Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing group parameters in the real-time specification for Java

The Real-Time Specification for Java (RTSJ) supports Processing Groups. However this typically requires the underlying operating system to provide group budgets, which is not widespread practice. As the RTSJ attempts to define its semantics for multiprocessor systems, the issue of the meaning and implementability of the ProcessingGroupParameters class needs to be re-examined. This paper reviews the possible options. It proposes that Processing Groups be directly represented with various subclasses providing different implementation mechanisms. The relationship between Processing Groups and the implementation of non-bound asynchronous event handlers is also explored.
Conceptual Clustering of Social Bookmarking Sites

Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g. , along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio. us bookmarking system.
Sensitivity analysis of expert-based probabilistic population projections in the case of Austria.

The traditional way of dealing with uncertainty in population projections through \f2high\f1 and \f2low\f1 variants is unsatisfactory because it remains unclear what range of uncertainty these alternative paths are assumed to cover. Probabilistic approaches have not found their way into \f2official\f1 population projections. This paper proposes an expert-based probabilistic approach (random scenario approach) that seems to meet important criteria for successful application to national and international projections: 1) it provides significant advantages to current practice, 2) it presents an evolution of current practice rather than a discontinuity, 3) it is scientifically sound, and 4) it is applicable to all countries. In a recent \f2Nature\f1 article (Lutz et al. 1997) this method was applied to 13 world regions. This paper discusses the applicability to national projections by directly taking the alternative assumptions defined by the Austrian Statistical Office. Sensitivity analyses that resolve some methodological questions about the approach are also presented.
The role of regionalization in large river restoration

The Willamette River basin is a relatively large river system (~31,200 km') located in western Oregon flowing North into the Columbia River (WENTZ & Mci<ENZIE 1991). lt is the 13th largest river in the conterminous United States as regards flow, and produces more runoff per drainage area than any of the large rivers in the U.S. (I<AMMERER 1990). The basin is composed of three major ecological regions: the Coast Range, the Cascades and the Willamette Valley (Fig. l) (USEPA 1998, ÜMERNIK 1987). Soon after settlement of the region by European immigrants in the mid-1800s, the mainstem floodplain of the river (Willamette Valley ecoregion) was vastly altered by human in-river actions (i.e. removal of large woody debris, channelization, application of revetments) and land use changes (i.e. removal of riparian forests, filling of wetlands and intermittent river channels, urbanization and large-scale agricultural practices adjacent to the main channel) (BENNER & SEDELL 1997). Reclamation efforts of the 1960s involving improvements in sewage treatment, industria! discharge and summer low flow augmentation were effective in dramatically improving the water quality. However, virrually no holistic restoration of the Willamette River has been made to move toward the natural antecedent biological or ecological conditions (BERGER 1992).
Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation

In this paper, a hybrid fuzzy adaptive output feedback control design approach is proposed for a class of multiinput and multioutput strict-feedback nonlinear systems with unknown time-varying delays, unmeasured states, and input saturation. First, fuzzy logic systems are employed to approximate unknown nonlinear functions in the system. Next, a smooth function is used to approximate the input saturation and an adaptive fuzzy state observer is constructed to solve the problem of unmeasured states. Based on the designed adaptive fuzzy state observer, a serial-parallel estimation model is established. By applying adaptive fuzzy dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial-parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws is developed based on Lyapunov-Krasovskii functional. It is proved that all variables of the closed-loop system are bounded and the system outputs can follow the given bounded reference signals as close as possible. A simulation example is provided to further show the effectiveness of this novel control scheme.
Upregulations of CRH and CRHR1 in the Epileptogenic Tissues of Patients with Intractable Infantile Spasms

Infantile spasms (IS) are an age‐specific epileptic syndrome with specific clinical symptom and electroencephalogram (EEG) features, lacking treatment options, and a poor prognosis. Excessive endogenous corticotropin‐releasing hormone (CRH) in infant brain might result in IS. However, the data from human IS are limited. In our study, we investigated the expressions of CRH and its receptor type 1 (CRHR1) in surgical tissues from patients with IS and autopsy controls.
Scenario-driven approach for business process development

The development of services-based systems starts from defining business requirements to be implemented as high-level business processes. In this paper, we describe a scenario-driven approach for developing business processes specified as WS-BPEL descriptions. We aim for simplicity in the business level notation and leverage example-like modelling principles in order to enable process sketching. The first step in our approach is to identify the essential functional requirements for business processes. The requirements are modelled as simple scenarios, each of them defining a sample run through the process, i.e., required behaviour that the underlying service-based system should allow. The scenarios, specifying sent and received messages among the services, are synthesised into a state machine. The state machine is transformed into an initial process model given in UML activity model notation. To enable mapping into WS-BPEL code, the transformation exploit domain-specific rules, i.e., our target model consists of a subset of UML with WS-BPEL specific constraints and stereotypes. The initial process model can be further refined to enable generation of executable WS-BPEL descriptions. We apply the approach on two cases, a simple process for managing loan requests and an industry case study from a logistics provider are presented.
Revealing structure components of the retina by deep learning networks

Deep convolutional neural networks (CNNs) have demonstrated impressive performance on visual object classification tasks. In addition, it is a useful model for predication of neuronal responses recorded in visual system. However, there is still no clear understanding of what CNNs learn in terms of visual neuronal circuits. Visualizing CNN’s features to obtain possible connections to neuronscience under-pinnings is not easy due to highly complex circuits from the retina to higher visual cortex. Here we address this issue by focusing on single retinal ganglion cells with a simple model and electrophysiological recordings from salamanders. By training CNNs with white noise images to predicate neural responses, we found that convolutional filters learned in the end are resembling to biological components of the retinal circuit. Features represented by these filters tile the space of conventional receptive field of retinal ganglion cells. These results suggest that CNN could be used to reveal structure components of neuronal circuits.
Probabilistic arithmetic and energy efficient embedded signal processing

Probabilistic arithmetic, where the ith output bit of addition and multiplication is correct with a probability pi , is shown to be a vehicle for realizing extremely energy-efficient, embedded computing. Specifically, probabilistic adders and multipliers, realized using elements such as gates that are in turn probabilistic, are shown to form a natural basis for primitives in the signal processing (DSP) domain. In this paper, we show that probabilistic arithmetic can be used to compute the FFT in an extremely energy-efficient manner, yielding energy savings of over 5. 6X in the context of the widely used synthetic aperture radar (SAR) application [1]. Our results are derived using novel probabilistic cmos (PC-MOS) technology, characterized and applied in the past to realize ultra-efficient architectures for probabilistic applications [2, 3, 4]. When applied to the dsp domain, the resulting error in the output of a probabilistic arithmetic primitive, such as an adder for example, manifests as degradation in the signal-to-noise ratio (SNR) ofthe sar image that is reconstructed through the FFT algorithm. In return for this degradation that is enabled by our probabilistic arithmetic primitives ? - degradation visually indistinguishable from an image reconstructed using conventional deterministic approaches -- significant energy savings and performance gains are shown to be possible per unit of SNR degradation. These savings stem from a novel method of voltage scaling, which we refer to as biased voltage scaling (or BIVOS), that is the major technical innovation on which our probabilistic designs are based.
Robot-assisted Low Anterior Resection for Situs Inversus Totalis: A Novel Technical Approach for an Uncommon Condition

Introduction: Situs inversus totalis (SIT) is an uncommon condition, with an incidence of 1 in 10,000. Surgery for SIT patients is more difficult because of the uncommon anatomy. Experience in laparoscopic surgery for patients with SIT is very limited. Only a few cases of laparoscopic colorectal resections have been reported in the literature. We present the first robot-assisted low anterior resection for rectal cancer in a patient with SIT. Patient: A 70-year-old woman with SIT who presented with rectal bleeding underwent a colonoscopy and barium enema. This workup revealed a rectal cancer 10 cm from the anal verge. The magnetic resonance imaging scan revealed a T3/4 tumor in the rectum with perirectal lymph node involvement, whereas the computed tomography positron emission tomography scan did not reveal any distal metastasis. She underwent neoadjuvant chemoradiotherapy 6 weeks before surgery. Postoperatively, she made an uneventful recovery and was discharged on day 6. Surgical Technique: After laparoscopic examination and displacement of the small bowel, 4 robot trocars were inserted into 4 quadrants of the abdomen. A fifth port was inserted and used by the assistant. The robot cart was docked from the right side with arms 1, 2, and 3 in the right upper quadrant (Cadiere grasper), left lower quadrant (bipolar Maryland grasper), and left upper quadrant (monopolar scissors), respectively, for colonic mobilization without splenic flexure takedown. For pelvic dissection, arms 1 and 3 were moved to the right upper quadrant and right lower quadrant, respectively. After adequate pelvic dissection, the robot cart was undocked, and a laparoscopic articulating linear stapler was used to transect the rectum from the left lower quadrant port. Bowel continuity was restored with a circular stapler. A loop ileostomy was created through the extraction site in the right lower quadrant. Conclusions: Robot-assisted low anterior resection for SIT patients can be performed safely and confers the benefits of laparoscopic low anterior resection with additional advantages unique to the da Vinci system.
Spatioseasonal Variations of Atmospheric Ammonia Concentrations Over the United States: Comprehensive Model‐Observation Comparison

Atmospheric ammonia plays an important role in a number of environmental issues, including new particle formation and aerosol indirect radiative forcing. Over the United States, atmospheric ammonia has seen an increasing trend due in most part to the declining SO2 and NOx emissions. We conduct the first comprehensive assessment of multiyear Goddard Earth Observing System (GEOS)‐Chem simulated ammonia concentration ([NH3]) over conterminous United States along with surface observations from all 90 National Atmospheric Deposition Program Ammonia Monitoring Network (AMoN) sites that have at least 2 years of continuous measurements. Model‐simulated [NH3] is along empirically expected lines with regard to temporal trends, seasonal variations, and spatial distribution. GEOS‐Chem‐simulated [NH3], compared to AMoN observed values, has weighted average correlation (τ) of 0.50 ± 0.15 and mean fractional bias (MFB) of −8.8 ± 56%. Most sites (63 out of 90) have −60% < MFB < +60%. The deviations from observed values vary spatially and seasonally, and there is significant wintertime underestimation (−44 ± 58%) across most of conterminous United States (except the Pacific states). The largest positive deviations occur in the Pacific states (101 ± 46%) and the largest negative deviations in the Southern Plain states (−73 ± 39%) and the Mountain states (−73 ± 84%), both in the winter months. Over the Great Plains region, GEOS‐Chem simulated [NH3] shows a much stronger dependence to emissions than AMoN observed [NH3], indicating scope for improved representation of emissions for the region. Over Southeast United States, there appears to be the strong effect of the changing emissions of SO2 and NOx in both modeled and observed [NH3].
Do glaciers enhance organic carbon burial? : an isotopic approach linking continental weathering, iron-(oxhydr)oxides and climate change

This thesis explores continental weathering patterns in glacial and non-glacial river catchments in Iceland and Greenland. Specific attention is placed on characterizing the relative iron (oxyhydr)oxide export rates of glacial and non-glacial catchments to the ocean. Total element concentration and iron stable isotope measurements indicate that chemical weathering differences do exist between glacial and non-glacial catchments. The differences appear primarily related to variations in soil formation and organic matter availability between the environments. Physical, rather than chemical, differences between glacial and non-glacial catchments however dominate the relative differences in (oxyhyr)oxide export rates. Glacial and non-glacial river sediments from otherwise analogous terrains contain about the same quantity of iron (oxyhyr)oxide on a weight normalized basis. This equates to glacial rivers exporting far more iron (oxyhyr)oxides on a discharge weighted basis, because glacial rivers contain far higher suspended sediment concentrations that non-glacial rivers. Existing research shows that organic carbon accumulation and burial in marine environments scale directly with iron (oxyhydr)oxide accumulation. This means that shifts in continental weathering over glacial-interglacial cycles drive further changes in marine carbon burial creating a global climate feedback loop.
Renal Antioxidant Enzymes and Fibrosis-Related Markers in the Rat Adriamycin Model

Excessive generation of reactive oxygen intermediates can induce changes in the cellular antioxidant defence system. In this study we examine the antioxidant enzyme status and the expression of fibrosis-related marker proteins in the Adriamycin model of chronic renal failure in the rat. Twenty weeks after Adriamycin treatment, rats have overt nephrotic syndrome and renal failure with development of tubulo-interstitial fibrosis and glomerulosclerosis. Lipids accumulate in blood and in both glomeruli and tubulo-interstitial tissue. Desmin and α-smooth muscle actin expression increases in glomeruli and in the tubulo-interstitial area. Renal cortex antioxidant enzyme activities are decreased 20 weeks after Adriamycin injection (to 41% for catalase, to 56% for total superoxide dismutase and to 69% for glutathione peroxidase). The mRNA levels of catalase, Cu/Zn-superoxide dismutase and glutathione peroxidase-1 evaluated by Northern blot are decreased by more than 50% for catalase, Cu/Zn-superoxide dismutase and glutathione peroxidase-1. We conclude that in the rat Adriamycin-induced model of chronic renal failure with fibrosis, the combination of decreased antioxidant enzyme status in renal cortex with high concentrations of lipids in blood and renal tissue facilitates oxidative damage. Development of fibrosis is paralleled by increased expression of desmin and α-smooth muscle actin.
Cardiovascular Adverse Events in Patients With Cancer Treated With Bevacizumab: A Meta‐Analysis of More Than 20 000 Patients

Background The monoclonal antibody bevacizumab effectively inhibits angiogenesis in several types of cancers by blocking vascular endothelial growth factor. However, life‐threatening cardiovascular adverse effects could limit its use and may warrant specific follow‐up strategies. Methods and Results We systematically searched MEDLINE, Cochrane, EMBASE, and Web of Science for randomized controlled trials published until November 2016 that assessed patients with cancer treated with or without bevacizumab in addition to standard chemotherapy. A total of 20 050 patients with a broad range of cancer types from 22 studies were included in this analysis (10 394 in the bevacizumab group and 9656 in the control group). The risks of arterial and venous adverse events were higher in the bevacizumab groups (relative risk [RR], 1.37; 95% CI, 1.10–1.70 [P=0.004] and RR, 1.29; 95% CI, 1.12–1.47 [P<0.001], respectively), and more arterial adverse events occurred in patients taking high‐dose bevacizumab regimens. Bevacizumab treatment was associated with the highest risk of cardiac and cerebral ischemia in the high‐dose bevacizumab groups (RR, 4.4; 95% CI, 1.59–12.70 [P=0.004] and RR, 6.67; 95% CI, 2.17–20.66 [P=0.001], respectively). In addition, the risk of bleeding and arterial hypertension were higher in the bevacizumab groups (RR, 2.74; 95% CI, 2.38–3.15 [P<0.001] and RR, 4.73; 95% CI, 4.15–5.39 [P<0.00001], respectively), with higher values for patiens taking high‐dose regimens. Conclusions Treatment with bevacizumab increases the risk of arterial adverse events, particularly cardiac and cerebral ischemia, venous adverse events, bleeding, and arterial hypertension. This risk is additionally increased with high doses of bevacizumab. Further studies should determine the appropriate options for cardio‐oncology management. Clinical Trial Registration URL: https://www.crd. york.ac. uk. Unique identifier: PROSPERO(CRD42016054305).
The string edit distance matching problem with moves

The edit distance between two strings S and R is defined to be the minimum number of character inserts, deletes and changes needed to convert R to S. Given a text string t of length n, and a pattern string p of length m, informally, the string edit distance matching problem is to compute the smallest edit distance between p and substrings of t. A well known dynamic programming algorithm takes time O(nm) to solve this problem, and it is an important open problem in Combinatorial Pattern Matching to significantly improve this bound.We relax the problem so that (a) we allow an additional operation, namely, substring moves, and (b) we approximate the string edit distance upto a factor of O(log n log*n). Our result is a near linear time deterministic algorithm for this version of the problem. This is the first known significantly subquadratic algorithm for a string edit distance problem in which the distance involves nontrivial alignments. Our results are obtained by embedding strings into L1 vector space using a simplified parsing technique we call Edit Sensitive Parsing (ESP). This embedding is approximately distance preserving, and we show many applications of this embedding to string proximity problems including nearest neighbors, outliers, and streaming computations with strings.
Quadrilateral Meshing with Directionality Control through the Packing of Square Cells

This paper proposes a computational method for fully automated quadrilateral meshing. Unlike previous methods, this new scheme can create a quadrilateral mesh whose directionality is precisely controlled. Given as input: (1) a 2D geometric domain, (2) a desired node spacing distribution as a scalar function deened over the domain, and (3) a desired mesh directionality as a vector eld deened over the domain, the proposed method rst packs square cells closely in the domain. The centers of the squares are then connected by Delaunay triangulation, yielding a triangular mesh topology. The triangular mesh is further converted into a quad-dominant mesh or an all-quad mesh that satisses the given mesh directionality. Since the closely packed square cells mimic a pattern of Voroni polygons corresponding to a well-shaped graded quadrilateral mesh, the proposed method generates a high quality mesh whose element sizes and mesh directionality conform well to the given input.
Fock quantization of a scalar field with time dependent mass on the three-sphere: Unitarity and uniqueness

We study the Fock description of a quantum free field on the three-sphere with a mass that depends explicitly on time, also interpretable as an explicitly time dependent quadratic potential. We show that, under quite mild restrictions on the time dependence of the mass, the specific Fock representation of the canonical commutation relations which is naturally associated with a massless free field provides a unitary dynamics even when the time varying mass is present. Moreover, we demonstrate that this Fock representation is the only acceptable one, up to unitary equivalence, if the vacuum has to be SO(4)-invariant (i.e., invariant under the symmetries of the field equation) and the dynamics is required to be unitary. In particular, the analysis and uniqueness of the quantization can be applied to the treatment of cosmological perturbations around Friedmann-Robertson-Walker spacetimes with the spatial topology of the three-sphere, like e.g. for gravitational waves (tensor perturbations). In addition, we analyze the extension of our results to free fields with a time dependent mass defined on other compact spatial manifolds. We prove the uniqueness of the Fock representation in the case of a two-sphere as well, and discuss the case of a three-torus.
Optimizing clustering algorithm in mobile ad hoc networks using genetic algorithmic approach

We show how genetic algorithms can be useful in enhancing the performance of clustering algorithms in mobile ad hoc networks. In particular, we optimize our recently proposed weighted clustering algorithm (WCA). The problem formulation along with the parameters are mapped to individual chromosomes as input to the genetic algorithmic technique. Encoding the individual chromosomes is an essential part of the mapping process; each chromosome contains information about the clusterheads and the members thereof, as obtained from the original WCA. The genetic algorithm then uses this information to obtain the best solution (chromosome) defined by the fitness function. The proposed technique is such that each clusterhead handles the maximum possible number of mobile nodes in its cluster in order to facilitate the optimal operation of the medium access control (MAC) protocol. Consequently, it results in the minimum number of clusters and hence clusterheads. Simulation results exhibit improved performance of the optimized WCA than the original WCA. Moreover, the loads among clusters are more evenly balanced by a factor of ten.