Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Output Kernels with Block Coordinate Descent

We propose a method to learn simultaneously a vector-valued function and a kernel between its components. The obtained kernel can be used both to improve learning performance and to reveal structures in the output space which may be important in their own right. Our method is based on the solution of a suitable regularization problem over a reproducing kernel Hilbert space of vector-valued functions. Although the regularized risk functional is non-convex, we show that it is invex, implying that all local minimizers are global minimizers. We derive a block-wise coordinate descent method that efficiently exploits the structure of the objective functional. Then, we empirically demonstrate that the proposed method can improve classification accuracy. Finally, we provide a visual interpretation of the learned kernel matrix for some well known datasets.
Evaluation of anisotropic small-angle neutron scattering data from metastable β-Ti alloy

ABSTRACT Small-angle neutron scattering (SANS) data from single-crystal metastable β-Ti alloys exhibit an anisotropic character with interparticle interference maxima due to ordering of the dense system of ω particles. For an evaluation of such data, the program NOC (previously used for evaluation of data from dense ordered γ′ precipitate system in single-crystal nickel-based superalloys) was well suited. Nevertheless, an improvement of this evaluation program was necessary in its model-forming part. A further change of the evaluation program concerned the mode in which the size distribution was calculated. This upgrade is presented. The improved NOC program was employed for the evaluation of SANS data of annealed metastable single-crystal β-Ti alloy containing ω particles. 3D fit in reciprocal space was successfully used. A model of ellipsoids did not lead to a better fit than a model of particles with the spherical shape. The microstructural parameters of ω particles were determined.
CYP450 Enzyme-Mediated Metabolism of TCAS and Its Inhibitory and Induced Effects on Metabolized Enzymes in Vitro

In this study, we investigated the enzymes catalyzing the phaseⅠmetabolism of thiacalixarene (TCAS) based on in vitro system including cDNA-expressed P450 enzymes, human liver microsomes plus inhibitors and monoclonal antibodies. In addition, the inhibitory potential of TCAS on major CYP450 drug metabolizing enzymes (CYP1A2, CYP2C9, CYP2B6, CYP2D6 and CYP3A4) was assessed. The results showed that CYP1A2 and CYP2C9 mediated TCAS hydroxylation. IC50 values for TCAS in rat and human liver microsomes were greater than 50 µM, and it demonstrated a weak inhibition of rat and human CYP450 enzymes. Finally, sandwiched hepatocytes were used to evaluate the induction of CYP1A and CYP3A to define the function of TCAS in vivo. The results showed that incubation of TCAS at different concentrations for 72 h failed to induce CYP1A and CYP3A. However, incubation of the cells with 50 and 100 µM TCAS caused a profound decrease in the activities of CYP1A and CYP3A, which was probably due to cytotoxic effects, suggesting that exposure to TCAS might be a health concern.
Low-Carbon Transport Policy in ASEAN Countries: A Comparative Analysis

Emerging countries in Southeast Asia are facing considerable challenges in addressing rising motorisation and its negative impact on air quality, traffic, energy security, liveability, and greenhouse gas emissions. Indeed, even as initial policies to address these issues are being agreed and implemented, current trends are incompatible with sustainable development and long-term climate change targets. This paper presents a comparative analysis of the approach and status of sustainable, low-carbon transport policy in ASEAN countries and identifies differences and similarities, with the aim of helping assessment of feasibility of future policies and informing future studies on policy innovations and cross-country learning. The methodology is based on the taxonomy of policy components developed by Howlett and Cashore, and our data on comprehensive country studies for Indonesia, the Philippines, Thailand and Vietnam and interviews. We find that each country has a specific set of goals, objectives and targets that support sustainable transport, and, directly or indirectly, climate change mitigation. In terms of specific instruments and calibrations, which we analyse based on the Avoid-Shift-Improve approach, there are notable differences between the countries, for example in fuel economy policy.
Differences in Knowledge of Breast Cancer Screening Among African American, Arab American, and Latina Women

Introduction We examined differences in knowledge and socioeconomic factors associated with 3 types of breast cancer screening (breast self-examination, clinical breast examination, and mammogram) among African American, Arab, and Latina women. Methods Community health workers used a community-based intervention to recruit 341 women (112 Arab, 113 Latina, and 116 African American) in southeastern Michigan to participate in a breast cancer prevention intervention from August through October 2006. Before and after the intervention, women responded to a previously validated 5-item multiple-choice test on breast cancer screening (possible score range: 0 to 5) in their language of preference (English, Spanish, or Arabic). We used generalized estimating equations to analyze data and to account for family-level and individual correlations. Results Although African American women knew more about breast cancer screening at the baseline (pretest median scores were 4 for African American, 3 for Arab and 3 for Latina women), all groups significantly increased their knowledge after participating in the breast cancer prevention intervention (posttest median scores were 5 for African American and 4 for Arab and Latina women). Generalized estimating equations models show that Arab and Latina women made the most significant gains in posttest scores (P < .001). Conclusion Racial/ethnic differences in knowledge of breast cancer screening highlight the need for tailored information on breast cancer screening for African American, Arab, and Latina women to promote adherence to breast cancer screening guidelines.
Exploiting Multi-Spatial Correlations of Motion Data in a Body Sensor Network

Human body motions usually exhibit a high degree of coherence and correlation in patterns. This allows exploiting spatial correlations of motion data being captured by a body sensor network. Since human bodies are relatively small, earlier work has shown how to compress motion data by allowing a node to overhear at most κ = 1 node's transmission and exploit the correlation with its own data for data compression. In this work, we consider multi-spatial correlations by extending κ = 1 to κ >; 1 and constructing a partial-ordering directed acyclic graph (DAG) to represent the compression dependencies among sensor nodes. While a minimum-cost tree for κ = 1 can be found in polynomial time, we show that finding a minimum-cost DAG is NP-hard even for κ = 2. We then propose an efficient heuristic and verify its performance by real sensing data.
Generation of Functional Ventricular Heart Muscle from Mouse Ventricular Progenitor Cells

A Fix to the Heart Regenerative cardiovascular medicine is a promising avenue for therapeutic application in advanced heart failure. Although clinical trials have suggested some limited benefits in cell transplantation therapy, robust cardiac muscle formation is lacking. Domian et al. (p. 426) examined the developmental processes in normal mature cardiac muscle. A two-color murine reporter system was used to isolate committed ventricular progenitors, which were then used to build functional force-generating cardiac tissue. Such combinations of tissue engineering and stem cell biology may eventually lead to cardiac regenerative therapy. A combination of tissue engineering and stem cell biology is used to build functional force-generating mouse cardiac tissue. The mammalian heart is formed from distinct sets of first and second heart field (FHF and SHF, respectively) progenitors. Although multipotent progenitors have previously been shown to give rise to cardiomyocytes, smooth muscle, and endothelial cells, the mechanism governing the generation of large numbers of differentiated progeny remains poorly understood. We have employed a two-colored fluorescent reporter system to isolate FHF and SHF progenitors from developing mouse embryos and embryonic stem cells. Genome-wide profiling of coding and noncoding transcripts revealed distinct molecular signatures of these progenitor populations. We further identify a committed ventricular progenitor cell in the Islet 1 lineage that is capable of limited in vitro expansion, differentiation, and assembly into functional ventricular muscle tissue, representing a combination of tissue engineering and stem cell biology.
Optimal sizing of generalized memory polynomial model structure based on Hill-Climbing heuristic

Digital Predistortion (DPD) is used to compensate the nonlinearities and memory effects of the Power Amplifiers (PA). Generalized Memory Polynomial (GMP) is usually applied for PA as well as predistorter modeling. However there are very huge number of different GMP model structures. In this paper, we propose an algorithm based on Hill-Climbing algorithm to search for the GMP model structure which provides the best tradeoff between modeling accuracy and its complexity. The proposed method has been evaluated on real Doherty Power Amplifier. The results show that the proposed algorithm allows to decrease the searching time by a factor typically greater than 104.
Variational formulas and disorder regimes of random walks in random potentials

We give two variational formulas (qVar1) and (qVar2) for the quenched free energy of a random walk in random potential (RWRP) when (i) the underlying walk is directed or undirected, (ii) the environment is stationary and ergodic, and (iii) the potential is allowed to depend on the next step of the walk which covers random walk in random environment (RWRE). In the directed i.i. d. case, we also give two variational formulas (aVar1) and (aVar2) for the annealed free energy of RWRP. These four formulas are the same except that they involve infima over different sets, and the first two are modified versions of a previously known variational formula (qVar0) for which we provide a short alternative proof. Then, we show that (qVar0) always has a minimizer, (aVar2) never has any minimizers unless the RWRP is an RWRE, and (aVar1) has a minimizer if and only if the RWRP is in the weak disorder regime. In the latter case, the minimizer of (aVar1) is unique and it is also the unique minimizer of (qVar1), but (qVar2) has no minimizers except for RWRE. In the case of strong disorder, we give a sufficient condition for the nonexistence of minimizers of (qVar1) and (qVar2) which is satisfied for the log-gamma directed polymer with a sufficiently small parameter. We end with a conjecture which implies that (qVar1) and (qVar2) have no minimizers under very strong disorder.
Outward-Looking Circular Motion Analysis of Large Image Sequences

This paper presents a novel and simple method of analyzing the motion of a large image sequence captured by a calibrated outward-looking video camera moving on a circular trajectory for large-scale environment applications. Previous circular motion algorithms mainly focus on inward-looking turntable-like setups. They are not suitable for outward-looking motion where the conic trajectory of corresponding points degenerates to straight lines. The circular motion of a calibrated camera essentially has only one unknown rotation angle for each frame. The motion recovery for the entire sequence computes only one fundamental matrix of a pair of frames to extract the angular motion of the pair using Laguerre's formula and then propagates the computation of the unknown rotation angles to the other frames by tracking one point over at least three frames. Finally, a maximum-likelihood estimation is developed for the optimization of the whole sequence. Extensive experiments demonstrate the validity of the method and the feasibility of the application in image-based rendering.
Hyperspectral Image Compression Optimized for Spectral Unmixing

In this paper, we present a new lossy compression method for hyperspectral images that aims to optimally compress in both spatial and spectral domains and simultaneously minimizes the effect of the compression on linear spectral unmixing performance. To achieve this, a nonnegative Tucker decomposition is applied. This decomposition is a function of three dimension parameters. By employing a link between this decomposition and the linear spectral mixing model, an optimization problem is defined to find the optimal parameters by minimizing the root-mean-square error between the abundance matrices of the original and reconstructed data sets. The resulting optimization problem is solved by a particle swarm optimization algorithm. An approximate method for fast estimation of the free parameters is introduced as well. Our simulation results show that, in comparison with well-known state-of-the-art lossy compression methods, an improved compression and spectral unmixing performance of the reconstructed hyperspectral image is obtained. It is noteworthy to mention that the superiority of our method becomes more apparent as the compression ratio grows.
Tight regulation, modulation, and high-level expression by vectors containing the arabinose PBAD promoter

We have constructed a series of plasmid vectors (pBAD vectors) containing the PBAD promoter of the araBAD (arabinose) operon and the gene encoding the positive and negative regulator of this promoter, araC. Using the phoA gene and phoA fusions to monitor expression in these vectors, we show that the ratio of induction/repression can be 1,200-fold, compared with 50-fold for PTAC-based vectors. phoA expression can be modulated over a wide range of inducer (arabinose) concentrations and reduced to extremely low levels by the presence of glucose, which represses expression. Also, the kinetics of induction and repression are very rapid and significantly affected by the ara allele in the host strain. Thus, the use of this system which can be efficiently and rapidly turned on and off allows the study of important aspects of bacterial physiology in a very simple manner and without changes of temperature. We have exploited the tight regulation of the PBAD promoter to study the phenotypes of null mutations of essential genes and explored the use of pBAD vectors as an expression system.
Printer-friendly Version Interactive Discussion Air–sea Co 2 Fluxes and the Controls on Ocean Surface Pco 2 Variability in Coastal and Open-ocean Southwestern Atlantic Ocean: a Modeling Study Printer-friendly Version Interactive Discussion Bgd Printer-friendly Version Interactive Discussion

This discussion paper is/has been under review for the journal Biogeosciences (BG). Please refer to the corresponding final paper in BG if available. Abstract We use an eddy-resolving, regional ocean biogeochemical model to investigate the main variables and processes responsible for the climatological spatio-temporal variability of pCO 2 and the air–sea CO 2 fluxes in the southwestern Atlantic Ocean. Overall, the region acts as sink of atmospheric CO 2 south of 30 • S, and is close to equilibrium 5 with the atmospheric CO 2 to the north. On the shelves, the ocean acts as a weak source of CO 2 , except for the mid/outer shelves of Patagonia, which act as sinks. In contrast, the inner shelves and the low latitude open ocean of the southwestern Atlantic represent source regions. Observed nearshore-to-offshore and meridional pCO 2 gradients are well represented by our simulation. A sensitivity analysis shows the im-10 portance of the counteracting effects of temperature and dissolved inorganic carbon (DIC) in controlling the seasonal variability of pCO 2. Biological production and solubil-ity are the main processes regulating pCO 2 , with biological production being particularly important on the shelf regions. The role of mixing/stratification in modulating DIC, and therefore surface pCO 2 is shown in a vertical profile at the location of the Ocean 15 Observatories Initiative (OOI) site in the Argentine Basin (42 • S, 42 • W).
Word-level prosody in Sotho-Tswana

We introduce an algorithm to derive word-level tone assignments for the Sotho-Tswana languages. Prerequisite inputs are identified, and the steps to transform these inputs to tone assignments for each syllable are described. Manual implementation of the algorithm shows very good agreement with tone levels measured in a small Sotho-Tswana corpus.
Semi-Supervised Learning of a Pronunciation Dictionary from Disjoint Phonemic Transcripts and Text

While the performance of automatic speech recognition systems has recently approached human levels in some tasks, the application is still limited to specific domains. This is because system development relies on extensive supervised training and expert tuning in the target domain. To solve this problem, systems must become more self-sufficient, having the ability to learn directly from speech and adapt to new tasks. One open question in this area is how to learn a pronunciation dictionary containing the appropriate vocabulary. Humans can recognize words, even ones they have never heard before, by reading text and understanding the context in which a word is used. However, this ability is missing in current speech recognition systems. In this work, we propose a new framework that automatically expands an initial pronunciation dictionary using independently sampled acoustic and textual data. While the task is very challenging and in its initial stage, we demonstrate that a model based on Bayesian learning of Dirichlet processes can acquire word pronunciations from phone transcripts and text of the WSJ data set.
Understanding and Modelling the Impact of Climate Change on Infectious Diseases – Progress and Future Challenges

The effects of global change on human health have attracted increasing attention in recent years, with anthropogenic influences thought to have significant influences on the Earth’s climate (Intergovernmental Panel on Climate Change [IPCC], 2007). Climate change is thought likely to have important effects on human, animal and plant life. In addition to indirect effects on human behaviour such as shifting migration patterns, direct effects of climate change on human health are potentially severe. Together with implications through changing air quality, increased exposure to UV radiation, changes in food production, increasing water shortages and contamination, and economic instability, climate change is widely expected to also significantly affect the global spread, intensity and distribution of infectious diseases (Hunter, 2003; McMichael et al., 2006). In this chapter, we review current knowledge on the impacts of global change on infectious diseases (Section 1), highlighting how combining global and regional climate models with mathematical (and statistical) models of disease transmission (Section 2) provides valuable tools for better understanding future disease scenarios as environmental conditions change. Such models may be used to address important questions on the current and projected impacts of climate change on disease transmission and we illustrate these issues (and the extent to which they have been addressed in modelling work to date) in Section 3. It should be remembered, however, that despite the power of weather, climate and disease models, considerable uncertainties remain. Identifying the origin of these uncertainties, highlighting where improved data may improve model accuracy, realism and confidence, together with translating uncertainties in model inputs into uncertainties in model outputs, are important benefits of modelling. Highlighting where key uncertainties lie is discussed in Section 4, illustrating where future research priorities may be directed to further our understanding of this emerging field.
Regional Differences in Ventricular Fibrillation in the Open-Chest Porcine Left Ventricle

Abstract— It has been hypothesized that during ventricular fibrillation (VF), the fastest activating region, the dominant domain, contains a stable reentrant circuit called a mother rotor. This hypothesis postulates that the mother rotor spawns wavefronts that propagate to maintain VF elsewhere and implies that the ratio of wavefronts propagating off a region to those propagating onto it (propoff/propon) should be >1 for the dominant domain but <1 elsewhere. To test this prediction in the left ventricular (LV) epicardium of a large animal, most of the LV free wall was mapped with 1008 electrodes in 7 pigs. VF activation rate was faster in the posterior than in the anterior LV (10.0±1.3Hz versus 9.3±1.3Hz;P <0.001). The anterior LV had a higher fraction of wavefronts that blocked than did the posterior LV and had a propoff/propon ratio <1 (P <0.001). The mean conduction velocity vectors of the VF wavefronts pointed in the direction from the posterior to the anterior LV. Although these findings favor a dominant domain in the posterior LV, the facts that the anterior LV had a higher incidence of reentry than did the posterior LV and that the posterior LV did not have propoff/propon significantly different from 1 do not. Thus, quantitative regional differences are present over the porcine LV epicardium during VF. Although these differences are not totally consistent with the presence of a dominant domain within the LV free wall, the mean conduction velocity vector is consistent with one in the septum.
3D Holographic Millimeter-Wave Imaging for Concealed Metallic Forging Objects Detection

This chapter investigates the feasibility of using 3D holographic millimeter-wave (HMMW) imaging for diagnosis of concealed metallic forging objects (MFOs) in inhomogeneous medium. A 3D numerical system, including radio frequency (RF) transmitters and detectors, various realistic MFOs models and signal and imaging processing, is developed to analyze the measured data and reconstruct images of target MFOs. Simulation and experimental validations are performed to evaluate the HMMW approach for diagnosis of concealed MFOs. Results show that various concealed objects can be clearly represented in the reconstructed images with accurate sizes, locations and shapes. The proposed system has the potential for further investigation of concealed MFOs under clothing in the future, which has the potential applications in on body concealed weapon detection at security sites or MFOs detection in children.
MIPMANET: mobile IP for mobile ad hoc networks

Mobile ad hoc networking allows nodes to form temporary networks and communicate beyond transmitter range by supporting multihop communication through IP routing. Routing in such networks is often reactive, i.e., performed on-demand, as opposed to Internet routing that is proactive. As ad hoc networks are formed on a temporary basis, any IP address should be allowed to appear in an ad hoc network.This paper presents MIPMANET, a solution for connecting an ad hoc network, in which on-demand routing is used, to the Internet. MIPMANET provides Internet access by using Mobile IP with foreign agent care-of addresses and reverse tunneling. This allows nodes to enjoy the mobility services of Mobile IP while at the same time the requirements on the ad hoc routing protocol are kept to a minimum.Simulations of MIPMANET have been performed in Network Simulator 2. The Ad hoc On-demand Distance Vector (AODV) routing protocol has been used for routing within the ad hoc network. These simulations show that the ability to choose the closest access point to the Internet is worth extra work, as less traffic is generated in the network resulting in lower delays and fewer dropped packets.