Miracle-dz/UniFAR-FTUs huggingface dataset:
Transient anomalous charge production in strong-field QCD

We investigate axial charge production in two-color QCD out of equilibrium. We compute the real-time evolution starting with spatially homogeneous strong gauge fields, while the fermions are in vacuum. The idealized class of initial conditions is motivated by glasma flux tubes in the context of heavy-ion collisions. We focus on axial charge production at early times, where important aspects of the anomalous dynamics can be derived analytically. This is compared to real-time lattice simulations. Quark production at early times leading to anomalous charge generation is investigated using Wilson fermions. Our results indicate that coherent gauge fields can transiently produce significant amounts of axial charge density, while part of the induced charges persist to be present even well beyond characteristic decoherence times. The comparisons to analytic results provide stringent tests of real-time representations of the axial anomaly on the lattice.
Glycosylation-independent ERAD pathway serves as a backup system under ER stress

Glycosylated and nonglycosylated proteins misfolded in the ER are degraded by discrete but interchangeable pathways in the ERAD system. Disulfide reductase ERdj5 plays a central role in both pathways through the complex formation with EDEM and/or BiP. The nonglycoprotein ERAD pathway serves as a backup system under ER stress conditions.
Generative Mixology: An Engine for Creating Cocktails

This paper details an expert cocktail generation system. After using expert knowledge to break down cocktails into eight categories, the system generates cocktails from a particular category using a context-free stochastic grammar. These cocktails were then evaluated by human participants in a research setting. Participants evaluated the cocktails on the basis of quality, novelty and typicality to check the creative potential of the generator’s output.
In Vitro schedule-dependent interactions between the multitargeted antifolate LY231514 and gemcitabine in human colon adenocarcinoma cell lines.

PURPOSE Multitargeted antifolate (MTA) and gemcitabine (GEM) have shown preclinical and clinical activity in tumor histotypes such as colon, renal, small and non-small cell lung cancers, hepatomas and carcinoid tumors. In our study, we investigated the cytotoxic activity of MTA alone or in combination with GEM using different exposure schedules in three different colon cancer cell lines (LoVo, WiDr, and LRWZ). EXPERIMENTAL DESIGN Cytotoxic activity was evaluated by sulforhodamine B assay, cell cycle perturbations and apoptosis were evaluated by flow cytometry, and thymidylate synthase expression was evaluated by immunohistochemical method. RESULTS A 48-h exposure to MTA caused a minimal and no-dose-response effect on the three cell lines used. Flow cytometric analysis showed a cell accumulation in S phase that completely resolved in LoVo and LRWZ cell lines and persisted in WiDr cells after a 48-h washout. Moreover, a significant increase in thymidilate synthase expression was observed in all of the cell lines after MTA exposure. Among the different combinations tested, the highest synergistic interaction, assessed using Kern's method and expressed as the synergistic ratio index, was produced by pretreatment with GEM followed by MTA (ratio index: 1.3- 6.7). It is possible that the depletion of nucleotide pools induced by MTA and required for DNA synthesis prevented cells from repairing DNA damage caused by GEM. The type and degree of drug interactions were not paralleled by apoptosis, which was almost always negligible, or by the type and persistency of the cell cycle perturbations. CONCLUSIONS Our results indicate that the sequential administration of GEM --> MTA provides the greatest benefit in the clinical treatment of colon cancer.
Analytical performance evaluation of manufacturing cells using Petri net model and moment generating function

In this paper, a manufacturing cell is represented as a generalized stochastic Petri net model. Then, by applying moment generating function based approach, the steady-state probability formulation, and accordingly, the production rate and the work-in-process of the manufacturing cell are expressed, respectively, as a symbolic function of all the timed transition rates, such as the part processing rate, the failure rate and the repair rate. Finally, the analytical results are compared with the previous research results to verify the validity of the suggested method.
Learning in Repeated Games: Human Versus Machine

While Artificial Intelligence has successfully outperformed humans in complex combinatorial games (such as chess and checkers), humans have retained their supremacy in social interactions that require intuition and adaptation, such as cooperation and coordination games. Despite significant advances in learning algorithms, most algorithms adapt at times scales which are not relevant for interactions with humans, and therefore the advances in AI on this front have remained of a more theoretical nature. This has also hindered the experimental evaluation of how these algorithms perform against humans, as the length of experiments needed to evaluate them is beyond what humans are reasonably expected to endure (max 100 repetitions). This scenario is rapidly changing, as recent algorithms are able to converge to their functional regimes in shorter time-scales. Additionally, this shift opens up possibilities for experimental investigation: where do humans stand compared with these new algorithms? We evaluate humans experimentally against a representative element of these fast-converging algorithms. Our results indicate that the performance of at least one of these algorithms is comparable to, and even exceeds, the performance of people.
The Impact of Changes in Network Structure on Diffusion of Warnings

Diffusion occurs in various contexts and generally involves a network of entities that interact in some way. Through these interactions, some property, e.g. information, idea, innovation, disease, etc., is diffused through the network. The flow of these information, ideas, etc. may in turn have an effect on how the entities interact. The network becomes dynamic as a result of the diffusion process. This paper presents a general model of diffusive processes in dynamic networks. The model is based on a small number of parameterized diffusion axioms. We use the model to explore how social network structure, population inhomogeneity, and seed set selection affects the diffusion process. Simulation experiments were performed on three simulated networks: grid; Erdos-Renyi; scale free; and one LiveJournal blog comment network. The context of the experiments reflect on an evacuation scenario where a warning message is diffused through the network and the goals are to propagate the message and perform evacuation. The network dynamics observed in this study are the results of the diffusion process, where nodes may leave the network some time after receiving a warning message. The simulation results indicate that inhomogeneities in the population help with the spread of the warning and leads to largest evacuation. The network structure and the seeding mechanism used in delivering the initial broadcast also have drastic impact on the efficiency of the diffusion.
Measuring Portfolio Credit Risk Correctly: Why Parameter Uncertainty Matters

Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian inference reveals that - for realistic assumptions about the portfolio's credit quality and the data underlying parameter estimates - this uncertainty substantially increases the tail risk perceived by the investor. Since incorporating parameter uncertainty in a measure of tail risk is computationally demanding, the paper also derives and analyzes a closed-form approximation to such a measure.
An Architecture for Advance Reservations in the Internet

Much work has been done on establishing resource reservations over the Internet 3, 2, 8], but almost all of this work has consisted of establishing a reservation that begins immediately and has indeenite duration. An important issue is how to request an advance reservation, a reservation made now for resources that are to be reserved in the future. In this paper, we propose an architecture for Advance Reservation Servers (ARS), and describe their operation. By using ARS, no reservation state or scheduling state needs to be set up in the routers until the reservation is established. No multicast routing state (for multicast sessions) needs to be set up, either, until the reservation is established.
Dynamic Neighborhood Hybrid Particle Swarm Optimization for Constrained Optimization

Particle swarm optimization (PSO) is simple and efficient, but there is serious premature convergence for solving constrained optimization problem. In order to control premature convergence, this paper proposed dynamic neighborhood hybrid particle swarm optimization (DNH_PSO), which firstly uses the dynamic neighborhood strategy that based on the random topology and the von Neumann topology to improve the global search capacity, secondly incorporates adaptive penalty function constraint handling mechanism, finally introduces Quasi-Newton method effectively enhanced the efficiency of local search ability and convergence speed. Through the experimental comparison with benchmark functions and results show that the algorithm had better global convergence in solving constrained optimization problems.
Antecedents and Consequences of Flow Experience in Virtual Brand Community

Market competition currently becomes increasingly keen. Under this environment, virtual brand community is expected to have greater effect on the consumers' brand attitude than ever before. This paper studied how information experience and interaction experience influence flow experience, and what role flow experience may play in promotion of participation and formation of brand identification in virtual brand community. Through randomly sampling, this study selected 205 members who had a certain period of networking experience for empirical study. After implementing a structural equation model to test the research framework and hypotheses, this study finds that interaction experience has direct positive effect on flow experience; flow experience has direct positive effect on participation of community and brand identification. At the same time participation of community has direct positive effect on brand identification. Information experience does not help form flow experience. The rational is to provide tactics for practitioners to enhance their abilities to manage the virtual brand community.
Comparison of Electroacupuncture and Morphine-Mediated Analgesic Patterns in a Plantar Incision-Induced Pain Model

Electroacupuncture (EA) is a complementary therapy to improve morphine analgesia for postoperative pain, but underlying mechanism is not well-known. Herein, we investigated EA-induced analgesic effect in a plantar incision (PI) model in male Sprague-Dawley rats. PI was performed at the left hind paw. EA of 4 Hz and high intensity or sham needling was conducted at right ST36 prior to PI and repeated for another 2 days. Behavioral responses to mechanical and thermal stimuli, spinal phospho-ERK, and Fos expression were all analyzed. In additional groups, naloxone and morphine were administered to elucidate involvement of opioid receptors and for comparison with EA. EA pretreatment significantly reduced post-PI tactile allodynia for over 1 day; repeated treatments maintained analgesic effect. Intraperitoneal naloxone could reverse EA analgesia. Low-dose subcutaneous morphine (1 mg/kg) had stronger inhibitory effect on PI-induced allodynia than EA for 1 h. However, analgesic tolerance appeared after repeated morphine injections. Both EA and morphine could equally inhibit PI-induced p-ERK and Fos inductions. We conclude that though EA and morphine attenuate postincision pain through opioid receptor activations, daily EA treatments result in analgesic accumulation whereas daily morphine injections develop analgesic tolerance. Discrepant pathways and mechanisms underlying two analgesic means may account for the results.
Testing for autocorrelation in systems of equations

This paper deals with the problem of testing for the presence of autocorrelation in a system of general linear models (Seemingly Unrelated Regressions, SUR) when the model is formulated as a vector autoregression (VAR) with exogenous variables. The solution presented in this paper is a generalization of the h-statistic for the single equation single parameter case given in Durbin (1970a). All derivations are based on first principles and no use is made of Durbin’s original arguments.
MU-MIMO Downlink Transmission Strategy Based on the Distributed Antennas for 3GPP LTE-A

The multiple input multiple output (MIMO) technology and the distributed antenna system (DAS) have emerged as the promising candidates for the future mobile communications. In this paper, we observe the downlink (DL) transmission in a single-cell multi-user MIMO (MU-MIMO) system based on the distributed antennas for 3GPP Long Term Evolution-Advanced (LTE-A). It is found that the existing methods presented in 3GPP LTE discussion may deteriorate system throughput sharply due to the inaccurate channel information feedback from user equipment (UE). We propose a novel strategy including several methods for the MU-MIMO DL transmission in DAS. First, a UE-specific channel vector quantization method is proposed to enable the BS to acquire more accurate channel direction information (CDI). In addition, we develop a new method for the channel quality information (CQI) computation at the side of UE. The extensive simulation performed in the various scenarios discloses that the proposed strategy achieves the performance gain in terms of system throughput by 600% at most and 20% at least.
DISTRIBUTED MECHATRONICS CONTROLLER FOR MODULAR WALL CLIMBING ROBOT

Practical wall climbing robots that are used for applications requiring them to be fitted with task specific tools should be large enough to carry the additional tool payload. As size of robot is increased, inflexible body frame of wall-climbing robot limits its capability to change surfaces and to maneuver on uneven surfaces. In this paper, modular design of wall-climbing robot implementing two articulated legs per module (biped robotic modules) is presented. The design improves robot’s maneuverability and flexibility when changing surfaces or whilst walking on uneven surfaces. The minimum number of sensors and actuators in each module is fifteen. As the number of modules used in the design of the robot is increased, the number of actuators and sensors increase exponentially. Distributed mechatronics controller of such systems is presented. There is a limit of the number of modules that can results in practical operation of the wallclimbing robot. The developed control system uses three layers of message prioritization in order to control and schedule robot’s tasks.
Naltrexone/Bupropion extended release‐induced weight loss is independent of nausea in subjects without diabetes†

Naltrexone/bupropion extended release (NB) is indicated as an adjunct to a reduced‐calorie diet and increased physical activity for chronic weight management in adults with an initial body mass index of ≥30 or ≥27 kg m−2 and ≥1 weight‐related comorbidity (e.g. hypertension, type 2 diabetes and dyslipidaemia). In phase 3 clinical studies, nausea occurred in significantly higher proportions of subjects randomized to NB vs. placebo (PBO). In this pooled analysis of three phase 3, 56‐week, PBO‐controlled studies, we characterized nausea and weight loss in NB‐ and PBO‐treated subjects without diabetes. Subjects receiving NB (n = 1778) lost significantly more weight than those receiving PBO (n = 1160). Weight change was not significantly different between subjects reporting and not reporting nausea in either treatment arm. Severity of nausea was mild to moderate in ≥95% of all cases. In the NB arm, the highest incidence of nausea onset (9%) was reported during week 1. The median duration of mild, moderate and severe nausea in subjects receiving NB was 14, 9 and 13 days, respectively. Our results demonstrate that nausea associated with NB is rarely severe, primarily occurs early in treatment and is not a contributor to weight loss.
Text categorization of low quality images

Categorization of text images into content oriented classes would be a useful capability in a variety of document handling systems Many methods can be used to cat egorize texts once their words are known but OCR can garble a large proportion of words particularly when low quality images are used Despite this we show for one data set that fax quality images can be cat egorized with nearly the same accuracy as the original text Further the categoriza tion system can be trained on noisy OCR output without need for the true text of any image or for editing of OCR output The use of a vector space classi er and train ing method robust to large feature sets com bined with discarding of low frequency OCR output strings are the key to our approach
D-instanton induced interactions on a D3-brane

Non-perturbative features of the derivative expansion of the effective action of a single D3-brane are obtained by considering scattering amplitudes of open and closed strings. This motivates expressions for the coupling constant dependence of world-volume interactions of the form (∂F)4 (where F is the Born-Infeld field strength), (∂2)4 (where are the normal coordinates of the D3-brane) and other interactions related by = 4 supersymmetry. These include terms that transform with non-trivial modular weight under Montonen-Olive duality. The leading D-instanton contributions that enter into these effective interactions are also shown to follow from an explicit stringy construction of the moduli space action for the D-instanton/D3-brane system in the presence of D3-brane open-string sources (but in the absence of a background antisymmetric tensor potential). Extending this action to include closed-string sources leads to a unified description of non-perturbative terms in the effective action of the form (embedding curvature)2 together with open-string interactions that describe contributions of the second fundamental form.
Exemplar-Based Image Inpainting with Collaborative Filtering

This paper proposes a novel patch synthesis approach for exemplar-based propagation in image in painting. Currently, plural non-local exemplar patches synthesis is widely adopted to fill missing pixels. It generally provides good results, but sometimes shows poor visual quality due to dissimilarity between exemplars and targets. In this paper, a collaborative filtering approach is used to enhance the exemplar-based propagation to obtain ideal in painting results. The approach works on pixel level information, while many exemplar-based propagation algorithms focus on patch level information. Object removal and stain image recovering are carried out to evaluate the proposed approach. Experiments show that our approach provides good visual quality in object removal and high PSNR in stain image recovering.
The Clinical Presentation of Childhood-Onset Schizophrenia: A Literature Review

This literature review explores the research on the clinical presentation of childhood-onset schizophrenia (COS) that was conducted in the period 1994–2004. A literature search was done using Internet search engines and psychological databases to collect English-language journal articles from 1994 onwards. Research indicates that COS is a stable diagnosis. Generally, there is a clear history of premorbid abnormalities, an insidious onset and a deteriorating course. For the majority of cases there seems to be a poor outcome. Despite the limitations in the research conducted thus far, findings provide important insights into COS and several possibilities for future research.
The Hare and the Tortoise : Network structure in collaborative problem solving

Policy makers often face similar problems, and tackling them is often a social effort, where individuals can share information through network ties about how to solve the problems they face. In particular, it has been amply documented that actors tend to emulate successful others that they observe. We present a simulation demonstrating that more efficient communication can actually lower total performance in the long run. This effect is manifest in complex (e.g. rugged) problem spaces, where extensive searches are expensive for the individual. When actors can communicate easily, average performance improves initially, but harder-to-find optimal solutions are less likely to be discovered. Small-world networks and cliques in communication have important implications for the social outcomes in a collaborative network.
Facial Template Protection Using Extended Visual Cryptography And Chaotic Encryption

Protection of biometric data is of prime importance now a days. In this paper a new method is proposed for the protection of biometric facial data using visual cryptography and chaotic encryption. By using visual cryptography each private face image is decomposed into two public host images. The original image gets revealed only when both of these images are available simultaneously. By using chaotic encryption extra protection as well as privacy is ensured for these images. Chaotic encryption is applied onto each share. Any system having chaotic behaviour is used for getting values for encrypting the shares. Here 1D logistic map is used.
Working Capital Management

As soon as a firm starts operating and furthermore, the moment it starts to grow, it needs to come to a decision about how to invest funds, how much cash and inventory to hold on to, how much financing to provide to customers, how to obtain the necessary funds, how much debt to take on and in which terms-all the answers to these questions have serious consequences for a firm's cash flow and profitability. Working Capital Management is a hands-on look at the crucial decision of how to define and finance the operating investments of a business. Starting with an overview of the fundamental framework of corporate finance, the authors set out to define the central, and usually underestimated, role that working capital plays within this structure. They show not only how to prevent the losses that result from mishandling of working capital, but also how to fully exploit the strategic potential that intelligent, expert management of working capital allows. The book is the first to emphasize the relevance of the interplay between the investment and finance aspects of working capital, by discussing all of the main components of a firm's operating expenses from both an investment and finance perspective. After focusing on the varying aspects and themes of working capital, such as inventory management, strategic accounting, trade credit, and short-term debt, the authors move on to identify the long-term implications and opportunities raised by this often overlooked aspect of corporate finance. Lorenzo Preve and Virginia Sarria Allende have at last provided a resource that identifies the impact of day-to-day business decisions, uncovering a highly influential, aspect of all firms' financial situation. Available in OSO: http://www.oxfordscholarship. com/oso/public/content/economicsfinance/9780199737413/toc.html