Solving ill-posed bilevel programs

This paper deals with ill-posed bilevel programs, i.e., problems admitting multiple lower-level solutions for some upper-level parameters. Many publications have been devoted to the standard optimistic case of this problem, where the difficulty is essentially moved from the objective function to the feasible set. This new problem is simpler but there is no guaranty to obtain local optimal solutions for the original optimistic problem by this process. Considering the intrinsic non-convexity of bilevel programs, computing local optimal solutions is the best one can hope to get in most cases. To achieve this goal, we start by establishing an equivalence between the original optimistic problem an a certain set-valued optimization problem. Next, we develop optimality conditions for the latter problem and show that they generalize all the results currently known in the literature on optimistic bilevel optimization. Our approach is then extended to multiobjective bilevel optimization, and completely new results are derived for problems with vector-valued upper- and lower-level objective functions. Numerical implementations of the results of this paper are provided on some examples, in order to demonstrate how the original optimistic problem can be solved in practice, by means of a special set-valued optimization problem

Clinical-Grade Human Embryonic Stem Cell-Derived Mesenchymal Stromal Cells Ameliorate the Progression of Osteoarthritis in a Rat Model

Mesenchymalstem cell (MSC)-based therapy is being increasingly explored in preclinical and clinical studies as a regenerative method for treating osteoarthritis (OA). However, the use of primary MSCs is hampered by a number of limitations, including donor heterogeneity and inconsistent cell quality. Here, we tested the therapeutic potential of embryonic stem cell-derived MSCs (ES-MSCs) in anOA rat model. ES-MSCs were generated and identified by morphology, trilineage differentiation and flow cytometry. Sprague Dawley rats were treated with either a single dose (106 cells/rat) of ES-MSCs or with three doses spaced one week apart for each dose, starting at four weeks after anterior cruciate ligament transectionto induce OA. Cartilage quality was evaluated at 6 and 10 weeks after treatment with behavioral analysis, macroscopic examination, and histology. At sixweeks after treatment, the groups treated with both single and repeated doses of ES-MSCs had significantly better modified Mankin scores and International Cartilage Repair Society (ICRS) macroscopic scores in the femoral condyle compared to the control group. At 10 weeks after treatment, the repeated doses group had a significantly better ICRS macroscopic scores in the femoral condyle compared to the single dose and control groups. Histological analysis also showed more proteoglycan and less cartilage loss, along with lower Mankin scores in the repeated doses group. In conclusion, treatment with multiple injections of ES-MSCs can ameliorate OA in a rat model. TheES-MSCs have potential to be considered as a regenerative therapy for OA, and can provide an infinite cellular source

Skyrmion fluctuations at a first-order phase transition boundary

Magnetic skyrmions are topologically protected spin textures with promising prospects for applications in data storage. They can form a lattice state due to competing magnetic interactions and are commonly found in a small region of the temperature - magnetic field phase diagram. Recent work has demonstrated that these magnetic quasi-particles fluctuate at the μeV energy scale. Here, we use a coherent x-ray correlation method at an x-ray free-electron laser to investigate these fluctuations in a magnetic phase coexistence region near a first-order transition boundary where fluctuations are not expected to play a major role. Surprisingly, we find that the relaxation of the intermediate scattering function at this transition differs significantly compared to that deep in the skyrmion lattice phase. The observation of a compressed exponential behavior suggests solid-like dynamics, often associated with jamming. We assign this behavior to disorder and the phase coexistence observed in a narrow field-window near the transition, which can cause fluctuations that lead to glassy behavior

Two-dimensional universal conductance fluctuations and the electron-phonon interaction of topological surface states in Bi2Te2Se nanoribbons

The universal conductance fluctuations (UCFs), one of the most important manifestations of mesoscopic electronic interference, have not yet been demonstrated for the two-dimensional surface state of topological insulators (TIs). Even if one delicately suppresses the bulk conductance by improving the quality of TI crystals, the fluctuation of the bulk conductance still keeps competitive and difficult to be separated from the desired UCFs of surface carriers. Here we report on the experimental evidence of the UCFs of the two-dimensional surface state in the bulk insulating Bi2Te2Se nanoribbons. The solely-B\perp-dependent UCF is achieved and its temperature dependence is investigated. The surface transport is further revealed by weak antilocalizations. Such survived UCFs of the topological surface states result from the limited dephasing length of the bulk carriers in ternary crystals. The electron-phonon interaction is addressed as a secondary source of the surface state dephasing based on the temperature-dependent scaling behavior

The Evolution of the Epidemic of Charcoal-Burning Suicide in Taiwan: A Spatial and Temporal Analysis

Shu-Sen Chang and colleagues describe the epidemiology of an epidemic of suicide by charcoal burning in Taiwan and discuss possible reasons for its spread

Weak pairwise correlations imply strongly correlated network states in a neural population

Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher order interactions among large groups of elements play an important role. In the vertebrate retina, we show that weak correlations between pairs of neurons coexist with strongly collective behavior in the responses of ten or more neurons. Surprisingly, we find that this collective behavior is described quantitatively by models that capture the observed pairwise correlations but assume no higher order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behavior. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.Comment: Full account of work presented at the conference on Computational and Systems Neuroscience (COSYNE), 17-20 March 2005, in Salt Lake City, Utah (http://cosyne.org

Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids

Multicellular tumor spheroids are an important {\it in vitro} model of the pre-vascular phase of solid tumors, for sizes well below the diagnostic limit: therefore a biophysical model of spheroids has the ability to shed light on the internal workings and organization of tumors at a critical phase of their development. To this end, we have developed a computer program that integrates the behavior of individual cells and their interactions with other cells and the surrounding environment. It is based on a quantitative description of metabolism, growth, proliferation and death of single tumor cells, and on equations that model biochemical and mechanical cell-cell and cell-environment interactions. The program reproduces existing experimental data on spheroids, and yields unique views of their microenvironment. Simulations show complex internal flows and motions of nutrients, metabolites and cells, that are otherwise unobservable with current experimental techniques, and give novel clues on tumor development and strong hints for future therapies.Comment: 20 pages, 10 figures. Accepted for publication in PLOS One. The published version contains links to a supplementary text and three video file

Structure of hadron resonances with a nearby zero of the amplitude

We discuss the relation between the analytic structure of the scattering amplitude and the origin of an eigenstate represented by a pole of the amplitude.If the eigenstate is not dynamically generated by the interaction in the channel of interest, the residue of the pole vanishes in the zero coupling limit. Based on the topological nature of the phase of the scattering amplitude, we show that the pole must encounter with the Castillejo-Dalitz-Dyson (CDD) zero in this limit. It is concluded that the dynamical component of the eigenstate is small if a CDD zero exists near the eigenstate pole. We show that the line shape of the resonance is distorted from the Breit-Wigner form as an observable consequence of the nearby CDD zero. Finally, studying the positions of poles and CDD zeros of the KbarN-piSigma amplitude, we discuss the origin of the eigenstates in the Lambda(1405) region.Comment: 7 pages, 3 figures, v2: published versio

Controlling Cherenkov angles with resonance transition radiation

Cherenkov radiation provides a valuable way to identify high energy particles in a wide momentum range, through the relation between the particle velocity and the Cherenkov angle. However, since the Cherenkov angle depends only on material's permittivity, the material unavoidably sets a fundamental limit to the momentum coverage and sensitivity of Cherenkov detectors. For example, Ring Imaging Cherenkov detectors must employ materials transparent to the frequency of interest as well as possessing permittivities close to unity to identify particles in the multi GeV range, and thus are often limited to large gas chambers. It would be extremely important albeit challenging to lift this fundamental limit and control Cherenkov angles as preferred. Here we propose a new mechanism that uses constructive interference of resonance transition radiation from photonic crystals to generate both forward and backward Cherenkov radiation. This mechanism can control Cherenkov angles in a flexible way with high sensitivity to any desired range of velocities. Photonic crystals thus overcome the severe material limit for Cherenkov detectors, enabling the use of transparent materials with arbitrary values of permittivity, and provide a promising option suited for identification of particles at high energy with enhanced sensitivity.Comment: There are 16 pages and 4 figures for the manuscript. Supplementary information with 18 pages and 5 figures, appended at the end of the file with the manuscript. Source files in Word format converted to PDF. Submitted to Nature Physic

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers