nils-herrmann/clean_scirepeval huggingface dataset:
Concise Integer Linear Programming Formulations for Dependency Parsing

We formulate the problem of nonprojective dependency parsing as a polynomial-sized integer linear program. Our formulation is able to handle non-local output features in an efficient manner; not only is it compatible with prior knowledge encoded as hard constraints, it can also learn soft constraints from data. In particular, our model is able to learn correlations among neighboring arcs (siblings and grandparents), word valency, and tendencies toward nearlyprojective parses. The model parameters are learned in a max-margin framework by employing a linear programming relaxation. We evaluate the performance of our parser on data in several natural languages, achieving improvements over existing state-of-the-art methods.
Inflammation in atherosclerosis

Abundant data link hypercholesterolaemia to atherogenesis. However, only recently have we appreciated that inflammatory mechanisms couple dyslipidaemia to atheroma formation. Leukocyte recruitment and expression of pro-inflammatory cytokines characterize early atherogenesis, and malfunction of inflammatory mediators mutes atheroma formation in mice. Moreover, inflammatory pathways promote thrombosis, a late and dreaded complication of atherosclerosis responsible for myocardial infarctions and most strokes. The new appreciation of the role of inflammation in atherosclerosis provides a mechanistic framework for understanding the clinical benefits of lipid-lowering therapies. Identifying the triggers for inflammation and unravelling the details of inflammatory pathways may eventually furnish new therapeutic targets.
A discussion on the validation tests employed to compare human action recognition methods using the MSR Action3D dataset

This paper aims to determine which is the best human action recognition method based on features extracted from RGB-D devices, such as the Microsoft Kinect. A review of all the papers that make reference to MSR Action3D, the most used dataset that includes depth information acquired from a RGB-D device, has been performed. We found that the validation method used by each work differs from the others. So, a direct comparison among works cannot be made. However, almost all the works present their results comparing them without taking into account this issue. Therefore, we present different rankings according to the methodology used for the validation in orden to clarify the existing confusion.
Congenital cystic eye with multiple dermal appendages and intracranial congenital anomalies.

Congenital cystic eye (anophthalmia with cyst) is an extremely rare anomaly discovered at birth with few reported cases in the literature, resulting from partial or complete failure during invagination of the primary optic vesicle during fetal development. Herein we present the radiographic, ultrasound, and magnetic resonance imaging findings of a unique case of congenital cystic eye associated with dermal appendages and advanced intracranial congenital anomalies in a 3-month-old boy.
A Decision Support System for Global Team Management: Expert Evaluation

The literature is rich in examples of both successful and failed global software development projects. However, practitioners do not have the time to wade through the many recommendations to work out which ones apply to them. To this end, we developed a prototype Decision Support System (DSS) for Global Teaming (GT), with the goal of making research results available to practitioners.  We want the system we build to be based on the real needs of practitioners: the end users of our system. Therefore the aim of this study is to assess the usefulness and usability of our proof-of-concept in order to create a tool that is actually used by practitioners.  Twelve experts in GSD evaluated our system. Each individual participant tested the system and completed a short usability questionnaire.  Feedback on the prototype DSS was positive. All experts supported the concept, although many suggested areas that could be improved. Both expert practitioners and researchers participated, providing different perspectives on what we need to do to improve the system.  Involving both practitioners (users) and researchers in the evaluation elicited a range of useful feedback, providing useful insights that might not have emerged had we focused on one or the other group. However, even when we implement recommended changes, we still need to persuade practitioner to adopt the new tool.
The effects of exercise on spatial learning and anxiety-like behavior are mediated by an IGF-I-dependent mechanism related to hippocampal neurogenesis

Knowledge about the effects of physical exercise on brain is accumulating although the mechanisms through which exercise exerts these actions remain largely unknown. A possible involvement of adult hippocampal neurogenesis (AHN) in the effects of exercise is debated while the physiological and pathological significance of AHN is under intense scrutiny. Recently, both neurogenesis-dependent and independent mechanisms have been shown to mediate the effects of physical exercise on spatial learning and anxiety-like behaviors. Taking advantage that the stimulating effects of exercise on AHN depend among others, on serum insulin-like growth factor I (IGF-I), we now examined whether the behavioral effects of running exercise are related to variations in hippocampal neurogenesis, by either increasing or decreasing it according to serum IGF-I levels. Mutant mice with low levels of serum IGF-I (LID mice) had reduced AHN together with impaired spatial learning. These deficits were not improved by running. However, administration of exogenous IGF-I ameliorated the cognitive deficit and restored AHN in LID mice. We also examined the effect of exercise in LID mice in the novelty-suppressed feeding test, a measure of anxiety-like behavior in laboratory animals. Normal mice, but not LID mice, showed reduced anxiety after exercise in this test. However, after exercise, LID mice did show improvement in the forced swim test, a measure of behavioral despair. Thus, many, but not all of the beneficial effects of exercise on brain function depend on circulating levels of IGF-I and are associated to increased hippocampal neurogenesis, including improved cognition and reduced anxiety.
BoS cost savings and LCOE reduction for a 10 MW PV system with the 500 kW transformerless inverter

This paper presents the cost advantages that a high-performance, 500 kW, transformerless PV inverter can have for a solar PV system. Higher efficiency, smaller size, and lower installation costs impact balance-of -system (BoS) costs and reduce the levelized cost of energy (LCOE) compared with traditional, transformer-based PV inverters. These cost advantages should be considered as integrators and end-users in China and the U.S. select and install inverters in PV systems. This paper focuses on the effect of a more efficient PV inverter on BoS cost and LCOE, analyzing real PV grid-connected, transformerless inverter applications as well as unipolar and bipolar PV array configurations. Some standards and specifications for the PV inverters are introduced, such as CEC-weighted and EU efficiency. Using the Solar Advisory Model (SAM) and PVSYST software with PV module, inverter, and weather data, a simulation to calculate the LCOE and system performance rate of a bipolar PV array with a transformerless inverter is presented for a 10 MW PV system in Dunhuang, China.
Respiratory syncytial virus-positive bronchiolitis in hospitalized infants is associated with thrombocytosis.

Secondary thrombocytosis is associated with a variety of clinical conditions, one of which is lower respiratory tract infection. However, reports on thrombocytosis induced by viral infections are scarce.



To assess the rate of thrombocytosis (platelet count > 500 x 10(9)/L) in hospitalized infants with bronchiolitis and to investigate its potential role as an early marker of respiratory syncytial virus infection.



Clinical data on 469 infants aged < or = 4 months who were hospitalized for bronchiolitis were collected prospectively and compared between RSV-positive and RSV-negative infants.



The rate of thrombocytosis was significantly higher in RSV-positive than RSV-negative infants (41.3% vs. 29.2%, P=0.031). The odds ratio of an infant with bronchiolitis and thrombocytosis to have a positive RSV infection compared to an infant with bronchiolitis and a normal platelet count was 1.7 (P= 0.023, 95% confidence interval 1.07-2.72). There was no significant difference in mean platelet count between the two groups.



RSV-positive bronchiolitis in hospitalized young infants is associated with thrombocytosis.
Colloidal micro- and nano-particles as templates for polyelectrolyte multilayer capsules.

Colloidal particles play an important role in various areas of material and pharmaceutical sciences, biotechnology, and biomedicine. In this overview we describe micro- and nano-particles used for the preparation of polyelectrolyte multilayer capsules and as drug delivery vehicles. An essential feature of polyelectrolyte multilayer capsule preparations is the ability to adsorb polymeric layers onto colloidal particles or templates followed by dissolution of these templates. The choice of the template is determined by various physico-chemical conditions: solvent needed for dissolution, porosity, aggregation tendency, as well as release of materials from capsules. Historically, the first templates were based on melamine formaldehyde, later evolving towards more elaborate materials such as silica and calcium carbonate. Their advantages and disadvantages are discussed here in comparison to non-particulate templates such as red blood cells. Further steps in this area include development of anisotropic particles, which themselves can serve as delivery carriers. We provide insights into application of particles as drug delivery carriers in comparison to microcapsules templated on them.
Uropathogenic Escherichia coli in Iran: Serogroup distributions, virulence factors and antimicrobial resistance properties

Urinary tract infections (UTIs) are one of the most common bacterial infections with global expansion. These infections are predominantly caused by uropathogenic Escherichia coli (UPEC). Totally, 123 strains of Escherichia coli isolated from UTIs patients, using bacterial culture method were subjected to polymerase chain reactions for detection of various O- serogroups, some urovirulence factors, antibiotic resistance genes and resistance to 13 different antibiotics. According to data, the distribution of O1, O2, O6, O7 and O16 serogroups were 2.43%, besides O22, O75 and O83 serogroups were 1.62%. Furthermore, the distribution of O4, O8, O15, O21 and O25 serogroups were 5.69%, 3.25%, 21.13%, 4.06% and 26.01%, respectively. Overall, the fim virulence gene had the highest (86.17%) while the usp virulence gene had the lowest distributions of virulence genes in UPEC strains isolated from UTIs patients. The vat and sen virulence genes were not detected in any UPEC strains. Totally, aadA1 (52.84%), and qnr (46.34%) were the most prevalent antibiotic resistance genes while the distribution of cat1 (15.44%), cmlA (15.44%) and dfrA1 (21.95%) were the least. Resistance to penicillin (100%) and tetracycline (73.98%) had the highest while resistance to nitrofurantoin (5.69%) and trimethoprim (16.26%) had the lowest frequencies. This study indicated that the UPEC strains which harbored the high numbers of virulence and antibiotic resistance genes had the high ability to cause diseases that are resistant to most antibiotics. In the current situation, it seems that the administration of penicillin and tetracycline for the treatment of UTIs is vain.
Deep-FSMN for Large Vocabulary Continuous Speech Recognition

In this paper, we present an improved feedforward sequential memory networks (FSMN) architecture, namely Deep-FSMN (DFSMN), by introducing skip connections between memory blocks in adjacent layers. These skip connections enable the information flow across different layers and thus alleviate the gradient vanishing problem when building very deep structure. As a result, DFSMN significantly benefits from these skip connections and deep structure. We have compared the performance of DFSMN to BLSTM both with and without lower frame rate (LFR) on several large speech recognition tasks, including English and Mandarin. Experimental results shown that DFSMN can consistently outperform BLSTM with dramatic gain, especially trained with LFR using CD-Phone as modeling units. In the 20000 hours Fisher (FSH) task, the proposed DFSMN can achieve a word error rate of 9.4% by purely using the cross-entropy criterion and decoding with a 3-gram language model, which achieves a 1.5% absolute improvement compared to the BLSTM. In a 20000 hours Mandarin recognition task, the LFR trained DFSMN can achieve more than 20% relative improvement compared to the LFR trained BLSTM. Moreover, we can easily design the lookahead filter order of the memory blocks in DFSMN to control the latency for real-time applications.
Agonist depot versus OCP programming of frozen embryo transfer: a retrospective analysis of freeze-all cycles

In segmented ART treatment or so-called ‘freeze-all’ strategy fresh embryo transfer is deferred, embryos cryopreserved, and the embryo transferred in a subsequent frozen embryo transfer (FET) cycle. The purpose of this cohort study was to compare a GnRHa depot with an oral contraceptive pill (OCP) programming protocol for the scheduling of an artificial cycle FET (AC-FET) after oocyte pick-up (OPU). This retrospective cohort study was conducted on prospectively performed segmented ART cycles performed between September 2014 and April 2015. The pregnancy, treatment duration, and cycle cancellation outcomes of 170 OCP programmed AC-FET cycles were compared with 241 GnRHa depot programmed AC-FET cycles. No significant difference was observed in the per transfer pregnancy and clinical pregnancy rates between the OCP and GnRHa groups, 72.0 versus 77.2 %, and 57.8 versus 64.3 %, respectively. Furthermore, the early pregnancy loss rate was non-significantly different between the OCP and GnRH protocol groups, 19.8 versus 16.7 %, respectively. However, nine (5.29 %) cycles were cancelled due to high progesterone in the OCP protocol group, while no cycles were cancelled in the GnRHa protocol group and the time taken between OPU and FET was 19 days longer (54.7 vs 35.6 days) in the OCP protocol compared to the GnRHa protocol. The results of this AC-FET programming study suggests that the inclusion of GnRHa depot cycle programming into a segmented ART treatment will ensure pregnancy, while significantly reducing treatment duration and cycle cancellation.
Spectroscopic and clinical aspects of noninvasive glucose measurements.

Frequent determination of glucose concentrations in diabetic patients is an important tool for diabetes management. This requires repetitive lancing and finger bleeding. Use of noninvasive (NI) detection techniques offers several advantages, such as the absence of pain and exposure to sharp objects and biohazard materials, the potential for increased frequency of testing, and hence, tighter control of the glucose concentrations, and the potential for a closed-loop system including a monitor and an insulin pump. These potential advantages have led to considerable interest in the commercialization of NI glucose monitoring devices. Review of the scientific, patent, and commercial literature indicates that the spectroscopic basis for NI determination of glucose is not yet well established, and attempts at commercialization may be several steps ahead of our understanding the origin and characteristics of an in vivo glucose-specific or glucose-related signal. Several technologies have potential for leading to viable measuring devices, but most of the data are based on in vitro experimentation. Because of the technical complexity of in vivo glucose measurements, this review aims at discussing the gap between the established need and current technology limitations.
Impact of GM crops on biodiversity.

The potential impact of GM crops on biodiversity has been a topic of interest both in general as well as specifically in the context of the Convention on Biological Diversity. Agricultural biodiversity has been defined at levels from genes to ecosystems that are involved or impacted by agricultural production (www.cbd.int/agro/whatis.shtml). After fifteen years of commercial cultivation, a substantial body of literature now exists addressing the potential impacts of GM crops on the environment. This review takes a biodiversity lens to this literature, considering the impacts at three levels: the crop, farm and landscape scales. Within that framework, this review covers potential impacts of the introduction of genetically engineered crops on: crop diversity, biodiversity of wild relatives, non-target soil organisms, weeds, land use, non-target above-ground organisms, and area-wide pest suppression. The emphasis of the review is peer-reviewed literature that presents direct measures of impacts on biodiversity. In addition, possible impacts of changes in management practises such as tillage and pesticide use are also discussed to complement the literature on direct measures. The focus of the review is on technologies that have been commercialized somewhere in the world, while results may emanate from non-adopting countries and regions. Overall, the review finds that currently commercialized GM crops have reduced the impacts of agriculture on biodiversity, through enhanced adoption of conservation tillage practices, reduction of insecticide use and use of more environmentally benign herbicides and increasing yields to alleviate pressure to convert additional land into agricultural use.
Multi-modal Unsupervised Feature Learning for RGB-D Scene Labeling

Most of the existing approaches for RGB-D indoor scene labeling employ hand-crafted features for each modality independently and combine them in a heuristic manner. There has been some attempt on directly learning features from raw RGB-D data, but the performance is not satisfactory. In this paper, we adapt the unsupervised feature learning technique for RGB-D labeling as a multi-modality learning problem. Our learning framework performs feature learning and feature encoding simultaneously which significantly boosts the performance. By stacking basic learning structure, higher-level features are derived and combined with lower-level features for better representing RGB-D data. Experimental results on the benchmark NYU depth dataset show that our method achieves competitive performance, compared with state-of-theart.
Inventory forecasting model using genetic programming and Holt-Winter's exponential smoothing method

Accurate and reliable inventory forecasting can save an organization from overstock, under-stock and no stock/stock-out situation of inventory. Overstocking leads to high cost of storage and its maintenance, whereas under-stocking leads to failure to meet the demand and losing profit and customers, similarly stock-out leads to complete halt of production or sale activities. Inventory transactions generate data, which is a time-series data having characteristic volume, speed, range and regularity. The inventory level of an item depends on many factors namely, current stock, stock-on-order, lead-time, annual/monthly target. In this paper, we present a perspective of treating Inventory management as a problem of Genetic Programming based on inventory transactions data. A Genetic Programming — Symbolic Regression (GP-SR) based mathematical model is developed and subsequently used to make forecasts using Holt-Winters Exponential Smoothing method for time-series modeling. The GP-SR model evolves based on RMSE as the fitness function. The performance of the model is measured in terms of RMSE and MAE. The estimated values of item demand from the GP-SR model is finally used to simulate a time-series and forecasts are generated for inventory required on a monthly time horizon.
Through-focus performance with multifocal contact lenses: effect of binocularity, pupil diameter and inherent ocular aberrations.

To evaluate the effects of the wearer's pupil size and spherical aberration on visual performance with centre-near, aspheric multifocal contact lenses (MFCLs). The advantage of binocular over monocular vision was also investigated.



Twelve young volunteers, with an average age of 27 ± 5 years, participated in the study. LogMAR Visual Acuity (VA) was measured under cycloplegia for a range of defocus levels (from +3.0 to -3.0 D, in 0.5 D steps) with no correction and with three aspheric MFCLs (Air Optix Aqua Multifocal) with a centre-near design, providing correction for 'Low', 'Med' and 'High' near demands. Measurements were performed for all combinations of the following conditions: (1) artificial pupils of 6 and 3 mm diameter, (2) binocular and monocular (dominant eye) vision. Depth-of-focus (DOF) was calculated from the VA vs defocus curves. Ocular aberrations under cycloplegia were measured using iTrace.



VA at -3.0 D defocus (simulating near performance) was statistically higher for the 3 mm than for the 6 mm pupil (p = 0.006), and for binocular rather than for monocular vision (p < 0.001). Similarly, DOF was better for the 3 mm pupil (p = 0.002) and for binocular viewing conditions (p < 0.001). Both VA at -3.0 D defocus and DOF increased as the 'addition' of the MFCL correction increased. Finally, with the centre-near MFCLs a linear correlation was found between VA at -3.0 D defocus and the wearer's ocular spherical aberration (R(2) = 0.20 p < 0.001 for 6 mm data), with the eyes exhibiting the higher positive spherical aberration experiencing worse VAs. By contrast, no correlation was found between VA and spherical aberration at 0.00 D defocus (distance vision).



Both near VA and depth-of-focus improve with these MFCLs, with the effects being more pronounced for small pupils and for binocular rather than monocular vision. Coupling of the wearer's ocular spherical aberration with the aberration profiles provided by MFCLs affects their functionality.
Multiple Sound Source Mapping for a Mobile Robot by Self-motion Triangulation

The paper describes a 2D sound source mapping system for a mobile robot. We developed a multiple sound sources localization method for a mobile robot with a 32 channel concentric microphone array. The system can separate multiple moving sound sources using direction localization. Directional localization and separation of different pressure sound sources is achieved using the delay and sum beam forming (DSBF) and the frequency band selection (FBS) algorithm. Sound sources were mapped by using a wheeled robot equipped with the microphone array. The robot localizes sounds direction on the move and estimates sound sources position using triangulation. Assuming the movement of sound sources, the system set a time limit and uses only the last few seconds data. By using the random sample consensus (RANSAC) algorithm for position estimation, we achieved 2D multiple sound source mapping from time limited data with high accuracy. Also, moving sound source separation is experimentally demonstrated with segments of the DSBF enhanced signal derived from the localization process
A Novel Method of Feature Selection based on SVM

A novel method of feature selection combined with sample selection is proposed to select discriminant features in this paper. Based on support vector machine trained on training set, the samples excluding the misclassified samples and support vector samples are used to select informative features during the procedure of recursive feature selection. The feature selection method is applied to seven datasets, and the classification results of the selected discriminant features show that the method is effective and reliable for selecting features with high classification information.