nils-herrmann/clean_scirepeval huggingface dataset:
Which Are the Best Features for Automatic Verb Classification

Much research in lexical acquisition has concentrated on the hypothesis that the behavior of a verb, particularly with respect to the expression of arguments and the assignment of semantic roles is to a large extent driven by deep semantic regularities. We focus on the empirical basis for a central part of this research, Levin (1993), (which we abbreviate as Levin from now on). The core of Levin’s work is a set of claims about the connections between meaning regularities and syntactic alternation patterns. These connections form the basis for a detailed classification of a large number of English verbs. In computational linguistics, Levin’s classification has been shown to reduce redundancy in verb descriptions and to enable potentially useful generalizations across similar verbs. This has motivated a wealth of work on automatic acquisition of verb lexicons from labeled and unlabeled corpora. This is a clear demonstration of the transfer of useful ideas from theoretical linguistics to computational linguistics. Until now, there has been little transfer in the opposite direction. In the present case study, we investigate the relation between Levin’s approach, the theoretical motivations for her work and the corpus data. Concretely, we wish to discover maximally informative and effective features for automatic verb classification. We develop and evaluate a wide range of different feature sets, evaluating each against Levin-style verb classification. We perform automatic classification experiments using Bayesian Multinomial Regression (a state-ofthe-art log-linear modeling framework which we found to outperform SVMs for this task) with the proposed feature spaces. Our experiments suggest that subcategorization frames, despite their theoretical credibility, are not the most effective basis for automatic classifiers. Rather, we find that the best-performing classifier use a combination of dependency information and simple co-occurrence features. This observation is consistent with the hypothesis that robust and practically useful extensions of Levin’s classes will be based not only on alternation patterns but also on semantic similarities.
Bevacizumab in combination with oxaliplatin-based chemotherapy as first-line therapy in metastatic colorectal cancer: a randomized phase III study.

To evaluate the efficacy and safety of bevacizumab when added to first-line oxaliplatin-based chemotherapy (either capecitabine plus oxaliplatin [XELOX] or fluorouracil/folinic acid plus oxaliplatin [FOLFOX-4]) in patients with metastatic colorectal cancer (MCRC).



Patients with MCRC were randomly assigned, in a 2 x 2 factorial design, to XELOX versus FOLFOX-4, and then to bevacizumab versus placebo. The primary end point was progression-free survival (PFS).



A total of 1,401 patients were randomly assigned in this 2 x 2 analysis. Median progression-free survival (PFS) was 9.4 months in the bevacizumab group and 8.0 months in the placebo group (hazard ratio [HR], 0.83; 97.5% CI, 0.72 to 0.95; P = .0023). Median overall survival was 21.3 months in the bevacizumab group and 19.9 months in the placebo group (HR, 0.89; 97.5% CI, 0.76 to 1.03; P = .077). Response rates were similar in both arms. Analysis of treatment withdrawals showed that, despite protocol allowance of treatment continuation until disease progression, only 29% and 47% of bevacizumab and placebo recipients, respectively, were treated until progression. The toxicity profile of bevacizumab was consistent with that documented in previous trials.



The addition of bevacizumab to oxaliplatin-based chemotherapy significantly improved PFS in this first-line trial in patients with MCRC. Overall survival differences did not reach statistical significance, and response rate was not improved by the addition of bevacizumab. Treatment continuation until disease progression may be necessary in order to optimize the contribution of bevacizumab to therapy.
Role of Nasal Skin Massage in Optimizing Secondary Rhinoplasty Results


Rhinoplasty is the most frequent aesthetic surgery in Iran.1 Recent reports signifies its prevalence rate as high as 180 cases of rhinoplasty per 100,000 population which is the highest in the world.1,2 In addition to plastic surgeons, there are many other surgeons performing rhinoplasty surgery without academic aesthetic surgery training. With increasing the rate of rhinoplasty by the academically untrained surgeons, chance of secondary deformities has been increased dramatically. A pervasive trend among Iranian patients and surgeons is to miniaturize the nose as much as possible, which usually results in a pathologically small nose. After ceasing the edema, these patients develop a small malformed nose with evident breathing problems.3-5 So they start complaining about the shape, size and function of the nose. They wish to have an a esthetically pleasant nose with proportional size. Severe skin shortage makes secondary surgeries unsuccessful in most secondary rhinoplasty cases, especially in patients with foreshortened nose. It makes soft tissue dissection, skeletonization and graft implantation extremely laborious and sub-standardizes function as well as aesthetic results. Surgical attempt for inserting different types and shaped grafts especially large and extended grafts in these cases, will go to fail due to inability of tensionless skin closure.6-13 Since 15 years ago, we have implemented skin massage as a new approach in these patients. They have been trained for nasal skin massage technique with manipulating and putting traction on the nasal skin in forward and downward directions. These manipulations should be performed at all directions, mostly in forward and downward directions and all parts of the nose . Massage performed 6-8 times a day intermittently for 2-5 minutes (per each session) in 3 consecutive months. It has been recommended to do it bimanually or with help of two opposing fingers of dominant hand with application of some mineral or organic oil in order to lubricate and soften the skin. Patients will experience remarkable skin softening after several weeks of massage therapy. A follow-up visit after 12 weeks of massage therapy is recommended, in which the surgeon determines the proper plan based on the amount of skin laxity . In case of acceptable result, surgery could be performed, otherwise the patient is asked for applying another 3 months period of massage therapy. This approach has several advantages: First of all, skin would Editorial
Epidemic malaria and warmer temperatures in recent decades in an East African highland

Climate change impacts on malaria are typically assessed with scenarios for the long-term future. Here we focus instead on the recent past (1970-2003) to address whether warmer temperatures have already increased the incidence of malaria in a highland region of East Africa. Our analyses rely on a new coupled mosquito-human model of malaria, which we use to compare projected disease levels with and without the observed temperature trend. Predicted malaria cases exhibit a highly nonlinear response to warming, with a significant increase from the 1970s to the 1990s, although typical epidemic sizes are below those observed. These findings suggest that climate change has already played an important role in the exacerbation of malaria in this region. As the observed changes in malaria are even larger than those predicted by our model, other factors previously suggested to explain all of the increase in malaria may be enhancing the impact of climate change.
A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model

In recent years, data mining researchers have developed efficient association rule algorithms for retail market basket analysis. Still, retailers often complain about how to adopt association rules to optimize concrete retail marketing-mix decisions. It is in this context that, in a previous paper, the authors have introduced a product selection model called PROFSET. This model selects the most interesting products from a product assortment based on their cross-selling potential given some retailer defined constraints. However this model suffered from an important deficiency: it could not deal effectively with supermarket data, and no provisions were taken to include retail category management principles. Therefore, in this paper, the authors present an important generalization of the existing model in order to make it suitable for supermarket data as well, and to enable retailers to add category restrictions to the model. Experiments on real world data obtained from a Belgian supermarket chain produce very promising results and demonstrate the effectiveness of the generalized PROFSET model.
Counter-fitting Word Vectors to Linguistic Constraints

In this work, we present a novel counter-fitting method which injects antonymy and synonymy constraints into vector space representations in order to improve the vectors’ capability for judging semantic similarity. Applying this method to publicly available pre-trained word vectors leads to a new state of the art performance on the SimLex-999 dataset. We also show how the method can be used to tailor the word vector space for the downstream task of dialogue state tracking, resulting in robust improvements across different dialogue domains.
AMAI : Adaptive Music for Affect Improvement

This paper introduces Adaptive Music for Affect Improvement (AMAI), a music generation and playback system whose goal is to steer the listener towards a state of more positive affect. AMAI utilizes techniques from game music in order to adjust elements of the music being heard; such adjustments are made adaptively in response to the valence levels of the listener as measured via facial expression and emotion detection. A user study involving AMAI was conducted, with N=19 participants across three groups, one for each strategy of Discharge, Diversion, and Discharge→ Diversion. Significant differences in valence levels between music-related stages of the study were found between the three groups, with Discharge → Diversion exhibiting the greatest increase in valence, followed by Diversion and finally Discharge. Significant differences in positive affect between groups were also found in one before-music and after-music pair of self-reported affect surveys, with Discharge→ Diversion exhibiting the greatest decrease in positive affect, followed by Diversion and finally Discharge; the resulting differences in facial expression valence and self-reported affect offer contrasting con-
Rethinking Reprojection: Closing the Loop for Pose-Aware Shape Reconstruction from a Single Image

An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application of canonical deep learning methods to regress from the image directly to the 3D shape and pose labels. These approaches, however, are problematic from two perspectives. First, they are minimizing the error between 3D shapes and pose labels - with little thought about the nature of this “label error” when reprojecting the shape back onto the image. Second, they rely on the onerous and ill-posed task of hand labeling natural images with respect to 3D shape and pose. In this paper we define the new task of pose-aware shape reconstruction from a single image, and we advocate that cheaper 2D annotations of objects silhouettes in natural images can be utilized. We design architectures of pose-aware shape reconstruction which reproject the predicted shape back on to the image using the predicted pose. Our evaluation on several object categories demonstrates the superiority of our method for predicting pose-aware 3D shapes from natural images.
Activating mutations of NOTCH1 in human T cell acute lymphoblastic leukemia.

Very rare cases of human T cell acute lymphoblastic leukemia (T-ALL) harbor chromosomal translocations that involve NOTCH1, a gene encoding a transmembrane receptor that regulates normal T cell development. Here, we report that more than 50% of human T-ALLs, including tumors from all major molecular oncogenic subtypes, have activating mutations that involve the extracellular heterodimerization domain and/or the C-terminal PEST domain of NOTCH1. These findings greatly expand the role of activated NOTCH1 in the molecular pathogenesis of human T-ALL and provide a strong rationale for targeted therapies that interfere with NOTCH signaling.
Structure of bone morphogenetic protein 9 procomplex.

Bone morphogenetic proteins (BMPs) belong to the TGF-β family, whose 33 members regulate multiple aspects of morphogenesis. TGF-β family members are secreted as procomplexes containing a small growth factor dimer associated with two larger prodomains. As isolated procomplexes, some members are latent, whereas most are active; what determines these differences is unknown. Here, studies on pro-BMP structures and binding to receptors lead to insights into mechanisms that regulate latency in the TGF-β family and into the functions of their highly divergent prodomains. The observed open-armed, nonlatent conformation of pro-BMP9 and pro-BMP7 contrasts with the cross-armed, latent conformation of pro-TGF-β1. Despite markedly different arm orientations in pro-BMP and pro-TGF-β, the arm domain of the prodomain can similarly associate with the growth factor, whereas prodomain elements N- and C-terminal to the arm associate differently with the growth factor and may compete with one another to regulate latency and stepwise displacement by type I and II receptors. Sequence conservation suggests that pro-BMP9 can adopt both cross-armed and open-armed conformations. We propose that interactors in the matrix stabilize a cross-armed pro-BMP conformation and regulate transition between cross-armed, latent and open-armed, nonlatent pro-BMP conformations.
Neural Information Processing

In this paper, an improved ant colony algorithm based on cloud model is proposed to study the multi-robot task allocation problem. The improvement of the proposed algorithm mainly includes the construction of adaptive control mechanism, pheromone updating mechanism and task point selection mechanism. Some important optimization operators are designed such as evaluation of pheromone distribution, determination of suboptimal solution and selection of task point. Simulation results show that the proposed algorithm can obtain high-quality solution and fast convergence, the effect is significant.
Probabilistic Model Checking for Complex Cognitive Tasks - A case study in human-robot interaction

This paper proposes to use probabilistic model checking to synthesize optimal robot policies in multi-tasking autonomous systems that are subject to human-robot interaction. Given the convincing empirical evidence that human behavior can be related to reinforcement models, we take as input a well-studied Q-table model of the human behavior for flexible scenarios. We first describe an automated procedure to distill a Markov decision process (MDP) for the human in an arbitrary but fixed scenario. The distinctive issue is that – in contrast to existing models – under-specification of the human behavior is included. Probabilistic model checking is used to predict the human’s behavior. Finally, the MDP model is extended with a robot model. Optimal robot policies are synthesized by analyzing the resulting two-player stochastic game. Experimental results with a prototypical implementation using PRISM show promising results.
Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype.

Basal-like breast cancer is associated with high grade, poor prognosis, and younger patient age. Clinically, a triple-negative phenotype definition [estrogen receptor, progesterone receptor, and human epidermal growth factor receptor (HER)-2, all negative] is commonly used to identify such cases. EGFR and cytokeratin 5/6 are readily available positive markers of basal-like breast cancer applicable to standard pathology specimens. This study directly compares the prognostic significance between three- and five-biomarker surrogate panels to define intrinsic breast cancer subtypes, using a large clinically annotated series of breast tumors.



Four thousand forty-six invasive breast cancers were assembled into tissue microarrays. All had staging, pathology, treatment, and outcome information; median follow-up was 12.5 years. Cox regression analyses and likelihood ratio tests compared the prognostic significance for breast cancer death-specific survival (BCSS) of the two immunohistochemical panels.



Among 3,744 interpretable cases, 17% were basal using the triple-negative definition (10-year BCSS, 6 7%) and 9% were basal using the five-marker method (10-year BCSS, 62%). Likelihood ratio tests of multivariable Cox models including standard clinical variables show that the five-marker panel is significantly more prognostic than the three-marker panel. The poor prognosis of triple-negative phenotype is conferred almost entirely by those tumors positive for basal markers. Among triple-negative patients treated with adjuvant anthracycline-based chemotherapy, the additional positive basal markers identified a cohort of patients with significantly worse outcome.



The expanded surrogate immunopanel of estrogen receptor, progesterone receptor, human HER-2, EGFR, and cytokeratin 5/6 provides a more specific definition of basal-like breast cancer that better predicts breast cancer survival.
A robotic bipedal model for human walking with slips

Slip is the major cause of falls in human locomotion. We present a new bipedal modeling approach to capture and predict human walking locomotion with slips. Compared with the existing bipedal models, the proposed slip walking model includes the human foot rolling effects, the existence of the double-stance gait and active ankle joints. One of the major developments is the relaxation of the nonslip assumption that is used in the existing bipedal models. We conduct extensive experiments to optimize the gait profile parameters and to validate the proposed walking model with slips. The experimental results demonstrate that the model successfully predicts the human recovery gaits with slips.
Computational Mapping of the Ground Reflectivity with Laser Scanners

In this investigation we focus on the problem of mapping the ground reflectivity with multiple laser scanners mounted on mobile robots/vehicles. The problem originates because regions of the ground become populated with a varying number of reflectivity measurements whose value depends on the observer and its corresponding perspective. Here, we propose a novel automatic, data-driven computational mapping framework specifically aimed at preserving edge sharpness in the map reconstruction process and that considers the sources of measurement variation. Our new formulation generates map-perspective gradients and applies sub-set selection fusion and de-noising operators to these through iterative algorithms that minimize an ℓ1 sparse regularized least squares formulation. Reconstruction of the ground reflectivity is then carried out based on Poisson's formulation posed as an ℓ2 term promoting consistency with the fused gradient of map-perspectives and a term that ensures equality constraints with reference measurement map data. We demonstrate our new framework outperforms the capabilities of existing ones with experiments realized on Ford's fleet of autonomous vehicles. For example, we show we can achieve map enhancement (i.e., contrast enhancement), artifact removal, de-noising and map-stitching without requiring an additional reflectivity adjustment to calibrate sensors to the specific mounting and robot/vehicle motion.
How do testers do it? An exploratory study on manual testing practices

We present the results of a qualitative observation study on the manual testing practices in four software development companies. Manual testing practices are seldom studied, and based on the literature we conjecture that they have a strong effect on the effectiveness of manual testing. We observed testing sessions of 11 software professionals performing system level functional testing. As a result we identified 22 manual testing practices that we classified into 9 test session strategies and 13 detailed test execution techniques. Many of the identified techniques were based on similar ideas as traditional test case design techniques. However, the subjects applied these techniques during manual testing without separate test design phase. The results indicate that software professionals use a wide set of strategies and techniques when performing manual testing. Testers seem to need and use techniques even if applying exploratory testing.
Safety and walking ability of KAFO users with the C-Brace® Orthotronic Mobility System, a new microprocessor stance and swing control orthosis

There are clear indications for benefits of stance control orthoses compared to locked knee ankle foot orthoses. However, stance control orthoses still have limited function compared with a sound human leg.



The aim of this study was to evaluate the potential benefits of a microprocessor stance and swing control orthosis compared to stance control orthoses and locked knee ankle foot orthoses in activities of daily living.



Survey of lower limb orthosis users before and after fitting of a microprocessor stance and swing control orthosis.



Thirteen patients with various lower limb pareses completed a baseline survey for their current orthotic device (locked knee ankle foot orthosis or stance control orthosis) and a follow-up for the microprocessor stance and swing control orthosis with the Orthosis Evaluation Questionnaire, a new self-reported outcome measure devised by modifying the Prosthesis Evaluation Questionnaire for use in lower limb orthotics and the Activities of Daily Living Questionnaire.



The Orthosis Evaluation Questionnaire results demonstrated significant improvements by microprocessor stance and swing control orthosis use in the total score and the domains of ambulation ( p = .001), paretic limb health ( p = .04), sounds ( p = .02), and well-being ( p = .01). Activities of Daily Living Questionnaire results showed significant improvements with the microprocessor stance and swing control orthosis with regard to perceived safety and difficulty of activities of daily living.



The microprocessor stance and swing control orthosis may facilitate an easier, more physiological, and safer execution of many activities of daily living compared to traditional leg orthosis technologies.  This study compared patient-reported outcomes of a microprocessor stance and swing control orthosis (C-Brace) to those with traditional knee ankle foot orthosis and stance control orthosis devices. The C-Brace offers new functions including controlled knee flexion during weight bearing and dynamic swing control, resulting in significant improvements in perceived orthotic mobility and safety.
Deconvolution of astronomical images using the multiscale maximum entropy method

— Following the ideas of Bontekoe et al. who noticed that the classical Maximum Entropy Method (MEM) had difficulties to efficiently restore high and low spatial frequency structure in an image at the same time, we use the wavelet transform, a mathematical tool to decompose a signal into different frequency bands. We introduce the concept of multi-scale entropy of an image, leading to a better restoration at all spatial frequencies. This deconvolution method is flux conservative and the use of a multiresolution support solves the problem of MEM to choose the α parameter, i.e. the relative weight between the goodness-of-fit and the entropy. We show that our algorithm is efficient too for filtering astronomical images. A range of practical examples illustrate this approach.