nils-herrmann/clean_scirepeval huggingface dataset:
Targeting of prolamins by RNAi in bread wheat: effectiveness of seven silencing fragment combinations for obtaining lines devoid of coeliac disease epitopes from highly immunogenic gliadins.
Venue: Plant biotechnology journal

Gluten proteins are responsible for the viscoelastic properties of wheat flour but also for triggering pathologies in susceptible individuals, of which coeliac disease (CD) and noncoeliac gluten sensitivity may affect up to 8% of the population. The only effective treatment for affected persons is a strict gluten free diet. Here, we report the effectiveness of seven plasmid combinations, encompassing RNAi fragments from a g o gliadins, and LMW glutenin subunits, for silencing the expression of different prolamin fractions. Silencing patterns of transgenic lines were analysed by gel electrophoresis, RP HPLC and mass spectrometry (LC MS/MS) whereas gluten immunogenicity was assayed by an anti gliadin 33 mer monoclonal antibody (moAb) Plasmid combinations 1 and 2 downregulated only g and a gliadins, respectively. Four plasmid combinations were highly effective in the silencing of o gliadins and g gliadins, and three of these also silenced a gliadins. HMW glutenins were upregulated in all but one plasmid combination, while LMW glutenins were downregulated in three plasmid combinations. Total protein and starch contents were unaffected regardless of the plasmid combination used. Six plasmid combinations provided strong reduction in the gluten content as measured by moAb and for two combinations, this reduction was higher than 90% in comparison with the wild type. CD epitope analysis in peptides identified in LC MS/MS showed that lines from three plasmid combinations were totally devoid of CD epitopes from the highly immunogenic a and o gliadins. Our findings raise the prospect of breeding wheat species with low levels of harmful gluten, and of achieving the important goal of developing nontoxic wheat cultivars.
Sodium signaling and astrocyte energy metabolism
Venue: Glia

The Na+ gradient across the plasma membrane is constantly exploited by astrocytes as a secondary energy source to regulate the intracellular and extracellular milieu, and discard waste products. One of the most prominent roles of astrocytes in the brain is the Na+ dependent clearance of glutamate released by neurons during synaptic transmission. The intracellular Na+ load collectively generated by these processes converges at the Na,K ATPase pump, responsible for Na+ extrusion from the cell, which is achieved at the expense of cellular ATP. These processes represent pivotal mechanisms enabling astrocytes to increase the local availability of metabolic substrates in response to neuronal activity. This review presents basic principles linking the intracellular handling of Na+ following activity related transmembrane fluxes in astrocytes and the energy metabolic pathways involved. We propose a role of Na+ as an energy currency and as a mediator of metabolic signals in the context of neuron glia interactions. We further discuss the possible impact of the astrocytic syncytium for the distribution and coordination of the metabolic response, and the compartmentation of these processes in cellular microdomains and subcellular organelles. Finally, we illustrate future avenues of investigation into signaling mechanisms aimed at bridging the gap between Na+ and the metabolic machinery. GLIA 2016;64:1667 1676
Geographical distribution of Amblyomma cajennense (sensu lato) ticks (Parasitiformes: Ixodidae) in Brazil, with description of the nymph of A. cajennense (sensu stricto)
Venue: Parasites Vectors

BackgroundUntil recently, Amblyomma cajennense (Fabricius, 1787) was considered to represent a single tick species in the New World. Recent studies have split this taxon into six species. While the A. cajennense species complex or A. cajennense (sensu lato) (s.l. is currently represented by two species in Brazil, A. cajennense (sensu stricto) (s.s. and Amblyomma sculptum Berlese, 1888, their geographical distribution is poorly known.MethodsThe distribution of the A. cajennense (s.l. in Brazil was determined by morphological examination of all lots of A. cajennense (s.l. in two large tick collections of Brazil, and by collecting new material during three field expeditions in the possible transition areas between the distribution ranges of A. cajennense (s.s. and A. sculptum. Phylogenetic analysis inferred from the ITS2 rRNA gene was used to validate morphological results. Morphological description of the nymphal stage of A. cajennense (s.s. is provided based on laboratory reared specimens.ResultsFrom the tick collections, a total 12,512 adult ticks were examined and identified as 312 A. cajennense (s.s. 6,252 A. sculptum and 5,948 A. cajennense (s.l. A total of 1,746 ticks from 77 localities were collected during field expeditions, and were identified as 249 A. cajennense (s.s. 443 A. sculptum, and 1,054 A. cajennense (s.l. [these A. cajennense (s.l. ticks were considered to be males of either A. cajennense (s.s. or A. sculptum] At least 23 localities contained the presence of both A. cajennense (s.s. and A. sculptum in sympatry. DNA sequences of the ITS2 gene of 50 ticks from 30 localities confirmed the results of the morphological analyses. The nymph of A. cajennense (s.s. is morphologically very similar to A. sculptum.ConclusionOur results confirmed that A. cajennense (s.l. is currently represented in Brazil by only two species, A. cajennense (s.s. and A. sculptum. While these species have distinct distribution areas in the country, they are found in sympatry in some transition areas. The current distribution of A. cajennense (s.l. has important implications to public health, since in Brazil A. sculptum is the most important vector of the bacterium Rickettsia rickettsii, the etiological agent of Brazilian spotted fever.
N dimensional hypervolumes to study stability of complex ecosystems.
Venue: Ecology letters

Although our knowledge on the stabilising role of biodiversity and on how it is affected by perturbations has greatly improved, we still lack a comprehensive view on ecosystem stability that is transversal to different habitats and perturbations. Hence, we propose a framework that takes advantage of the multiplicity of components of an ecosystem and their contribution to stability. Ecosystem components can range from species or functional groups, to different functional traits, or even the cover of different habitats in a landscape mosaic. We make use of n dimensional hypervolumes to define ecosystem states and assess how much they shift after environmental changes have occurred. We demonstrate the value of this framework with a study case on the effects of environmental change on Alpine ecosystems. Our results highlight the importance of a multidimensional approach when studying ecosystem stability and show that our framework is flexible enough to be applied to different types of ecosystem components, which can have important implications for the study of ecosystem stability and transient dynamics.
Effector gd T Cell Differentiation Relies on Master but Not Auxiliary Th Cell Transcription Factors
Venue: The Journal of Immunology

gd T lymphocytes are programmed into distinct IFN g producing CD27+ (gd27+ and IL 17 producing CD27 (gd27 subsets that play key roles in protective or pathogenic immune responses. Although the signature cytokines are shared with their ab Th1 (for gd27+ and Th17 (for gd27 cell counterparts, we dissect in this study similarities and differences in the transcriptional requirements of murine effector gd27+ gd27 CCR6 and gd27 CCR6+ gd T cell subsets and ab T cells. We found they share dependence on the master transcription factors T bet and RORgt for IFN g and IL 17 production, respectively. However, Eomes is fully dispensable for IFN g production by gd T cells. Furthermore, the Th17 cell auxiliary transcription factors RORa and BATF are not required for IL 17 production by gd27 cell subsets. We also show that gd27 (but not gd27+ cells become polyfunctional upon IL 1b plus IL 23 stimulation, cosecreting IL 17A, IL 17F, IL 22, GM CSF, and IFN g. Collectively, our in vitro and in vivo data firmly establish the molecular segregation between gd27+ and gd27 T cell subsets and provide novel insight on the nonoverlapping transcriptional networks that control the differentiation of effector gd versus ab T cell subsets.
Stationarity and Long Range Dependence of Carbon Dioxide Emissions: Evidence for Disaggregated Data

This paper examines the stationarity of global carbon dioxide emissions and its components gas, liquids, solids, cement production and gas flaring, as well as global per capita emissions for a long span of data using long range dependence techniques. The empirical results suggest that the series are highly persistent with orders of integration which are above 1 in practically all cases. Disaggregating the data by components, cement production displays the highest persistence, and allowing for structural breaks, two breaks are detected (at 1830 and 1946) for the total series and solids, and one single break (at 1946) for gas, liquids and cement production. In general, higher orders of integration are detected after the break at World War II.
Novel clustering based approach for Local Outlier Detection
Venue: 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

With the rapid expansion of data scale, big data mining and analysis have attracted increasing attention. Outlier detection as an important task of data mining is widely used in many applications. However, conventional outlier detection methods have difficulty handling large scale datasets. In addition, most of them typically can only identify global outliers and are over sensitive to parameters variation. In this paper, we propose a novel method for robust local outlier detection with statistical parameters, which incorporates the clustering based ideas in dealing with big data. Firstly, this method finds some density peaks of dataset by 3s standard. Secondly, each remaining data object in the dataset is assigned to the same cluster as its nearest neighbor of higher density. Finally, we use Chebyshev's inequality and density peak reachability to identify local outliers of each group. The experimental results demonstrate the efficiency and accuracy of the proposed method in identifying both global and local outliers. Moreover, the method is also proved to be more stability analysis than typical outlier detection methods, such as LOF (Local Outlier Factor) and DBSCAN (Density Based Spatial Clustering of Applications with Noise)
On the naturalness of software
Venue: Commun. ACM

Natural languages like English are rich, complex, and powerful. The highly creative and graceful use of languages like English and Tamil, by masters like Shakespeare and Avvaiyar, can certainly delight and inspire. But in practice, given cognitive constraints and the exigencies of daily life, most human utterances are far simpler and much more repetitive and predictable. In fact, these utterances can be very usefully modeled using modern statistical methods. This fact has led to the phenomenal success of statistical approaches to speech recognition, natural language translation, question answering, and text mining and comprehension. We begin with the conjecture that most software is also natural, in the sense that it is created by humans at work, with all the attendant constraints and limitations and thus, like natural language, it is also likely to be repetitive and predictable. We then proceed to ask whether a) code can be usefully modeled by statistical language models and b) such models can be leveraged to support software engineers. Using the widely adopted n gram model, we provide empirical evidence supportive of a positive answer to both these questions. We show that code is also very repetitive, and in fact even more so than natural languages. As an example use of the model, we have developed a simple code completion engine for Java that, despite its simplicity, already improves Eclipse's built in completion capability. We conclude the paper by laying out a vision for future research in this area.
Identification of Factors Promoting Reading Habits of Students: A Case Study on Pakistan

This study is aimed at exploring the factors that are influential in promoting the reading habits of students. The data was collected from 1050 students of three public universities of Punjab with the help of a questionnaire. The study reveals the fact that reading habits are being nurtured from home in which parents play a vital role. Along with parents, teachers nourish this reading habit through their continuous guidance and support. It is recommended that parents and teachers should work in collaboration with one another and create a healthy atmosphere that increases the interest of students in reading. This self interest and support of parents and teachers help in promoting the reading habits of students.  Reading habits; effective study; parental contribution; teachers' support; self interest
Towards a Literate Society the Place of Reading in Rwanda Today

Lack of a reading culture in Rwanda is a widely talked about issue. The government of Rwanda has literary "taken the bull by the horns" in a bid to tame this widespread national malaise. There are a number of efforts ongoing to promote a culture of reading among Rwanda, a society that has hitherto been described as oral. The country's historical disposition has always favoured the spoken word over the written word. Compounded by the traditional and cultural realities, reading has always been kept at the periphery. Inspired by the need for economic development and national stability, Rwanda has put in place a blueprint for promoting literacy skills across the country. Notwithstanding her tumultuous past that culminated with the 1994 Genocide against the Tutsi, considerable milestones have been achieved in reading. However, there is still more to be done for this to be a reality. This paper argues that Rwanda a monolingual country has the potential to harness Kinyarwanda and transform it into a launching pad for promoting literacy. While acknowledging a myriad challenges that the nation grapples with, the country is in a pole position by taking advantage of technology to digitize reading. Better still teachers are charged with the mandate to explore explicit comprehension techniques to teach reading. Suggestions on the common strategies for teaching comprehension are outlined according to Adler (2001)
The Influence of Personality Traits on Emotion Expression in Bulimic Spectrum Disorders: A Pilot Study.
Venue: European eating disorders review the journal of the Eating Disorders Association

Facial expressions are critical in forming social bonds and in signalling one's emotional state to others. In eating disorder patients, impairments in facial emotion recognition have been associated with eating psychopathology severity. Little research however has been carried out on how bulimic spectrum disorder (BSD) patients spontaneously express emotions. Our aim was to investigate emotion expression in BSD patients and to explore the influence of personality traits. Our study comprised 28 BSD women and 15 healthy controls. Facial expressions were recorded while participants played a serious video game. Expressions of anger and joy were used as outcome measures. Overall, BSD participants displayed less facial expressiveness than controls. Among BSD women, expressions of joy were positively associated with reward dependence, novelty seeking and self directedness, whereas expressions of anger were associated with lower self directedness. Our findings suggest that specific personality traits are associated with altered emotion facial expression in patients with BSD.
Doping graphene with boron: a review of synthesis methods, physicochemical characterization, and emerging applications

Graphene based materials can be effectively modified by doping in order to specifically tailor their properties toward specific applications. So far the most used and widely investigated dopant heteroatom is probably nitrogen. However, boron is also an equally important element that can induce novel and complementary properties leading to specific implementation in alternative devices and technologies. In this paper, we survey the most recent preparation methods of boron doped graphene, including materials with specific morphology such as nanoribbons, quantum dots and 3D interconnected systems. We illustrate the results of theoretical and experimental studies dealing with the description and understanding of the main structural, electronic and chemical properties of this material. The emerging applications of boron doped graphene in several technological fields such as electrochemistry, sensors, photovoltaics, catalysis and biology are extensively reviewed.
Epitaxial Graphene on SiC: A Review of Growth and Characterization

This review is devoted to one of the most promising two dimensional (2D) materials, graphene. Graphene can be prepared by different methods and the one discussed here is fabricated by the thermal decomposition of SiC. The aim of the paper is to overview the fabrication aspects, growth mechanisms, and structural and electronic properties of graphene on SiC and the means of their assessment. Starting from historical aspects, it is shown that the most optimal conditions resulting in a large area of one ML graphene comprise high temperature and argon ambience, which allow better controllability and reproducibility of the graphene quality. Elemental intercalation as a means to overcome the problem of substrate influence on graphene carrier mobility has been described. The most common characterization techniques used are low energy electron microscopy (LEEM) angle resolved photoelectron spectroscopy (ARPES) Raman spectroscopy, atomic force microscopy (AFM) in different modes, Hall measurements, etc. The main results point to the applicability of graphene on SiC in quantum metrology, and the understanding of new physics and growth phenomena of 2D materials and devices.
Analysis on L vortex development in a transitional boundary layer

Although plentiful research on L vortex can be found in literature, the mechanism of Lvortex generation is still in veil. Despite the difference in initial perturbation conditions in both experiments and numerical simulations, the following L vortex was found to be basically the same, which leads to an assumption that L vortex is an inherent characteristic of boundary layer equations. On the other hand, the initial disturbance or T S wave is believed to function as trigger and should not be viewed as an embryonic form of L vortex. The notion L vortex comes from wave growth according to primary and secondary instability theory is not convincing at all. In this paper, the shape of L vortex and its relation with initial disturbance is carefully investigated using direct numerical simulation (DNS) The mechanism of L vortex generation is the ultimate goal of this paper.
Fabricating and Tailoring Polyaniline (PANI) Nanofibers with High Aspect Ratio in a Low Acid Environment in a Magnetic Field.
Venue: Chemistry, an Asian journal

In a 0.010 m HCl solution, we successfully transformed irregular polyaniline (PANI) agglomerates into uniform PANI nanofibers with a diameter of 46 145 nm and a characteristic length on the order of several microns by the addition of superparamagnetic Fe3 O4 microspheres in a magnetic field. The PANI morphological evolution showed that the PANI nanofibers stemmed from the PANI coating shell synthesized on the surface of the Fe3 O4 microsphere chains. It was found that the magnetic field could optimize the PANI nanofibers with a narrow diameter size distribution, and effectively suppressed secondary growth. When compared with other microspheres (like silica and polystyrene) only the use of superparamagnetic Fe3 O4 microspheres resulted in the appearance of PANI nanofibers. Attempts to form these high quality PANI nanofibers in other concentrations of HCl solution were unsuccessful. This deficiency was largely attributed to the inappropriate quantity of aniline cations.
Outstanding adsorption performance of high aspect ratio and super hydrophobic carbon nanotubes for oil removal.
Venue: Chemosphere

Oil removal from water is a highly important area due to the large production rate of emulsified oil in water, which is considered one of the major pollutants, having a negative effect on human health, environment and wildlife. In this study, we have reported the application of high quality carbon nanotube bundles produced by an injected vertical chemical vapor deposition (IV CVD) reactor for oil removal. High quality, bundles, super hydrophobic, and high aspect ratio carbon nanotubes were produced. The average diameters of the produced CNTs ranged from 20 to 50 nm while their lengths ranged from 300 to 500 mm. Two types of CNTs namely, P CNTs and C CNTs, (Produced CNTs from the IV CVD reactor and commercial CNTs) were used for oil removal from water. For the first time, thermogravimetric analysis (TGA) was conducted to measure maximum oil uptake using CNT and it was found that P CNT can take oil up to 17 times their weight. The effect of adsorbent dosage, contact time, and agitation speed were examined on the oil spill clean up efficiency using batch sorption experiments. Higher efficiency with almost 97% removal was achieved using P CNTs compared to 87% removal using C CNTs.
Automated detection of diabetic retinopathy in retinal images
Venue: Indian journal of ophthalmology

Diabetic retinopathy (DR) is a disease with an increasing prevalence and the main cause of blindness among working age population. The risk of severe vision loss can be significantly reduced by timely diagnosis and treatment. Systematic screening for DR has been identified as a cost effective way to save health services resources. Automatic retinal image analysis is emerging as an important screening tool for early DR detection, which can reduce the workload associated to manual grading as well as save diagnosis costs and time. Many research efforts in the last years have been devoted to developing automatic tools to help in the detection and evaluation of DR lesions. However, there is a large variability in the databases and evaluation criteria used in the literature, which hampers a direct comparison of the different studies. This work is aimed at summarizing the results of the available algorithms for the detection and classification of DR pathology. A detailed literature search was conducted using PubMed. Selected relevant studies in the last 10 years were scrutinized and included in the review. Furthermore, we will try to give an overview of the available commercial software for automatic retinal image analysis.
Gated Graph Sequence Neural Networks
Venue: ICLR

Graph structured data appears frequently in domains including chemistry, natural language semantics, social networks, and knowledge bases. In this work, we study feature learning techniques for graph structured inputs. Our starting point is previous work on Graph Neural Networks (Scarselli et al. 2009) which we modify to use gated recurrent units and modern optimization techniques and then extend to output sequences. The result is a flexible and broadly useful class of neural network models that has favorable inductive biases relative to purely sequence based models (e.g. LSTMs) when the problem is graph structured. We demonstrate the capabilities on some simple AI (bAbI) and graph algorithm learning tasks. We then show it achieves state of the art performance on a problem from program verification, in which subgraphs need to be matched to abstract data structures.