θ-structures of Mandarin Resultative Verb Compounds

Mandarin Resultative Verb Compounds, different from any simplex words, have complicated θ-structures, since both the verb (Vcaus) and its complement (Cres) have the capacity of assigning their own thematic roles. The thematic roles assigned by Vcaus form the θ-structure’s main structure, and those assigned by Cres form the embedded structure. Sometimes an entity plays a role in the main structure, and at the same time plays a role in the embedded structure. If the two roles are identical, they are “coindexed”; if they are different, they form a composite role. RVC’s θ-structure is further compounded when ambiguity occurs and when causation is taken into consideration. The ambiguity of RVCs can be attributed to the different combination of thematic roles. As for causation, the two causative roles, causer and cause, can be assigned to thematic roles according to certain constraints

The Mapping of Thematic Roles to Grammatical Functions in Mandarin BA Construction Denoting Causation: From the Perspective of Lexical Mapping Theory

NP1 in the position of the subject of the mandarin BA construction denoting causation is usually occupied by patientlike roles and NP2 immediately following BA is usually occupied by agentlike roles. The causative relation between NP1 and NP2, with the former being the Cause, and the latter the Affectee, derives from the word BA, which triggers in the lexicon the morpholexical operation of causativization when it unites with the predicate. The operation involves either assignment of causative roles Cause and Affectee to the existent thematic roles or insertion of a new role Cause to the thematic structure, with the prominence of Cause or the thematic role assigned Cause always being over the other roles. Having undergone this morpholexical operation, the thematic structure correctly maps to and generates the grammatical functional structure according to the general principles and conditions stipulated by the Lexical Mapping Theory (LMT). The result of this research shows that even for a construction as unique as the mandarin BA construction denoting causation compared with any other languages, LMT is still well applicable in explaining its role-function mapping

On Input-to-State Stability of Impulsive Stochastic Systems with Time Delays

This paper is concerned with pth moment input-to-state stability (p-ISS) and stochastic input-to-state stability (SISS) of impulsive stochastic systems with time delays. Razumikhin-type theorems ensuring p-ISS/SISS are established for the mentioned systems with external input affecting both the continuous and the discrete dynamics. It is shown that when the impulse-free delayed stochastic dynamics are p-ISS/SISS but the impulses are destabilizing, the p-ISS/SISS property of the impulsive stochastic systems can be preserved if the length of the impulsive interval is large enough. In particular, if the impulse-free delayed stochastic dynamics are p-ISS/SISS and the discrete dynamics are marginally stable for the zero input, the impulsive stochastic system is p-ISS/SISS regardless of how often or how seldom the impulses occur. To overcome the difficulties caused by the coexistence of time delays, impulses, and stochastic effects, Razumikhin techniques and piecewise continuous Lyapunov functions as well as stochastic analysis techniques are involved together. An example is provided to illustrate the effectiveness and advantages of our results

Iterative Nearest Neighborhood Oversampling in Semisupervised Learning from Imbalanced Data

Transductive graph-based semi-supervised learning methods usually build an undirected graph utilizing both labeled and unlabeled samples as vertices. Those methods propagate label information of labeled samples to neighbors through their edges in order to get the predicted labels of unlabeled samples. Most popular semi-supervised learning approaches are sensitive to initial label distribution happened in imbalanced labeled datasets. The class boundary will be severely skewed by the majority classes in an imbalanced classification. In this paper, we proposed a simple and effective approach to alleviate the unfavorable influence of imbalance problem by iteratively selecting a few unlabeled samples and adding them into the minority classes to form a balanced labeled dataset for the learning methods afterwards. The experiments on UCI datasets and MNIST handwritten digits dataset showed that the proposed approach outperforms other existing state-of-art methods

Monocyte-derived alveolar macrophages autonomously determine severe outcome of respiratory viral infection

Various lung insults can result in replacement of resident alveolar macrophages (AM) by bone marrow monocyte–derived (BMo)–AM. However, the dynamics of this process and its long-term consequences for respiratory viral infections remain unclear. Using several mouse models and a marker to unambiguously track fetal monocyte–derived (FeMo)–AM and BMo-AM, we established the kinetics and extent of replenishment and their function to recurrent influenza A virus (IAV) infection. A massive loss of FeMo-AM resulted in rapid replenishment by self-renewal of survivors, followed by the generation of BMo-AM. BMo-AM progressively outcompeted FeMo-AM over several months, and this was due to their increased glycolytic and proliferative capacity. The presence of both naïve and experienced BMo-AM conferred severe pathology to IAV infection, which was associated with a proinflammatory phenotype. Furthermore, upon aging of naïve mice, FeMo-AM were gradually replaced by BMo-AM, which contributed to IAV disease severity in a cell-autonomous manner. Together, our results suggest that the origin rather than training of AM determines long-term function to respiratory viral infection and provide an explanation for the increased severity of infection seen in the elderly