The Essence of Foreign Language Learning in Today’s Globalizing World: Benefits and Hindrances

This paper highlights the essence of foreign language learning in today’s globalizing world as well as underscores its benefits and hindrances. It emphasizes that foreign language does collectively bind us together as human beings predicated upon our irresistible interdependence in various ways. Rationally speaking, being knowledgeable of a second or foreign language is extremely pertinent because it provides numerous life time opportunities. Yielding the dividends of studying abroad, employment, personal development, security, political and economic benefits among others make foreign language learning absolutely beneficial. Consequently, this paper sees foreign language conversance as a key that could unlock the door of your life and it must not be ignored. However, despite its overarching benefits, foreign language learning is continually constrained with the challenges of complexity, ignorance of its importance, learner-native speaker gaps, weak policies and inadequate support. Some of these challenges are related to the constructs of motivational beliefs and strategies which are vital to foreign language learning because learners must believe in themselves, value tasks and use appropriate strategies if they are to succeed. Finally, it recommends a collective concerted effort against monolingualism, but supports the formulation of salient policies and programs including the inclusion of foreign languages in the curricula, increased financial and moral supports, and early teaching of foreign languages to kids. Key words: foreign language, language benefits and barriers, motivational beliefs, language learning strategies, globalizing world

Measuring velocity ratios with correlation functions

We show how to determine the ratio of the transverse velocity of a source to the velocity of emitted particles, using split-bin correlation functions. The technique is to measure $S_2$ and $S_2^{\phi}$, subtract the contributions from the single-particle distribution, and take the ratio as the bin size goes to zero. We demonstrate the technique for two cases: each source decays into two particles, and each source emits a large number of particles.Comment: 9 pages, LaTeX, 2 PostScript figure

The Solid State \u3csup\u3e13\u3c/sup\u3eC-NMR and \u3csup\u3e19\u3c/sup\u3eF-NMR Spectra of Some Graphite Fluorides

The solid state 13C nuclear magnetic resonance spectra of fluorinated graphites show two resonances, one of which is assigned to aromatic carbon and the other to aliphatic carbon. The resonances are very broad with the high-field resonance centered at about 35 ppm below tetramethylsilane (TMS) and a low-field resonance centered at about 160 ppm below tetramethylsilane. The high-field resonance is typical of an sp3-like carbon and the low-field resonance is assigned to sp2-like carbons. It is found that the aromatic resonance in graphite decreases with an increase in fluorination of the graphite fluorides examined in this study. The 19F nuclear magnetic resonance spectra of C4F and CF1 each show one resonance. The fluorine resonance in C4F is 180 ppm above CFCI3 whereas the fluorine resonance in CF1 is 55 ppm above CFCI3. These peaks are in the range for fluorine bonded to aromatic and aliphatic carbons, respectively

Valuing Nature in Business-A Case Study of Chemical Manufacturing and Forest Products Industries

Over the past several decades, there has been an increased realization of the extent to which the means of production in human society depend on and impact increasingly fragile natural systems. Working with our client, The Nature Conservancy, we researched trends in ecosystem valuation within the chemical manufacturing and forest product industries, discerning ways to identify and evaluate future ecosystem investment opportunities. This research resulted in a framework that businesses could use to identify future ecosystem service opportunities and then score the opportunities’ business values using a multi-criteria analysis approach. We identified potential ecosystem service opportunities by overlaying classifications of business risk on major operational subsectors within the industries, populating the resulting table with key ecosystem impacts and opportunities. Through the application of this process, we identified three hypothetical ecosystem service projects applicable to both the chemical manufacturing and forest product industries and used them to test our scoring framework. The identified projects were constructed wetlands for wastewater treatment, coastal habitat protection for storm surge protection, and forest carbon sequestration. We ranked the business value of each project using five criteria important to businesses: financial value, reputational benefits, environmental risk reduction, political and regulatory enabling conditions, and level of knowledge and activity in the field. According to our research, businesses emphasize financial benefits most highly when evaluating potential investments, so we weighted financial values most heavily in our ranking scheme. Our analysis indicated that a forest carbon sequestration project had the highest potential business value relative to the other project types due to its higher expected financial benefits. The constructed wetland project, which also had a relatively high expected financial benefit, followed second. Finally, the coastal habitat protection project had the lowest relative business value due to high costs, a low level of scientific knowledge, and weak regulatory support. The identification and ranking methodologies are designed to be flexible, allowing adaptation for use given varying business objectives. The weights on the five valuation criteria can be adjusted to reflect a business’s concerns. This scoring methodology is useful for businesses because few tools exist to enable comparative analysis of business ecosystem service investments. We believe this tool provides a useful approach to determining the value that nature and ecosystem services provide to a wide range of businesses, and we recommend its application outside the chemical manufacturing and forest products industry for further refinement

Dilated FCN: Listening Longer to Hear Better

Deep neural network solutions have emerged as a new and powerful paradigm for speech enhancement (SE). The capabilities to capture long context and extract multi-scale patterns are crucial to design effective SE networks. Such capabilities, however, are often in conflict with the goal of maintaining compact networks to ensure good system generalization. In this paper, we explore dilation operations and apply them to fully convolutional networks (FCNs) to address this issue. Dilations equip the networks with greatly expanded receptive fields, without increasing the number of parameters. Different strategies to fuse multi-scale dilations, as well as to install the dilation modules are explored in this work. Using Noisy VCTK and AzBio sentences datasets, we demonstrate that the proposed dilation models significantly improve over the baseline FCN and outperform the state-of-the-art SE solutions.Comment: 5 pages; will appear in WASPAA conferenc

Accelerating the Generalized Born with Molecular Volume and Solvent Accessible Surface Area Implicit Solvent Model Using Graphics Processing Units

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154497/1/jcc26133.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154497/2/jcc26133_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154497/3/jcc26133-sup-0001-supinfo.pd

Does space natter? The case of the housing expenditure cap

In our evaluation of the housing expenditure share cap, a macroprudential policy, we discover the importance of modeling space. The spatial considerations allow households to sort into segmented housing markets based on income. Our model generates the observed negative relationship between housing expenditure share and income. More importantly, the cap policy causes a more considerable reduction in housing costs for low-income families than for high-income families in a spatial model. Depending on the assumption of households' preference, this mechanism leads to a minor increase or even a modest decrease in welfare inequality in a spatial model than in a spaceless model