Miracle-dz/UniFAR-FTUs huggingface dataset:
Kyoto Protocol and Emission Trading: Does the Us Make a Difference?

This paper presents an estimate of the costs of reducing CO2 emissions as agreed in Kyoto by Annex 1 countries. Unlike most of the existing literature, this paper uses an Almost Ideal Demand System model for energy products to estimate the role of each country within the Annex 1 market. A major result is the provision of marginal (and total) abatement costs for each. The recent position of the US is also discussed, showing the cost of some alternative outcomes.
Knowledge Discovery in Texts Supporting e-Democracy

 This paper presents a survey of basic concepts in the area of text data mining and some o f the methods used in order to elicit useful information (knowledge) from (possibly large) collections of te xtual data. Exploitation of some of the described techni ques within the WEBOCRAT system is presented as well. WEBOCRAT aims to bring public administration closer to citizens, making it more accessible and easier t o understand. The system will encourage more participation in democracy as well as making administration more fficient.
Modulation of Spinal GABAergic Inhibition and Mechanical Hypersensitivity following Chronic Compression of Dorsal Root Ganglion in the Rat

Chronic compression of dorsal root ganglion (CCD) results in neuropathic pain. We investigated the role of spinal GABA in CCD-induced pain using rats with unilateral CCD. A stereological analysis revealed that the proportion of GABA-immunoreactive neurons to total neurons at L4/5 laminae I–III on the injured side decreased in the early phase of CCD (post-CCD week 1) and then returned to the sham-control level in the late phase (post-CCD week 18). In the early phase, the rats showed an increase in both mechanical sensitivity of the hind paw and spinal WDR neuronal excitability on the injured side, and such increase was suppressed by spinally applied muscimol (GABA-A agonist, 5 nmol) and baclofen (GABA-B agonist, 25 nmol), indicating the reduced spinal GABAergic inhibition involved. In the late phase, the CCD-induced increase in mechanical sensitivity and neuronal excitability returned to pre-CCD levels, and such recovered responses were enhanced by spinally applied bicuculline (GABA-A antagonist, 15 nmol) and CGP52432 (GABA-B antagonist, 15 nmol), indicating the regained spinal GABAergic inhibition involved. In conclusion, the alteration of spinal GABAergic inhibition following CCD and leading to a gradual reduction over time of CCD-induced mechanical hypersensitivity is most likely due to changes in GABA content in spinal GABA neurons.
Noninvasive in vivo assessment of soft contact lens type on tear film surface quality.

PURPOSE To evaluate the effect of soft contact lens type on the in vivo tear film surface quality (TFSQ) on daily disposable lenses and to establish whether two recently developed techniques for noninvasive measurement of TFSQ can distinguish between different contact lens types. METHODS Thirteen subjects wearing four different types of daily soft contact lenses participated in the study. Dynamic area high-speed videokeratoscopy (HSV) and lateral shearing interferometry (LSI) were used to quantitatively assess TFSQ in natural blinking conditions in the morning soon after lens insertion and in the afternoon following 8 hours of lens wear. RESULTS All considered contact lenses caused a significant reduction in TFSQ compared with bare eye measures. Significant differences (P < 0.05) in the average TFSQ were also observed between all contact lens materials in LSI measurements and in the majority of dynamic area HSV measurements. The potential relationship between the contact lens parameters and the observed decline in the prelens TFSQ was explored. CONCLUSIONS Noninvasive techniques of tear film surface assessment have the potential to discriminate contact lens type/material on eye. LSI was found to more effectively perform this discrimination than the dynamic area HSV technique.
Configuration of actors and roles in establishing ICT

Establishing technologies has brought mixed socio-economic impacts across nations and regions. Researchers have studied the relationships between the establishment technologies and its impacts through identifying innovative processes, major actors, and available resources. However, the challenge to this literature is how less resourced countries have achieved greater prosperity than better resourced countries by establishing Information and Communication Technology (ICT). To understand and analyze this phenomenon, we propose a typology of the configuration of roles and actors in establishing ICT based on an innovation framework. The proposed typology can be used not only to explain different socio-economic impacts among countries or regions, but also to suggest a constructive way in establishing ICT through reconfiguring involved actors in the key roles.
An Exploratory Analysis of Multiple Multivariate Time Series

Our aim is to extend standard principal component analysis for non-time series data to explore and highlight the main structure of multiple sets of multivariate time series. To this end, standard variance-covariance matrices are generalized to lagged cross-autocorrelation matrices. The methodology produces principal component time series, which can be analysed in the usual way on a principal component plot, except that the plot also includes time as an additional dimension.
Kernel Based Detection of Mislabeled Training Examples

The problem of identifying mislabeled training examples has been examined in several studies, with a variety of approaches developed for editing the training data to obtain better classifiers. Many of these approaches involve applying an individual or an ensemble of classifiers to the training set and filtering the mislabeled examples based on their consistency with respect to the classifier’s outputs. In this study, we formulate mislabeled detection as an optimization problem and introduce a kernel-based approach for filtering the mislabeled examples. Experimental results using a variety of data sets from the UCI data repository demonstrate the effectiveness of our proposed method, compared to existing nearest-neighbor and ensemble-based filtering schemes.
Function and Regulation of Cdk 7

7 REVIEW OF THE LITERATURE 11 Cell Division Cycle 11 Cyclin-Dependent Kinases 12 Cdks as Mediators of Cell Cycle Progression 13 The Cell Cycle of Fission yeast, Schizosaccharomyces pombe 14 Regulation of Cdks 14 Cdk regulation by T-loop phosphorylation 15 Two types of Cdk-activating T-loop Kinases Cdk7 and Cak1 16 Functions of Cdk7 as a subunit of TFIIH 18 Regulation of transcription through the RNA pol II CTD 18 RNA pol II CTD kinases 19 Regulation of Cdk7 in cell cycle and transcription 21 AIMS OF THE STUDY 22 RESULTS AND DISCUSSION: 23 Csk1 is the T-loop kinase of Mcs6 23 Regulation of Csk1 and Mcs6 23 Mammalian Csk1 Heterologs 24 Mcs6 is the T-loop kinase of Cdk1(Cdc2) 25 Identification of novel regulatory mechanisms of Mcs6 function 26 Function of mammalian Cdk8 27 Preimplantation requirement of Cdk8 and function in repression of transcription 28
Automatic Generation of Warehouse Mediators Using an Ontology Engine

Data warehouses created for dynamic scientific environments, such as genetics, face significant challenges to their long-term feasibility One of the most significant of these is the high frequency of schema evolution resulting from both technological advances and scientific insight Failure to quickly incorporate these modifications will quickly render the warehouse obsolete, yet each evolution requires significant effort to ensure the changes are correctly propagated DataFoundry utilizes a mediated warehouse architecture with an ontology infrastructure to reduce the maintenance acquirements of a warehouse. Among the things, the ontology is used as an information source for automatically generating mediators, the methods that transfer data between the data sources and the warehouse The identification, definition and representation of the metadata required to perform this task is a primary contribution of this work.
Learning non-target items for interesting clothes segmentation in fashion images

In this paper we propose a color-based approach for skin detection and interest garment selection aimed at an automatic segmentation of pieces of clothing. For both purposes, the color description is extracted by an iterative energy minimization approach and an automatic initialization strategy is proposed by learning geometric constraints and shape cues. Experiments confirms the good performance of this technique both in the context of skin removal and in the context of classification of garments.
Proposed Regulation of Gene Expression by Glucose in Rodent Heart

Background During pressure overload-induced hypertrophy, unloading-induced atrophy, and diabetes mellitus, the heart induces ‘fetal’ genes (e.g. myosin heavy chain β; mhcβ). Hypothesis We propose that altered glucose homeostasis within the cardiomyocyte acts as a central mechanism for the regulation of gene expression in response to environmental stresses. The evidence is as follows. Methods and Results Forced glucose uptake both ex vivo and in vivo results in mhc isoform switching. Restricting dietary glucose prevents mhc isoform switching in hearts of both GLUT1-Tg mice and rats subjected to pressure overload-induced hypertrophy. Thus, glucose availability correlates with mhc isoform switching under all conditions investigated. A potential mechanism by which glucose affects gene expression is through O-linked glycosylation of specific transcription factors. Glutamine:fructose-6-phosphate amidotransferase (GFAT) catalyzes the flux generating step in UDP-N-acetylglucosamine biosynthesis, the rate determining metabolite in protein glycosylation. Ascending aortic constriction increased intracellular levels of UDP-N-acetylglucosamine, and the expression of gfat2, but not gfat1, in the rat heart. Conclusions Collectively, the results strongly suggest glucose-regulated gene expression in the heart, and the involvement of glucose metabolites in isoform switching of sarcomeric proteins characteristic for the fetal gene program.
Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing

Max-product (max-sum) message passing algorithms are widely used for MAP inference in MRFs. It has many variants sharing a common flavor of passing "messages" over some graph-object. Recent advances revealed that its convergent versions (such as MPLP, MSD, TRW-S) can be viewed as performing block coordinate descent (BCD) in a dual objective. That is, each BCD step achieves dual-optimal w.r. t. a block of dual variables (messages), thereby decreases the dual objective monotonically. However, most existing algorithms are limited to updating blocks selected in rather restricted ways. In this paper, we show a "unified" message passing algorithm that: (a) subsumes MPLP, MSD, and TRW-S as special cases when applied to their respective choices of dual objective and blocks, and (b) is able to perform BCD under much more flexible choices of blocks (including very large blocks) as well as the dual objective itself (that arise from an arbitrary dual decomposition).
The anthropomorphic flutist robot WF-4R: from mechanical to perceptual improvements

One of the earliest motivations for developing humanoid robots centered on creating robots that may coexist with humans in environments created for human beings. For several years, at Waseda University, the development of the anthropomorphic flutist player has been focused on improving the musical interaction between the human and the robot to clarify the human flute playing and to propose novel assisted music teaching tools. In this paper, a new architecture for autonomously transferring skills from robot to human using the flutist robot is introduced. Furthermore, the new version of the flutist robot, the WF-4R (Waseda Flutist No.4 Refined) is presented; where the arm system was added to assure the positioning accuracy of the flute and the development of a melody recognition system to enable the robot to interact with students at the same logical level of perception. An experimental setup has been performed in order to verify the effectiveness of both mechanical and perceptual systems. As a result, using the arms system, we have assured the repetitiveness of the flute positioning. Furthermore, the implemented music recognition system was able to recognize the melody of flutist players (an overall recognition rate of 90%); demonstrating that HMM (usually used for speech recognition) is also effective for flute melody identification.
Barium titanate core – gold shell nanoparticles for hyperthermia treatments

The development of new tools and devices to aid in treating cancer is a hot topic in biomedical research. The practice of using heat (hyperthermia) to treat cancerous lesions has a long history dating back to ancient Greece. With deeper knowledge of the factors that cause cancer and the transmissive window of cells and tissues in the near-infrared region of the electromagnetic spectrum, hyperthermia applications have been able to incorporate the use of lasers. Photothermal therapy has been introduced as a selective and noninvasive treatment for cancer, in which exogenous photothermal agents are exploited to achieve the selective destruction of cancer cells. In this manuscript, we propose applications of barium titanate core–gold shell nanoparticles for hyperthermia treatment against cancer cells. We explored the effect of increasing concentrations of these nanoshells (0–100 μg/mL) on human neuroblastoma SH-SY5Y cells, testing the internalization and intrinsic toxicity and validating the hyperthermic functionality of the particles through near infrared (NIR) laser-induced thermoablation experiments. No significant changes were observed in cell viability up to nanoparticle concentrations of 50 μg/mL. Experiments upon stimulation with an NIR laser revealed the ability of the nanoshells to destroy human neuroblastoma cells. On the basis of these findings, barium titanate core–gold shell nanoparticles resulted in being suitable for hyperthermia treatment, and our results represent a promising first step for subsequent investigations on their applicability in clinical practice.
Association of TLR4 polymorphisms with subclinical mastitis in Brazilian holsteins

The identification of dairy cows with greater or lower potential to develop mastits has been pursued for many years among different segments of the milk industry, including governmental organizations. Genomic studies have suggested that Single Nucleotide Polymorphisms (SNPs) within the pattern recognition receptors (PRR) could lead to different responses to pathogens, and consequently result in mastitis resistance or susceptibility. To investigate whether toll like receptor 4 (TLR4) gene is associated with subclinical mastitis in Holstein cows from a property in the state of Goiás, Brazil, TaqMan allelic discrimination and somatic cell count were performed. One hundred and fifty milk samples were analyzed for SCC and centesimal composition. Twenty percent of those samples with SCC above 200,000 (n=13) were screened for real-time PCR identification of microorganisms and blood samples were genotyped for TLR4 SNPs. There was a higher prevalence of Gram-positive bacteria in the analyzed samples (88.9%) and animals that had the combined genotypes AACCCC, GGTCGG and GACCGC presented the lowest somatic cell scores, and consequently those genotypes have the potential to be applied as molecular markers for assisted animal selection to improve milk quality.
On traffic fairness in data center fabrics

A present challenge in data center networks (DCN) is to better understand the impact of novel flattened and modular DCN architectures on congestion control protocols, and viceversa. One of the major concerns in congestion control being the fairness in the offered throughput, the impact of the additional path diversity and forwarding features, brought by the novel DCN architectures and protocols, on the throughput of individual endpoints (servers) and aggregation points (edge switches) is unclear. This paper attempts to answer these open questions. Specifically, how best is the allocation of the competing elastic demand flows and how is this allocation impacted with the increase in capacity? We provide an optimization formulation of the problem based on the proportional fairness principle of TCP. We conducted a series of test scenarios on the fat-tree data center topology by considering load balancing and link capacities for different network cases in order to present our analysis on the results. We observed that the traffic allocation fairness is primarily impacted by the weights associated with the TCP implementation in use.
Generalized discriminative training for speech recognition

Discriminative training for speech recognition aims to minimize the errors caused by the generative models. It is often formulated as an optimization problem involving the references and the competing hypotheses. While discriminative training can improve recognition performance, it comes with a few drawbacks. First, the optimization problem is difficult to solve due to the complex objective functions. This leads to the need of heuristics and smoothing techniques for optimization. Second, discriminative training is time consuming since it can take days or weeks to finish on large systems. The goal of this thesis is to reformulate the optimization problems of discriminative training, so that we can develop better optimization algorithms which are more efficient. Our methods are based on Lagrange relaxation which we convert the difficult optimization problems into simpler convex problems. Our proposed generalized Baum-Welch (GBW) algorithm is a generalization of the Baum-Welch (BW) algorithm and the extended Baum-Welch (EBW) algorithm. Through the GBW framework, we discover an interesting connection between EBW and information theory. This inspires us to develop better and faster EBW variants, including the recursive EBW algorithm and statistical EBW algorithm. By using the same framework of GBW, we propose generalized discriminative feature transformation (GDFT) algorithm which transforms the constrained maximum likelihood regression (CMLLR) to perform feature space discriminative training. We compare our GDFT with the state-of-the-art feature space maximum mutual information (fMMI), and show that GDFT is competitive in accuracy and runs much faster. Based on our proposed algorithms, we introduce single pass discriminative training which aims to extract as much improvement as possible by only allowing process the data once. Our experiments show that single pass training can obtain 80-90% of the improvement available in the standard discriminative training procedure. All our proposed algorithms are evaluated on large scale speech recognition systems.
Tuning parameters across mixed dimensional instances: a performance scalability study of Sep-G-CMA-ES

Sep-G-CMA-ES is a variant of G-CMA-ES with lower time complexity. In this paper, we evaluate the impact that various ways of tuning have on the performance of Sep-G-CMA-ES on scalable continuous benchmark functions. We have extracted seven parameters from Sep-G-CMA-ES and tuned them across training functions with different features using an automatic algorithm configuration tool called Iterated F-Race. The best performance of Sep-G-CMA-ES was obtained when it was tuned using functions of different dimensionality (a strategy that we call mixed dimensional). Our comparative study on scalable benchmark functions also shows that the default Sep-G-CMA-ES outperforms G-CMA-ES. Moreover, the tuned version of Sep-G-CMA-ES significantly improves over both G-CMA-ES and default Sep-G-CMA-ES.
Smooth Collision Avoidance: Practical Issues in Dynamic Humanoid Motion

In this paper we address smooth and collision-free whole-body motion planning for humanoid robots. A two-stage iterative planning framework is introduced where geometric motion planner and dynamic pattern generator interacts by exchanging the trajectory, to obtain 3D whole-body dynamic motions simultaneous tasks including locomotion, in complex environments. We propose a practical method for smooth motion reshaping to avoid collisions in generated dynamic motion. Based on motion editing techniques in computer graphics animation, smooth collision-avoiding motion is generated through trajectory deformation. The validity of the proposed reshaping method is verified by computer simulations and experiments using humanoid platform HRP-2
Pax6 Inactivation in the Adult Pancreas Reveals Ghrelin as Endocrine Cell Maturation Marker

The transcription factor Pax6 is an important regulator of development and cell differentiation in various organs. Thus, Pax6 was shown to promote neural development in the cerebral cortex and spinal cord, and to control pancreatic endocrine cell genesis. However, the role of Pax6 in distinct endocrine cells of the adult pancreas has not been addressed. We report the conditional inactivation of Pax6 in insulin and glucagon producing cells of the adult mouse pancreas. In the absence of Pax6, beta- and alpha-cells lose their molecular maturation characteristics. Our findings provide strong evidence that Pax6 is responsible for the maturation of beta-, and alpha-cells, but not of delta-, and PP-cells. Moreover, lineage-tracing experiments demonstrate that Pax6-deficient beta- and alpha-cells are shunted towards ghrelin marked cells, sustaining the idea that ghrelin may represent a marker for endocrine cell maturation.
Interactive model‐based reconstruction of the human head using an RGB‐D sensor

We present a novel method for the interactive markerless reconstruction of human heads using a single commodity RGB‐D sensor. Our entire reconstruction pipeline is implemented on the graphics processing unit and allows to obtain high‐quality reconstructions of the human head using an interactive and intuitive reconstruction paradigm. The core of our method is a fast graphics processing unit‐based nonlinear quasi‐Newton solver that allows us to leverage all information of the RGB‐D stream and fit a statistical head model to the observations at interactive frame rates. By jointly solving for shape, albedo and illumination parameters, we are able to reconstruct high‐quality models including illumination corrected textures. All obtained reconstructions have a common topology and can be directly used as assets for games, films and various virtual reality applications. We show motion retargeting, retexturing and relighting examples. The accuracy of the presented algorithm is evaluated by a comparison against ground truth data. Copyright © 2014 John Wiley & Sons, Ltd.