Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioral Consequences and Cortical Reorganization in Homonymous Hemianopia

The most common visual defect to follow a lesion of the retrochiasmal pathways is homonymous hemianopia (HH), whereby, in each eye, patients are blind to the contralesional visual field. From a behavioral perspective, in addition to exhibiting a severe deficit in their contralesional visual field, hemianopic patients can also present implicit residual capacities, now usually referred to collectively as blindsight. It was recently demonstrated that HH patients can also suffer from a subtle deficit in their ipsilesional visual field, called sightblindness (the reverse case of blindsight). Furthermore, the nature of the visual deficit in the contralesional and ipsilesional visual fields, as well as the pattern of functional reorganization in the occipital lobe of HH patients after stroke, all appear to depend on the lesion side. In addition to their contralesional and ipsilesional visual deficits, and to their residual capacities, HH patients can also experience visual hallucinations in their blind field, the physiopathological mechanisms of which remain poorly understood. Herein we review blindsight in terms of its better-known aspects as well as its less-studied clinical signs such as sightblindness, hemispheric specialization and visual hallucinations. We also discuss the implications of recent experimental findings for rehabilitation of visual field defects in hemianopic patients.
Static Probabilistic Timing Analysis for Multicore Processors with Shared Cache

I. INTRODUCTION As a result of stringent requirements on size, weight, and power consumption (SWaP), as well as the need to provide advanced new functionality through software, critical real-time embedded systems in the aerospace, space, and automotive markets are beginning to make use of multicore processors for hard real-time applications. The deployment of hard real-time applications on advanced multicore processors requires a number of challenges to be overcome. A wealth of research has been done on scheduling and schedulability analysis for multicore platforms (see [7] for a survey); however, this work needs to be underpinned by safe and tight estimates of the Worst-Case Execution Time (WCET) of component tasks. Considerable work has been done on WCET analysis assuming non-pre-emptive execution on single processors (see [13] for a survey), and the impact of Cache Related Pre-emption Delays (CRPD) has been taken into account for multitasking systems [1], [2], [11]. However, research into adapting WCET techniques to address the challenges of multicore processors, and specifically the use of caches that are shared between two or more processors, is in its infancy. Many multicore processors make use of a cache hierarchy with private L1 caches per core and an L2 cache shared between cores. Sharing the L2 cache provides a significant performance boost over private L2 caches of the same total size, improving average-case performance and energy efficiency; however, the inter-core cache interference makes the WCET analysis problem extremely challenging. The problem is exacerbated by timing anomalies: The worst-case path for code executed in isolation may no longer be the worst-case path when inter-core cache contention is accounted for – see Figure 2 in [14]. The simplest and, as far as we are aware, the only compositional solution available so far is to assume that all L2 accesses are cache misses; however, as L2 latencies are typically high this is extremely pessimistic. Initial papers in this area [10], [14], [15], and [16] provide analysis which has complex dependencies on the detailed execution behaviour of contending tasks on other cores. However, details of the contending tasks may not necessarily be available for analysis, and even if they are, then such cross dependencies go against requirements for composability, which are necessary for the efficient development and integration of complex systems. II. PROBABILISTIC APPROACH One possible solution is to make use of randomisation techniques, in particular random cache replacement policies, which make the probability of pathological …
On MCMC sampling in Bayesian MLP neural networks

Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distributions. The integrals are generally approximated with Markov chain Monte Carlo (MCMC) methods. There are several practical issues which arise when implementing MCMC. This article discusses the choice of starting values and the number of chains in Bayesian MLP models. We propose a new method for choosing the starting values based on early stopping and we demonstrate the benefits of using several independent chains.
Mining API mapping for language migration

To address business requirements and to survive in competing markets, companies or open source organizations often have to release different versions of their projects in different languages. Manually migrating projects from one language to another (such as from Java to C#) is a tedious and error-prone task. To reduce manual effort or human errors, tools can be developed for automatic migration of projects from one language to another. However, these tools require the knowledge of how Application Programming Interfaces (APIs) of one language are mapped to APIs of the other language, referred to as API mapping relations. In this paper, we propose a novel approach, called MAM (Mining API Mapping), that mines API mapping relations from one language to another using API client code. MAM accepts a set of projects each with two versions in two languages and mines API mapping relations between those two languages based on how APIs are used by the two versions. These mined API mapping relations assist in migration of projects from one language to another. We implemented a tool and conducted two evaluations to show the effectiveness of MAM. The results show that our tool mines 25,805 unique mapping relations of APIs between Java and C# with more than 80% accuracy. The results also show that mined API mapping relations help reduce 54.4% compilation errors and 43.0% defects during migration of projects with an existing migration tool, called Java2CSharp. The reduction in compilation errors and defects is due to our new mined mapping relations that are not available with the existing migration tool.
Force–velocity trade‐off in Darwin's finch jaw function: a biomechanical basis for ecological speciation?

Summary 1. Biomechanical trade-offs have been proposed to constrain trajectories of evolutionary diversification. In songbirds, however, one such trade-off may facilitate diversification; adaptations that enhance bite force capacity are assumed to constrain vocal performance by hampering velocities of beak gape modulations required for vocal resonance tracking during song production. Resulting divergence in vocal mating signals may thus generate mating isolation between groups that eat foods of differing size and hardness. 2. We tested for a force‐velocity trade-off in jaw function in Darwin’s finches, by measuring bite forces and jaw movements during song production in birds on Santa Cruz Island. Bite force and speed of jaw closing varied broadly in our sample, and were negatively correlated both within and among species. Moreover, these correlations were largely independent of overall body size and phylogenetic relationships. 3. Adaptations to varying food types thus appear to drive divergence not only in beak size and bite force, but also in jaw closing velocity and vocal performance capacity. These results support a biomechanical link between adaptive divergence and mating signal divergence, the two key features that were assumed to have driven this radiation.
Performance-based design of distributed real-time systems

The paper presents a design method for distributed systems with statistical, end-to-end real-time constraints, and with underlying stochastic resource requirements. A system is modeled as a set of chains, where each chain is a distributed pipeline of tasks, and a task can represent any activity requiring nonzero load from some CPU or network resource. Every chain has two end-to-end performance requirements: its delay constraint denotes the maximum amount time a computation can take to flow through the pipeline, from input to output. A chain's quality constraint mandates a minimum allowable success rate for outputs that meet their delay constraints. The design method solves this problem by deriving (1) a fixed proportion of resource load to give each task; and (2) a deterministic processing rate for every chain, an which the objective is to optimize the output success rate (as determined by an analytical approximation). They demonstrate their technique on an example system, and compare the estimated success rates with those derived via simulated on-line behavior.
Structural investigation of InAs nanowires with coherent X-rays

Detailed knowledge of the internal structure of nanocrystals is of major importance in order to understand and monitor new physical properties. However, the experimental characterization remains challenging. The development of coherent X-ray sources at third-generation synchrotrons opens new possibilities based on the high sensitivity of the coherent beam with the internal nanocrystal displacement field. This paper aims at illustrating the use of coherent X-ray Bragg diffraction for crystalline defect investigation and lens-less imaging of morphology and strain. The two approaches are used to characterize an InAs nanowire sample. Limits of the method and near-future perspectives are discussed in the framework of strain analysis in nanocrystals.
Adaptation of the AhoTTS Text to Speech System to PDA Platfoms

This paper presents the work carried on to adapt a Basque language Text-To-Speech (TTS) system into a mobile device of limited resources. The aim is to make possible the use of the AhoTTS conversion system of the UPV/EHUs Aholab group, in a Personal Digital Assistant (PDA), and to test the system performance in several aspects, such as sound sample generation times. The selected PDA is a Pocket PC under the Windows CE operating system. The converter has been compiled in a library which provides an Application Programming Interface (API) to the applications. Some applications that use the created API are also described.
Investigating Markov model discriminationfor ion channelsBY

Hodgson (1999) formulates a Bayesian method of ion channel analysis, in which he uses an alternating renewal model of channel kinetics and an autore-gressive process to model patch clamp noise. He computes the resulting posterior by a reversible jump Markov chain Monte Carlo method (Green 1995). Our focus here is on extending this analysis to the more physically realistic hidden Markov models of channel dynamics. Here, the states of the channel are partitioned into classes of states having the same conductance, so that patch clamp recording is informative only about the aggregated process. This loss of information increases the challenge of making structural inference about the underlying Markov chain. The study we present, involving discrimination between a few simple models, serves to give some indication as to the feasibility of more general Markov model determination for ion channels. 1 Hidden Markov models for ion channels Ion channels, large proteins spanning cell membranes, are thought to exist in a nite number of physicochemically distinct states, some of which allow the passage of current in the form of selected ions. Their kinetics are most frequently modelled by a continuous-time Markov chain in which the state space is partitioned into classes of states having the same conductance. Since it is the current through the channel which is measured (with noise), states having the same con-ductance are indistinguishable. A thorough exposition of the relevant theoretical properties of hidden Markov models is given by Colquhoun and Hawkes (1982). In theory the technique of patch clamp recording (see, for example, Sakmann and Neher 1995) reveals which class the channel state belongs to, so that inference about the postulated`hidden' Markov chain may be based on this so-calledàg-gregated' process. Such inference is the subject of Fredkin and Rice (1986). In practice, degradation of patch clamp records by additive noise and ltering prior to digitisation further complicates the statistician's task. We restrict attention to the usual case of just two conductance classes, termedòpen' and`closed'. A conventional algorithm to restore the true channel current from a patch clamp record involves thresholding followed by the deletion of apparent sojourns in either class of duration less than some critical value, a practice known as \time interval omission". The use of the thresholded signal as data, with and without time interval omission, in making inference about hidden Markov models has 1
Influence of grinding on graphite crystallinity from experimental and natural data: implications for graphite thermometry and sample preparation

Abstract This paper examines the effects of shear stress on the structural parameters that define the ‘crystallinity’ of graphite. The results show that highly crystalline graphite samples ground for up to 120 min do not undergo detectable changes in the three-dimensional arrangement of carbon layers but crystallite sizes (Lc and La) decrease consistently with increasing grinding time. Grinding also involves particle-size diminution that results in lower temperatures for the beginning of combustion and exothermic maxima in the differential thermal analysis curves. These changes in the structural and thermal characteristics of graphite upon grinding must be taken into account when such data are used for geothermometric estimations. Tectonic shear stress also induces reduction of the particle size and the Lc and La values of highly crystalline graphite. Thus, the temperature of formation of graphite according to structural as well as thermal data is underestimated by up to 100°C in samples that underwent the most intense shear stress. Therefore, application of graphite geothermometry to fluid-deposited veins where graphite is the only mineral found should take into consideration the effect of tectonic shearing, or the estimated temperatures must be considered as minimum temperatures of formation only.
Adventitial CXCL1/G-CSF Expression in Response to Acute Aortic Dissection Triggers Local Neutrophil Recruitment and Activation Leading to Aortic Rupture

Rationale: In-hospital outcomes are generally acceptable in patients with type B dissection; however, some patients present with undesirable complications, such as aortic expansion and rupture. Excessive inflammation is an independent predictor of adverse clinical outcomes. Objective: We have investigated the underlying mechanisms of catastrophic complications after acute aortic dissection (AAD) in mice. Methods and Results: When angiotensin II was administered in lysyl oxidase inhibitor–preconditioned mice, AAD emerged within 24 hours. The dissection was initiated at the proximal site of the descending thoracic aorta and propagated distally into an abdominal site. Dissection of the aorta caused dilatation, and ≈70% of the mice died of aortic rupture. AAD triggered CXCL1 and granulocyte-colony stimulating factor expression in the tunica adventitia of the dissected aorta, leading to elevation of circulating CXCL1/granulocyte-colony stimulating factor levels. Bone marrow CXCL12 was reduced. These chemokine changes facilitated neutrophil egress from bone marrow and infiltration into the aortic adventitia. Interference of CXCL1 function using an anti-CXCR2 antibody reduced neutrophil accumulation and limited aortic rupture post AAD. The tunica adventitia of the expanded dissected aorta demonstrated high levels of interleukin-6 (IL-6) expression. Neutrophils were the major sources of IL-6, and CXCR2 neutralization significantly reduced local and systemic levels of IL-6. Furthermore, disruption of IL-6 effectively suppressed dilatation and rupture of the dissected aorta without any influence on the incidence of AAD and neutrophil mobilization. Conclusions: Adventitial CXCL1/granulocyte-colony stimulating factor expression in response to AAD triggers local neutrophil recruitment and activation. This leads to adventitial inflammation via IL-6 and results in aortic expansion and rupture.
Towards a Novel Issue Tracking System for "Industry 4.0" Environments

In this paper we describe the concept and system design of a novel tracking system for deviations and disturbances in a production environment. We motivate the need for such a system by reporting our observations of two production systems of German manufacturing companies. Our envisioned system focuses on helping and motivating people to digitally document the problems, potential causes and steps to overcome the issues more thoroughly and provide capabilities that make these easily accessible at the point in time when they are needed. Such a functionality is not only helpful for problem solving in the general production system itself, but can also be used for other specific aspects of it, e.g. errors requiring documentation in the manual end-assembly that can also profit from the same strategies.
SiC/SiC Ceramic Matrix Composites Developed for High-Temperature Space Transportation Applications

Researchers at the NASA Glenn Research Center have been developing durable, high-temperature ceramic matrix composites (CMCs) with silicon carbide (SiC) matrices and SiC or carbon fibers for use in advanced reusable launch vehicle propulsion and airframe applications in the Next Generation Launch Technology (NGLT) Program. These CMCs weigh less and are more durable than competing metallic alloys, and they are tougher than silicon-based monolithic ceramics. Because of their high specific strength and durability at high temperatures, CMCs such as C/SiC (carbon- fiber-reinforced silicon carbide) and SiC/SiC (silicon-carbide-fiber-reinforced silicon carbide) may increase vehicle performance and safety significantly and reduce the cost of transporting payloads to orbit.
Towards an agent-based symbiotic architecture for autonomic management of virtualized data centers

The increasing scale and complexity of virtualized data centers pose significant challenges to system management software stacks, which still rely on special-purpose controllers to optimize the operation of cloud infrastructures. Autonomic computing allows complex systems to assume much of their own management, achieving self-configuration, self-optimization, self-healing, and self-protection without external intervention. This paper proposes an agent-based architecture for autonomic cloud management, where resources and virtual machines are associated with worker agents that monitor changes in their local environments, interact with each other, make their own decisions, and take adaptive actions supervised by a network of management processes. To fulfill global objectives, the management processes conduct what-if simulations and update the worker agents' local rules when necessary. Such a guided decentralized decision making method can mitigate the pressure on the system management stack, improve the effectiveness of resource management, and accelerate the response to failures and attacks.
Recent advances in the understanding of renal inflammation and fibrosis in lupus nephritis

Lupus nephritis is a potentially reversible cause of severe acute kidney injury and is an important cause of end-stage renal failure in Asians and patients of African or Hispanic descent. It is characterized by aberrant exaggerated innate and adaptive immune responses, autoantibody production and their deposition in the kidney parenchyma, triggering complement activation, activation and proliferation of resident renal cells, and expression of pro-inflammatory and chemotactic molecules leading to the influx of inflammatory cells, all of which culminate in destruction of normal nephrons and their replacement by fibrous tissue. Anti-double-stranded DNA (anti-dsDNA) antibody level correlates with disease activity in most patients. There is evidence that apart from mediating pathogenic processes through the formation of immune complexes, pathogenic anti-dsDNA antibodies can bind to resident renal cells and induce downstream pro-apoptotic, pro-inflammatory, or pro-fibrotic processes or a combination of these. Recent data also highlight the critical role of macrophages in acute and chronic kidney injury. Though clinically effective, current treatments for lupus nephritis encompass non-specific immunosuppression and the anti-inflammatory action of high-dose corticosteroids. The clinical and histological impact of novel biologics targeting pro-inflammatory molecules remains to be investigated. Insight into the underlying mechanisms that induce inflammatory and fibrotic processes in the kidney of lupus nephritis could present opportunities for more specific novel treatment options to improve clinical outcomes while minimizing off-target untoward effects. This review discusses recent advances in the understanding of pathogenic mechanisms leading to inflammation and fibrosis of the kidney in lupus nephritis in the context of established standard-of-care and emerging therapies.
Continued warming could transform Greater Yellowstone fire regimes by mid-21st century

Climate change is likely to alter wildfire regimes, but the magnitude and timing of potential climate-driven changes in regional fire regimes are not well understood. We considered how the occurrence, size, and spatial location of large fires might respond to climate projections in the Greater Yellowstone ecosystem (GYE) (Wyoming), a large wildland ecosystem dominated by conifer forests and characterized by infrequent, high-severity fire. We developed a suite of statistical models that related monthly climate data (1972–1999) to the occurrence and size of fires >200 ha in the northern Rocky Mountains; these models were cross-validated and then used with downscaled (∼12 km × 12 km) climate projections from three global climate models to predict fire occurrence and area burned in the GYE through 2099. All models predicted substantial increases in fire by midcentury, with fire rotation (the time to burn an area equal to the landscape area) reduced to <30 y from the historical 100–300 y for most of the GYE. Years without large fires were common historically but are expected to become rare as annual area burned and the frequency of regionally synchronous fires increase. Our findings suggest a shift to novel fire–climate–vegetation relationships in Greater Yellowstone by midcentury because fire frequency and extent would be inconsistent with persistence of the current suite of conifer species. The predicted new fire regime would transform the flora, fauna, and ecosystem processes in this landscape and may indicate similar changes for other subalpine forests.