Miracle-dz/UniFAR-FTUs huggingface dataset:
Retroperitoneal metastases in testicular cancer: role of CT measurements of residual masses in decision making for resection after chemotherapy.

PURPOSE To determine the relative importance of computed tomographic (CT) measurements for the prediction of histologic findings in residual masses in patients with nonseminomatous testicular cancer. MATERIALS AND METHODS Measurements of the maximum transverse size of retroperitoneal metastases before and after chemotherapy were available in 641 patients who underwent resection after chemotherapy while their levels of tumor markers were normal. Radiologic measurements of mass size and clinical characteristics (histologic findings in primary tumor and levels of alpha-fetoprotein, human chorionic gonadotropin, and lactate dehydrogenase before chemotherapy) were related to histologic findings in the residual mass with logistic regression analysis. RESULTS At resection, 302 patients had benign tissue, and 339 had residual tumor (mature teratomas or cancer). Tumor was more frequent in larger masses after chemotherapy but was unrelated to mass size before chemotherapy. Inclusion of the reduction in size significantly improved the logistic regression model, which included mass size after chemotherapy. This model was further improved with the addition of clinical characteristics. Areas under the receiver operating characteristic curves increased from 0.74 to 0.77 and 0.83 with these models. CONCLUSION A small retroperitoneal mass after chemotherapy is an important predictor of benign histologic findings in residual masses in patients with nonseminomatous testicular cancer. However, better predictions can be made when the reduction in size and clinical characteristics are considered as well. Decisions regarding resection should be based on the combination of these characteristics rather than on only mass size after chemotherapy.
Statistical determination of endotoxin content in influenza virus vaccine by the limulus amoebocyte lysate test

To determine laboratory-to-laboratory variability of the limulus amoebocyte lysate (LAL) test for evaluating endotoxin content in influenza virus vaccine, a collaborative study was designed. Participants were six influenza virus vaccine manufacturers and the Bureau of Biologics (BoB). Lysate lot 116, Reference Influenza Virus Vaccine for Endotoxin Assay E-1, and four test vaccines having different ratios of LAL activity relative to reference E-1 were supplied by the BoB. Each laboratory used its normal test procedure. All vaccines were coded. One pair (reference and test) of vaccines per day was tested for 4 days a week over a 4-week period. All data were analyzed at the BoB. The degree of variability experienced by testing laboratories was estimated by the study. This estimate did not conflict with experience gained from previous routine testing in any of the participating laboratories. A statistical approach to the evaluation of LAL data from testing influenza virus vaccine for endotoxin content was developed based upon the overall variation obtained from the collaborative study.
Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges

Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large‐scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., <300 nm). In preparation for anticipated future hyperspectral satellite missions, we take the first step here of exploring global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption‐based indices that indicate CDOM composition to determine the ability of satellite‐derived slope to inform the analysis and modeling of large‐scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.
RTP Payload Format for H.264 Reduced-Complexity Decoding Operation (RCDO) Video

This memo describes an RTP Payload format for the Reduced-Complexity Decoding Operation (RCDO) for H.264 Baseline profile bitstreams, as specified in H.241. RCDO reduces the decoding cost and resource consumption of the video processing. The RTP Payload format is based on the description in RFC 3984.
Free anterolateral thigh flaps for upper extremity soft tissue reconstruction

Introduction: Limb-threatening wounds of the upper extremity pose a challenge to the micro vascular surgeon. The aim of this study is to analyze the outcome of free anterolateral thigh flaps for upper extremity soft tissue reconstruction. Methods: A retrospective review of patients undergoing this procedure from 2005 to 2012 was performed. Case note analysis was performed to determine demographic and perioperative factors, and complications and outcomes. Results: Thirty-two patients with a mean age of 53 years (9–84 yrs) underwent upper extremity reconstruction with an anterolateral thigh (ALT) flap. There were 24 (75%) males and 8 (25%) females. The etiology of the soft tissue defects was: infection (44.6%); post-tumor ablation (40%); and trauma (15.6%). The defect site was most commonly in the forearm (53.1%), followed by the elbow (12.5 %), arm (12.5%) and hand (21.9%). The mean timing of free flap transfer was 6.8 days after admission to our institution (minimum 1 days, maximum 9 days). Mean operative time of surgery was 4 h 39 min (minimum 3 h 2 min, maximum 6 h 20 min). The mean hospitalization was 24.8 days (minimum 5, maximum 85). The ALT success rate was at 92.3%. Partial flap necrosis was documented in five cases (15.6%). Complete flap loss occurred in two post-traumatic cases who both lost their limbs. Discussion: This flap, in the hands of experienced surgeons, provides reliable coverage of upper extremity defects.
Usage Guided Clustering of Web Pages with the Median Self Organizing Map

Web Usage Mining aims at improving Web sites thanks to the analysis of the behavior of their users. This paper proposes to cluster web pages of aw eb site thanks to usage data. In big web sites, clustering individual pages is not possible, therefore the proposed method is based on a prior clustering of pages that uses semantic information about the site, such as its organization on the server. Then usage based dissimilarities between prior clusters is defined and an adaptation of the Self Organization Map to such data is used to provide visualization and clustering of groups of pages of the site. The method is illustrated on the web site of INRIA.
Weighted Couple Sparse Representation With Classified Regularization for Impulse Noise Removal

Many impulse noise (IN) reduction methods suffer from two obstacles, the improper noise detectors and imperfect filters they used. To address such issue, in this paper, a weighted couple sparse representation model is presented to remove IN. In the proposed model, the complicated relationships between the reconstructed and the noisy images are exploited to make the coding coefficients more appropriate to recover the noise-free image. Moreover, the image pixels are classified into clear, slightly corrupted, and heavily corrupted ones. Different data-fidelity regularizations are then accordingly applied to different pixels to further improve the denoising performance. In our proposed method, the dictionary is directly trained on the noisy raw data by addressing a weighted rank-one minimization problem, which can capture more features of the original data. Experimental results demonstrate that the proposed method is superior to several state-of-the-art denoising methods.
Visual analysis and exploration of fluid flow in a cooling jacket

We present a visual analysis and exploration of fluid flow through a cooling jacket. Engineers invest a large amount of time and serious effort to optimize the flow through this engine component because of its important role in transferring heat away from the engine block. In this study we examine the design goals that engineers apply in order to construct an ideal-as-possible cooling jacket geometry and use a broad range of visualization tools in order to analyze, explore, and present the results. We systematically employ direct, geometric, and texture-based flow visualization techniques as well as automatic feature extraction and interactive feature-based methodology. And we discuss the relative advantages and disadvantages of these approaches as well as the challenges, both technical and perceptual with this application. The result is a feature-rich state-of-the-art flow visualization analysis applied to an important and complex data set from real-world computational fluid dynamics simulations.
A high-throughput low-latency arithmetic encoder design for HDTV

In this paper, we propose a high-throughput low-latency arithmetic encoder (AE) design suitable for high definition (HD) real-time applications employing advanced video coding standards such as H.264/AVC or AVS and using a macroblock (MB) level pipeline. First, in order to derive the performance requirement on the AE, a buffer model in connected with which it is designed is thoroughly analyzed. Then, using joint algorithm-architecture optimization and multi-bin processing techniques, we introduce a novel binary arithmetic coder (BAC) architecture with throughput of 2~4 bins per cycle sufficient for real-time encoding. Furthermore, a hybrid context memory scheme is presented to meet the throughput requirement on the BAC. Simulation result shows that our design can support 1080p at 60 fps for AVS HDTV real-time coding with a bin rate up to 107K per MB line. Synthesized with the TSMC 0. 13μm technology, the AE can run at 200MHz and costs 47.3K gates. By operating at 130MHz, the design is also verified in an AVS HD encoder on a Xilinx Virtex-6 FPGA prototype board for 1080p at 30 fps.
Role of the Basal Ganglia in Balance Control

In this review paper, we summarize the important contributions of the basal ganglia to the regulation of postural control. After a brief overview of basal ganglia circuitries, the emphasis is on clinical observations in patients with focal lesions in parts of the basal ganglia, as the impairments seen here can serve to highlight the normal functions of the basal ganglia nuclei in postural control. Two particularly relevant functions are discussed in detail: first, the contribution of the basal ganglia to flexibility and to gaining control of balancecorrecting responses, including the ability to lend priority to the elements of a postural task; and second, processing afferent information by the basal ganglia, which is increasingly recognized as being highly relevant for postural control.
Facial Expression Recognition Based on Local Binary Pattern Features and Support Vector Machine

Facial expression recognition has been researched much in recent years because of their applications in intelligent communication systems. Many methods have been developed based on extracting Local Binary Pattern (LBP) features associating different classifying techniques in order to get more and more better effects of facial expression recognition. In this work, we propose a novel method for recognizing facial expressions based on Local Binary Pattern features and Support Vector Machine with two effective improvements. First is the preprocessing step and second is the method of dividing face images into nonoverlap square regions for extracting LBP features. The method was experimented on three typical kinds of database: small (213 images), medium (2040 images) and large (5130 images). Experimental results show the effectiveness of our method for obtaining remarkably better recognition rate in comparison with other methods.
Outbreak of Rust Caused by Coleosporium asterum on Solidago virgaurea var. gigantea in Ulleung-do

Abstract From June to October 2012, severe outbreaks of rust disease on Solidago virgaurea var. gigantea were observed in 5 different regions of Ulleung-do, Korea. Typical rust symptoms appeared as yellow spots, uredinia on leaves, and massive urediniospores covering the entire plant. Severely infected plants became discolored and died. On the basis of its morphological and molecular characteristics, the causal agent was identified as Coleosporium asterum. This pathogen has been reported as rust disease on S. virgaurea in the Canada and United States. In Korea, rust disease on S. virgaurea var. gigantea was reported as Uromyces rudbeckia in 1992. To the best of our knowledge, C. asterum is a novel rust pathogen on S. virgaurea var. gigantea in Korea.
Analyse d'un coupleur bidirectionnel a fibres optiques monomodes fusionnees.

The analysis of fused biconical single-mode fiber couplers shows that, as opposed to other types of single-mode fiber coupler, the coupling mechanism is not associated with evanescent waves and that the infinite cladding approximation is not valid. The two original claddings must be considered, after fusion and stretching, to form a single guide whose asymmetric excitation gives rise to the well-known beat phenomenon between two normal modes of the guide. For calculation purposes, this asymmetrically excited single guide is modeled into a pair of equivalent circular guides tangent to each other and having the same longitudinal profile as the real structure. The experimental results are compared with the theory.
Turbulent diffusion in the geostrophic inverse cascade

Motivated in part by the problem of large-scale lateral turbulent heat transport in the Earth’s atmosphere and oceans, and in part by the problem of turbulent transport itself, we seek to better understand the transport of a passive tracer advected by various types of fully developed two-dimensional turbulence. The types of turbulence considered correspond to various relationships between the streamfunction and the advected field. Each type of turbulence considered possesses two quadratic invariants and each can develop an inverse cascade. These cascades can be modified or halted, for example, by friction, a background vorticity gradient or a mean temperature gradient. We focus on three physically realizable cases: classical two-dimensional turbulence, surface quasi-geostrophic turbulence, and shallow-water quasi-geostrophic turbulence at scales large compared to the radius of deformation. In each model we assume that tracer variance is maintained by a large-scale mean tracer gradient while turbulent energy is produced at small scales via random forcing, and dissipated by linear drag. We predict the spectral shapes, eddy scales and equilibrated energies resulting from the inverse cascades, and use the expected velocity and length scales to predict integrated tracer fluxes. When linear drag halts the cascade, the resulting diffusivities are decreasing functions of the drag coefficient, but with different dependences for each case. When β is significant, we find a clear distinction between the tracer mixing scale, which depends on β but is nearly independent of drag, and the energy-containing (or jet) scale, set by a combination of the drag coefficient and β. Our predictions are tested via highresolution spectral simulations. We find in all cases that the passive scalar is diffused down-gradient with a diffusion coefficient that is well-predicted from estimates of mixing length and velocity scale obtained from turbulence phenomenology.
In situ chemical speciation of iron in estuarine sediments using XANES spectroscopy with partial least-squares regression.

X-ray absorption near-edge structure (XANES) spectroscopy has been applied to the quantitative determination of iron species in estuarine sediments. Mixtures of pyrite, olivine, and goethite were prepared as model mixtures containing ferrous sulfides, ferrous silicates, and ferric oxides and/or hydroxides, respectively. For resolving XANES spectra of these mixtures and quantifying the Fe-bearing minerals, partial least-squares (PLS) regression has been employed. The obtained PLS regression gave sufficient precision and this technique was applied to the XANES spectra of estuarine sediments collected from the Tama River in Tokyo, Japan. The relative abundances of iron species thus determined were consistent with the Mrssbauer spectroscopic results.
The preparation of highly water-soluble multi-walled carbon nanotubes by irreversible noncovalent functionalization with a pyrene-carrying polymer

Multi-walled carbon nanotubes (MWNTs) have been solubilized in water via a noncovalent method of exfoliation and centrifugation cycles with the assistance of hydrolyzed poly(styrene-co-maleic anhydride) carrying pyrene (HPSMAP). After the obtained solution was micro-filtered and dried, a water-soluble complex of HPSMAP–MWNTs was obtained. The solubility of HPSMAP–MWNTs was measured to be 46.2 mg ml−1 with a net MWNT concentration of 7.4 mg ml−1 in water. Thermal gravimetric analyses showed that there was a large amount of polymer remaining on the surface of MWNTs irreversibly after thoroughly removing the free polymer. Other characterizations using transmission electron microscopy, Fourier transform infrared (FTIR) spectroscopy, fluorescence spectra, and fluorescence decay were conducted.
A minimum variance calibration algorithm for pan-tilt robotic cameras in natural environments

A new generation of inexpensive robotic pan-tilt cameras can maintain high-resolution panoramic displays of natural environments. However, the pan-tilt mechanisms are imprecise: small errors can produce large errors in the panoramic display. It is thus important to accurately estimate pan-tilt values. We present a new calibration algorithm that does not rely on calibration markers or fixed orthogonal edges which are rarely available in natural scenes. Our calibration algorithm uses image variance density to optimally estimate camera pan and tilt values by incrementally refining image registration using overlapping images from prior frames. Experiments suggest that the new calibration algorithm can reduce calibration error by 81%. In a companion paper, we present a new image registration algorithm based on spherical projection that optimally aligns the resulting frames
Comparing different smoothing methods to detect double-cropping rice phenology based on LAI products – a case study in the Hunan province of China

ABSTRACT Many studies have demonstrated the remarkable potential of assimilating remotely sensing leaf area index (LAI) products into crop models in estimating regional crop yield. To ensure the temporal consistency between crop models and remote-sensing system, it is prerequisite to derive the crop phenology information from the LAI products. However, previous studies mainly detected the phenology through the vegetation index (VI). Although some pieces of research applied LAI in phenology monitoring for trees and shrubs, fewer focused on crops, especially those with two or three growing seasons annually. Thus, which smoothing algorithm methods are suitable to obtain phenology of double-cropping rice and their difference in smoothing for crops are still unknown. Based on the Global Land Surface Satellite (GLASS)LAI products, we applied four favourite smoothing algorithms (Asymmetric Gaussian fitting, Double Logistic fitting, Savitzky–Golay filter, and Wavelet-based Filter method) to reduce noise and reconstruct the LAI profile and then detected the phenological information of double-cropping rice in Hunan Province. Compared with ground actual observations, we found that two fitting methods are not suitable to smooth double-cropping rice LAI, while the wavelet method performed the best. Based on the wavelet method, we estimated the phenological information of double-cropping rice at different regional scales as well and the results reflected that the accuracy of regional estimation is also acceptable. This study implied that the wavelet method is rather suitable to detect phenological information of crops from LAI products, which provides narrow gaps between two growing season. Our contribution can benefit researchers who focus on agriculture or remote sensing, especially those who would like to assimilate remotely sensed information into crop growth models.
ACaaS: Access Control as a Service for IaaS Cloud

Organizations and enterprises have been outsourcing their computation, storage, and workflows to Infrastructure-as-a-Service (IaaS) based cloud platforms. The heterogeneity and high diversity of IaaS cloud environment demand a comprehensive and fine-grained access control mechanism, in order to meet dynamic, extensible, and highly configurable security requirements of these cloud consumers. However, existing security mechanisms provided by IaaS cloud providers do not satisfy these requirements. To address such an emergent demand, we propose a new cloud service called access control as a service (ACaaS), a service-oriented architecture in cloud to support multiple access control models, with the spirit of plug gable access control modules in modern operating systems. As a proof-of-concept reference prototype, we design and implement ACaaS_RBAC to provide role-based access control (RBAC) for Amazon Web Services (AWS), where cloud customers can easily integrate the service into enterprise applications in order to extend RBAC policy enforcement in AWS.
Comparative Fitness of a Parent Leishmania donovani Clinical Isolate and Its Experimentally Derived Paromomycin-Resistant Strain

Paromomycin has recently been introduced for the treatment of visceral leishmaniasis and emergence of drug resistance can only be appropriately judged upon its long term routine use in the field. Understanding alterations in parasite behavior linked to paromomycin-resistance may be essential to assess the propensity for emergence and spread of resistant strains. A standardized and integrated laboratory approach was adopted to define and assess parasite fitness of both promastigotes and amastigotes using an experimentally induced paromomycin-resistant Leishmania donovani strain and its paromomycin-susceptible parent wild-type clinical isolate. Primary focus was placed on parasite growth and virulence, two major components of parasite fitness. The combination of in vitro and in vivo approaches enabled detailed comparison of wild-type and resistant strains for which no differences could be demonstrated with regard to promastigote growth, metacyclogenesis, in vitro infectivity, multiplication in primary peritoneal mouse macrophages and infectivity for Balb/c mice upon infection with 2 x 107 metacyclic promastigotes. Monitoring of in vitro intracellular amastigote multiplication revealed a consistent decrease in parasite burden over time for both wild-type and resistant parasites, an observation that was subsequently also confirmed in a larger set of L. donovani clinical isolates. Though the impact of these findings should be further explored, the study results suggest that the epidemiological implications of acquired paromomycin-resistance may remain minimal other than the loss of one of the last remaining drugs effective against visceral leishmaniasis.