Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Nanometal Oxides In Situ in Nonwoven Polyester Fabric for the Removal of Bacterial Indicators of Pollution from Wastewater

The objective of this study is to investigate and assess the use of in situ deposit nanosilver (nAg2O) or nanocopper oxides (nCuO) into nonwoven polyester fabric (NWPF) as a safe and effective antibacterial filter of pollution from domestic wastewater. The bactericidal effect of both nAg2O and nCuO was examined against Gram-negative bacteria (Escherichia coli, Salmonella typhi) and Gram-positive bacteria (Enterococcus faecalis, Staphylococcus aureus) using agar diffusion disk method. In addition, the capability of nAg2O and nCuO as disinfectants for secondary treated domestic wastewater was investigated as a case study. Transmission electron microscope (TEM) confirmed the formation of nAg2O and nCuO particles with average particle sizes of 15 and 41 nm, respectively. Disk diffusion results showed that nAg2O had a higher bactericidal effect than nCuO. Moreover, the disinfection of secondary treated wastewater using 1.27 mg/cm3 of nAg2O in the nonwoven fabric was capable of hindering 99.6% and 91.7% of total and fecal coliforms within 10 minutes with a residual value of 18 and 15 MPN-index/100 mL, respectively. The residual total and fecal coliform concentrations were far less than that stated in the national and international limits for wastewater reuse in agriculture purpose.
Fast and Robust Arabic Error Correction System

In this paper we describe the implementation of an Arabic error correction system developed for the EMNLP2014 shared task on automatic error correction for Arabic text. We proposed a novel algorithm, where we find some correction rules and calculate their probability based on the training data, they we rank the correction rules, then we apply them on the text to maximize the overall Fscore for the provided data. The system achieves and F-score of 0.6573 on the test data.
SOLVING THE DISCRETE lp-APPROXIMATION PROBLEM BY A METHOD OF CENTERS1

The discrete lp-approximation problem is a basic problem in approximation theory and optimization. This problem is normally solved by Newton-type methods which are complicated by the nondifferentiability of the gradient function for p ∈ [1, 2). This paper discusses a scheme and its implementation for solving this problem by a method of analytic centers, which provides a unified treatment for all p ≥ 1 and has a polynomial bound of complexity. The original problem is reformulated as a constrained convex programming problem which admits a self-concordant logarithmic barrier. A special structure of the Newton system derived from minimizing the potential function is utilized to reduce the amount of computation. Some other implementation techniques are also presented. Computational results show that the method of centers is robust for all p.
Accurate Multi-cycle ATPG in Presence of X-Values

Unknown (X) values in a circuit impair test quality and increase test costs. Classical n-valued algorithms for fault simulation and ATPG, which typically use a three- or four-valued logic for the good and faulty circuit, are in principle pessimistic in presence of X-values and cannot accurately compute the achievable fault coverage. In partial scan or pipelined circuits, X-values originate in non-scan flip-flops. These circuits are tested using multi-cycle tests. Here we present multi-cycle test generation techniques for circuits with X-values due to partial scan or other X-sources. The proposed techniques have been integrated into a multi-cycle ATPG framework which employs formal Boolean and quantified Boolean (QBF) satisfiability techniques to compute the possible signal states in the circuit accurately. Efficient encoding of the problem instance ensures reasonable runtimes. We show that in presence of X-values, the detection of stuck-at faults requires not only exact formal reasoning in a single cycle, but especially the consideration of multiple cycles for excitation of the fault site as well as propagation and controlled reconvergence of fault effects. For the first time, accurate deterministic ATPG for multi-cycle test application is supported for stuck-at faults. Experiments on ISCAS'89 and industrial circuits with X-sources show that this new approach increases the fault coverage considerably.
Energy Production and Economic Growth: A Causality Analaysis for Turkey Based on Computer

High levels of energy prices and the promise of international initiatives on decreasing the greenhouse gas emissions have regenerated the argument about the execution of energy conservation policies. This paper investigates the causal relationship between aggregated and disaggregated levels of energy production, energy demand, energy import and economic growth for Turkey for the period of 1975–2007. The relationship between the energy production, energy demand, energy import and Gross Domestic Product is examined. To this end, Engle-Granger cointegration, Error Correction Model and Granger causality tests are applied in order to determine the aforementioned relation. It is found that the energy production has direct relationship with the GDP and it has causality effects.
Effect of Center Frequency on the Sensitivity to Interaural Time Differences in Filtered Pulse Trains

Some cochlear implant (CI) listeners are sensitive to interaural time differences (ITD) in the temporal fine structure for pulse rates up to 800 pulses per second (pps) [1,2]. The rate limitation in normal hearing (NH) depends on the type of stimulus. For high-frequency filtered transients, the rate limit is within the range 256 − 600 pps, thus lower than in CI listeners [1,2,3]. For pure tones, the rate limit is about 1500 Hz, thus higher than in CI listeners [4]. This study attempted to verify that the NH listeners’ performance using high-frequency filtered pulse-trains in [1,2] was not underestimated by a potentially unfavorable choice of the center frequency (CF) of the stimulus (4.6 kHz) based on the following hypothesis: if the ringing of the auditory filters limits ITD perception at higher pulse rates, the maximum pulse rate showing significant effects of ITD will increase with increasing CF.
Generating Automated Text Complexity Classifications That Are Aligned with Targeted Text Complexity Standards. Research Report. ETS RR-10-28.

The Common Core Standards call for students to be exposed to a much greater level of text complexity than has been the norm in schools for the past forty years. Textbook publishers, teachers, and assessment developers are being asked to refocus materials and methods to ensure that students are challenged to read texts at steadily increasing complexity levels as they progress through school so that all students remain on track to achieve college and career readiness by the end of 12th grade. Although automated text analysis tools have been proposed as one method for helping educators achieve this goal, research suggests that existing tools are subject to three limitations: inadequate construct coverage; overly narrow criterion variables; and inappropriate treatment of genre effects. Modeling approaches developed to address these limitations are described. Recommended approaches are incorporated into a new text analysis system called SourceRater. Validity analyses implemented on an independent sample of texts suggest that, compared to existing approaches, SourceRater's estimates of text complexity are more reflective of the complexity classifications given in the new Standards. Implications for the development of learning progressions designed to help educators organize curriculum, instruction and assessment in reading are discussed.
Development of Isolated Word Speech Recognition System

The isolated word speech recognition system based on dynamic time warping (DTW) has been developed. Speaker adaptation is performed using speaker recognition techniques. Vector quantization is used to create reference templates for speaker recognition. Linear predictive coding (LPC) parameters are used as features for recognition. Performance is evaluated using 12 words of Lithuanian language pronounced ten times by ten speakers.
Clustering Ontology-enriched Graph Representation for Biomedical Documents based on Scale-Free Network Theory

The following item is made available as a courtesy to scholars by the author(s) and Drexel University Library and may contain materials and content, including computer code and tags, artwork, text, graphics, images, and illustrations (Material) which may be protected by copyright law. Unless otherwise noted, the Material is made available for non profit and educational purposes, such as research, teaching and private study. For these limited purposes, you may reproduce (print, download or make copies) the Material without prior permission. All copies must include any copyright notice originally included with the Material. You must seek permission from the authors or copyright owners for all uses that are not allowed by fair use and other provisions of the U.S. Copyright Law. The responsibility for making an independent legal assessment and securing any necessary permission rests with persons desiring to reproduce or use the Material. Abstract⎯ In this paper we introduce a novel document clustering approach that solves some major problems of traditional document clustering approaches. Instead of depending on traditional vector space model, this approach represents documents as graphs using domain knowledge in ontology because graphs can represent the semantic relationships among the concepts in documents. Based on scale-free network theory, our approach generates a model for each document cluster from the ontology-enriched graph representation by identifying k high density subgraphs capturing the core semantic relationship information about each document cluster. Using these k high density subgraphs, each document is assigned to a proper document cluster. Our extensive experimental results on MEDLINE articles show that our approach outperforms two leading document clustering algorithms, BiSecting K-means and CLUTO's vcluster. Moreover, our approach provides a meaningful explanation for document clustering through generated models. This explanation helps users to understand clustering results and documents as a whole.
A Distributed Graph Algorithm for Discovering Unique Behavioral Groups from Large-Scale Telco Data

It is critical for a large telecommunications company such as Singtel to truly understand the behavior and preference of its customers, in order to win their loyalty in a highly fragmented and competitive market. In this paper we propose a novel graph edge-clustering algorithm (DGEC) that can discover unique behavioral groups, from rich usage data sets (such as CDRs and beyond). A behavioral group is a set of nodes that share similar edge properties reflecting customer behavior, but are not necessarily connected to each other and therefore different from the usual notion of graph communities. DGEC is an optimization-based model that uses the stochastic proximal gradient method, implemented as a distributed algorithm that scales to tens of millions of nodes and edges. The performance of DGEC is satisfactory for deployment, with an execution time of 2.4 hours over a graph of 5 million nodes and 27 million edges in a 8-machine environment (32 cores and 64GB memory per machine). We evaluate the behavioral groups discovered by DGEC by combining other information such as demographics and customer profiles, and demonstrate that these behavioral groups are objective, consistent and insightful. DGEC has now been deployed in production, and also shows promising potential to extract new usage behavioral features from other data sources such as web browsing, app usage and TV consumption.
Clinical and Genetic Analysis of Multiple Endocrine Neoplasia Type 1-Related Primary Hyperparathyroidism in Chinese

Objective Multiple endocrine neoplasia type 1-related primary hyperparathyroidism (MHPT) differs in many aspects from sporadic PHPT (SHPT). The aims of this study were to summarize the clinical features and genetic background of Chinese MHPT patients and compare the severity of the disease with those of SHPT. Design and Methods A total of 40 MHPT (27 sporadic, 7 families) and 169 SHPT cases of Chinese descent were retrospectively analyzed. X-rays and ultrasound were used to assess the bone and urinary system. Dual energy x-ray absorptiometry (DXA) were performed to measure bone mineral density (BMD). Besides direct sequencing of the MEN1 and CDKN1B genes, multiplex ligation-dependent probe amplification (MLPA) was used to screen gross deletion for the MEN1 gene. Results Compared with SHPT patients, MHPT patients showed lower prevalence of typical X-ray changes related to PHPT (26.3% vs. 55.7%, P = 0.001) but higher prevalence of urolithiasis/renal calcification (40.2% vs. 60.0%, P = 0.024). MHPT patients showed higher phosphate level (0.84 vs. 0.73mmol/L, P<0.05) but lower ALP (103.0 vs. 174.0U/L, P<0.001) and PTH (4.0 vs. 9.8×upper limit, P<0.001) levels than SHPT patients. There were no significant differences in BMD Z-scores at the lumbar spine and femoral neck between the two groups. Mutations in the MEN1 gene were detected in 27 MHPT cases. Among the nine novel mutations were novel, one of them involved the deletion of exon 5 and 6. Conclusions MHPT patients experienced more common kidney complications but less skeletal issues, and a milder biochemical manifestation compared with SHPT patients. MEN1 mutation detection rate was 79.4% and 9 of the identified mutations were novel.
Revealing the Nature of Dark Energy Using Bayesian Evidence

We apply the Bayesian concept of ‘evidence’ to reveal systematically the nature of dark energy from present and future supernova luminosity distance measurements. We express the unknown dark energy equation of state w(z) as a low order polynomial in redshift and use evidence to find the polynomial order, thereby establishing the minimum order required by the data. We apply this method to the current supernova data, and with a prior 1 � w(z) � 1 and m = 0.3±0.05, obtain a large probability of 91% for the cosmological constant model, with the remaining 9% assigned to the two more complex models tested. We also investigate the use of evidence for future supernova data sets such as distances obtainable from surveys like the Supernova Acceleration Probe (SNAP). Given a low uncertainty on the present day matter density we find that, if the underlying dark energy model is only modestly evolving, then a constant w(z) fit is sufficient. However, if the evolution of the dark energyequation of state to linear order is larger than |w1| � 0.5, then the evolution can be established with statistical significance. For models where we can assume the prior 1 � w(z) � 1, the correct polynomial order can be established even for modestly evolving equations of state.
Detection of Anthropogenic Climate Change in the World ’ s Oceans

ing method is easily generalized to allow for different ways of hardening the particle coats. With the use of appropriate reagents, this technique is also compatible with schemes that thermally or optically initiate the hardening of the coats. Figure 6 shows confocal images of a polystyrene bead encapsulated with an agarose coat that was hardened by lowering its temperature. In Fig. 7, we show an optical micrograph of a poppy seed encapsulated in a poly(styrenesulfonic acid) coat that was photopolymerized. The selective withdrawal geometry may also be inverted by inserting the straw through the bottom of the withdrawal container, with the straw tip positioned below the interface. Now the denser aqueous fluid is the primary fluid being withdrawn , and the particles to be coated are placed in the oil (upper fluid). This inversion extends the applicability of this coating technique to hydrophobic particles in oil-soluble reagents as well as to heavy particles in the upper fluid that will sediment to the interfa-cial boundary. The selective withdrawal coating technique complements other currently available techniques, such as surface-induced polymer-ization (10), which can also produce coats of uniform thickness on irregularly shaped particles but which often require modification of the particle surface and therefore may not be feasible. In our technique, as illustrated in the description of the polyamide coating, the particles can be completely separated from the caustic reagents that initiate the polymeriza-tion at the outer interface. Moreover, surface-induced polymerization requires the reagent to be stable in the solution being polymer-ized. This is not always possible (as with the polyamide coat installation, the trichloride reagent is unstable in aqueous solutions), and selective withdrawal can solve this problem by initiating polymerization with a reagent that is stable in the fluid surrounding the coat. Finally, many polymer coatings are either difficult [e.g., the photopolymerized poly-(styrenesulfonic acid) coat shown in Fig. 7] or impossible (e.g., the thermally hardened agarose coat shown in Fig. 6) to prepare using techniques such as surface-induced polymer-ization and must be hardened in bulk. For these cases in particular, selective withdrawal presents a valuable advantage over currently available coating techniques. The selective withdrawal technique can be readily optimized. With a single tube we estimate that 10,000 particles can be coated per hour. Preliminary experiments have demonstrated that this technique can be scaled up by using an array of tubes in parallel. Injecting particles directly into the region below the spout …
The environmental industry, environmental policies, and international trade (Symposium on contemporary issues of international trade)

In this paper we construct a two country model with a final good and an environmental good such as a pollution abatement equipment to examine the formation of comparative advantage based on the international differences of environmental policies and the effects of the emission tax under free trade. The main results of our paper are as follows. First, the subsidy on the environmental good purchase can be a substitute for the emission tax. That is, the government can impose the lower emission tax by raising the subsidy in order to achieve the first best allocation. Second, a raise in the emission tax decreases the relative price of the environmental good while a raise in the subsidy increases the relative price. Hence, ceteris paribus, the country with a higher emission tax or a lower subsidy on the use of the environmental good has a comparative advantage in this good. Third, the effects of the emission tax in one country on the amount of pollution and welfare depends on the specialization pattern under free trade.
Prerequisites to authentication protocols proved by binding theory

The paper proposes a binding theory and security prerequisites proposition to authentication protocols. The binding theory constructs a formal theory model by which can quickly infer some security properties. Binding theory comes from the basic ideas that the key used in cryptographic protocols is the kernel component for the security protocols. Based on binding theory, security prerequisites proposition to authentication protocols is modeled and proved. Binding theory and security prerequisites proposition to authentication protocols can simply and efficiently decide security properties when authentication protocols have security weakness for authentication properties. Some classical security protocols are taken as examples to infer and discover some of their security properties broken by binding theory and security prerequisites proposition.
Improving Exploration in UCT Using Local Manifolds

Monte-Carlo planning has been proven successful in manysequential decision-making settings, but it suffers from poorexploration when the rewards are sparse. In this paper, weimprove exploration in UCT by generalizing across similarstates using a given distance metric. We show that this algorithm,like UCT, converges asymptotically to the optimalaction. When the state space does not have a natural distancemetric, we show how we can learn a local manifold from thetransition graph of states in the near future. to obtain a distancemetric. On domains inspired by video games, empiricalevidence shows that our algorithm is more sample efficientthan UCT, particularly when rewards are sparse.
Autonomous Aerial Sensors for Wind Power Meteorology - A Pre-Project

max. 2000 char. ): Autonomous Aerial Sensors, i.e. meteorological sensors mounted on Unmanned Aerial Systems UAS, can characterise the atmospheric flow in and around wind farms. We instrumented three planes, a helicopter and a lighter-than-air LTA system to fly one week together in a well-instrumented wind farm, partly with nanosynchronised sensors (time stamped with about 100 ns global accuracy). Between bankruptcy of a partner, denied overflight rights at the main test location, denied Civil Aviation Authorities permits at the alternative location, stolen planes, and crashed UAS we managed to collect data at a wind farm in Lolland and on an atmospheric campaign in France. Planning of an offshore campaign using the developed techniques is underway. ISSN 0106-2840 ISBN 978-87-550-3945-2 Contract no.: 2009-1-10268 Group's own reg. no.: 1130 122-01 Sponsorship: Energinet.dk, under the Public Service Obligation (PSO) scheme Cover : The Lighter-than-Air system of DTU with hangar (left) and some wind turbines in Nøjsomheds Odde. Right: Flyby of a SUMO drone at the Nøjsomheds Odde wind farm in Lolland, Denmark. Picture courtesy of Jesper Hjelme, IWAL. Pages: 90 Tables:6 References: Information Service Department Risø National Laboratory for Sustainable Energy Technical University of Denmark P.O. Box 49 DK-4000 Roskilde Denmark Telephone +45 46774005 bibl@risoe.dtu.dk Fax +45 46774013 www.risoe.dtu.dk
Lifshitz critical point in the cuprate superconductor YBa2Cu3Oy from high-field Hall effect measurements

The Hall coefficient RH of the cuprate superconductor YBa 2Cu3Oy was measured in magnetic fields up to 60 T for a hole concentration p from 0.078 to 0.152 in the underdoped regime. In fields large enough to suppress superconductivity, RH(T) is seen to go from positive at high temperature to negative at low temperature, for p0.08. This change of sign is attributed to the emergence of an electron pocket in the Fermi surface at low temperature. At p<0.08, the normal-state R H(T) remains positive at all temperatures, increasing monotonically as T→0. We attribute the change of behavior across p=0.08 to a Lifshitz transition, namely a change in Fermi-surface topology occurring at a critical concentration pL=0.08, where the electron pocket vanishes. The loss of the high-mobility electron pocket across pL coincides with a tenfold drop in the conductivity at low temperature, revealed in measurements of the electrical resistivity ρ at high fields, showing that the so-called metal-insulator crossover of cuprates is in fact driven by a Lifshitz transition. It also coincides with a jump in the in-plane anisotropy of ρ, showing that without its electron pocket, the Fermi surface must have strong twofold in-plane anisotropy. These findings are consistent with a Fermi-surface reconstruction caused by a unidirectional spin-density wave or stripe order. © 2011 American Physical Society.