WordRank: Learning Word Embeddings via Robust Ranking

Embedding words in a vector space has gained a lot of attention in recent years. While state-of-the-art methods provide efficient computation of word similarities via a low-dimensional matrix embedding, their motivation is often left unclear. In this paper, we argue that word embedding can be naturally viewed as a ranking problem due to the ranking nature of the evaluation metrics. Then, based on this insight, we propose a novel framework WordRank that efficiently estimates word representations via robust ranking, in which the attention mechanism and robustness to noise are readily achieved via the DCG-like ranking losses. The performance of WordRank is measured in word similarity and word analogy benchmarks, and the results are compared to the state-of-the-art word embedding techniques. Our algorithm is very competitive to the state-of-the- arts on large corpora, while outperforms them by a significant margin when the training set is limited (i.e., sparse and noisy). With 17 million tokens, WordRank performs almost as well as existing methods using 7.2 billion tokens on a popular word similarity benchmark. Our multi-node distributed implementation of WordRank is publicly available for general usage.Comment: Conference on Empirical Methods in Natural Language Processing (EMNLP), November 1-5, 2016, Austin, Texas, US

Partitioning a graph into degenerate subgraphs

Let $G = (V, E)$ be a connected graph with maximum degree $k\geq 3$ distinct from $K_{k+1}$. Given integers $s \geq 2$ and $p_1,\ldots,p_s\geq 0$, $G$ is said to be $(p_1, \dots, p_s)$-partitionable if there exists a partition of $V$ into sets~$V_1,\ldots,V_s$ such that $G[V_i]$ is $p_i$-degenerate for $i\in\{1,\ldots,s\}$. In this paper, we prove that we can find a $(p_1, \dots, p_s)$-partition of $G$ in $O(|V| + |E|)$-time whenever $1\geq p_1, \dots, p_s \geq 0$ and $p_1 + \dots + p_s \geq k - s$. This generalizes a result of Bonamy et al. (MFCS, 2017) and can be viewed as an algorithmic extension of Brooks' theorem and several results on vertex arboricity of graphs of bounded maximum degree. We also prove that deciding whether $G$ is $(p, q)$-partitionable is $\mathbb{NP}$-complete for every $k \geq 5$ and pairs of non-negative integers $(p, q)$ such that $(p, q) \not = (1, 1)$ and $p + q = k - 3$. This resolves an open problem of Bonamy et al. (manuscript, 2017). Combined with results of Borodin, Kostochka and Toft (\emph{Discrete Mathematics}, 2000), Yang and Yuan (\emph{Discrete Mathematics}, 2006) and Wu, Yuan and Zhao (\emph{Journal of Mathematical Study}, 1996), it also settles the complexity of deciding whether a graph with bounded maximum degree can be partitioned into two subgraphs of prescribed degeneracy.Comment: 16 pages; minor revisio

Connecting the Cytoskeleton to the Endoplasmic Reticulum and Golgi

A tendency in cell biology is to divide and conquer. For example, decades of painstaking work have led to an understanding of endoplasmic reticulum (ER) and Golgi structure, dynamics, and transport. In parallel, cytoskeletal researchers have revealed a fantastic diversity of structure and cellular function in both actin and microtubules. Increasingly, these areas overlap, necessitating an understanding of both organelle and cytoskeletal biology. This review addresses connections between the actin/microtubule cytoskeletons and organelles in animal cells, focusing on three key areas: ER structure and function; ER-to-Golgi transport; and Golgi structure and function. Making these connections has been challenging for several reasons: the small sizes and dynamic characteristics of some components; the fact that organelle-specific cytoskeletal elements can easily be obscured by more abundant cytoskeletal structures; and the difficulties in imaging membranes and cytoskeleton simultaneously, especially at the ultrastructural level. One major concept is that the cytoskeleton is frequently used to generate force for membrane movement, with two potential consequences: translocation of the organelle, or deformation of the organelle membrane. While initially discussing issues common to metazoan cells in general, we subsequently highlight specific features of neurons, since these highly polarized cells present unique challenges for organellar distribution and dynamics

Novel Roles for Actin in Mitochondrial Fission

Mitochondrial dynamics, including fusion, fission and translocation, are crucial to cellular homeostasis, with roles in cellular polarity, stress response and apoptosis. Mitochondrial fission has received particular attention, owing to links with several neurodegenerative diseases. A central player in fission is the cytoplasmic dynamin-related GTPase Drp1, which oligomerizes at the fission site and hydrolyzes GTP to drive membrane ingression. Drp1 recruitment to the outer mitochondrial membrane (OMM) is a key regulatory event, which appears to require a pre-constriction step in which the endoplasmic reticulum (ER) and mitochondrion interact extensively, a process termed ERMD (ER-associated mitochondrial division). It is unclear how ER-mitochondrial contact generates the force required for pre-constriction or why pre-constriction leads to Drp1 recruitment. Recent results, however, show that ERMD might be an actin-based process in mammals that requires the ER-associated formin INF2 upstream of Drp1, and that myosin II and other actin-binding proteins might be involved. In this Commentary, we present a mechanistic model for mitochondrial fission in which actin and myosin contribute in two ways; firstly, by supplying the force for pre-constriction and secondly, by serving as a coincidence detector for Drp1 binding. In addition, we discuss the possibility that multiple fission mechanisms exist in mammals

Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data

__Abstract__ Time varying patterns in US growth are analyzed using various univariate model structures, starting from a naive model structure where all features change every period to a model where the slow variation in the conditional mean and changes in the conditional variance are specified together with their interaction, including survey data on expected growth in order to strengthen the information in the model. Use is made of a simulation based Bayesian inferential method to determine the forecasting performance of the various model specifications. The extension of a basic growth model with a constant mean to models including time variation in the mean and variance requires careful investigation of possible identification issues of the parameters and existence conditions of the posterior under a diffuse prior. The use of diffuse priors leads to a focus on the likelihood fu nction and it enables a researcher and policy adviser to evaluate the scientific information contained in model and data. Empirical results indicate that incorporating time variation in mean growth rates as well as in volatility are important in order to improve for the predictive performances of growth models. Furthermore, using data information on growth expectations is important for forecasting growth in specific periods, such as the the recession periods around 2000s and around 2008

Incorporation of a sequential BMP-2/BMP-7 delivery system into chitosan-based scaffolds for bone tissue engineering

The aim of this study was to develop a 3-D construct carrying an inherent sequential growth factor delivery system. Poly(lactic acid-co-glycolic acid) (PLGA) nanocapsules loaded with bone morphogenetic protein BMP-2 and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) nanocapsules loaded with BMP-7 made the early release of BMP-2 and longer term release of BMP-7 possible. 3-D fiber mesh scaffolds were prepared from chitosan and from chitosan–PEO by wet spinning. Chitosan of 4% concentration in 2% acetic acid (CHI4–HAc2) and chitosan (4%) and PEO (2%) in 5% acetic acid (CHI4– PEO2–HAc5) yielded scaffolds with smooth and rough fiber surfaces, respectively. These scaffolds were seeded with rat bone marrow mesenchymal stem cells (MSCs). When there were no nanoparticles the initial differentiation rate was higher on (CHI4–HAc2) scaffolds but by three weeks both the scaffolds had similar alkaline phosphatase (ALP) levels. The cell numbers were also comparable by the end of the third week. Incorporation of nanoparticles into the scaffolds was achieved by two different methods: incorporation within the scaffold fibers (NP–IN) and on the fibers (NP–ON). It was shown that incorporation on the CHI4–HAc2 fibers (NP–ON) prevented the burst release observed with the free nanoparticles, but this did not influence the total amount released in 25 days. However NP–IN for the same fibers revealed a much slower rate of release; ca. 70% released at the end of incubation period. The effect of single, simultaneous and sequential delivery of BMP-2 and BMP-7 from the CHI4–HAc2 scaffolds was studied in vitro using samples prepared with both incorporation methods. The effect of delivered agents was higher with the NP–ON samples. Delivery of BMP-2 alone suppressed cell proliferation while providing higher ALP activity compared to BMP-7. Simultaneous delivery was not particularly effective on cell numbers and ALP activity. The sequential delivery of BMP-2 and BMP-7, on the other hand, led to the highest ALP activity per cell (while suppressing proliferation) indicating the synergistic effect of using both growth factors holds promise for the production of tissue engineered bone.This project was conducted within the scope of the EU FP6 NoE Project Expertissues (NMP3-CT-2004-500283). We acknowledge the support to PY through the same project in the form of an integrated PhD grant. We also would like to acknowledge the support from Scientific and Technical Research Council of Turkey (TUBITAK) through project METUNANOBIOMAT (TBAG 105T508)

Effect of scaffold architecture and BMP-2/BMP-7 delivery on in vitro bone regeneration

The aim of this study was to develop 3-D tissue engineered constructs that mimic the in vivo conditions through a self-contained growth factor delivery system. A set of nanoparticles providing the release of BMP-2 initially followed by the release of BMP-7 were incorporated in poly(ε-caprolactone) scaffolds with different 3-D architectures produced by 3-D plotting and wet spinning. The release patterns were: each growth factor alone, simultaneous, and sequential. The orientation of the fibers did not have a significant effect on the kinetics of release of the model protein BSA; but affected proliferation of bone marrow mesenchymal stem cells. Cell proliferation on random scaffolds was significantly higher compared to the oriented ones. Delivery of BMP-2 alone suppressed MSC proliferation and increased the ALP activity to a higher level than that with BMP-7 delivery. Proliferation rate was suppressed the most by the sequential delivery of the two growth factors from the random scaffold on which the ALP activity was the highest. Results indicated the distinct effect of scaffold architecture and the mode of growth factor delivery on the proliferation and osteogenic differentiation of MSCs, enabling us to design multifunctional scaffolds capable of controlling bone healing.This project was conducted within the scope of the EU FP6 NoE Project Expertissues (NMP3-CT-2004-500283). We acknowledge the support to PY through the same project in the form of an integrated PhD grant. We also would like to acknowledge the support from Scientific and Technical Research Council of Turkey (TUBITAK) through project METUNANOBIOMAT (TBAG 105T508)