Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypertension as a predictive biomarker for efficacy of bevacizumab treatment in metastatic colorectal cancer: a meta-analysis.

PURPOSE Bevacizumab has demonstrated survival benefit in patients with metastatic colorectal cancer (mCRC) when combined with chemotherapy. However, no validated predictors currently exist for its efficacy. Hypertension has been evaluated as a surrogate marker for efficacy of bevacizumab, although analyses, to date, have yielded conflicting results. The aim of this meta-analysis was to dissect the association between hypertension and efficacy of bevacizumab treatment in mCRC. METHODS We searched PubMed, EMBASE, Chinese Biomedical Database (CBM), and Wan Fang Digital Journals before September, 2013. The primary clinical outcomes included objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Relative risk (RR) or summary hazard ratio (HR) were calculated using a fixed-effects or random-effects model, depending on the heterogeneity of the included studies. Studies meeting our search criteria were assessed. RESULTS Nine studies were considered eligible, with 1674 mCRC patients included. Six (308 patients, 104 with hypertension), 8 (1661 patients, 431 with hypertension) and 5 (1512 patients, 408 with hypertension) studies were eligible for the ORR, PFS and OS meta-analysis, respectively. Bevacizumab-related hypertension was associated with increased ORR (RR= 1.63; 95% CI 1.26-2.12; p=0.0002), improved PFS (HR=0.68; 95% CI 0.58-0.79; p<0.00001) and OS (HR=0.52; 95% CI 0.42-0.66; p<0.00001). There was no statistically significant difference between-study heterogeneity. CONCLUSION These analyses suggest that hypertension may be a potential biomarker for efficacy of bevacizumab treatment in mCRC. Additional large prospective trials are required to confirm its predictive role.
The Role of Globalization in the Within-Industry Shift Away from Unskilled Workers in France

Growth in international trade and globalization has been correlated in nearly all countries with a worsening of the less skilled labor situation relative to the skilled. In this empirical paper, I show that an important component of recent globalization in France has been a huge growth in vertical specialization -- the completion of the different production stages of a good in different countries. By shifting relative labor demand across countries, globalization of this form could explain the poor relative showing of unskilled labor in industrial countries. Using input-output tables and labor data, I find that in France vertical specialization -- defined as the share of imported inputs in production -- rose from 9% in 1977 to 14% in 1993. Further estimations show that vertical specialization contributed from 11% to 15% of the decline in the share of unskilled workers in French manufacturing employment for the 1977-1985 period and for 25% of the decline in the 1985-1993 period.
Metabolism of ara-C by blast cells from patients with ANLL.

The dose-response relationship between extracellular concentration of cytosine arabinoside (ara-C) and intracellular formation of the putative active metabolites of ara-C [ara-C incorporation into DNA and intracellular pools of ara-C in triphosphate form (ara-CTP)] was investigated in blast cells obtained from patients with acute nonlymphocytic leukemia (ANLL) by exposing these cells in vitro to 10, 100, or 1,000 nmol/L of ara-C. We studied 23 untreated patients who subsequently achieved complete remission (CR) with a regimen using daunorubicin and conventional doses of ara-C (ara-C-sensitive group), and 30 patients judged to be ara-C-resistant either by failing initial induction therapy (16 patients) or by having relapsed on an ara-C-containing maintenance regimen (14 patients). In both patient groups, ara-C incorporation into DNA and intracellular ara-CTP both displayed statistically significant increases in response to increasing extracellular concentrations of ara-C (P = .0001 in both cases), with the rate of increase of ara-CTP greater than that of ara-C incorporation. Moreover, blast cells from all patients, even those who were most clinically resistant to ara-C, were able to form ara-CTP and to incorporate ara-C into DNA. Each tenfold increment in extracellular ara-C concentration caused an 8.5-fold increase in ara-CTP, but only a 3.6-fold increase in ara-C incorporation into DNA. Thus, the efficiency of incorporation of ara-C into DNA (defined as the ratio of ara-C incorporation to ara-CTP pools) decreased by 58% with each tenfold increment in the extracellular concentration of ara-C (P less than .0001), presumably as a result of the inhibitory effect of ara-CTP on DNA polymerase. Using an analysis of covariance, modest differences were found in the levels of the ara-C metabolite variables in the ara-C-sensitive group as compared with the resistant group. However, because there was considerable overlap in ara-C metabolite formation among the patient groups, it was not possible to predict clinical outcome by these in vitro assessments of ara-C metabolism.
Taking the perspective of customers: theory, exercises, experiences and practical recommendations

It is important that companies consider their products and services, as well as new ideas concerning them, from the customer’s viewpoint. We assert that simple empathising exercises can, when facilitated skilfully, help companies in this pursuit. This article presents a series of five empathising exercises, the theoretical notions behind them, an analysis of the experiences of business developers who put them into practice, and practical advice for facilitating them. The central component of the exercises is using customer persona as target of empathising. Our empirical analysis shows how the process of empathising, i.e., taking the perspective of the customer persona, is depicted by the business developers who participated in the exercises.
An adaptive multi-rate system for visual tracking in augmented reality applications

The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracking of an object in augmented reality environments. The multi-sensor system consists of a webcam and a 3-axis MEMS inertial sensor both with different sample rates. The augmented reality application has been designed for the object detection problem, and it has been tested experimentally in a suitably developed test set-up.
Catheter ablation of papillary muscle arrhythmias: Implications of mitral valve prolapse and systolic dysfunction

The left ventricular (LV) papillary muscles are important components of the mitral valve apparatus. Catheter ablation of ventricular arrhythmias from these sites is challenging. We aim to describe the association between LV papillary muscle ventricular arrhythmias (VAs) and mitral valve prolapse (MVP), and to determine the outcomes of ablation in these patients with a focus on those with MVP and cardiomyopathy.
Inverse fourier transform technique of measuring averaged absorption cross section in the reverberation chamber and Monte Carlo study of its uncertainty

The averaged absorption cross section (ACS) of a lossy object characterises its ability to capture power from diffused electromagnetic waves. The averaged ACS is very important in many EMC research areas such as indoor wireless channel modelling and human safety exposure study. The measurement of averaged ACS in a reverberation chamber can be achieved by measuring the rate of power loss in the time domain, however this technique requires dense frequency sampling for taking the inverse Fourier transform, which is very time consuming. A new scenario which accelerates the measurement speed is presented in this paper. It combines the technique of non-linear curve fitting to the power delay profile, segmented frequency sweeping and continuous mode stirring. The scenario was validated by measuring the averaged ACS of a hollow plastic sphere filled with deionized water in an EMC reverberation chamber. Measurement results showed a good accordance with the simulations and the measurement uncertainty was studied numerically with the Monte Carlo method.
Auditor licensing in the European Union: a comparative study based on cultural differences

This paper examines the links between the ways in which auditors are licensed in eleven EU countries and the cultures of those countries using the model developed by Gray (1988). The paper shows that there are significant differences in the ways that auditor licensing is carried out and that culture could be associated with the different approaches. The paper also discusses the methodology employed and makes suggestions for future research directions for both auditor licensing and culture-based comparative work.
Cost‐Effective Regulation of Nonpoint Emissions from Pastoral Agriculture: A Stochastic Analysis

type="main" xml:id="ajar12034-abs-0001"> Nutrient emissions from pastoral agriculture are a global cause of declining water quality. Their management is complicated through variability arising from climate and soil influences. This paper compares the implications of input-based policies and direct restrictions on leaching to achieve 10 and 20 per cent reductions in nitrogen (N) load, in the context of pasture-based New Zealand dairy farms. The most important mitigation practices on these farms are de-intensification (involving reductions in N fertiliser application and stocking rate) and the application of nitrification inhibitors. A stylised conceptual model, incorporating both sources of variability, is used to identify the implications of alternative policies. Direct restriction of estimated N leaching is the most cost-effective policy to reduce N leaching by 10 and 20 per cent. These results indicate the general insufficiency of input-based mechanisms for water quality improvement, given the low correlation between input use and leaching, possible substitution with unrestricted inputs and their failure to motivate the use of mitigation strategies. Additionally, model output indicates that inherent variability in water quality, mainly due to climate influences, can dominate the benefits of regulatory action in any given year.
A General Framework for Parameterized Schedulability Bound Analysis of Real-Time Systems

In real-time systems, utilization-based schedulability test is a common approach to determine whether or not tasks can be admitted without violating deadline requirements. The test is extremely simple, since it only needs to compare the utilization of the tasks with a predetermined bound. As such, utilization-based schedulability tests are suitable for online use. The challenge is how to derive a reasonable utilization bound for a given system. Most existing results are obtained on a case-by-case basis because of their analytical complexity. In this paper, we develop a flexible and unified representation framework of real-time systems (i.e., tasks and schedulers) based on network calculus techniques. Our representation framework, together with the proposed bound derivation method, leads to a general bound result, which is applicable to a large family of real-time systems.
Understanding the Crystallization Mechanism of a Wollastonite Base Glass Using Isoconversional, IKP Methods and Master Plots

The complex development of crystals found in the crystallization of SiO2–Al2O3–CaO–Na2O glass has been explained using Differential Thermal Analysis. The crystal growth process has been studied using isoconversional, invariant kinetic parameters, and master plots methods. The applied kinetic models have revealed activation energy values that are over 360 and 385 kJ/mol by employing the integral and differential kinetic methods, respectively. The crystallization process schedule that was previously observed using scanning electron microscopy has been corroborated in this study using the kinetic methods. The crystallization of wollastonite occurs through a complex two-stage mechanism, with early threedimensional growth of crystals (A3 mechanism) on the surface of glass particles followed by one-dimensional growth of needles (A3/2 mechanism) toward the interior of grains. The results presented in this article are in agreement with a previous paper that employed the Kissinger non-isothermal method and the Ligero approximation.
Finding Suspicious Activities in Financial Transactions and Distributed Ledgers

Banks and financial institutions around the world must comply with several policies for the prevention of money laundering and in order to combat the financing of terrorism. Nowadays, there is a raise in the popularity of novel financial technologies such as digital currencies, social trading platforms and distributed ledger payments, but there is a lack of approaches to enforce the aforementioned regulations accordingly. Software tools are developed to detect suspicious transactions usually based on knowledge from experts in the domain, but as new criminal tactics emerge, detection mechanisms must be updated. Suspicious activity examples are scarce or nonexistent, hindering the use of supervised machine learning methods. In this paper, we describe a methodology for analyzing financial information without the use of ground truth. A user suspicion ranking is generated in order to facilitate human expert validation using an ensemble of anomaly detection algorithms. We apply our procedure over two case studies: one related to bank fund movements from a private company and the other concerning Ripple network transactions. We illustrate how both examples share interesting similarities and that the resulting user ranking leads to suspicious findings, showing that anomaly detection is a must in both traditional and modern payment systems.
Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition

Recognizing multiple labels of images is a fundamental but challenging task in computer vision, and remarkable progress has been attained by localizing semantic-aware image regions and predicting their labels with deep convolutional neural networks. The step of hypothesis regions (region proposals) localization in these existing multi-label image recognition pipelines, however, usually takes redundant computation cost, e.g., generating hundreds of meaningless proposals with non-discriminative information and extracting their features, and the spatial contextual dependency modeling among the localized regions are often ignored or over-simplified. To resolve these issues, this paper proposes a recurrent attention reinforcement learning framework to iteratively discover a sequence of attentional and informative regions that are related to different semantic objects and further predict label scores conditioned on these regions. Besides, our method explicitly models long-term dependencies among these attentional regions that help to capture semantic label co-occurrence and thus facilitate multi-label recognition. Extensive experiments and comparisons on two large-scale benchmarks (i.e., PASCAL VOC and MS-COCO) show that our model achieves superior performance over existing state-of-the-art methods in both performance and efficiency as well as explicitly identifying image-level semantic labels to specific object regions.
THE LINKS BETWEEN THE PRICE OF OIL AND THE VALUE OF US DOLLAR

Using monthly data, this paper studies the cointegration between the real price of oil and the real effective exchange rate of US dollar allowing for structural breaks. Contrary to the conclusion from previous literature, this paper finds that the cointegration between the oil price and the value of US dollar does not significantly exist unless the effects of two structural breaks in the past, November 1986 and February 2005, are controlled for.
Binary Generative Adversarial Networks for Image Retrieval

The most striking successes in image retrieval using deep hashing have mostly involved discriminative models, which require labels. In this paper, we use binary generative adversarial networks (BGAN) to embed images to binary codes in an unsupervised way. By restricting the input noise variable of generative adversarial networks (GAN) to be binary and conditioned on the features of each input image, BGAN can simultaneously learn a binary representation per image, and generate an image plausibly similar to the original one. In the proposed framework, we address two main problems: 1) how to directly generate binary codes without relaxation? 2) how to equip the binary representation with the ability of accurate image retrieval? We resolve these problems by proposing new sign-activation strategy and a loss function steering the learning process, which consists of new models for adversarial loss, a content loss, and a neighborhood structure loss. Experimental results on standard datasets (CIFAR-10, NUSWIDE, and Flickr) demonstrate that our BGAN significantly outperforms existing hashing methods by up to 107% in terms of mAP (See Table 2).
An Analysis of the Reasons for the Asymmetries Surrounding Earnings Benchmarks

Several studies report an asymmetry in the distribution of earnings around specified benchmarks. However, doubt has arisen over whether the observed ‘kink’ in the distribution of earnings is solely caused by earnings management. We use a ratio analysis approach to examine a range of specific accruals for evidence of earnings management. We find little evidence that firms immediately above the benchmark have abnormal receivables, inventories or provisions. However, they do increase cash-from-customers and reduce inventory. Thus, our results support the recent research that suggests that firms engage in real actions to meet earnings benchmarks.
Study on Simulation of Machining Deformation and Experiments for Thin-walled Parts of Titanium Alloy

Deformation problems are main factors affecting the precision of machining the thinwalled parts. This paper focuses on the thin-walled parts of titanium alloy that is the difficult-to-machine material, based on the analysis of deformation characteristics and force, the milling force mathematical model of the ball-end milling cutter was established. On the basis of the 3D milling model of thin-walled parts of titanium alloy, the deformation regularity and cutting force variations were analyzed with the finite element simulation method. Through the experiments of machining thin-walled parts, the cutting force model was verified. The experiments results and simulations results match well. The work provides an effective basis for further study on the control of machining deformation of thin-wall parts of titanium alloy.
Density of sampling and interpolation in reproducing kernel Hilbert spaces

We derive necessary density conditions for sampling and for interpolation in general reproducing kernel Hilbert spaces satisfying some natural conditions on the geometry of the space and the reproducing kernel. If the volume of shells is small compared to the volume of balls (weak annular decay property) and if the kernel possesses some off‐diagonal decay or even some weaker form of localization, then there exists a critical density D with the following property: a set of sampling has density ⩾D , whereas a set of interpolation has density ⩽D . The main theorem unifies many known density theorems in signal processing, complex analysis, and harmonic analysis. For the special case of bandlimited function we recover Landau's fundamental density result. In complex analysis we rederive a critical density for generalized Fock spaces. In harmonic analysis we obtain the first general result about the density of coherent frames.
Changes in glucose fermentation pathways by an enriched bacterial culture in response to regulated dissolved H2 concentrations

It is well established that metabolic pathways in the fermentation of organic waste are primarily controlled by dissolved H2 concentrations, but there is no reported study that compares observed and predicted shifts in fermentation pathways induced by manipulating the dissolved H2 concentration. A perfusion system is presented that was developed to control dissolved H2 concentrations in the continuous fermentation of glucose by a culture highly enriched towards Thermoanaerobacterium thermosaccharolyticum (86 ± 9% relative abundance) from an originally diverse consortia in the leachate of a laboratory digester fed with municipal solid waste. Media from a 2.5 L CSTR was drawn through sintered steel membrane filters to retain biomass, allowing vigorous sparging in a separate chamber without cellular disruption. Through a combination of sparging and variations in glucose feeding rate from 0.8 to 0.2 g/L/d, a range of steady state fermentations were performed with dissolved H2 concentrations as low as an equivalent equilibrated H2 partial pressure of 3 kPa. Trends in product formation rates were simulated using a H2 regulation partitioning model. The model correctly predicted the direction of products redistribution in response to H2 concentration changes and the acetate and butyrate formation rates when H2 concentrations were less than 6 kPa. However, the model over‐estimated acetate, ethanol and butanol productions at the expense of butyrate production at higher H2 concentrations. The H2 yield at the lowest dissolved H2 concentration was 2.67 ± 0.08 mol H2/mol glucose, over 300% higher than the yield achieved in a CSTR operated without sparging. Biotechnol. Bioeng. 2015;112: 1177–1186. © 2014 Wiley Periodicals, Inc.
Returns to education in Sri Lanka: a pseudo-panel approach

This study employs a pseudo-panel approach to estimate the returns to education among income earners in Sri Lanka. Pseudo-panel data are constructed from nine repeated cross sections of Sri Lanka's Labor Force Survey data from 1997 to 2008, for workers born during 1953–1974. The results show that for males, one extra year of education increases monthly earnings by about 5% using the pseudo-panel estimation rather than 9% as in the ordinary least-squares (OLS) estimation. This indicates that not controlling for unobservables such as ability and motivation biases the OLS estimation of returns upwards by about 4% on average, driven mainly by what happens in urban areas. It also suggests that males with higher ability seem to be acquiring more years of education. This is contrary to what has been observed recently in countries such as Thailand [Warunsiri, S. , and R. McNown. 2010. “The Return to Education in Thailand: A Pseudo-Panel Approach. ” World Development 38 (1): 1616–1625], where the opportunity cost of education seems to be high, such that high-ability individuals leave education for the labour market.
Investigating The Fusion of Classifiers Designed Under Different Bayes Errors

We investigate a number of parameters commonly affecting the design of a multiple classifier system in order to find when fusing is most beneficial. We extend our previous investigation to the case where unequal classifiers are combined. Results indicate that Sum is not affected by this parameter, however, Vote degrades when a weaker classifier is introduced in the combining system. This is more obvious when estimation error with uniform distribution exists.