A Type-Theoretic Account of Neg-Raising Predicates in Tree Adjoining Grammars

International audienceNeg-Raising (NR) verbs form a class of verbs with a clausal complement that show the following behavior: when a negation syntactically attaches to the matrix predicate, it can semantically attach to the embedded predicate. This paper presents an account of NR predicates within Tree Adjoining Grammar (TAG). We propose a lexical semantic interpretation that heavily relies on a Montague-like semantics for TAG and on higher-order types

Exploring the measurement of markedness and its relationship with other linguistic variables

Antonym pair members can be differentiated by each word's markedness-that distinction attributable to the presence or absence of features at morphological or semantic levels. Morphologically marked words incorporate their unmarked counterpart with additional morphs (e.g., "unlucky" vs. "lucky"); properties used to determine semantically marked words (e.g., "short" vs. "long") are less clearly defined. Despite extensive theoretical scrutiny, the lexical properties of markedness have received scant empirical study. The current paper employs an antonym sequencing approach to measure markedness: establishing markedness probabilities for individual words and evaluating their relationship with other lexical properties (e.g., length, frequency, valence). Regression analyses reveal that markedness probability is, as predicted, related to affixation and also strongly related to valence. Our results support the suggestion that antonym sequence is reflected in discourse, and further analysis demonstrates that markedness probabilities, derived from the antonym sequencing task, reflect the ordering of antonyms within natural language. In line with the Pollyanna Hypothesis, we argue that markedness is closely related to valence; language users demonstrate a tendency to present words evaluated positively ahead of those evaluated negatively if given the choice. Future research should consider the relationship of markedness and valence, and the influence of contextual information in determining which member of an antonym pair is marked or unmarked within discourse

3D deep convolutional neural network-based ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI

Hyperpolarized gas MRI enables visualization of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. In this work, we evaluate a 3D V-Net to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 743 helium-3 (3He) or xenon-129 (129Xe) volumetric scans and corresponding expert segmentations from 326 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined 3He and 129Xe MRI scans outperformed other DL methods, achieving a mean ± SD Dice of 0.958 ± 0.022, average boundary Hausdorff distance of 2.22 ± 2.16 mm, Hausdorff 95th percentile of 8.53 ± 12.98 mm and relative error of 0.087 ± 0.049. Moreover, no difference in performance was observed between 129Xe and 3He scans in the testing set. Combined training on 129Xe and 3He yielded statistically significant improvements over the conventional methods (p < 0.0001). The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and noise artifacts and is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing

Cisplatin-induced emesis: systematic review and meta-analysis of the ferret model and the effects of 5-HT3 receptor antagonists

PURPOSE: The ferret cisplatin emesis model has been used for ~30 years and enabled identification of clinically used anti-emetics. We provide an objective assessment of this model including efficacy of 5-HT(3) receptor antagonists to assess its translational validity. METHODS: A systematic review identified available evidence and was used to perform meta-analyses. RESULTS: Of 182 potentially relevant publications, 115 reported cisplatin-induced emesis in ferrets and 68 were included in the analysis. The majority (n = 53) used a 10 mg kg(−1) dose to induce acute emesis, which peaked after 2 h. More recent studies (n = 11) also used 5 mg kg(−1), which induced a biphasic response peaking at 12 h and 48 h. Overall, 5-HT(3) receptor antagonists reduced cisplatin (5 mg kg(−1)) emesis by 68% (45–91%) during the acute phase (day 1) and by 67% (48–86%) and 53% (38–68%, all P < 0.001), during the delayed phase (days 2, 3). In an analysis focused on the acute phase, the efficacy of ondansetron was dependent on the dosage and observation period but not on the dose of cisplatin. CONCLUSION: Our analysis enabled novel findings to be extracted from the literature including factors which may impact on the applicability of preclinical results to humans. It reveals that the efficacy of ondansetron is similar against low and high doses of cisplatin. Additionally, we showed that 5-HT(3) receptor antagonists have a similar efficacy during acute and delayed emesis, which provides a novel insight into the pharmacology of delayed emesis in the ferret

Three-Dimensional Object Registration Using Wavelet Features

Recent developments in shape-based modeling and data acquisition have brought three-dimensional models to the forefront of computer graphics and visualization research. New data acquisition methods are producing large numbers of models in a variety of fields. Three-dimensional registration (alignment) is key to the useful application of such models in areas from automated surface inspection to cancer detection and surgery. The algorithms developed in this research accomplish automatic registration of three-dimensional voxelized models. We employ features in a wavelet transform domain to accomplish registration. The features are extracted in a multi-resolutional format, thus delineating features at various scales for robust and rapid matching. Registration is achieved by using a voting scheme to select peaks in sets of rotation quaternions, then separately identifying translation. The method is robust to occlusion, clutter, and noise. The efficacy of the algorithm is demonstrated through examples from solid modeling and medical imaging applications

Granulocyte-colony stimulating factor for stroke treatment: mechanisms of action and efficacy in preclinical studies

G-CSF is widely employed for the treatment of chemotherapy-induced neutropenia. Recently, neuroprotective effects of G-CSF in animal stroke models were discovered including infarct size reduction and enhancement of functional recovery. The underlying mechanisms of action of G-CSF in ischemia appear to be a direct anti-apoptotic activity in neurons and a neurogenesis inducing capacity. Additional effects may be based on the stimulation of new blood-vessel formation, the stimulation of immunocompetence and -modulation as well as on bone marrow mobilization. In addition to a discussion of these mechanisms, we will review the available preclinical studies and analyze their impact on the overall efficacy of G-CSF in experimental stroke

Evolutionary and pulsational properties of white dwarf stars

Abridged. White dwarf stars are the final evolutionary stage of the vast majority of stars, including our Sun. The study of white dwarfs has potential applications to different fields of astrophysics. In particular, they can be used as independent reliable cosmic clocks, and can also provide valuable information about the fundamental parameters of a wide variety of stellar populations, like our Galaxy and open and globular clusters. In addition, the high densities and temperatures characterizing white dwarfs allow to use these stars as cosmic laboratories for studying physical processes under extreme conditions that cannot be achieved in terrestrial laboratories. They can be used to constrain fundamental properties of elementary particles such as axions and neutrinos, and to study problems related to the variation of fundamental constants. In this work, we review the essentials of the physics of white dwarf stars. Special emphasis is placed on the physical processes that lead to the formation of white dwarfs as well as on the different energy sources and processes responsible for chemical abundance changes that occur along their evolution. Moreover, in the course of their lives, white dwarfs cross different pulsational instability strips. The existence of these instability strips provides astronomers with an unique opportunity to peer into their internal structure that would otherwise remain hidden from observers. We will show that this allows to measure with unprecedented precision the stellar masses and to infer their envelope thicknesses, to probe the core chemical stratification, and to detect rotation rates and magnetic fields. Consequently, in this work, we also review the pulsational properties of white dwarfs and the most recent applications of white dwarf asteroseismology.Comment: 85 pages, 28 figures. To be published in The Astronomy and Astrophysics Revie