Miracle-dz/UniFAR-FTUs huggingface dataset:
Social Status, Inflation and Endogenous Growth in a Cash‐In‐Advance Economy: A Reconsideration Using the Credit Channel

Conventional models of social status purport a positive infl ation-growth relationship, and attribute this empirical contradiction to the presence of a consumer's desire for social status. These models are dominated by a substitution effect of money holdings for capital holdings, as an increase in the in ation rate due to money growth raises the cost of holding money and depresses the real money holdings. Using a monetary endogenous growth model, the effects of wealth-induced social status on long-run growth is reconsidered. The analysis is enhanced through the addition of a competitive banking sector that intermediates the available capital in the economy, subject to a mandatory cash reserve requirement. The cash reserve requirement creates a wedge between the deposit rate and the loan rate. While, the real loan rate is tied with the constant marginal product of capital, the real deposit rate is negatively related to the rate of infl ation. This leads to another, opposing substitution effect of deposit holdings for real money holdings and hence, increases the cost of holding deposits as infl ation increases. The consolidated theoretical model described herein supports a diverse range of theoretical findings, contingent on the presence of wealth effects or the spirit of capitalism, using a simpler and more tractable framework that accounts for the role of the banking system in monetary policy decision outcomes. Significantly, as long as the mandatory reserve requirement imposed on the banking system by the monetary authority exceeds a (small) critical value, an increase in the money growth rate will lead to a decrease in the long-run growth rate of the economy.
Hubungan antara sindrom FOMO (fear of missing out) dengan kecenderungan nomophobia pada remaja

Tujuan penelitian ini adalah untuk mengetahui hubungan antara sindrom FOMO (fear of missing out) dengan kecenderungan nomophobia pada remaja. Metode yang digunakan adalah kuantitatif korelasional. Alat pengumpulan data menggunakan skala nomophobia dan skala sindrom FOMO. Subyek penelitian berjumlah 127 siswa dari jumlah populasi 426 siswa di SMA Avisena Kedungcangkring Jabon Sidoarjo. Teknik yang digunakan pada penelitian ini adalah teknik nonprobability sampling dengan teknik purposive sampling. Teknik yang digunakan untuk menganalisis penelitian ini adalah analissi Product Moment. Hasil penelitian menunjukkan bahwa terdapat hubungan antara sindrom FOMO (fear of missing out) dengan kecenderungan nomophobia pada remaja, koefisien korelasi sebesar 0,717 yang bertanda positif dan taraf signifikansi 0,000 (p≤0,05). Artinya, semakin tinggi tingkat sindrom FOMO semakin tinggi pula tingkat kecenderungan nomophobia pada remaja.
Inhibition of T cell and antibody responses to house dust mite allergen by inhalation of the dominant T cell epitope in naive and sensitized mice

Antigen-specific CD4+ T cells play an important role in the allergic immune response to house dust mite (HDM) allergens in humans. The group 1 allergen of Dermatophagoides spp. is a major target antigen in both B and T cell recognition of HDM. In vitro studies have shown that the presentation of peptides to human T cells under appropriate conditions may lead to a state of specific nonresponsiveness. Therefore, to determine if peptides are able to modulate the function of allergen- reactive T cells in vivo, we have used a murine model of T cell recognition of the HDM allergen Der p 1. The results demonstrate that inhalation of low concentrations of peptide containing the major T cell epitope of Der p 1 (residues 111-139), induces tolerance in naive C57BL/6J mice such that they become profoundly unresponsive to an immunogenic challenge with the intact allergen. When restimulated in vitro with antigen, lymph node T cells isolated from tolerant mice secrete very low levels of interleukin 2, proliferative poorly, and are unable to provide cognate help to stimulate specific antibody production. Furthermore, intranasal peptide therapy was able to inhibit an ongoing immune response to the allergen in mice and this has potential implications in the development of allergen-based immunotherapy.
Antibacterial synergy of curcumin with antibiotics against biofilm producing clinical bacterial isolates

Introduction: The role of natural bioactive substances in treating infections has been rediscovered as bacterial resistance become common to most of the antibiotics. Curcumin is a bioactive substance from turmeric. Owing to antimicrobial properties, its prospect as an antibacterial agent is currently under focus. Materials and Methods: We have evaluated the in vitro synergy of curcumin with antibiotics against sixty biofilm producing bacterial isolates. Congo red agar method was used to identify the biofilm producing isolates. Curcumin minimum inhibitory concentration (MIC) was determined by agar dilution method. Its antibiotic synergy was identified by the increase in disc diffusion zone size on Mueller-Hinton agar with 32 mg/L curcumin. Results: The mean MICs of curcumin against Gram-positive and Gram-negative isolates were 126.9 mg/L and 117.4 mg/L, respectively. Maximum synergy was observed with ciprofloxacin among Gram-positive and amikacin, gentamicin, and cefepime among Gram-negative isolates. Conclusions: Curcumin per se as well as in combination with other antibiotics has a demonstrable antibacterial action against biofilm producing bacterial isolates. It may have a beneficial role in supplementing antibiotic therapy.
The Scale-Free Character of the Cluster Mass Function and the Universality of the Stellar Initial Mass Function

Our recent determination of a Salpeter slope for the initial mass function (IMF) in the field of 30 Doradus appears to be in conflict with simple probabilistic counting arguments advanced in the past to support observational claims of a steeper IMF in the LMC field. In this paper we reexamine these arguments and show by explicit construction that, contrary to these claims, the field IMF is expected to be exactly the same as the stellar IMF of the clusters out of which the field was presumably formed. We show that the current data on the mass distribution of clusters themselves is in excellent agreement with our model, and is consistent with a single spectrum by the number of stars of the type nβ, with β between –1.8 and –2.2 down to the smallest clusters, without any preferred mass scale for cluster formation. We also use the random sampling model to estimate the statistics of the maximal mass star in clusters, and confirm the discrepancy with observations found by Weidner & Kroupa. We argue that rather than signaling the violation of the random sampling model, these observations reflect the gravitationally unstable nature of systems with one very large mass star. We stress the importance of the random sampling model as a null hypothesis, whose violation would signal the presence of interesting physics.
Boundary CFT construction of D-branes in vacuum string field theory

In previous papers we built (multiple) D-branes in flat space-time as classical solutions of the string field theory based on the tachyon vacuum. In this paper we construct classical solutions describing all D-branes in any fixed space-time background defined by a two dimensional CFT of central charge 26. A key role is played by the geometrical definition of the sliver state in general boundary CFT's. The correct values for ratios of D-brane tensions arise because the norm of the sliver solution is naturally related to the disk partition function of the appropriate boundary CFT. We also explore the possibility of reproducing the known spectrum of physical states on a D-brane as deformations of the sliver.
Maintaining good health for older people with dementia who experience fractured neck of femur: report for phase 2

1 We are very grateful to the members of our expert panel who provided very valuable comments and suggestions on our model and its assumptions, and on the various scenarios. We are especially grateful to Dr John Holmes (Senior Lecturer in Liaison Psychiatry of Old Age, University of Leeds) who provided advice and further information on the Leeds hospitals study. Figure 8. Variations in hospital stay expenditure resulting from a policy to ensure days to surgery are no greater than 24 hours .
Financial Market Contagion during the Global Financial Crisis

Scholars worldwide have provided both theoretical and empirical insights into financial market contagion. The devastation from the recent financial crisis is immeasurable, and researchers commonly believe that the crisis seemingly originated from the U.S. and spread immediately to the other global financial hubs. Several studies have been conducted on financial markets, but this issue has yet to be addressed. Using U.S. dollar-denominated MSCI daily indices for the period 2006–2010, this paper employs Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) and vector error correction (VEC) models to address the multi-dimensional phenomena around financial market contagion. The empirical results demonstrate the existence of contagion in the financial markets during the global crisis. However, the crisis originated in the U.S., and its effects escalated immediately to the other global markets. The results also indicate that benefits from portfolio diversification decayed significantly among countries during the crisis.
Analyse et approximation numérique de quelques modèles macroscopiques de trafic routier

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Analyse et approximation numérique de quelques modèles macroscopiques de trafic routier Paola Goatin
NEURAL NETWORKS APPLIED TO STOCK MARKET FORECASTING: AN EMPIRICAL ANALYSIS

Neural networks are an artificial intelligence method for modeling complex target functions. For certain types of problems, such as learning to interpret complex real-world sensor data, artificial neural networks (ANNs) are among the most effective learning methods. During the last decade, they have been widely applied to the domain of financial time series prediction, and their importance in this field is growing. This paper aims to analyze neural networks for financial time series forecasting, specifically, their ability to predict future trends of North American, European, and Brazilian stock markets. Their accuracy is compared to that of a traditional forecasting method, generalized autoregressive conditional heteroskedasticity (GARCH). Furthermore, the best choice of network design is examined for each data sample. This paper concludes that ANNs do indeed have the capability to forecast the stock markets studied, and, if properly trained, robustness can be improved, depending on the network structure. In addition, the Ashley–Granger–Schmalancee and Morgan–Granger–Newbold tests indicate that ANNs outperform GARCH models in statistical terms.
Comparative Study of Membrane Potential-Sensitive Fluorescent Probes and their Use in Ion Channel Screening Assays

In this study, the authors compared and evaluated 4 membrane potential probes in the same cellular assay: the oxonol dye DiBAC4(3), the FLIPR membrane potential (FMP) dye (Molecular Devices), and 2 novel fluorescence resonance energy transfer (FRET) dye systems from PanVera [CC2-DMPE/DiSBAC2(3)] and Axiom [DiSBAC1(3)/DiSBAC1(5)]. The kinetic parameters of each membrane probe were investigated in RBL-2H3 cells expressing an endogenous inward rectifier potassium channel (IRK1). The FMP dye presented the highest signal over background ratio whereas the FRET dyes from PanVera gave the fastest response. The determination of IC50 values for 8 different channel modulators indicated a good correlation between the 4 membrane probe systems. The compound-dye interaction was evaluated in the presence of compounds at 10 [. proportional]M and clearly indicated no effect on the FMP or the PanVera donor dye, whereas some major interference with the oxonol probes was observed. Using a cell permeabilization assay in the presence of gramicidin, the authors concluded that the FRET dyes from PanVera and the FMP dye are unable to measure the gramicidin-induced cell membrane hyperpolarizations. The 4 dye systems were investigated under high-throughput screening (HTS) conditions, and their respective Z' parameter was deter-mined. The characteristics of each dye system and its potential use in HTS assays is discussed. (Journal of Biomolecular Screening 2003:533-543)
An Introduction to Expert Systems

As indicated in the quote above, the great Sherlock Holmes (and his physician creator, Sir Arthur Conan Doyle) realized the limitation of human memory and thought. A recent editorial in the Annals of Internal Medicine discussed this problem in the context of modern medicine and similarly referred to "the brain’s limited capacity for storage and processing" of medical information.2 In the past, physicians have attempted to overcome these limitations by the use of referrals, journals and textbooks but with unsatisfactory results.3 The conclusions of a study undertaken by the Massachusetts Medical Society and the National Academy of Sciences suggested that the situation could be improved with computer technology.4 One type of advanced computer technology designed specifically to assist in decision making is expert systems, the product of research in artificial intelligence.
Corrigendum: Conical plurisubharmonic measure and new cross theorems

In the previous version of this paper we prove a theorem on the boundary behavior of the conical plurisubharmonic measure. However, the proof turns out to be incomplete. In the present version we give a corrected proof of this theorem. We next apply it to the theory of separately holomorphic functions. These applications are presented in a more accessible way than in the previous version.
Towards application/file-level characterization of block references: a case for fine-grained buffer management

Two contributions are made in this paper. First, we show that system level characterization of file block references is inadequate for maximizing buffer cache performance. We show that a finer-grained characterization approach is needed. Though application level characterization methods have been proposed, this is the first attempt, to the best of our knowledge, to consider file level characterizations. We propose an Application/File-level Characterization (AFC) scheme where we detect on-line the reference characteristics at the application level and then at the file level, if necessary. The results of this characterization are used to employ appropriate replacement policies in the buffer cache to maximize performance. The second contribution is in proposing an efficient and fair buffer allocation scheme. Application or file level resource management is infeasible unless there exists an allocation scheme that is efficient and fair. We propose the ΔHIT allocation scheme that takes away a block from the application/file where the removal results in the smallest reduction in the number of expected buffer cache hits. Both the AFC and ΔHIT schemes are on-line schemes that detect and allocate as applications execute. Experiments using trace-driven simulations show that substantial performance improvements can be made. For single application executions the hit ratio increased an average of 13 percentage points compared to the LRU policy, with a maximum increase of 59 percentage points, while for multiple application executions, the increase is an average of 12 percentage points, with a maximum of 32 percentage points for the workloads considered.
For a Few Euros More

Although perceived by candidates and parties as important in affecting political outcomes, the link between spending and success in multi-candidate, multiparty election campaigns remains unproven. Not only are there relatively few studies of campaign spending effects in multi-party systems, there are none examining the effect under the Single Transferable Vote (STV) electoral system. Our study examines spending effects in the Irish local elections of 1999 using STV with district magnitudes between 3 and 7 seats, contested by a median of 10 candidates in each district. Using detailed data on 1,838 candidates from 180 local constituencies and 30 councils, we provide precise estimates of the relationship between campaign spending at the candidate level in each district and electoral success, including the probability of winning. In a context where spending is miniscule relative to other contexts, and takes place under a completely different electoral system, our results echo previous studies from other contexts showing a strong effect of challenger spending and only weak effects of incumbent spending. Once allowance is made for the endogeneity of incumbent spending, however, we find a much less substantial difference between the effectiveness of spending by challengers and by incumbents, except on the marginal effect of spending on the probability of winning, where challenger spending is shown to be much more important.
Predicting In Vivo Efficacy of Potential Restenosis Therapies by Cell Culture Studies: Species-Dependent Susceptibility of Vascular Smooth Muscle Cells

Although drug-eluting stents (DES) are successfully utilized for restenosis therapy, the development of local and systemic therapeutic means including nanoparticles (NP) continues. Lack of correlation between in vitro and in vivo studies is one of the major drawbacks in developing new drug delivery systems. The present study was designed to examine the applicability of the arterial explant outgrowth model, and of smooth muscle cells (SMC) cultures for prescreening of possible drugs. Elucidation of different species sensitivity (rat, rabbit, porcine and human) to diverse drugs (tyrphostins, heparin and bisphsophonates) and a delivery system (nanoparticles) could provide a valuable screening tool for further in vivo studies. The anticipated sensitivity ranking from the explant outgrowth model and SMC mitotic rates (porcine>rat>>rabbit>human) do not correlate with the observed relative sensitivity of those animals to antiproliferative therapy in restenosis models (rat≥rabbit>porcine>human). Similarly, the inhibitory profile of the various antirestenotic drugs in SMC cultures (rabbit>porcine>rat>>human) do not correlate with animal studies, the rabbit- and porcine-derived SMC being highly sensitive. The validity of in vitro culture studies for the screening of controlled release delivery systems such as nanoparticles is limited. It is suggested that prescreening studies of possible drug candidates for restenosis therapy should include both SMC cell cultures of rat and human, appropriately designed with a suitable serum.
Finite-dimensional attractors for the Bertozzi--Esedoglu--Gillette--Cahn--Hilliardequation in image inpainting

In this article, we are interested in the study of the asymptotic behavior, in terms of finite-dimensional attractors, of a generalization of the Cahn--Hilliard equation with a fidelity term (integrated over $\Omega\backslash D$ instead of the entire domain $\Omega$, $D \subset \subset \Omega$). Such a model has, in particular, applications in image inpainting. The difficulty here is that we no longer have the conservation of mass, i.e. of the spatial average of the order parameter $u$, as in the Cahn--Hilliard equation. Instead, we prove that the spatial average of $u$ is dissipative. We finally give some numerical simulations which confirm previous ones on the efficiency of the model.
Together we stand: Siamese Networks for Similar Question Retrieval

Community Question Answering (cQA) services like Yahoo! Answers 1 , Baidu Zhidao 2 , Quora 3 , StackOverﬂow 4 etc. provide a platform for interaction with experts and help users to obtain precise and accurate answers to their questions. The time lag between the user posting a question and receiving its answer could be reduced by retrieving similar historic questions from the cQA archives. The main challenge in this task is the “lexico-syntactic” gap between the current and the previous questions. In this paper, we pro-pose a novel approach called “Siamese Convolutional Neural Network for cQA (SCQA)” to ﬁnd the semantic similarity between the current and the archived questions. SCQA consist of twin convolutional neural networks with shared parameters and a contrastive loss function joining them. SCQA learns the similarity metric for question-question pairs by leveraging the question-answer pairs available in cQA forum archives. The model projects semantically similar question pairs nearer to each other and dissimilar question pairs far-ther away from each other in the semantic space. Experiments on large scale real-life “Yahoo! Answers” dataset reveals that SCQA outperforms current state-of-the-art approaches based on translation models, topic models and deep neural network
Theory of Stochastic Optimal Economic Growth

Stochastic optimal growth involves the study of the optimal intertemporal allocation of capital and consumption in an economy where production is subject to random disturbances. The theory traces its roots to the seminal work on deterministic optimal growth by Ramsey [106], Cass [21] and Koopmans [55]. Its influence has been enhanced by research that shows how the convex stochastic growth model can be decentralized to represent the behavior of consumers and firms in a dynamic competitive equilibrium of a productive economy ([102], [115], [15]). This makes the stochastic optimal growth model useful both as a normative exercise and in the development of positive theories of how the economy works. As a consequence, the theory has emerged as one of the central paradigms of dynamic economics. It is based on a simple, yet powerful model that encompasses fundamental questions that are basic to any theory of dynamic economic behavior: What are the characteristics and determinants of optimal policies? What are the economic incentives that govern the optimal intertemporal allocation of resources? What is the transient and long run behavior of variables in the model? Under different assumptions the model admits a rich set of answers to these questions. Historically, the main focal point of the theory has been issues of aggregate economic growth. At the same time its primary variable, capital, has a flexible interpretation that allows the model and its extensions to represent a wide variety of economic problems ranging from the study of business cycles ([59], [63]) and asset pricing ([14], [15]) to the allocation of renewable natural resources ([77], [82], [83]). Equally important, the model provides a strong theoretical foundation for applied analysis of these problems. The model can be solved numerically and has proved a testing ground for many numerical techniques used today in the analysis of dynamic economic problems. This chapter provides an overview of key results the theory of discounted stochastic optimal growth in discrete time.1 The paper begins with an analysis of