The Challenges of Cross-Modal Translation: English-to-Sign-Language Translation in the Zardoz System

The sign languages used by deaf communities around the world represent a linguistic challenge that natural-language researchers in AI have only recently begun to take up. This challenge is particularly relevant to research in Machine Translation (MT), as natural sign languages have evolved in deaf communities into efficient modes of gestural communication, which differ from English not only in modality but in grammatical structure, exploiting a higher dimensionality of spatial expression. In this paper we describe Zardoz, an on-going AI research system that tackles the cross-modal MT problem, translating English text into fluid sign language. The paper presents an architectural overview of Zardoz, describing its central blackboard organization, the nature of its interlingual representation, and the major components which interact through this blackboard both to analyze the verbal input and generate the corresponding gestural output in one of a number of sign variants.     

Physical Maltreatment Victim to Antisocial Child: Evidence of an Environmentally Mediated Process.

The well-documented finding that child physical maltreatment predicts later antisocial behavior has at least 2 explanations: (a) Physical maltreatment causes antisocial behavior, and (b) genetic factors transmitted from parents to children influence the likelihood that parents will be abusive and that children will engage in antisocial behavior. The authors tested these hypotheses in the representative Environmental-Risk cohort of 1,116 twin pairs and their families, who were assessed when the twins were 5 and 7 years old. Mothers reported on children's experience of physical maltreatment, and mothers and teachers reported on children's antisocial behavior. The findings support the hypothesis that physical maltreatment plays a causal role in the development of children's antisocial behavior and that preventing maltreatment can prevent its violent sequelae. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mapping of polished coal surfaces by automated reflectance microscopy

The capabilities of Rapid Scan, a system of automated reflectance microscopy, has been extended to the actual mapping of petrographic variation across polished coal surfaces. This is accomplished through computer control of a microscope stepping stage and the storage of binary reflectance data on disc in a matrix form which permits the proper spatial arrangement of values to be re-created. The maps depict lithotype variation, and the distribution of mineral occurrences, cracks and cleat. An image processor can be employed in further map analysis such as the compilation of reflectance profiles from selected areas.     

OLED初具市场规模

We have all heard the hype about OLED displays and that they are going to offer great picture quality as well as energy efficiency in a very thin profile package. The issue at hand is whether they will be priced competitively in the market and overcome some of their shortcomings in the short term.     

Tumor Infiltration with CD20+CD73+ B Cells Correlates with Better Outcome in Colorectal Cancer

Immunotherapy has become increasingly important in the treatment of colorectal cancer (CRC). Currently, CD73, also known as ecto-5′-nucleotidase (NT5E), has gained considerable interest as a potential therapeutic target. CD73 is one of the key enzymes catalyzing the conversion of extracellular ATP into adenosine, which in turn exerts potent immune suppressive effects. However, the role of CD73 expression on various cell types within the CRC tumor microenvironment remains unresolved. The expression of CD73 on various cell types has been described recently, but the role of CD73 on B-cells in CRC remains unclear. Therefore, we analyzed CD73 on B-cells, especially on tumor-infiltrating B-cells, in paired tumor and adjacent normal tissue samples from 62 eligible CRC patients. The highest expression of CD73 on tumor-infiltrating B-cells was identified on class-switched memory B-cells, followed by naive B-cells, whereas no CD73 expression was observed on plasmablasts. Clinicopathological correlation analysis revealed that higher CD73⁺ B-cells infiltration in the CRC tumors was associated with better overall survival. Moreover, metastasized patients showed a significantly decreased number of tumor-infiltrating CD73⁺ B-cells. Finally, neoadjuvant therapy correlated with reduced CD73⁺ B-cell numbers and CD73 expression on B-cells in the CRC tumors. As promising new immune therapies are being developed, the role of CD73⁺ B-cells and their subsets in the development of colorectal cancer should be further explored to find new therapeutic options.     

Memory capacity, selective control, and value-directed remembering in children with and without attention-deficit/hyperactivity disorder (ADHD).

Objective: The ability to select what is important to remember, to attend to this information, and to recall high-value items leads to the efficient use of memory. The present study examined how children with and without attention-deficit/hyperactivity disorder (ADHD) performed on an incentive-based selectivity task in which to-be-remembered items were worth different point values. Method: Participants were 6–9 year old children with ADHD (n = 57) and without ADHD (n = 59). Using a selectivity task, participants studied words paired with point values and were asked to maximize their score, which was the overall value of the items they recalled. This task allows for measures of memory capacity and the ability to selectively remember high-value items. Results: Although there were no significant between-groups differences in the number of words recalled (memory capacity), children with ADHD were less selective than children in the control group in terms of the value of the items they recalled (control of memory). All children recalled more high-value items than low-value items and showed some learning with task experience, but children with ADHD Combined type did not efficiently maximize memory performance (as measured by a selectivity index) relative to children with ADHD Inattentive type and healthy controls, who did not differ significantly from one another. Conclusions: Children with ADHD Combined type exhibit impairments in the strategic and efficient encoding and recall of high-value items. The findings have implications for theories of memory dysfunction in childhood ADHD and the key role of metacognition, cognitive control, and value-directed remembering when considering the strategic use of memory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Role of Lattice Matching Techniques in the Characterization of Polymorphic Forms

An inspection of the recent literature reveals that polymorphism is a frequently encountered phenomenon. The recognition of polymorphic forms plays a vital role in the materials sciences because such structures are characterized by different crystal packing and accordingly have different physical properties. In the pharmaceutical industry, recognition of polymorphic forms can be critical for, in certain cases, a polymorphic form of a drug may be an ineffective therapeutic agent due to its unfavorable physical properties. A check of the recent literature has revealed that in some cases new polymorphic forms are not recognized. In other instances, a supposedly new polymeric form is actually the result of an incorrect structure determination. Fortunately, lattice-matching techniques, which have proved invaluable in the identification and characterization of crystal structures, represent a powerful tool for analyzing polymorphic forms. These lattice-matching methods are based on either of two strategies: (a) the reduced cell strategy–the matching of reduced cells of the respective lattices or (b) the matrix strategy–the determination of a matrix or matrices relating the two lattices coupled with an analysis of the matrix elements. Herein, these techniques are applied to three typical cases–(a) the identification of a new polymorphic form, (b) the demonstration that a substance may not be a new polymorphic form due to missed symmetry, and (c) the evaluation of pseudo polymorphism because of a missed lattice. To identify new polymorphic forms and to prevent errors, it is recommended that these lattice matching techniques become an integral part of the editorial review process of crystallography journals.     

Endothelial cell electrical impedance parameter artifacts produced by a gold electrode and phase sensitive detection

Frequency dependent cellular micro-impedance estimates obtained from a gold two-electrode configuration using phase sensitive detection have become increasingly used to evaluate cellular barrier model parameters. The results of this study show that cellular barrier function parameter estimates optimized using measurements obtained from this biosensor are highly susceptible to both time dependent and systematic instrumental artifacts. Based on a power spectral analysis of experimentally measured microelectrode voltages, synchronous, 60 Hz, and white Gaussian noise were identified as the most significant time dependent instrumental artifacts. The reduction of these artifacts using digital filtering produced a corresponding reduction in the optimized model parameter fluctuations. Using a series of instrumental circuit models, this study also shows that electrode impedance voltage divider effects and circuit capacitances can produce systematic deviations in cellular barrier function parameter estimates. Although the implementation of an active current source reduced the voltage divider effects, artifacts produced by coaxial cable and other circuit capacitive elements at frequencies exceeding 1 kHz still remained. Reducing time dependent instrumental fluctuations and systematic errors produced a significant reduction in cellular model barrier parameter errors and improved the model fit to experimental data.     

Capillary‐Bridge Mediated Assembly of Conjugated Polymer Arrays toward Organic Photodetectors

Large‐scale patterning of high‐quality organic semiconductors is crucial for the fabrication of optoelectronic devices with high efficiency and low cost. Yet, owing to the uncontrollable dewetting dynamics of organic liquid in conventional solution patterning techniques, large defect density of organic architectures is inevitable, which is detrimental to the device performance. To address this challenge, herein a capillary‐bridge‐mediated assembly technique is developed for regulating the dewetting process, yielding large‐scale 1D microstructure ordered arrays. The 1D arrays organic photodetectors exhibit a high optoelectronic performance of light on/off ratio exceeding 100, responsivity of 3.24 A W^?1, detectivity of 3.20 × 10¹¹ Jones and fast response speed, showing a great improvement compared with spin‐coated membrane devices. In addition, the significant enhancement of the device photodetection under the electronic field modulation is investigated by applying a back‐gate voltage and explained with the photocurrent predominating in the OFF state and the neglected thermocurrent and tunneling current promoting in the ON state of the phototransistor devices. The research offers a new insight for the facile fabrication of large‐scale integrated photodetectors and other organic devices based on patterned conjugated polymers.     

Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition

Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from super-linear increases in computational time with increasing data size and number of signals being processed (data dimension). Certain principal machine-learning algorithms are commonly found embedded in larger detection, estimation, or classification operations. Three such principal algorithms are the Parzen window-based, non-parametric estimation of Probability Density Functions (PDFs), K-means clustering and correlation. Because they form an integral part of numerous machine-learning applications, fast and efficient execution of these algorithms is extremely desirable. FPGA-based reconfigurable computing (RC) has been successfully used to accelerate computationally intensive problems in a wide variety of scientific domains to achieve speedup over traditional software implementations. However, this potential benefit is quite often not fully realized because creating efficient FPGA designs is generally carried out in a laborious, case-specific manner requiring a great amount of redundant time and effort. In this paper, an approach using pattern-based decomposition for algorithm acceleration on FPGAs is proposed that offers significant increases in productivity via design reusability. Using this approach, we design, analyze, and implement a multi-dimensional PDF estimation algorithm using Gaussian kernels on FPGAs. First, the algorithm’s amenability to a hardware paradigm and expected speedups are predicted. After implementation, actual speedup and performance metrics are compared to the predictions, showing speedup on the order of 20× over a 3.2 GHz processor. Multi-core architectures are developed to further improve performance by scaling the design. Portability of the hardware design across multiple FPGA platforms is also analyzed. After implementing the PDF algorithm, the value of pattern-based decomposition to support reuse is demonstrated by rapid development of the K-means and correlation algorithms.