Miracle-dz/UniFAR-FTUs huggingface dataset:
Compressed pattern matching for text and images

In this dissertation, we have studied compressed pattern matching problem for both text and images. We present a series of novel compressed pattern matching algorithms, which are divided into two major parts. The first major work is done for the popular LZW compression algorithm. The second major work is done for the current lossless image compression standard JPEG-LS. Specifically, our contributions from the first major work are: (1) We have developed an “almost-optimal” compressed pattern matching algorithm that reports all pattern occurrences. An earlier “almost-optimal” algorithm reported in the literature is only capable of detecting the first occurrence of the pattern and the practical performance of the algorithm is not clear. We have implemented our algorithm and provide extensive experimental results measuring the speed of our algorithm. We also developed a faster implementation for so-called “simple patterns”. The simple patterns are patterns that no unique symbol appears more than once. (2) We have developed a novel compressed pattern matching algorithm for multiple patterns using the Aho-Corasick algorithm. The algorithm takes O(mt + n + r) time with O(mt) extra space, where n is the size of the compressed file, m is the total size of all patterns, t is the size of the LZW trie and r is the number of occurrences of the patterns. All the above algorithms have been implemented and extensive experiments have been conducted to test the performance of our algorithms and to compare with the best existing algorithms. The experimental results show that our compressed pattern matching algorithm for multiple patterns is competitive among the best algorithms and is practically the fastest among all approaches when the number of patterns is not very large. Therefore, our algorithm is preferable for general string matching applications. LZW is one of the most efficient and popular compression algorithms used extensively and both of our algorithms require no modification on the compression algorithm. Our work, therefore, has great economical and market potential. Our contributions from the second major work are: (1) We have developed a new global context variation of the JPEG-LS compression algorithm and the corresponding compressed pattern matching algorithm. Comparing to the original JPEG-LS, the global context variation is search-aware and has faster encoding and decoding speeds. (2) We have developed a two-pass variation of the JPEG-LS algorithm and the corresponding compressed pattern matching algorithm. The two-pass variation achieves search-awareness through a common compression technique called semi static dictionary. (Abstract shortened by UMI.)
The gender wage gap in developing and transition countries

The aim of my dissertation is to study the gender wage gap with a specific focus on developing and transition countries. In the first chapter I present the main existing theories proposed to analyse the gender wage gap and I review the empirical literature on the gender wage gap in developing and transition countries and its main findings. Then, I discuss the overall empirical issues related to the estimation of the gender wage gap and the issues specific to developing and transition countries. The second chapter is an empirical analysis of the gender wage gap in a developing countries, the Union of Comoros, using data from the multidimensional household budget survey “Enquete integrale aupres des menages” (EIM) run in 2004. The interest of my work is to provide a benchmark analysis for further studies on the situation of women in the Comorian labour market and to contribute to the literature on gender wage gap in Africa by making available more information on the dynamics and mechanism of the gender wage gap, given the limited interest on the topic in this area of the world. The third chapter is an applied analysis of the gender wage gap in a transition country, Poland, using data from the Labour Force Survey (LSF) collected for the years 1994 and 2004. I provide a detailed examination of how gender earning differentials have changed over the period starting from 1994 to a more advanced transition phase in 2004, when market elements have become much more important in the functioning of the Polish economy than in the earlier phase. The main contribution of my dissertation is the application of the econometrical methodology that I describe in the beginning of the second chapter. First, I run a preliminary OLS and quantile regression analysis to estimate and describe the raw and conditional wage gaps along the distribution. Second, I estimate quantile regressions separately for males and females, in order to allow for different rewards to characteristics. Third, I proceed to decompose the raw wage gap estimated at the mean through the Oaxaca-Blinder (1973) procedure. In the second chapter I run a two-steps Heckman procedure by estimating a model of participation in the labour market which shows a significant selection bias for females. Forth, I apply the Machado-Mata (2005) techniques to extend the decomposition analysis at all points of the distribution. In Poland I can also implement the Juhn, Murphy and Pierce (1991) decomposition over the period 1994-2004, to account for effects to the pay gap due to changes in overall wage dispersion beyond Oaxaca’s standard decomposition.
TISSUE-SPECIFIC FUNCTIONAL EFFECT PREDICTION OF GENETIC VARIATION AND APPLICATIONS TO COMPLEX TRAIT GENETICS

Over the past few years, large scale genomics projects such as the ENCODE and Roadmap Epigenomics have produced genome-wide data on a large number of biochemical assays for a diverse set of human cell types and tissues. Such data play an important role in predicting the functional effects of noncoding genetic variation. We discuss here unsupervised approaches to integrate these diverse annotations for specific tissues and cell types into a single predictor of tissue-specific functional importance. We provide a global view of the sharing of functional variants across large number of tissues and cell types, and demonstrate that functional variants in promoters are more likely to be shared across many tissues compared with enhancers. A multidimensional scaling analysis based on functional scores in multiple tissues reveals clear patterns of similarity between certain tissue types, including similarity between primary tissues derived from the same embryonic tissue of origin. Using eQTL data from the Genotype-Tissue Expression (GTEx) project we show that eQTLs in specific GTEx tissues tend to be most enriched among the functional variants in relevant tissues in Roadmap. Furthermore, we show how these integrated functional scores can be used to derive the most likely tissue-/cell-type for a complex trait using summary statistics from genome-wide association studies (GWAS), and derive a tissue-based correlation map of various complex traits. Finally, we show how the tissue-specific functional scores in conjunction with GWAS summary statistics can shed light on genes and biological processes implicated in a complex trait. Functional scores are available for every possible position in the hg19 human reference genome for 127 tissues and cell types assayed in Roadmap Epigenomics.
Throughput-Optimal Scheduling for Downlink Zero-Forcing SDMA Systems

The downlink zero-forcing beamforming strategy in the case of random packet arrivals is investigated. Under this setting, the relevant fairness criterion is the stabilization of all buffer queues which guarantees a bounded average delay for all users. It has been shown that maximizing a queue-length-weighted sum of the rates is an optimal in the sense that it can guarantee stability of the system. A good cross layer scheduling scheme should jointly consider the queue length and the channel variation of the channel from the physical layer. The average delay, average throughput, and average user queue length of the channel-aware-only scheduling, queue-aware-only scheduling and joint channel-aware and queue-aware scheduling are evaluated. Simulation results show that the joint channel-aware and queue-aware scheduling algorithm can take full advantage of the multiuser diversity gain and provide average delay (or throughput) and fairness improvement compared with channel-aware-only schemes and queue-aware-only schemes.
Programming the Adapteva Epiphany 64-core network-on-chip coprocessor

Energy efficiency is the primary impediment in the path to exascale computing. Consequently, the high-performance computing community is increasingly interested in low-power high-performance embedded systems as building blocks for large-scale high-performance systems. The Adapteva Epiphany architecture integrates low-power RISC cores on a 2D mesh network and promises up to 70 GFLOPS/Watt of theoretical performance. However, with just 32 KB of memory per eCore for storing both data and code, programming the Epiphany system presents significant challenges. In this paper we evaluate the performance of a 64-core Epiphany system with a variety of basic compute and communication micro-benchmarks. Further, we implemented two well known application kernels, 5-point star-shaped heat stencil with a peak performance of 65.2 GFLOPS and matrix multiplication with 65.3 GFLOPS in single precision across 64 Epiphany cores. We discuss strategies for implementing high-performance computing application kernels on such memory constrained low-power devices and compare the Epiphany with competing low-power systems. With future Epiphany revisions expected to house thousands of cores on a single chip, understanding the merits of such an architecture is of prime importance to the exascale initiative.
Towards a new tuberculosis drug: pyridomycin – nature's isoniazid

Tuberculosis, a global threat to public health, is becoming untreatable due to widespread drug resistance to frontline drugs such as the InhA‐inhibitor isoniazid. Historically, by inhibiting highly vulnerable targets, natural products have been an important source of antibiotics including potent anti‐tuberculosis agents. Here, we describe pyridomycin, a compound produced by Dactylosporangium fulvum with specific cidal activity against mycobacteria. By selecting pyridomycin‐resistant mutants of Mycobacterium tuberculosis, whole‐genome sequencing and genetic validation, we identified the NADH‐dependent enoyl‐ (Acyl‐Carrier‐Protein) reductase InhA as the principal target and demonstrate that pyridomycin inhibits mycolic acid synthesis in M. tuberculosis. Furthermore, biochemical and structural studies show that pyridomycin inhibits InhA directly as a competitive inhibitor of the NADH‐binding site, thereby identifying a new, druggable pocket in InhA. Importantly, the most frequently encountered isoniazid‐resistant clinical isolates remain fully susceptible to pyridomycin, thus opening new avenues for drug development.
The Determinants of the CEO Successor Choice in Family Firms

This paper studies the factors that influence the CEO succession decision in family firms whose incumbent CEO is a member of the controlling family. The sample includes all such firms from France, Germany and the UK. We propose a new measure of directors' independence, which adjusts for various links with the controlling family. While we find that conventionally defined directors' independence has no impact on the CEO succession decision, our corrected measure reduces the likelihood of the successor being another family member. There is also evidence that firms from France that are cross-listed in the UK or USA are less likely to appoint another family CEO.
Essays on Female Education, Fertility, and Health: Evidence From Turkey and the US

Title of Document: ESSAYS ON FEMALE EDUCATION, FERTILITY, AND HEALTH: EVIDENCE FROM TURKEY AND THE US Pinar Mine Gunes, PhD, 2014 Directed By: Kenneth Leonard, Professor Agricultural and Resource Economics Education is an important factor in reducing poverty, improving child health, and empowering women, which are key indicators of economic development and are supported by the United Nations Millennium Development Goals. While education is positively associated with these development indicators, identifying the extent that education has a causal impact in developing countries requires exogenous variation in education. Two dissertation chapters rely on a change in compulsory schooling law (CSL) in Turkey as a natural experiment to identify the causal impact of education. In 1997, the Turkish government extended compulsory schooling from five to eight years, and in addition created new schools and classrooms, hired additional teachers, and provided transportation to rural areas. As a result, enrollment rates and education attainment significantly increased, especially for females. I use the change in the CSL as a natural experiment, using variation in the exposure to the CSL across cohorts as instruments to education. In the second chapter, I find that mother’s primary school completion improves infant health, as measured by very low birth weight, and child health, as measured by height-for-age and weight-for-age z-scores, even after controlling for many potential confounding factors. Exploring heterogeneous effects indicates that maternal education improves child health more in provinces with lower income and urbanization rates. I also demonstrate that primary school completion leads to earlier preventive care initiation and reduces smoking. Using parameters from various studies, I find that the benefits outweigh the cost of the CSL. The third chapter demonstrates that an extra year of female schooling reduces teenage fertility by 0.03 births, which is a reduction of 33%. Exploring heterogeneous effects indicates that female education reduces teenage fertility more in provinces with higher initial fertility and lower population density. Finally, the CSL postpones childbearing by delaying marriage, thereby reducing fertility. The fourth chapter explores the effect of teenage childbearing on health outcomes and behaviors of mothers using a nationally representative sample of twins from the Midlife Development in the US dataset. I employ within-family estimations using samples of siblings, twin pairs, and identical twin pairs, to overcome the bias generated by unobserved family background and genetic traits. The results suggest that teenage childbearing does not affect long-term health; however, it adversely affects exercise and preventive care behaviors. Further, I find that the effects of teenage childbearing may operate through education and the quality of the spouse. ESSAYS ON FEMALE EDUCATION, FERTILITY, AND HEALTH: EVIDENCE FROM TURKEY AND THE US
Parallel Complexity for Matroid Intersection and Matroid Parity Problems

Let two linear matroids have the same rank in matroid intersection. A maximum linear matroid intersection (maximum linear matroid parity set) is called a basic matroid intersection (basic matroid parity set), if its size is the rank of the matroid. We present that enumerating all basic matroid intersections (basic matroid parity sets) is in NC, provided that there are polynomial bounded basic matroid intersections (basic matroid parity sets). For the graphic matroids, We show that constructing all basic matroid intersections is in NC if the number of basic graphic matroid intersections is polynomial bounded. To our knowledge, these algorithms are the first deterministic NC-algorithms for matroid intersection and matroid parity. Our result also answers a question of Harvey [8].
Telomere dysfunction suppresses multiple endocrine neoplasia in mice

Multiple endocrine neoplasia (MEN) syndrome is typified by the occurrence of tumors in two or more hormonal tissues. Whereas the genetics of MEN syndrome is relatively well understood, the tumorigenic mechanisms for these cancers remain relatively obscure. The Cdk4R24C mouse model develops highly penetrant pituitary tumors and endocrine pancreas adenomas, and, as such, this model is appropriate to gain insight into mechanisms underlying MEN. Using this model, here we provide evidence supporting an important role for telomerase in the pathogenesis of MEN. We observed increased aneuploidy in Cdk4R/R fibroblasts along with significantly elevated telomerase activity and telomere length in Cdk4R/R islets and embryonic fibroblasts. To better understand the role of telomerase, we generated Cdk4R24C mice with inactivation of the mTERC locus, which codes for the essential RNA component of the enzyme telomerase (mTERC−/− Cdk4R/R mice). Embryonic fibroblasts and islets derived from mTERC−/− Cdk4R/R mice exhibit reduced telomere length and proliferative capacity. Further, mTERC−/− Cdk4R/R fibroblasts display reduced transformation potential. Importantly, mTERC−/− Cdk4R/R mice display significantly reduced spontaneous tumorigenesis. Strikingly, we observed dramatic suppression of pituitary tumors and endocrine pancreas adenomas in mTERC−/− Cdk4R/R mice. Telomere dysfunction suppressed tumor initiation and increased latency of tumor development while not affecting the progression of established tumors. In summary, these results are suggestive of an important role for telomerase in tumor development in the Cdk4R24C mouse model, specifically in the genesis of tumors in the pituitary and the endocrine pancreas.
Geospatial Structure of a Planetary-Scale Social Network

Little is known about geographic properties of large-scale social networks. In this paper, we examine the geospatial attributes of a planetary-scale social network of 240 million people and 1.3 billion edges. We study the interplay among topological, geographical, and algorithmically generated paths connecting pairs of nodes in a social network. Starting in the realm of cyberspace, we find that topologically shortest paths of average length of 6.6 exist between pairs of nodes in the network and that the average degree of separation among nodes is robust to removal of hub nodes. Moving to the realm of locations and distances in geographic space, we find that topologically shortest paths in the social graph grow with increasing geographic distance between path's endpoint nodes. We discover that shortest topological paths are geographically inefficient, but that geography provides an important cue for local algorithmic policies for navigating between source and target nodes. Local algorithmic strategies for navigating the larger network structure in the absence of global navigation procedures have varying success. At the early stages of the navigation, navigating to a hub node helps, while in the middle stage, geography provides the most important clue. While local algorithms for navigating have trouble reaching the target node, they are successful in reaching nodes that are geographically close to the target. Taken together, our results demonstrate a complex interplay between topological and geographical properties of social networks and explain the success of local strategies for navigating such networks.
Streets of the ‘spice zombies’: Dependence and poverty stigma in times of austerity

Following the 2016 general ban on new psychoactive substances, synthetic cannabinoids (‘spice’-type drugs) have moved into unregulated street markets and have become popular among homeless populations in the United Kingdom. Images of so-called ‘spice zombies’, rough sleepers in public spaces experiencing severe substance-induced fits, have been used by local and national media to suggest the growing scale of the problem. This article proposes that such depictions should be read through a cultural analysis rooted in the political economy of austerity policies, where the twofold stigma of substance and welfare dependencies directs guilt at the poor, concealing the systemic cruelty of benefits reforms. Through the circulation of such tropes and the ridiculing of a superfluous abject underclass that embodies them, media and political discourses of the ‘broken society’ highlight an evident need for welfare reduction and more generally for the austerity project.
Sharing a Polluted River

A river carries pollutants to people living along it if it is polluted. To make the water in the river clean, some costs are incurred. This poses a question of how to split the costs of cleaning the whole river among the agents located along it. To answer this question, we resort to the two main advocated doctrines in international disputes: the theory of Absolute Territorial Sovereignty (ATS) and the theory of Unlimited Territorial Integrity (UTI). Applying these two doctrines, we accordingly propose two methods: the Local Responsibility Sharing (LRS) method and the Upstream Equal Sharing (UES) method. For each method, we provide an axiomatic characterization. Interestingly, both the LRS method and the UES method coincide with the Shapley value solutions to the corresponding (cost) games that are naturally induced according to the ATS and the UTI doctrines respectively. Moreover, both the LRS solution and the UES solution are the core allocations of the corresponding games. Thus, both the LRS method and the UES method can be considered as fair or reasonable solutions to the pollution cost allocation problem.
[OII] λ 3727 Emission from the Companion to the Quasar BR 1202–0725 at z = 4.7

Results of a narrow-band imaging for the redshifted [Oil] A3727 emission around a quasar at z = 4.7 obtained with the Subaru telescope and CISCO (a Cassegrain near infrared camera) are presented. A significant emission line is detected in the narrow-band H2 [v = 1-0 S(l)] filter at a location ~ 2. " 4 northwest from the quasar, where the presence of a companion has been reported in Lyman a emission and the rest-frame UV continuum. We identify this line as [Oil] A3727 emission and confirm that the source really is a companion at z = 4.7. The [Oil] A3727 flux from the companion is estimated to be 2.5 x 10 -17 erg s _1 cm -2 . If the companion is a star-forming object, the inferred star-formation rate is as high as 45-230 M® yr_1, even without assuming an extinction correction. This value is higher than those derived from the Lyman a emission or from the UV continuum. Thus, provided that the difference is caused by dust extinction, the extinction-corrected star-formation rate is calculated to be 45 to 2300 M® yr -1 , depending on the assumed extinction curves.
Chronic Neuroinflammation in Alzheimer's Disease: New Perspectives on Animal Models and Promising Candidate Drugs

Chronic neuroinflammation is now considered one of the major factors in the pathogenesis of Alzheimer's disease (AD). However, the most widely used transgenic AD models (overexpressing mutated forms of amyloid precursor protein, presenilin, and/or tau) do not demonstrate the degree of inflammation, neurodegeneration (particularly of the cholinergic system), and cognitive decline that is comparable with the human disease. Hence a more suitable animal model is needed to more closely mimic the resulting cognitive decline and memory loss in humans in order to investigate the effects of neuroinflammation on neurodegeneration. One of these models is the glial fibrillary acidic protein-interleukin 6 (GFAP-IL6) mouse, in which chronic neuroinflammation triggered constitutive expression of the cytokine interleukin-6 (IL-6) in astrocytes. These transgenic mice show substantial and progressive neurodegeneration as well as a decline in motor skills and cognitive function, starting from 6 months of age. This animal model could serve as an excellent tool for drug discovery and validation in vivo. In this review, we have also selected three potential anti-inflammatory drugs, curcumin, apigenin, and tenilsetam, as candidate drugs, which could be tested in this model.