Miracle-dz/UniFAR-FTUs huggingface dataset:
Was there a (Methodological) Keynesian Revolution

1 I believe myself to be writing a book on economic theory which will largely revolutionise-not, I suppose, at once but in the course of the next ten years – the way the world thinks about economic problems (Keynes, 1935). 1. Introduction The purpose of this paper is to examine whether, how far, and in what sense we might say that there has been a Keynesian revolution at the level of methodology. This involves an interpretation of Keynes's expression 'the way the world thinks about economic problems' as referring, not just to the content of economics, but also to the mode of thought and specific methodology employed in addressing that content. It is hard to separate content from methodology; at least here we put the accent on methodology.
Emotion classification of Thai text based using term weighting and machine learning techniques

In this research, I proposed Emotion Classification of Thai Text based Using Term weighting and Machine Learning Techniques focusing on the comparison of various common term weighting schemes. I found Boolean weighting with Support Vector Machine is most effective in our experiments. I also discovered that the Boolean weighting is suitable for combination with the Information gain feature selection method. The Boolean weighting with Support Vector Machine algorithm yielded the best performance with the accuracy over all algorithms. Based on our experiments, the Support Vector Machine algorithm with the Information gain feature selection yielded the best performance with the accuracy of 77.86%. Our experimental results also reveal that feature weighting methods have a positive effect on the Thai Emotion Classification Framework.
Annotating attribution relations and their features

Attribution has attracted increasing attention in recent years following the development of Opinion Analysis and Information Extraction applications. Given a piece of information or an opinion, being able to correctly identify its source (either a specific entity e.g. President Obama or a class thereof e.g. experts, official sources, rumours) and determine how different sources and features of attribution affect the way information is perceived would be extremely beneficial. It would in fact enhance opinion-oriented applications of Language Technology and revolutionise the way we can select information, e.g. on the basis of source expertise and reliability. However, approaches to the automatic extraction of attribution relations have achieved only partial results to date and are therefore not sufficient to enable the development of reliable applications. In addition, there has been little or no attempt to discern the impact of different sources and attribution strategies on the perception and interpretation of the attributed material. Grounded on previous analysis of this relation in Italian [2] and English [4] news corpora, this study addresses several of the attribution strategies identified to develop a more comprehensive system for the extraction of attributions and their relevant features from news texts.
Synthesis, characterization, biodegradation, and drug delivery application of biodegradable lactic/glycolic acid polymers: I. Synthesis and characterization

A series of lactic/glycolic acid polymers with various molar ratios of lactic to glycolic acid and various molecular weights were synthesized using the ring-opening polymerization method. The polymerization conditions for the lactic/glycolic acid polymer synthesis were as follows: 150°C, 700 μm Hg, 3 h, 0.03 wt% of catalyst (stannous 2-ethyl-hexanoate) concentration. The molecular weight of these polymers was controlled by using a molecular weight controller, lauryl alcohol. The synthesized polymers have been characterized with respect to polymer composition, molecular weight, inherent viscosity, and glass transition temperature. The characterization experiments show a good correlation between the polymer compositions and the feed ratios of lactic to glycolic acid. The molecular weight of the lactic/glycolic polymers, ranging from 10 876 to 166 630 D and the intrinsic viscosity of the polymers, ranging from 0.16 to 0.86 dl g-1, are controlled by the amount of molecular weight controller used. The effect of the amount of the molecular weight controller on the polymer molecular weight and the polymer inherent viscosity was studied. Results indicate that the molecular weight and inherent viscosity of the polymers have a log-log linear relationship with the amount of molecular weight controller used. The lactic/glycolic acid polymers are amorphous, glassy, and transparent. The glass transition temperature of the polymers range from 21.95 to 51.29°C, depending on the polymer molecular weight and the composition.
Electrical Parameter Extraction & Modeling of Si 1-xGex HBT for HF Applications

SiGe technology is sincerely challenging III/V and II/VI technologies in the realm of high frequency electronics applications, for example optical fibre and mobile communications. In this paper a model of SiGe HBT with uniform impurity doping in the base for high frequency application is studied. The high frequency parameters are extracted with the help of simulated Zand Yparameters of two port equivalent circuits of the proposed SiGe HBT device and electrical parameters are calculated with the help of small-signal analysis of projected device. Later, the topics are also involved in instantaneous investigation of effect of Ge concentration on various electrical as well as HF parameters of this SiGe HBT. This method is validated by the examination of certain linear relations of device frequency behaviour as forecasted by the analogous theoretical analysis. Further, the precision of our method is validated by simulated S–parameter plots. The device characteristics of the proposed model are found much advanced to those of III-V semiconductor devices. These results have been also validated using a viable numerical device simulator ATLAS from Silvaco International. Keywords-Silicon; SiGe;HBT; Ge Concentration; Small-signal Analysis; Intrinsic Parameters
Comparative analysis of protein structure using multiscale additive functionals

This work reports a new methodology aimed at describing characteristics of protein structural shapes, and suggests a framework in which to resolve or classify automatically such structures into known families. This new approach to protein structure characterization is based on elements of integral geometry using biologically relevant measurements of shape and considering them on a multi-scale representation which align the proposed methodology to the recently reported "tube picture" of a protein structure as a minimal representation model. The method has been applied with good results to a subset of protein structures known to be especially challenging to revert into families, confirming the potential of the proposed method for accurate structure classification.
Coding for a radio transmission system with spectrum pooling and unequal resource sharing

We examine a radio transmission system based on spectrum pooling, whereby the spectrum is divided into subchannels, and some users are allowed privileged access to the most reliable unused subchannels. The performance of this system is evaluated by assuming that a powerful error-control code is used, and hence by computing the information outage probability. It is shown that choosing the best channel improves considerably the performance of the privileged users. In addition, the remaining (unprivileged) users are penalized only marginally.
Send Orders of Reprints at Reprints@benthamscience.net Revision in Cemented and Cementless Infected Hip Arthroplasty

Infection is a frequent cause of failure after joint replacement surgery. The infection rate after total hip arthroplasty (THA) has been reduced to 1-2% in the last years. However, it still represents a challenging problem for the orthopedic surgeon. Difficulty of therapeutic approach, and poor functional outcomes together with length of treatment and overall cost are the main burden of this issue. Even the diagnosis of an infected hip could be challenging although it is the first step of an accurate treatment. At the end, many cases require removing the implants. Afterwards, the treatment strategy varies according to authors with three different procedures: no re-implantation, immediate placement of new implants or a two-stage surgery re-implantation. Based on the most recently systematic review there is no suggestion that one-or two-stage revision methods have different re-infection outcomes. The two-stage implant-exchange protocol remains the gold standard. It is considered as the most efficacious clinical approach for the treatment of periprosthetic infection, especially in patients with sinus tracts, swelling, extended abscess formation in depth and infection of Methicillin Resistant Staphylococcus Aureus (MRSA), and other multidrug-resistant bacteria as reported in recent consensus documents.
Adaptive MIMO radar detection in non-Gaussian and heterogeneous clutter considering fluctuating targets

Previously, the Generalized Likelihood Ratio Test - Linear Quadratic (GLRT-LQ) has been extended to the Multiple-Input Multiple-Output (MIMO) case where all transmit-receive subarrays are considered jointly as a system such that only one detection threshold is used. The new MIMO detector is Constant False Alarm Rate (CFAR) with respect to the clutter power fluctuations. In this paper, the adaptive version of this detector is considered, as well as a fluctuating target model similar to that of the Swerling Target. The degradation of the detection performance due to the estimation of the covariance matrix and the fluctuation of the target is studied through simulations for both the well-known Optimum Gaussian Detector (OGD) and the new MIMO detector under Gaussian and non-Gaussian clutter.
Cluster-Based Sequence Analysis of Complex Manufacturing Process

Wafer fabrication in the semiconductor industry is probably one of the most complex manufacturing processes. Maintaining high yields through the statistical process control as a sole monitoring method for quality control is obviously inefficient in such highly complicated operations. We thus present in this paper a sequence analysis method, which is one of the advanced data mining techniques, to identify and extract unique patterns from manufacturing data that can reveal and differentiate low performance processes from the normal ones. We also provide the program coding, implemented with the R language, for easy experimental repetition.
Security Threats to Hadoop: Data Leakage Attacks and Investigation

As one of the most popular platforms for processing big data, Hadoop has low costs, convenience, and fast speed. However, it is also a significant target of data leakage attacks, as a growing number of businesses and individuals store and process their private data in it. How to investigate data leakage attacks in Hadoop is an important but long-neglected issue. This article first presents some possible data leakage attacks in Hadoop. Then an investigation framework is proposed and tested based on some simulated cases.
Power considerations in the design of the Alpha 21264 microprocessor

Power dissipation is rapidly becoming a limiting factor in high performance microprocessor design due to ever increasing device counts and clock rates. The 21264 is a third generation Alpha microprocessor implementation, containing 15.2 million transistors and operating at 600 MHz. This paper describes some of the techniques the Alpha design team utilized to help manage power dissipation. In addition, the electrical design of the power, ground, and clock networks is presented.
Differential Pressure Prediction in Air Leak Detection Using RBF Neural Network

The objective of this paper is to increase the accuracy of the air leak detection through predicting the differential pressure using radial basis function(RBF)neural network. Air leak detection plays an important role in ensuring excellent performance of products. If the detection accuracy is low, unqualified products may be judged as qualified or otherwise. So it is important to increase the detection accuracy which is influenced by temperature, test pressure, chamber volume, balance time and so on. It is not easy to compensate the detection error directly, for the movement status of the gas in the chamber being complicated. This paper applies radial basis function(RBF)neural network to establish the function relationship between the leakage and influence factors and predict the differential pressure value which is used to determine whether the products leak or not. Experiment results using test data obtained on the differential-pressure-based air leak detection platform show that detection using RBF neural network has a higher accuracy than the detection not using it and RBF neural network for accuracy increase in air leak detection is feasibility.
A Generalized Fact and Model of Long-Run Economic Growth: Kaldor Fact as a Special Case

This paper provides new evidence on the long-run relationship between economic growth and labor's share in national income, based on a comprehensive panel data set for 123 countries from 1950 to 2004. Xie's primary finding is that labor's share follows a cubic relationship with real GDP per capita over the long process of development. At the beginning of the modern economic growth process, the share of labor in national income first decreases until an initial threshold is reached. After that, labor's share keeps increasing until the country's GDP per capita reaches a second threshold before falling again. Xie argues that these dynamics apply not only to the less developed countries in the postwar years, but also to the advanced countries like the United States and the United Kingdom during their early economic take-offs, starting in the late 18th and 19th century, respectively. Finally, he proposes a two-sector constant elasticity of substitution (CES)-type growth model and simulate the model to replicate and explain the possible mechanism behind such a nonlinear pattern of movements in labor's share.
Implementing S-Expression Based Extended Languages in Lisp Tasuku Hiraishi

Many extended, C-like languages can be implemented by translating them into C. This paper proposes an extension scheme for SC languages (extended /plain C languages with an S-expression based syntax). The extensions are implemented by transformation rules over S-expressions, that is, Lisp functions with pattern-matching on S-expressions. Thus, many flexible extensions to C can be implemented at low cost because (1) of the ease with which new constructs can be added to an SC language, and (2) of the preexisting Common Lisp capabilities for reading /printing, analyzing, and transforming S-expressions themselves. We also present a practical example of just such an extended language.
Reversal of the interferon-sensitive phenotype of a vaccinia virus lacking E3L by expression of the reovirus S4 gene

The vaccinia virus (VV) E3L gene, which encodes a potent inhibitor of the interferon (IFN)-induced, double-stranded RNA (dsRNA)-dependent protein kinase, PKR, is thought to be involved in the IFN-resistant phenotype of VV. The E3L gene products, p25 and p20, act as inhibitors of PKR, presumably by binding and sequestering activator dsRNA from the kinase. In this study we demonstrate that VV with the E3L gene specifically deleted (vP1080) was sensitive to the antiviral effects of IFN and debilitated in its ability to rescue vesicular stomatitis virus from the antiviral effects of IFN. Infection of L929 cells with E3L-minus virus led to rRNA degradation typical of activation of the 2'-5'-oligoadenylate synthetase/RNase L system, and extracts of infected cells lacked the PKR-inhibitory activity characteristic of wild-type VV. The reovirus S4 gene, which encodes a dsRNA-binding protein (sigma 3) that can also inhibit PKR activation by binding and sequestering activator dsRNA, was inserted into vP1080. The resultant virus (vP1112) was partially resistant to the antiviral effects of IFN in comparison with vP1080. Further studies demonstrated that transient expression of the reovirus sigma 3 protein rescued E3L-minus VV replication in HeLa cells. In these studies, rescue by sigma 3 mutants correlated with their ability to bind dsRNA. Finally, vP112 was also able to rescue the replication of the IFN-sensitive virus vesicular stomatitis virus in a manner similar to that of wild-type VV. Together, these results suggest that the reovirus S4 gene can replace the VV E3L gene with respect to interference with the IFN-induced antiviral activity.
Stream on the Sky: Outsourcing Access Control Enforcement for Stream Data to the Cloud

There is an increasing trend for businesses to migrate their systems towards the cloud. Security concerns that arise when outsourcing data and computation to the cloud include data confidentiality and privacy. Given that a tremendous amount of data is being generated everyday from plethora of devices equipped with sensing capabilities, we focus on the problem of access controls over live streams of data based on triggers or sliding windows, which is a distinct and more challenging problem than access control over archival data. Specifically, we investigate secure mechanisms for outsourcing access control enforcement for stream data to the cloud. We devise a system that allows data owners to specify fine-grained policies associated with their data streams, then to encrypt the streams and relay them to the cloud for live processing and storage for future use. The access control policies are enforced by the cloud, without the latter learning about the data, while ensuring that unauthorized access is not feasible. To realize these ends, we employ a novel cryptographic primitive, namely proxy-based attribute-based encryption, which not only provides security but also allows the cloud to perform expensive computations on behalf of the users. Our approach is holistic, in that these controls are integrated with an XML based framework (XACML) for high-level management of policies. Experiments with our prototype demonstrate the feasibility of such mechanisms, and early evaluations suggest graceful scalability with increasing numbers of policies, data streams and users.
An Advanced Collusion Attack against User Friendship Privacy in OSNs

Online Social Networks (OSNs) are providing a variety of applications for human users to interact with families, friends and even strangers. One of such applications, friend search engine, which allows the general public to query individual users' friend list, is gaining popularity recently. However, without proper design, this application may disclose users' private relationship information. In this paper, we propose an advanced collusion attack, where a victim user's friendship privacy setting can be compromised through a carefully designed query sequence coordinately launched by multiple malicious requstors. The effect of the proposed collusion attack is validated through synthetic social network data sets. In addition, the analysis of such advanced collusion attacks will also benefit the future design of more robust privacy preserving friend search engine in OSNs.
SUB ADDITIVE MEASURES OF FUZZY INFORMATION

In the present communication, we review the existing measures of fuzzy information. We define and characterize two fuzzy information measures which are sub additive and different from known measures of fuzzy information. We also study monotonic behavior and particular cases of these fuzzy information measures. 2000 Mathematics Subject Classification: 94A17 and 94 D 05
Imaging Axonal Degeneration and Repair in Preclinical Animal Models of Multiple Sclerosis

Multiple sclerosis (MS) is a central nervous system (CNS) disease characterized by chronic neuroinflammation, demyelination, and axonal damage. Infiltration of activated lymphocytes and myeloid cells are thought to be primarily responsible for white matter damage and axonopathy. Over time, this neurologic damage manifests clinically as debilitating motor and cognitive symptoms. Existing MS therapies focus on symptom relief and delay of disease progression through reduction of neuroinflammation. However, long-term strategies to remyelinate, protect, or regenerate axons have remained elusive, posing a challenge to treating progressive forms of MS. Preclinical mouse models and techniques, such as immunohistochemistry, flow cytometry, and genomic and proteomic analysis have provided advances in our understanding of discrete time-points of pathology following disease induction. More recently, in vivo and in situ two-photon (2P) microscopy has made it possible to visualize continuous real-time cellular behavior and structural changes occurring within the CNS during neuropathology. Research utilizing 2P imaging to study axonopathy in neuroinflammatory demyelinating disease has focused on five areas: (1) axonal morphologic changes, (2) organelle transport and health, (3) relationship to inflammation, (4) neuronal excitotoxicity, and (5) regenerative therapies. 2P imaging may also be used to identify novel therapeutic targets via identification and clarification of dynamic cellular and molecular mechanisms of axonal regeneration and remyelination. Here, we review tools that have made 2P accessible for imaging neuropathologies and advances in our understanding of axonal degeneration and repair in preclinical models of demyelinating diseases.
A STATISTICS-BASED FRAMEWORK FOR AUTOMATED SOFTWARE TESTING

To achieve software quality, testing is an essential component in all software development. It involves the execution of a deterministic software system with test data and a comparison of the results with the expected output, which must satisfy users’ requirements. This accounts for over 25% of the cost of a software development. Consequently, automation has considerable potential. Quality programming introduced by Cho can automatically generate data for testing, based on a so–called ‘SIAD tree’ which is used to represent the hierarchical and network relation between input elements, and also incorporates rules into the tree for using the inputs. However, it lacks a very clear framework to show how to achieve automated testing. As an improvement, we present a statistics–based framework for automated software testing (SFAST), which is an extension of the testing concept in quality programming to achieve automated testing. In SFAST, we propose a SOAD tree which is similar to the structure of SIAD tree to describe the syntax structure of product unit and its defectiveness. Based on this tool, the inspection of test results can be automatically achieved by lexical and syntax analysis. An example for a grade report database system incorporating the framework is also illustrated.
Constraints on Layout in Multimodal Document Generation

A model of layout in illustrated documents must be informed by the rhetorical structure of the content. However, real-life production constraints often force an ‘imperfect’ realisation of the rhetorical structure on the page. Navigational elements must consequently be introduced into the layout to support the reading path. Layout structures, including the placement of the navigational elements, are then created based on the content segmentation and importance assignments suggested both by the rhetorical structure and by generic constraints for the document genre and production media.