-34c expression is associated with poor outcome in de novo acute myeloid leukemia.

INTRODUCTION
MicroRNA-34c (miR-34c) has been found to play important roles in tumorigenesis. However, little is known about miR-34c expression and the impact on prognosis in acute myeloid leukemia (AML).


METHODS
Real-time quantitative PCR (qRT-PCR) was performed to analyze the status of miR-34c expression in 122 patients with de novo AML and 62 normal controls.


RESULTS
MiR-34c expression in AML was significantly downregulated compared to controls (P < 0.001). Receiver operating characteristic curves (ROC) indicated the distinguishing value of miR-34c for discriminating whole-cohort AML, non-M3 AML, and cytogenetically normal AML (CN-AML) patients from healthy controls. No significant differences were found between low miR-34c-expressing and high miR-34c-expressing patients in age, sex, hemoglobin, platelet count, percentage of blasts in bone marrow (BM), WHO classifications, karyotypes, and eight gene mutations, but low miR-34c cases had higher white blood cells (WBC) than high miR-34c cases (P = 0.035). MiR-34c low-expressed patients had similar rates of complete remission (CR) as miR-34c high-expressed patients in whole-cohort AML, non-M3 AML, and CN-AML patients (P = 0.347, 0.314 and 0.167, respectively). Kaplan-Meier analysis indicated that patients with low miR-34c level had markedly shorter overall survival (OS) time in whole-cohort AML, non-M3 AML, and CN-AML patients (P = 0.033, 0.024 and 0.001, respectively). Furthermore, multivariate analysis confirmed that low miR-34c expression was an independent risk factor not only in whole-cohort AML (P = 0.040) but also in non-M3 AML (P = 0.015) and CN-AML patients (P = 0.021).


CONCLUSIONS
Our findings indicate that low miR-34c level is a novel promising biomarker in predicting prognosis in patients with de novo AML.
Job Satisfaction , Organizational Commitment , and Turnover Intention : A Case Study on Employees of a Retail Company in Malaysia

High employee turnover rate in Malaysia’s retail industry has become a major issue that needs to be addressed. This study determines the levels of job satisfaction, organizational commitment, and turnover intention of employees in a retail company in Malaysia. The relationships between job satisfaction and organizational commitment on turnover intention are also investigated. A questionnaire was developed using Job Descriptive Index, Organizational Commitment Questionnaire, and Lee and Mowday’s turnover intention items and data were collected from 62 respondents. The findings suggested that the respondents were moderately satisfied with job satisfaction facets such as promotion, work itself, co-workers, and supervisors but were unsatisfied with salary. They also had moderate commitment level with considerably high intention to leave the organization. All satisfaction facets (except for co-workers) and organizational commitment were significantly and negatively related to turnover intention. Based on the findings, retention strategies of retail employees were proposed. Keywords—Job satisfaction, organizational commitment, retail employees, turnover intention.
Best tests/clinical findings for screening and diagnosis of patellofemoral pain syndrome: a systematic review.

BACKGROUND
Diagnosis of patellofemoral pain syndrome (PFPS) is commonly performed using a myriad of clinical and imaging-based criteria.


OBJECTIVES
The objective of this systematic literature review was to summarize the research on accuracy of individual clinical tests/findings for PFPS.


DATA SOURCES
MEDLINE, ProQuest Nursing and Allied Health, Cochrane Trials, PEDro, and CINAHL. STUDY SELECTION OR ELIGIBILITY CRITERIA: PRISMA guidelines were followed for this review. To be considered for review, the study required: (1) a description of a clinical test or tests used for diagnosing PFPS (including a test that was combined with another finding such as patient history), (2) a report of the diagnostic accuracy of the measures (e.g., sensitivity and specificity), and (3) an acceptable reference standard for comparison. STUDY APPRAISAL OR SYNTHESIS METHODS: Quality Assessment of Studies of Diagnostic Accuracy (QUADAS) scores were completed on each selected article. Sensitivity, specificity, and negative and positive likelihood ratios (LR-/LR+) were calculated for each diagnostic test described.


RESULTS
The systematic search strategy and hand search revealed 704 potential articles, 9 of which met the criteria for this review; analysing a total of 22 PFPS clinical tests. After assessment using the QUADAS score, 1 of the 9 articles was of high quality. The tests with the highest reported diagnostic value were also associated with studies that had the lowest QUADAS values.


CONCLUSION
A majority of the studies that have investigated diagnostic accuracy of clinical tests for PFPS demonstrate notable design or reporting biases, and at this stage, determining the best tests for diagnosis of PFPS is still difficult.
Monitoring structural deterioration of railway turnout systems via dynamic wheel/rail interaction

Article history: Available online 4 April 2014 ‘Big data’ obtained from wayside detection systems and sensors installed on board a train show that actual loading history for a railway track is rather dynamic and transient. The dynamic loadings due to train and track interactions redistribute from the rails to the rail pad, from the rail pad to the railway sleeper, and from the railway sleeper to the underlying ground. Dynamic content redistributed onto each layer of track is also filtered by energy dissipation characteristic of materials and structures. As a critical infrastructure, railway turnout is a structural grillage system used to divert a train to other directions or other tracks. The wheel–rail contact over the crossing transfer zone often causes detrimental impact loads that rapidly deteriorate the turnout and its components. The dynamic responses of wheel–rail interaction depend largely on the non-smooth trajectory or wearing condition of crossing geometry. In reality, a railway line spreads over a large distance and monitoring such rail infrastructure is one of the challenges in rail industry. This paper presents a methodology and application to evaluate and monitor the structural deterioration of railway turnout systems in an Australian urban rail network. The method has integrated numerical train/track simulations, axle box acceleration and ride quality data obtained from the calibrated track inspection vehicle “AK Car”. © 2014 Elsevier Ltd.
FUNDAMENTALS OF FLUID FILM JOURNAL BEARING OPERATION AND MODELING by Minhui He

Widely used in turbomachinery, the fluid film journal bearing is critical to a machine’s overall reliability level. Their design complexity and application severity continue to increase making it challenging for the plant machinery engineer to evaluate their reliability. This tutorial provides practical knowledge on their basic operation and what physical effects should be included in modeling a bearing to help ensure its reliable operation in the field. All the important theoretical aspects of journal bearing modeling, such as film pressure, film and pad temperatures, thermal and mechanical deformations, and turbulent flow are reviewed. Through some examples, the tutorial explores how different effects influence key performance characteristics like minimum film thickness, Babbitt temperature as well as stiffness and damping coefficients. Due to their increasing popularity, the operation and analysis of advanced designs using directed lubrication principles, such as inlet grooves and starvation, are also examined with several examples including comparisons to manufacturers’ test data. 155 FUNDAMENTALS OF FLUID FILM JOURNAL BEARING OPERATION AND MODELING
Unscented Kalman filter and Magnetic Angular Rate Update (MARU) for an improved Pedestrian Dead-Reckoning

The Extended Kalman Filter (EKF) has been the state of the art in Pedestrian Dead-Reckoning for foot-mounted Inertial Measurements Units. However due to the non-linearity in the propagation of the orientation the EKF is not the optimal Bayesian filter. We propose the usage of the Unscented Kalman Filter (UKF) as the integration algorithm for the inertial measurements. The UKF improves the mean and covariance propagation needed for the Kalman filter. Although the UKF provides a better estimate of the orientation, with Zero velocity UPdaTes (ZUPT) measurements, the yaw and the bias in the gyroscope associated with it becomes unobserved and might generate errors in the positioning. We studied the changes in the magnetic field during the stance phase and their relationship with the turn rates to propose three measurements using the magnetometer signal that will be called Magnetic Angular Rate Updates (MARUs). The first measurement uses the change in the angle of the magnetic field in the horizontal plane to measure the change in the yaw and provides a simple measurement for the UKF implementation. The second measurement relates the change in the magnetic field vector to the turn rate and provides information on the bias of the gyroscope for an UKF. The last measurement uses a first order approximation to generate a linear relationship with the gyroscope bias and therefore it can be used in an EKF. Finally we proposed a metric for the reliability of the stance as a way to use the pre and post stance information but adjusting the covariance of the measurements gradually from swing to stance. These methods were tested on real and simulated signals and they have shown improvements over the original PDR algorithms.
Pedestrian Inattention Blindness While Playing Pokémon Go as an Emerging Health-Risk Behavior: A Case Report

BACKGROUND
Cases of trauma resulting from the use of mobile phones while driving motor vehicles have become quite common in recent years. Road injuries incurred by people playing video games on mobile phones (or other media devices) while walking have also become a cause for concern. Pokémon Go has been the world's most popular game since it was launched in July 2016, with more than 15 million players trying to catch all Pokémon available in the game; however, the case detailed here is the first reported accident in the medical literature caused by a pedestrian distracted by the game while crossing a street.


OBJECTIVE
We aim to provide additional information on the innovative nature of distractions that generate risks in road-users, and to explore the underreporting of pedestrian-motor vehicle collisions due to mobile device usage.


METHODS
We included in this case report a 25-year-old male who suddenly crossed a road while playing Pokémon Go and was hit by a van, reporting several injuries and being assisted by the Emergency Medical Service of our hospital (Padova, Italy). The patient's history, the circumstances in which the collision happened, imaging data, and clinical course information were recorded per our hospital's privacy policy.


RESULTS
The patient hit by the van was playing Pokémon Go on his mobile phone while crossing a street, despite red traffic lights, which he did not notice due to of the distraction induced by the game.


CONCLUSIONS
Mobile videogames that imply movement (ie, walking, running, cycling) to play are an effective way to improve physical activity practice, especially in adolescents and young adults. Nevertheless, cases like the one presented here point out that these games could pose a significant risk to users who play while walking, cycling, or driving in unsafe areas such as city streets, because players become distracted and may ignore surrounding hazards. Comprehensive, multilevel interventions are needed to reduce accidents caused by distraction, and to stress findings on the positive and negative effects of video games, which are becoming a source of public health concern. Health care providers should be aware of their chief role in these possible prevention strategies, based on their direct interactions with road incident victims.
Decoding hand movement velocity from electroencephalogram signals during a drawing task

BACKGROUND
Decoding neural activities associated with limb movements is the key of motor prosthesis control. So far, most of these studies have been based on invasive approaches. Nevertheless, a few researchers have decoded kinematic parameters of single hand in non-invasive ways such as magnetoencephalogram (MEG) and electroencephalogram (EEG). Regarding these EEG studies, center-out reaching tasks have been employed. Yet whether hand velocity can be decoded using EEG recorded during a self-routed drawing task is unclear.


METHODS
Here we collected whole-scalp EEG data of five subjects during a sequential 4-directional drawing task, and employed spatial filtering algorithms to extract the amplitude and power features of EEG in multiple frequency bands. From these features, we reconstructed hand movement velocity by Kalman filtering and a smoothing algorithm.


RESULTS
The average Pearson correlation coefficients between the measured and the decoded velocities are 0.37 for the horizontal dimension and 0.24 for the vertical dimension. The channels on motor, posterior parietal and occipital areas are most involved for the decoding of hand velocity. By comparing the decoding performance of the features from different frequency bands, we found that not only slow potentials in 0.1-4 Hz band but also oscillatory rhythms in 24-28 Hz band may carry the information of hand velocity.


CONCLUSIONS
These results provide another support to neural control of motor prosthesis based on EEG signals and proper decoding methods.
Initial therapy, persistence and regimen change in a cohort of newly treated type 2 diabetes patients.

AIMS
The aim was to describe the utilization of antidiabetic agents, in terms of persistence and regimen change, in the management of a cohort of newly treated type 2 diabetes patients and to investigate associated socio-demographic and treatment factors.


METHODS
A population-based retrospective cohort study was conducted using the national pharmacy claims database in Ireland. Subjects were analyzed for persistence and regimen change. Cox proportional hazards regression examined associations of socio-demographic and treatment factors on treatment patterns. Hazard ratios (HR) and 95% CIs are presented.


RESULTS
A total of 20947 subjects were identified in the study over a 2 year period. Most were initiated on metformin (76%) or sulphonylureas (22%) and 77% were persistent with therapy 12 months after initiation. The likelihood of non-persistence was significantly lower in the youngest (40-49 years) age groups (reference 60-69 years) (HR 1.62, 95% CI 1.42, 1.84) and those on sulphonylureas (HR 1.49, 95% CI 1.36, 1.64). The likelihood of receiving a regimen change was significantly lower in the older (80+ years) age groups (HR 0.63, 95% CI 0.56, 0.71), females (HR 0.91, 95% CI 0.86, 0.95), and those with pre-existing CVD (1 vs. 0 CVD medicines) (HR 0.82, 95% CI 0.74, 0.90), and higher in those on sulphonylureas (HR 1.83, 95% CI 1.73, 1.94).


CONCLUSIONS
Type of treatment, pre-existing CVD and demographic factors are shown to be associated with the observed treatment patterns. Guideline recommended agents were widely used on treatment initiation though a substantial minority were not initiated on the recommended first line agent. Use of guideline recommended agents was not as evident during treatment progression. Further optimization of initial and subsequent antidiabetic agent prescribing may be possible.
Efficient parallel kNN joins for large data in MapReduce

In data mining applications and spatial and multimedia databases, a useful tool is the kNN join, which is to produce the k nearest neighbors (NN), from a dataset S, of every point in a dataset R. Since it involves both the join and the NN search, performing kNN joins efficiently is a challenging task. Meanwhile, applications continue to witness a quick (exponential in some cases) increase in the amount of data to be processed. A popular model nowadays for large-scale data processing is the shared-nothing cluster on a number of commodity machines using MapReduce [6]. Hence, how to execute kNN joins efficiently on large data that are stored in a MapReduce cluster is an intriguing problem that meets many practical needs. This work proposes novel (exact and approximate) algorithms in MapReduce to perform efficient parallel kNN joins on large data. We demonstrate our ideas using Hadoop. Extensive experiments in large real and synthetic datasets, with tens or hundreds of millions of records in both R and S and up to 30 dimensions, have demonstrated the efficiency, effectiveness, and scalability of our methods.