Miracle-dz/UniFAR-FTUs huggingface dataset:
Arctic and boreal ecosystems of western North America as components of the climate system

Synthesis of results from several Arctic and boreal research programmes provides evidence for the strong role of high‐latitude ecosystems in the climate system. Average surface air temperature has increased 0.3 °C per decade during the twentieth century in the western North American Arctic and boreal forest zones. Precipitation has also increased, but changes in soil moisture are uncertain. Disturbance rates have increased in the boreal forest; for example, there has been a doubling of the area burned in North America in the past 20 years. The disturbance regime in tundra may not have changed. Tundra has a 3–6‐fold higher winter albedo than boreal forest, but summer albedo and energy partitioning differ more strongly among ecosystems within either tundra or boreal forest than between these two biomes. This indicates a need to improve our understanding of vegetation dynamics within, as well as between, biomes. If regional surface warming were to continue, changes in albedo and energy absorption would likely act as a positive feedback to regional warming due to earlier melting of snow and, over the long term, the northward movement of treeline. Surface drying and a change in dominance from mosses to vascular plants would also enhance sensible heat flux and regional warming in tundra. In the boreal forest of western North America, deciduous forests have twice the albedo of conifer forests in both winter and summer, 50–80% higher evapotranspiration, and therefore only 30–50% of the sensible heat flux of conifers in summer. Therefore, a warming‐induced increase in fire frequency that increased the proportion of deciduous forests in the landscape, would act as a negative feedback to regional warming.
Folding pathway of a lattice model for protein folding

The folding of a protein-like heteropolymer is studied by direct simulation of a lattice model that folds rapidly to a well-defined “native” structure. The details of each molecular folding event depend on the random initial conformation as well as the random thermal fluctuations of the polymer. By analysing the statistical properties of hundreds of folding events, a classical folding “pathway” for such a polymer is found which includes partially folded, on-pathway intermediates that are shown to be metastable equilibrium states of the polymer. The folding reaction has a well-defined ensemble of transition state conformations that are characterized by common core structures. (January 4, 1998; Revised March 1, 1998)
New opportunities in trace elements structural characterization: high-energy X-ray absorption near-edge structure spectroscopy.

Garnets in lower crustal mafic and ultramafic rocks usually contain rare-earth elements (REE) in trace concentrations. Direct characterization of REE at trace levels in natural garnets is not available in the literature because of the difficulty of obtaining structural information by means of conventional diffraction methods. Here, the characterization of Nd at trace levels (176-1029 p.p.m.) in a set of natural garnets performed by means of Nd K-edge X-ray absorption near-edge structure spectroscopy is presented, showing the capability of high-energy XANES for REE in trace structural determinations.
A Flexible Pressure Sensor Based on an Interlocked Micropillars Array With Secondary Nanoprotrusions for Health Monitoring

Flexible pressure sensors are an essential component in artificial systems to monitor human health. Recently, flexible pressure sensors with micronanostructures in interlocked geometry have attracted extensive attention because they effectively improve the sensing performance. However, it is a challenge that the fabrication methods are complex and expensive, and the layered interface between microstructure and nanostructure is unstable. Here, a flexible pressure sensor with an interlocked polydimethylsiloxane (PDMS) micropillars array combined secondary nanoprotrusions on their surfaces is proposed, which can be shaped in one step with the merits of simplicity, controllability, and low cost. The unique combined micronanostructures ensure the sensor with a wide linear range (0–32 kPa), relatively high piezoresistive sensitivity ( $26.08~\Omega $ /kPa), low detection limit (15 Pa), fast response speed (response time is 56 ms and relaxation time is 140 ms), and excellent stability (>1000 cycles). These superior properties set a foundation for applying the sensor in detecting various human physiological signals from pulse to joint deformation. Based on this sensor, a smart mask integrated system is proposed, displaying and recording breathing conditions in real time. These results demonstrate that the sensor can be used in health monitoring and disease diagnosis, as well as its potential application in other wearable devices.
In117, an Unusual In0-Like Class 1 Integron Containing CR1 and blaCTX-M-2 and Associated with a Tn21-Like Element

ABSTRACT An unusual In0-like class 1 integron containing a common region that includes the putative recombinase gene named orf513 (CR1) and blaCTX-M-2 was characterized from Escherichia coli. The integron contained an unusual gene cassette array, estX-aadA1, embedded between the 5′-conserved segment (5′-CS) and 3′-CS1 regions and was flanked by mer-Tn21 sequences downstream of the tni truncated module. This element constitutes one of the few examples of CR1-bearing class 1 integrons that has been fully characterized.
Biogeosciences CO 2 perturbation experiments : similarities and differences between dissolved inorganic carbon and total alkalinity manipulations

Increasing atmospheric carbon dioxide (CO 2) through human activities and invasion of anthropogenic CO 2 into the surface ocean alters the seawater carbonate chemistry, increasing CO2 and bicarbonate (HCO − 3 ) at the expense of carbonate ion (CO 2− 3 ) concentrations. This redistribution in the dissolved inorganic carbon (DIC) pool decreases pH and carbonate saturation state ( ). Several components of the carbonate system are considered potential key variables influencing for instance calcium carbonate precipitation in marine calcifiers such as coccolithophores, foraminifera, corals, mollusks and echinoderms. Unravelling the sensitivities of marine organisms and ecosystems to CO 2 induced ocean acidification (OA) requires well-controlled experimental setups and accurate carbonate system manipulations. Here we describe and analyse the chemical changes involved in the two basic approaches for carbonate chemistry manipulation, i.e. changing DIC at constant total alkalinity (TA) and changing TA at constant DIC. Furthermore, we briefly introduce several methods to experimentally manipulate DIC and TA. Finally, we examine responses obtained with both approaches using published results for the coccolithophoreEmiliania huxleyi . We conclude that under most experimental conditions in the context of ocean acidification DIC and TA manipulations yield similar changes in all parameters of the carbonate system, which implies direct comparability of data obtained with the two basic approaches for CO2 perturbation. Correspondence to: K. G. Schulz (kschulz@ifm-geomar.de)
Improved Dust Forecast by Assimilating MODIS IR-Based Nighttime AOT in the ADAM2 Model

A data assimilation (DA) system employing dayand nighttime aerosol optical thickness (AOT) was developed for the Asian Dust Aerosol Model 2 (ADAM2), using the optimal interpolation (OI) method. The DA system assimilated nighttime AOT for dust retrieved from MODIS infrared (IR) measurements with an artificial neural network (ANN) approach. An Asian dust case that occurred during 14−18 March 2009 was simulated using ADAM2. To examine the impact of the inclusion of nighttime AOT on forecasts of the data assimilation system, experiments were performed with different assimilation cycles (i.e., DA1: 24-hour cycle with daytime MODIS AOT only, DA2: 12-hour cycle with additional nighttime AOT). A control simulation was also performed without data assimilation (CTL). Forecasts were assessed using MODIS-derived AOT distributions as well as ground-based skyradiometer, PM10, and lidar observations. The model-estimated vertical distribution of the dust extinction coefficient was also compared with lidar measurements. Both experiments (DA1, DA2) were found to have improved forecasting, but DA2 outperformed DA1. Results suggest that the ANN-based nighttime AOT contributes more positively to the forecasting through better temporal coverage for data assimilation. (Citation: Lee, S.-S., E.-H. Lee, B.-J. Sohn, H. C. Lee, J. H. Cho, and S.-B. Ryoo, 2017: Improved dust forecast by assimilating MODIS IR-based nighttime AOT in the ADAM2 model. SOLA, 13, 192−198, doi:10.2151/sola.2017-035.)
Epithelial mesenchymal transition traits in honey‐driven keratinocyte wound healing: Comparison among different honeys

Honey has been used since ancient times for wound repair, but the subjacent mechanisms are almost unknown. We have tried to elucidate the modulatory role of honey in an in vitro model of HaCaT keratinocyte re‐epithelialization by using acacia, buckwheat, and manuka honeys. Scratch wound and migration assays showed similar increases of re‐epithelialization rates and chemoattractant effects in the presence of different types of honey (0.1%, v/v). However, the use of kinase and calcium inhibitors suggested the occurrence of different mechanisms. All honeys activated cyclin‐dependent kinase 2, focal adhesion kinase, and rasGAP SH3 binding protein 1. However, vasodilator‐stimulated phosphoprotein, integrin‐β3, cdc25C, and p42/44 mitogen activated protein kinase showed variable activation pattern. Re‐epithelialization recapitulates traits of epithelial‐mesenchymal transition (EMT) and the induction of this process was evaluated by a polymerase chain reaction array, revealing marked differences among honeys. Manuka induced few significant changes in the expression of EMT‐regulatory genes, while the other two honeys acted on a wider number of genes and partially showed a common profile of up‐ and down‐regulation. In conclusion, our findings have shown that honey‐driven wound repair goes through the activation of keratinocyte re‐epithelialization, but the ability of inducing EMT varies sensibly among honeys, according to their botanical origin.
Identification of Arx targets unveils new candidates for controlling cortical interneuron migration and differentiation

Mutations in the homeobox transcription factor ARX have been found to be responsible for a wide spectrum of disorders extending from phenotypes with severe neuronal migration defects, such as lissencephaly, to mild forms of intellectual disabilities without apparent brain abnormalities, but with associated features of dystonia and epilepsy. Arx expression is mainly restricted to populations of GABA-containing neurons. Studies of the effects of ARX loss of function, either in humans or mutant mice, revealed varying defects, suggesting multiple roles of this gene in brain patterning, neuronal proliferation and migration, cell maturation and differentiation, as well as axonal outgrowth and connectivity. However, to date, little is known about how Arx functions as a transcription factor or which genes it binds and regulates. Recently, we combined chromatin immunoprecipitation and mRNA expression with microarray analysis and identified approximately 1000 gene promoters bound by Arx in transfected neuroblastoma N2a cells and mouse embryonic brain. To narrow the analysis of Arx targets to those most likely to control cortical interneuron migration and/or differentiation, we compare here our data to previously published studies searching for genes enriched or down-regulated in cortical interneurons between E13.5 and E15.5. We thus identified 14 Arx-target genes enriched (Cxcr7, Meis1, Ppap2a, Slc 12a5, Ets2, Phlda1, Egr1, Igf1, Lmo3, Sema6, Lgi1, Alk, Tgfb3, and Napb) and 5 genes specifically down-regulated (Hmgn3, Lmo1, Ebf3, Rasgef1b, and Slit2) in cortical migrating neurons. In this review, we present these genes and discuss how their possible regulation by Arx may lead to the dysfunction of GABAergic neurons, resulting in mental retardation and epilepsy.
Appearance-focused Internet Use and the Thin-beauty Ideal

Websites featuring appearance-focused content are a medium for constant appearance comparisons, addiction and pressure to meet existing beauty-ideals. This study investigated a sample of 264 males and females who use appearance-focused websites, with a view to determining the relationship with appearance dissatisfaction and self-worth. Data collection involved posting links to online questionnaires on popular social networking sites. Internet appearance exposure was found to correlate with a greater drive for thinness in females, suggesting that exposure to the thin-ideal body images presented online reinforces womeni¯s desire to achieve the cultural expectations of body shape and weight. Furthermore the study highlighted that internet addiction was associated with a drive for thinness and low self-esteem in both males and females, with differences exhibited in regards to body-esteem. These findings emphasise the need for pathological internet use to be incorporated into media literacy programs and to encourage a critical stance toward current beauty standards.
Enhanced mobility and energy efficiency in 5G ultra-dense networks with lean carrier design

5G networks are expected to support significantly higher data rates than legacy networks through ultra-dense deployment of networks, higher system bandwidths and higher spectral efficiency. Such networks would also be supporting a diverse set of use cases in order to provide connectivity solutions for other industry verticals. One of the key requirements of 5G is to support all these enhancements with higher energy efficiency, for which the lean system design avoiding always-on signals is considered to be a key enabler. In this paper, we propose a mobility based reference signal configuration adaptation mechanism, and investigate the impacts on mobility support and energy efficiency with such a system design. Based on the performance evaluations conducted, it is shown that such lean design, optimized for mobility can provide enhanced mobility support and higher user throughput, while enabling higher energy saving potential. The higher throughput is obtained due to the reduction of always-on signals which are used for discovery in legacy networks and flexibly utilizing them for data transmissions in 5G networks.
Infection and Drug Resistance Dovepress Antibiotic Lock Therapy: Review of Technique and Logistical Challenges

Antibiotic lock therapy (ALT) for the prevention and treatment of catheter-related bloodstream infections is a simple strategy in theory, yet its real-world application may be delayed or avoided due to technical questions and/or logistical challenges. This review focuses on these latter aspects of ALT, including preparation information for a variety of antibiotic lock solutions compatibility, and dwell times are summarized. Logistical challenges such as lock preparation procedures, use of additives (eg, heparin, citrate, or ethylenediaminetetraacetic acid), timing of initiation and therapy duration, optimal dwell time and catheter accessibility, and risks of ALT are also described. Development of local protocols is recommended in order to avoid these potential barriers and encourage utilization of ALT where appropriate.
Direct in vivo evidence demonstrating neointimal migration of adventitial fibroblasts after balloon injury of rat carotid arteries.

BACKGROUND Clinical and experimental evidence suggest that the adventitia participates in the response to endoluminal vascular injury. The current study used a direct approach to test the hypothesis that, after balloon injury of the rat carotid artery, adventitial fibroblasts migrate in a luminal direction and contribute to neointima formation. METHODS AND RESULTS Primary syngeneic adventitial fibroblasts were stably transduced with retroviral particles coordinating expression of beta-galactosidase (LacZ) and introduced into the adventitia of right carotid arteries of rats immediately after balloon injury. At defined times after injury and fibroblast implantation, rats were euthanized, and arterial tissue was examined for detection of LacZ mRNA (reverse transcription polymerase chain reaction), DNA (polymerase chain reaction), and in situ enzymatic activity. LacZ expression was detected in the media 5 days postinjury and in both media and neointima at 7, 10, and 14 days postinjury. LacZ was undetectable in injured vessels that had not been seeded with transduced fibroblasts and was restricted to the adventitia in seeded vessels that were not injured. CONCLUSIONS These observations provide direct demonstration of adventitial fibroblast migration into neointima of arteries after endoluminal injury.
The shared dirichlet priors for bayesian language modeling

We present a new full Bayesian approach for language modeling based on the shared Dirichlet priors. This model is constructed by introducing the Dirichlet distribution to represent the uncertainty of n-gram parameters in training phase as well as in test time. Given a set of training data, the marginal likelihood over n-gram probabilities is illustrated in a form of linearly-interpolated n-grams. The hyperparameters in Dirichlet distributions are interpreted as the prior backoff information which is shared for the group of n-gram histories. This study estimates the shared hyperparameters by maximizing the marginal distribution of n-gram given the training data. Such Bayesian language model is connected to the smoothed language model. Experimental results show the superiority of the proposed method to the other methods in terms of perplexity and word error rate.
Compression-Based Graph Mining Exploiting Structure Primitives

How can we retrieve information from sparse graphs? Traditional graph mining approaches focus on discovering dense patterns inside complex networks, for example modularity-based or cut-based methods. However, most real world data sets are very sparse. Nevertheless, traditional approaches tend to omit interesting sparse patterns like stars. In this paper, we propose a novel graph mining technique modeling the transitivity and the hub ness of a graph using structure primitives. We exploit these structure primitives for effective graph compression using the Minimum Description Length Principle. The compression rate is an unbiased measure for the transitivity or hub ness and therefore provides interesting insights into the structure of even very sparse graphs. Since real graphs can be composed of sub graphs of different structures, we propose a novel algorithm CXprime (Compression-based exploiting Primitives) for clustering graphs using our coding scheme as an objective function. In contrast to traditional graph clustering methods, our algorithm automatically recognizes different types of sub graphs without requiring the user to specify input parameters. Additionally we propose a novel link prediction algorithm based on the detected substructures, which increases the quality of former methods. Extensive experiments evaluate our algorithms on synthetic and real data.
Simulation Studies of Increased Initial TCP Window Size

An increase in the permissible initial window size of a TCP connection, from one segment to three or four segments, has been under discussion in the tcp-impl working group. This document covers some simulation studies of the effects of increasing the initial window size of TCP. Both long-lived TCP connections (file transfers) and short-lived web-browsing style connections were modeled. The simulations were performed using the publicly available ns-2 simulator and our custom models and files are also available.
Associative Memory with Dynamic Synapses

We have examined a role of dynamic synapses in the stochastic Hopfield-like network behavior. Our results demonstrate an appearance of a novel phase characterized by quick transitions from one memory state to another. The network is able to retrieve memorized patterns corresponding to classical ferromagnetic states but switches between memorized patterns with an intermittent type of behavior. This phenomenon might reflect the flexibility of real neural systems and their readiness to receive and respond to novel and changing external stimuli.
Filtering Agent-Using CBR as a Service

With the growth and commercialization of the Internet, many busy people find themselves receiving more e-mail than ever before. Thus, e-mail filtering has become an important problem. Many mailers provide filtering based on the mail header: the sender, the domain of the sender, and the subject. In the first phase of the AlterEgo project, we are developing an e-mail filtering agent that uses the content of the whole message, plus a model of the world and a model of the user, including their important goals. Initially, Case-Based Reasoning seemed llke a promising master approach; messages that are similar to messages that were deemed important in the past should be important now. However, since the user’s world may often change significantly and sometimes suddenly, the relevant similarity to a past message may be at a very abstract level. This will result in an expensive search for similarity. Hence, in our initial prototype, we have developed an approach that is driven by model-based reasoning, and is aided by case-based reasoning.
Automated extraction of signs from continuous sign language sentences using Iterated Conditional Modes

Recognition of signs in sentences requires a training set constructed out of signs found in continuous sentences. Currently, this is done manually, which is a tedious process. In this work, we consider a framework where the modeler just provides multiple video sequences of sign language sentences, constructed to contain the vocabulary of interest. We learn the models of the recurring signs, automatically. Specifically, we automatically extract the parts of the signs that are present in most occurrences of the sign in context. These parts of the signs that is stable with respect to adjacent signs, are referred to as signemes. Each video is first transformed into a multidimensional time series representation, capturing the motion and shape aspects of the sign. We then extract signemes from multiple sentences, concurrently, using Iterated Conditional Modes (ICM). We show results by learning multiple instances of 10 different signs from a set of 136 sign language sentences. We classify the extracted signemes as correct, partially correct or incorrect depending on whether both the start and end locations are correct, only one of them is correct or both are incorrect, respectively. Out of the 136 extracted video signemes, 98 were correct, 20 were partially correct and 18 were incorrect. To demonstrate the generality of the unsupervised modeling idea, we also show the ability to automatically extract common spoken words in audio. We consider the English glosses (spoken) corresponding to the sign language sentences and extract the audio counterparts of the signs. Of the 136 such instances, we recovered 127 correct, 8 partially correct, and 1 incorrect representation of the words.
Cross layer privacy support for identity management

One of the most important objectives of Identity Management (IdM) Systems is to provide end user privacy. However, these concepts rarely extend beyond the application layer. In the IST SWIFT project a special attention is given to cross-layer Identity Management support, and in this paper we show why applying only IdM solutions is insufficient to preserve user privacy if network mechanisms are not considered. We present a solution to retain user privacy by using network pseudonyms closely coordinated with the IdM framework proposed by the SWIFT project. We include these concepts in the IdM framework and present the necessary architecture and functional mechanisms required to support the privacy extensions.