Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical modelling of sediment delivery from tidewater glaciers to the marine environment

Glaciated fjords are dynamic sedimentary environments with high deposition rates, thus providing high-resolution sedimentary records of deglaciation. This thesis introduces two numerical models, SedBerg and SedPlume, developed to simulate marine sedimentation from tidewater glaciers for the dominant transport processes of icebergrafting and glacial meltwater plumes. Icebergs calved from tidewater glaciers contain sediment, which is released as the icebergs melt. The SedBerg Model utilises Monte Carlo based techniques to simulate the formation, drift and melt of a population of icebergs, and the subsequent deposition. Subaqueous and subaerial melt of the icebergs result in a continuous rainout of sediment with occasional sediment dumping from overturning events. Underlying the model are a number of parametric probability distributions to describe the stochastic behaviour of iceberg formation and dynamics. Parametric values of the probability density functions are found using maximum likelihood estimation from field observations. Turbid meltwater emerging from beneath a glacier into a fjord rises as a buoyant forced plume due to salinity and temperature contrasts with the ambient fjord water. The SedPlume Model utilises an integral model formulation for the conservation of volume, momentum, buoyancy and sediment mass along the path of a turbulent, entraining plume injected into stably stratified ambient fluid. The resulting system of non-linear ordinary differential equations are solved numerically using an adaptive stepsize fourth-order Runge-Kutta method. When the plume reaches the surface, it is treated as a radially spreading surface gravity current, for which exact solutions exist for the mass flux of sediment deposited. A case study is examined for each model. The SedBerg Model is applied to Kangerdlugssuaq Fjord in East Greenland, as an example of an iceberg-dominated depositional environment. The sedimentation rate due to iceberg rafting is simulated for Kangerdlugssuaq Fjord over the last 1500 years, with climatic, oceanographic and glacial conditions estimated from a mixture of present day measurements and inferences from the sedimentary record. The SedPlume Model is applied to McBride Inlet in Alaska, as an example of a glacial meltwater-dominated sedimentary environment, with input data and ice-proximal sedimentation rates taken from published data. The influence of various parameters on sediment deposition is investigated for each of the two models. For the SedBerg Model, the parameters considered are: iceberg size; temperature and depth of thermocline; and seeds of the random number generator for water and wind velocities. For the SedPlume Model, the parameters studied are: subglacial conduit radius and initial meltwater velocity; initial sand fraction; and ambient density gradient. The SedBerg and SedPlume Models enable quantitative assessments of the role and importance of different environmental and climatic conditions on the rate of deposition and the formation of distinctive marine deposits by tidewater glaciers.
Automatic speech recognition in Mandarin for embedded platforms

In this paper, we describe a real-time automatic speech recognition system for Mandarin for low-cost embedded platforms using fixed-point digital signal processors. The hands-free, speaker-independent speech recognition system employs 41 mono-phone models for representing the sounds in Mandarin Chinese and 11 whole-word models for connected digit recognition. The system achieves greater than 98% recognition accuracy on our hands-free test database of 46 distinct command phrases. The system achieves 95.9% digit accuracy on a 14 speaker, hands-free, connected digit recognition database. The analysis of the results shows that for speakers without dialect, the digit recognition accuracy is almost 98%. We present a detailed analysis of the digit recognition results and propose further improvements. A real-time platform based upon Lucent’s DSP1627 fixed-point digital signal processor has been developed.
CUNI in WMT14: Chimera Still Awaits Bellerophon

We present our English! Czech and English! Hindi submissions for this year’s WMT translation task. For English! Czech, we build upon last year’s CHIMERA and evaluate several setups. English! Hindi is a new language pair for this year. We experimented with reverse self-training to acquire more (synthetic) parallel data and with modeling target-side morphology.
Continuous action recognition based on hybrid CNN-LDCRF model

Continuous action recognition in video is more challenging compared with traditional isolated action recognition. In this paper, we proposed a hybrid framework combining Convolutional Neural Network (CNN) and Latent-Dynamic Conditional Random Field (LDCRF) to segment and recognize continuous actions simultaneously. Most existing action recognition works construct complex handcrafted features, which are highly problem dependent. We utilize CNN model, a type of deep models, to automatically learn high level action features directly from raw inputs. The LDCRF model is used to model the intrinsic and extrinsic dynamics of actions. The CNN is embedded in the bottom layer of LDCRF, which converts the structure of LDCRF from shallow to deep. This framework incorporates action feature learning and continuous action recognition procedures in a unified way. The training of our model is in end-to-end fashion. The parameters of CNN and LDCRF are jointly optimized by gradient descent algorithm. We test our method on two public dataset: KTH and HumanEva. Experiment shows our method achieves improved recognition accuracy compared with several other methods. We also demonstrate the superiority of features learnt by CNN compared with handcrafted features.
Clustering Data on Manifold with Local and Global Consistency

Data clustering aims at finding the hidden patterns in a large collection of data and a large body of effective algorithms have been proposed to partition the data in the past three decades. However, most of the algorithms fail to handle data that expose a manifold structure which is common in many data-driven application, such as interpretation and recognition of video, handwritten character and image data. In this paper, we study the problem of clustering on manifold that aims to partition a set of input data into several clusters each of which contains data points from a simple low-dimensional manifold. We apply the basic assumption of local and global consistency on the manifold. A novel algorithm name CMLGC is proposed to find the proper clusters on the manifold. Our research can also be seen as an instance of manifold learning. The encouraging results on several synthetic and real-world data set are obtained which validate our proposed algorithm.
An improvement of translation quality with adding key-words in parallel corpus

In this paper, we propose a new approach to improve the translation quality by adding the Key-Words of a sentence to the parallel corpus. The main idea of the approach is to find the key-words of sentences that cannot be properly translated by the model, and then put it or them in the training corpus in a separated line as a sentence. During our experiment, we use two statistical machine translation (SMT) systems, word-based SMT (ISI-rewrite) and phrase-based SMT (Moses), and a small parallel corpus (4,000 sentences) to check our assumption. To our glad, we get a better BLEU score than the original parallel text. It can improve about 6% in word-based SMT (isi-rewrite) and 4% in phrased-based SMT (Moses). At last we build a 120,000 English-Chinese parallel corpus in this way.
Analyzing the Effect of Cluster Head in Low Energy Adaptive Clustering Hierarchical in Wireless Sensor Network

The wireless sensor networks consist of hundreds of inexpensive wireless nodes, each with some computational power and sensing capability, operational power and sensing capability, operating in an unattended mode. Clustering is an efficient approach to capitalize the energy of energy constraint sensor nodes in wireless sensor networks (WSNs). Low Energy Adaptive Clustering Hierarchy (LEACH) is a major breakthrough for clustering technique by forming and rotating cluster head among nodes randomly. In present work the cluster heads are formed, number of cluster heads was fixed to 8 and LEACH scheme was simulated in NS-2 to study the performance in terms of network lifetime and energy consumption rate for each cluster head. The most significant performance was found in the cluster head having optimum load balancing factor and moderate distance from base station.
GENRE CLASSIFICATION BASED ON TONE OBJECTS (MIREX 2013 SUBMISSION — DRAFT)

This extended abstract details the submission to the 2013 Music Information Retrieval Evaluation eXchange in the Audio Classiﬁcation Train/Test task. The proposed sys-tem is designed to perform improved genre classiﬁcation by combining temporal segmentation and source separation of music signals into so-called tone objects . The audio features extracted from these tone objects are low-level and well-known. Gaussian Mixture Models (GMMs) and Support Vector Machines (SVMs) are used for classiﬁcation. This submission is motivated by promising results obtained on other genre data sets.
Determination of the anti-inflammatory and cytoprotective effects of l-glutamine and l-alanine, or dipeptide, supplementation in rats submitted to resistance exercise

Abstract We evaluated the effects of chronic oral supplementation with l-glutamine and l-alanine in their free form or as the dipeptide l-alanyl-l-glutamine (DIP) on muscle damage, inflammation and cytoprotection, in rats submitted to progressive resistance exercise (RE). Wistar rats (n 8/group) were submitted to 8-week RE, which consisted of climbing a ladder with progressive loads. In the final 21 d before euthanasia, supplements were delivered in a 4 % solution in drinking water. Glutamine, creatine kinase (CK), lactate dehydrogenase (LDH), TNF-α, specific IL (IL-1β, IL-6 and IL-10) and monocyte chemoattractant protein-1 (MCP-1) levels were evaluated in plasma. The concentrations of glutamine, TNF-α, IL-6 and IL-10, as well as NF-κB activation, were determined in extensor digitorum longus (EDL) skeletal muscle. HSP70 level was assayed in EDL and peripheral blood mononuclear cells (PBMC). RE reduced glutamine concentration in plasma and EDL (P<0·05 v. sedentary group). However, l-glutamine supplements (l-alanine plus l-glutamine (GLN+ALA) and DIP groups) restored glutamine levels in plasma (by 40 and 58 %, respectively) and muscle (by 93 and 105 %, respectively). GLN+ALA and DIP groups also exhibited increased level of HSP70 in EDL and PBMC, consistent with the reduction of NF-κB p65 activation and cytokines in EDL. Muscle protection was also indicated by attenuation in plasma levels of CK, LDH, TNF-α and IL-1β, as well as an increase in IL-6, IL-10 and MCP-1. Our study demonstrates that chronic oral l-glutamine treatment (given with l-alanine or as dipeptide) following progressive RE induces cyprotective effects mediated by HSP70-associated responses to muscle damage and inflammation.
Remaining Inductor Current Phenomena of Complex DC–DC Converters in Discontinuous Conduction Mode: General Concepts and Case Study

Remaining inductor current phenomena occur in several dc-dc converters operating in discontinuous conduction mode, but they do not agree with the classical definition of the discontinuous conduction mode. Since these special phenomena often cause misunderstanding during theoretical analysis and engineering applications, a reexamination is performed in this paper. Based on the investigation of energy characteristics, a new explanation of the discontinuous conduction mode is proposed so that all discontinuous cases, including the remaining inductor current phenomena, can be unified by the proposed concepts. The paper presents the canonical explanation, existence conditions and main solving principles, which simplify the derivation process of steady-state performance of a complex dc-dc converter. Case study on a fifth order self-lift Luo converter and a seventh order re-lift SEPIC converter are performed, respectively, and the corresponding simulation results are shown to validate the theoretical analysis.
Empirical Dynamic Programming

We propose empirical dynamic programming algorithms for Markov decision processes. In these algorithms, the exact expectation in the Bellman operator in classical value iteration is replaced by an empirical estimate to get “empirical value iteration” (EVI). Policy evaluation and policy improvement in classical policy iteration are also replaced by simulation to get “empirical policy iteration” (EPI). Thus, these empirical dynamic programming algorithms involve iteration of a random operator, the empirical Bellman operator. We introduce notions of probabilistic fixed points for such random monotone operators. We develop a stochastic dominance framework for convergence analysis of such operators. We then use this to give sample complexity bounds for both EVI and EPI. We then provide various variations and extensions to asynchronous empirical dynamic programming, the minimax empirical dynamic program, and show how this can also be used to solve the dynamic newsvendor problem. Preliminary experimental results suggest a faster rate of convergence than stochastic approximation algorithms.
A generic framework for scalable and convergent multi-robot active simultaneous localization, mapping and target tracking

In this paper, a new approach is proposed and analyzed for developing efficient and scalable methodologies for multi-robot active Cooperative Simultaneous Localization And Mapping and Target Tracking (C-SLAMTT). The proposed approach employs an active estimation scheme that switches among linear elements and, as a result, its computational requirements scale linearly with the number of estimated quantities (number of number of robots, landmarks and targets). The parameters of the proposed scheme are calculated off-line using a convex optimization algorithm which is based on Semi-Definite Programming (SDP) and approximation using Sum-of-Squares (SoS) polynomials. As shown by rigorous arguments, the estimation accuracy of the proposed scheme is equal to the optimal estimation accuracy plus a term that is inversely proportional to the number of estimator's switching elements (or, equivalently, to the memory storage capacity of the robots' equipment). The proposed approach can handle various types of constraints such as “stay-within-an-area”, obstacle avoidance and maximum speed constraints. The efficiency of the approach is demonstrated on a 3D active cooperative simultaneous mapping and target tracking application employing flying robots.
Synergistically Enhanced CYP2B6 Inducibility between a Polymorphic Mutation in CYP2B6 Promoter and Pregnane X Receptor Activation

CYP2B6 is a highly inducible and polymorphic enzyme involved in the metabolism of an increasing number of clinically important drugs. Significant interindividual variability in CYP2B6 expression has been attributed to either genetic polymorphisms or chemical-mediated induction through the activation of constitutive androstane receptor and/or pregnane X receptor (PXR). It was reported that the −82T→C substitution within the CYP2B6*22 allele creates a functional CCAAT/enhancer-binding protein (C/EBP) binding site and enhances the basal expression of the CYP2B6 gene. Here, we explored whether this polymorphic mutation could affect drug-mediated induction of CYP2B6. Cell-based promoter reporter assays demonstrated that CYP2B6 luciferase activity was synergistically enhanced in the presence of both −82T→C mutation and rifampicin (RIF)-activated PXR. On the other hand, this synergism was attenuated by disrupting the C/EBP binding site or knocking down C/EBPα expression. Mechanistic studies revealed that C/EBPα plays an important role in such synergism by directly interacting with PXR; enhancing RIF-mediated recruitment of PXR to the −82T→C harboring CYP2B6 promoter; and looping the PXR-bound distal phenobarbital-responsive enhancer module toward the proximal C/EBP binding site. Furthermore, the genotype-phenotype association was evaluated in cultured human primary hepatocytes from 44 donors. Interestingly, RIF-mediated induction of CYP2B6 in four −82T/C carriers was higher compared with that in the reference −82T/T homozygotes. Together, our results demonstrate, for the first time, a synergistic interplay between a CYP2B6 polymorphism and PXR-mediated induction, which may contribute to the large individual variations and inducibility of CYP2B6 in humans.
Dynamic Computation Migration in DSM Systems

Dynamic computation migration is the runtime choice between computation and data migration. Dynamic computation migration speeds up access to concurrent data structures with unpredictable read/write patterns. This paper describes the design, implementation, and evaluation of dynamic computation migration in a multithreaded distributed shared-memory system, MCRL. Two policies are studied, STATIC and REPEAT. Both migrate computation for writes. STATIC migrates data for reads, while REPEAT maintains a limited history of accesses and sometimes migrates computation for reads. On a concurrent, distributed B-tree with 50% lookups and 50% inserts, STATIC improves performance by about 17% on both Alewife and the CM-5. REPEAT generally performs better than STATIC. With 80% lookups and 20% inserts, REPEATimproves performance by 23% on Alewife, and by 46% on the CM-5.
Transparent Programming of Heterogeneous Smartphones for Sensing

Sensing on smartphones is known to be power-hungry. It has been shown that this problem can be solved by adding an ultra low-power processor to execute simple, frequent sensor data processing. While very effective in saving energy, this resulting heterogeneous, distributed architecture poses a significant challenge to application development. We present Reflex, a suite of runtime and compilation techniques to conceal the heterogeneous, distributed nature from developers. The Reflex automatically transforms the developer's code for distributed execution with the help of the Reflex runtime. To create a unified system illusion, Reflex features a novel software distributed shared memory (DSM) design that leverages the extreme architectural asymmetry between the low-power processor and the powerful central processor to achieve both energy efficiency and performance. We report a complete realization of Reflex for heterogeneous smartphones with Maemo/Linux as the central kernel. Using a tri-processor hardware prototype and sensing applications reported in recent literature, we evaluate the Reflex realization for programming transparency, energy efficiency, and performance. We show that Reflex supports a programming style that is very close to contemporary smartphone programming. It allows existing sensing applications to be ported with minor source code changes. Reflex reduces the system power in sensing by up to 83%, and its runtime system only consumes 10% local memory on a typical ultra-low power processor.
Clarification to provide further understanding of the conduct and design of TROPIC: A Phase 3 trial of cabazitaxel versus mitoxantrone in patients with metastatic castration-resistant prostate cancer.

Dear Editors, We read with interest the article “Efficacy and safety of second-line agents for treatment of metastatic castration-resistant prostate cancer progressing after docetaxel. A systematic review and meta-analysis” by Perletti et al. in your journal (Arch Ital Urol Androl. 2015; 87:121-9), which describes the results of a systematic literature review assessing second-line agents used in the treatment of metastatic castration-resistant prostate cancer (mCRPC) progressing after docetaxel-based regimens. The authors analyzed ten articles reporting the results of five Phase 3, randomized, controlled trials that enrolled patients with mCRPC progressing during or after first-line docetaxel treatment. This included the Phase 3 TROPIC trial of cabazitaxel versus mitoxantrone (1), which provided the basis for the regulatory approval of cabazitaxel in this setting. The authors conducted a risk of bias analysis for each trial included in their review and concluded that the TROPIC trial had a high risk of selection and performance/detection bias. However, in Table 2, the authors made several assumptions about the methodology of the TROPIC trial, which we feel warrant clarification.
Inconsistent Responses of Hot Extremes to Historical Land Use and Cover Change Among the Selected CMIP5 Models

Land use and cover change (LUCC) is an important anthropogenic forcing of the climate system. Previous studies have demonstrated that LUCC significantly impacts both mean and extreme temperatures. In this study, we explored the multimodel performance of simulating LUCC‐induced asymmetric effects on the different percentiles of maximum temperatures (Tmax) as well as the possible reasons for these effects using results from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Four state‐of‐art Earth system models (which provide the necessary data) are selected for investigating this issue. In general, all the cases of the model from the Geophysical Fluid Dynamics Laboratory show robust asymmetric responses between the 90th (TX90P) and 10th percentiles (TX10P) of Tmax, mainly due to cropland expansions, especially over India, the Sahel, and some parts of North America. However, weak and insignificant responses are shown for both the TX90P and TX10P in other models. The different changes in the Tmax variability among the models are primarily responsible for the occurrence of asymmetric features. Furthermore, by decomposing the Tmax changes over three typical regions, we analyze the potential causes for the inconsistencies among these models' results and find two crucial processes, that is, the repartitioning of the turbulent heat fluxes and the changes of the diurnal cycle variability due to LUCC. Whether these processes are pronounced determines the occurrence of the asymmetric Tmax responses. Overall, this study provides a critical clue for reducing the uncertainties of the LUCC effects on temperature extremes, which should be evaluated against observations.
Verbreitung und Bestand des Auerhuhns Tetrao urogallus in der Schweiz 2001 und ihre Veränderungen im 19. und 20. Jahrhundert

Numbers and distribution of Capercaillie Tetrao urogallus in Switzerland 2001 and their changes in the 19th and 20th century. – Male Capercaillie were censused at their leks in spring 2001 in most parts of their range in Switzerland. A large part in the canton of Grisons was not censused with the same method but by a stratified sampling of tracks, droppings and feathers. The Capercaillie is distributed in the Jura mountains, along the northern slopes of the Alps and in the central Alps of the canton of Grisons. On 147 leks, 252 Capercaillie were counted. The total number of Capercaillie males in Switzerland is estimated to be between 450 and 500. In 1968 / 1971 and in 1985 two censuses had been carried out with the same method. The first revealed an estimated number of Capercaillie males of at least 1100, the second of 550 – 650. Since 1985, the range has shrunk, too. Capercaillie has almost completely disappeared from the northwestern slopes of the Alps. The main reasons for the long-term negative trend in population numbers of Capercaillie seem to be changes in forest structure and human disturbances. Meteorological data suggest that between 1985 and 2001 the decline has been overlayed by population fluctuation caused by changing weather conditions.