Miracle-dz/UniFAR-FTUs huggingface dataset:
Relatively small earthquakes of Javakheti Highland as the precursors of large earthquakes occuring in the Caucasus

Javakheti Highland is one of the most seismic active regions of the Caucasus. The majority of earthquakes observed throughout the region occur within this small area ( f = 40.8° – 41.8° ; l = 43.3° – 44.3°). One can expect that exclusive seismic activity of Javakheti Highland testifies to global geophysical processes which take place throughout the Caucasus region. Based on the above-mentioned, of interest was to study variation with time of the number of earthquakes occurring in Javakheti region. We analysed some 695 relatively small earthquakes (2.5 M > 6.0 of the region which occurred in the same period. It was found that each large earthquake of the Caucasus is anticipated by clear precursor in a form of an anomalous change in the number of relatively small earthquakes in Javakheti Highland.
Derivation Of Spreading Parameters Of Oil At Sea For Oil Spill Modeling

ABSTRACT Oil spill models are commonly used to simulate the large-scale (tens to hundreds of kilometers) transport of oil spills in the oceans. The values of the spreading parameters of these models are obtained empirically by fitting to observed slicks, thus they do not account explicitly for the effects of waves. In addition, there is little success in using these values to predict the spread at smaller scales (tens of meters to a few kilometers). This works attempts to better understand the physics of oil movement in the ocean by focusing on the small-scale mechanisms. The investigation also leads to evaluation of small-scale spreading parameters. The Random Walk Method is used in a Monte Carlo simulation framework to track the transport of oil due to the effects of waves, buoyancy, and turbulent diffusion. The small-scale spreading parameters are then calculated using the Method of Moments. Our results indicated that the approach for using a spreading coefficient becomes after a time equal to about 30.
Herding the Crowd: Automated Planning for Crowdsourced Planning

An important application of human computation is crowdsourced planning and scheduling. In this paper, we present an architecture for an automated system that can significantly improve the effectiveness of the crowd in collaborating and coming up with effective plans by herding it. We define two main problems that have to be solved when designing such automated crowd-herding systems: interpretation, and steering; and discuss how automated planning techniques can be used to solve these problems.
The Plant Immunity Regulating F-Box Protein CPR1 Supports Plastid Function in Absence of Pathogens

The redox imbalanced 6 mutant (rimb6) of Arabidopsis thaliana was isolated in a genetic screening approach for mutants with defects in chloroplast-to-nucleus redox signaling. It has an atypically low activation status of the 2-Cys peroxiredoxin-A promoter in the seedling stage. rimb6 shows wildtype-like germination, seedling development and greening, but slower growth and reduced biomass in the rosette stage. Mapping of the casual mutation revealed that rimb6 carries a single nucleotide polymorphism in the gene encoding CONSTITUTIVE EXPRESSER OF PATHOGENESIS RELATED (PR) GENES 1, CPR1 (At4g12560), leading to a premature stop codon. CPR1 is known as a repressor of pathogen signaling and regulator of microtubule organization. Allelism of rimb6 and cpr1 revealed a function of CPR1 in chloroplast stress protection. Expression studies in pathogen signaling mutants demonstrated that CPR1-mediated activation of genes for photosynthesis and chloroplast antioxidant protection is, in contrast to activation of pathogen responses, regulated independently from PAD4-controlled salicylic acid (SA) accumulation. We conclude that the support of plastid function is a basic, SA-independent function of CPR1.
Mesenchymal stem cells and platelet-rich plasma enhance bone formation in sinus grafting: a histomorphometric study in minipigs.

OBJECTIVES Autologous, allogenic, and alloplastic materials for sinus augmentation have specific drawbacks, which has stimulated an ongoing search for new materials and tissue-engineering constructs. We investigated whether mesenchymal stem cells (MSCs) and platelet-rich plasma (PRP) seeded on a fluorohydroxyapatite (FH) scaffold can improve bone formation and bone-to-implant contact (BIC) in maxillary sinus grafting. MATERIAL AND METHODS Bilateral sinus augmentation procedures were performed in eight minipigs. MSCs, PRP, and FH scaffold (test site) or FH alone (control site) were grafted in each maxillary sinus. Distal to the osteotomy, one dental implant per sinus was placed in the grafting material through the facial sinus wall. The animals were killed 3 months after grafting, and block sections of the implant sites were harvested and prepared for histomorphometric analysis. RESULTS After 12 weeks, a significant increase in bone formation occurred in the test sites compared with the control sites (42.51%versus 18.98%; p=0.001). In addition, BIC was significantly greater in the test sites compared with the control sites in the regenerated area (23.71%versus 6.63%; p=0.028). CONCLUSIONS These findings show that sinus augmentation with MSCs-PRP, combined with FH may enhance bone formation and osseointegration of dental implants compared with FH alone in minipigs.
A level-set method for modeling the evolution of glacier geometry

Abstract A level-set method is proposed for modeling the evolution of a glacier surface subject to a prescribed mass balance. This leads to a simple and versatile approach for computing the evolution of glaciers: the description of vertical fronts and overriding phenomena presents no difficulties, topological changes are handled naturally and steady-state solutions can be calculated without integration over time. A numerical algorithm is put forth as a means of solving the proposed model of glacier surface evolution. It is evaluated by comparing different numerical solutions of the model with analytical and published numerical solutions. The level-set method appears to be a reliable approach for dealing with different glaciological problems.
Modelling surface runoff to evaluate the effects of wildfires in multiple semi‐arid, shrubland‐dominated catchments

Wildfires change the infiltration properties of soil, reduce the amount of interception and result in increased runoff. A wildfire at Northeast Attica, Central Greece, in August 2009, destroyed approximately one third of a study area consisting of a mixture of shrublands, pastures and pines. The present study simultaneously models multiple semi‐arid, shrubland‐dominated Mediterranean catchments and assesses the hydrological response (mean annual and monthly runoff and runoff coefficients) during the first few years following wildfires. A physically based, hydrological model (MIKE SHE) was chosen. Calibration and validation results of mean monthly discharge presented very good agreement with the observed data for the pre‐wildfire and post‐wildfire period for two subcatchments (Nash–Sutcliffe Efficiency coefficient of 79.7%). The model was then used to assess the pre‐wildfire and post‐wildfire runoff responses for each of seven catchments in the study area. Mean annual surface runoff increased for the first year and after the second year following the wildfires increased by 112% and 166%, respectively. These values are within the range observed in similar cases of monitored sites. This modelling approach may provide a way of prioritizing catchment selection with respect to post‐fire remediation activities. Additionally, this modelling assessment methodology would be valuable to other semi‐arid areas because it provides an important means for comprehensively assessing post‐wildfire response over large regions and therefore attempts to address some of the scaled issues in the specific literature field of research. Copyright © 2015 John Wiley & Sons, Ltd.
Land-use/land-cover and water quality in the Cape Fear River Basin, North Carolina: spatial-temporal relationships

As North Carolina experiences population growth and related development, it will become increasingly important to understand how different land-use/land-cover (LULC) types shape the geography of water quality. This dissertation explores the relationships that exists between water quality and land types across the Cape Fear River Basin, North Carolina. Key water quality parameters including fecal coliform, dissolved oxygen (DO), ammonium nitrogen (NH3-N), phosphorus (P), and nitrate-nitrite nitrogen (NO2-NO3), and LULC types were quantified and spatially illustrated to understand how relationships varied across the river basin from 2001 to 2006. Regression models were developed to statistically link water quality parameters with LULC types across the river basin and within each of the physiographic regions. Results indicate that this diverse landscape contributes varying amounts of pollution to surface waters within the basin. Specific findings include that although there was little change in land types during the study period, there were statistically significant relationships between land types and surface water quality. Although regression models illustrate that each of the dependent variables contributed some level of pollution to surface water systems in the basin, fecal coliform, and DO concentrations, in particular, were impacted by key land types including wetlands, mixed forest, and exurban development. In addition, there were regional differences among the three physiographic regions and water quality parameters. The primary findings suggest that transitional land-uses (i.e. mixed forest and exurban development) that surround urban cores can play a key role in shaping the geography of water quality across the river basin. As a result, resource agencies and decision makers alike should consider how land-use policies and activities related to transitional landscapes may adversely impact surface water quality across river basins.
Yet another spinocerebellar ataxia

The world of spinocerebellar ataxias (SCA) is increasingly confusing to the uninitiated and had already made an expert in the field entitle his editorial “Yet another ataxia: will it ever end? ” 6 years ago.1 With now 29 SCA genes or loci identified, things are looking even more complicated today.2 Recognized mechanisms leading to spinocerebellar degeneration include polyglutamine expansions (SCA1, 2, 3, 6, 7, 17) and intronic expansions (SCA10) as well conventional mutations in genes encoding cytoskeletal proteins (βIII spectrin, SCA5), ion channels (voltage gated potassium channel Kv3.3, SCA13), protein kinases (protein kinase C gamma, SCA14), fibroblast growth factors (FGF14, SCA27), and a tau tubulin kinase (tau tubulin kinase 2, SCA11). 2,3 The recent discovery of the underlying genetic defect for SCA15 and the article by Hara and colleagues, published in this issue of Neurology ®, which describes further mutations in SCA15 families, are nevertheless of considerable interest.4,5 Affected members from SCA15 families typically present with fairly pure ataxia which is only very slowly progressive.6 The illness may already manifest itself …
Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data

We introduce a low-complexity method for acquiring fine-grained classes of named entities from the Web. The method exploits the large amounts of textual data available on the Web, while avoiding the use of any expensive text processing techniques or tools. The quality of the extracted classes is encouraging with respect to both the precision of the sets of named entities acquired within various classes, and the labels assigned to the sets of named entities.
Aspect Based Sentiment Analysis to Extract Meticulous Opinion Value

Opinion Mining and Sentiment Analysis is a process of identifying opinions in large unstructured/structured data and then analysing polarity of those opinions. Opinion mining and sentiment analysis have found vast application in analysing online ratings, analysing product based reviews, e-governance, and managing hostile content over the internet. This paper proposes an algorithm to implement aspect level sentiment analysis. The algorithm takes input from the remarks submitted by various teachers of a student. An aspect tree is formed which has various levels and weights are assigned to each branch to identify level of aspect. Aspect value is calculated by the algorithm by means of the proposed aspect tree. Dictionary based method is implemented to evaluate the polarity of the remark. The algorithm returns the aspect value clubbed with opinion value and sentiment value which helps in concluding the summarized value of remark.
Changes in the global carbon cycle occurred as two episodes during the Permian–Triassic crisis

Coeval records of ocean, atmosphere, and terrestrial change are crucial to understanding the pattern and causes of global mass extinction across the Permian-Triassic boundary (PTB). However, relationships among changes in different settings remain largely unclear, primarily due to the challenges associated with the correlation among disparate records. Here we compare marine carbon isotopic records with marine and terrestrial environmental and biotic events recorded in sediments from the Meishan PTB section of south China. Time-scaled carbonate carbon isotopes exhibit two gradual major shifts across the PTB at Meishan, and these are duplicable elsewhere around the Tethys Ocean. The two shifts are associated with two episodes of enhanced terrestrial weathering indicated by an increased abundance of 13 C-enriched moretanes relative to hopanes and an elevated abundance of black carbon fragments. Key marine events previously reported for the PTB, including photic zone euxinia, faunal mass extinction, and cyanobacterial expansion, also occur as two episodes, coinciding with both of the progressive shifts to negative δ 13 C values and enhanced weathering. The temporal sequence of the duplicable events suggests that the biotic crisis was a consequence of prolonged and episodic changes in the marine and continental systems, and argues against an extraterrestrial impact as the main cause.
Nonparanormal Belief Propagation (NPNBP)

The empirical success of the belief propagation approximate inference algorithm has inspired numerous theoretical and algorithmic advances. Yet, for continuous non-Gaussian domains performing belief propagation remains a challenging task: recent innovations such as nonparametric or kernel belief propagation, while useful, come with a substantial computational cost and offer little theoretical guarantees, even for tree structured models. In this work we present Nonparanormal BP for performing efficient inference on distributions parameterized by a Gaussian copulas network and any univariate marginals. For tree structured networks, our approach is guaranteed to be exact for this powerful class of non-Gaussian models. Importantly, the method is as efficient as standard Gaussian BP, and its convergence properties do not depend on the complexity of the univariate marginals, even when a nonparametric representation is used.
A Generic Framework for Efficient 2-D and 3-D Facial Expression Analogy

Facial expression analogy provides computer animation professionals with a tool to map expressions of an arbitrary source face onto an arbitrary target face. In the recent past, several algorithms have been presented in the literature that aim at putting the expression analogy paradigm into practice. Some of these methods exclusively handle expression mapping between 3-D face models, while others enable the transfer of expressions between images of faces only. None of them, however, represents a more general framework that can be applied to either of these two face representations. In this paper, we describe a novel generic method for analogy-based facial animation that employs the same efficient framework to transfer facial expressions between arbitrary 3-D face models, as well as between images of performer's faces. We propose a novel geometry encoding for triangle meshes, vertex-tent-coordinates, that enables us to formulate expression transfer in the 2-D and the 3-D case as a solution to a simple system of linear equations. Our experiments show that our method outperforms many previous analogy-based animation approaches in terms of achieved animation quality, computation time and generality.
Aquatrichlorido(1-cyanomethyl-4-aza-1-azoniabicyclo[2.2.2]octane-κN 4)copper(II) monohydrate

The asymmetric unit of the title compound, [CuCl3(C8H14N3)(H2O)]·H2O, comprises a neutral complex and a molecule of free water. The complex contains coordinated CuII ions, with Cu—Cl distances ranging from 2.3471 (8) to 2.4011 (8) Å, and with Cu—N and Cu—O distances of 2.0775 (19) and 2.0048 (18) Å, respectively. The resulting coordination polyhedron is a trigonal bipyramid with the Cl atoms in the equatorial plane. In the crystal, O—H⋯Cl and O—H⋯O hydrogen bonds link the molecules into a three-dimensional structure.
Effects of dietary tryptophan and phenylalanine–tyrosine depletion on phasic alertness in healthy adults – A pilot study

Background The synthesis of the neurotransmitters serotonin (5-HT) and dopamine (DA) in the brain can be directly altered by dietary manipulation of their relevant precursor amino acids (AA). There is evidence that altered serotonergic and dopaminergic neurotransmission are both associated with impaired attentional control. Specifically, phasic alertness is one specific aspect of attention that has been linked to changes in 5-HT and DA availability in different neurocircuitries related to attentional processes. The present study investigated the impact of short-term reductions in central nervous system 5-HT and DA synthesis, which was achieved by dietary depletion of the relevant precursor AA, on phasic alertness in healthy adult volunteers; body weight–adapted dietary tryptophan and phenylalanine–tyrosine depletion (PTD) techniques were used. Methods The study employed a double-blind between-subject design. Fifty healthy male and female subjects were allocated to three groups in a randomized and counterbalanced manner and received three different dietary challenge conditions: acute tryptophan depletion (ATD, for the depletion of 5-HT; N=16), PTD (for the depletion of DA; N=17), and a balanced AA load (BAL; N=17), which served as a control condition. Three hours after challenge intake (ATD/PTD/BAL), phasic alertness was assessed using a standardized test battery for attentional performance (TAP). Blood samples for AA level analyses were obtained at baseline and 360 min after the challenge intake. Results Overall, there were no significant differences in phasic alertness for the different challenge conditions. Regarding PTD administration, a positive correlation between the reaction times and the DA-related depletion magnitude was detected via the lower plasma tyrosine levels and the slow reaction times of the first run of the task. In contrast, higher tryptophan concentrations were associated with slower reaction times in the fourth run of the task in the same challenge group. Conclusion The present study is the first to demonstrate preliminary data that support an association between decreased central nervous system DA synthesis, which was achieved by dietary depletion strategies, and slower reaction times in specific runs of a task designed to assess phasic alertness in healthy adult volunteers; these findings are consistent with previous evidence that links phasic alertness with dopaminergic neurotransmission. A lack of significant differences between the three groups could be due to compensatory mechanisms and the limited sample size, as well as the dietary challenge procedures administered to healthy participants and the strict exclusion criteria used. The potential underlying neurochemical processes related to phasic alertness should be the subject of further investigations.
Pharmacokinetic–Pharmacodynamic Analysis of the Static Allodynia Response to Pregabalin and Sildenafil in a Rat Model of Neuropathic Pain

The objective of this study was to develop a pharmacokinetic–pharmacodynamic (PK-PD) model of the static allodynia response to pregabalin with and without sildenafil in a chronic constriction injury model of neuropathic pain. Six treatment groups were evaluated every 30 min for 6 h. Rats were treated with either 1) a saline infusion; 2) a 2-h pregabalin infusion at 4 mg·kg−1·h−1; 3) a 2-h pregabalin infusion at 10 mg·kg−1·h−1; 4) a 2.2-mg loading dose + 12 mg·kg−1·min−1 infusion of sildenafil; 5) a 2-h pregabalin infusion at 1.6 mg·kg−1·h−1 with sildenafil; and 6) a 2-h infusion of pregabalin at 4 mg·kg−1·h with sildenafil. The static allodynia endpoint was modeled by using three population PD approaches: 1) the behavior of the injured paw using a three-category ordinal logistic regression model; 2) paw withdrawal threshold (PWT) (g) between the injured and uninjured paw using the Hill equation with a baseline function; and 3) the baseline normalized difference in PWT between the injured and uninjured paw. The categorical model showed a significant shift in the concentration–response relationship of pregabalin to lower concentrations with concomitant sildenafil. Likewise, the continuous PK-PD models demonstrated a reduction in the EC50 of pregabalin necessary for PD response in the presence of sildenafil. The difference-transformed PD model resulted in a 54.4% (42.3–66.9%) decrease in EC50, whereas the percentage-transformed PD model demonstrated a 53.5% (42.7–64.3%) shift. It is concluded from these studies that there is a synergistic PD interaction between pregabalin and sildenafil.
Declarative Machine Learning - A Classification of Basic Properties and Types

Declarative machine learning (ML) aims at the high-level specification of ML tasks or algorithms, and automatic generation of optimized execution plans from these specifications. The fundamental goal is to simplify the usage and/or development of ML algorithms, which is especially important in the context of large-scale computations. However, ML systems at different abstraction levels have emerged over time and accordingly there has been a controversy about the meaning of this general definition of declarative ML. Specification alternatives range from ML algorithms expressed in domain-specific languages (DSLs) with optimization for performance, to ML task (learning problem) specifications with optimization for performance and accuracy. We argue that these different types of declarative ML complement each other as they address different users (data scientists and end users). This paper makes an attempt to create a taxonomy for declarative ML, including a definition of essential basic properties and types of declarative ML. Along the way, we provide insights into implications of these properties. We also use this taxonomy to classify existing systems. Finally, we draw conclusions on defining appropriate benchmarks and specification languages for declarative ML.
Early Paleozoic terranes of New Zealand

Abstract Lower Paleozoic rocks of New Zealand comprise two major assemblages each with their own distinct sedimentary tectonic, metamorphic and igneous history; they thus represent two distinct tectono-stratigraphic terranes. In Nelson-Westland, the western, or Buller, terrane consists of the Western Sedimentary Belt, together with Ordovician paragneiss at Charleston and in Victoria Range. The sedimentary sequence, ranging in age from basal to Upper Ordovician, comprises continentderived quartz-rich turbidites with black shales inferred to have been deposited in submarine fans and slope basins. The eastern, Takaka terrane (Central and Eastern Sedimentary Belts) is much more varied in lithofacies, composition and age (Cambrian to Silurian) and itself comprises several tectonic, probably thrust, slices. Volcanics, volcaniclastics, siliceous and calcareous siltstone, conglomerate and turbidites dominate the Cambrian part of the sequence and indicate proximity to a Cambrian island arc. The oldest sediments ar.