Miracle-dz/UniFAR-FTUs huggingface dataset:
Higher Education Service-Learning Sourcebook:

Service-learning in higher education symbiotically combines community service and academic study--that both fields strengthen in the union is one reason for the movement's increasing popularity. This comprehensive guide to service-learning in colleges and universities includes: * A-Z encyclopedia of terms and concepts * Directory of service-learning programs and services at 325 colleges and universities * Resource guide to essential information culled from books, journals, Web sites, and Internet discussion groups * Directory of service-learning organizations, conferences, institutes, and training opportunities * Inventory of awards, scholarships, fellowships, internships, and grants in the field This multi-faceted new resource is a gold mine for college administrators, faculty, students, and volunteer coordinators involved in higher education service-learning.
A state-space partitioned-block adaptive filter for echo cancellation using inter-band correlations in the Kalman gain computation

A partitioned-block-based architecture for a model-based acoustic echo canceller in the frequency domain was recently presented. Partitioned-block-based frequency domain adaptive filters provide a lower algorithmic delay compared to the non-partitioned formulations, which is achieved by partitioning the acoustic echo path and hence shortening the time-frequency transforms. Under these circumstances, avoiding the linearisation of the involved circular convolutions can significantly impair the performance. This paper extends the already proposed diagonalization of the Kalman gain matrix by taking into account the neglected inter-band correlations to improve the performance of the acoustic echo canceller. This comes at the cost of a moderate increase in the algorithmic complexity.
Explaining EU Citizens’ Trust in the ECB in Normal and Crisis Times

We study the determinants of trust in the ECB as measured by the European Commission’s Eurobarometer survey in particular during the global financial crisis and the European sovereign debt crisis. We find that the fall in trust in the ECB in crisis times can be rather well explained based on the pre-crisis determinants, and show that the fall in trust reflected the macroeconomic deterioration, a more generalised fall in the trust in European institutions in the wake of the crisis as well as the severity of the banking sector’s problems, to which the ECB was associated in the public opinion.
Teacher Development in Slovenia for Teaching Foreign Languages at the Primary Level

The introduction of foreign languages into the first three-year cycle of primary school has spurred the need for qualified teachers, and is one of the main discussion points among experts in foreign language teaching. Most of the contemporary studies report that there is a global gap between the supply of qualified teachers of foreign languages to young learners and the demand for them as programmes expand. These studies emphasize the paramount importance in assuring the quality of early foreign language instruction. Therefore, the authors of this paper first present some of the models of initial and in-service training of teachers of foreign languages to young learners across the world and then focus on a more in-depth presentation and analysis of the training of teachers of foreign languages at the primary level in Slovenia. All the existing national programmes for teacher development are compared and discussed. Finally, some guidelines and recommendations are given regarding training teachers to teach foreign languages to young learners.
A Welfare Analysis of Unilateral Trade and FDI Liberalization

This paper uses a heterogeneousfirms model to examine the procompetitive channel through which FDI affects national welfare. The model shows that the country from which FDI originates experiences a welfare gain following liberalization. However, a counterintuitive finding is that the welfare of the host country deteriorates. This is explained by the production relocation process that leads to an increase in the mass of domestic firms in the source country and a decrease in the host country. The model also confirms that unilateral trade liberalization brings a similar result even in the presence of bilateral FDI flows.
Enterococcus faecalis Produces Abundant Extracellular Structures Containing DNA in the Absence of Cell Lysis during Early Biofilm Formation

ABSTRACT Enterococcus faecalis is a common Gram-positive commensal bacterium of the metazoan gastrointestinal tract capable of biofilm formation and an opportunistic pathogen of increasing clinical concern. Dogma has held that biofilms are slow-growing structures, often taking days to form mature microcolonies. Here we report that extracellular DNA (eDNA) is an integral structural component of early E. faecalis biofilms (≤4 h postinoculation). Combining cationic dye-based biofilm matrix stabilization techniques with correlative immuno-scanning electron microscopy (SEM) and fluorescent techniques, we demonstrate that—in early E. faecalis biofilms—eDNA localizes to previously undescribed intercellular filamentous structures, as well as to thick mats of extruded extracellular matrix material. Both of these results are consistent with previous reports that early biofilms are exquisitely sensitive to exogenous DNase treatment. High-resolution SEM demonstrates a punctate labeling pattern in both structures, suggesting the presence of an additional, non-DNA constituent. Notably, the previously described fratricidal or lytic mechanism reported as the source of eDNA in older (≥24 h) E. faecalis biofilms does not appear to be at work under these conditions; extensive visual examination by SEM revealed a striking lack of lysed cells, and bulk biochemical assays also support an absence of significant lysis at these early time points. In addition, some cells demonstrated eDNA labeling localized at the septum, suggesting the possibility of DNA secretion from metabolically active cells. Overall, these data are consistent with a model in which a subpopulation of viable E. faecalis cells secrete or extrude DNA into the extracellular matrix. IMPORTANCE This paper reports the production of extracellular DNA during early biofilm formation in Enterococcus faecalis. The work is significant because the mechanism of eDNA (extracellular DNA) production is independent of cell lysis and the DNA is confined to well-defined structures, suggesting a novel form of DNA secretion by viable cells. Previous models of biofilm formation in enterococci and related species propose cell lysis as the mechanism of DNA release. This paper reports the production of extracellular DNA during early biofilm formation in Enterococcus faecalis. The work is significant because the mechanism of eDNA (extracellular DNA) production is independent of cell lysis and the DNA is confined to well-defined structures, suggesting a novel form of DNA secretion by viable cells. Previous models of biofilm formation in enterococci and related species propose cell lysis as the mechanism of DNA release.
From variable density sampling to continuous sampling using Markov chains

Since its discovery over the last decade, Compressed Sensing (CS) has been successfully applied to Magnetic Resonance Imaging (MRI). It has been shown to be a powerful way to reduce scanning time without sacrificing image quality. MR images are actually strongly compressible in a wavelet basis, the latter being largely incoherent with the k-space or spatial Fourier domain where acquisition is performed. Nevertheless, since its first application to MRI [1], the theoretical justification of actual k-space sampling strategies is questionable. Indeed, the vast majority of k-space sampling distributions have been heuris- tically designed (e.g., variable density) or driven by experimental feasibility considerations (e.g., random radial or spiral sampling to achieve smoothness k-space trajectory). In this paper, we try to reconcile very recent CS results with the MRI specificities (magnetic field gradients) by enforcing the measurements, i.e. samples of k-space, to fit continuous trajectories. To this end, we propose random walk continuous sampling based on Markov chains and we compare the reconstruction quality of this scheme to the state-of-the art.
Review spam detection using active learning

As the access to Internet has been so much easier in the last decade or so, people are using online applications more than ever. Online marketing, in fact, the whole e-commerce is getting enormous day by day if not in every minute. Online Reviews play a very important role in this field and proving itself to be auspicious in terms of decision making from a customer's point of view. Even though these are very sensitive and significant information, ensuring the authenticity of user-generated content (Reviews, forums, blogs, discussion groups etc.) is erratically visible. That is why spamming, fake reviews and fabricated opinions are on the rise. Materially, it has become a profitable business which hampers the ingenuousness of the real fact. Several techniques have been introduced regarding this problem which depend mostly upon empirical conditions, rating consistency, obvious content features, and helpfulness voting etc. which confines the effectiveness of this undertaking. Most of the existing researches are supervised models whereas, good quality large-scale datasets are still very scarce and most of the models use pseudo fake reviews instead of real fake reviews. In this research, we introduce active learning approach to detect review spam using the TF-IDF features of the review content. Our model achieves phenomenal improvements in performance measures, working on almost 3600 reviews from different domains. In the best case, it achieves up to 88% accuracy and precision, recall and f-scores are above 85% in most cases. Additionally, about 2000 reviews were manually labeled during the process. Finally, after evaluating results, it indicates that this is a promising methodology for detecting review spams.
Radiation therapy and esophageal cancer.

BACKGROUND Squamous cell carcinoma and adenocarcinoma account for more than 90% of all esophageal cancer cases. Although the incidence of squamous cell carcinoma has declined, the incidence of adenocarcinoma has risen due to increases in obesity and gastroesophageal reflux disease. METHODS The authors examine the role of radiation therapy alone (external beam and brachytherapy) for the management of esophageal cancer or combined with other modalities. The impact on staging and appropriate stratification of patients referred for curative vs palliative intent with modalities is reviewed. The authors also explore the role of emerging radiation technologies. RESULTS Current data show that neoadjuvant chemoradiotherapy followed by surgical resection is the accepted standard of care, with 3-year overall survival rates ranging from 30% to 60%. The benefit of adjuvant radiation therapy is limited to patients with node-positive cancer. The survival benefit of surgical resection after chemoradiotherapy remains controversial. External beam radiation therapy alone results in few long-term survivors and is considered palliative at best. Radiation dose-escalation has failed to improve local control or survival. Brachytherapy can provide better long-term palliation of dysphagia than metal stent placement. Although three-dimensional conformal treatment planning is the accepted standard, the roles of IMRT and proton therapy are evolving and potentially reduce adverse events due to better sparing of normal tissue. CONCLUSIONS Future directions will evaluate the benefit of induction chemotherapy followed by chemoradiotherapy, the role of surgery in locally advanced disease, and the identification of responders prior to treatment based on microarray analysis.
Performance evaluation of Galois Field arithmetic operators for optimizing Reed Solomon Codec

A series of experiments has been conducted to show that efficiency improvement in Galois Field (GF) operators does not directly correspond to the system performance at application level. The experiments were motivated by so many research works focusing on performance improvement of GF operators. Numerous variants of operators were formed based on various combination of operation types (multiplication, division, inverse, square), representation basis (Polynomial, Normal, Dual), and processing types (serial, parallel). Each of the variants has the most efficient form in either time (fastest) or space (smallest occupied area) when implemented in FPGA chips. In fact, GF operators are not utilized individually, rather integrated one to the others in implementing algorithms, mostly in error correction codes and cryptography applications. The experiments based on the implementation of Reed Solomon Encoder and Decoder RS(15,11) 4-bit using VHDL by means of two synthesis tools the Xilinx ISE 8.2i and the Altium ProChip Designer concludes that application performance mainly depends on the composition and distribution of the operators as well as their interaction and interconnection within the system architecture.
SHAPE-Seq 2.0: systematic optimization and extension of high-throughput chemical probing of RNA secondary structure with next generation sequencing

RNA structure is a primary determinant of its function, and methods that merge chemical probing with next generation sequencing have created breakthroughs in the throughput and scale of RNA structure characterization. However, little work has been done to examine the effects of library preparation and sequencing on the measured chemical probe reactivities that encode RNA structural information. Here, we present the first analysis and optimization of these effects for selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq). We first optimize SHAPE-Seq, and show that it provides highly reproducible reactivity data over a wide range of RNA structural contexts with no apparent biases. As part of this optimization, we present SHAPE-Seq v2.0, a ‘universal’ method that can obtain reactivity information for every nucleotide of an RNA without having to use or introduce a specific reverse transcriptase priming site within the RNA. We show that SHAPE-Seq v2.0 is highly reproducible, with reactivity data that can be used as constraints in RNA folding algorithms to predict structures on par with those generated using data from other SHAPE methods. We anticipate SHAPE-Seq v2.0 to be broadly applicable to understanding the RNA sequence–structure relationship at the heart of some of life's most fundamental processes.
Advanced low cost clustering system

This document describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method. The computation time is about 800 frame/sec for a VGA sequence on a 2.3GHz processor (ARM Cortex-A15). Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lens, linear and fish-eye.
Millimeter-Wave Enhanced Local Area Systems: A High-Data-Rate Approach for Future Wireless Networks

Wireless data traffic is projected to skyrocket 10 000 fold within the next 20 years. To tackle this incredible increase in wireless data traffic, a first approach is to further improve spectrally efficient systems such as 4G LTE in bands below 6 GHz by using more advanced spectral efficiency techniques. However, the required substantial increase in system complexity along with fundamental limits on hardware implementation and channel conditions may limit the viability of this approach. Furthermore, the end result would be an extremely spectrally efficient system with little room for future improvement to meet the ever-growing wireless data usage. The second approach is to move up in frequency, into an unused nontraditional spectrum where enormous bandwidths are available, such as at millimeter wave (mmWave). The mmWave option enables the use of simple air interfaces since large bandwidths can be exploited (e.g., 2 GHz) to achieve high data rates rather than relying on highly complex techniques originally aimed at achieving a high spectral efficiency with smaller bandwidths. In addition, mmWave systems will easily evolve to even higher system capacities, because there will be plenty of margin to improve the spectral efficiency as data demands further increase. In this paper, a case is made for using mmWave for a fifth generation (5G) wireless system for ultradense networks by presenting an overview of enhanced local area (eLA) technology at mmWave with emphasis on 5G requirements, spectrum considerations, propagation and channel modeling, air-interface and multiantenna design, and network architecture solutions.
Knowledge-Based Deformable Matching for Pathology Detection

Image registration is the process of matching corresponding features between images. Medical images present a challenge for registration because the same anatomical features vary considerably in appearance across individuals, and any pathology may aggravate the variation. We propose a registration method that uses knowledge of anatomy to cope with variations in the appearance of corresponding features and to help detect pathologies. The same anatomical feature may have a different density, shape, and size across individuals, but there exists a normal range of variation. Various clinical conditions may affect the gross anatomical morphology, but certain pathologies have characteristic impacts on the anatomy. Traditional registration methods do not seek guidance from this domain knowledge, and they fail to yield accurate registrations because medical images have complicated shapes, non-uniform textures, and ill-defined boundaries. Our algorithm will attempt to apply domain knowledge in the registration process to cope with the variations in appearance. We are especially interested in the registration of images showing pathologies because of its medical importance. In pursuit of this, we have developed a hierarchical registration algorithm that permits variations in appearance. We will infuse domain knowledge to discern normal and abnormal variations in appearances. The hierarchical registration algorithm has three levels. First a 3-D transformation (rotation, uniform scaling, and translation) globally aligns the different image sets. Secondly a smooth 3-D deformation approximately matches the anatomical structures in the image sets. This attempts to address the inherent differences in the appearances of their anatomical structures. Finally, the match is refined by a free-form deformation to adjust to the small variations overlooked by the smooth deformation. We have developed this algorithm and conducted experiments on real data sets with and without pathologies. The results from the above registration algorithm are promising, but the algorithm has some limitations. We intend to extract and encode domain knowledge (e.g. using Principal Component Analysis), and apply it to guide the registration process (only permitting normal variations or characteristic impact caused by certain pathologies). To handle intensity variation, we plan to use mutual information as the matching criterion. We will establish a standard validation method and test database to quantitatively evaluate the accuracy of our algorithm and related work. The system will help in detecting lesions, observing the development of pathologies over time, indexing and retrieval in medical databases, conducting cross-patient analysis, and studying the functionality of different parts of the brain.
Photocatalytic Conversion of CO2 to Hydrocarbon Fuels via Plasmon-Enhanced Absorption and Metallic Interband Transitions

A systematic study of the mechanisms of Au nanoparticle/TiO2-catalyzed photoreduction of CO2 and water vapor is carried out over a wide range of wavelengths. When the photon energy matches the plasmon resonance of the Au nanoparticles (free carrier absorption), which is in the visible range (532 nm), we observe a 24-fold enhancement in the photocatalytic activity because of the intense local electromagnetic fields created by the surface plasmons of the Au nanoparticles. These intense electromagnetic fields enhance sub-bandgap absorption in the TiO2, thereby enhancing the photocatalytic activity in the visible range. When the photon energy is high enough to excite d band electronic transitions in the Au, in the UV range (254 nm), a different mechanism occurs resulting in the production of additional reaction products, including C2H6, CH3OH, and HCHO. This occurs because the energy of the d band excited electrons lies above the redox potentials of the additional reaction products CO2/C2H6, CO2/CH3OH, and CO.
The Value of Heterogeneous Property Rights and the Costs of Water Volatility

&NA; The system of prior appropriation in the Western Unites States prioritizes property rights for water based on the establishment of beneficial use, creating a hierarchy where rights initiated first are more secure. I estimate the demand for security in water rights through their capitalization in agricultural property markets in the Yakima River Basin, a major watershed in Washington State. All water rights are satisfied in an average year, so the relative value of secure property rights is a function of water supply volatility and the costs of droughts are predominantly born by those with weak rights. In aggregate, security in water rights does not capitalize into property values at the irrigation district level; however, there is heterogeneity in the premium for secure water rights. The lack of a premium for district‐level water security is robust to a variety of econometric methods to account for correlated district unobservables, and the null result produces an economically significant upper bound on the value to water security for the district. The ability for farmers to adapt to water supply volatility, as well as expectations about water markets and government infrastructure investment, are leading explanations for the lack of an aggregate premium. These explanations are supported by the pattern of heterogeneity in the water security premium.