Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Regularity Without Development

A major challenge in evolutionary computation is to find the right level of abstraction of biological development to capture its essential properties without introducing unnecessary inefficiencies. In this paper, a novel abstraction of natural development, called Compositional Pattern Producing Networks (CPPNs), is proposed. Unlike most computational abstractions of natural development, CPPNs do not include a developmental phase, differentiating them from developmental encodings. Instead of development, CPPNs employ compositions of functions derived from gradient patterns present in developing natural organisms. In this paper, a variant of the NeuroEvolution of Augmenting Topologies (NEAT) method, called CPPN-NEAT, evolves increasingly complex CPPNs, producing patterns with strikingly natural characteristics.
Biofilm Formation and Immunomodulatory Activity of Proteus mirabilis Clinically Isolated Strains

Urinary tract infections (UTIs) and catheter-associated UTIs (CAUTIs) are the principal hospital-acquired infections. Proteus mirabilis is characterized by several virulence factors able to promote adhesion and biofilm formation and ameliorate the colonization of urinary tract and the formation of crystalline biofilms on the abiotic surface of the urinary catheters. Since, to date, the role of P. mirabilis in the etiopathogenesis of different types of urinary tract infections is not well established, in this study we sought to characterize two different clinically isolated strains of P. mirabilis (PM1 and PM2) with distinctive phenotypes and analyzed various virulence factors possibly implicated in the ability to induce UTIs and CAUTIs. In particular, we analyzed motility, biofilm formation both on abiotic and biotic surfaces of PM1 and PM2 and paralleled these parameters with the ability to induce an inflammatory response in an epithelial cell model. Results showed that PM1 displayed major motility and a capacity to form biofilm and was associated with an anti-inflammatory response of host cells. Conversely, PM2 exhibited lack motility and a had slower organization in biofilm but promoted an increase of proinflammatory cytokine expression in infected epithelial cells. Our study provides data useful to start uncovering the pathologic basis of P. mirabilis-associated urinary infections. The evidence of different virulence factors expressed by PM1 and PM2 highlights the possibility to use precise and personalized therapies targeting specific virulence pathways.
Urban water management reform : the case of China

Water scarcity is particularly acute in urban areas in developing countries, where a safe and secure water supply is threatened by rapid economic development and urbanization, population growth, and the deterioration of water environment. In this dissertation, it is argued that the appropriate policy interventions might allow developing countries to achieve economic development with less capita water consumptions, the privatization reform and the participation of multinational corporations in Chinese water sector contributed to the growth of productivity of the whole sector, and environmental campaign and public participation enhance citizens’ environmental awareness which in turn contribute to water conservation.
Activity-Dependent Cleavage of the K-Cl Cotransporter KCC2 Mediated by Calcium-Activated Protease Calpain

The K-Cl cotransporter KCC2 plays a crucial role in neuronal chloride regulation. In mature central neurons, KCC2 is responsible for the low intracellular Cl− concentration ([Cl−]i) that forms the basis for hyperpolarizing GABAA receptor-mediated responses. Fast changes in KCC2 function and expression have been observed under various physiological and pathophysiological conditions. Here, we show that the application of protein synthesis inhibitors cycloheximide and emetine to acute rat hippocampal slices have no effect on total KCC2 protein level and K-Cl cotransporter function. Furthermore, blocking constitutive lysosomal degradation with leupeptin did not induce significant changes in KCC2 protein levels. These findings indicate a low basal turnover rate of the total KCC2 protein pool. In the presence of the glutamate receptor agonist NMDA, the total KCC2 protein level decreased to about 30% within 4 h, and this effect was blocked by calpeptin and MDL-28170, inhibitors of the calcium-activated protease calpain. Interictal-like activity induced by incubation of hippocampal slices in an Mg2+-free solution led to a fast reduction in KCC2-mediated Cl− transport efficacy in CA1 pyramidal neurons, which was paralleled by a decrease in both total and plasmalemmal KCC2 protein. These effects were blocked by the calpain inhibitor MDL-28170. Taken together, these findings show that calpain activation leads to cleavage of KCC2, thereby modulating GABAergic signaling.
Selecting the best open source tools for collecting and visualzing social media content

Social media data and information become a real concern for many parties such as countries and organizations for analysis, strategies and decision making purposes. Selecting the best open source social media tool for collection and visualization data from social networks' web is a big challenge. In this paper, we propose an integrated approach to select the most appropriate tools for collecting and visualizing information that are available on social media web. The proposed approach has two phases, namely, evaluation and selection. The current practice of evaluation process involves expert users opinions on the tool to rate it's importance based on the users' satisfaction which is measured on the efficiency of the tool for finding required results. The evaluation phase of the proposed technique combines the current practice with the weight of importance, where the later one has been calculated by applying statistical methods. The selection phase has designed based on the well-known PROMETHEE technique. The results have been showed as a ranking list of the selected libraries and frameworks/tools for both the data collection and data visualization.
Analysis of neural interaction during adaptation of reach-to-grasp task under perturbation with Bayesian networks

In this work, we took the analysis of neural interactions change in M1 of a monkey during the adaptation process for it to complete reach-to-grasp tasks with external perturbation across days. BN model was applied to model and evaluate neural interaction networks from recorded neural spike trains data of each set. Our results showed that for delay period across sets, interaction level of neural network tended to be higher during later stage of adaptation than during begin stage, which indicated the monkey performed more fully preparation through adaptation. In addition, for both delay period and peri-movement period, the neural interaction networks tended to change more stably from one set to the next as the monkey adapted to the perturbation experiment better.
3D volume localization using miniatures

The prediction of the position of a given volume sample in a full body atlas, also known as a volume localization, is a part of an initial stage of image retrieval in most of the dedicated CAD systems. In this paper we present two methods for volume localization, namely histogram matching and classifier regression. Since the histogram matching method ignores the spatial orientation, it is used when the orientation of the volume cubes are not the same. On the other hand the classifier regression is much faster and can be used as a quick estimation and as a tool to reduce the scope of the initial problem. Both presented methods were tested on a dataset with 3962 volumes of a human body atlas. The accuracy and the speed of execution was compared and is presented in this paper.
Transacting in a cultural industry (A theoretical examination of the relevance of Transaction Cost Economics to the analysis of inter-firm relationships within the popular music industry)

This theoretical paper examines the transaction cost framework as described by its main proponent in the context of the popular recorded music industry. We take the two firm typologies within the industry, major and independent, and discuss whether TCE variables can identify suitable governance structures for managing the transactions between them. We argue that asset idiosyncrasies such as cultural knowledge and reputation, and the nature of the non-linear causally ambiguous creation of cultural product create a climate that militates against TCE's ability to identify the optimal governance structure.
Forecasting Foreign Currency Exchange Rates for Air Force Budgeting

Abstract : This thesis examines the current method of forecasting foreign currency exchange rates for the annual US Air Force budget. Using 5 methods against the status quo of a center-weighted average, the paper evaluates the absolute percent error (APE) over three time periods extending from Fiscal Year (FY) 1979 to FY 2014. The results strongly indicate that four of the alternative methods outperform over the short term, and one method for all three time periods. Furthermore, a non-parametric comparison of the median APE demonstrates statistical similarities between the four methods over the short term, and allows for the Air Force to choose which method to exercise for future forecasting. Overall, the paper recommends using a private firm s forecasts to decrease the median APE by 3.36% and avoiding $36.1 million opportunity cost.
Papers, Please…: X.509 certificate revocation in practice

X.509v3 certificates are the current standard of verifiable associating an entity with a public key, and are widely used in different networking applications: from HTTPS in browsers, SSH connections, to e-mail, PDF and code signing. This wide usage also necessitates the existence of a robust, reliable way to detect and deal with compromised or otherwise invalid certificates. Certificate Revocation Lists (CRLs) and the Online Certificate Status Protocol (OCSP) are the two mechanisms currently deployed to handle revoked certificates. In this position paper we present preliminary results of our research into the practical use of these protocols, using an existing data-set to show that almost 85% of certificates currently in use contain no revocation information, and compare different browsers under different operating systems as to their dealing with unreachable OCSP servers. We find that browser behaviour in this case ranges from opening the site without any warnings whatsoever to totally blocking it, indicating no clear default reaction and no reliable behaviour.
Bridging the Utilitarian-Hedonic Divide in Crowdsourcing Applications

This paper introduces a novel perspective on the gamification of crowdsourcing tasks by conceptualizing it as the introduction of hedonic quality into the solution of utilitarian tasks and into the design of corresponding systems. We demonstrate how such a conceptualization can enable crowdsourcing applications to involve new kinds of crowds in everyday contexts that cannot be reached with existing models. We illustrate its application with the design of TrendRack, a gamified crowdsourcing application in the domain of fashion. We then discuss the results from a first evaluation, suggesting successful engagement of fashion customers in everyday contexts.
Server Selection Schemes Considering Node Status For a Fault-Tolerant Streaming Service on a Peer-to-Peer Network

: Peer-to-Peer (P2P) networks are attracting considerable research interest because of their scalability and high performance relative to cost. One of the important services on a P2P network is the streaming service. However, because each node in the P2P network is autonomous, it is difficult to provide a stable streaming service on the network. Therefore, for a stable streaming service on the P2P network, a fault-tolerant scheme must be provided. In this paper, we propose two new node selection schemes, Playback Node First (PNF) and Playback Node First with Prefetching (PNF-P) that can be used for a service migration-based fault-tolerant streaming service. The proposed schemes exploit the fact that the failure probability of a node currently being served is lower than that of a node not being served. Simulation results show that the proposed schemes outperform traditional node selection schemes.
Education Signalling and the School-to-work Transition

This paper studies the relation between labour market institutions and educational systems and how this relation may affect youth unemployment rates. By constructing a signalling model in which education can be used as a signal of workers’ unobserved productivity and firms face firing costs, we investigate how the structure of the educational system and the labour market institutions may influence the school-to-work transition of young unexperienced workers. In particular, we find that different educational systems can lead to different youth unemployment rates, even for high-skilled individuals. Besides, the framework presented in this paper allows to understand how the existence of minimum wages affects individual’s education decision and helps to explain some of the observed empirical regularities.
Hybrid Discrete-Continuous Signal Processing : Employing Field-Programmable Analog Components for Energy-Sparing Computation Employing Analog VLSI to Design Energy-Sparing Systems

With power increasingly becoming the dominant limiting factor for today's computing needs, the promising methods of Hybrid Discrete-Continuous Architecture (HDCA) is being researched to aid in the advancement of energy saving computing solutions. As an older computational model, analog processing is coming back to help solve today's computational needs at efficiencies unachievable with purely digital systems. Utilizing both analog and digital components, HDCA aims to combine the two domains to do what each domain does best, together. With computational energyefficiency approaching 10,000 times the computational efficiency of purely digital systems, HDCA is poised to be a major breakthrough in the coming years. In this paper we will discuss what HDCA is, why we are researching it, the applications HDCA can be used for, and various experiments and simulations demonstrating the energy saving capabilities of HDCA.
Anomaly identification with limited sampling budget

We consider a network of data streams from which an anomalous process with known target distribution is to be identified. Because in practice obtaining observations may be expensive, we assume that there is a constraint on the total number of observations based on which the decision has to be made. We derive a sufficient condition on the sampling budget such that the error probability is kept below some desired level. Furthermore, we show how to obtain a sampling allocation that can improve upon equal sampling allocation and achieves the desired accuracy.
Probing the quantum coherence of a nanomechanical resonator using a superconducting qubit: I. Echo scheme

We propose a scheme in which the quantum coherence of a nanomechanical resonator can be probed using a superconducting qubit. We consider a mechanical resonator coupled capacitively to a Cooper pair box and assume that the superconducting qubit is tuned to the degeneracy point so that its coherence time is maximized and the electro-mechanical coupling can be approximated by a dispersive Hamiltonian. When the qubit is prepared in a superposition of states, this drives the mechanical resonator progressively into a superposition which in turn leads to apparent decoherence of the qubit. Applying a suitable control pulse to the qubit allows its population to be inverted resulting in a reversal of the resonator dynamics. However, the resonator's interactions with its environment mean that the dynamics is not completely reversible. We show that this irreversibility is largely due to the decoherence of the mechanical resonator and can be inferred from appropriate measurements on the qubit alone. Using estimates for the parameters involved based on a specific realization of the system, we show that it should be possible to carry out this scheme with existing device technology.
Extremely faint high proper motion objects from SDSS stripe 82

We have detected about 40 new, extremely faint (i>21) high proper motion (μ>0.14 arcsec/yr) objects from deep multi‐epoch Sloan Digital Sky Survey (SDSS) imaging data in a 110×2.5 = 275 square degrees area on the celestial equator (SDSS stripe 82). According to their location in a reduced proper motion diagram and from comparison with known objects, these objects are representatives of three different classes: 1) L and T dwarfs, 2) ultracool (>sdM7) subdwarfs, 3) cool white dwarfs. Low‐resolution optical spectroscopy with the VLT has confirmed this classification and provided preliminary spectroscopic distance estimates. The resulting tangential velocities give first hints on the membership of these nearby low‐luminosity objects in the Galactic disk or halo populations.
Spatially Correlated Allocation Models for Count Data

Spatial heterogeneity of count data on a rare phenomenon occurs commonly in many domains of application, in particularly in disease mapping. We present new methodology to analyse such data, based on a hierarchical allocation model. We assume that the counts follow a Poisson model at the lowest level of the hierarchy, and introduce a nite mixture model for the Poisson rates at the next level. The novelty lies in the allocation model to the mixture components, which follows a spatially correlated process, the Potts model, and in treating the number of components of the spatial mixture as unknown. Inference is performed in a Bayesian framework using reversible jump MCMC. The model introduced can be viewed as a Bayesian semiparametric approach to specifying exible spatial distribution in hierarchical models. It could also be used in contexts where the spatial mixture subgroups are themselves of interest, as in health care monitoring. Performance of the model and comparison with an alternative well-known Markov random eld model speciication for the Poisson rates are demonstrated on synthetic data sets. We found that our allocation model avoids the problem of oversmoothing in cases where the underlying rates exhibit discontinuities, while giving equally good results in cases of smooth gradient-like or highly autocorrelated rates. The methodology is illustrated on epidemiological applications to data on rare disease and health outcome in France.
AGE-DEPENDENT EFFECTS OF CHRONIC GABAA RECEPTOR BLOCKADE IN BARREL CORTEX Lynn Gargan, B.S., M.S. Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY APPROVED:

GABA A receptor binding is transiently increased in rat whisker barrels during the second postnatal week, at a time when neurons in the developing rat cortex are vulnerable to excitotoxic effects. To test whether these GABA A receptors might serve to protect neurons from excessive excitatory input, polymer implants containing the GABA A receptor antagonist bicuculline were placed over barrel cortex for a 4-day period in young (postnatal days 8 – 12) and adult rats. In the cortex of young, but not adult rats, the chronic blockade of GABA A receptors resulted in substantial tissue loss and neuron loss. The greater loss of neurons in young rats supports the hypothesis that a high density of GABA A receptors protects neurons from excessive excitatory input during a sensitive period in development. iii ACKNOWLEDGMENTS I would like to acknowledge my committee members who have guided me through
Impact of Financial Liberalization on Welfare: Evidence from Nepal

This study aims at examining the impact of financial liberalization on welfare and presents the empirical evidence from Nepal using ARDL modeling cointegration test method. The test results indicate that financial liberalization is positively associated with increased employment opportunities in both rural and urban areas but negatively associated with the bank credits to the poor. From these results, it can be argued that the net impact of financial liberalization on welfare is ambiguous. Specifically, the incidence of poverty is adversely affected by financial liberalization.
A safety spacing policy and its impact on highway traffic flow

This paper proposes a Safety Spacing Policy (SSP) that can ensure safe operation while at the same time improving traffic flow for Adaptive Cruise Control (ACC) system. The proposed SSP, a nonlinear function of vehicle velocity, uses both the information of vehicle's state and braking capacity to adjust the position and velocity of the controlled vehicle. String stability, traffic flow stability and traffic capacity of the proposed policy are analyzed. The SSP can ensure vehicle string stability and it can also yield stable traffic flow and higher traffic capacity that are superior to the traditional Constant Time Gap (CTG) system. Especially in the high-density traffic conditions, the proposed new policy can provide higher traffic capacity to relief traffic congestion while the CTG policy fails to do so. In addition, traffic simulations show that SSP can ensure vehicle safety in hard brake and acceleration scenarios. The proposed new spacing policy is a promising alternative to the traditional CTG policy.
Balanced Budget Rules and Aggregate Instability: The Role of Consumption Taxes

It is known that, in the context of a real business cycle model with constant returns to scale and a balanced budget fiscal policy rule, steady state indeterminacy may arise as a result of endogenously determined labor income tax rates. This happens for a range of empirically plausible tax rates and this range is amplified if government expenditures are financed by a combination of capital and labor income taxes. This paper revisits the issue of indeterminacy and aggregate instability when government expenditures may be financed by consumption taxes as well. It is shown that by introducing consumption taxes, the ranges of indeterminacies shrink, thus reducing the possibility of aggregate instability. The results also provide an additional argument in favor of (the less distortionary) consumption taxes in place of capital taxes.
Bone-Targeted Agents for the Management of Breast Cancer Patients with Bone Metastases

Despite advances in adjuvant therapy for breast cancer, bone remains the most common site of recurrence. The goal of therapy for these patients is palliative and focused on maximizing the duration and quality of their life, while concurrently minimizing any disease or treatment-related complications. Bone metastases predispose patients to reduced survival, pain, impaired quality of life and the development of skeletal-related events. With an increased understanding of the pathophysiology of bone metastasis, effective treatments for their management have evolved and are now in widespread clinical use. This article will discuss the pathogenesis of bone metastases and review the key clinical evidence for the efficacy and safety of currently available systemic bone-targeted therapies in breast cancer patients with an emphasis on bisphosphonates and the receptor activator of nuclear factor kappa B ligand (RANKL) inhibitors. We will also discuss novel strategies and therapies currently in development.