Resonance enhancement has been increasingly employed in the emergent femtosecond stimulated Raman spectroscopy (FSRS) to selectively monitor molecular structure and dynamics with improved spectral and temporal resolutions and signal-to-noise ratios. Such joint efforts by the technique- and application-oriented scientists and engineers have laid the foundation for exploiting the tunable FSRS...
Work-related musculoskeletal disorders (WMSDs) are prevalent among surgeons due to a variety of risk factors. Various subjective tools have been used to investigate the associations between these risk factors and their contributions to the development of WMSDs. This study aimed to provide a summary of a collection of popular subjective...
Epigenetic mechanisms are important for control of plant development, and may play a particularly important role in trees given their long life cycles and distinctive and stable tissue types. To help understand the role of epigenetics in tree development, we produced transgenic poplars with reduced activity of the DDM1 genes,...
To obtain a mechanistic understanding of the chemical processes, techniques that offer a frame-by-frame visualization of molecular structure during a reaction are of vital importance. Numerous efforts and advances have been made in order to acquire such vivid molecular “movies”, especially in the electronic excited state. Ultrafast molecular spectroscopy method...
Improved cookstoves have been designed and disseminated for several decades in an effort to address the human health and environmental issues caused by the inefficient, traditional biomass cooking and heating methods used by 40% of the world’s people. Engineers and designers working on these improved stoves have tended to focus...
We demonstrate the versatile broadband wavelength tunability of frequency upconverted multicolor cascaded fourwave-mixing (CFWM) signals spanning the continuous wavelength range from UV to near IR in a thin type-I BBO crystal using 35 fs, 800 nm fundamental and chirped IR supercontinuum white light pulses. Two sets of spatially dispersed CFWM...
Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
Most tasks in natural language processing (NLP) involves structured information from both input (e.g., a sentence or a paragraph) and output (e.g., a tag sequence, a parse tree or a translated sentence). While neural models achieve great successes in other domains such as computer vision, applying those frameworks to NLP...
Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...