Miracle-dz/UniFAR-FTUs huggingface dataset:
Magma Chamber Growth During Intercaldera Periods: Insights From Thermo‐Mechanical Modeling With Applications to Laguna del Maule, Campi Flegrei, Santorini, and Aso

Crustal magma chambers can grow to be hundreds to thousands of cubic kilometers, potentially feeding catastrophic caldera‐forming eruptions. Smaller volume chambers are expected to erupt frequently and freeze quickly; a major outstanding question is how magma chambers ever grow to the sizes required to sustain the largest eruptions on Earth. We use a thermo‐mechanical model to investigate the primary factors that govern the extrusive:intrusive ratio in a chamber, and how this relates to eruption frequency, eruption size, and long‐term chamber growth. The model consists of three fundamental timescales: the magma injection timescale τin, the cooling timescale τcool, and the timescale for viscous relaxation of the crust τrelax. We estimate these timescales using geologic and geophysical data from four volcanoes (Laguna del Maule, Campi Flegrei, Santorini, and Aso) to compare them with the model. In each of these systems, τin is much shorter than τcool and slightly shorter than τrelax, conditions that in the model are associated with efficient chamber growth and simultaneous eruption. In addition, the model suggests that the magma chambers underlying these volcanoes are growing at rates between ~10−4 and 10−2 km3/year, speeding up over time as the chamber volume increases. We find scaling relationships for eruption frequency and size that suggest that as chambers grow and volatiles exsolve, eruption frequency decreases but eruption size increases. These scaling relationships provide a good match to the eruptive history from the natural systems, suggesting that the relationships can be used to constrain chamber growth rates and volatile saturation state from the eruptive history alone.
P03, the microfocus and nanofocus X-ray scattering (MiNaXS) beamline of the PETRA III storage ring: the microfocus endstation

The MiNaXS (P03) beamline of the new third-generation synchrotron radiation source PETRA III (DESY, Germany) has been designed to perform small-, ultra-small- and wide-angle X-ray scattering in both transmission and grazing-incidence geometries. The high photon flux available at the beamline enables time-resolved investigations of kinetic phenomena with a time resolution below 100 ms. The microfocus endstation started user operation in May 2011.
Line assisted vision applications in structured environments

Recently, line feature has been used as addition feature in various computer vision applications such as 3D reconstruction and pose estimation, due to the lack of point feature in structured environments. In this paper, we review line assisted vision applications in structured environments: image stitching and segmentation. By showing the qualitative improvement of two applications, we indirectly prove the effectiveness of line feature. We also suggest line-based future research direction in structured environments.
One-Shot Learning with a Hierarchical Nonparametric Bayesian Model

We develop a hierarchical Bayesian model that learns categories from single training examples. The model transfers acquired knowledge from previously learned categories to a novel category, in the form of a prior over category means and variances. The model discovers how to group categories into meaningful super-categories that express different priors for new classes. Given a single example of a novel category, we can efficiently infer which super-category the novel category belongs to, and thereby estimate not only the new category's mean but also an appropriate similarity metric based on parameters inherited from the super-category. On MNIST and MSR Cambridge image datasets the model learns useful representations of novel categories based on just a single training example, and performs significantly better than simpler hierarchical Bayesian approaches. It can also discover new categories in a completely unsupervised fashion, given just one or a few examples.
Salt-Sensitive Hypertension and Cardiac Hypertrophy in Transgenic Mice Expressing a Corin Variant Identified in Blacks

Blacks represent a high-risk population for salt-sensitive hypertension and heart disease, but the underlying mechanism remains unclear. Corin is a cardiac protease that regulates blood pressure by activating natriuretic peptides. A corin gene variant (T555I/Q568P) was identified in blacks with hypertension and cardiac hypertrophy. In this study, we tested the hypothesis that the corin variant contributes to the hypertensive and cardiac hypertrophic phenotype in vivo. Transgenic mice were generated to express wild-type (WT) or T555I/Q568P variant corin in the heart under the control of &agr;-myosin heavy chain promoter. The mice were crossed into a corin knockout (KO) background to create KO/TgWT and KO/TgV mice that expressed WT or variant corin, respectively, in the heart. Functional studies showed that KO/TgV mice had significantly higher levels of proatrial natriuretic peptide in the heart compared with that in control KO/TgWT mice, indicating that the corin variant was defective in processing natriuretic peptides in vivo. By radiotelemetry, corin KO/TgV mice were found to have hypertension that was sensitive to dietary salt loading. The mice also developed cardiac hypertrophy at 12 to 14 months of age when fed a normal salt diet or at a younger age when fed a high-salt diet. The phenotype of salt-sensitive hypertension and cardiac hypertrophy in KO/TgV mice closely resembles the pathological findings in blacks who carry the corin variant. The results indicate that corin defects may represent an important mechanism in salt-sensitive hypertension and cardiac hypertrophy in blacks.
Facilitating Multi-Lingual Sense Annotation: Human Mediated Lemmatizer

Sense marked corpora is essential for supervised word sense disambiguation (WSD). The marked sense ids come from wordnets. However, words in corpora appear in morphed forms, while wordnets store lemma. This situation calls for accurate lemmatizers. The lemma is the gateway to the wordnet. However, the problem is that for many languages, lemmatizers do not exist, and this problem is not easy to solve, since rule based lemmatizers take time and require highly skilled linguists.Satistical stemmers on the other hand do not return legitimate lemma. We present here a novel scheme for creating accurate lemmatizers quickly. These lemmatizers are human mediated. The key idea is that a trie is created out of the vocabulary of the language. The lemmatizing process consists in navigating the trie, trying to find a match between the input word and an entry in the trie. At the point of first mismatch, the yield of the subtree rooted at the partially matched node is output as the list of possible lemma. If the correct lemma does not appear in the listas noted by a human lexicographerbacktracking is initiated. This can output more possibilities. A ranking function filters and orders the output list of lemma. We have evaluated the performance of this human mediated lemmatizer for eighteen Indian Languages and five European languages. We have compared accuracy figures against well known lemmatizers/stemmers like Morpha, Morfessor and Snowball stemmers, and observed superior performance in all cases. Our work shows a way of speedily creating human assisted accurate lemmatizers, thereby removing a difficult roadblock in many NLP tasks, e.g., sense annotation.
Combined test of serum CgA and NSE improved the power of prognosis prediction of NF-pNETs

Purpose Chromogranin A (CgA) and neuron-specific enolase (NSE) are important markers for neuroendocrine tumors; however, the clinical value of combining these markers has not been well studied. In this study, we investigated the utility of each marker individually and in combination for patients with nonfunctional pancreatic neuroendocrine tumors (NF-pNETs). Patients and Methods In this study, NF-pNET patients and controls were recruited from December 2011 to March 2016; 784 serum samples from peripheral vein were collected. The clinical characteristics and biomarker values of all the individuals were recorded and analyzed. Tumor burdens were calculated by CT/MRI scan. Receiver-operating characteristic curves were constructed to assess the diagnostic predictive values; sensitivity and specificity were calculated to determine the cut-off value. Therapeutic responses reflected on the changes of the biomarkers’ concentration were assessed by the RECIST criterion. Clinical relations between the prognosis and the biomarker values were also analyzed. Statistical significance was defined as P value less than 0.05. Results Among the 167 NF-pNETs patients, 82 were males (49.1%) and the mean age was 50.0 (17.4). The mean CgA values of G1, G2 and G3 NF-pNENs were 75, 121 and 134 μg/L (P < 0.05), respectively. In NF-pNETs, CgA correlated with the WHO tumor grade (WHO G1 vs G2, P < 0.05); the linear regression relationships were found between the tumor burdens (both in pancreas and liver) and CgA concentration (P < 0.001); changes in CgA and NSE concentrations also reflect treatment response (P < 0.001). Conclusion CgA and NSE are important diagnostic and follow-up markers in patients with NF-pNETs. The combined monitoring of CgA and NSE possesses more accuracy than individual values of CgA and NSE at predicting prognosis and disease progression.
In vitro 1H NMR studies of RD human cell infection with echovirus 11

The effects of echovirus 11 infection on RD human cell line (derived from rhabdomyosarcoma) were studied using 1H NMR spectroscopy and optical microscopy. Both uninfected and infected cells consumed glucose and produced lactate, acetate and formate as extracellular metabolites. In infected whole cells, phosphocholine and uridine‐sugar were observed in addition to the metabolites observed in uninfected cells. Water‐soluble intracellular metabolites of infected cells showed glutamine, phosphocholine and glycine which were not observed in uninfected cells. Cellular metabolites except lipid components gradually decreased and disappeared during 24–48 h of viral infection. The quantity of lipid components in infected cells was comparable with that in uninfected cells, indicating that echovirus 11 does not utilize cell lipid molecules. Unlike optical microscopy, 1H NMR spectroscopy identified early stages of infection through metabolic changes. These results may have potential implications in probing virus–cell interactions using NMR‐based metabolomics. Copyright © 2006 John Wiley & Sons, Ltd.
Neural Stem Cells in Models of Chronic Spinal Cord Injury

Recently, we reported that neural stem cells (NSCs) grafted into rat T3 complete transection sites at subacute stages of spinal cord injury (SCI) formed functional relays between transected segments and improved motor functions. In the current study, we explored the therapeutic effects of NSC grafts at chronic stages of SCI by delaying grafts until 6 months after injury. Grafted cells successfully filled lesion cavities with neurons and glia, but host derived collagenous tissue separated the entire graft, resulting in disruption of neuronal relays. Compared to subacute grafts, delayed grafts showed similar neuron densities, but graft sizes were significantly smaller. Moreover, grafted neurons extended numerous axons into the chronically injured spinal cord for long distances: projections rostrally to C4 and caudally to T12. In addition, host raphespinal axons regenerated into delayed grafts as robustly as subacute grafts. Immunoelectron microscopic analysis confirmed new synapse formations between host and grafted neurons. Interestingly, the inhibitory scar that surrounds chronic lesion sites was significantly attenuated through delayed NSC grafts, suggesting a possible mechanism underlying great axonal growth from grafted and host neurons in chronic SCI. Despite of these findings, there was a lack of functional improvement, which is at least due to the presence of collagenous tissue separating the graft. Collectively, these findings indicate that NSC grafts have great potential to form functional relays at chronic stages of SCI. To achieve functional recovery, improvements in grafting methods and/or additional treatments targeting inhibitory mechanisms intrinsic to the chronically injured state will be required
Compensation for Changing Motor Uncertainty

When movement outcome differs consistently from the intended movement, errors are used to correct subsequent movements (e.g., adaptation to displacing prisms or force fields) by updating an internal model of motor and/or sensory systems. Here, we examine changes to an internal model of the motor system under changes in the variance structure of movement errors lacking an overall bias. We introduced a horizontal visuomotor perturbation to change the statistical distribution of movement errors anisotropically, while monetary gains/losses were awarded based on movement outcomes. We derive predictions for simulated movement planners, each differing in its internal model of the motor system. We find that humans optimally respond to the overall change in error magnitude, but ignore the anisotropy of the error distribution. Through comparison with simulated movement planners, we found that aimpoints corresponded quantitatively to an ideal movement planner that updates a strictly isotropic (circular) internal model of the error distribution. Aimpoints were planned in a manner that ignored the direction-dependence of error magnitudes, despite the continuous availability of unambiguous information regarding the anisotropic distribution of actual motor errors.
Tissue-specific regulation of inflammation by macrophage migration inhibitory factor and glucocorticoids in fructose-fed Wistar rats

High fructose consumption is commonly associated with insulin resistance, disturbed glucose homeostasis and low-grade inflammation. Increased glucocorticoid production within adipose tissue has been implicated in the pathogenesis of fructose-induced metabolic syndrome. Immunosuppressive actions of glucocorticoids can be counter-regulated by macrophage migration inhibitory factor (MIF), which is recognised as a key molecule in metabolic inflammation. In the present study, we hypothesised that coordinated action of glucocorticoids and MIF can mediate the effects of a high-fructose diet on adipose tissue and liver inflammation. We examined the effects of long-term consumption of a 10 % fructose solution on corticosterone (CORT) and MIF levels in rat blood plasma, liver and adipose tissue, as well as MIF and TNF-α mRNA expression and NF-κB activation in the same tissues. The high-fructose diet led to an increase in both CORT and MIF in the adipose tissue, and a highly significant positive correlation between their levels was observed. The attenuated NF-κB activation and unaltered TNF-α mRNA expression noticed in the adipose tissue could be interpreted as an outcome of the opposing actions of CORT and MIF. In contrast to adipose tissue, inflammation in the liver was characterised by NF-κB activation, an increased TNF-α mRNA level and unchanged levels of MIF protein, MIF mRNA and CORT. Overall, these findings suggest that a high-fructose diet differently affects the levels of glucocorticoids and MIF in the adipose tissue and liver, implicating that fructose over-consumption has tissue-specific effects on regulation of metabolic inflammation.
Web-Based Support of Crop Selection for Climate Adaptation

Farmers must now consider climate adaptation amongst other variables when they select crops for the coming year. A changing climate means traditional crop choices may not perform well. Yet, it may be difficult to trust recommendations about new crop choices provided without extensive local knowledge. This paper describes the design and implementation of a prototype tool to support Canadian farmers in their crop selections. However, authoritative data about growing conditions that maximize crop performance has been difficult to assemble. Therefore, we propose an extension to the prototype system that would allow farmers to submit reports of crop performance along with data that describes their growing conditions. With many farmers contributing these experience reports, the data in these reports could be mined to provide localized information about the performance of different crops and the conditions which best support each.
Relative Deprivation and Sickness Absence in Sweden

Background: A high prevalence of sickness absence in many countries, at a substantial societal cost, underlines the importance to understand its determining mechanisms. This study focuses on the link between relative deprivation and the probability of sickness absence. Methods: 184,000 men and women in Sweden were followed between 1982 and 2001. The sample consists of working individuals between the ages of 19 and 65. The outcome is defined as experiencing more than 14 days of sickness absence during a year. Based on the complete Swedish population, an individual’s degree of relative deprivation is measured through income compared to individuals of the same age, sex, educational level and type. In accounting for the possibility that sickness absence and socioeconomic status are determined by common factors, discrete-time duration models were estimated, accounting for unobserved heterogeneity through random effects. Results: The results confirm that the failure to account for the dynamics of the individual’s career biases the influence from socioeconomic characteristics. Results consistently suggest a major influence from relative deprivation, with a consistently lower risk of sickness absence among the highly educated. Conclusions: Altering individual’s health behavior through education appears more efficient in reducing the reliance on sickness absence, rather than redistributive policies.
Predicting Transportation Carbon Emission with Urban Big Data

Transportation carbon emission is a significant contributor to the increase of greenhouse gases, which directly threatens the change of climate and human health. Under the pressure of the environment, it is very important to master the information of transportation carbon emission in real time. In the traditional way, we get the information of the transportation carbon emission by calculating the combustion of fossil fuel in the transportation sector. However, it is very difficult to obtain the real-time and accurate fossil fuel combustion in the transportation field. In this paper, we predict the real-time and fine-grained transportation carbon emission information in the whole city, based on the spatio-temporal datasets we observed in the city, that is taxi GPS data, transportation carbon emission data, road networks, points of interests (<italic>POI</italic>s), and meteorological data. We propose a three-layer perceptron neural network (3-<inline-formula><tex-math notation="LaTeX">$layerPNN$</tex-math><alternatives> <inline-graphic xlink:href="dong-ieq1-2728805.gif"/></alternatives></inline-formula>) to learn the characteristics of collected data and infer the transportation carbon emission. We evaluate our method with extensive experiments based on five real data sources obtained in Zhuhai, China. The results show that our method has advantages over the well-known three machine learning methods (Gaussian Naive Bayes, Linear Regression, and Logistic Regression) and two deep learning methods (Stacked Denoising Autoencoder and Deep Belief Networks).
Automated Manipulation of Biological Cells Using Gripper Formations Controlled By Optical Tweezers

The capability of noninvasive and precise micromanipulation of sensitive, living cells is necessary for understanding their underlying biological processes. Optical tweezers (OT) is an effective tool that uses highly focused laser beams for accurate manipulation of cells and dielectric beads at microscale. However, direct exposure of the laser beams on the cells can negatively influence their behavior or even cause a photo-damage. In this paper, we introduce a control and planning approach for automated, indirect manipulation of cells using silica beads arranged into gripper formations. The developed approach employs path planning and feedback control for efficient, collision-free transport of a cell between two specified locations. The planning component of the approach computes a path that explicitly respects the nonholonomic constraints of the gripper formations. The feedback control component ensures stable tracking of the path by manipulating the cell using a set of predefined maneuvers. We demonstrate the effectiveness of the approach by transporting a yeast cell using four different types of gripper formations along collision-free paths on our OT setup. We analyzed the performance of the proposed gripper formations with respect to their maximum transport speeds and the laser intensity experienced by the cell that depends on the laser power used.
Achilles tendinopathy: some aspects of basic science and clinical management

Achilles tendinopathy is prevalent and potentially incapacitating in athletes involved in running sports. It is a degenerative, not an inflammatory, condition. Most patients respond to conservative measures if the condition is recognised early. Surgery usually involves removal of adhesions and degenerated areas and decompression of the tendon by tenotomy or measures that influence the local circulation.
Combining Theory and Implementation : A Proposed Course on Distributed Computing

Universities typically offer graduate-level courses in computer science that focus either on implementing software systems or on the theoretical foundations of these systems. In such an environment students who enjoy programming select elective courses that focus on software implementation. Likewise, students who enjoy theoretical topics select elective courses that focus on foundational topics. The result is a set of graduating students who are either good programmers, but lack the theoretical foundations supporting the programming concepts, or good theoreticians who lack the ability to implement software systems well. We believe computer science graduates should be proficient at both theory and implementation. One of the graduate-level theory courses offered at Clemson University is The Foundations of Distributed Computing (CpSc 873). We outline a new syllabus based on this course where not only are the theoretical foundations taught, but also a concrete implementation of the algorithms developed.
Vertical land motion and sea level change in Macaronesia

S U M M A R Y This study addresses long-term sea level variability in Macaronesia from a holistic perspective using all available instrumental records in the region, including a dense network of GPS continuous stations, tide gauges and satellite observations. A detailed assessment of vertical movement from GPS time series underlines the influence of the complex volcano-tectonic setting of the Macaronesian islands in local uplift/subsidence. Relative sea level for the region is spatially highly variable, ranging from −1.1 to 5.1 mm yr−1. Absolute sea level from satellite altimetry exhibits consistent trends in the Macaronesia, with a mean value of 3.0 ± 0.5 mm yr−1. Typically, sea level trends from tide gauge records corrected for vertical movement using the estimates from GPS time series are lower than uncorrected estimates. The agreement between satellite altimetry and tide gauge trends corrected for vertical land varies substantially from island to island. Trends derived from the combination of GPS and tide gauge observations differ by less than 1 mm yr−1 with respect to absolute sea level trends from satellite altimetry for 56 per cent of the stations, despite the heterogeneity in length of both GPS and tide gauge series, and the influence of volcanic-tectonic processes affecting the position of some GPS stations.