nils-herrmann/clean_scirepeval huggingface dataset:
Long non coding RNA ADNCR suppresses adipogenic differentiation by targeting miR 204.
Venue: Biochimica et biophysica acta

Adipogenesis is a complex and precisely orchestrated process mediated by a network of adipogenic regulatory factors. Several studies have highlighted the relevance of lncRNAs in adipocyte differentiation, but the precise molecular mechanism has largely remained elusive. In the present study, we performed Ribo Zero RNA Seq to investigate both the poly(A)+and poly(A) lncRNAs of in vitro cultured bovine preadipocytes and differentiated adipocytes. A stringent set of 2882 lncRNAs was finally identified. A comparison of the lncRNAs expression profiles revealed that 16 lncRNAs are differentially expressed during adipocyte differentiation. We focused on the most downregulated lncRNA, which we named adipocyte differentiation associated long noncoding RNA (ADNCR) Mechanistically, ADNCR inhibited adipocyte differentiation by functioning as a competing endogenous RNA (ceRNA) for miR 204, thereby augmenting the expression of the miR 204 target gene, SIRT1, which is known to inhibit adipocyte differentiation and adipogenic gene expression by docking with NCoR and SMART to repress PPARg activity. Our data not only provide a valuable genomic resource for the identification of lncRNAs with functional roles in adipocyte differentiation but also reveal new insights into understanding the mechanisms of adipogenic differentiation.
Semantic preview benefit in English: Individual differences in the extraction and use of parafoveal semantic information.
Venue: Journal of experimental psychology. Learning, memory, and cognition

Although there is robust evidence that skilled readers of English extract and use orthographic and phonological information from the parafovea to facilitate word identification, semantic preview benefits have been elusive. We sought to establish whether individual differences in the extraction and/or use of parafoveal semantic information could account for this discrepancy. Ninety nine adult readers who were assessed on measures of reading and spelling ability read sentences while their eye movements were recorded. The gaze contingent boundary paradigm was used to manipulate the availability of relevant semantic and orthographic information in the parafovea. On average, readers showed a benefit from previews high in semantic feature overlap with the target. However, reading and spelling ability yielded opposite effects on semantic preview benefit. High reading ability was associated with a semantic preview benefit that was equivalent to an identical preview on first pass reading. High spelling ability was associated with a reduced semantic preview benefit despite an overall higher rate of skipping. These results suggest that differences in the magnitude of semantic preview benefits in English reflect constraints on extracting semantic information from the parafovea and competition between the orthographic features of the preview and the target.
Discrete differential evolutionary algorithm for job shop scheduling problem with minimizing total weighted tardiness
Venue: 2016 IEEE Congress on Evolutionary Computation (CEC)

In the modern manufacturing and operations management, on time delivery is a critical factor towards realizing customer satisfaction. This paper focuses on job shop scheduling problem to minimize total weighted tardiness and proposes a discrete differential evolution algorithm for this problem. In order to improve the search ability and efficiency, this paper hybrids the local search which is based on the scheduling critical path theory, and develops a migration operation based on the population diversity theory to jump out of local optimum. Computational results on benchmark instances from the literatures show that the proposed algorithm can compete with the existing algorithms.
M2 macrophages in metabolism
Venue: Diabetology International

Adipose tissue not only functions as the major energy storing tissue, but also functions as an endocrine organ that regulates systemic metabolism by releasing various hormones called adipokines. Macrophages play a critical role in maintaining adipocyte health in a lean state and in remodeling during the progression of obesity. Large numbers of classically activated (M1) macrophages accumulate in adipose tissue as adipocytes become larger because of excessive energy conditions, and they adversely affect insulin resistance by triggering local and systemic inflammation. In contrast, alternatively activated (M2) macrophages seem to maintain the health of adipose tissues in a lean state. In addition, they play a role in adapting to excess energy states, because M2 macrophage dysfunction caused by genetic disruption of the M2 gene results in metabolic disorders under high fat fed conditions that are probably attributable to their anti inflammatory functions. Nonetheless, how M2 macrophages contribute to maintaining the health of adipose tissue and therefore to insulin sensitivity is largely unknown. In this article, we review the literature on the role of M1 and M2 macrophages in metabolism, with a special focus on the role of M2 macrophages in adipose tissue. Likewise, we raise topics of M2 macrophages in non adipose tissues to expand our understanding of macrophage heterogeneity.
A CLASSICAL REVIEW ON ARSHA (HAEMORRHOIDS/PILES) CURRENT TREATMENT STRATEGIES AND FUTURE PROSPECTS

Arsha (Piles) is an extremely common problem and it has been reported since thousands of years and its prevalence rate is highest among all anorectal disorders. Piles are unique to human beings. Nearly half of the population generally experience one haemorrhoidal episode at some point during their lives. Arsha (Haemorrhoids) is clinically an engorged condition of haemorrhoidal venous plexus along with abnormally displaced enlarged anal cushion, characterized by inflammed or prolapsed pile mass, bleeding per rectum and some discharge from anus. The term haemorrhoids is popularly used to refer for pathological varicosity of the haemorrhoidal veins due to increased pressure, is usually resulted by straining during defecation, chronic constipation or diarrhoea, pregnancy etc. In modern medical science, many procedures are described for management of haemorrhoids, of which haemorrhoidectomy is commonly preferred by surgeons, but after sometime of excision there is great possibility of reappearance of the disease. But in Ayurveda fourfold management of Arsha has been indicated viz. Bheshaj, Kshar Karma, Agnikarma and Shastra Karma according to chronicity and presentation of the disease. Among these, Bheshaj Chikitsa and Kshar Karma s show wonderful results in management of Arsha. In this review article an attempt has been made to review the studies carried out on Arsha in the department of Shalya Tantra Rishikul Campus, Uttarakhand Ayurved University Haridwar, Uttarakhand.
Empirical calibration of the clinopyroxene garnet magnesium isotope geothermometer and implications
Venue: Contributions to Mineralogy and Petrology

The large equilibrium Mg isotope fractionation between clinopyroxene and garnet observed in eclogites makes it a potential high precision geothermometer, but calibration of this thermometer by natural samples is still limited. Here, we report Mg isotopic compositions of eclogite whole rocks as well as Mg and O isotopic compositions of clinopyroxene and garnet separates from 16 eclogites that formed at different temperatures from the Dabie orogen, China. The whole rock d26Mg values vary from 1.20 to +0.10 %0. Among them, 11 samples display limited d26Mg variations from 0.36 to 0.17 %0, similar to those of their protoliths. The mineral separates exhibit very different d26Mg values, from 0.39 to +0.39 %0 for clinopyroxenes and from 1.94 to 0.81 %0 for garnets. The clinopyroxene garnet Mg isotope fractionation (D26Mgclinopyroxene garnet d26Mgclinopyroxene d26Mggarnet) varies from 1.05 to 2.15 %0. The clinopyroxene garnet O isotope fractionation (D18Oclinopyroxene garnet d18Oclinopyroxene d18Ogarnet) varies from 1.01 to +0.98 %0. Equilibrium Mg isotope fractionation between clinopyroxene and garnet in the investigated samples is selected based on both the d26Mgclinopyroxene versus d26Mggarnet plot and the state of O isotope equilibrium between clinopyroxene and garnet. The equilibrium D26Mgclinopyroxene garnet and corresponding temperature data obtained in this study, together with those available so far in literatures for natural eclogites, are used to calibrate the clinopyroxene garnet Mg isotope thermometer. This yields a function of D26Mgclinopyroxene garnet (0.99 0.06) x 106/T2, where T is temperature in Kelvin. The refined function not only provides the best empirically calibrated clinopyroxene garnet Mg isotope thermometer for precise constraints of temperatures of clinopyroxene and garnet bearing rocks, but also has potential applications in high temperature Mg isotope geochemistry.
Seismic heating signatures in the Japan Trench subduction plate boundary fault zone evidence from a preliminary rock magnetic 'geothermometer'

Frictional heating during earthquake rupture reveals important information on earthquake mechanisms and energy dissipation. The amount of annealing varies widely and is, as yet, poorly constrained. Here we use magnetic susceptibility versus temperature measurements during cycling to increasingly elevated temperatures to constrain the maximum temperature a slip zone has experienced. The case study comprises sheared clay cored from the Japan Trench subduction plate boundary fault zone (decollement) which accommodated the large slip of the 2011 Mw 9.0 Tohoku oki earthquake. The decollement was cored during the Integrated Ocean Drilling Program (IODP) Expedition 343, the Japan Trench Fast Drilling Project (JFAST) Heating signatures with estimated maximum temperatures ranging from ~300 to over 500 degC are determined close to the multiple slip surfaces within the decollement. Since it is impossible to tie a specific slip surface to a certain earthquake, thermal evidence for the cumulative effect of several earthquakes is unveiled. This as yet preliminary rock magnetic 'geothermometer' would be a useful tool to detect seismic heating along faults that experienced medium temperature rise, a range which is difficult to assess with other approaches.
Aspect Based Sentiment Analysis Using a Two Step Neural Network Architecture
Venue: SemWebEval@ESWC

The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed opinions in customer reviews in a fine grained way, valuable opportunities and insights for customers and businesses can be gained. We propose a neural network based system to address the task of Aspect Based Sentiment Analysis to compete in Task 2 of the ESWC 2016 Challenge on Semantic Sentiment Analysis. Our proposed architecture divides the task in two subtasks: aspect term extraction and aspect specific sentiment extraction. This approach is flexible in that it allows to address each subtask independently. As a first step, a recurrent neural network is used to extract aspects from a text by framing the problem as a sequence labeling task. In a second step, a recurrent network processes each extracted aspect with respect to its context and predicts a sentiment label. The system uses pretrained semantic word embedding features which we experimentally enhance with semantic knowledge extracted from WordNet. Further features extracted from SenticNet prove to be beneficial for the extraction of sentiment labels. As the best performing system in its category, our proposed system proves to be an effective approach for the Aspect Based Sentiment Analysis.
NLANGP at SemEval 2016 Task 5: Improving Aspect Based Sentiment Analysis using Neural Network Features
Venue: *SEMEVAL

This paper describes our system submitted to Aspect Based Sentiment Analysis Task 5 of SemEval 2016. Our system consists of two components: binary classifiers trained using single layer feedforward network for aspect category classification (Slot 1) and sequential labeling classifiers for opinion target extraction (Slot 2) Besides extracting a variety of lexicon features, syntactic features, and cluster features, we explore the use of deep learning systems to provide additional neural network features. Our system achieves the best performances on the English datasets, ranking 1st for four evaluations (Slot 1 for both restaurant and laptop domains, Slot 2, and Slot 1 2)
Music Preferences and the Adolescent Brain

Music plays an important part in the transitional period of life for adolescents as they define their personal and social identities and build their preferences for music. Recent neuroscientific research into the adolescent brain has produced developmental models that work to explain the neural reasons behind teenage behavior and development. These neural responses and developments of the brain provide some understanding for many of the social, as well as musical, choices that teenagers make during this period. By examining processes in the adolescent brain, we can begin to understand some reasons behind choices for music preference, which can aid music educators in determining the best ways to present music to teenagers in the music classroom. The purpose of this article is to present a review of previous research in adolescent brain development, music preference, and the application of such research in the musical education of adolescent students.
Variational Auto encoded Deep Gaussian Processes
Venue: ICLR

We develop a scalable deep non parametric generative model by augmenting deep Gaussian processes with a recognition model. Inference is performed in a novel scalable variational framework where the variational posterior distributions are reparametrized through a multilayer perceptron. The key aspect of this reformulation is that it prevents the proliferation of variational parameters which otherwise grow linearly in proportion to the sample size. We derive a new formulation of the variational lower bound that allows us to distribute most of the computation in a way that enables to handle datasets of the size of mainstream deep learning tasks. We show the efficacy of the method on a variety of challenges including deep unsupervised learning and deep Bayesian optimization.
Novel microsatellite markers in Pistacia vera L. and their transferability across the genus Pistacia

This study was undertaken primarily to develop new simple sequence repeat (SSR) markers for pistachio (Pistacia vera L. and related Pistacia species using genomic libraries enriched for dinucleotide (GA)n and trinucleotide (AAG)n microsatellite motifs. A total of 192 clones were sequenced from each library, 135 primer pairs were designed, and 110 generated PCR products. Forty six loci from the GA library and 18 loci from the AAG library produced polymorphic fragments following testing of 12 pistachio cultivars. A total of 264 alleles were generated from the polymorphic loci with an average of 4.13 alleles per locus. Polymorphism information content (PIC) was 0.51, whereas the observed (Ho) and expected heterozygosity (He) values were 0.52 and 0.56, respectively. Transferability of 110 SSR primer pairs were tested in ten wild Pistacia species, and 100 were transferable to at least one of the Pistacia species. Pistacia eurycarpa Yalt. had the highest number of transferable loci, whereas Pistacia texana Swingle and Pistacia lentiscus L. had the lowest one. This is the first study to report candidate SSR markers for P. eurycarpa, Pistacia palaestina and P. texana. It is apparent that SSR markers developed in this study could aid germplasm characterization, construction of genetic linkage maps and comparative mapping in the genus Pistacia.
Strengthening Existing Continuous Non Composite Steel Girder Bridges Using Post Installed Shear Connectors

This study investigated the use of post installed shear connectors for strengthening existing non composite continuous steel girder bridges. The existing bridges considered in this study have strength deficiencies in both the positive and the negative moment regions. The type of post installed shear connector investigated in this study was an adhesive anchor, which is installed from underneath the bridge deck. The strengthening approach involves installing adhesive anchors to increase girder flexural capacity in positive moment regions, and allowing inelastic moment redistribution in negative moment regions. A variety of theoretical, computational, and experimental studies were completed as part of this investigation. The findings of this research indicate that strengthening non composite continuous steel girder bridges with post installed shear connectors and moment redistribution is a feasible and efficient method of extending the useful service life of a bridge. Increases of more than 60% in the load rating of bridges considered in this study were attained by strengthening to a composite ratio of only 30% Design recommendations are provided in this report.
Continental flood basalt weathering as a trigger for Neoproterozoic Snowball Earth

Atmospheric CO2 levels and global climate are regulated on geological timescales by the silicate weathering feedback. However, this thermostat has failed multiple times in Earth's history, most spectacularly during the Cryogenian (c. 720 635 Ma) Snowball Earth episodes. The unique middle Neoproterozoic paleogeography of a rifting, low latitude, supercontinent likely favored a globally cool climate due to the influence of the silicate weathering feedback and planetary albedo. Under these primed conditions, the emplacement and weathering of extensive continental flood basalt provinces may have provided the final trigger for runaway global glaciation. Weathering of continental flood basalts may have also contributed to the characteristically high carbon isotope ratios d 13 C of Neoproterozoic seawater due to their elevated P contents. In order to test these hypotheses, we have compiled new and previously published Neoproterozoic Nd isotope data from mudstones in northern Rodinia (North America, Australia, Svalbard, and South China) and Sr isotope data from carbonate rocks. The Nd isotope data are used to model the mafic detrital input into sedimentary basins in northern Rodinia. The results reveal a dominant contribution from continental flood basalt weathering during the ca. 130 m.y. preceding the onset of Cryogenian glaciation, followed by a precipitous decline afterwards. These data are mirrored by the Sr isotope record, which reflects the importance of chemical weathering of continental flood basalts on solute fluxes to the early middle Neoproterozoic ocean, including a pulse of unradiogenic Sr input into the oceans just prior to the onset of Cyrogenian glaciation. Hence, our new data support the hypotheses that elevated rates of flood basalt weathering contributed to both the high average d 13 C of seawater in the Neoproterozoic and to the initiation of the first (Sturtian) Snowball Earth.
Mechanical behaviour of basalt fibre reinforced concrete

Chopped basalt fibre has recently gained popularity in concrete reinforcing applications due to its environmentally friendly manufacturing process and excellent mechanical properties. The aim of this research is to evaluate the relative merit of two types of basalt fibre (bundle dispersion fibres and minibars) in enhancing the mechanical behaviour of concrete. Concrete specimens were cast with three different quantities of each fibre, then evaluated based on flexural and drop weight impact testing. Interfacial properties were also investigated by scanning electron microscopy. The results indicated both types of fibre increased pre cracking strength, but only minibars enhanced the post cracking behaviour, likely due to protection from the polymer.
Permutation equivariant neural networks applied to dynamics prediction
Venue: ArXiv

The introduction of convolutional layers greatly advanced the performance of neural networks on image tasks due to innately capturing a way of encoding and learning translation invariant operations, matching one of the underlying symmetries of the image domain. In comparison, there are a number of problems in which there are a number of different inputs which are all 'of the same type' multiple particles, multiple agents, multiple stock prices, etc. The corresponding symmetry to this is permutation symmetry, in that the algorithm should not depend on the specific ordering of the input data. We discuss a permutation invariant neural network layer in analogy to convolutional layers, and show the ability of this architecture to learn to predict the motion of a variable number of interacting hard discs in 2D. In the same way that convolutional layers can generalize to different image sizes, the permutation layer we describe generalizes to different numbers of objects.
Regulation of Macrophage Recognition through the Interplay of Nanoparticle Surface Functionality and Protein Corona.
Venue: ACS nano

Using a family of cationic gold nanoparticles (NPs) with similar size and charge, we demonstrate that proper surface engineering can control the nature and identity of protein corona in physiological serum conditions. The protein coronas were highly dependent on the hydrophobicity and arrangement of chemical motifs on NP surface. The NPs were uptaken in macrophages in a corona dependent manner, predominantly through recognition of specific complement proteins in the NP corona. Taken together, this study shows that surface functionality can be used to tune the protein corona formed on NP surface, dictating the interaction of NPs with macrophages.
Protein bio corona: critical issue in immune nanotoxicology
Venue: Archives of Toxicology

With the expansion of the nanomedicine field, the knowledge focusing on the behavior of nanoparticles in the biological milieu has rapidly escalated. Upon introduction to a complex biological system, nanomaterials dynamically interact with all the encountered biomolecules and form the protein "bio corona." The decoration with these surface biomolecules endows nanoparticles with new properties. The present review will address updates of the protein bio corona characteristics as influenced by nanoparticle's physicochemical properties and by the particularities of the encountered biological milieu. Undeniably, bio corona generation influences the efficacy of the nanodrug and guides the actions of innate and adaptive immunity. Exploiting the dynamic process of protein bio corona development in combination with the new engineered horizons of drugs linked to nanoparticles could lead to innovative functional nanotherapies. Therefore, bio medical nanotechnologies should focus on the interactions of nanoparticles with the immune system for both safety and efficacy reasons.