LLukas22/scidocs huggingface dataset:
Patterns and utility of routine surveillance in high grade endometrial cancer.

OBJECTIVE
To evaluate surveillance methods and their utility in detecting recurrence of disease in a high grade endometrial cancer population.


METHODS
We performed a multi-institutional retrospective chart review of women diagnosed with high grade endometrial cancer between the years 2000 and 2011. Surveillance data was abstracted and analyzed. Surveillance method leading to detection of recurrence was identified and compared by stage of disease and site of recurrence.


RESULTS
Two hundred and fifty-four patients met the criteria for inclusion. Vaginal cytology was performed in the majority of early stage patients, but was utilized less in advanced stage patients. CA-125 and CT imaging were used more frequently in advanced stage patients compared to early stage. Thirty-six percent of patients experienced a recurrence and the majority of initial recurrences (76%) had a distant component. Modalities that detected cancer recurrences were: symptoms (56%), physical exam (18%), surveillance CT (15%), CA-125 (10%), and vaginal cytology (1%). All local recurrences were detected by symptoms or physical exam findings. While the majority of loco-regional and distant recurrences (68%) were detected by symptoms or physical exam, 28% were detected by surveillance CT scan or CA 125. One loco-regional recurrence was identified by vaginal cytology but no recurrences with a distant component detected by this modality.


CONCLUSIONS
Symptoms and physical examination identify the majority of high grade endometrial cancer recurrences, while vaginal cytology is the least likely surveillance modality to identify a recurrence. The role of CT and CA-125 surveillance outside of a clinical trial needs to be further reviewed.
CREDIT SUPPLY, FLIGHT TO QUALITY AND EVERGREENING: AN ANALYSIS OF BANK-FIRM RELATIONSHIPS AFTER LEHMAN

This paper analyzes the effects of the financial crisis on credit supply by using highly detailed data on bank-firm relationships in Italy after Lehman’s collapse. We control for firms’ unobservable characteristics, such as credit demand and borrowers’ risk, by exploiting multiple lending. We find evidence of a contraction of credit supply, associated to low bank capitalization and scarce liquidity. The ability of borrowers to compensate through substitution across banks appears to have been limited. We also document that larger lesscapitalized banks reallocated loans away from riskier firms, contributing to credit procyclicality. Such ‘flight to quality’ has not occurred for smaller less-capitalized banks. We argue that this may have reflected, among other things, evergreening practices. We provide corroborating evidence based on data on borrowers' productivity and interest rates at bankfirm level. JEL Classification: E44, E51, G21, G34, L16.
MOSFET modeling for RF IC design

High-frequency (HF) modeling of MOSFETs for radio-frequency (RF) integrated circuit (IC) design is discussed. Modeling of the intrinsic device and the extrinsic components is discussed by accounting for important physical effects at both dc and HF. The concepts of equivalent circuits representing both intrinsic and extrinsic components in a MOSFET are analyzed to obtain a physics-based RF model. The procedures of the HF model parameter extraction are also developed. A subcircuit RF model based on the discussed approaches can be developed with good model accuracy. Further, noise modeling is discussed by analyzing the theoretical and experimental results in HF noise modeling. Analytical calculation of the noise sources has been discussed to understand the noise characteristics, including induced gate noise. The distortion behavior of MOSFET and modeling are also discussed. The fact that a MOSFET has much higher "low-frequency limit" is useful for designers and modelers to validate the distortion of a MOSFET model for RF application. An RF model could well predict the distortion behavior of MOSFETs if it can accurately describe both dc and ac small-signal characteristics with proper parameter extraction.
Time-series prediction using a local linear wavelet neural network

A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weights between the hidden layer and output layer of conventional WNN are replaced by a local linear model. A hybrid training algorithm of particle swarm optimization (PSO) with diversity learning and gradient descent method is introduced for training the LLWNN. Simulation results for the prediction of time-series show the feasibility and effectiveness of the proposed method. r 2005 Elsevier B.V. All rights reserved.
An effective and fast iris recognition system based on a combined multiscale feature extraction technique

The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and the various sources of intra-class variations result in the difficulty of iris representation. Although, a number of iris recognition methods have been proposed, it has been found that several accurate iris recognition algorithms use multiscale techniques, which provide a well-suited representation for iris recognition. In this paper and after a thorough analysis and summarization, a multiscale edge detection approach has been employed as a pre-processing step to efficiently localize the iris followed by a new feature extraction technique which is based on a combination of some multiscale feature extraction techniques. This combination uses special Gabor filters and wavelet maxima components. Finally, a promising feature vector representation using moment invariants is proposed. This has resulted in a compact and efficient feature vector. In addition, a fast matching scheme based on exclusive OR operation to compute bits similarity is proposed where the result experimentation was carryout out using CASIA database. The experimental results have shown that the proposed system yields attractive performances and could be used for personal identification in an efficient and effective manner and comparable to the best iris recognition algorithm found in the current literature. 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
A novel kernelized fuzzy C-means algorithm with application in medical image segmentation

Image segmentation plays a crucial role in many medical imaging applications. In this paper, we present a novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data. The algorithm is realized by modifying the objective function in the conventional fuzzy C-means (FCM) algorithm using a kernel-induced distance metric and a spatial penalty on the membership functions. Firstly, the original Euclidean distance in the FCM is replaced by a kernel-induced distance, and thus the corresponding algorithm is derived and called as the kernelized fuzzy C-means (KFCM) algorithm, which is shown to be more robust than FCM. Then a spatial penalty is added to the objective function in KFCM to compensate for the intensity inhomogeneities of MR image and to allow the labeling of a pixel to be influenced by its neighbors in the image. The penalty term acts as a regularizer and has a coefficient ranging from zero to one. Experimental results on both synthetic and real MR images show that the proposed algorithms have better performance when noise and other artifacts are present than the standard algorithms.
Local Free-Style Perforator Flaps in Head and Neck Reconstruction: An Update and a Useful Classification.

BACKGROUND
Any standard skin flap of the body including a detectable or identified perforator at its axis can be safely designed and harvested in a free-style fashion.


METHODS
Fifty-six local free-style perforator flaps in the head and neck region, 33 primary and 23 recycle flaps, were performed in 53 patients. The authors introduced the term "recycle" to describe a perforator flap harvested within the borders of a previously transferred flap. A Doppler device was routinely used preoperatively for locating perforators in the area adjacent to a given defect. The final flap design and degree of mobilization were decided intraoperatively, depending on the location of the most suitable perforator and the ability to achieve primary closure of the donor site. Based on clinical experience, the authors suggest a useful classification of local free-style perforator flaps.


RESULTS
All primary and 20 of 23 recycle free-style perforator flaps survived completely, providing tension-free coverage and a pleasing final contour for patients. In the remaining three recycle cases, the skeletonization of the pedicle resulted in pedicle damage, because of surrounding postradiotherapy scarring and flap failure. All donor sites except one were closed primarily, and all of them healed without any complications.


CONCLUSIONS
The free-style concept has significantly increased the potential and versatility of the standard local and recycled head and neck flap alternatives for moderate to large defects, providing a more robust, custom-made, tissue-sparing, and cosmetically superior outcome in a one-stage procedure, with minimal donor-site morbidity.


CLINICAL QUESTION/LEVEL OF EVIDENCE
Therapeutic, V.
Helium-hyperoxia: a novel intervention to improve the benefits of pulmonary rehabilitation for patients with COPD.

BACKGROUND
Helium-hyperoxia (HH) reduces dyspnea and increases exercise tolerance in patients with COPD. We investigated whether breathing HH would allow patients to perform a greater intensity of exercise and improve the benefits of a pulmonary rehabilitation program.


METHODS
Thirty-eight nonhypoxemic patients with COPD (FEV(1)=47 +/- 17%(pred)) were randomized to rehabilitation breathing HH (60:40 He:O(2); n = 19) or air (n = 19). Patients cycled for 30 min, 3 days/week for 6 weeks breathing the assigned gas. Exercise intensity was prescribed from baseline, gas-specific, incremental exercise tests and was advanced as tolerated. The primary outcome was exercise tolerance assessed as a change in constant-load exercise time (CLT) following rehabilitation. Secondary outcomes were changes in exertional symptoms, health related quality of life (as assessed by the Short-form 36 and St George respiratory questionnaires), and peak oxygen consumption during an incremental exercise test.


RESULTS
The HH group had a greater change in CLT following rehabilitation compared to the air group (9.5 +/- 9.1 vs 4.3 +/- 6.3 min, p < 0.05). At an exercise isotime, dyspnea was significantly reduced in both groups, while leg discomfort only decreased in the HH group. The changes in exertional symptoms and peak oxygen consumption were not different between groups. Health-related quality of life significantly improved in both groups; however, the change in St. George respiratory questionnaire total score was greater with HH (-7.6 +/- 6.4 vs -3.6 +/- 5.6, p < 0.05). During rehabilitation, the HH group achieved a higher exercise intensity and training duration throughout the program (p < 0.05).


CONCLUSIONS
Breathing HH during pulmonary rehabilitation increases the intensity and duration of exercise training that can be performed and results in greater improvements in CLT for patients with COPD.
Rainbow Color Map (Still) Considered Harmful

In this article, we reiterate the characteristics that make the rainbow color map a poor choice, provide examples that clearly illustrate these deficiencies even on simple data sets, and recommend better color maps for several categories of display. The goal is to make the rainbow color map as rare in visualization as the goto statement is in programming - which complicates the task of analyzing and verifying program correctness
Bayesian Optimization with Exponential Convergence

This paper presents a Bayesian optimization method with exponential convergencewithout the need of auxiliary optimization and without the δ-cover sampling. Most Bayesian optimization methods require auxiliary optimization: an additional non-convex global optimization problem, which can be time-consuming and hard to implement in practice. Also, the existing Bayesian optimization method with exponential convergence [ 1] requires access to the δ-cover sampling, which was considered to be impractical [ 1, 2]. Our approach eliminates both requirements and achieves an exponential convergence rate.
Ease of use and usefulness as measures of student experience in a multi-platform e-textbook pilot

As the use of electronic textbooks continues to expand and we approach the point where dominance of digital over print is becoming increasingly inevitable (Reynolds, 2011), research is needed to understand how students accept and use the technology. This is especially critical as we begin to explore the electronic format for required textbooks in higher education. The current study evaluates university students’ experiences with electronic textbooks (e-textbooks) during a pilot project with two textbook publishers, Flat World Knowledge (FWK) and Nelson Education (Nelson). Using the Technology Acceptance Model (TAM) as a framework, we examine the perceived ease of use and perceived usefulness of the technology. While previous research suggests that students have a general preference for textbooks in print rather than electronic format (Allen, 2009; Parsons, 2014; Woody, et al., 2010), our study suggests that preference may not dictate the likelihood that students will seek out and use print options. Our study also indicated that student experience with the open/affordable textbook (FWK) was very comparable to that of the high cost commercial text (Nelson). Despite overall positive reviews for the etextbooks across both platforms, students experienced a drop in enthusiasm for e-textbooks from the beginning to the end of the pilot.
A Double‐Edged Sword: Transformational Leadership and Individual Creativity

Leadership research has focused on the positive effects of transformational and charismatic leadership but has neglected the negative side effects. Addressing this gap, we analysed followers’ dependency on the leader as a relevant negative side effect in the relationship between transformational leadership and followers’ creativity and developed an integrative framework on parallel positive and negative effects of transformational leadership. As expected, results from a study with 416 R&D employees showed that transformational leadership promotes followers’ creativity but at the same time increases followers’ dependency which in turn reduces their creativity. This negative indirect effect attenuates the positive influence of transformational leadership on followers’ creativity.
Platelet-rich plasma efficacy versus corticosteroid injection treatment for chronic severe plantar fasciitis.

BACKGROUND
Chronic plantar fasciitis is a common orthopedic condition that can prove difficult to successfully treat. In this study, autologous platelet-rich plasma (PRP), a concentrated bioactive blood component rich in cytokines and growth factors, was compared to traditional cortisone injection in the treatment of chronic cases of plantar fasciitis resistant to traditional nonoperative management.


METHODS
Forty patients (23 females and 17 males) with unilateral chronic plantar fasciitis that did not respond to a minimum of 4 months of standardized traditional nonoperative treatment modalities were prospectively randomized and treated with either a single ultrasound guided injection of 3 cc PRP or 40 mg DepoMedrol cortisone. American Orthopedic Foot and Ankle Society (AOFAS) hindfoot scoring was completed for all patients immediately prior to PRP or cortisone injection (pretreatment = time 0) and at 3, 6, 12, and 24 months following injection treatment. Baseline pretreatment radiographs and MRI studies were obtained in all cases to confirm the diagnosis of plantar fasciitis.


RESULTS
The cortisone group had a pretreatment average AOFAS score of 52, which initially improved to 81 at 3 months posttreatment but decreased to 74 at 6 months, then dropped to near baseline levels of 58 at 12 months, and continued to decline to a final score of 56 at 24 months. In contrast, the PRP group started with an average pretreatment AOFAS score of 37, which increased to 95 at 3 months, remained elevated at 94 at 6 and 12 months, and had a final score of 92 at 24 months.


CONCLUSIONS
PRP was more effective and durable than cortisone injection for the treatment of chronic recalcitrant cases of plantar fasciitis.


LEVEL OF EVIDENCE
Level I, prospective randomized comparative series.
Terbinafine increases the plasma concentration of paroxetine after a single oral administration of paroxetine in healthy subjects

Paroxetine is believed to be a substrate of CYP2D6. However, no information was available indicating drug interaction between paroxetine and inhibitors of CYP2D6. The aim of this study was to examine the effects of terbinafine, a potent inhibitor of CYP2D6, on pharmacokinetics of paroxetine. Two 6-day courses of either a daily 150-mg of terbinafine or a placebo, with at least a 4-week washout period, were conducted. Twelve volunteers took a single oral 20-mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 h after dosing. Compared with the placebo, terbinafine treatment significantly increased the peak plasma concentration (Cmax) of paroxetine, by 1.9-fold (6.4 ± 2.4 versus 12.1 ± 2.9 ng/ml, p < 0.001), and the area under the plasma concentration-time curve from zero to 48 h [AUC (0–48)] of paroxetine by 2.5-fold (127 ± 67 vs 318 ± 102 ng/ml, p < 0.001). Elimination half-life differed significantly (15.3 ± 2.4 vs 22.7 ± 8.8 h, p < 0.05), although the magnitude of alteration (1.4-fold) was smaller than Cmax or AUC. The present study demonstrated that the metabolism of paroxetine after a single oral dose was inhibited by terbinafine, suggesting that inhibition of CYP2D6 activity may lead to a change in the pharmacokinetics of paroxetine. However, further study is required to confirm this phenomenon at steady state.
Coronary restenosis after sirolimus-eluting stent implantation: morphological description and mechanistic analysis from a consecutive series of cases.

BACKGROUND
We describe the clinical and morphological patterns of restenosis after sirolimus-eluting stent (SES) implantation.


METHODS AND RESULTS
From 121 patients with coronary angiography obtained >30 days after SES implantation, restenosis (diameter stenosis >50%) was identified in 19 patients and 20 lesions (located at the proximal 5-mm segment in 30% or within the stent in 70%). Residual dissection after the procedure or balloon trauma outside the stent was identified in 83% of the proximal edge lesions. Lesions within the stent were focal, and stent discontinuity was identified in some lesions evaluated by intravascular ultrasound.


CONCLUSIONS
Sirolimus-eluting stent edge restenosis is frequently associated with local trauma outside the stent. In-stent restenosis occurs as a localized lesion, commonly associated with a discontinuity in stent coverage. Local conditions instead of intrinsic drug-resistance to sirolimus are likely to play a major role in post-SES restenosis.
Performance analysis of various machine learning-based approaches for detection and classification of lung cancer in humans

Lung cancer is one of the most common causes of death among all cancer-related diseases (Cancer Research UK in Cancer mortality for common cancers. http://www.cancerresearchuk.org/health-professional/cancer-statistics/mortality/common-cancers-compared, 2017). It is primarily diagnosed by performing a scan analysis of the patient’s lung. This scan analysis could be of X-ray, CT scan, or MRI. Automated classification of lung cancer is one of the difficult tasks, attributing to the varying mechanisms used for imaging patient’s lungs. Image processing and machine learning approaches have shown a great potential for detection and classification of lung cancer. In this paper, we have demonstrated effective approach for detection and classification of lung cancer-related CT scan images into benign and malignant category. Proposed approach firstly processes these images using image processing techniques, and then further supervised learning algorithms are used for their classification. Here, we have extracted texture features along with statistical features and supplied various extracted features to classifiers. We have used seven different classifiers known as k-nearest neighbors classifier, support vector machine classifier, decision tree classifier, multinomial naive Bayes classifier, stochastic gradient descent classifier, random forest classifier, and multi-layer perceptron (MLP) classifier. We have used dataset of 15750 clinical images consisting of both 6910 benign and 8840 malignant lung cancer related images to train and test these classifiers. In the obtained results, it is found that accuracy of MLP classifier is higher with value of 88.55% in comparison with the other classifiers.
We Are Family: Joint Pose Estimation of Multiple Persons

We present a novel multi-person pose estimation framework, which extends pictorial structures (PS) to explicitly model interactions between people and to estimate their poses jointly. Interactions are modeled as occlusions between people. First, we propose an occlusion probability predictor, based on the location of persons automatically detected in the image, and incorporate the predictions as occlusion priors into our multi-person PS model. Moreover, our model includes an inter-people exclusion penalty, preventing body parts from different people from occupying the same image region. Thanks to these elements, our model has a global view of the scene, resulting in better pose estimates in group photos, where several persons stand nearby and occlude each other. In a comprehensive evaluation on a new, challenging group photo datasets we demonstrate the benefits of our multi-person model over a state-of-the-art single-person pose estimator which treats each person independently.
Designing for deeper learning in a blended computer science course for middle school students

ion, and testing. Figure 2 (which also shows this comparison data with college students) reveals a significant shift from naïve “computercentric” notions of computer scientists (“make/fix/study computer”) to a more sophisticated understanding of CS as a problem-solving discipline that uses the computer as a tool to solve real-world problems in many diverse fields.