Miracle-dz/UniFAR-FTUs huggingface dataset:
Ju n 20 06 Galactic Nuclei and Jets in Wave Gravity

“Wave gravity” refers to a quantum-mechanical gravity theo ry introduced in two previous papers [1, 2]. Although based on t he optics of de Broglie waves instead of curved space-time, it agrees w ith the standard tests of general relativity. As in that theory, gal actic nuclei are dark objects where gravity prevents the escape of most ra diation. In this case, collapse is counteracted by rising internal pr essure and black hole singularities don’t occur. Unlike black holes, t hese nuclei can have internal magnetic fields, and high-energy plasma ca n escape along magnetic field lines closely aligned with the gravitat ional field direction. This allows a different model of jets from active galactic nuclei, where jets can arise without direct fueling by accreti on disks. It also offers a new basis for the tight correlation observed [1 3] between the masses of galactic nuclei and their hosts.
Exploring the Neural Mechanisms Supporting Structured Sequence Processing and Language Using Event-Related Potentials: Some Preliminary Findings

Structured sequence processing (SSP) refers to the neurocognitive mechanisms used to learn sequential patterns in the environment. SSP ability seems to be important for language (Conway, Bauernschmidt, Huang, & Pisoni, 2010); however, there are few neural studies showing an empirical connection between SSP and language. The purpose of this study was to investigate the association between SSP and language processing by comparing the underlying neural components elicited during each type of task. Healthy adult subjects completed a visual, non-linguistic SSP task incorporating an artificial grammar and a visual morphosyntactic language task. Both tasks were designed to cause violations in expectations of items occurring in a series. Event-related potentials (ERPs) were used to examine the underlying neural mechanisms associated with these expectancy violations. The results indicated the P3a component elicited by the SSP task and the P600 component elicited by the language task shared similarities in their topographic distribution. These preliminary analyses suggest that the P3a and P600 may reflect processes involving detection of sequential violations in non-language and language domains, which is consistent with the idea that language processing relies on general-purpose SSP mechanisms.
Surface reconstruction of laser scanner data using piecewise RBF methods

Digital, three-dimensional models of real world objects are required for many applications. These can be obtained by fitting global radial basis functions to point cloud data captured using laser scanners, a process that can be computationally intensive for large data sets. A faster approach is to evaluate a number of local radial basis functions and combine these into a complete representation. This paper demonstrates a partition of unity approach to this problem, adapted from a method outlined in Tobor et al. [Journal of WSCG, Vol.12, No.1-3, 2004]. Results are presented for synthetic and real point cloud data captured with a FastSCANtrade laser scanner, using standard and novel isosurfacing methods.
Multi-Hop-Enabled Energy-Efficient MAC Protocol for Underwater Acoustic Sensor Networks

In multi-hop underwater acoustic sensor networks (UWASNs), packet collisions due to hidden and local nodes adversely affect throughput, energy efficiency and end-to-end delay. Existing medium access control (MAC) protocols try to solve the problem by utilizing a single-phase contention resolution mechanism, which causes a large number of control packet exchanges and energy overhead. In this paper, we introduce a MAC protocol that splits this single-phase contention resolution mechanism into two phases to provide efficient multi-hop networking. In the first phase, local nodes are eliminated from the contention, and in the later phase, the adverse effects of hidden nodes are mitigated. This two-phased contention resolution provides higher energy efficiency, better throughput and shorter end-to-end delay, and it also enables adaptability for different network architectures. A probabilistic model of the proposed protocol is also developed to analyse the performance. The proposed protocol has been evaluated through quantitative analysis and simulation. Results obtained through quantitative analysis and simulation reveal that the proposed protocol achieves significantly better energy efficiency, higher and more stable throughput and lower end-to-end delay compared to existing protocols, namely T-Lohi and slotted floor acquisition multiple access (S-FAMA).
EMG based approach for wearer-centered control of a knee joint actuated orthosis

This paper presents a new human-exoskeleton interaction approach to provide torque assistance of the lower limb movements upon wearer's intention. The exoskeleton interacts with the wearer; the shank-foot orthosis system behaves as a second order dynamic system with gravity and elastic torque balance. The intention of the wearer is estimated by using a realistic musculoskeletal model of the muscles actuating the knee joint. The identification process concerns the inertial parameters of the shank-foot, the exoskeleton and the musculotendon parameters. Real-time experiments, conducted on a healthy subject during flexion and extension movements of the knee joint, have shown satisfactory results in terms of tracking error, intention detection and assistance torque generation. This approach guarantees asymptotic stability of the shank-foot-exoskeleton and adaptation to human-exoskeleton interaction. Moreover, the proposed control law is robust with respect to external disturbances.
On the Usage of GRECOSAR, an Orbital Polarimetric SAR Simulator of Complex Targets, to Vessel Classification Studies

This paper presents a synthetic aperture radar (SAR) simulator that is able to generate polarimetric SAR (POLSAR) and polarimetric inverse SAR data of complex targets. It solves the electromagnetic problem via high-frequency approximations, such as physical optics and the physical theory of diffraction, with notable computational efficiency. In principle, any orbital monostatic sensor working at any band, resolution, and operating mode can be modeled. To make simulations more realistic, the target's bearing and speed are considered, and for the particular case of vessels, even the translational and rotational movements induced by the sea state. All these capabilities make the simulator a powerful tool for supplying large amounts of data with precise scenario information and for testing future sensor configurations. In this paper, the usefulness of the simulator on vessel classification studies is assessed. Several simulated polarimetric images are presented to analyze the potentialities of coherent target decompositions for classifying complex geometries, thus basing an operational algorithm. The limitations highlighted by the results suggest that other approaches, like POLSAR interferometry, should be explored
Influence of pre-infarction angina, collateral flow, and pre-procedural TIMI flow on myocardial salvage index by cardiac magnetic resonance in patients with ST-segment elevation myocardial infarction.

BACKGROUND In patients with ST-segment elevation myocardial infarction (STEMI) pre-infarction angina, pre-procedural TIMI flow and collateral flow to the myocardium supplied by the infarct related artery are suggested to be cardioprotective. We evaluated the effect of these factors on myocardial salvage index (MSI) and infarct size adjusting for area at risk in patients with STEMI treated with primary percutaneous coronary intervention. METHODS AND RESULTS Cardiac magnetic resonance (CMR) was used to measure myocardial area at risk within 1-7 days and final infarct size 90 ± 21 days after the STEMI in 200 patients. MSI was calculated as (area-at-risk infarct size) / area-at-risk. Patients with pre-infarction angina had a median MSI of 0.80 (IQR 0.67 to 0.86) versus 0.72 (0.61 to 0.80) in those without pre-infarction angina, P = 0.004). In a regression analysis of the infarct size plotted against the area-at-risk there was a strong trend that the line for the pre-infarction angina group was below the one for the non-angina group (P = 0.05). Patients with pre-procedural TIMI flow 0/1, 2 and 3 had a median MSI of (0.69 (IQR 0.59 to 0.76), 0.78 (0.68 to 0.86) and 0.85 (0.77 to 0.91), respectively (P<0.001). Collateral flow did not change MSI (P = 0.45) nor area-at-risk (P = 0.40) and no significant difference in infarct size adjusted for area at risk (P = 0.25) was observed. CONCLUSIONS Pre-infarction angina increases MSI in patients with STEMI supporting the theory that pre-infarction angina leads to ischemic preconditioning. As opposed to the presence of angiographically visible collateral flow to the infarct area pre-procedural TIMI flow is strongly associated with MSI.
Recessively inherited L-DOPA-responsive parkinsonism in infancy caused by a point mutation (L205P) in the tyrosine hydroxylase gene.

Tyrosine hydroxylase (TH) catalyzes the conversion of L-tyrosine to L-dihydroxyphenylalanine (L-DOPA), the rate-limiting step in the biosynthesis of dopamine. This report describes a missense point mutation in the human TH (hTH) gene in a girl presenting parkinsonian symptoms in early infancy and a very low level of the dopamine metabolite homovanillic acid in the CSF. DNA sequencing revealed a T614-to-C transition in exon 5 (L205P). Both parents and the patient's brother are heterozygous for the mutation. Site-directed mutagenesis and expression in different systems revealed that the recombinant mutant enzyme had a low homospecific activity, i.e. approximately 1.5% of wt-hTH in E. coli and approximately 16% in a cell-free in vitro transcription-translation system. When transiently expressed in human embryonic kidney (A293) cells a very low specific activity (approximately 0.3% of wt-hTH) and immunoreactive hTH (< 2%) was obtained. The expression studies are compatible with the severe clinical phenotype of the L205P homozygous patient carrying this recessively inherited mutation. Treatment with L-DOPA resulted in normalisation of the CSF homovanillic acid concentration and a sustained improvement in parkinsonian symptoms.
Complement C1s activation in degenerating articular cartilage of rheumatoid arthritis patients: immunohistochemical studies with an active form specific antibody

OBJECTIVE The first complement component C1s was reported to have novel functions to degrade matrix components, besides its activities in the classic complement pathway. This study explores participation of C1s in articular cartilage degradation in rheumatoid arthritis (RA). METHODS Normal articular cartilage (n=6) and cartilage obtained from joints with RA (n=15) and osteoarthritis (OA, n=10) were immunostained using anti-C1s monoclonal antibodies PG11, which recognises both active and inactive C1s, and M241, which is specifically reactive to activated C1s. The effects of inflammatory cytokines on C1s production by human articular chondrocytes were also examined by sandwich ELISA. RESULTS In normal articular cartilage, C1s was negative in staining with both PG11 and M241. In contrast, degenerating cartilage of RA was stained with PG11 (14 of 15 cases), and in most of the cases (13 of 15 cases) C1s was activated as revealed by M241 staining. In OA, C1s staining was restricted in severely degrading part of cartilage (5 of 10 cases), and even in that part C1s was not activated. In addition, C1s production by chondrocytes in vitro was increased by an inflammatory cytokine, tumour necrosis factor α. CONCLUSION These results suggest that C1s activated in degenerative cartilage matrix of RA but not in that of OA. C1s is thought to participate in the pathogenesis of RA through its collagenolytic activity in addition to the role in the classic cascade.
Design metrics for gate oxide leakage characterisation in nano-CMOS transistors

In this paper, we propose a set of novel metrics, of primary interest to modelling and design engineers, for characterising the impact of gate oxide tunnelling current in nanoscale CMOS (nano-CMOS) devices. We concentrate on three distinct quantities: (i) steady-state on current (ION ); (ii) steady-state off current (IOFF ); and (iii) effective tunnelling capacitance during transitions (C t eff ). We define C t eff as the change in tunnelling current with respect to the rate of change of input voltage, which represents the capacitive load of the transistor due to tunnelling. This concisely encapsulates both qualitative as well as quantitative information about the swing in tunnelling current during state transitions, while simultaneously accounting for the transition rate. We also investigate, via Monte Carlo simulations, the effect of process and design variations on the metrics. To the best of our knowledge, this is the first ever work that quantifies gate leakage during state transitions through the use of C t eff
Modeling Occlusion by Discriminative AND-OR Structures

Occlusion presents a challenge for detecting objects in real world applications. To address this issue, this paper models object occlusion with an AND-OR structure which (i) represents occlusion at semantic part level, and (ii) captures the regularities of different occlusion configurations (i.e., the different combinations of object part visibilities). This paper focuses on car detection on street. Since annotating part occlusion on real images is time-consuming and error-prone, we propose to learn the the AND-OR structure automatically using synthetic images of CAD models placed at different relative positions. The model parameters are learned from real images under the latent structural SVM (LSSVM) framework. In inference, an efficient dynamic programming (DP) algorithm is utilized. In experiments, we test our method on both car detection and car view estimation. Experimental results show that (i) Our CAD simulation strategy is capable of generating occlusion patterns for real scenarios, (ii) The proposed AND-OR structure model is effective for modeling occlusions, which outperforms the deformable part-based model (DPM) DPM, voc5 in car detection on both our self-collected street parking dataset and the Pascal VOC 2007 car dataset pascal-voc-2007}, (iii) The learned model is on-par with the state-of-the-art methods on car view estimation tested on two public datasets.
The Godbillon-Vey class, invariants of manifolds and linearised M-Theory

We apply the Godbillon-Vey class to compute the transition amplitudes between some non-commutative solitons in M-Theory; our context is that of Connes-Douglas-Schwarz where they considered compactifications of matrix models on noncommutative tori. Two important consequences follow: we describe a new normalisation for the Abelian Chern-Simons theory using symplectic 4-manifolds as providing cobordisms for tight contact 3-manifolds and we construct a new(? ) invariant for 3-manifolds. Moreover we modify the topological Lagrangian density suggested for M-Theory in a previous article to a \textsl{quadratic} one using the fact that the \emph{functor of immersions is a linearisation (or ``the differential'') of the functor of embeddings}
Root Architecture Diversity and Meristem Dynamics in Different Populations of Arabidopsis thaliana

Arabidopsis thaliana has been an excellent model system for molecular genetic approaches to development and physiology. More recently, the potential of studying various accessions collected from diverse habitats has been started to exploit. Col-0 has been the best-studied accession but we now know that several traits show significant divergences among them. In this work, we focused in the root that has become a key system for development. We studied root architecture and growth dynamics of 12 Arabidopsis accessions. Our data reveal a wide variability in root architecture and root length among accessions. We also found variability in the root apical meristem (RAM), explained mainly by cell size at the RAM transition domain and possibly by peculiar forms of organization at the stem cell niche in some accessions. Contrary to Col-0 reports, in some accessions the RAM size not always explains the variations in the root length; indicating that elongated cell size could be more relevant in the determination of root length than the RAM size itself. This study contributes to investigations dealing with understanding the molecular and cellular basis of phenotypic variation, the role of plasticity on adaptation, and the developmental mechanisms that may restrict phenotypic variation in response to contrasting environmental conditions.
Aligning parallel arrays to reduce communication

Axis and stride alignment is an important optimization in compiling data-parallel programs for distributed-memory machines. We previously developed an optimal algorithm for aligning array expressions. Here, we examine alignment for more general program graphs. We show that optimal alignment is NP-complete in this setting, so we study heuristic methods. This paper makes two contributions. First, we show how local graph transformations can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. Second, we give a heuristic that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. Our algorithms have been implemented; we present experimental results showing their effect on the performance of some example programs running on the CM-5. <<ETX>>
Leading toward new horizons with soft skills

Purpose This paper aims to highlight the importance of soft skills for leadership and offers recommendations for soft skill development training for the next generation of leaders. Design/methodology/approach An integrated review of current research literature was conducted on management, leadership and soft skills to develop recommendations for integrating the development of soft skills in leadership development training protocol. Findings A one-size-fits-all approach does not work for soft skills development or measurement. Each soft skill is defined differently and should be assessed based on different behavioral actions. Progress in this area of measurement development will make a great impact on the use of soft skills. The development of assessment tools for the different soft skills across professional disciplines is assumed to enhance other aspects of transformational leadership such as coaching and mentoring. Research limitations/implications Current strategies for the assessment and measurement of soft skills present an obstacle for including these skills in current leadership training models. Practical implications The paper includes implications for the development of soft skills for the next generation of leaders and offers recommendations for integrating the development of soft skills in leadership training programs. Originality/value This paper fulfills an identified need to study how soft skills can be measured and assessed. This is important given that specific skills vary across professional disciplines and organizational contexts.
Observation and Abstract Behaviour in Specification and Implementation of State-based Systems

Classical algebraic specification is an accepted framework for specification. A criticism which applies is the fact that it is functional, not based on a notion of state as most software development and implementation languages are. We formalise the idea of a state-based object or abstract machine using algebraic means. In contrast to similar approaches we consider dynamic logic instead of equational logic as the framework for specification and implementation. The advantage is a more expressive language allowing us to specify safety and liveness conditions. It also allows a clearer distinction of functional and state-based parts which require different treatment in order to achieve behavioural abstraction when necessary. We shall in particular focus on abstract behaviour and observation. A behavioural notion of satisfaction for state-elements is needed in order to abstract from irrelevant details of the state realisation.
Dependence-Maximization Clustering with Least-Squares Mutual Information

Recently, statistical dependence measures such as mutual information and kernelized covariance have been successfully applied to clustering, called dependencemaximization clustering. In this paper, we propose a novel dependencemaximization clustering method based on an estimator of a squared-loss variant of mutual information called least-squares mutual information. A notable advantage of the proposed method over existing ones is that hyperparameters such as kernel parameters and regularization parameters can be objectively optimized based on cross-validation. Thus, subjective manual-tuning of hyperparameters is not necessary in the proposed method, which is a highly useful property in unsupervised clustering scenarios. Through experiments, we illustrate the usefulness of the proposed approach.
GALOIS GROUPS OF SCHUBERT PROBLEMS OF LINES ARE AT LEAST ALTERNATING

We show that the Galois group of any Schubert problem involving lines in projective space contains the alternating group. This constitutes the largest family of enu- merative problems whose Galois groups have been largely determined. Using a criterion of Vakil and a special position argument due to Schubert, our result follows from a particular inequality among Kostka numbers of two-rowed tableaux. In most cases, a combinatorial injection proves the inequality. For the remaining cases, we use the Weyl integral formula to obtain an integral formula for these Kostka numbers. This rewrites the inequality as an integral, which we estimate to establish the inequality.
Nominal (Universal) Algebra: Equational Logic with Names and Binding

In informal mathematical discourse (such as the text of a paper on theoretical computer science), we often reason about equalities involving binding of object-variables. We find ourselves writing assertions involving meta-variables and captureavoidance constraints on where object-variables can and cannot occur free. Formalizing such assertions is problematic because the standard logical frameworks cannot express capture-avoidance constraints directly. In this article, we make the case for extending the logic of equality with meta-variables and capture-avoidance constraints, to obtain ‘nominal algebra’. We use nominal techniques that allow for a direct formalization of meta-level assertions, while remaining close to informal practice. We investigate proof-theoretical properties, we provide a sound and complete semantics in nominal sets and we compare and contrast our design decisions with other possibilities leading to similar systems.
Hellinger Versus Kullback–Leibler Multivariable Spectrum Approximation

In this paper, we study a matricial version of a generalized moment problem with degree constraint. We introduce a new metric on multivariable spectral densities induced by the family of their spectral factors, which, in the scalar case, reduces to the Hellinger distance. We solve the corresponding constrained optimization problem via duality theory. A highly nontrivial existence theorem for the dual problem is established in the Byrnes-Lindquist spirit. A matricial Newton-type algorithm is finally provided for the numerical solution of the dual problem. Simulation indicates that the algorithm performs effectively and reliably.