Miracle-dz/UniFAR-FTUs huggingface dataset:
On Selective Indirect Tax Reform in Developing Countries

The current consensus on indirect tax reform in developing countries favors a reduction in trade taxes with an increase in VAT to raise revenue. The theoretical results on selective reform that underlie this consensus are, however, derived from partial models that ignore the existence of an informal economy. Once the incomplete coverage of VAT due to an informal economy is acknowledged, we show that, contrary to the current consensus, the standard revenue-neutral selective reform of trade taxes and VAT reduces welfare under plausible conditions. Moreover, a VAT base broadening with a revenue-neutral reduction in trade taxes may also reduce welfare. The results raise serious doubts about the wisdom of the indirect tax reform policies pursued by a large number of developing countries.
Distributed construction of random expander graphs

We present a novel distributed algorithm for constructing random regular graphs that are composed of d independent Hamilton cycles. The protocol is completely decentralized as no globally-known server is required. The constructed topologies are expanders with O(logd n) diameter with high probability. Our construction is highly scalable because both the processing and the space requirements at each node grow logarithmically with the network size. A new node can join the topology at any existing node in O(logd n) time with O(d logd n) messages. A node can leave in O(1) time with O(d) messages. In addition, the protocol allows an adversarial sequence of join and leave operations. We also discuss a layered construction of random regular graphs, which has applications in peer-to-peer networking.
A Flexible Approach to Finding Representative Pattern Sets

Frequent pattern mining often produces an enormous number of frequent patterns, which imposes a great challenge on visualizing, understanding and further analysis of the generated patterns. This calls for finding a small number of representative patterns to best approximate all other patterns. In this paper, we develop an algorithm called MinRPset to find a minimum representative pattern set with error guarantee. MinRPset produces the smallest solution that we can possibly have in practice under the given problem setting, and it takes a reasonable amount of time to finish when the number of frequent closed patterns is below one million. MinRPset is very space-consuming and time-consuming on some dense datasets when the number of frequent closed patterns is large. To solve this problem, we propose another algorithm called FlexRPset, which provides one extra parameter K to allow users to make a trade-off between result size and efficiency. We adopt an incremental approach to let the users make the trade-off conveniently. Our experiment results show that MinRPset and FlexRPset produce fewer representative patterns than RPlocal-an efficient algorithm that is developed for solving the same problem.
A COMPARISON OF SOFTWARE REUSE SUPPORT IN OBJECT-ORIENTED METHODOLOGIES

Software reusability has been regarded as one of the most important areas for improving software development productivity and quality in the 1990's. The object-oriented approach to information systems development has promised to achieve large-scale software reuse. Objectoriented analysis and design methodologies have aimed at the realization of the promised benefits; however, the degree to which the methodologies support reuse and deliver on this promise is an interesting, open question. This paper investigates how object-oriented analysis and design methodologies support software reusability. It provides an objective comparison of seven object-oriented analysis and design methodologies with respect to the support of software reuse. Several important observations are made based on the comparison. This study provides valuable information to researchers, practitioners and organizations for studying, selection and adoption of object-oriented analysis and design methodologies.
Automated Web Patrol with Strider HoneyMonkeys: Finding Web Sites That Exploit Browser Vulnerabilities

Internet attacks that use malicious web sites to install malware programs by exploiting browser vulnerabilities are a serious emerging threat. In response, we have developed an automated web patrol system to automatically identify and monitor these malicious sites. We describe the design and implementation of the Strider HoneyMonkey Exploit Detection System, which consists of a pipeline of “monkey programs” running possibly vulnerable browsers on virtual machines with different patch levels and patrolling the Web to seek out and classify web sites that exploit browser vulnerabilities. Within the first month of utilizing this system, we identified 752 unique URLs hosted on 288 web sites that could successfully exploit unpatched Windows XP machines. The system automatically constructed topology graphs based on traffic redirection to capture the relationship between the exploit sites. This allowed us to identify several major players who are responsible for a large number of exploit pages. By monitoring these 752 exploit-URLs on a daily basis, we discovered a malicious web site that was performing zero-day exploits of the unpatched javaprxy.dll vulnerability and was operating behind 25 exploit-URLs. It was confirmed as the first “inthe-wild”, zero-day exploit of this vulnerability that was reported to the Microsoft Security Response Center. Additionally, by scanning the most popular one million URLs as classified by a search engine, we found over seven hundred exploit-URLs, many of which serve popular content related to celebrities, song lyrics, wallpapers, video game cheats, and wrestling.
Multi-path PALSAR interferometric observations of the 2008 magnitude 8.0 Wenchuan Earthquake

The Satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) has already demonstrated its potential to map co-, post- and inter-seismic deformation. This paper presents an.alysis of the surface-displacement field of the 12 May 2008 magnitude 8.0 Wenchuan Earthquake using the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) DInSAR. Six PALSAR interferograms of paths 471 to 476 are generated. A new approach, which uses the information of overlapping interferograms, has been developed to compensate for orbit error. The main advantage of this approach is that the calculation is performed without the need for phase unwrapping. Once the orbit error has been compensated for, the interferograms are then merged to form a single interferogram. The final mosaic of interferograms demonstrates a much more consistent co-seismic surface-displacement field than the original interferograms.
Mining User Queries with Markov Chains: Application to Online Image Retrieval

We propose a novel method for automatic annotation, indexing and annotation-based retrieval of images. The new method, that we call Markovian Semantic Indexing (MSI), is presented in the context of an online image retrieval system. Assuming such a system, the users' queries are used to construct an Aggregate Markov Chain (AMC) through which the relevance between the keywords seen by the system is defined. The users' queries are also used to automatically annotate the images. A stochastic distance between images, based on their annotation and the keyword relevance captured in the AMC, is then introduced. Geometric interpretations of the proposed distance are provided and its relation to a clustering in the keyword space is investigated. By means of a new measure of Markovian state similarity, the mean first cross passage time (CPT), optimality properties of the proposed distance are proved. Images are modeled as points in a vector space and their similarity is measured with MSI. The new method is shown to possess certain theoretical advantages and also to achieve better Precision versus Recall results when compared to Latent Semantic Indexing (LSI) and probabilistic Latent Semantic Indexing (pLSI) methods in Annotation-Based Image Retrieval (ABIR) tasks.
Culture and International Business Organizational Culture and Identity Strategies in International Management : an interdisciplinary review

The notion of organizational culture has raised a considerable interest during the past two decades in the field of International Management for being a factor playing an important role in the various organizational processes leading ultimately to performance. However organizational culture is generally presented as a set of values and ideas that would be homogeneously shared by the entire organization, a monolithic vision generally rejected by most social scientists and psychologists. This paper examines how different disciplines have conceptualized organizational culture and identity, progressively revealing its complex and multidimensional nature. We argue that there is a considerable discrepancy between the claimed organizational culture expressed and promoted by the top management as an indirect control mechanism and the sub-cultures and identities coexisting in a firm. Using the example of research on identity and culture in Mergers and Acquisitions, we show that the shift from the traditional “monolithic culture” analysis to the more complex “multiple culture” perspective requires major change in the approach of human interaction in International Business and Management.
CD44 Upregulation in E-Cadherin-Negative Esophageal Cancers Results in Cell Invasion

E-cadherin is frequently lost during epithelial-mesenchymal transition and the progression of epithelial tumorigenesis. We found a marker of epithelial-mesenchymal transition, CD44, upregulated in response to functional loss of E-cadherin in esophageal cell lines and cancer. Loss of E-cadherin expression correlates with increased expression of CD44 standard isoform. Using an organotypic reconstruct model, we show increased CD44 expression in areas of cell invasion is associated with MMP-9 at the leading edge. Moreover, Activin A increases cell invasion through CD44 upregulation after E-cadherin loss. Taken together, our results provide functional evidence of CD44 upregulation in esophageal cancer invasion.
SCN10A/Nav1.8 modulation of peak and late sodium currents in patients with early onset atrial fibrillation.

AIMS To test the hypothesis that vulnerability to atrial fibrillation (AF) is associated with rare coding sequence variation in the SCN10A gene, which encodes the voltage-gated sodium channel isoform NaV1.8 found primarily in peripheral nerves and to identify potentially disease-related mechanisms in high-priority rare variants using in-vitro electrophysiology. METHODS AND RESULTS We re-sequenced SCN10A in 274 patients with early onset AF from the Vanderbilt AF Registry to identify rare coding variants. Engineered variants were transiently expressed in ND7/23 cells and whole-cell voltage clamp experiments were conducted to elucidate their functional properties. Resequencing SCN10A identified 18 heterozygous rare coding variants (minor allele frequency ≤1%) in 18 (6.6%) AF probands. Four probands were carriers of two rare variants each and 14 were carriers of one coding variant. Based on evidence of co-segregation, initial assessment of functional importance, and presence in ≥1 AF proband, three variants (417delK, A1886V, and the compound variant Y158D-R814H) were selected for functional studies. The 417delK variant displayed near absent current while A1886V and Y158D-R814H exhibited enhanced peak and late (INa-L) sodium currents; both Y158D and R818H individually contributed to this phenotype. CONCLUSION Rare SCN10A variants encoding Nav1.8 were identified in 6.6% of patients with early onset AF. In-vitro electrophysiological studies demonstrated profoundly altered function in 3/3 high-priority variants. Collectively, these data strongly support the hypothesis that rare SCN10A variants may contribute to AF susceptibility.
Poly-Lactide/Exfoliated C30B Interactions and Influence on Thermo-Mechanical Properties Due to Artificial Weathering

Thermal stability as well as enhanced mechanical properties of poly-lactide (PLA) can increase PLA applications for short-use products. The conjunction of adequate molecular weight (MW) as well as satisfactory thermo-mechanical properties, together, can lead to the achievement of suitable properties. However, PLA is susceptible to thermal degradation and thus an undesired decay of MW and a decrease of its mechanical properties during processing. To avoid this PLA degradation, nanofiller is incorporated as reinforcement to increase its thermo-mechanical properties. There are many papers focusing on filler effects on the thermal stability and mechanical properties of PLA/nanocomposites; however, these investigations lack an explanation of polymer/filler interactions. We propose interactions between PLA and Cloisite30B (C30B) as nanofiller. We also study the effects on the thermal and mechanical properties due to molecular weight decay after exposure to artificial weathering. PLA blank and nanocomposites were subjected to three time treatments (0, 176, and 360 h) of exposure to artificial weathering in order to achieve comparable materials with different MW. MW was acquired by means of Gel Permeation Chromatography (GPC). Thermo-mechanical properties were investigated through Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), X-ray Diffraction (XRD), Dynamic Mechanical Thermal Analysis (DMTA) and Fourier Transform Infrared Spectroscopy (FTIR).
Real-Time Speaker Adaptation for Speech Recognition on Mobile Devices

This paper introduce a real-time speaker adaptation method for speech recognition on mobile devices. In order to adapt speech recognition system to any speakers, we employ vocal tract length normalization (VTLN). In conventional VTLN, warping factors are computed by maximum likelihood estimation. After all possible warping factors are applied to speech recognition, the best warping factor is selected corresponding to speaker or speech. Therefore it is not efficient for mobile devices because of expensive computation although its performance is good. To reduce computational effort, we employ pitch-based VTLN and simplify pitch estimation. The proposed method gives the relative word error rate reduction by 21.5% in Korean while the speed is slower by 10.5% as compared to the baseline.
Nonlinear System Identification Provides Insight Into Protein Folding

Much like the shape of a tool suggests its intended purpose, knowledge of a protein's structure can provide substantial insight into its function. Therefore, computational prediction of protein structure based solely on protein sequence data is a challenge of fundamental importance to biomedical research. An effective solution promises significant advances in computational drug discovery and an increased understanding of complex disease processes such as cancer. We have recently developed a novel approach to determining the secondary structure of proteins from protein sequence data which makes use of parallel cascade identification (PCI), a powerful method of nonlinear system identification. PCI is used to create two layers of dynamic nonlinear systems that map divergent evolutionary profile input data into secondary structure assignment output data. PCI prediction accuracy compares well with eleven top contemporary methods over a dataset of new protein structures. Furthermore, PCI is a highly effective means to combine multiple experts achieving the highest observed accuracy over two test datasets and also the lowest rate of occurrence of a particularly detrimental class of errors. One limitation of the PCI classifiers is that approximately 13% of all amino acids cannot readily be assigned predictions due to settling times introduced by the dynamic linear component in each cascade model. In this paper we describe a number of methods designed to overcome this limitation. While zero-padding of the input sequence data proved to be the most effective solution in terms of prediction accuracy, an analysis of causal, anti-causal, and mixed cascades provides interesting insights into the biological mechanism of protein folding
ERP for SMEs - is proprietary software an alternative?

Purpose – To show that developing proprietary software is the best alternative for many small and medium‐sized enterprises (SMEs). Full control of the software makes it possible to remain flexible and dynamic, and to conform to the need of the customer at any time.Design/methodology/approach – The approach is case based.Findings – Modern development tools make in‐house development feasible. Costs are often comparable to that of using standard ERP systems. In‐house development does not need to encompass all functions, as it is easy to integrate off‐the‐shelf systems with proprietary development. Being in control of core software is important for the day‐to‐day activities of a company, and also for gaining a strategic advantage.Practical implications – In‐house development will be most useful for niche companies. Further, SMEs will have an advantage as they more easily can integrate standard systems with proprietary software.Originality/value – Many managers have excluded the possibility of developing their.
Research on Multi-Fractal Wavelet Model Based on Different Distributed Multipliers

In order to synthesize and analyze network traffic, many specialists have been applying the beta Multi-fractal Wavelet Model (beta MWM) to do researches. In this paper, we adopted other two kinds of MWM, point-mass MWM and hybrid MWM, to compare with the beta MWM by synthesizing network traffic. Having done lots of experiments, analyzing and comparing real traffic with synthesized one, we found that the choice of beta-distribution wavelet multipliers Aj,k is not essential. According to the different properties of network traffic, we can use distributions with more parameters in the MWM. Meanwhile the traffic synthesized which is the most similar to the real one could be obtained by adjusting the scales. This is the foundation for the forecasting, controlling and optimal designing of the network traffic, and of simulating and managing of network, etc.
A Mumford-Shah level-set approach for the inversion andsegmentation of SPECT/CT data

This paper presents a level-set based approach for the simultaneous reconstruction and segmentation of the activity as well as the density distribution from tomography data gathered by an integrated SPECT/CT scanner. Activity and density distributions are modeled as piecewise constant functions. The segmenting contours and the corresponding function values of both the activity and the density distribution are found as minimizers of a Mumford-Shah like functional over the set of admissible contours and -- for fixed contours -- over the spaces of piecewise constant density and activity distributions which may be discontinuous across their corresponding contours. For the latter step a Newton method is used to solve the nonlinear optimality system. Shape sensitivity calculus is used to find a descent direction for the cost functional with respect to the geometrical variables which leads to an update formula for the contours in the level-set framework. A heuristic approach for the insertion of new components for the activity as well as the density function is used. The method is tested for synthetic data with different noise levels.
A DOE Approach to Product Qualification For Linear Handset Power Amplifiers

Variation in starting wafer material impacts yield and performance of linear power amplifiers for handset applications. This work presents a design of experiment approach for evaluating circuit sensitivities based on epi material variations that can be used for product qualification. This approach provides a systematic understanding of how the epi material influences the final product performance and allows expected parametric spread to be predicted accurately with a minimal number of wafers. As a result, product performance distributions can be quickly and accurately determined in the development phase of a product.
Fast Independent Component Analysis Algorithm for Quaternion Valued Signals

An extension of the fast independent component analysis algorithm is proposed for the blind separation of both \BBQ-proper and \BBQ-improper quaternion-valued signals. This is achieved by maximizing a negentropy-based cost function, and is derived rigorously using the recently developed \mbi\BBH\BBR calculus in order to implement Newton optimization in the augmented quaternion statistics framework. It is shown that the use of augmented statistics and the associated widely linear modeling provides theoretical and practical advantages when dealing with general quaternion signals with noncircular (rotation-dependent) distributions. Simulations using both benchmark and real-world quaternion-valued signals support the approach.
Part-of-speech tagging of Modern Hebrew text

Abstract Words in Semitic texts often consist of a concatenation of word segments, each corresponding to a part-of-speech (POS) category. Semitic words may be ambiguous with regard to their segmentation as well as to the POS tags assigned to each segment. When designing POS taggers for Semitic languages, a major architectural decision concerns the choice of the atomic input tokens (terminal symbols). If the tokenization is at the word level, the output tags must be complex, and represent both the segmentation of the word and the POS tag assigned to each word segment. If the tokenization is at the segment level, the input itself must encode the different alternative segmentations of the words, while the output consists of standard POS tags. Comparing these two alternatives is not trivial, as the choice between them may have global effects on the grammatical model. Moreover, intermediate levels of tokenization between these two extremes are conceivable, and, as we aim to show, beneficial. To the best of our knowledge, the problem of tokenization for POS tagging of Semitic languages has not been addressed before in full generality. In this paper, we study this problem for the purpose of POS tagging of Modern Hebrew texts. After extensive error analysis of the two simple tokenization models, we propose a novel, linguistically motivated, intermediate tokenization model that gives better performance for Hebrew over the two initial architectures. Our study is based on the well-known hidden Markov models (HMMs). We start out from a manually devised morphological analyzer and a very small annotated corpus, and describe how to adapt an HMM-based POS tagger for both tokenization architectures. We present an effective technique for smoothing the lexical probabilities using an untagged corpus, and a novel transformation for casting the segment-level tagger in terms of a standard, word-level HMM implementation. The results obtained using our model are on par with the best published results on Modern Standard Arabic, despite the much smaller annotated corpus available for Modern Hebrew.