Miracle-dz/UniFAR-FTUs huggingface dataset:
The inability of an early post-transplantation intrarenal resistive index to predict renal allograft function at 12 weeks after engraftment in young adults

Background The intrarenal resistive index (RI) is a promising tool for predicting renal graft outcomes. Due to the complexity of graft function and the presence of diverse contributing factors, however, the available data are inconclusive. Purpose To examine the performance of the RI 1 week after transplant in predicting allograft function at week 12, with an emphasis on the type of intrarenal artery used in the examination. Material and Methods A total of 58 first-time living-donor kidney-allograft-transplantation patients aged less than 50 years underwent Doppler ultrasonography (US) of the intrarenal arteries 1 week after engraftment. The RI was calculated for both the segmental (RI-C) and interlobar-arcuate (RI-P) arteries. Serum creatinine level and the creatinine reduction ratio (CRR) were determined at weeks 1 and 12 post transplantation. Results While the RI did not correlate with serum creatinine level and CRR at week 1, significant correlations were present between the RI and serum creatinine level (r = 0.28, P = 0.03 for both RI-C and RI-P) and CRR (r = –0.25, P = 0.05 for both RI-C and RI-P) at week 12. The sensitivity, specificity, positive predictive value, and negative predictive value of using RI-C in predicting abnormal 12-week serum creatinine level were 51.2%, 52.9%, 72.4%, and 31.3%, respectively; and 53.7%, 47.1%, 70.9%, and 29.6% for RI-P, respectively (P > 0.99 for all comparisons). Conclusion Early post-transplantation RI correlates significantly with both serum creatinine level and creatinine reduction ratio 12 weeks after engraftment with intermediate predictive accuracy.
Estimating optimal treatment regimes from a classification perspective

A treatment regime maps observed patient characteristics to a recommended treatment. Recent technological advances have increased the quality, accessibility, and volume of patient‐level data; consequently, there is a growing need for powerful and flexible estimators of an optimal treatment regime that can be used with either observational or randomized clinical trial data. We propose a novel and general framework that transforms the problem of estimating an optimal treatment regime into a classification problem wherein the optimal classifier corresponds to the optimal treatment regime. We show that commonly employed parametric and semi‐parametric regression estimators, as well as recently proposed robust estimators of an optimal treatment regime can be represented as special cases within our framework. Furthermore, our approach allows any classification procedure that can accommodate case weights to be used without modification to estimate an optimal treatment regime. This introduces a wealth of new and powerful learning algorithms for use in estimating treatment regimes. We illustrate our approach using data from a breast cancer clinical trial. Copyright © 2012 John Wiley & Sons, Ltd.
Pre-training of an artificial neural network for software fault prediction

Software fault prediction is one of the significant stages in the software testing process. At this stage, the probability of fault occurrence is predicted based on the documented information of the software systems that are already tested. Using this prior knowledge, developers and testing teams can better manage the testing process. There are many efforts in the field of machine learning to solve this classification problem. We propose to use a pre-training technique for a shallow, i.e. with fewer hidden layers, Artificial Neural Network (ANN). While this method is usually employed to prevent over-fitting in deep ANNs, our results indicate that even in a shallow network, it improves the accuracy by escaping from local minima. We compare the proposed method with four SVM-based classifiers and a regular ANN without pre-training on seven datasets from NASA codes in the PROMISE repository. Results confirm that the pre-training improves accuracy by achieving the best overall ranking of 1.43. Among seven datasets, our method has higher accuracy in four of them, while ANN and support vector machine are the best for two and one datasets, respectively.
The Magellanic Zoo: Mid-Infrared Spitzer Spectroscopy of Evolved Stars and Circumstellar Dust in the Magellanic Clouds

We observed a sample of evolved stars in the Large and Small Magellanic Clouds (LMC and SMC) with the Infrared Spectrograph on the Spitzer Space Telescope. Comparing samples from the SMC, LMC, and the Galaxy reveals that the dust production rate depends on metallicity for oxygen-rich stars, but carbon stars with similar pulsation properties produce similar quantities of dust, regardless of their initial metallicity. Other properties of the oxygen-rich stars also depend on metallicity. As the metallicity decreases, the fraction of naked (i.e., dust-free) stars increases, and among the naked stars, the strength of the 8 μm absorption band from SiO decreases. Our sample includes several massive stars in the LMC with long pulsation periods that produce significant amounts of dust, probably because they are young and relatively metal-rich. Little alumina dust is seen in circumstellar shells in the SMC and LMC, unlike in Galactic samples. Three oxygen-rich sources also show emission from magnesium-rich crystalline silicates. Many also show an emission feature at 14 μm. The one S star in our sample shows a newly detected emission feature centered at 13.5 μm. At lower metallicity, carbon stars with similar amounts of amorphous carbon in their shells have stronger absorption from molecular acetylene (C2H2) and weaker emission from SiC and MgS dust, as discovered in previous studies.
Ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCO): A long‐lived protein in the deep ocean

We demonstrate that the distribution of ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCO) in the deep North Pacific is a unique tracer for the accumulation of biochemically identifiable organic residue of the export flux. RuBisCO is found both dissolved and assembled in microgels in a dynamic gel‐to‐dissolved‐to‐gel continuum that may protect RuBisCO from degradation in the water column. High concentrations are located below biologically productive equatorial and subarctic systems, and low concentrations are associated with the subtropical gyre. RuBisCO tracks the advective transport of export products along deep circulation pathways of the ocean interior, serving as a quantifiable biochemical tracer of modern organic carbon exported to and resident in the deep ocean.
Evidence and characteristics of a diverse and metabolically active microbial community in deep subsurface clay borehole water.

The Boom Clay in Belgium is investigated in the context of geological nuclear waste disposal, making use of the High Activity Disposal Experimental Site (HADES) underground research facility. This facility, located in the Boom Clay at a depth of 225 m below the surface, offers a unique access to a microbial community in an environment, of which all geological and geochemical characteristics are being thoroughly studied. This study presents the first elaborate description of a microbial community in water samples retrieved from a Boom Clay piezometer (borehole water). Using an integrated approach of microscopy, metagenomics, activity screening and cultivation, the presence and activity of this community are disclosed. Despite the presumed low-energy environment, microscopy and molecular analyses show a large bacterial diversity and richness, tending to correlate positively with the organic matter content of the environment. Among 10 borehole water samples, a core bacterial community comprising seven bacterial phyla is defined, including both aerobic and anaerobic genera with a range of metabolic preferences. In addition, a corresponding large fraction of this community is found cultivable and active. In conclusion, this study shows the possibility of a microbial community of relative complexity to persist in subsurface Boom Clay borehole water.
Historical Institutionalism in Contemporary Political Science

Al igual que el personaje en la obra de Moliere que habló en prosa durante toda su vida sin saberlo, los cientistas políticos contemporáneos están familiarizados con los ejemplos clásicos de la investigación del institucionalismo histórico sin por ello ser conscientes de que ejemplifican un género coherente, que cuenta con elementos que funcionan en forma similar al de los otros dos grandes enfoques de investigación de la ciencia política contemporánea, el conductismo basado en encuestas y los modelos de la elección racional. Los institucionalistas históricos analizan las configuraciones organizacionales mientras otros observan escenarios particulares aislados; ponen atención en coyunturas críticas y procesos de largo plazo, mientras que otros solamente consideran porciones de tiempo o maniobras de corto plazo. De este modo, al aproximarse a cuestiones importantes, los institucionalistas históricos hacen visibles y comprensibles contextos más amplios y procesos que interactúan, dan forma y reforman los estados, la política y el diseño de la política pública. El trabajo de Stephen Skowronek, The Politics Presidents Make (1997), por ejemplo, revela ciclos recurrentes en la naturaleza y éxito del liderazgo presidencial a través de la historia de los Estados Unidos. Otro estudio de largo plazo en la política americana, Gaining Access: Congress and the Farm Lobby, 1919-1981 (1991), de John Mark Hansen, desarrolla un modelo de interacción entre grupos de interés y el gobierno con el objetivo de explicar la emergencia, persistencia y eclipse final de la influencia nacional de las asociaciones rurales nacionales. Atravesando naciones y períodos de tiempo, Peter A. Hall, en su libro de 1986, Governing the Economy: The Politics of State Intervention in Britain and France, explica como las instituciones y organizaciones se intersectan para dar forma no sólo a las políticas gubernamentales sino también a las estrategias y alianzas de los grupos de interés e intelectuales. Yendo aun más lejos, Shaping the Political Arena: Critical Junctures, the Labor Movement, and Regime Dynamics in Latin America, escrito por Ruth Berins Collier y David Collier (1991) y Birth of the Leviathan: Building States and Regimes in Early Modern Europe, por Thomas Ertman (1997), explican las dinámicas de los regímenes y la variedad de formaciones de los estados nacionales modernos.
Control Cloud Data Access Privilege and Anonymity With Fully Anonymous Attribute-Based Encryption

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the AnonyControl-F, which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.
Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett’s Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.
The usage of neural networks and time series in pattern recognition and forecasting of power consumption profiles

Most of the power quality disturbances such as unbalances, sags, swells and harmonic distortion are ultimately related to power consumption variations. In this manner, with the aim of identifying electrical problems causing PQ disturbances, a suitable knowledge of these power consumption profiles is required. These profiles can be obtained by either a continuous monitoring or by using some tools capable of representing the behavior of the power demand. This paper presents a comparison between two analytical tools, one is an artificial intelligence approach by means of neural networks, and the other one uses statistical techniques such as time series analysis. These techniques not only can represent power consumption profiles, but also may predict them allowing the customer to make a suitable planning of the electrical facilities.
An MRI/CT-based cardiac electroanatomical mapping system with scattered data interpolation algorithm

In this paper we are proposing an MRI/CT-guided cardiac electroanatomical mapping system, EpreMap. EpreMap was developed as an extension to the guidance system developed at King's College London for cardiac electrophysiology procedures. This platform allows for both the registration of MRI/CT anatomical data to X-ray fluoroscopy and the determination of the catheter positions. EpreMap is a contact mapping system. By using a radial basis function (RBF) based scattered data interpolation algorithm, EpreMap can create a cardiac activation map for a whole chamber starting from five sampling points. The activation map is updated with every new measurement. Offline studies showed that cardiac activation maps created by using EpreMap were highly correlated with the maps created by using a non-contact mapping system. EpreMap was used in three clinical cases. The clinical studies proved the workflow of EpreMap was valid in the clinical environment. For one clinical case, the result of EpreMap was validated against a non-contact mapping system. Clinically significant regions identified by using the two mapping systems were strongly correlated.
Impact of the plant rhizosphere and augmentation on remediation of polychlorinated biphenyl contaminated soil

This study investigated the interactive effects of bioaugmentation, biostimulation, and the rhizosphere during remediation of Aroclor 1242‐contaminated soil. Treatments were repeatedly augmented with polychlorinated bipheny (PCB)‐degrading bacteria, inducers (carvone and salicylic acid), surfactant (sorbitan trioleate), minimal salts medium in a 20‐cm high soil column, or a combination of these elements. Soils containing a single Brassica nigra plant achieved 61% PCB removal in the 0 to 2 and 2 to 6 cm depths after 9 weeks of bioaugmentation, whereas only 43 and 14% PCB removal, respectively, was achieved in unplanted controls. Gas diffusion coefficients of 13.0 and 5.0 × 10−7 m2 s−1 were calculated from a methane diffusion assay for planted and unplanted soils respectively, indicating the positive effect of plant roots on gas diffusion into the soil. A second, modified column study removed 87, 73, 63, and 45% of PCB after 12 weeks in the 0 to 5, 5 to 11, 11 to 26, and 26 to 35 cm depths, respectively, in planted‐bioaugmented soils, whereas 65, 54, 53, and 47% of PCB was removed from the planted‐minimal salts treatment, respectively. Shifts in the soil microbial community structure were demonstrated by denaturing gradient gel electrophoresis of bacterial 16S ribosomal DNA. Results support that Brassica nigra directly contributed to accelerated PCB removal by increased oxygen diffusion, amendment infiltration, and microbial enrichment.
Optimization of grasping an object by using required acceleration and equilibrium-force sets

In this paper, we search optimal grasp points and configurations of fingers for not only resisting an external force applied to a grasped object but also generating a desirable acceleration of the object. Based on the concept of required external force set, we define required acceleration and equilibrium-force sets. By using the sets, we formulate an optimization problem from the viewpoint of decreasing the magnitudes of the joint torques required to generate the required acceleration and equilibrium-force. We also show that we can solve the problem by using a branch-and-bound method. The validity of our approach is shown by numerical examples.
Comparison of molecular typing methods for Candida albicans

Four molecular approaches to determining the types of Candida albicans strains were compared. The strains used were those whose repeated DNA (ribosomal and mitochondrial) EcoRI restriction fragment length polymorphisms (RFLP) were determined by Stevens et al. (D. A. Stevens, F. C. Odds, and S. Scherer, Rev. Infect. Dis. 12:258-266, 1990). Scherer and Stevens (S. Scherer and D. A. Stevens, Proc. Natl. Acad. Sci. USA 85:1452-1456, 1988) used the same strains to examine the Southern blots of genomic EcoRI digests probed with the repeated sequence 27A. The results of these investigators were compared with determinations of RFLPs generated from repeated DNA by the enzyme HinfI and examination of the karyotypes of strains under two sets of conditions, one for the smaller chromosomes and one for the larger ones. Analysis of RFLPs of repeated DNA is most convenient but shows the lowest degree of resolution. Use of the repeated sequence and use of karyotype have very high resolution, but the former method is more convenient than the latter. HinfI digestion is more sensitive than EcoRI digestion but equally convenient. By using all four methods, separate types were identified for 18 of the 20 strains examined.
A daily salt balance model for stream salinity generation processes following partial clearing from forest to pasture

Abstract. We developed a coupled salt and water balance model to represent the stream salinity generation process following land use changes. The conceptual model consists of three main components with five stores: (i) Dry, Wet and Subsurface Stores, (ii) a saturated Groundwater Store and (iii) a transient Stream zone Store. The Dry and Wet Stores represent the salt and water movement in the unsaturated zone and also the near-stream dynamic saturated areas, responsible for the generation of salt flux associated with surface runoff and interflow. The unsaturated Subsurface Store represents the salt bulge and the salt fluxes. The Groundwater Store comes into play when the groundwater level is at or above the stream invert and quantifies the salt fluxes to the Stream zone Store. In the stream zone module, we consider a "free mixing" between the salt brought about by surface runoff, interflow and groundwater flow. Salt accumulation on the surface due to evaporation and its flushing by initial winter flow is also incorporated in the Stream zone Store. The salt balance model was calibrated sequentially following successful application of the water balance model. Initial salt stores were estimated from measured salt profile data. We incorporated two lumped parameters to represent the complex chemical processes like diffusion-dilution-dispersion and salt fluxes due to preferential flow. The model has performed very well in simulating stream salinity generation processes observed at Ernies and Lemon experimental catchments in south west of Western Australia. The simulated and observed stream salinity and salt loads compare very well throughout the study period with NSE of 0.7 and 0.4 for Ernies and Lemon catchment respectively. The model slightly over predicted annual stream salt load by 6.2% and 6.8%.
Functional manipulation of bit streams

SUMMARY Writing code that manipulates bit streams is a painful and error-prone programming task. Currently, it is often performed via bit twiddling techniques based on using explicit bit shifts and bit masks in buffers explicitly allocated and managed by the programmer. Still, this kind of programming is commonplace in many applications ranging from decoding streaming media files to implementing network protocols. In this article we show how high-level constructs from functional programming, such as pattern matching and comprehensions, can make bit stream manipulation more succinct, less error-prone, and totally memory-safe. We formally define these language constructs and show a variety of example uses from several different application areas. We also describe how these constructs have been implemented efficiently in the functional programming language Erlang. The resulting performance is superior to that of other (purely) functional languages and competitive to that of low-level, unsafe languages such as C.
Temporally controlled targeted somatic mutagenesis in embryonic surface ectoderm and fetal epidermal keratinocytes unveils two distinct developmental functions of BRG1 in limb morphogenesis and skin barrier formation

Animal SWI2/SNF2 protein complexes containing either the brahma (BRM) or brahma-related gene 1 (BRG1) ATPase are involved in nucleosome remodelling and may control the accessibility of sequence-specific transcription factors to DNA. In vitro studies have indicated that BRM and BRG1 could regulate the expression of distinct sets of genes. However, as mice lacking BRM are viable and fertile, BRG1 might efficiently compensate for BRM loss. By contrast, as Brg1-null fibroblasts are viable but Brg1-null embryos die during the peri-implantation stage, BRG1 might exert cell-specific functions. To further investigate the in vivo role of BRG1, we selectively ablated Brg1 in keratinocytes of the forming mouse epidermis. We show that BRG1 is selectively required for epithelial-mesenchymal interactions in limb patterning, and during keratinocyte terminal differentiation, in which BRM can partially substitute for BRG1. By contrast, neither BRM nor BRG1 are essential for the proliferation and early differentiation of keratinocytes, which may require other ATP-dependent nucleosome-remodelling complexes. Finally, we demonstrate that cell-specific targeted somatic mutations can be created at various times during the development of mouse embryos cell-specifically expressing the tamoxifen-activatable Cre-ERT2 recombinase.