Miracle-dz/UniFAR-FTUs huggingface dataset:
Embryonal subregion-derived stromal cell lines from novel temperature-sensitive SV40 T antigen transgenic mice support hematopoiesis.

Throughout life, the hematopoietic system requires a supportive microenvironment that allows for the maintenance and differentiation of hematopoietic stem cells (HSC). To understand the cellular interactions and molecules that provide these functions, investigators have previously established stromal cell lines from the late gestational stage and adult murine hematopoietic microenvironments. However, the stromal cell microenvironment that supports the emergence, expansion and maintenance of HSCs during mid-gestational stages has been largely unexplored. Since several tissues within the mouse embryo are known to harbor HSCs (i.e. aortagonads-mesonephros, yolk sac, liver), we generated numerous stromal cell clones from these mid-gestational sites. Owing to the limited cell numbers, isolations were performed with tissues from transgenic embryos containing the ts SV40 Tag gene (tsA58) under the transcriptional control of constitutive and ubiquitously expressing promoters. We report here that the growth and cloning efficiency of embryonic cells (with the exception of the aorta) is increased in the presence of the tsA58 transgene. Furthermore, our results show that the large panel of stromal clones isolated from the different embryonal subregions exhibit heterogeneity in their ability to promote murine and human hematopoietic differentiation. Despite our findings of heterogeneity in hematopoietic growth factor gene expression profiles, high-level expression of some factors may influence hematopoietic differentiation. Interestingly, a few of these stromal clones express a recently described chordin-like protein, which is an inhibitor of bone morphogenic proteins and is preferentially expressed in cells of the mesenchymal lineage.
A novel data association algorithm based on intuitionistic fuzzy clustering

In this paper, a new data association algorithm based on intuitionistic fuzzy clustering for multi-target tracking in cluttered environment was proposed. In the proposed algorithm, the joint association probabilities in JPDAF are reconstructed by utilizing the intuitionistic fuzzy membership degree of the measurement belonging to the target. In order to compute the intuitionistic fuzzy membership degree, a new intuitionistic fuzzy clustering method is proposed. At the same time, to deal with the uncertainty of the measurements, a new weight assignment is introduced. Finally, the simulation results show that the proposed algorithm is effective, and the performance of tracking is higher than the JPDAF algorithm.
Bifurcation of internal solitary wave modes from the essential spectrum

The bifurcation of internal modes from the phonon band in models supporting solitary wave solutions has been one of the exciting new phenomena in the field. We will present a number of analytical and semi-analytical techniques for the detection, study and understanding of these modes. We will see how they appear, without threshold, due to the discretization of the continuum equations. This perturbation is viewed in terms of a singular continuum approximation and analyzed by both perturbation theory and the Evans’ function method. It is shown that these methods give equivalent results. Moreover, they are corroborated by mixed analytical-numerical computations based on the discrete Evans’ function recently developed by the first author. The extent to which these predictions survive to strong discretizations are discussed. The results will be presented in the context of both the sine-Gordon and the φ models. PACS: 45.10. Hj,63.20. Pw,45.10. -b
Ambient Returns: Creative Capital's Contribution to Local Manufacturing Competitiveness

This paper addresses the possibility that competitive rural manufacturing is increasingly driven by quality-of-life factors required to attract highly skilled and creative workers. Recent findings that highly creative workers are drawn to amenity-rich rural areas provide the empirical leverage for testing anecdotal claims that these areas tend to contain small manufacturing bases that are more reliant on innovation. This contrasts with the cost advantage rationale of traditional rural manufacturing, an advantage that is eroding with increased globalization. The analysis provides the first empirical evidence that the start of entrepreneurial manufacturing plants and the adoption of advanced technologies and management practices are strongly associated with the local employment share in highly creative occupations.
Automatic detection of glaucoma in retinal images

A new method to detect glaucoma is proposed in this paper, which is based on principle components analysis (PCA) and Bayes classifier. Firstly, optic disc center is located using the combination of thresholding and distance transformation. Eigenvector spaces of normal set and glaucoma set are obtained respectively using PCA. A test image is projected onto these two spaces and the distance between projection and each template is calculated. Finally, decision is made according to Bayes classifier. The success rate of optic disk localization is 95.3% and 89.9% for normal set and glaucoma set respectively. The glaucoma detection algorithm was tested by over three hundred retinal images and the success rate is 78%.
DYSLEXIA, DYSPRAXIA and ADHD-CAN NUTRITION HELP?

There is a wide spectrum of conditions in which deficiencies of highly unsaturated fatty acids (HUFA) appear to play a role (Glen et al, 1999). This includes atopic (allergic) conditions such as eczema and asthma as well as psychiatric disorders such as schizophrenia and depression. The focus here is on the role of HUFA in three common learning and behavioural disorders dyslexia, dyspraxia and attentiondeficit / hyperactivity disorder (ADHD), although similar issues may also be relevant to the autistic spectrum (Richardson and Ross, 2000).
Sound field decomposition in reverberant environment using sparse and low-rank signal models

A sound field decomposition method for a reverberant environment is proposed. Sound field decomposition is the foundation of various acoustic signal processing applications and enables the estimation of the entire sound field from pressure measurements. Although spatial Fourier analysis of the sound field has been widely used, sparse decomposition of the sound field has recently been proved to be effective in several applications. However, in current methods, no constraints are imposed on ambiance components, whereas source components are assumed to be sparsely distributed in the space. This results in inaccurate decomposition in a reverberant environment. The proposed method is based on sparse and low-rank signal models, which are used for simultaneous decomposition of the observed signals into source and ambiance components. Numerical simulation results indicated that the decomposition accuracy is superior to that of current methods.
A ug 2 00 4 GEOMETRIC AND COMBINATORIAL REALIZATIONS OF CRYSTAL GRAPHS

For irreducible integrable highest weight modules of the finite and affine Lie algebras of type A and D, we define an isomorphism between the geometric realization of the crystal graphs in terms of irreducible components of Nakajima quiver varieties and the combinatorial realizations in terms of Young tableaux and Young walls. For type A (1) n , we extend the Young wall construction to arbitrary level, describing a combinatorial realization of the crystals in terms of new objects which we call Young pyramids.
Reconfigurable Implementation of Wavelet based Image Denoising

A reconfigurable system for denoising images based on the statistical modeling of wavelet coefficients is presented. The basic algorithm calls for approximating the noisy wavelet coefficients based on observing their local neighbourhood. The architecture for the lifting based wavelet transform followed by the windowing technique for neighbourhood observation has been implemented keeping real time applications in the picture. The architecture has regular data flow and is adaptable to arbitrary image sizes. The wavelet used is the Daubechies' 9/7 biorthogonal wavelet. The PSNR results for different test images have been presented along with hardware and timing results.
Kaleckian vs. Marxian specifications of the investment function: Some empirical evidence for the US

Following Lavoie et al. (2004), this paper empirically assesses four investment functions closing the Kaleckian baseline model in the long-run: (a) the Naive-Kaleckian specification without any long-run adjustment; (b) the Intermediate-Kaleckian specification with an endogenous adjustment of the normal utilization rate; (c) the Hysteresis-Kaleckian specification with an additional endogenous adjustment of autonomous investment; and (d) the French-Marxian specification with an exogenous normal utilization rate and endogenous autonomous investment. Confronting these specifications with data of the US manufacturing sector, we compare them with respect to the plausibility of the parameter estimates, the goodness of fit, the parameter stability, the out-of-sample performances and relative encompassing. We find the Intermediate-Kaleckian specification to be superior. For the Hysteresis-Kaleckian specification, we get implausible results which contradict Lavoie et al. (2004). Yet, their estimates seem to be biased due to endogeneity issues.
YouTouch! Low-Cost User Identification at an Interactive Display Wall

We present YouTouch! , a system that tracks users in front of an interactive display wall and associates touches with users. With their large size, display walls are inherently suitable for multi-user interaction. However, current touch recognition technology does not distinguish between users, making it hard to provide personalized user interfaces or access to private data. In our system we place a commodity RGB + depth camera in front of the wall, allowing us to track users and correlate them with touch events. While the camera's driver is able to track people, it loses the user's ID whenever she is occluded or leaves the scene. In these cases, we re-identify the person by means of a descriptor comprised of color histograms of body parts and skeleton-based biometric measurements. Additional processing reliably handles short-term occlusion as well as assignment of touches to occluded users. YouTouch! requires no user instrumentation nor custom hardware, and there is no registration nor learning phase. Our system was thoroughly tested with data sets comprising 81 people, demonstrating its ability to re-identify users and correlate them to touches even under adverse conditions.
High-resolution Structure Refinement

The ‘small-molecule’ program SHELXL is finding increased application in refinement of macromolecules against high resolution data. SHELXL is slow (compared with other macromolecular programs) but very general. Even with data to atomic resolution, restraints are still required for anisotropic refinement and handling disorder. Full-matrix refinement is useful in the initial rigid group refinement and can be used to estimate standard deviations for the final refined structure. NCS, anti-bumping and chirality restraints enable SHELXL to be employed at more moderate resolution too. The solvent model and factors affecting convergence are also
Outdoor see-through vision utilizing surveillance cameras

This paper presents a new outdoor mixed-reality system designed for people who carry a camera-attached small handy device in an outdoor scene where a number of surveillance cameras are embedded. We propose a new functionality in outdoor mixed reality that the handy device can display live status of invisible areas hidden by some structures such as buildings, walls, etc. The function is implemented on a camera-attached, small handy subnotebook PC (HPC). The videos of the invisible areas are taken by surveillance cameras and they are precisely overlapped on the video of HPC camera, hence a user can notice objects in the invisible areas and see directly what the objects do. We utilize surveillance cameras for two purposes. (1) They obtain videos of invisible areas. The videos are trimmed and warped so as to impose them into the video of the HPC camera. (2) They are also used for updating textures of calibration markers in order to handle possible texture changes in real outdoor world. We have implemented a preliminary system with four surveillance cameras and proved that our system can visualize invisible areas in real time.
Coping with International Conflict: A Systematic Approach to Influence in International Negotiation

I. INTRODUCTION. 1. Negotiation in the Context of International Conflict. 2. Thinking Like an Activist. II. UNDERSTANDING THE PROBLEM. 3. Case Study -The Middle East. 4. Understanding Partisan Perceptions. 5. The Decision from the Other Side's Point of View. 6. The View from the Bureaucracy. III. UNDERSTANDING THE TASK. 7. Case Study on Arms Control - The Antiballistic Missile Treaty. 8. Understanding the Human Dimension. 9. Building a Productive Framework for Negotiation. 10. Solving the Inventing Problem. 11. Defining Our Purpose and Strategy. IV. PUTTING IDEAS TO WORK. 12. Case Study - The Bombing Campaign in Vietnam. 13. Analyzing Threats and Sanctions. 14. Changing the Demand. 15. Legitimacy and International Law. 16. Selecting a Point of Choice. 17. Finding a "Yesable" Proposition. Index
Visualization of Macrophage Recruitment to Inflammation Lesions using Highly Sensitive and Stable Radionuclide-Embedded Gold Nanoparticles as a Nuclear Bio-Imaging Platform

Reliable and sensitive imaging tools are required to track macrophage migration and provide a better understating of their biological roles in various diseases. Here, we demonstrate the possibility of radioactive iodide-embedded gold nanoparticles (RIe-AuNPs) as a cell tracker for nuclear medicine imaging. To demonstrate this utility, we monitored macrophage migration to carrageenan-induced sites of acute inflammation in living subjects and visualized the effects of anti-inflammatory agents on this process. Macrophage labeling with RIe-AuNPs did not alter their biological functions such as cell proliferation, phenotype marker expression, or phagocytic activity. In vivo imaging with positron-emission tomography revealed the migration of labeled macrophages to carrageenan-induced inflammation lesions 3 h after transfer, with highest recruitment at 6 h and a slight decline of radioactive signal at 24 h; these findings were highly consistent with the data of a bio-distribution study. Treatment with dexamethasone (an anti-inflammation drug) or GSK5182 (an ERRγ inverse agonist) hindered macrophage recruitment to the inflamed sites. Our findings suggest that a cell tracking strategy utilizing RIe-AuNPs will likely be highly useful in research related to macrophage-related disease and cell-based therapies.
PoincarÉ Planes in Nonlinear Electronics

Details of electronic circuitry to define Poincare planes in the phase space of nonlinear electronic systems are presented. It allows an experimental setup to capture data at every moment the system's orbit crosses the Poincare plane. We illustrate how the circuit is used in an experimental setup that allows us (i) to reconstruct bifurcation cascades and to disclose induced first return chaotic maps in a harmonically forced nonlinear oscillator, and (ii) to study bistable switching in Chua's oscillator.
An Empirical Study on Optimal Correlation between Market Share and Concerns on Companies Measured through Search Engine Suggests

This paper proposes to utilize a search engine as a social sensor which is to be used for predicting market shares. More specifically, this paper studies a task of comparing rates of concerns of those who search for Web pages among several companies which supply products, given a specific products domain. In this paper, we measure concerns of those who search for Web pages through search engine suggests. Then, we analyze whether rates of concerns of those who search for Web pages have certain correlation with actual market share. Furthermore, as an intermediate statistics between the rates of concerns of those who search for Web pages and market share, we also examine correlations between the page view statistics at the kakaku.com site and the other two statistics. The results of the analysis show that those three statistics have certain correlations among each other. This paper further presents an empirical study on measuring an optimal correlation between the rates of concerns of those who search for Web pages and market share, as well as that between the rates of concerns of those who search for Web pages and the page view statistics at the kakaku.com site.
Monotone switching networks for directed connectivity are strictly more powerful than certain-knowledge switching networks

L (Logarithmic space) versus NL (Non-deterministic logarithmic space) is one of the great open problems in computational complexity theory. In the paper "Bounds on monotone switching networks for directed connectivity", we separated monotone analogues of L and NL using a model called the switching network model. In particular, by considering inputs consisting of just a path and isolated vertices, we proved that any monotone switching network solving directed connectivity on $N$ vertices must have size at least $N^{\Omega(\lg(N))}$ and this bound is tight. If we could show a similar result for general switching networks solving directed connectivity, then this would prove that $L \neq NL$. However, proving lower bounds for general switching networks solving directed connectivity requires proving stronger lower bounds on monotone switching networks for directed connectivity. To work towards this goal, we investigated a different set of inputs which we believed to be hard for monotone switching networks to solve and attempted to prove similar lower size bounds. Instead, we found that this set of inputs is actually easy for monotone switching networks for directed connectivity to solve, yet if we restrict ourselves to certain-knowledge switching networks, which are a simple and intuitive subclass of monotone switching networks for directed connectivity, then these inputs are indeed hard to solve. In this paper, we give this set of inputs, demonstrate a "weird" polynomially-sized monotone switching network for directed connectivity which solves this set of inputs, and prove that no polynomially-sized certain-knowledge switching network can solve this set of inputs, thus proving that monotone switching networks for directed connectivity are strictly more powerful than certain-knowledge switching networks.
THE RENEWABLE ENERGY INDUSTRY IN MASSACHUSETTS AS A COMPLEX SYSTEM

An abstract model of a local photovoltaic market was developed from a model-based field study. The system described by informants displays features of distributed and embedded agency: actors have the ability to take meaningful action, but that action and its effects are limited by the complexity of the system and by the actions of other actors. The structures necessary for dynamic growth are present, as expected in an industry that has had the growth of the PV market so far. Under several reasonable conditions, growth can be halted before reaching its potential: if reinforcing feedback processes saturate; if industry capacity grows too slowly; or if goals are too low or if they erode. Coordinated actions—multiple small interventions—are more effective than isolated large actions as a policy for market growth.
Semantic Interpret at ion of Nominahat ions

A computational approach to the semantic interpretation of nominalizations is described. Interpretation of nominalizations involves three tasks: deciding whether the nominalization is being used in a verbal or non-verbal sense; disambiguating the nominalized verb when a verbal sense is used; and determining the fillers of the thematic roles of the verbal concept or predicate of the nominalization. A verbal sense can be recognized by the presence of modifiers that represent the arguments of the verbal concept. It is these same modifiers which provide the semantic clues to disambiguate the nominalized verb. In the absence of explicit modifiers, heuristics are used to discriminate between verbal and nonverbal senses. A correspondence between verbs and their nominalizations is exploited so that only a small amount of additional knowledge is needed to handle the nominal form. These methods are tested in the domain of encyclopedic texts and the results are shown.
Vehicle Routing Problem with Simultaneous Pickup and Delivery in Cross-Docking Environment

 Abstract—This study will discuss the vehicle routing problem with simultaneous pickup and delivery in a cross-docking environment. The transportation system includes three stages: (1) pickup goods, (2) delivery goods and pickup returned goods, and (3) delivery all returned goods. In the second stage, some operations of stage (3) may be accepted if time and loading capacity are available. We believe this special design can further reduce the transportation cost. A mathematical model is developed. The objective of this model is to minimize overall transportation cost including the vehicle transportation cost and the fixed cost of each route. An appropriate heuristic algorithm for solving the problem is also developed by using Tabu logic. Result of numerical example indicates that the proposed three-stage transportation system and heuristic algorithm can solve the vehicle routing problem effectively and efficiently.
Survival of Patients with Hepatocellular Carcinoma (HCC) Treated by Percutaneous Radio-Frequency Ablation (RFA) Is Affected by Complete Radiological Response

Background Radio-frequency ablation (RFA) has been employed in the treatment of Barcelona Clinic Liver Cancer (BCLC) early stage hepatocellular carcinoma (HCC) as curative treatments. Aim To assess the effectiveness and the safety of RFA in patients with early HCC and compensated cirrhosis. Methods A cohort of 151 consecutive patients with early stage HCC (122 Child-Pugh class A and 29 class B patients) treated with RFA were enrolled. Clinical, laboratory and radiological follow-up data were collected from the time of first RFA. A single lesion was observed in 113/151 (74.8%), two lesions in 32/151 (21.2%), and three lesions in 6/151 (4%) of patients. Results The overall survival rates were 94%, 80%, 64%, 49%, and 41% at 12, 24, 36, 48 and 60 months, respectively. Complete response (CR) at 1 month (p<0.0001) and serum albumin levels (p = 0.0004) were the only variables indipendently linked to survival by multivariate Cox model. By multivariate analysis, tumor size (p = 0.01) is the only variable associated with an increased likehood of CR. The proportion of major complications after treatment was 4%. Conclusions RFA is safe and effective for managing HCC with cirrhosis, especially for patients with HCC ≤3 cm and higher baseline albumin levels. Complete response after RFA significantly increases survival.
An Improved Fuzzy C Means and Kathunen-Loeve Transform Method for Face Detection

An new approach based on Kathumem-Loeve(K-L) transform and improved fuzzy C means algorithm for human face detection is proposed. In the method, the image space is partitioned to primary space and subordinate space by K-L transform, by which the human face can be detected from complex scene coarsely, but how to obtain a reasonable threshold become a key problem. Generally, most scholars adopt the value of experience to distinguish face image. In this paper, in order to estimate human face, an improved fuzzy C means method is used to classify the Euclidean distance calculated by K-L transform. The result of the experiment shows that this approach can solve the problem of human face detection in scale, location, orientation and pose from complex scene.