Estimating the number of species via a martingale estimating function

A martingale estimating function is proposed to estimate the number of species under a multinomial model with possibly unequal cell probabilities. This approach provides a class of estimators including the maximum likelihood estimator for the equiprobable case and the nonparametric sample coverage estimator (Chao and Lee (1992)) for the non-equiprobable case. Consistency of the proposed estimators is discussed. A simulation study investigates the behavior of the proposed procedure. A data set on Chinese poems is given for illustration.published_or_final_versio

Enzymatic activation of cell-penetrating peptides in self-assembled nanostructures triggers fibre-to-micelle morphological transition

Enzyme-assisted fibre-to-micelle transition in self-assembled nanostructures controls presentation of cell-penetrating peptides.</p

Growth, Reproductive Condition, And Digestive Tubule Atrophy Of Pacific Oyster Crassostrea Gigas In Gamakman Bay Off The Southern Coast Of Korea

Spat of Pacific oysters (Crassostrea gigas) were collected from Gamakman Bay, Korea, and raised in a spat hardening facility located in the low intertidal zone of the bay for a hardening/stunting period of 10 mo. Seasonal changes in growth, reproductive condition, and digestive tubule atrophy (DTA) of these hardened/stunted oysters were monitored for more than a year after transplanting to a suspended longline system in a grow-out area in the bay. After transplantation, the hardened/stunted oysters showed a logarithmic increase in shell size for the first 4 mo, from June to October, and growth remained stable from late fall to early spring. During the 12 mo of the grow-out, the shell size of the hardened/stunted oysters increased from 15.4-74.2 mm, and tissue weight increased from 0.49-12.85 g. Histological analysis revealed that gametogenesis of hardened/stunted oysters commenced as early as February when water temperature remained at 10 degrees C, and spawning occurred from July to September when water temperature reached 25-27 degrees C. DTA assessed from histological analysis was higher from September to February, when the chlorophyll a level in the bay was lower. These data suggest that seasonal fluctuations in water temperature and food availability in the water column are the 2 main environmental parameters governing reproduction and growth of oyster in Gamakman Bay, and DTA could be a useful biomarker for monitoring the nutritional condition of oysters

Activation of the innate immune receptor Dectin-1 upon formation of a 'phagocytic synapse'.

Innate immune cells must be able to distinguish between direct binding to microbes and detection of components shed from the surface of microbes located at a distance. Dectin-1 (also known as CLEC7A) is a pattern-recognition receptor expressed by myeloid phagocytes (macrophages, dendritic cells and neutrophils) that detects β-glucans in fungal cell walls and triggers direct cellular antimicrobial activity, including phagocytosis and production of reactive oxygen species (ROS). In contrast to inflammatory responses stimulated upon detection of soluble ligands by other pattern-recognition receptors, such as Toll-like receptors (TLRs), these responses are only useful when a cell comes into direct contact with a microbe and must not be spuriously activated by soluble stimuli. In this study we show that, despite its ability to bind both soluble and particulate β-glucan polymers, Dectin-1 signalling is only activated by particulate β-glucans, which cluster the receptor in synapse-like structures from which regulatory tyrosine phosphatases CD45 and CD148 (also known as PTPRC and PTPRJ, respectively) are excluded (Supplementary Fig. 1). The 'phagocytic synapse' now provides a model mechanism by which innate immune receptors can distinguish direct microbial contact from detection of microbes at a distance, thereby initiating direct cellular antimicrobial responses only when they are required

Role of strain in the blistering of hydrogen-implanted silicon

The authors investigated the physical mechanisms underlying blistering in hydrogen-implanted silicon by examining the correlation between implantation induced damage, strain distribution, and vacancy diffusion. Using Rutherford backscattering, scanning electron microscopy, and atomic force microscopy, they found that the depth of blisters coincided with that of maximum implantation damage. A model based on experimental results is presented showing the effect of tensile strain on the local diffusion of vacancies toward the depth of maximum damage, which promotes the nucleation and growth of platelets and ultimately blisters. © 2006 American Institute of Physics

Stabilizing forces acting on ZnO polar surfaces: STM, LEED, and DFT

published_or_final_versio

The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption

BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services

Graph inductive biases in transformers without message passing

Transformers for graph data are increasingly widely studied and successful in numerous learning tasks. Graph inductive biases are crucial for Graph Transformers, and previous works incorporate them using message-passing modules and/or positional encodings. However, Graph Transformers that use message-passing inherit known issues of message-passing, and differ significantly from Transformers used in other domains, thus making transfer of research advances more difficult. On the other hand, Graph Transformers without message-passing often perform poorly on smaller datasets, where inductive biases are more crucial. To bridge this gap, we propose the Graph Inductive bias Transformer (GRIT) -- a new Graph Transformer that incorporates graph inductive biases without using message passing. GRIT is based on several architectural changes that are each theoretically and empirically justified, including: learned relative positional encodings initialized with random walk probabilities, a flexible attention mechanism that updates node and node-pair representations, and injection of degree information in each layer. We prove that GRIT is expressive -- it can express shortest path distances and various graph propagation matrices. GRIT achieves state-of-the-art empirical performance across a variety of graph datasets, thus showing the power that Graph Transformers without message-passing can deliver

Graph inductive biases in transformers without message passing

Transformers for graph data are increasingly widely studied and successful in numerous learning tasks. Graph inductive biases are crucial for Graph Transformers, and previous works incorporate them using message-passing modules and/or positional encodings. However, Graph Transformers that use message-passing inherit known issues of message-passing, and differ significantly from Transformers used in other domains, thus making transfer of research advances more difficult. On the other hand, Graph Transformers without message-passing often perform poorly on smaller datasets, where inductive biases are more important. To bridge this gap, we propose the Graph Inductive bias Transformer (GRIT) — a new Graph Transformer that incorporates graph inductive biases without using message passing. GRIT is based on several architectural changes that are each theoretically and empirically justified, including: learned relative positional encodings initialized with random walk probabilities, a flexible attention mechanism that updates node and node-pair representations, and injection of degree information in each layer. We prove that GRIT is expressive — it can express shortest path distances and various graph propagation matrices. GRIT achieves state-of-the-art empirical performance across a variety of graph datasets, thus showing the power that Graph Transformers without message-passing can deliver

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models