Mechanical properties and chemical stability of pivalolactone-based poly(ether ester)s

The processing, mechanical and chemical properties of poly(ether ester)s, prepared from pivalolactone (PVL), 1,4-butanediol (4G) and dimethyl terephthalate (DMT), were studied. The poly(ether ester)s could easily be processed by injection moulding, owing to their favourable rheological and thermal properties. The tensile response of a poly(ether ester) with a butylene terephthalate (4GT) content of 72 mol%, which exhibited the phenomena of necking and strain-hardening, was related to the morphology of these copolymers. The influence of the short 4G-PVL segments was reflected in a high Young's modulus and yield stress, and resulted in a tough behaviour for the poly(ether ester), with an ultimate elongation of 500%. The poly(ether ester)s were stable towards treatment at room temperature with water or weakly acidic or alkaline solutions. Conditioning at 90°C in water for 264 h resulted in a water uptake of 1 wt%, whereas the rate of hydrolysis was 0.0003 (expressed in An rel h-1) for the poly(ether ester) with a 4GT content of 72 mol%. Although a decay in the mechanical properties for the PVL-based poly(ether ester) after exposure to water at 90°C was observed, these materials were assumed to have a higher hydrolytical stability than other poly(ether ester)

Cross-lingual syntactically informed distributed word representations

We develop a novel cross-lingual word representation model which injects syntactic information through dependency-based contexts into a shared cross-lingual word vector space. The model, termed CL-DepEmb, is based on the following assumptions: (1) dependency relations are largely language-independent, at least for related languages and prominent dependency links such as direct objects, as evidenced by the Universal Dependencies project; (2) word translation equivalents take similar grammatical roles in a sentence and are therefore substitutable within their syntactic contexts. Experiments with several language pairs on word similarity and bilingual lexicon induction, two fundamental semantic tasks emphasising semantic similarity, suggest the usefulness of the proposed syntactically informed cross-lingual word vector spaces. Improvements are observed in both tasks over standard cross-lingual "offline mapping" baselines trained using the same setup and an equal level of bilingual supervision

Isomorphic Transfer of Syntactic Structures in Cross-Lingual NLP

The transfer or share of knowledge between languages is a popular solution to resource scarcity in NLP. However, the effectiveness of cross-lingual transfer can be challenged by variation in syntactic structures. Frameworks such as Universal Dependencies (UD) are designed to be cross-lingually consistent, but even in carefully designed resources trees representing equivalent sentences may not always overlap. In this paper, we measure cross-lingual syntactic variation, or anisomorphism, in the UD treebank collection, considering both morphological and structural properties. We show that reducing the level of anisomorphism yields consistent gains in cross-lingual transfer tasks. We introduce a source language selection procedure that facilitates effective cross-lingual parser transfer, and propose a typologically driven method for syntactic tree processing which reduces anisomorphism. Our results show the effectiveness of this method for both machine translation and cross-lingual sentence similarity, demonstrating the importance of syntactic structure compatibility for boosting cross-lingual transfer in NLP

Specialising Word Vectors for Lexical Entailment

We present LEAR (Lexical Entailment Attract-Repel), a novel post-processing method that transforms any input word vector space to emphasise the asymmetric relation of lexical entailment (LE), also known as the IS-A or hyponymy-hypernymy relation. By injecting external linguistic constraints (e.g., WordNet links) into the initial vector space, the LE specialisation procedure brings true hyponymy-hypernymy pairs closer together in the transformed Euclidean space. The proposed asymmetric distance measure adjusts the norms of word vectors to reflect the actual WordNet-style hierarchy of concepts. Simultaneously, a joint objective enforces semantic similarity using the symmetric cosine distance, yielding a vector space specialised for both lexical relations at once. LEAR specialisation achieves state-of-the-art performance in the tasks of hypernymy directionality, hypernymy detection, and graded lexical entailment, demonstrating the effectiveness and robustness of the proposed asymmetric specialisation model

Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources

Word vector specialisation (also known as retrofitting) is a portable, light-weight approach to fine-tuning arbitrary distributional word vector spaces by injecting external knowledge from rich lexical resources such as WordNet. By design, these post-processing methods only update the vectors of words occurring in external lexicons, leaving the representations of all unseen words intact. In this paper, we show that constraint-driven vector space specialisation can be extended to unseen words. We propose a novel post-specialisation method that: a) preserves the useful linguistic knowledge for seen words; while b) propagating this external signal to unseen words in order to improve their vector representations as well. Our post-specialisation approach explicits a non-linear specialisation function in the form of a deep neural network by learning to predict specialised vectors from their original distributional counterparts. The learned function is then used to specialise vectors of unseen words. This approach, applicable to any post-processing model, yields considerable gains over the initial specialisation models both in intrinsic word similarity tasks, and in two downstream tasks: dialogue state tracking and lexical text simplification. The positive effects persist across three languages, demonstrating the importance of specialising the full vocabulary of distributional word vector spaces.https://www.aclweb.org/anthology/N18-104

Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules

Morphologically rich languages accentuate two properties of distributional vector space models: 1) the difficulty of inducing accurate representations for low-frequency word forms; and 2) insensitivity to distinct lexical relations that have similar distributional signatures. These effects are detrimental for language understanding systems, which may infer that inexpensive is a rephrasing for expensive or may not associate acquire with acquires. In this work, we propose a novel morph-fitting procedure which moves past the use of curated semantic lexicons for improving distributional vector spaces. Instead, our method injects morphological constraints generated using simple language-specific rules, pulling inflectional forms of the same word close together and pushing derivational antonyms far apart. In intrinsic evaluation over four languages, we show that our approach: 1) improves low-frequency word estimates; and 2) boosts the semantic quality of the entire word vector collection. Finally, we show that morph-fitted vectors yield large gains in the downstream task of dialogue state tracking, highlighting the importance of morphology for tackling long-tail phenomena in language understanding tasks

Energy-efficient vertical handover parameters, classification and solutions over wireless heterogeneous networks: a comprehensive survey

In the last few decades, the popularity of wireless networks has been growing dramatically for both home and business networking. Nowadays, smart mobile devices equipped with various wireless networking interfaces are used to access the Internet, communicate, socialize and handle short or long-term businesses. As these devices rely on their limited batteries, energy-efficiency has become one of the major issues in both academia and industry. Due to terminal mobility, the variety of radio access technologies and the necessity of connecting to the Internet anytime and anywhere, energy-efficient handover process within the wireless heterogeneous networks has sparked remarkable attention in recent years. In this context, this paper first addresses the impact of specific information (local, network-assisted, QoS-related, user preferences, etc.) received remotely or locally on the energy efficiency as well as the impact of vertical handover phases, and methods. It presents energy-centric state-of-the-art vertical handover approaches and their impact on energy efficiency. The paper also discusses the recommendations on possible energy gains at different stages of the vertical handover process

Multiple Genome Comparison within a Bacterial Species Reveals a Unit of Evolution Spanning Two Adjacent Genes in a Tandem Paralog Cluster

It has been assumed that an open reading frame (ORF) represents a unit of gene evolution as well as a unit of gene expression and function. In the present work, we report a case in which a unit comprising the 3′ region of an ORF linked to a downstream intergenic region that is in turn linked to the 5′ region of a downstream ORF has been conserved, and has served as the unit of gene evolution. The genes are tandem paralogous genes from the bacterium Staphylococcus aureus, for which more than ten entire genomes have been sequenced. We compared these multiple genome sequences at a locus for the lpl (lipoprotein-like) cluster (encoding lipoprotein homologs presumably related to their host interaction) in the genomic island termed νSaα. A highly conserved nucleotide sequence found within every lpl ORF is likely to provide a site for homologous recombination. Comparison of phylogenies of the 5′-variable region and the 3′-variable region within the same ORF revealed significant incongruence. In contrast, pairs of the 3′-variable region of an ORF and the 5′-variable region of the next downstream ORF gave more congruent phylogenies, with distinct groups of conserved pairs. The intergenic region seemed to have coevolved with the flanking variable regions. Multiple recombination events at the central conserved region appear to have caused various types of rearrangements among strains, shuffling the two variable regions in one ORF, but maintaining a conserved unit comprising the 3′-variable region, the intergenic region, and the 5′-variable region spanning adjacent ORFs. This result has strong impact on our understanding of gene evolution because most gene lineages underwent tandem duplication and then diversified. This work also illustrates the use of multiple genome sequences for high-resolution evolutionary analysis within the same species

Prospective community study of family stress and anxiety in (pre)adolescents: the TRAILS study

For prevention of anxiety in children and adolescents, it is important to know whether family stress is a predictor of anxiety. We studied this in 1,875 adolescents from the Tracking Adolescents’ Individual Lives Survey (TRAILS) who were followed up for 2 years, from age 10–12 to 12–14 years. Adolescents reported anxiety and depression symptoms at both assessments, and parents reported family stress (family dysfunction and parenting stress) at the first assessment. Family dysfunction was not associated with future anxiety, whereas high parenting stress was. Furthermore, family dysfunction was more strongly associated with anxiety than with depression, whereas parenting stress was more strongly associated with depression. Level of parental psychopathology explained part of the association of family stress with anxiety. The associations were modest and the understanding of the origins of adolescents’ anxiety will require identifying other factors than family stress that account for more of the variance