Miracle-dz/UniFAR-FTUs huggingface dataset:
Influencia de la contaminación química y fecal sobre la estructura de las comunidades bacterianas del río Almendares, La Habana, Cuba

Las comunidades bacterianas desempenan un papel fundamental en los ecosistemas acuaticos, contribuyendo a la mineralizacion de la materia organica. En el presente trabajo se estudiaron tres estaciones de muestreo del rio Almendares (Rio Cristal, Paila y Puente de Hierro), con el objetivo de analizar la variabilidad espacio-temporal de las comunidades bacterianas y correlacionar la estructura de la comunidad del bacterioplancton con parametros fisico-quimicos y microbiologicos. Se realizaron muestreos durante los meses de Octubre, Febrero y Abril del 2011-2012 y se determinaron las variables temperatura, pH, concentraciones de nutrientes inorganicos (NO 2 , NO 3 , NH 4 y PO 4 ), Demanda Quimica de Oxigeno (DQO), oxigeno disuelto, solidos totales disueltos, concentraciones de coliformes termotolerantes, E. coli y enterococos. Mediante la electroforesis en gel con gradiente desnaturalizante se observaron diferencias en la estructura de la comunidad bacteriana de la estacion Paila con respecto a las estaciones Rio Cristal y Puente de Hierro. La variabilidad temporal de las comunidades bacterianas solo se observo en las estaciones Rio Cristal y Puente de Hierro donde las muestras de Octubre fueron diferentes a las de Febrero-Abril. Los resultados obtenidos a traves del analisis de correspondencia canonica mostraron que existe una relacion significativa entre las variables temperatura, pH, NO 3 , NH 4 , DQO, coliformes termotolerantes y enterococos y la estructura de las comunidades bacterianas. Estos parametros fisicoquimicos e indicadores de contaminacion fecal explicaron el 93.1% de la varianza total de la diversidad de las muestras del rio Almendares, indicando la influencia de las altas concentraciones de nutrientes y contaminantes microbiologicos en la estructura de las comunidades bacterianas.
Birefringence and tilt angle in the antiferroelectric, ferroelectric, and intermediate phases of chiral smectic liquid crystals

Using a high resolution optical polarimeter, we have measured the temperature dependence of the birefringence and optical rotation in chiral smectic liquid crystals that exhibit antiferroelectric, ferroelectric, and intermediate phases. The temperature dependence of the magnitude of the tilt angle was determined from the birefringence of 4-~1-methyl-heptyloxycarbonyl-phenyl! 48-octylbiphenyl-4-carboxylate ~MHPOBC! and of 4-~1-methylheptyloxycarbonyl-phenyl! 48-octylcarbonyloxybiphenyl-4-carboxylate ~MHPOCBC! Both substances exhibit a crossover of the order parameter exponent from the classical value of b50.5 close to the transition to the tricritical value b50.25 far away. This stresses the importance of the sixth order terms in the Landau free-energy expansion for ferroelectric and antiferroelectric liquid crystals. In addition, a discontinuous behavior in the magnitude of the tilt is observed when crossing the smectic- Ca ‐ smectic-C* or smectic-C* ‐ smectic-C A transitions, whereas the smectic- A ‐ smectic-C a transition is continuous. The simultaneously determined optical rotation is used to elucidate the structures and the nature of phase transitions. The results are well explained within the framework of a discrete phenomenological model with nearest and next nearest neighbor interactions between the smectic layers. @S1063-651X~98! 01607-9#
The sizes, shapes, and mineralogy of asbestos structures that induce lung tumors or mesothelioma in AF/HAN rats following inhalation.

Data from inhalation studies in which AF/HAN rats were exposed to nine different types of asbestos dusts (in 13 separate experiments) are employed in a statistical analysis to determine if a measure of asbestos exposure (expressed as concentrations of structures with defined sizes, shapes and mineralogy) can be identified that satisfactorily predicts the observed lung tumor or mesothelioma incidence in the experiments. Due to limitations in the characterization of asbestos structures in the original studies, new exposure measures were developed from samples of the original dusts that were re-generated and analyzed by transmission electron microscopy using a direct transfer technique. This analysis provided detailed information on the mineralogy (i.e., chrysotile, amosite, crocidolite or tremolite), type (i.e., fiber, bundle, cluster, or matrix), size (length and width) and complexity (i.e., number of identifiable components of a cluster or matrix) of each individual structure. No univariate measure of exposure was found to provide an adequate description of the lung tumor responses observed among the inhalation studies, although the measure most highly correlated with tumor incidence is the concentration of structures > or = 20 microns in length. Multivariate measures of exposure were identified that do adequately describe the lung tumor responses. Structures contributing to lung tumor risk appear to be long (> or = 5 microns) thin (0.4 microns) fibers and bundles, with a possible contribution by long and very thick (> or = 5 microns) complex clusters and matrices. Potency appears to increase with increasing length, with structures longer than 40 microns being about 500 times more potent than structures between 5 and 40 microns in length. Structures < 5 microns in length do not appear to make any contribution to lung tumor risk. This analysis did not find a difference in the potency of chrysotile and amphibole toward the induction of lung tumors. However, mineralogy appears to be important in the induction of mesothelioma with chrysotile being less potent than amphibole.
A Feature Selection Algorithm Based on Poisson Estimates

Feature selection is one of the key technologies for text categorization. Currently, it mainly includes technologies based statistics which is primarily from information theory and technologies based semantics which covers natural language processing, semantic web etc. Based on Poisson Hypothesis, this article presents a new method combining both and tries to find features in documents with more semantic information. The contrast experiments carried on the Reuters-21578 corpus with the IG, Chi2 and WN algorithms show that this method has more advantages than other algorithms.
SMIS Members: A Membership Analysis

This article discusses the results of a survey of SMIS members. Members were asked to respond to questions regarding demographics, their satisfaction with SMIS services, and the importance of eighteen management issues which MIS management might address. The article presents percentage results of individual questions and interprets the results of those questions. No attempt is made to use any bivariate statistics in this article. All questions asked on the survey are presented in this article.
Transaortic Transcatheter Aortic Valve Implantation as a second choice over the Transapical access

Background and Aims: In this report, we present our experience with the transaortic transcatheter aortic valve implantation using the SAPIEN valve. The procedural success, 30-day outcome, and survival up to 2 years are compared with the transapical access performed in patients in our institution. Material and Methods: Of a total of 282 transcatheter aortic valve implantation patients, 100 consecutive patients had a non-transfemoral approach. The transaortic and transapical access routes were used in 36 and 64 patients, respectively. The transaortic group had a higher mean logistic EuroSCORE (32.6 vs 25.2, p = 0.021) and more patients with left ventricular ejection fraction less than 40% (33.3% vs 14.1%, p = 0.023). Results: The respective technical success rates for the transaortic and transapical groups were 100% and 95.2% (p = NS). There were significantly more perioperative hemodynamic problems necessitating cardiopulmonary resuscitation or mechanical circulatory support in the transapical group (18.8% vs 2.8%, p = 0.023). The transaortic group had a slightly shorter hospital stay (7 vs 8 days, p = 0.018). The 30-day mortality was 8.6% and 10.9% in the transaortic and transapical group, respectively (p = NS). Combined safety outcome was similar in both groups at 30 days. The respective 1-year survival rates for the transaortic and transapical groups were 71.5% and 68.3%, respectively (p = NS). Conclusion: The trans transcatheter aortic valve implantation is a considerable choice to transapical approach. Despite a higher risk patient cohort, the clinical outcome is at least comparable to the transapical transcatheter aortic valve implantation, and it can be utilized as a second choice for patients with prohibitive iliac-femoral anatomy for transfemoral access.
A modified modular eigenspace approach to face recognition

We describe a method for face recognition based on the eigenimage technique that allows images to be represented by a limited set of parameters and be compared according to simple similarity criteria for classification or retrieval purposes. Our method is not applied to the whole image of the face, but to sub-images representing the most salient face components (eyes, nose, mouth). The method is able to recognise with good precision faces having different head postures on the image plane, because faces are straightened through a rotation transform. Moreover the paper reports results we have achieved with such a method on two publicly-available reference sets of images.
Aneuploidy in the Human Cleavage Stage Embryo

The cleavage stage embryo (days 1–3) stands out due to the high level of chromosomal anomalies, especially mosaicism that arises prior to global embryonic genome activation. Molecular cytogenetic studies show that an average of 60% of in vitro derived embryos have at least one aneuploid cell by the time they are 3 days old. However, comprehensive studies of the chromosome content of individual cells have revealed that 25% of these embryos have no aneuploid cells, a fact that sits well with the knowledge that at most 1 in 5 have the capacity to implant. The evidence is that extensive mosaicism, affecting several chromosomes, interferes with development to a greater extent than does uniform aneuploidy. Follow-up studies on embryos after pre-implantation genetic aneuploidy screening indicate that the frequency of meiotic errors varies according to the referral reason, with the highest frequency being recorded for the recurrent miscarriage category and the lowest in the repeated implantation failure group where younger women have a good response to ovarian stimulation. The exceptionally high incidence of pre- and post-zygotic chromosomal anomalies seen in early human embryos is thus the product of several mechanisms. Firstly, the error-prone cell cycle during the embryonic cleavage stage and secondly, parental susceptibility to meiotic and mitotic chromosomal instability together with their general genetic background.
Joint Capped Norms Minimization for Robust Matrix Recovery

The low-rank matrix recovery is an important machine learning research topic with various scientific applications. Most existing low-rank matrix recovery methods relax the rank minimization problem via the trace norm minimization. However, such a relaxation makes the solution seriously deviate from the original one. Meanwhile, most matrix recovery methods minimize the squared prediction errors on the observed entries, which is sensitive to outliers. In this paper, we propose a new robust matrix recovery model to address the above two challenges. The joint capped trace norm and capped `1-norm are used to tightly approximate the rank minimization and enhance the robustness to outliers. The evaluation experiments are performed on both synthetic data and real world applications in collaborative filtering and social network link prediction. All empirical results show our new method outperforms the existing matrix recovery methods.
Distribution of nitrifying activity in the Seine River (France) from Paris to the estuary

The distribution of nitrification has been measured with the H14CO3− incorporation method in the Seine River and its estuary during summer conditions. The Seine River below Paris receives large amounts of ammonium through wastewater discharge. In the river itself, this ammonium is only slowly nitrified, while in the estuary nitrification is rapid and complete. We show that this contrasting behavior is related to the different hydrosedimentary conditions of the two systems, as nitrifying bacteria are associated with suspended particles. In the river, particles and their attached bacteria either rapidly settle or have a sestonic behavior. Because of the short residence times of the water masses, the slow growing nitrifying population has no time to develop sufficiently to nitrify the available ammonium. The estuary is characterized by strong tidal dynamics. Particles settle and are resuspended continuously with the strong current inversions of ebb and flood. As a result of these dynamics, particles and their attached nitrifying bacteria experience longer residence times in a temporary suspended state than the water masses themselves, providing to slow growing nitrifying bacteria the opportunity to develop a large population capable of nitrifying all the available ammonium.
Research on the genetic regression model of Earth-rock dam safety monitoring and its application

In this paper, the factors which influence the piezometric level of Earth-rock dams are combined randomly by using a genetic algorithm to do selective preference. A new genetic regression model is established based on considering the comprehensive influence of fitting and prediction accuracy in fitness function. Through analyzing the seepage monitoring data of Dong Wu Shi Reservoir, it is shown that the prediction accuracy of this method is better than that of the general statistical regression.
Modeling subjective health outcomes: top 10 reasons to use Thurstone's method.

of Medical Care, Krabbe 1 provides us with a much needed discussion of the potential usefulness of Thurstone’s approach for quantifying subjective health outcomes using ordinal information, such as rankings. As pointed out eloquently by Krabbe, Thurstone’s articles, 2,3 have had a tremendous influence on the development of methods for collecting and analyzing evaluative judgments in the form of preferences, attitudes, or more specifically, health outcomes. In fact, it is our view that Krabbe’s discussion is rather modest. We feel more exuberant and present a list of top-10 reasons for using Thurstonian models. Although presented separately, these reasons should be viewed in conjunction because in this way they demonstrate the power and generality of this approach for studying and understanding evaluative judgments. For many years, it was not possible to apply Thurstone’s model in its full generality because of computational limitations. In technical terms, given rankings of p health outcomes p-1 dimensional integration over a normal distribution is needed if the model is to be estimated by maximum likelihood. Before the computer revolution, this integration was unfeasible and when Thurstone proposed his model more than 80 years ago only univariate integration could be done. Having been trained as an engineer, Thurstone 2 proposed an effective 2-stage estimation procedure that has been the skeleton upon which most classic research on Thurstonian models have been built. 4 Krabbe discusses this method very nicely. Given the proportions by which one health outcome is preferred over another (the P matrix in Krabbe’s article), one obtains the corresponding normal deviates (Z values) by univariate integration. Then, the parameters of the model are obtained from the Z values by minimum distance methods. If only univariate integration is to be performed, only highly restrictive versions of Thurstone’s general model can be estimated (such as the so-called Case V model considered by Krabbe). Fortunately, these computational limitations are now overcome and Thurstone’s model can be estimated in its full generality. As a result, the applicability of this approach has widened tremendously as our list of top-10 reasons illustrates. To put it bluntly, we are comparing a 1930s model car to the latest model when we look at Thurstone’s classic Case V representation with its unrestricted counterpart. Still, the basic advantages of Thurstone’s models should not be dismissed as illustrated by Krabbe, and our list of reasons highlights a number of them before we discuss the current capabilities of a Thurstonian
Combination of spectral unmixing algorithms for the fusion of the hyperspectral and multispectral data with unknown spectral response function

In this paper Least Square-Non Negative Matrix Factorization Spectral Unmixing Combination (LS-NNMF-SUC) is presented for the fusion of hyperspectral (HS) and multispectral (MS) data. The observed HS and MS images are respectively the spatial and the spectral degradations according to the sensor characteristics of the High spatial-resolution HS (HHS) image, which is reconstructed based on the high spectral information of Low spatial resolution HS (LHS) image represented by endmembers and high spatial information of High spatial-resolution MS (HMS) image represented by abundances. In this work, the proposed algorithm deals with practical remote sensing situation, where the spectral relationship between the observed HMS image and the estimated HHS image is unknown. As a result, a Spectral Unmixing Combination (SUC) diagram based on Least square (LS) and Non-negative Matrix Factorization (NNMF) Spectral Unmixing is developed, in which the one loop NNMF and LS Spectral Unmixing is performed on the MS and HS images sequentially. The spatial spread transform matrix of the sensor observation model is used to produce the matched abundances of the LHS image, in order to unmix the later. Simulation results performed on HYDICE and AVIRIS data demonstrate the efficiency of the proposed fusion algorithm.
A case study in the use of defect classification in inspections

In many software organizations, defects are classified very simply, using categories such as Minor, Major, Severe, Critical. Simple classifications of this kind are typically used to assign priorities in repairing defects. Deeper understanding of the effectiveness of software development methodologies and techniques requires more detailed classification of defects. A variety of classifications has been proposed.Although most detailied schemes have been developed for the purpose of analyzing software processes, defect classification schemes have the potential for more specific uses. These uses require the classification scheme to be tailored to provide relevant details. In this vein, a new scheme was developed to evaluate and compare the effectiveness of software inspection techniques. This paper describes this scheme and its use as a metric in two empirical studies. Its use was considered successful, but issues of validity and repeatability are discussed.
Sampling Techniques & Determination of Sample Size in Applied Statistics Research : an Overview

Applied statistics research plays pivotal role in diverse problems of social sciences, agricultural sciences, health sciences, and business research. Many investigations are conducted by survey research. The technique of sampling and determination of sample size have crucial role in survey-based research problems in applied statistics. Specific sampling techniques are used for specific research problems because one technique may not be appropriate for all problems. Similarly, if the sample size is inappropriate it may lead to erroneous conclusions. The present paper gives an overview of some commonly used terms and techniques such as sample, random sampling, stratified random sampling, power of the test, confidence interval that need to be specified for a sample size calculation and some techniques for determination of sample size, and also describes some sampling methods such as purposive random sampling, random sampling, stratified random sampling, systematic random sampling and quota sampling for specific research purposes.
Analysis and implementation of low-power perceptual multiband noise reduction for the hearing aids application

Traditional noise reduction designs provide good performance but suffer from high complexity and long latency, which limits their application to hearing aids. Targeted for strict low-power and low-latency requirement of completely-in-the-canal type hearing aids, this study analyses and implements a previously proposed sample-based perceptual multiband spectral subtraction with a multiplication-based entropy voice activity detection. Simulation results reveal that the authors design can provide similar speech quality as others, but with lower computational complexity and simple control effort. The corresponding core-based architecture design further exploits processing characteristics of the proposed approach to reduce power consumption with a sign-magnitude and a preprocessed input data reuse scheme. Chip measurement shows that the design only consumes 83.7 µW at 0.6 V operation with 90 nm high threshold voltage (HVT) (high VT ) standard cell library.
Dynamic Bandplanning for Vectored DSL

There are two types of crosstalk in digital subscriber line (DSL) systems, namely near-end crosstalk (NEXT) and far-end crosstalk (FEXT). NEXT is usually much stronger than FEXT. Therefore, high-speed DSL systems transmit in preplanned disjoint downstream (DS) and upstream (US) frequency bands to avoid NEXT. Although easy for implementation, such a fixed bandplan can lead to inefficient bandwidth usage, depending on the DS and US bit rate requirements and the loop topology, particularly in so-called vectored DSL systems, which include signal coordination for FEXT cancellation. In dynamic bandplanning (DBP), each frequency band is allocated to either DS, US, or to both directions depending on the aforementioned parameters. In this paper, we consider optimal DBP for vectored DSL with linear as well as with nonlinear transmitter/receiver structures. We propose an optimal DBP algorithm for systems with disjoint DS and US bands. For systems with overlapping bands, the problem of finding the optimal transmitter/receiver filters is nonconvex and we propose two iterative algorithms based on recent optimum spectrum balancing schemes from the literature. We also study the effect of echo and US NEXT cancellation on the system performance. Finally, simulation results are provided to demonstrate that our algorithms can indeed significantly increase the achievable bit rates.
Orthonormal Diversity-Multiplexing Precoding in MIMO Systems at Finite SNR

A novel and flexible means of symbol rate adaptation for MIMO systems is presented and analyzed. Constellations of L Grassmannian subspaces are used to precede a length-M symbol vector, resulting in a symbol rate of M/L. The result is a practical and versatile method of trading between diversity and multiplexing gains at operational signal-to-noise ratios.