Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Web through its Language

A tight integration between ontological and linguistic knowledge is critical within the information processes of the Semantic Web. In Information Extraction, ontologies should include knowledge components neglected in domain conceptualizations generally used for other tasks. In this paper, we analyze such critical information in the light of existing applications. Accordingly, a methodology for semi-automatic development of an IE ontology integrating pre-existing domain and lexical knowledge is presented. The proposed ontological framework supports the discovery of new relations among known concepts by means of text processing, but also induction of new conceptual information.
Multi-Document Discourse Parsing Using Traditional and Hierarchical Machine Learning

Multi-document handling is essential today, when many documents on the same topic are produced, especially considering the Web. Both readers and computer applications can benefit from a discourse analysis of this multi- document content, since it demonstrates clearly the relations among portions of these documents. This work aims to identify such relations automatically using machine learning techniques. Particularly, this work focuses on the identification of relations predicted by the Cross-document Structure Theory (CST). The obtained results improve the state of the art.
EFFECT OF ETHANOLIC EXTRACT OF LEAVES OF MORINGA OLIFERA LAM. ON ACETIC ACID INDUCED COLITIS IN ALBINO RATS.

To evaluate the effect of ethanolic extract of leaves of Moringa olifera Lam. on acetic acid induced colitis in albino rats ethanolic extract of Moringa olifera was prepared by percolation method. Acute toxicity test was done by using OECD guidelines. Albino rats were divided into four groups (n=5). Group A and B received 3% gum acacia. Group C and D received ethanolic extract of Moringa olifera (EEMO) 500 mg/kg BW and 5-aminosalisylic acid (5-ASA) 100 mg /kg BW respectively. Colitis was induced by transrectal administration of 4% acetic acid on 5th day. All animals were sacrificed after 48 hour of colitis induction and distal 10 cm of the colon was dissected. Colon was weighed for disease activity index (DAI) and scored macroscopically and microscopically. Biochemical assessment of tissue myeloperoxidase (MPO), catalase (CAT) and superoxide dismutase (SOD) was done in colonic tissue homogenate and malondialdehyde (MDA) was estimated in serum. Moringa olifera showed significant (p<0.05) reduction in DAI, macroscopic and microscopic lesion score as well as significant (p<0.05) improvement in MPO, MDA, CAT, and SOD level as compared to Group B. The ethanolic extract of leaves of Moringa olifera showed significant amelioration of experimentally induced colitis, which may be attributed to its anti-inflammatory and antioxidant property.
The numinosity of soul: Andre Delbecq’s legacy for MSR

ABSTRACT The purpose of this piece is to offer a sense of Andre Delbecq as the pioneering founder of management, spirituality, and religion (MSR) as a field of scholarly inquiry. In his unique way, André, informed by his solid knowledge of organizational processes and his Christian faith, integrated spirituality into his teaching and scholarship. First I offer an overview of his early career roots which laid the foundation for this work and the impetus for his work on MSR, which defined the later years of his long and distinguished career. Then I review the context and motivations that led to his offering a seminar on Spirituality for Organizational Leadership, from which evolved what he saw as successful strategies for MSR scholarship and teaching. Next, comes an overview of his view of the fundamental role MSR should play in organizational design and culture, with an emphasis on teamwork and decision-making. Following this is an exploration of his groundbreaking work on leadership formation with a focus on the spiritual journey, discernment, and humility as an offset to hubris. Finally his thoughts concerning “Where do we go from here’ are offered.
Hepcidin is a Better Predictor of Iron Stores in Premenopausal Women than Blood Loss or Dietary Intake

The relationship between dietary intake, circulating hepcidin and iron status in free-living premenopausal women has not been explored. This cross-sectional study aimed to identify dietary determinants of iron stores after accounting for blood loss and to determine whether iron intake predicts iron stores independently of hepcidin in a sample of Australian women. Three hundred thirty eight women aged 18–50 years were recruited. Total intake and food sources of iron were determined via food frequency questionnaire; the magnitude of menstrual losses was estimated by self-report; and blood donation volume was quantified using blood donation records and self-reported donation frequency. Serum samples were analysed for ferritin, hepcidin and C-reactive protein concentrations. Linear regression was used to investigate associations. Accounting for blood loss, each 1 mg/day increase in dietary iron was associated with a 3% increase in iron stores (p = 0.027); this association was not independent of hepcidin. Hepcidin was a more influential determinant of iron stores than blood loss and dietary factors combined (R2 of model including hepcidin = 0.65; R2 of model excluding hepcidin = 0.17, p for difference <0.001), and increased hepcidin diminished the positive association between iron intake and iron stores. Despite not being the biggest contributor to dietary iron intake, unprocessed meat was positively associated with iron stores, and each 10% increase in consumption was associated with a 1% increase in iron stores (p = 0.006). No other dietary factors were associated with iron stores. Interventions that reduce hepcidin production combined with dietary strategies to increase iron intake may be important means of improving iron status in women with depleted iron stores.
License plate automatic detection and recognition using level sets and neural networks

In this paper, we propose a method for automatic license plate detection and recognition in the city of Abu Dhabi. The proposed method starts by segmenting moving vehicles using background subtraction. Segmented vehicles are tracked using a color-based particle-filtering technique until the vehicle is in position for a high resolution image to be taken by a still camera. The license plate is detected by converting the image into the LAB color space and using level set methods to locate its contour. Regularity and size are used to filter erroneous blobs. Geometric features are extracted from the blobs of license plate numbers and are passed to trained neural networks for classification. A model of the proposed system is built and its operations verified. Results show the proposed system's ability to determine a vehicles authorization status from the recognition of the license plate class or color as well as its number.
“They’re messing up our future because we need to learn these things”: a qualitative exploration of sexual health education experiences of Allegheny County adolescents

Introduction: Comprehensive Sex Education is relevant to public health in that it contributes to positive sexual and reproductive health outcomes among adolescents. Pennsylvania schools are not required to provide students with any sex education, though they must provide information about HIV and STDs and are required to stress abstinence. As a formative element of a larger needs assessment, the purpose of this work is to understand the sexual health education experiences and needs of adolescents in Allegheny County, as well as their recommendations for improving sexual health education and services. Methodology: In this qualitative study, semi-structured focus groups were conducted with eighteen adolescents recruited through community organizations. Focus groups were recorded and transcribed, and data was analyzed for key themes using initial and focused coding methods. Results: Most adolescents found their sex education to be lacking, and believed that subpar sex education impacts health outcomes. However, participant experiences differed according to the schools they attended. Participants recommended that school-based sex education be improved by covering more topics, using a student-centered framework, and facilitating a school culture of openness. Participants also suggested that schools provide them with condoms and that community organizations increase advertising and outreach to their demographic. Additionally, participants indicated that stigma associated with sexual health impacts the flow of information in schools. Conclusion: Findings suggest that both school and community organizations can improve the sexual health education and services that they provide to adolescents. Community organizations in particular will use these results to build upon their existing sexual health education programming and services and better serve adolescents in Allegheny County and to advocate for improved state and local sex education policy and implementation.
Inverted PBI in MOEA/D and its impact on the search performance on multi and many-objective optimization

MOEA/D decomposes a multi-objective optimization problem into a number of single objective optimization problems. Each single objective optimization problem is defined by a scalarizing function using a weight vector. In MOEA/D, there are several scalarizing approaches such as the weighted Tchebycheff, the weighted sum, and the PBI (penalty-based boundary intersection). However, these conventional scalarizing approaches face a difficulty to approximate a widely spread Pareto front in some problems. To enhance the spread of Pareto optimal solutions in the objective space and improve the search performance of MOEA/D especially in many-objective optimization problems, in this work we propose the inverted PBI scalarizing approach which is an extension of the conventional PBI. We use many-objective knapsack problems and WFG4 problems with 2-8 objectives, and compare the search performance of NSGA-III and four MOEA/Ds using the weighted Tchebycheff, the weighted sum, the PBI and the inverted PBI. As results, we show that MOEA/D using the inverted PBI achieves higher search performance than other algorithms in problems with many-objectives and the difficulty to obtain a widely spread Pareto front in the objective space.
Performance evaluation of Intel® Transactional Synchronization Extensions for high-performance computing

Intel has recently introduced Intel® Transactional Synchronization Extensions (Intel® TSX) in the Intel 4th Generation Core™ Processors. With Intel TSX, a processor can dynamically determine whether threads need to serialize through lock-protected critical sections. In this paper, we evaluate the first hardware implementation of Intel TSX using a set of high-performance computing (HPC) workloads, and demonstrate that applying Intel TSX to these workloads can provide significant performance improvements. On a set of real-world HPC workloads, applying Intel TSX provides an average speedup of 1.41x. When applied to a parallel user-level TCP/IP stack, Intel TSX provides 1.31x average bandwidth improvement on network intensive applications. We also demonstrate the ease with which we were able to apply Intel TSX to the various workloads.
Association between Prepartum Feeding Behavior and Periparturient Health Disorders in Dairy Cows

The objective of this study was to investigate the relationship between prepartum feeding behavior, measured as time spent feeding per day, and periparturient health disorders, milk yield, milk composition, and milk somatic cell count in Jersey cows. Pregnant Jersey cows were marked with unique alphanumeric symbols and were moved into a prepartum group 4 weeks prior to their expected calving date. At enrollment, cows with a body condition score <2 or >4 or a locomotion score >3 were not included. Time spent feeding was measured using 10-min video scan sampling for 24-h periods of 2–4 days per week of the study. A total of 925 cows were eligible for analysis. Parity was based on lactation number at the time of enrollment and classified as nulliparous (cows pregnant with their first calf), primiparous (cows pregnant with their second calf), and multiparous (lactation ≥2). Multiparous cows with two or more health disorders spent approximately 10% less time feeding prepartum than cows that did not have any health disorders. Multiparous cows subsequently diagnosed with metritis had a tendency to spend 5% less time feeding prepartum than healthy counterparts. Primiparous cows with retained placenta had a 10% reduction in feeding time compared to healthy primiparous cows. Monitoring time spent feeding prepartum by primiparous and multiparous cows, even on a limited number of days, appeared to be beneficial in predicting cows at risk for periparturient health disorders. Real-time daily feeding behavior monitoring technologies that can be used by dairy farms are now available, which might prove to be even more helpful in identifying cows at risk for periparturient cow health disorders as more data points can be recorded for each cow and compared to her own behavior or that of specific cohorts.
Rising Wage Inequality in the Argentinean Manufacturing Sector : The Impact of Trade and Foreign Investment on Technology and Skill Upgrading

In the last 20 years, wage inequality has increased in many developing countries. Most research on this topic focuses on two possible causes: trade or skill-biased technical change. Several empirical studies document increases in skill intensity within all sectors, favoring the technological change explanation over trade. Instead, I present and test a model where trade and capital account liberalization increase the profitability of skill-biased new technologies in all sectors, but there is cross-firm heterogeneity in technology adoption due to differences in productivity, fixed costs of adoption and credit constraints. Liberalization drives the adoption of new technologies in developing countries by increasing market size, eliminating restrictions on technology transfers and reducing interest rates. Only the most productive firms enter export markets, and thus make enough profits to cover the fixed cost of technology adoption. Foreignowned firms are less subject to credit constraints, and hence are also more likely to be able to finance investment in technology. The model predicts that the level of technology spending and skill intensity after liberalization is discretely higher for exporters and foreign-owned firms; and the change in technology spending and skill upgrading has an inverted U shape, being highest for firms in the middle range of the productivity distribution, such as new entrants in the export market. I test these theoretical predictions in the context of the trade and capital account liberalization in Argentina in the early 1990s. I analyze a firmlevel data set that differs from standard industry surveys by including direct information on education of workers and on spending in technology adoption. I find that the increase in the relative demand of skilled labor does not come from labor reallocation across sectors, nor across firms but from skill upgrading within firms. Firms that upgrade technology faster also upgrade skill faster. The predictions of the model in terms of levels and changes in technology are confirmed by the data, controlling for sector, initial productivity and size. * I am grateful to Philippe Aghion, Pol Antras, Elhanan Helpman and specially Marc Melitz for their advice and support. For helpful suggestions and comments, I also wish to thank Ivan Fernandez-Val, Manuel Amador, Elsa V. Artadi, Thomas Chaney, Pascaline Dupas, Antara Dutta, Doireann Fitzgerald, Gita Gopinath, Marius Hentea, Gustavo Lugones, Kenneth Rogoff, Karine Serfaty and participants at the Harvard International Lunch. All remaining errors are mine. e-mail: bustos@fas.harvard. edu; address: Center for International Development at Harvard University, 79 JFK Steet, Cambridge MA 02138; phone: (617) 669 –9181; web address: www.people. fas.harvard. edu/~bustos.
Explicit large image theorems for modular forms

Let f be a (cuspidal) newform of weight k⩾2 and level Γ0(N) with N⩾1 . Ribet proved that, under the assumption that f is non‐CM, the residual representations ρ¯f,λ attached to f by Deligne have a large image, in a precise sense, for all but finitely many prime ideals λ . In this paper, we make Ribet's theorem explicit by proving that the residue characteristics of these finitely many prime ideals for which the conclusion of Ribet's theorem fails to satisfy some divisibility relation, or are bounded from above by explicit constants, depending on k and N . The results split into different cases according to the possible types for the image, and each of them is illustrated by some numerical examples.
Electronics, Information and Communication Engineering

A MIMO system can offer two types of gains i.e. spatial multiplexing (increase data rate) and diversity gain. However, these benefits of MIMO systems depend crucially on the kind of fading the channels undergo and whether the channel state information (CSI) is known at the transmitter. Most of the researches have been on Rayleigh channels. However in real world
CD-RAIS: Constrained dynamic striping in redundant array of independent SSDs

Solid state drives (SSDs) are increasingly deployed to construct storage arrays (RAIDs) in enterprise environments. The design decisions in RAID are traditionally devised for HDD RAIDs, which cannot fully exploit the characteristics of SSDs. In particular, SSD lacks the ability to update pages in-place. Random writes in traditional parity-based RAIS (SSD RAID) systems that has static striping result in significantly more writes, degraded performance, and shortened SSD lifetime. By dynamically forming full stripes, log-based design originally proposed in HDD RAID can mitigate the write-hole problem caused by random writes. However, it needs a directory to record locations for all data blocks, resulting in large space overhead and consequently sacrificing addressing efficiency. In this paper, we propose CD-RAIS, a compromise between static striping and dynamic striping. CD-RAIS groups requests that are from different SSD drives and places their corresponding unnecessarily consecutive logical blocks in one stripe. It mitigates the write-hole problem, meanwhile remains the same addressing efficiency as static striping. To enable dynamic data striping fit SSDs, CD-RAIS performs lazy data invalidation and consolidates updates to parity blocks. CD-RAIS greatly alleviates the write request increase due to parity block update in RAIS. Our experimental results show that, for random write dominated workloads, CD-RAIS achieves 65% response time improvement and 31% longer SSD lifespan over traditional RAIS schemes.
IATARPA: Implementation of anonymity threat avoidance routing protocol architecture for MANET

Mobile Ad hoc networks are a class of dynamic networks without any centralized administration. A major problem in Mobile Ad hoc networks (MANETs) is the anonymity threat arises among the nodes usually when they mobile. Many researches are concentred on the part of avoiding anonymity threat in MANET with different approaches using simulators. This paper presents an implementation of (ATARPA) Anonymity Threat Avoidance Routing Protocol Architecture in order to agonist the anonymity threat such as traceability, intrusion, observability and linkability. The ATARPA has been designed with the principle of reactive routing protocol. It provides strong security with anonymity protection and scalability.
The impact of practical network constraints on the performance of energy-aware routing schemes

Power consumption and CO2 emission have become a major concern over the last few years. Several recent studies have shown that servers and network equipments consume up to 45% of the energy consumption of data centers [1]. Software-defined networking is a new networking paradigm that decouples the control and data functionalities; thus, makes networks easily manageable and programmable. In software-defined networks (SDNs), the central controller has a global view of the network topology, traffic matrices and QoS requirements, which allows it to optimize the energy consumption of the network through energy-aware routing. In this paper, we investigate the impact of practical constraints, discreteness of link rates and limitation of flow rule space, on the performance of energy-aware routing schemes in SDN. The energy-aware routing problem is modeled as an integer linear program (ILP) with discrete cost function. The problem is modeled in GAMS and solved by CPLEX under real network settings and practical constraints. Results show that considering these constraints is critical in order to exploit the energy saving margin of SDNs.
The Ornstein-Uhlenbeck Process Does Not Reproduce Spiking Statistics of Neurons in Prefrontal Cortex

Cortical neurons of behaving animals generate irregular spike sequences. Recently, there has been a heated discussion about the origin of this irregularity. Softky and Koch (1993) pointed out the inability of standard single-neuron models to reproduce the irregularity of the observed spike sequences when the model parameters are chosen within a certain range that they consider to be plausible. Shadlen and Newsome (1994), on the other hand, demonstrated that a standard leaky integrate-and-fire model can reproduce the irregularity if the inhibition is balanced with the excitation. Motivated by this discussion, we attempted to determine whether the Ornstein-Uhlenbeck process, which is naturally derived from the leaky integration assumption, can in fact reproduce higher-order statistics of biological data. For this purpose, we consider actual neuronal spike sequences recorded from the monkey prefrontal cortex to calculate the higher-order statistics of the interspike intervals. Consistency of the data with the model is examined on the basis of the coefficient of variation and the skewness coefficient, which are, respectively, a measure of the spiking irregularity and a measure of the asymmetry of the interval distribution. It is found that the biological data are not consistent with the model if the model time constant assumes a value within a certain range believed to cover all reasonable values. This fact suggests that the leaky integrate-and-fire model with the assumption of uncorrelated inputs is not adequate to account for the spiking in at least some cortical neurons.
Automatic Memory Partitioning: Increasing memory parallelism via data structure partitioning

In high-level synthesis, pipelined designs are often restricted by the number of memory banks available to the synthesis system. Using multiple memory banks can improve the performance of accelerated applications. Currently, programmers must manually assign data structures to specific memory banks on the accelerator. This paper presents Automatic Memory Partitioning, a method for automatically partitioning data structures into multiple memory banks for increased parallelism and performance. We use source code instrumentation to collect memory traces in order to detect linear memory access patterns. The memory traces are used to split data structures into disjoint memory regions and determine which segments may benefit from parallel memory access. Experiments show significant improvements in performance while using a minimal number of memory banks.
If Derivatives Are Used to Hedge Risk , Why Do Some Firms Lose So Much Money ?

J . D A V I D C U M M I N S , R I C H A R D D . P H I L L I P S , A N D S T E P H E N D . S M I T H Cummins is the Harry J. Loman Professor of Insurance and Risk Management at the Wharton School, University of Pennsylvania, and a senior fellow at the Wharton Financial Institutions Center. Phillips is an assistant professor at Georgia State University. Smith holds the H. Talmage Dobbs Jr. Chair of Finance, Georgia State University, and is a visiting scholar at the Atlanta Fed. The authors thank Robert Bliss, Gerald Dwyer, Saikat Nandi, and Mary Rosenbaum for helpful comments.