Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Fusion Techniques at Different Domains in ImageCLEF Subtasks

In our participation in the 2009 edition of the ImageCLEF task we pursued two objectives, first to expand the number of subtasks in which we evaluate our proposed multimodal fusion presented in previous works, MultiModal Local Context Analysis (MMLCA). Furthermore, we evaluated three new proposals: a subquery generation technique based on clustering, a new variant of Multimodal Re-ranking TF-IDF (MMRR TF-IDF), finally we evaluated a term filtering technique for the medical domain which is based on WordNet Domains. [4]. From the experiments conducted: On the one hand, we have confirmed that MMLCA performs better than the other local expansion techniques evaluated. On the other hand, the results show that our proposal of subquery generation based on clustering combined with PRF obtains especially good results (the 5th best textual run of the Photo Retrieval subtask in terms of F-Meassure).
YFCC100M HybridNet fc6 Deep Features for Content-Based Image Retrieval

This paper presents a corpus of deep features extracted from the YFCC100M images considering the fc6 hidden layer activation of the HybridNet deep convolutional neural network. For a set of random selected queries we made available k-NN results obtained sequentially scanning the entire set features comparing both using the Euclidean and Hamming Distance on a binarized version of the features. This set of results is ground truth for evaluating Content-Based Image Retrieval (CBIR) systems that use approximate similarity search methods for efficient and scalable indexing. Moreover, we present experimental results obtained indexing this corpus with two distinct approaches: the Metric Inverted File and the Lucene Quantization. These two CBIR systems are public available online allowing real-time search using both internal and external queries.
Regulation of adverse remodelling by osteopontin in a genetic heart failure model.

AIMS Desmin, the muscle-specific intermediate filament protein, is a major target in dilated cardiomyopathy and heart failure in humans and mice. The hallmarks of desmin-deficient (des(-/-)) mice pathology include pronounced myocardial degeneration, extended fibrosis, and osteopontin (OPN) overexpression. We sought to identify the molecular and cellular events regulating adverse cardiac remodelling in des(-/-) mice and their potential link to OPN. METHODS AND RESULTS In situ hybridization, histology, and immunostaining demonstrated that inflammatory cells and not cardiomyocytes were the source of OPN. RNA profile comparison revealed that activation of inflammatory pathways, sustained by innate immunity mechanisms, predominated among all changes occurring in degenerating des(-/-) myocardium. The expression of the most highly up-regulated genes (OPN: 226×, galectin-3: 26×, osteoactivin/Gpnmb/DC-HIL: 160× and metalloprotease-12: 98×) was associated with heart infiltrating macrophages. To evaluate the role of OPN, we generated des(-/-)OPN(-/-) mice and compared their cardiac function and remodelling indices with those of des(-/-). Osteopontin promoted cardiac dysfunction in this model since des(-/-)OPN(-/-) mice showed 53% improvement of left ventricular function, paralleled to an up to 44% reduction in fibrosis. The diminished fibrotic response in the absence of OPN could be partly mediated by a dramatic reduction in myocardial galectin-3 levels, associated with an impaired galectin-3 secretion by OPN-deficient infiltrating macrophages. CONCLUSION Cardiomyocyte death due to desmin deficiency leads to inflammation and subsequent overexpression of a series of remodelling modulators. Among them, OPN seems to be a major regulator of des(-/-) adverse myocardial remodelling and it functions at least by potentiating galectin-3 up-regulation and secretion.
Contemporary Challenges for a Social Signal processing

This paper provides a short overview of Social Signal Processing. The exploration of how we react to the world and interact with it and each other remains one of the greatest scientific challenges. Latest research trends in cognitive sciences argue that our common view of intelligence is too narrow, ignoring a crucial range of abilities that matter immensely for how people do in life. This range of abilities is called social intelligence and includes the ability to express and recognize social signals produced during social interactions like agreement, politeness, empathy, friendliness, conflict, etc., coupled with the ability to manage them in order to get along well with others while winning their cooperation. Social Signal Processing (SSP) is the new research domain that aims at understanding and modeling social interactions (human-science goals), and at providing computers with similar abilities in human-computer interaction scenarios (technological goals). SSP is in its infancy and the journey towards artificial social intelligence and socially-aware computing is still long, the paper outlines its future perspectives and some of its most promising applications .
Agent-Based Computational Economics - An Introduction

Terming a specific approach to economics agent-based may appear paradoxical. Isn’t human behavior the foundation of economics and shouldn’t all economic theory be based on agents behavior in some sense? This, at least, is what conventional economic theory has been claiming since the 1970’s. In this introduction we shall argue that agent-based computational economics (ACE) allows agents and especially their interaction, a more pivotal role than does conventional microeconomics or microfounded theory. There is a difference between microeconomics and agent-based economics in the latter you are not satisfied with understanding exactly how a single agent acts in economic markets you are primarily interested in the system view that arises when you observe the interaction between a number of agents. From observing an isolated agent, it is impossible to foresee what happens when a multitude of agents interact it cannot be deduced. This adds importance to the computational part. In agent-based economics the computer is not merely used as a giant calculator finding analytical or numerical solutions, but is used as a central part in a new methodological approach to economics.
Amperometric Sensor for Detection of Chloride Ions†

Chloride ion sensing is important in many fields such as clinical diagnosis, environmental monitoring and industrial applications. We have measured chloride ions at a carbon paste electrode (CPE) and at a CPE modified with solid AgNO3, a solution of AgNO3 and/or solid silver particles. Detection limits (3 S/N) for chloride ions were 100 μM, 100 μM and 10 μM for solid AgNO3, solution of AgNO3 and/or solid silver particles, respectively. The CPE modified with silver particles is the most sensitive to the presence chloride ions. After that we approached to the miniaturization of the whole electrochemical instrument. Measurements were carried out on miniaturized instrument consisting of a potentiostat with dimensions 35 × 166 × 125 mm, screen printed electrodes, a peristaltic pump and a PC with control software. Under the most suitable experimental conditions (Britton-Robinson buffer, pH 1.8 and working electrode potential 550 mV) we estimated the limit of detection (3 S/N) as 500 nM.
The Method of Predicting Average Response Time of Cloud Service Based on MGM (1, N) - BP Neural Network

In the cloud computing environment, according to the predicting average response time of service, it can adjust to the follow-up system, so that the response time of the system is acceptable. The traditional methods of predicting average response time of serve mainly include the method of gray predicting and neural network model, but the two methods face several problems, such as longer processing time and unsuitable to larger volatility data. According to the above problems, the paper proposes the method of predicting average response time of cloud service based on the MGM (1, N) - BP neural network, the combination of two methods of predicting can use less sample information, it can get a high precision of predicting result and it can also predict the volatile system. Experimental results show the feasibility and effectiveness of the method.
A Dictionary of Finance and Banking

This best-selling Dictionary of Finance and Banking includes over 5,200 entries. The fifth edition has been fully revised and updated, and adds more than 150 new entries. These focus particularly upon recent terminology, institutions, and safety measures coined or introduced since the economic crash of 2008-9, including reactions to the crisis such as the Asset Protection Scheme and the Financial Stability Oversight Council. The dictionary defines terms from all aspects of personal and international finance, including money markets, private investments and borrowing, central banking, foreign exchanges, monetary policy, and public and government finance. Now with expanded coverage of capital structure and corporate restructuring. Recommended up-to-date web links for many entries, accessed via the Dictionary of Finance and Banking website, provide valuable extra information. With clear and accessible definitions, this jargon-free dictionary is a companion volume to the other financial titles in this best-selling series, A Dictionary of Business and Management, A Dictionary of Accounting, and A Dictionary of Economics, and provides accurate and valuable information for students, practitioners, private investors, and readers of the financial pages alike.
A snake-like swimming robot using IPMC actuator and verification of doping effect

Ionic polymer metal composite (IPMC) is one of the most promising EAF actuators for applications, and slave good property of response and durability. The characteristics of IPMC materials depend on a type of counter ion. In applying to mechanical systems such as a robot, there exist possibilities to change the properties of the dynamics by changing the counter ions according to environment or purpose adequately. In this paper, we consider swimming of a snake-like robot with IPMC actuator, and demonstrate a smooth swimming motion. Then, we also verify the doping effects by experiments.
Measurement Scheme for One‐Way Delay Variation with Detection and Removal of Clock Skew

One‐way delay variation (OWDV) has become increasingly of interest to researchers as a way to evaluate network state and service quality, especially for real‐time and streaming services such as voice‐over‐Internet‐protocol (VoIP) and video. Many schemes for OWDV measurement require clock synchronization through the global‐positioning system (GPS) or network time protocol. In clock‐synchronized approaches, the accuracy of OWDV measurement depends on the accuracy of the clock synchronization. GPS provides highly accurate clock synchronization. However, the deployment of GPS on legacy network equipment might be slow and costly. This paper proposes a method for measuring OWDV that dispenses with clock synchronization. The clock synchronization problem is mainly caused by clock skew. The proposed approach is based on the measurement of inter‐packet delay and accumulated OWDV. This paper shows the performance of the proposed scheme via simulations and through experiments in a VoIP network. The presented simulation and measurement results indicate that clock skew can be efficiently measured and removed and that OWDV can be measured without requiring clock synchronization.
Multimedia Fatigue Detection for Adaptive Infotainment User Interface

Current vehicles are equipped with user interfaces that assist the drivers by presenting essential information such as navigation, speed limit, etc. In this work we present a fatigue detection model in order to build an adaptive user interface for vehicles that changes its properties according to the fatigue level of the driver. When the driver is fatigued, the interface parameters, such as intensity and color combination, are modulated to make the user interface more attentive and intrusive. At other times, when the driver is not fatigued, the interface properties are optimized for aesthetics and pleasure. In this way, the adaptive interface provides a warning to the driver while she is fatigued along with the routine essential information. We take a multimedia approach to measure fatigue by analysing the driver behaviour. The system captures driver behaviour with four media streams that capture: angular velocity of steering wheel, force on brake pedal, force on gas pedal, and grip force. These continuous media stream are fused together with other contextual parameters to detect fatigue. In the experiments, we evaluate two fusion techniques and 16 media stream combinations. It is found that the fatigue detection accuracy increases almost linearly with number of media streams fused. We also found that the steering wheel provides best cue of fatigue, while the gas pedal provides weakest cue. Personalized Bayesian Networks further enhance the accuracy.
Sentential Paraphrase Generation for Agglutinative Languages Using SVM with a String Kernel

Paraphrase generation is widely used for various natural language processing (NLP) applications such as question answering, multi-document summarization, and machine translation. In this study, we identify the problems occurring in the process of applying existing probabilistic model-based methods to agglutinative languages, and provide solutions by reflecting the inherent characteristics of agglutinative languages. More specifically, we propose and evaluate a sentential paraphrase generation (SPG) method for the Korean language using Support Vector Machines (SVM) with a string kernel. The quality of generated paraphrases is evaluated using three criteria: (1) meaning preservation, (2) grammaticality, and (3) equivalence. Our experiment shows that the proposed method outperformed a probabilistic model-based method by 12%, 16%, and 17%, respectively, with respect to the three criteria.
Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems

We provide estimates of the warming of the world ocean for 1955–2008 based on historical data not previously available, additional modern data, correcting for instrumental biases of bathythermograph data, and correcting or excluding some Argo float data. The strong interdecadal variability of global ocean heat content reported previously by us is reduced in magnitude but the linear trend in ocean heat content remain similar to our earlier estimate.
Urban policy for renewable energy : case studies of New York and London

Despite growing attention to the issue of urban 'sustainability' and steady increases in the overall use of different renewable power technologies around the world, cities tend to have very low levels of 'green' power use or renewables technology deployment within their borders. Through field interviews and literature reviews, this thesis examines the factors that both help and hinder this situation, using New York City and London as case studies. New institutionalism and urban regime theories provide the analytical lenses through which the empirical research is viewed. Each theory examines this issue from a different perspective, with new institutionalism particularly adept at identifying explanations linked to the electric power sector's highly regulated policy environment. Urban regime theory (URT) emphasizes understanding who is involved in the policy-making and implementation process, and how their involvement influences any outcomes. Originally, URT was developed to analyze urban growth coalitions and other urban economic development activities, although researchers have more recently posited its applicability to a wide range of fields, including urban environmental policy-making. When examining energy policy-making in both London and New York, however, a traditional URT approach falls short because it does not easily accommodate the influence of formal regulatory mechanisms in shaping outcomes. By modifying URT, however, so it adopts aspects of a new institutionalist approach, highly compelling and comprehensive explanations for local energy policy and program decisions can be obtained. This thesis concludes by detailing circumstances under which this type of "Constrained" regime analysis is appropriate, and how its methodology differs from that of traditional urban regime theory.
Responses of Phosphate Transporter Gene and Alkaline Phosphatase in Thalassiosira pseudonana to Phosphine

Phosphine, which is released continuously from sediment, can affect the eco-physiological strategies and molecular responses of phytoplankton. To examine the effects of phosphine on phosphorus uptake and utilization in Thalassiosira pseudonana, we examined the transcriptional level of the phosphate transporter gene (TpPHO) and the activity of alkaline phosphatase (AKP) in relation to supplement of various concentrations of phosphine. TpPHO expression was markedly promoted by phosphine in both the phosphate-deficient and phosphate-4 µM culture. However, high phosphine concentrations can inhibit TpPHO transcription in the declining growth phase. AKP activity was also higher in the phosphine treatment groups than that of the control. It increased with increasing phosphine concentration in the range of 0 to 0.056 µM but was inhibited by higher levels of phosphine. These responses revealed that phosphine can affect phosphate uptake and utilization in T. pseudonana. This result was consistent with the effect of phosphine on algal growth, while TpPHO expression and AKP were even more sensitive to phosphine than algal growth. This work provides a basic understanding for further research about how phosphine affects phytoplankton.
Berberine Promotes Glucose Consumption Independently of AMP-Activated Protein Kinase Activation

Berberine is a plant alkaloid with anti-diabetic action. Activation of AMP-activated protein kinase (AMPK) pathway has been proposed as mechanism for berberine’s action. This study aimed to examine whether AMPK activation was necessary for berberine’s glucose-lowering effect. We found that in HepG2 hepatocytes and C2C12 myotubes, berberine significantly increased glucose consumption and lactate release in a dose-dependent manner. AMPK and acetyl coenzyme A synthetase (ACC) phosphorylation were stimulated by 20 µmol/L berberine. Nevertheless, berberine was still effective on stimulating glucose utilization and lactate production, when the AMPK activation was blocked by (1) inhibition of AMPK activity by Compound C, (2) suppression of AMPKα expression by siRNA, and (3) blockade of AMPK pathway by adenoviruses containing dominant-negative forms of AMPKα1/α2. To test the effect of berberine on oxygen consumption, extracellular flux analysis was performed in Seahorse XF24 analyzer. The activity of respiratory chain complex I was almost fully blocked in C2C12 myotubes by berberine. Metformin, as a positive control, showed similar effects as berberine. These results suggest that berberine and metformin promote glucose metabolism by stimulating glycolysis, which probably results from inhibition of mitochondrial respiratory chain complex I, independent of AMPK activation.
What Works Clearinghouse April 2011 WWC Quick Review of the Report “ Teacher Pay for Performance : Experimental Evidence From the Project on Incentives in Teaching ”

present previously published journal articles, book chapters, and reports with the permission of the publisher. RAND reprints have been formally reviewed in accordance with the publisher’s editorial policy, and are compliant with RAND’s rigorous quality assurance standards for quality and objectivity. This PDF document was made available from www.rand. org as a public service of the RAND Corporation.
On the Political Economy of Financial Reform

This paper studies what induces governments to undertake reforms aimed at financial development. Its starting point is Abiad and Mody (AER 95(1), 2005). Rather than their ordered logit technique, it uses a within groups approach allowing for error dependence across countries and over time. This paper finds that policy change in a country is negatively rather than positively associated with its liberalization level, while the regional liberalization gap does not appear relevant. On the effects of shocks and crises, it suggests that some of the Abiad and Mody (2005) findings are robust, but others are fragile. Furthermore, it claims that the extent of democracy is important for this analysis, and identifes a negative effect of the extent of democracy on policy reform.
Layered architecture for mobile web based applications

Mobile and other PDA devices allow us to access the World Wide Web anytime and anywhere. Developing dynamic web based applications for mobile devices is a challenging task, because these devices have limited computational resource such as CPU and Physical Memory. In order to overcome these limitations, we proposed layered architecture for the development of mobile web applications. This paper describes the architecture, design and implementation details. Experimental results demonstrate that proposed architecture can effectively reduce client side resource utilization by mobile web applications.
The Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR/LAI)

The aims are to validate and assess the performances of MODIS gross primary production (MODIS-GPP) and evapotranspiration (MODIS-ET) products in China's different land cover types and their sensitivity to remote sensing input data. In this study, MODIS-GPP and -ET are evaluated using flux derived/measured data from eight sites of ChinaFLUX. Results show that MODIS-GPP generally underestimates GPP (R 2 is 0.58, bias is −6.7 gC/m 2 /8-day and RMSE is 19.4 gC/m 2 /8-day) at all sites and MODIS-ET overestimates ET (R 2 is 0.36, bias is 6 mm/8-day and RMSE is 11 mm/8-day) when comparing with derived GPP and measured ET, respectively. For evergreen forests, MODIS-GPP gives a poor performance with R 2 varying from 0.03 to 0.44; in contrast, MODIS-ET provides more reliable results. In croplands, MODIS-GPP can explain 80% of GPP variance, but it overestimates flux derived GPP in non-growing season and underestimates flux derived GPP in growing season; similar overestimations also presented in MODIS-ET. For grasslands and mixed forests, MODIS-GPP and -ET perform good estimating accuracy. By designing four experimental groups and taking GPP simulation as an example, we suggest that the maximum light use efficiency of croplands should be optimized, and the differences of meteorological data have little impact on GPP estimation, whereas remote sensing leaf area index/fraction of photo-synthetically active radiation (LAI/FPAR) can greatly affect GPP/ET estimations for all land cover types. Thus, accurate remote sensing parameters are important for achieving reliable estimations.