Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunotherapy against the radial glia marker GLAST effectively triggers specific antitumor effectors without autoimmunity

The glutamate-aspartate transporter GLAST is a radial glia marker that is highly expressed in GL261 stem-like cells (GSCs). To target GLAST, we treated glioma-bearing mice with three subcutaneous injections of four GLAST peptides emulsified with Montanide ISA-51 in association with granulocyte macrophage colony-stimulating factor (GM-CSF) injections. Vaccination with GLAST peptides significantly prolonged survival, effectively enhanced systemic T-cell and NK-cell responses and promoted robust antitumor cytotoxicity. GLAST expression significantly decreased in gliomas from immunized mice, as evaluated by histological analysis and real-time PCR (RT-PCR). Moreover, the immunization protocol led to the upregulation of interferonγ (IFNγ) and tumor necrosis factorα (TNFα) as well as to the downregulation of transforming growth factor (TGF) β1 and β2 in the tumor. Beyond these changes, gliomas from immunized mice exhibited an increased recruitment of NK cells and antigen-specific CD8+ T cells expressing the tumor homing molecule VLA-4, as well as a local chemotactic gradient featuring expression of CXCL10 (which may be responsible for the recruitment of CTLs), CCL3, CCL4 and CCL5 (which are involved in NK-cell migration), and NKG2D ligand on glioma cells. Importantly, although GLAST is expressed in the central nervous system, autoimmune reactions were not observed in immunized mice. Altogether, these results support the contention that GLAST may constitute a glioma antigen against which immune responses can be efficiently induced without major safety concerns.
Drop dynamics on chemically patterned surfaces

We compare numerical and experimental results exploring the behaviour of liquid drops moving across a surface patterned with hydrophobic and hydrophilic stripes. A lattice Boltzmann algorithm is used to solve the hydrodynamic equations of motion of the drops allowing us to investigate their behaviour as the stripe widths and the wettability contrast are altered. We explain how the motion of the drop is determined by the interplay between the driving force and the variation in surface force as the drop moves between regions of different contact angle and we find that the shape of the drops can undergo large periodic deviations from spherical. When compared, the numerical results agree well with experiments on micron-scale drops moving across substrates patterned by microcontact printing.
Convective fingering of an autocatalytic reaction front.

We report experimental observations of the convection-driven fingering instability of an iodate-arsenous acid chemical reaction front. The front propagated upward in a vertical slab; the thickness of the slab was varied to control the degree of instability. We observed the onset and subsequent nonlinear evolution of the fingers, which were made visible by a pH indicator. We measured the spacing of the fingers during their initial stages and compared this to the wavelength of the fastest growing linear mode predicted by the stability analysis of Huang et al. [Phys. Rev. E 48, 4378 (1993), and unpublished]. We find agreement with the thickness dependence predicted by the theory. \textcopyright{} 1996 The American Physical Society.
Optimal Auctions with Convex Perceived Payments

Myerson derived a simple and elegant solution to the single-parameter revenue-maximization problem in his seminal work on optimal auction design assuming the usual model of quasi-linear utilities. In this paper, we consider a slight generalization of this usual model---from linear to convex "perceived" payments. This more general problem does not appear to admit a solution as simple and elegant as Myerson's. While some of Myerson's results extend to our setting, like his payment formula (suitably adjusted), others do not. For example, we observe that the solutions to the Bayesian and the robust (i.e., non-Bayesian) optimal auction design problems in the convex perceived payment setting do not coincide like they do in the case of linear payments. We therefore study the two problems in turn. We derive an upper and a heuristic lower bound on expected revenue in our setting. These bounds are easily computed pointwise, and yield monotonic allocation rules, so can be supported by Myerson payments (suitably adjusted). In this way, our bounds yield heuristics that approximate the optimal robust auction, assuming convex perceived payments. We close with experiments, the final set of which massages the output of one of the closed-form heuristics for the robust problem into an extremely fast, near-optimal heuristic solution to the Bayesian optimal auction design problem.
The Adjoint Method for an Inverse Design Problem in the Directional Solidification of Binary Alloys

This paper presents a systematic procedure based on the adjoint method for solving a class of inverse directional alloy solidification design problems in which a desired growth velocityvfis achieved under stable growth conditions. To the best of our knowledge, this is the first time that a continuum adjoint formulation is proposed for the solution of an inverse problem with simultaneous heat and mass transfer, thermo-solutal convection, and phase change. In this paper, the interfacial stability is considered to imply a sharp solid? liquid freezing interface. This condition is enforced using the constitutional undercooling criterion in the form of an inequality constraint between the thermal and solute concentration gradients,GandGc, respectively, at the freezing front. The main unknowns of the design problem are the heating and/or cooling boundary conditions on the mold walls. The inverse design problem is formulated as a functional optimization problem. The cost functional is defined by the square of theL2norm of the deviation of the freezing interface temperature from the temperature corresponding to thermodynamic equilibrium. A continuum adjoint system is derived to calculate the adjoint temperature, concentration, and velocity fields such that the gradient of the cost functional can be expressed analytically. The cost functional minimization process is realized by the conjugate gradient method via the finite element method solutions of the continuum direct, sensitivity, and adjoint problems. The developed formulation is demonstrated with an example of designing the directional solidification of a binary aqueous solution in a rectangular mold such that a stable vertical interface advances from left to right with a desired growth velocity.
A new algorithm for objective video quality assessment on Eye Tracking data

In this paper, we present an innovative algorithm based on a voting process approach, to analyse the data provided by an eye tracker during tasks of user evaluation of video quality. The algorithm relies on the hypothesis that a lower quality video is more “challenging” for the Human Visual System (HVS) than a high quality one, and therefore visual impairments influence the user viewing strategy. The goal is to generate a map of saliency of the human gaze on video signals, in order to create a No Reference objective video quality assessment metric. We consider the impairment of video compression (H.264/AVC algorithm) to generate different versions of video quality. We propose a protocol that assigns different playlists to different user groups, in order to avoid any effect of memorization of the visual stimuli on strategy. We applied our algorithm to data generated on a heterogeneous set of video clips, and the final result is the computation of statistical measures which provide a rank of the videos according to the perceived quality. Experimental results show that there is a strong correlation between the metric we propose and the quality of impaired video, and this fact confirms the initial hypothesis.
ALGEBRAIC TECHNIQUES FOR CONSTRUCTING MINIMAL WEIGHT THRESHOLD FUNCTIONS

A linear threshold element computes a function that is a sign of a weighted sum of the input variables. The best known lower bounds on the size of threshold circuits are for depth-2 circuits with small (polynomial-size) weights. However, in general, the weights are arbitrary integers and can be of exponential size in the number of input variables. Namely, obtaining progress in lower bounds for threshold circuits seems to be related to understanding the role of large weights. In the present literature, a distinction is made between the two extreme cases of linear threshold functions with polynomial-size weights, as opposed to those with exponential-size weights. Our main contributions are in devising two novel methods for constructing threshold functions with minimal weights and filling up the gap between polynomial and exponential weight growth by further refining the separation. Namely, we prove that the class of linear threshold functions with polynomial-size weights can be divided into subclasses according to the degree of the polynomial. In fact, we prove a more general result—that there exists a minimal weight linear threshold function for any arbitrary number of inputs and any weight size.
The Partisan Sort: How Liberals Became Democrats and Conservatives Became Republicans

As Washington elites drifted toward ideological poles over the past few decades, did ordinary Americans follow their lead? In "The Partisan Sort", Matthew Levendusky reveals that we have responded to this trend - but not, for the most part, by becoming more extreme ourselves. While polarization has filtered down to a small minority of voters, it also has had the more significant effect of reconfiguring the way we sort ourselves into political parties. In a marked realignment since the 1970s - when partisan affiliation did not depend on ideology and both major parties had strong liberal and conservative factions - liberals today overwhelmingly identify with Democrats, as conservatives do with Republicans. This 'sorting', Levendusky contends, results directly from the increasingly polarized terms in which political leaders define their parties. Exploring its far-reaching implications for the American political landscape, he demonstrates that sorting makes voters more loyally partisan, allowing campaigns to focus more attention on mobilizing committed supporters. Ultimately, Levendusky concludes, this new link between party and ideology represents a sea change in American politics.
Heuristic search for adaptive, defect-tolerant multiprocessor arrays

In this article, new heuristic-search methods and algorithms are presented for enabling highly efficient and adaptive, defect-tolerant multiprocessor arrays. We consider systems where a homogeneous multiprocessor array lies on top of reconfigurable interconnects which allow the pipeline stages of the processors to be connected in all possible configurations. Considering the multiprocessor array partitioned in substitutable units at the granularity of pipeline stages, we employ a variety of heuristic-search methods and algorithms to isolate and replace defective units. The proposed heuristics are designed for off-line execution and aim at minimizing the performance overhead necessarily introduced to the array by the interconnects' latency. An empirical evaluation of the designed algorithms is then carried out, in order to assess the targeted problem and the efficacy of our approach. Our findings indicate this to be a NP-complete computational problem, however, our heuristic-search methods can achieve, for the problem sizes we exhaustively searched, 100% accuracy in finding the optimal solution among 1019 possible candidates within 2.5 seconds. Alternatively, they can provide near-optimal solutions at an accuracy which consistently exceeds 70% (compared to the optimal solution) in only 10-4 seconds.
The Inflation Bias Result Revisited

The Kydland-Prescott, Barro-Gordon inflation bias result relies on the presumption that policymakers aim at achieving a level of employment above the normal level. This presumption has been recently questioned by both academics and policymakers on the ground of realism. This note shows that even if policymakers are content with the normal level of employment there is an inflation bias if the following two realistic conditions are satisfied. The central bank is uncertain about the future state of the economy and is more sensitive to policy misses leading to employment below the normal level that to policy misses leading to employment above it. The note also shows that there is reason to believe the bias today is smaller than in the past and discusses the implications of the analysis for the design of legal central bank objectives.
Nanotechnology-based drug delivery systems for the treatment of Alzheimer’s disease

Alzheimer’s disease is a neurological disorder that results in cognitive and behavioral impairment. Conventional treatment strategies, such as acetylcholinesterase inhibitor drugs, often fail due to their poor solubility, lower bioavailability, and ineffective ability to cross the blood–brain barrier. Nanotechnological treatment methods, which involve the design, characterization, production, and application of nanoscale drug delivery systems, have been employed to optimize therapeutics. These nanotechnologies include polymeric nanoparticles, solid lipid nanoparticles, nanostructured lipid carriers, microemulsion, nanoemulsion, and liquid crystals. Each of these are promising tools for the delivery of therapeutic devices to the brain via various routes of administration, particularly the intranasal route. The objective of this study is to present a systematic review of nanotechnology-based drug delivery systems for the treatment of Alzheimer’s disease.
Bottom-Up GIS

Abstract While the integration of GIS in the planning process is becoming more commonplace for efficient description of basic facts, it has not been widely used by planners for the incorporation of local knowledge. This article describes a new approach, termed “Bottom-Up GIS” (BUGIS), in which GIS is placed in the realm of expression and used as a means of expression. The advantage of using GIS in participatory planning activities is that it provides spatial complexity, spatial context, and interactivity and interconnection in the articulation of viewpoints. Thus, BUGIS can be an effective tool to deepen our understanding of residents' perceptions of local issues and preferences.
Building a Collocational Semantic Lexicon

Natural Language Generation (NLG) systems require a ccess to collocational information to help determine lexical choices constrained both by synta ctic and semantic concerns. Constructing linguistic resources to support these decisions can be tim -consuming whereas, if the information is extracted automatically, data sparsity limits the v ariety of the output. This paper reports on a method for extracting collocational data from the B ritish National Corpus, and then generalizing it using WordNet to tackle the sparsity problem. Th e method is evaluated using the lexical choice component of ENIGMA, an NLG system that generates c rypti crossword clues.
European Conference on Information Systems ( ECIS ) 2008 Organisations and Vanilla Software : What Do We Know About ERP Systems and Competitive Advantage ?

Enterprise Resource Planning (ERP) systems have become a de facto standard for integrating business functions. But an obvious question arises: if every business is using the same socalled “Vanilla” software (e.g. an SAP ERP system) what happens to the competitive advantage from implementing IT systems? If we discard our custom-built legacy systems in favour of enterprise systems do we also jettison our valued competitive advantage from IT? While for some organisations ERPs have become just a necessity for conducting business, others want to exploit them to outperform their competitors. In the last few years, researchers have begun to study the link between ERP systems and competitive advantage. This link will be the focus of this paper. We outline a framework summarizing prior research and suggest two researchable questions. A future article will develop the framework with two empirical case studies from within part of the European food industry.
Chapter Twenty-one Language Historical Context

The Brain-is wider than the sky-For-put them side by side-The one the other will contain-With ease and you beside The Brain is deeper than the sea-For-hold them-Blue to Blue-The one the other will absorb-As Sponges-Buckets-do The Brain is just the weight of God-For-Heft them-Pound for Pound-And they will differ-if they do-As Syllable from Sound. As Dickinson notes, brains have a remarkable capacity that differentiates them from other sorts of material substances: the ability to represent things intentionally. Although we often take this capacity for granted, it is no small feat that we are able to entertain the thoughts of a woman who has long since died. Many consider Dickinson to be a gifted poet, yet her ability to exploit the representational capacity afforded by language is shared by all humans. This capacity allows us to communicate with one another across distances of time and space and to affect one another's behavior. Natural language is a species-specific system that enables speakers to evoke cognitive models in listeners via the systematic combination of vocal sounds or visual signs. A schematic characterization of the speech event begins with the speaker's desire to communicate a message and ends with the listener's apprehension of that message. In this simplified model of the communicative act, language mediates between thoughts and motor commands on the speaker's end, and between acoustic signals and thoughts on the listener's end. However, the real magic in the system lies in the brains of the speech participants, and it is to the brain that psychophysiologists turn for answers to fundamental questions about the nature of language representations and the relationship between language and other cognitive processes. Linguists have posited a number of different kinds of representations to account for language production and comprehension. These constructs have proven quite useful for thinking about language processes, but their psychological reality remains a serious question. Much regularity can be observed in language, but are those regularities due to the fact that the brain implements linguistic rules? Work on the psychophysiology of language processing-using techniques such as ERPs, PET, and fMRI-has attempted to monitor how the brain changes with manipulations of particular linguistic representations. The assumption is that language subprocesses are subserved by different anatomical and physiological substrates that will generate distinct patterns of biological activity. These patterns can then be picked up by methods sensitive to fluctuations in electromagnetic and hemodynamic activity. Related to these …
Application of Genetic Algorithm on Remanufacturing Reverse Logistics Network Model

For the goal of energy-saving and environmental protection and increasing the re-utilization of recycling products for enterprises, the paper discusses an open-loop remanufacturing reverse logistics network which has a location selection of two layers, then constructs a mixed integer linear programming model to achieve the overall minimum cost including the freight between nodes, the fixed cost, the disposal cost and operation cost of storage and demolition nodes and remanufacturing centers, the penalty cost of the unmet or remaining demand quantity, as well as the operating subsidy of recycling product from government for dealing with environmental protection. According to the characteristics of the model, the paper uses two ways to solve the problem which are Lingo and adaptive genetic algorithm based on Matlab, and then provides an instance where solution steps and results analysis are given, which verifies the feasibility of applying adaptive genetic algorithm on the reverse logistics network model.
Predicate-Oriented Query of RDF Data Based on a Distributed Storage Model

With the expansion of semantic web, there is an increasing number of heterogeneous information data such as RDF. Nowadays, most of solutions operating RDF are centralized and have limitations of scalability. In this paper, we propose a method to solve the problem by storing and querying RDF data based on HBase and Hadoop. A storage model classified by class and predicate is used in HBase to support efficient queries. For multi-join queries of typical triangular pattern or linear structure, we put forward a method of reverse predicate encoding to reduce intermediate results of join operations which can improve the query efficiency to a certain extent. Our experiments on LUBM datasets verify the feasibility and effectiveness of the storage and query method.
Adaptive Powerline Interference Removal from Cardiac Signals Using Leaky Based Normalized Higher Order Filtering Techniques

In this paper we present an adaptive filter for denoising the ECG signal based on Least Mean Fourth (LMF) algorithms. LMF algorithm exhibits lower steady state error than the conventional LMS algorithm. This is due to the fact that the excess mean-square error of the LMS algorithm is dependent only on the second order moment of the noise. The second order moment, or variance of the noise evaluates to be the same for all the noise environments. Based upon this other types of mean fourth based algorithms are implemented. These are Normalized LMF (NLMF) and Error Normalized LMF (ENLMF). In order to increase the stability of the filter leakage factor is introduced. Based on these considerations Normalized Leaky LMF (NLLMF) and Error Normalized Leaky LMF (ENLLMF) adaptive cancellers are developed for cardiac signal enhancement. Different filter structures are presented to eliminate the 60 Hz power line interference from the ECG signal. Finally, we have applied this algorithm on ECG signals from the MIT-BIH data base and compared its performance with the conventional LMS algorithm. The results show that the performance of the ENLLMF based noise reduction filter is superior than the other implementations in terms of signal to noise ratio increment.
Optimized Signal to Noise Ratio Threshold Based on Transmission Power and Complexity of Cognitive Detector

Scarcity of the spectrum is becoming a major issue based on traditional frequency planning scheme, cognitive radio (CR) has been proposed for better spectrum utilization efficiency by intelligently sensing and opportunistic access. In this paper, a novel method is proposed to determine signal to noise ratio threshold (SNRT) based on transmission power and complexity of cognitive detector under lognormal shadowing conditions. Since there is tradeoff between detection probability and false alarm probability, we can maximize spectrum utilization efficiency with pre-determined detection performance,meanwhile SNRT is adjusted to void unacceptable interference to primary receiver (PR) and minimize complexity of cognitive detector according to transmission power. Numerical results will show that cognitive radio can adjust SNRT adaptively in order to guarantee the PR decoding signal from primary transmitter (PT) without unacceptable interference.