Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrochemical performance of hierarchical porous carbon materials obtained from the infiltration of lignin into zeolite templates.

Hierarchical porous carbon materials prepared by the direct carbonization of lignin/zeolite mixtures and the subsequent basic etching of the inorganic template have been electrochemically characterized in acidic media. These lignin-based templated carbons have interesting surface chemistry features, such as a variety of surface oxygen groups and also pyridone and pyridinic groups, which results in a high capacitance enhancement compared to petroleum-pitch-based carbons obtained by the same procedure. Furthermore, they are easily electro-oxidized in a sulfuric acid electrolyte under positive polarization to produce a large amount of surface oxygen groups that boosts the pseudocapacitance. The lignin-based templated carbons showed a specific capacitance as high as 250 F g(-1) at 50 mA g(-1) , with a capacitance retention of 50 % and volumetric capacitance of 75 F cm(-3) at current densities higher than 20 A g(-1) thanks to their suitable porous texture. These results indicate the potential use of inexpensive biomass byproducts, such as lignin, as carbon precursors in the production of hierarchical carbon materials for electrodes in electrochemical capacitors.
Advances in the laboratory diagnosis of viral respiratory disease

Background In recent years significant advances in the laboratory diagnostics available to detect respiratory viral infections have been achieved. Methods This article presents the types of diagnostic methods currently available to the practitioner, as well as those on the horizon. The article covers tissue culture, serology and direct examination as well as some rapid diagnostic techniques and molecular assays, previewing developing new technology. Conclusions Laboratory diagnosis will likely be clinically useful in some but not all cases of viral infection. As new diagnostic methods become widely available, it is increasingly important to develop guidelines for laboratory testing when viral illness is suspected.
Phase diagrams of mesomorphic mixtures

We have combined the Maier Saupe theory [1] of the nematic-isotropic transition and the Flory Huggins theory of mixtures to describe the phase diagrams of two nematogens A+B. The two components can have different order parameters S A , S B in the mixture. We can then predict the morphology of the phase diagrams in term of a relatively small number (4) of interaction parameters. The final numerical calculations are restricted to cases where the clearing points of the two components are nearly equal (cases of chemical similarity). For certain sets of parameters we find a rather remarkable phase diagram with two consolute points ― one at high temperatures in the isotropic phase and a second one at lower temperatures in the nematic phase. We also discuss the effects of chain length on the phase diagrams: when one component is a nematogenic polymer [2] with mesogenic side groups; and when the two components are polymers Combinaison de la theorie de la transformation isotrope-nematique de Maier-Saupe et la theorie des melanges de Flory-Huggins pour decrire les diagrammes de phase de deux nematogenes (A, B) qui peuvent avoir des parametres d'ordre differents. Prevision de la forme des diagrammes de phase avec 4 parametres seulement. Discussion de l'effet de la longueur de chaine quand un composant est un polymere nematogene avec des groupes lateraux mesogenes et quand les deux composants sont des polymeres
Designed to Succeed: Participatory Governance, Transaction Cost, and Policy Performance

This article examines the effect of participatory governance on policy performance in the United States, which is shaped by external and internal factors related to transaction cost. Externally, if transaction-cost-related policy conditions are uncertain-thereby increasing transaction cost-the effect of participatory governance on policy performance is less positive. Internally, noninstitutionalized participatory governance methods (e.g., public meetings) are less effective than institutionalized ones in improving policy performance (e.g., advisory committees). In addition, these internal and external factors affect the choice of participatory governance methods by government agencies: agencies are more likely to employ institutionalized participatory governance methods under low-transaction-cost policy conditions.
A statistical model based post-filtering algorithm for residual echo suppression

This invention provides a two-stage leaching procedure for manganese nodules for obtaining directly in one leaching stage the metal values other than manganese in one ammoniacal aqueous solution. The manganese nodules are reduced and then leached initially utilizing a solution of an ammonium salt, e.g., ammonium sulfate, to selectively leach out the manganese value, followed by a second stage leaching with an ammoniacal solution, to leach out the nickel, cobalt and copper values. The nickel, cobalt and copper values can then be individually separated from the second leach solution by liquid ion exchange extraction.
Neural Network Application on Ship Motion Prediction

The swing motion of the ship, which is mainly caused by sea wind and sea wave while on cruise, has significant impacts on completing the task of the ship. The paper analyzed the six degree of freedom ship motion. Put forward the characteristic of time series about ship motion methods. Based on the Back-Propagation neural network which has the characteristic that it can approach any nonlinear function in theory. Established the neural network model which is used to analyze the time series, and provided a Back-Propagation algorithm. Calculated an example. The calculation and results show that neutral network prediction is better than time series analysis. Therefore, it provides a new method for short-term ship motion prediction.
The Home-market Effect across Industries with Heterogeneous Firms

According to Krugman’s home-market effect hypothesis a large country has more firms or products in an increasing returns to scale sector than does a small country. However, the large country’s share of firms (or products) across industries, which are subject to increasing returns to scale, may vary with the characteristics of an industry. This study builds a model of monopolistic competition with heterogeneous firms to investigate several characteristics of an industry that affect the size of the home market effect. Our model predicts that industries with low trade costs, high fixed domestic costs, low fixed export costs, and high productivity dispersion will concentrate more in the large country. Using 3-digit SIC industries from 28 high income countries, the model’s predictions are empirically tested. The empirical results are consistent with the predictions of the theoretical model.
A 13-bp Deletion in the 3′ Untranslated Region of the β-Globin Gene Causes β-Thalassemia Major in Compound Heterozygosity with IVSII-1 Mutation

Objective: To describe hematological and molecular features of a 13-bp deletion in the 3′ untranslated region(3′ UTR) of the β-globin gene in carrier individuals and a compound heterozygous patient. Subjects and Methods: Five members of an Iranian family of Persian ethnic origin were studied. Red blood cell indices and hemoglobin analysis were carried out according to standard methods. Genomic DNA was obtained from peripheral blood cells by salting-out procedures. β-Globin gene amplification and DNA sequencing were performed. Results: One patient had a 13-bp deletion in the 3′ UTR of the β-globin gene that causes the β-thalassemia phenotype in combination with the IVSII-1 (G→A) mutation. The patient had inherited the IVSII-1 (G→A) mutation from his mother, while the second β-globin gene (inherited paternally) had a 13-bp deletion at nucleotide 90 downstream of the termination codon (CD +90 del 13 bp). The patient’s father and paternal grandmother, who are carriers of this deletion, had no hematological abnormalities. Conclusion: This case showed a patient with a 13-bp deletion in the 3′ UTR of β-globin gene that could cause a slight decrease in the stability of the mRNA, but did not have a hematological effect in the heterozygotes. The 13-bp deletion could be clinically important only in situations where β-chain synthesis in trans is compromised.
THE ROLE OF CANDIDA SURVEILLANCE CULTURES FOR IDENTIFICATION OF A PRETERM SUBPOPULATION AT HIGHEST RISK FOR INVASIVE FUNGAL INFECTION

Candida surveillance cultures were obtained from 51 neonatal intensive care unit patients. Sixteen infants showing positive cultures developed subsequent Candida infection, whereas it did not occur for the 35 infants with negative cultures. Fifteen of 16 infants (<1000 g) had <27 weeks of gestational age. Antifungal treatment was started at the time colonization was detected; only 1 infant died of Candida infection.
Androgen Stimulates Transcription and Replication of Xenotropic Murine Leukemia Virus-Related Virus

ABSTRACT Xenotropic murine leukemia virus-related virus (XMRV) is a gammaretrovirus originally identified in a subset of prostate cancer patients. Because androgens stimulate prostate tumors and some retroviruses, we investigated the effects of dihydrotestosterone (DHT) on XMRV transcription and replication. Transcription from the XMRV U3 region was stimulated up to 2-fold by DHT, but only in cells containing a functional androgen receptor. Mutations in the glucocorticoid response element (GRE) of XMRV impaired basal transcription and androgen responsiveness. Furthermore, DHT stimulated XMRV replication 3-fold, whereas androgen inhibitors (casodex and flutamide) suppressed viral growth up to 3-fold. Findings suggest that integration of the XMRV long terminal repeat (LTR) into host DNA could impart androgen stimulation on cellular genes.
Inducible Nitric Oxide Synthase Mediates Delayed Cardioprotection Induced by Morphine In Vivo: Evidence from Pharmacologic Inhibition and Gene-knockout Mice

Background:It is not known whether morphine induces delayed cardioprotection against ischemia and reperfusion. The authors measured the delayed preconditioning induced by morphine and determined the role of inducible nitric oxide synthase (iNOS) in mediating this effect using a pharmacological inhibitor and iNOS gene-knockout mice. Methods:Adult male wild-type and iNOS gene-knockout (B6, 129) mice were treated with morphine (0.3 or 0.1 mg/kg intraperitoneal) or saline. Twenty-four hours later, mice were subjected to 45 min of coronary artery occlusion followed by 120 min of reperfusion. S-methylthiourea sulfate (3 mg/kg, intraperitoneal) was given 30 min before the occlusion to block iNOS. Infarct size as a percentage of the area at risk was determined by triphenyltetrazolium chloride staining. iNOS and endothelial nitric oxide synthase expression were measured by Western blot. Results:Infarct size was significantly reduced in wild-type mice from 43.1 ± 5.3% in the saline group to 22.4 ± 4.4% in the higher-dose morphine group (0.3 mg/kg) (P < 0.05). This cardioprotective effect was abolished by S-methylthiourea sulfate (43.3 ± 3.9%) and was absent in iNOS gene-knockout mice (42.3 ± 4.7%). Pretreatment with the lower dose of morphine (0.1 mg/kg) did not reduce infarct size (41.1 ± 5.4%). A significant increase in myocardial iNOS expression was observed 24 h after morphine administration (0.3 mg/kg but not 0.1 mg/kg; P < 0.05), whereas endothelial nitric oxide synthase remained unchanged. Conclusions:Pretreatment with morphine induces delayed cardioprotection in mice. The authors demonstrated an obligatory role for iNOS in mediating morphine-induced delayed cardioprotection.
Control de Movil Robotico Mediante Interfaz Cerebro Computador

En este articulo se presenta una interfaz de control que permite comandar el movimiento de un robot movil en funcion de la captura de senales provenientes del cerebro del usuario. Dichas senales son adquiridas e interpretadas por medio del dispositivo Emotiv Epoc, el cual cuenta con 14 sensores tipo electrodo que captan senales electroencefalograficas (EEG) de alta resolucion, que despues son enviadas a un equipo de computo para ser procesadas. Se desarrolla una interfaz cerebro-computador (BCI) basada en el software y SDK del desarrollador del Emotiv mediante la cual se comanda de forma remota el robot movil. Se realizan pruebas de funcionalidad con el sensor para discriminar una intencion de desplazamiento por parte de un grupo de usuarios y un controlador difuso para sostener la direccion en casos de perdida de la concentracion. Como conclusion, se logra obtener un sistema eficiente para la manipulacion del robot.
Equipment Fault Prognosis Based on Temporal Association Rules

Equipment fault prognosis is important for reliability, operational safety, and efficient performance of equipment. Temporal fault data model is built according to the principles of the Apriori traditional association rules algorithm based on the characteristics of fault data. An Improved Apriori algorithm and frequent temporal association rules algorithm are proposed in this study by converting fault data to temporal item sets matrix. Equipment fault trends are predicted by mining the frequent temporal association rules of fault data based on the algorithm, which provides good support for equipment maintenance and management. At last an example is given to prove the feasibility and practical application of proposed algorithms. DOI : http://dx.doi. org/10.11591/telkomnika.v12i3. 4563 Full Text: PDF
Interference aware resource allocation for LTE uplink transmission

In this paper, we investigate a multi-cell Long Term Evolution (LTE) uplink resource allocation problem to mitigate the inter-cell interference based on interference graph, in which the vertices represent the user equipments (UEs) and the edges represent critical interference relations between the UEs. Besides, to avoid increasing the overhead of LTE system, we derive the interference graph based on the channel statistics of cellular links. Given that the uplink resource allocation is NP-hard, two heuristic algorithms are proposed to give solutions with reasonable complexity. The first one is centralized algorithm based on the global interference graph, and the other one is distributed algorithm based on local interference graph. Both the centralized and distributed algorithms can mitigate the inter-cell interference evidently. We show by simulations that the centralized algorithm outperforms the distributed one in terms of throughput and fairness at the cost of higher overhead and complexity. As well, simulation results show that the cell-edge throughput improvements of the algorithms are more than 100% compared with improved riding peaks algorithm and the fairness factors are greater than 0.88.
Risk considerations in the management of customer equity

Customers are intangible assets of the firm. Customer equity represents the total value of the current and potential customers to the firm. When firms measure or manage customer equity, they typically focus on expected cash flow streams but not the risk associated with them. Hence, customer risk complements the concept of customer equity – it allows managers to assess whether the firm’s returns from customers are commensurate with their risk. The notion of balancing customer equity and customer risk is rather new, so many scholars and managers have an incomplete understanding of how to manage the customer portfolio and optimize customer equity. The marketing literature has typically approached customer risk by considering the probability of customer defection and all other risks are assumed to be accounted for in the cost of capital. However, in the finance literature, risk is considered to arise from unanticipated variability in future cash flows. This chapter discusses the implications of this conceptualization of risk for managing customer equity. We argue that it is important to consider the variability or unpredictability of cash flows – arising from underlying customer interactions, consumption patterns, and purchase behavior, plus from organizational processes that support them. An understanding of customer variability is critical for firms to effectively forecast, allocate expenditures, manage customer equity, and prepare for the future via strategic investments. Risk can be managed both at the individual customer level and the level of the overall customer portfolio. Although a customer portfolio and a financial portfolio seem similar, the underlying assumptions concerning risk are very different. Nevertheless, we can build upon the financial approach to measuring and managing risk to generate important insights for managing customer portfolios. A firm should identify customer risk that can (and should) be divested away because it does not reap higher returns for assuming this risk and (instead) suffers losses when conditions change (Gupta et al., 2006). Tradeoffs between customer risk and return have become increasingly important due to the critical role of the
Mining Community Structures in Multidimensional Networks

We investigate the problem of community detection in multidimensional networks, that is, networks where entities engage in various interaction types (dimensions) simultaneously. While some approaches have been proposed to identify community structures in multidimensional networks, there are a number of problems still to solve. In fact, the majority of the proposed approaches suffer from one or even more of the following limitations: (1) difficulty detecting communities in networks characterized by the presence of many irrelevant dimensions, (2) lack of systematic procedures to explicitly identify the relevant dimensions of each community, and (3) dependence on a set of user-supplied parameters, including the number of communities, that require a proper tuning. Most of the existing approaches are inadequate for dealing with these three issues in a unified framework. In this paper, we develop a novel approach that is capable of addressing the aforementioned limitations in a single framework. The proposed approach allows automated identification of communities and their sub-dimensional spaces using a novel objective function and a constrained label propagation-based optimization strategy. By leveraging the relevance of dimensions at the node level, the strategy aims to maximize the number of relevant within-community links while keeping track of the most relevant dimensions. A notable feature of the proposed approach is that it is able to automatically identify low dimensional community structures embedded in a high dimensional space. Experiments on synthetic and real multidimensional networks illustrate the suitability of the new method.
MCF‐10AT: A Model for Human Breast Cancer Development

▪ Abstract: A number of lesions, collectively termed Proliferative Breast Disease (PBD), have been associated with high risk of developing breast cancer. Understanding of the natural history of PBD and its relationship to breast cancer progression has been hampered by the lack of an experimental model. MCF‐10AT cells are of human, breast epithelial cell origin. They grow as xenografts in immune‐incompetent mice where they produce normal‐appearing ducts, atypical hyperplasia, carcinoma‐in‐situ, and invasive carcinoma. Estrogen supplementation of the mice accelerates development of cancer. The MCF‐10AT model of PBD offers a new approach to the study of early breast cancer progression and its prevention. ▪
Phase unwrapping in the three-point Dixon method for fat suppression MR imaging.

PURPOSE TO present an algorithm for performing phase unwrapping for fat and water signal separation in the three-point Dixon (3PD) method of magnetic resonance (MR) imaging. MATERIALS AND METHODS The algorithm is based on a two-dimensional region-growing approach, which tracks phase evolution in 3PD images and unwraps the phase when a 2 pi jump is detected. The unwrapped phase data are consecutively used to calculate fat and water signal components on a per-pixel basis. The method was tested in eight volunteers. RESULTS The algorithm creates four output images: standard spin-echo, fat suppression, water suppression, and phase map images. This method corrects for the effects of magnetic field inhomogeneities and provides spatially uniform fat signal suppression superior to that achievable with the standard method. CONCLUSION This method of 3PD data reconstruction appears to be promising for routine application of fat suppression MR imaging in a clinical setting.
Short Selling ETFs

We provide novel evidence that arbitrageurs use exchange-traded funds (ETFs) as an avenue to circumvent short-sale constraints at the stock level. Using a large sample of U.S. equity ETF holdings, we document that shorting activity on ETFs rises with the difficulty of shorting the underlying stocks. Stocks that are heavily shorted via their holding ETFs underperform those lightly shorted by 94 basis points per month. The return predictability of ETF short selling on individual stocks is distinct from stock-level shorting measures, and is concentrated among stocks that face the most severe arbitrage constraints. Across a broad set of capital market anomalies, we find that anomaly returns are significantly attenuated when ETF ownership is high. Our evidence suggests that ETFs contribute to a more informationally efficient market by allowing arbitrageurs to target overpriced stocks that are otherwise difficult to short.
Contactless energy transmission system for linear servo motor

This paper proposes the calculation method of magnetic coupling coefficient of the contact-less energy transmission system for the linear servo motor by the three-dimensional finite element method with a variation of the secondary core positions. The primary, secondary self and leakage inductances, and the capacitances of a resonant circuit are calculated by the finite element analysis results. From these values, the magnetic coupling coefficients are obtained. The secondary voltages and currents at the secondary core positions are calculated by using the resonant circuit and compared.
Integrating Railway Maintenance Data - Development of a Semantic Data Model to Support Condition Monitoring Data from Multiple Sources

Railway networks comprise a large number of information systems, many of which are implemented by different stakeholders according to different design requirements, and in different ways. Owing to the safety-critical nature of these systems, data is rarely shared across boundaries, and the potential for re-use of information is lost. Using ontology, it is hoped that information from these systems can be extracted and shared, in order to facilitate better operational decision-making. This paper examines the aspects of data re-use likely to benefit the industry, and describes a railway condition monitoring ontology that is being designed in conjunction with several industrial stakeholders to improve operational efficiency.