nils-herrmann/clean_scirepeval huggingface dataset:
Mathematical Formula Identification in PDF Documents

Recognizing mathematical expressions in PDF documents is a new and important field in document analysis. It is quite different from extracting mathematical expressions in image-based documents. In this paper, we propose a novel method by combining rule-based and learning-based methods to detect both isolated and embedded mathematical expressions in PDF documents. Moreover, various features of formulas, including geometric layout, character and context content, are used to adapt to a wide range of formula types. Experimental results show satisfactory performance of the proposed method. Furthermore, the method has been successfully incorporated into a commercial software package for large-scale Chinese e-Book production.
Fuzzy rough classifiers for class imbalanced multi-instance data

In multi-instance learning, each learning object consists of many descriptive instances. In the corresponding classification problems, each training object is labeled, but its constituent instances are not. The classification objective is to predict the class label of unseen objects. As in traditional single-instance classification, when the class sizes of multi-instance data are imbalanced, classification is degraded. Many multi-instance classifiers have been proposed, but few take into account the possibility of class imbalance, which causes them to fail in this situation. In this paper, we propose a new type of classifier that embodies a solution to the multi-instance class imbalance problem. Our proposal relies on the use of fuzzy rough set theory. We present two families of classifiers respectively based on information extracted at bag-level and at instance-level. We experimentally show that our algorithms outperform state-of-theart solutions to multi-instance imbalanced data classification, evaluated by the popular metrics AUC and geometric mean. & 2015
Phase III safety evaluation of cyclosporine 0.1% ophthalmic emulsion administered twice daily to dry eye disease patients for up to 3 years.

To evaluate cyclosporine 0.1% ophthalmic emulsion over a 1- to 3-year period in moderate to severe dry eye disease patients.



Nonrandomized, multicenter, open-label clinical trial extending 2 ophthalmic cyclosporine phase III clinical trials.



Four hundred twelve patients previously dosed for 6 to 12 months with cyclosporine 0.05% or 0.1% in prior phase III trials.



Patients instilled ophthalmic cyclosporine 0.1% twice daily into both eyes for up to 3 consecutive 12-month extension periods.



Corneal staining, Schirmer tests, and symptom severity assessments were conducted during the first 12-month extension, with a patient survey during the second 12-month extension. Biomicroscopy and visual acuity (VA) examinations, intraocular pressure (IOP) measurements, and adverse effects queries occurred at 6-month intervals.



Mean duration of treatment was 19.8 months. Improvements in objective and subjective measures of dry eye disease were modest, probably because of prior treatment with cyclosporine. Most survey respondents said their symptoms began to resolve in the first 3 months of cyclosporine treatment during the previous phase III clinical trials. At study exit, VA decreased in 12.6% (93/738) and increased in 5.4% (40/738) of eyes by > or =2 lines; severity of biomicroscopy findings increased in 3.4% (chemosis; 26/760), 7.2% (conjunctival hyperemia; 55/760), or 8.5% (tear film debris; 64/756) of eyes; and mean IOP increased 0.18 mmHg relative to baseline. The most common treatment-related adverse events were burning (10.9% of patients [45/412]), stinging (3.9% , and conjunctival hyperemia (3.4% [14/412]). No serious treatment-related adverse events occurred. Most patients (95.2% [140/147]) said they would continue cyclosporine therapy; 97.9% (143/146) would recommend it to other dry eye patients.



Therapy of chronic dry eye disease with cyclosporine 0.1% ophthalmic emulsion for 1 to 3 years was safe, well tolerated, and not associated with systemic side effects. The results supplement the safety record of the commercially available cyclosporine 0.05% ophthalmic emulsion.
Effect of different ferrule designs on the fracture resistance and
failure pattern of endodontically treated teeth restored with fiber posts and
allceramic crowns

This study investigated the effect of different ferrule heights on endodontically treated premolars.



Fifty sound mandibular first premolars were endodontically treated and then restored with 7-mm fiber post (FRC Postec Plus #1 Ivoclar-Vivadent) luted with self-polymerized resin cement (Multilink, Ivoclar Vivadent) while the coronal section was restored with hybrid composite core build-up material (Tetric Ceram, Ivoclar-Vivadent), which received all-ceramic crown. Different ferrule heights were investigated: 1-mm circumferential ferrule without post and core (group 1 used as control), a circumferential 1-mm ferrule (group 2), non-uniform ferrule 2-mm buccally and 1-mm lingually (group 3), non-uniform ferrule 3-mm buccally and 2-mm lingually (group 4), and finally no ferrule preparation (group 5). The fracture load and failure pattern of the tested groups were investigated by applying axial load to the ceramic crowns (n=10). Data were analyzed statistically by one-way ANOVA and Tukey's post-hoc test was used for pair-wise comparisons (α=0.05).



There were no significant differences among the failure load of all tested groups (P<0.780). The control group had the lowest fracture resistance (891.43 ± 202.22 N) and the highest catastrophic failure rate (P<0.05). Compared to the control group, the use of fiber post reduced the percentage of catastrophic failure while increasing the ferrule height did not influence the fracture resistance of the restored specimens.



Within the limitations of this study, increasing the ferrule length did not influence the fracture resistance of endodontically treated teeth restored with glass ceramic crowns. Insertion of a fiber post could reduce the percentage of catastrophic failure of these restorations under function.
OUTS OF HOMESCHOOLING The Determinants of Parental Motivations and Student Achievement

This research investigates two major aspects of homeschooling. Factors determining parental motivations to homeschool and the determinants of the student achievement of home-educated children are identified. Original survey data from an organized group of homeschoolers is analyzed. Regression models are employed to predict parents’ motivations and their students’ standardized test achievement. Four sets of homeschooling motivations are identified. Academic and pedagogical concerns are most important, and it appears that the religious base of the movement is subsiding. Several major demographic variables have no impact upon parental motivations, indicating that this is a diverse group. Parents’ educational attainment and political identification are consistent predictors of their students’ achievement. Race and class—the two major divides in public education—are not significant determinants of standardized test achievement, suggesting that homeschooling is efficacious. It is concluded that homeschoolers are a heterogeneous population with varying and overlapping motivations.
The ParallelEye-CS Dataset: Constructing Artificial Scenes for Evaluating the Visual Intelligence of Intelligent Vehicles

Offline training and testing are playing an essential role in design and evaluation of intelligent vehicle vision algorithms. Nevertheless, long-term inconvenience concerning traditional image datasets is that manually collecting and annotating datasets from real scenes lack testing tasks and diverse environmental conditions. For that virtual datasets can make up for these regrets. In this paper, we propose to construct artificial scenes for evaluating the visual intelligence of intelligent vehicles and generate a new virtual dataset called “ParallelEye-CS”. First of all, the actual track map data is used to build 3D scene model of Chinese Flagship Intelligent Vehicle Proving Center Area, Changshu. Then, the computer graphics and virtual reality technologies are utilized to simulate the virtual testing tasks according to the Chinese Intelligent Vehicles Future Challenge (IVFC) tasks. Furthermore, the Unity3D platform is used to generate accurate ground-truth labels and change environmental conditions. As a result, we present a viable implementation method for constructing artificial scenes for traffic vision research. The experimental results show that our method is able to generate photorealistic virtual datasets with diverse testing tasks.
#phramacovigilance - Exploring Deep Learning Techniques for Identifying Mentions of Medication Intake from Twitter

Mining social media messages for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions of drug usage and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific cohorts, identifying posts mentioning intake of medicine by the user is necessary. Towards this objective, we train different deep neural network classification models on a publicly available annotated dataset and study their performances on identifying mentions of personal intake of medicine in tweets. We also design and train a new architecture of a stacked ensemble of shallow convolutional neural network (CNN) ensembles. We use random search for tuning the hyperparameters of the models and share the details of the values taken by the hyperparameters for the best learnt model in different deep neural network architectures. Our system produces state-of-the-art results, with a microaveraged F-score of 0.693.
The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation

The Leiden Ranking 2011/2012 is a ranking of universities based on bibliometric indicators of publication output, citation impact, and scientific collaboration. The ranking includes 500 major universities from 41 different countries. This paper provides an extensive discussion of the Leiden Ranking 2011/2012. The ranking is compared with other global university rankings, in particular the Academic Ranking of World Universities (commonly known as the Shanghai Ranking) and the Times Higher Education World University Rankings. The comparison focuses on the methodological choices underlying the different rankings. Also, a detailed description is offered of the data collection methodology of the Leiden Ranking 2011/ 2012 and of the indicators used in the ranking. Various innovations in the Leiden Ranking 2011/2012 are presented. These innovations include (1) an indicator based on counting a university’s highly cited publications, (2) indicators based on fractional rather than full counting of collaborative publications, (3) the possibility of excluding non-English language publications, and (4) the use of stability intervals. Finally, some comments are made on the interpretation of the ranking and a number of limitations of the ranking are pointed out.
Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.
Terrestrial and aquatic invertebrates as bioindicators for environmental monitoring, with particular reference to mountain ecosystems.

The use of terrestrial and aquatic invertebrates as a management tool for monitoring change in ecosystems is reviewed and critically evaluated. Their suitability and value for assessing a range of environmental problems from pollution impacts, through habitat evaluation for conservation to the long-term degradation and recovery of ecosystems, is critically discussed. Guidelines are provided for the choice of appropriate bioindicators. Examples of the use of a broad spectrum of invertebrates to assess a variety of environmental problems are summarized. The particular potential of invertebrates for monitoring montane ecosystems is highlighted.
Prediction of wind speed with non-linear autoregressive (NAR) neural networks

In this study, the wind speed prediction model is created that gives a minimum error for different hidden layer neuron numbers and delay step numbers. Using the one-minute time series, the prediction of the next wind speed is performed with the NAR neural network model. The predicted values of wind speed obtained are compared with predicted values of wind speed obtained with filter methods. For different window functions and lengths, wind speed prediction is made using filters with different weight coefficients. For the number of hidden layer neurons is 14 and the number of delay steps is 10, MAE, MSE and RMSE values are calculated as 0.0315, 0.0019, 0.0445, respectively, with NAR neural network. It is seen that the proposed method for the wind speed dataset has a higher prediction performance than thefilter methods.
Nano-Function materials for TSV technologies

This paper discloses that Nano-Function materials make TSV structure by printing technologies without CVD/PVD/Plating. For isolation layer forming, two types of TSV pattern had been examined. For metal fill, we adopted conductive paste or alloy plate contains nanomized alloys (Cu, Sn and additives) to fill via by less than 250°C condition. Re-melting temperature of the alloy is more than 300°C.
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons

We study the recognition of surfaces made from different materials such as concrete, rug, marble, or leather on the basis of their textural appearance. Such natural textures arise from spatial variation of two surface attributes: (1) reflectance and (2) surface normal. In this paper, we provide a unified model to address both these aspects of natural texture. The main idea is to construct a vocabulary of prototype tiny surface patches with associated local geometric and photometric properties. We call these 3D textons. Examples might be ridges, grooves, spots or stripes or combinations thereof. Associated with each texton is an appearance vector, which characterizes the local irradiance distribution, represented as a set of linear Gaussian derivative filter outputs, under different lighting and viewing conditions. Given a large collection of images of different materials, a clustering approach is used to acquire a small (on the order of 100) 3D texton vocabulary. Given a few (1 to 4) images of any material, it can be characterized using these textons. We demonstrate the application of this representation for recognition of the material viewed under novel lighting and viewing conditions. We also illustrate how the 3D texton model can be used to predict the appearance of materials under novel conditions.
FAST DUAL MINIMIZATION OF THE VECTORIAL TOTAL VARIATION NORM AND APPLICATIONS TO COLOR IMAGE PROCESSING

We propose a regularization algorithm for color/vectorial images which is fast, easy to code and mathematically well-posed. More precisely, the regularization model is based on the dual formulation of the vectorial Total Variation (VTV) norm and it may be regarded as the vectorial extension of the dual approach defined by Chambolle in [13] for gray-scale/scalar images. The proposed model offers several advantages. First, it minimizes the exact VTV norm whereas standard approaches use a regularized norm. Then, the numerical scheme of minimization is straightforward to implement and finally, the number of iterations to reach the solution is low, which gives a fast regularization algorithm. Finally, and maybe more importantly, the proposed VTV minimization scheme can be easily extended to many standard applications. We apply this L vectorial regularization algorithm to the following problems: color inverse scale space, color denoising with the chromaticity-brightness color representation, color image inpainting, color wavelet shrinkage, color image decomposition, color image deblurring, and color denoising on manifolds. Generally speaking, this VTV minimization scheme can be used in problems that required vector field (color, other feature vector) regularization while preserving discontinuities.
In-hospital cardiac arrest: incidence, prognosis and possible measures to improve survival

Medical literature on in-hospital cardiac arrest (IHCA) was reviewed to summarise: (a) the incidence of and survival after IHCA, (b) major prognostic factors, (c) possible interventions to improve survival. The incidence of IHCA is rarely reported in the literature. Values range between 1 and 5 events per 1,000 hospital admissions, or 0.175 events/bed annually. Reported survival to hospital discharge varies from 0% to 42%, the most common range being between 15% and 20%. Pre-arrest prognostic factors: the prognostic value of age is controversial. Among comorbidities, sepsis, cancer, renal failure and homebound lifestyle are significantly associated with poor survival. However, pre-arrest morbidity scores have not yet been prospectively validated as instruments to predict failure to survive after IHCA. Intra-arrest factors: ventricular fibrillation/ventricular tachycardia (VF/VT) as the first recorded rhythm and a shorter interval between IHCA and cardiopulmonary resuscitation or defibrillation are associated with higher survival. However, VF/VT is present in only 25–35% of IHCAs. Short-term survival is also higher in patients resuscitated with chest compression rates above 80/min. Interventions likely to improve survival include: early recognition and stabilisation of patients at risk of IHCA to enable prevention, faster and better in-hospital resuscitation and early defibrillation. Mild therapeutic hypothermia is effective as post-arrest treatment of out-of-hospital cardiac arrest due to VF/VT, but its benefit after IHCA and after cardiac arrest with non-VF/VT rhythms has not been clearly demonstrated.
Color-based segmentation and feature detection for ball and goal post on mobile soccer robot game field

This study presents the real time implementation of object detection and tracking algorithm on mobile soccer robot. Object detection is considered as one of the most important task because ball and goal post are the main component in soccer. The system uses the combination of color-based segmentation and feature detection to detect the color and also the shape feature of the object used in the soccer robot game. The color segmentation uses thresholding method in Hue, Saturation, and Value (HSV) color space to differentiate the ball and goal post color from other objects in the field. Then, morphological operation is applied to the thersholded image to minimize the error. After that, Hough line transform is applied to detect the feature of the goal post. Then, ellipse detection is also applied to find the ball feature. This step is used so the desired object is correctly detected, not other object that have the same color. The final step is to calculate the image moments to determine the centroid of the objects and tracking it. Object's color, feature, and coordinate are obtained from this purposed method. In the implementation, the robot has successfully detect ball, goal post, and its position in a real time manner.
Optimizing multiple UAV cooperative ground attack missions

This paper presents an optimization based approach for cooperative multiple UAV attack missions. The objective is to determine the minimum resources required to coordinately attack a target at a given set of directions. We restrict the paths of the munitions to direct Dubins paths to satisfy field of view constraints and to avoid certain undesirable paths. The proposed algorithm derives the feasible positions and headings for each attack angle, and determines intersection regions corresponding to any two attack angles. We pose a set cover problem, the solution of which gives the minimum number of UAVs required to accomplish the mission.
Head and neck PET/CT: therapy response interpretation criteria (Hopkins Criteria)-interreader reliability, accuracy, and survival outcomes.

There has been no established qualitative system of interpretation for therapy response assessment using PET/CT for head and neck cancers. The objective of this study was to validate the Hopkins interpretation system to assess therapy response and survival outcome in head and neck squamous cell cancer patients (HNSCC).



The study included 214 biopsy-proven HNSCC patients who underwent a posttherapy PET/CT study, between 5 and 24 wk after completion of treatment. The median follow-up was 27 mo. PET/CT studies were interpreted by 3 nuclear medicine physicians, independently. The studies were scored using a qualitative 5-point scale, for the primary tumor, for the right and left neck, and for overall assessment. Scores 1, 2, and 3 were considered negative for tumors, and scores 4 and 5 were considered positive for tumors. The Cohen κ coefficient (κ) was calculated to measure interreader agreement. Overall survival (OS) and progression-free survival (PFS) were analyzed by Kaplan-Meier plots with a Mantel-Cox log-rank test and Gehan Breslow Wilcoxon test for comparisons.



Of the 214 patients, 175 were men and 39 were women. There was 85.98%, 95.33%, 93.46%, and 87.38% agreement between the readers for overall, left neck, right neck, and primary tumor site response scores, respectively. The corresponding κ coefficients for interreader agreement between readers were, 0.69-0.79, 0.68-0.83, 0.69-0.87, and 0.79-0.86 for overall, left neck, right neck, and primary tumor site response, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the therapy assessment were 68.1%, 92.2%, 71.1%, 91.1%, and 86.9%, respectively. Cox multivariate regression analysis showed human papillomavirus (HPV) status and PET/CT interpretation were the only factors associated with PFS and OS. Among the HPV-positive patients (n = 123), there was a significant difference in PFS (hazard ratio [HR], 0.14; 95% confidence interval, 0.03-0.57; P = 0.0063) and OS (HR, 0.01; 95% confidence interval, 0.00-0.13; P = 0.0006) between the patients who had a score negative for residual tumor versus positive for residual tumor. A similar significant difference was observed in PFS and OS for all patients. There was also a significant difference in the PFS of patients with PET-avid residual disease in one site versus multiple sites in the neck (HR, 0.23; log-rank P = 0.004).



The Hopkins 5-point qualitative therapy response interpretation criteria for head and neck PET/CT has substantial interreader agreement and excellent negative predictive value and predicts OS and PFS in patients with HPV-positive HNSCC.
Microstrip bandstop filter using spurline and defected ground structures(DGS)

Microstrip filters are widely used in microwave circuit, This paper briefly describes the design principle of microstrip bandstop filter (BSF). A compact wide band high rejection BSF is presented. This filter consists of two parts: defected ground structures filter (DGS) and spurline filter. Due to the inherently compact characteristics of the spurline and DGS, the proposed filter shows a better rejection performance than open stub BSF in the same circuit size. The results of simulation and optimization given by HFSS12 prove the correctness of the design.