Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of abiraterone acetate on fatigue in patients with metastatic castration-resistant prostate cancer after docetaxel chemotherapy.

BACKGROUND Fatigue is a common, debilitating side-effect of prostate cancer and its treatment. Patient-reported fatigue was evaluated as part of COU-AA-301, a randomized, placebo-controlled, phase III trial of abiraterone acetate and prednisone versus placebo and prednisone in metastatic castration-resistant prostate cancer (mCRPC) patients after docetaxel chemotherapy. This is the first phase III study in advanced prostate cancer to evaluate fatigue outcomes using a validated fatigue-specific instrument. PATIENTS AND METHODS The Brief Fatigue Inventory (BFI) questionnaire was used to measure patient-reported fatigue intensity and fatigue interference with activities of daily life. All analyses were conducted using prespecified responder definitions of clinically meaningful changes. RESULTS A total of 797 patients were randomized to abiraterone acetate and prednisone, and 398 were randomized to placebo and prednisone. Compared with prednisone alone, in patients with clinically significant fatigue at baseline, abiraterone acetate and prednisone significantly increased the proportion of patients reporting improvement in fatigue intensity (58.1% versus 40.3%, P = 0.0001), improved fatigue interference (55.0% versus 38.0%, P = 0.0075), and accelerated improvement in fatigue intensity (median 59 days versus 194 days, P = 0.0155). CONCLUSIONS In patients with mCRPC progressing after docetaxel chemotherapy, abiraterone acetate and prednisone yielded clinically meaningful improvements in patient-reported fatigue compared with prednisone alone.
One-Year Outcomes of Cohort 1 in the Edwards SAPIEN Aortic Bioprosthesis European Outcome (SOURCE) Registry: The European Registry of Transcatheter Aortic Valve Implantation Using the Edwards SAPIEN Valve

Background— Transcatheter aortic valve implantation was developed to provide a therapeutic option for patients considered to be ineligible for, and to mitigate mortality and morbidity associated with, high-risk surgical aortic valve replacement. Methods and Results— The Edwards SAPIEN Aortic Bioprosthesis European Outcome (SOURCE) Registry was designed to assess initial post commercial clinical transcatheter aortic valve implantation results of the Edwards SAPIEN valve in consecutive patients in Europe. Cohort 1 consists of 1038 patients enrolled at 32 centers. One-year outcomes are presented. Patients with the transapical approach (n=575) suffered more comorbidities than transfemoral patients (n=463) with a significantly higher logistic EuroSCORE (29% versus 25.8%; P=0.007). These groups are different; therefore, outcomes cannot be directly compared. Total Kaplan Meier 1-year survival was 76.1% overall, 72.1% for transapical and 81.1% for transfemoral patients, and 73.5% of surviving patients were in New York Heart Association (NYHA) class I or II at 1 year. Combined transapical and transfemoral causes of death were cardiac in 25.1%, noncardiac in 49.2%, and unknown in 25.7%. Pulmonary complications (23.9%), renal failure (12.5%), cancer (11.4%), and stroke (10.2%) were the most frequent noncardiac causes of death. Multivariable analysis identified logistic EuroSCORE, renal disease, liver disease, and smoking as variables with the highest hazard ratios for 1-year mortality whereas carotid artery stenosis, hyperlipidemia, and hypertension were associated with lower mortality. Conclusion— The SOURCE Registry is the largest consecutively enrolled registry for transcatheter aortic valve implantation procedures. It demonstrates that with new transcatheter aortic techniques excellent 1-year survival in high-risk and inoperable patients is achievable and provides a benchmark against which future transcatheter aortic valve implantation cohorts and devices can be measured.
A qualitative analysis of haptic feedback in music focused exercises

We present the findings of a pilot-study that analysed the role of haptic feedback in a musical context. To examine the role of haptics in Digital Musical Instrument (DMI) design an experiment was formulated to measure the users' perception of device usability across four separate feedback stages: fully haptic (force and tactile combined), constant force only, vibrotactile only, and no feedback. The study was piloted over extended periods with the intention of exploring the application and integration of DMIs in real-world musical contexts. Applying a music orientated analysis of this type enabled the investigative process to not only take place over a comprehensive period, but allowed for the exploration of DMI integration in everyday compositional practices. As with any investigation that involves creativity, it was important that the participants did not feel rushed or restricted. That is, they were given sufficient time to explore and assess the different feedback types without constraint. This provided an accurate and representational set of qualitative data for validating the participants' experience with the different feedback types they were presented with.
Spatial-Spectral Kernel Sparse Representation for Hyperspectral Image Classification

Kernel sparse representation classification (KSRC), a nonlinear extension of sparse representation classification, shows its good performance for hyperspectral image classification. However, KSRC only considers the spectra of unordered pixels, without incorporating information on the spatially adjacent data. This paper proposes a neighboring filtering kernel to spatial-spectral kernel sparse representation for enhanced classification of hyperspectral images. The novelty of this work consists in: 1) presenting a framework of spatial-spectral KSRC; and 2) measuring the spatial similarity by means of neighborhood filtering in the kernel feature space. Experiments on several hyperspectral images demonstrate the effectiveness of the presented method, and the proposed neighboring filtering kernel outperforms the existing spatial-spectral kernels. In addition, the proposed spatial-spectral KSRC opens a wide field for future developments in which filtering methods can be easily incorporated.
Moving beyond molecules: patterning solid-state features via dip-pen nanolithography with sol-based inks.

Herein, we described a new dip-pen nanolithography (DPN)-based method for the direct patterning of organic/inorganic composite nanostructures on silicon and oxidized silicon substrates. The approach works by the hydrolysis of metal precursors in the meniscus between an AFM tip and a surface according to the reaction 2MCln + nH2O --> M2On + 2nHCl; M = Al, Si, and Sn. The inks are hybrid composites of inorganic salts with amphiphilic block copolymer surfactants. Three proof-of-concept systems involving Al2O3, SiO2, and SnO2 nanostructures on silicon and silicon oxide surfaces have been studied. Arrays of dots and lines can be written easily with control over feature size and shape on the sub-200 nm level. The structures have been characterized by atomic force microscopy, scanning electron microscopy, transmission electron microscopy, and energy-dispersive X-ray analysis. This work is important because it opens up the opportunity for using DPN to deposit solid-state materials rather than simple organic molecules onto surfaces with the resolution of an AFM without the need for a driving force other than chemisorption (e.g., applied fields).
Contact-Free Palm-Vein Recognition Based on Local Invariant Features

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.
Pipelines on heterogeneous systems: models and tools

We study the performance of pipeline algorithms in heterogeneous networks. The concept of heterogeneity is not only restricted to the differences in computational power of the nodes, but also refers to the network capabilities. We develop a skeleton tool that allows us an efficient block‐cyclic mapping of pipelines on heterogeneous systems. The tool supports pipelines with a number of stages much larger than the number of physical processors available. We derive an analytical formula that allows us to predict the performance of pipelines in heterogeneous systems. According to the analytical complexity formula, numerical strategies to solve the optimal mapping problem are proposed. The computational results prove the accuracy of the predictions and effectiveness of the approach. Copyright © 2005 John Wiley & Sons, Ltd.
Space-efficient static trees and graphs

Data structures that represent static unlabeled trees and planar graphs are developed. The structures are more space efficient than conventional pointer-based representations, but (to within a constant factor) they are just as time efficient for traversal operations. For trees, the data structures described are asymptotically optimal: there is no other structure that encodes n-node trees with fewer bits per node, as N grows without bound. For planar graphs (and for all graphs of bounded page number), the data structure described uses linear space: it is within a constant factor of the most succinct representation. <<ETX>>
Modelling and Querying Video Data

As video data is penetrating many information systems the need for database support for video data evolves. In this paper we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream. We also discuss query language features that can take advantage of the proposed model. We have identified basic operators that should be implemented in the query language to support content based queries. The paper also analyses how these operators can be used to provide video data queries. The model has been used as a basis for a television news archive prototype and some experimental results are presented.
Syndecan-1 knockdown inhibits glioma cell proliferation and invasion by deregulating a c-src/FAK-associated signaling pathway

Recent studies have shown that increased syndecan-1 (SDC1) expression in human glioma is associated with higher tumor grades and poor prognoses, but its oncogenic functions and the underlying molecular mechanisms remain unknown. Here, we examined SDC1 expression in datasets from The Cancer Genome Atlas and the National Center for Biotechnology Information Gene Expression Omnibus. Elevated SDC1 expression in glioma was closely associated with increases in tumor progression and shorter survival. We also examined SDC1 expression and evaluated the effects of stable SDC1 knockdown in glioma cell lines. SDC1 knockdown attenuated proliferation and invasion by glioma cells and markedly decreased PCNA and MMP-9 mRNA and protein expression. In a xenograft model, SDC1 knockdown suppressed the tumorigenic effects of U87 cells in vivo. SDC1 knockdown decreased phosphorylation of the c-Src/FAK complex and its downstream signaling molecules, Erk, Akt and p38 MAPK. These results suggest that SDC1 may be a novel therapeutic target in the treatment of glioma.
SoK: Lessons Learned from Android Security Research for Appified Software Platforms

Android security and privacy research has boomed in recent years, far outstripping investigations of other appified platforms. However, despite this attention, research efforts are fragmented and lack any coherent evaluation framework. We present a systematization of Android security and privacy research with a focus on the appification of software systems. To put Android security and privacy research into context, we compare the concept of appification with conventional operating system and software ecosystems. While appification has improved some issues (e.g., market access and usability), it has also introduced a whole range of new problems and aggravated some problems of the old ecosystems (e.g., coarse and unclear policy, poor software development practices). Some of our key findings are that contemporary research frequently stays on the beaten path instead of following unconventional and often promising new routes. Many security and privacy proposals focus entirely on the Android OS and do not take advantage of the unique features and actors of an appified ecosystem, which could be used to roll out new security mechanisms less disruptively. Our work highlights areas that have received the larger shares of attention, which attacker models were addressed, who is the target, and who has the capabilities and incentives to implement the countermeasures. We conclude with lessons learned from comparing the appified with the old world, shedding light on missed opportunities and proposing directions for future research.
When less is more (LIMO):controlled parallelism forimproved efficiency

While developing shared-memory programs, programmers often contend with the problem of how many threads to create for best efficiency. Creating as many threads as the number of available processor cores, or more, may not be the most efficient configuration. Too many threads can result in excessive contention for shared resources, wasting energy, which is of primary concern for embedded devices. Furthermore, thermal and power constraints prevent us from operating all the processor cores at the highest possible frequency, favoring fewer threads. The best number of threads to run depends on the application, user input and hardware resources available. It can also change at runtime making it infeasible for the programmer to determine this number. To address this problem, we propose LIMO, a runtime system that dynamically manages the number of running threads of an application for maximizing peformance and energy-efficiency. LIMO monitors threads' progress along with the usage of shared hardware resources to determine the best number of threads to run and the voltage and frequency level. With dynamic adaptation, LIMO provides an average of 21% performance improvement and a 2x improvement in energy-efficiency on a 32-core system over the default configuration of 32 threads for a set of concurrent applications from the PARSEC suite, the Apache web server, and the Sphinx speech recognition system.
A Graph-Based Approach for Classifying OWL 2 QL Ontologies

Ontology classification is the reasoning service that computes all subsumption relationships inferred in an ontology between concept, role, and attribute names in the ontology signature. OWL 2 QL is a tractable profile of OWL 2 for which ontology classification is polynomial in the size of the ontology TBox. However, to date, no efficient methods and implementations specifically tailored to OWL 2 QL ontologies have been developed. In this paper, we provide a new algorithm for ontology classication in OWL 2 QL, which is based on the idea of encoding the ontology TBox into a directed graph and reducing core reasoning to computation of the transitive closure of the graph. We have implemented the algorithm in the QuOnto reasoner and extensively evaluated it over very large ontologies. Our experiments show that QuOnto outperforms various popular reasoners in classification of OWL 2 QL ontologies.
On Non-Black-Box Simulation and the Impossibility of Approximate Obfuscation

The introduction of a non-black-box simulation technique by Barak (FOCS 2001) has been a major landmark in cryptography, breaking the previous barriers of black-box impossibility. Barak's technique has given rise to various powerful applications and is a key component in all known protocols with non-black-box simulation. We present the first non-black-box simulation technique that does not rely on Barak's technique (or on nonstandard assumptions). Invoking this technique, we obtain new and improved protocols resilient to various resetting attacks. These improvements include weaker computational assumptions and better round complexity. A prominent feature of our technique is its compatibility with rewinding techniques from classic black-box zero-knowledge protocols. The combination of rewinding with non-black-box simulation has proven instrumental in coping with challenging goals such as simultaneously resettable zero-knowledge, proofs of knowledge, and resettable security from one-way functions. While pre.
A Framework for Examining Topical Locality in Object-Oriented Software

The software entities of an object-oriented system should be organized in such a way that "spatial relatedness entails semantic relatedness". We refer this as the tenet of "topical locality" and argue that it is fundamental for the code base to be navigable. In this paper, we propose a novel experimental framework to test this key tenet and use large-scale open-source projects to assess three relationships. In particular, we find that: (1) class name along with header comments conveys class body's topic; (2) a code line is indicative of its surroundings; and (3) a contiguous code fragment may serve as a snapshot of the entire class. Our work not only shows the foundations necessary for the success of many code navigation approaches, but also opens avenues for further tool enhancements.
DE vs. PSO: A Performance Assessment for Expensive Problems

This paper investigates the suitability of the Particle Swarm Optimization (PSO) and the Differential Evolution (DE) algorithms in solving expensive optimization problems. Eight PSO variants, and eight DE variants are experimentally compared among each other. The Comparing Continuous Optimizers (COCO) methodology was adopted in comparing these variants on the noiseless BBOB testbed. Based on the results, we provide useful insights regarding the algorithms' relative efficiency and effectiveness under an expensive budget of function evaluations; and draw suggestions about which algorithm should be used depending on what we know about our optimization problem in terms of evaluation budget, dimensionality, and function structure. Furthermore, we propose possible future research directions addressing the algorithms limitations. Overall, DE variants perform well in low dimensions, whereas in higher dimensions, several PSO variants surpass DE algorithms. Among the top performers, JADE and χPSO are the robust algorithms for solving expensive budget problems.
Intracellular invasion of green algae in a salamander host

The association between embryos of the spotted salamander (Ambystoma maculatum) and green algae (“Oophila amblystomatis” Lamber ex Printz) has been considered an ectosymbiotic mutualism. We show here, however, that this symbiosis is more intimate than previously reported. A combination of imaging and algal 18S rDNA amplification reveals algal invasion of embryonic salamander tissues and cells during development. Algal cells are detectable from embryonic and larval Stages 26–44 through chlorophyll autofluorescence and algal 18S rDNA amplification. Algal cell ultrastructure indicates both degradation and putative encystment during the process of tissue and cellular invasion. Fewer algal cells were detected in later-stage larvae through FISH, suggesting that the decline in autofluorescent cells is primarily due to algal cell death within the host. However, early embryonic egg capsules also contained encysted algal cells on the inner capsule wall, and algal 18S rDNA was amplified from adult reproductive tracts, consistent with oviductal transmission of algae from one salamander generation to the next. The invasion of algae into salamander host tissues and cells represents a unique association between a vertebrate and a eukaryotic alga, with implications for research into cell–cell recognition, possible exchange of metabolites or DNA, and potential congruence between host and symbiont population structures.
A Narrow Quantitative Trait Locus in C. elegans Coordinately Affects Longevity, Thermotolerance, and Resistance to Paraquat

By linkage mapping of quantitative trait loci, we previously identified at least 11 natural genetic variants that significantly modulate Caenorhabditis elegans life-span (LS), many of which would have eluded discovery by knock-down or mutation screens. A region on chromosome IV between markers stP13 and stP35 had striking effects on longevity in three inter-strain crosses (each P < 10−9). In order to define the limits of that interval, we have now constructed two independent lines by marker-based selection during 20 backcross generations, isolating the stP13–stP35 interval from strain Bergerac-BO in a CL2a background. These congenic lines differed significantly from CL2a in LS, assayed in two environments (each P < 0.001). We then screened for exchange of flanking markers to isolate recombinants that partition this region, because fine-mapping the boundaries for overlapping heteroallelic spans can greatly narrow the implicated interval. Recombinants carrying the CL2a allele at stP35 were consistently long-lived compared to those retaining the Bergerac-BO allele (P < 0.001), and more resistant to temperature elevation and paraquat (each ∼1.7-fold, P < 0.0001), but gained little protection from ultraviolet or peroxide stresses. Two rounds of recombinant screening, followed by fine-mapping of break-points and survival testing, narrowed the interval to 0.18 Mb (13.35–13.53 Mb) containing 26 putative genes and six small-nuclear RNAs – a manageable number of targets for functional assessment.
Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology

Graph-theoretical approaches to biological network analysis have proven to be effective for small networks but are computationally infeasible for comprehensive genome-scale systems-level elucidation of these networks. The difficulty lies in the NP-hard nature of many global systems biology problems that, in practice, translates to exponential (or worse) run times for finding exact optimal solutions. Moreover, these problems, especially those of an enumerative flavor, are often memory-intensive and must share very large sets of data effectively across many processors. For example, the enumeration of maximal cliques - a core component in gene expression networks analysis, cis regulatory motif finding, and the study of quantitative trait loci for high-throughput molecular phenotypes can result in as many as 3^n/3 maximal cliques for a graph with n vertices. Memory requirements to store those cliques reach terabyte scales even on modest-sized genomes. Emerging hardware architectures with ultra-large globally addressable memory such as the SGI Altix and Cray X1 seem to be well suited for addressing these types of data-intensive problems in systems biology. This paper presents a novel framework that provides exact, parallel and scalable solutions to various graph-theoretical approaches to genome-scale elucidation of biological networks. This framework takes advantage of these large-memory architectures by creating globally addressable bitmap memory indices with potentially high compression rates, fast bitwise-logical operations, and reduced search space. Augmented with recent theoretical advancements based on fixed-parameter tractability, this framework produces computationally feasible performance for genome-scale combinatorial problems of systems biology.