The education and practice gap of accounting

Educators nowadays may equip students for jobs that will not exist in the future (Shusterman, 2015) or jobs that do not exist yet. Many students face confession after graduating from tertiary education. Not knowing what to expect, wondering if they can use what they learn from school at work (Elmes, 2017). This paper aims to gather the opinion of accounting students regarding what they think are the demanded skills to get an accounting job after the completion of education. After reviewing the literature, a questionnaire was produced and sent to students at a tertiary institute to gain their opinion. Results were then compared to the skills required in practice by employers when recruiting. The key findings this study obtained were that there is a gap between what soft skills students think is important for an accounting position compared to that of practitioners’ view as stated by other researchers. Results indicate there is little difference of required hard skills (accounting techniques) from view points of students and professionals. Further studies should be done with larger samples to generalise more widely. Recommendations are that tertiary schools can partner with local business and accounting firms to provide internship program for all accounting major students. Also students should communicate with other accounting students, possible seniors or past students to gain their thoughts on what is currently lacking in the school education

A CGE-Model Analysis of U.S. Imposed Automotive Tariffs

Using a computable generable equilibrium (CGE) model, this research paper evaluates the effects of a U.S. imposed 25% automotive import tariff on NAFTA countries and the European Union, the greatest U.S. automotive trade partners. Three simulations were conducted: the implementation of tariffs with no retaliation, equivalent retaliation on the same products, and retaliation on the top exports of politically significant states, with sensitivity analysis applied in the final scenario. The results demonstrate that the EU is marginally affected while the NAFTA countries experience the greatest increases in prices and reduction in total wages

Affordable Housing and Its Impact on Economic Diversity of New York City Neighborhoods

The study analyses the effectiveness of affordable housing as a policy tool to increase neighborhood economic diversity in New York City from 1990 to 2015. Due to limited time and data availability, it assesses neighborhood economic diversity mainly based on household income and educational attainment diversity index calculated from US census and American Community Service data. Affordable housing is the major tool adopted by local governments to improve affordability and economic diversity. In Mayor de Blasio's new affordable housing plan, increase neighborhood economic diversity by creating more affordable units has been listed as one of the main goals. However, few previous studies discussed and verified the effectiveness of affordable housing as a tool to increase economic diversity other than its impact on neighborhood. The study, under such context, aims to examine the justification and effectiveness of this policy goal by exploring whether past affordable housing units increase led to economic diversity improvement in New York City neighborhoods. The regression analysis results of the study reveal that from 1991-2000, proportion of new affordable housing units have a statistically significant relationship with changes in economic diversity. This relationship is weakened in the later 15 years. It is also a highly volatile relationship that can be easily affected by affordable housing program types, gentrification and many other factors

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user

Bio-templated Substrates for Biosensor Applications

Nanopatterning of materials is of particular interest for applications in biosensors, microfluidics, and drug delivery devices. In biosensor applications there is a need for rapid, low cost, and durable system for detection. This dissertation aims to investigate methods to pattern nanostructured surfaces using virus particles as templates. The virus species used in these experiments is a cysteine modified tobacco mosaic virus. The first project utilized the lamellar microphase separation of a block copolymer to pattern the virus particles. Although microphase separation of the poly(styrene-b-2-vinylpyridine) (PS-P2VP) into lamellae was confirmed, specificity of the viruses to the gold doped block of the polymer could not be achieved. Single virus particles lay across multiple lamellae and aggregated in side-to-side and head-to-tail arrangements. The second project studied the effect of a surfactant on virus assembly onto a gold chip. The experiments included placing a gold chip in virus solutions with varying triton concentrations (0-0.15%), then plating the virus particles with a metal. Results showed that as the triton concentration in the virus solution increases, the virus density on the surface decreases. The gold coated virus particles were applied to Surface Enhanced Raman Spectroscopy (SERS) detection in the final project. SERS is of interest for biosensor applications due to its rapid detection, low cost, portability, and label-free characteristics. In recent years, it has shown signal enhancement using gold, silver, and copper nanoparticles in solutions and on roughened surfaces. The gold plated virus surfaces were tested as SERS substrates using R6G dye as the analyte. An enhancement factor (EF) of 10^4 was seen in these samples versus the non-SERS substrate. This corresponded to the sample with 0.05% triton in the virus solution which showed the most intersection points between the virus particles and the most uniform coverage of the viruses on the surface. This value is lower than that of previous studies; however, future work may be performed to optimize conditions to achieve the highest signal possible

The Early Progenitors of Mouse Dendritic Cells and Plasmacytoid Predendritic Cells Are within the Bone Marrow Hemopoietic Precursors Expressing Flt3

Flt3 ligand (Flt3L) is a growth factor for hemopoietic progenitors and can promote the expansion of both conventional dendritic cells (DCs) and plasmacytoid predendritic cells (p-preDCs). The cells responding to Flt3L treatment and the precursors for the DCs and p-preDCs had not been fully characterized. We examined different mouse bone marrow (BM) hemopoietic precursor populations for the surface expression of Flt3 and tested them for early DC and p-preDC precursor activity. Most DC precursor activity, other than that given by multipotent hemopoietic stem cells, was within the downstream precursors expressing Flt3. The majority of mouse BM common lymphoid precursors expressed high levels of Flt3 and these were the most efficient precursors of both DCs and p-preDCs. In contrast, only a small proportion of the common myeloid precursors (CMPs) expressed Flt3, but the precursor activity for both DCs and p-preDCs was within this minor Flt3+ CMP fraction. The granulocyte and macrophage precursors and pro-B cells did not express Flt3 and had no DC or p-preDC precursor activity. These findings demonstrate that the early precursors for all DC subtypes are within the BM Flt3+ precursor populations, regardless of their lymphoid or myeloid lineage orientation

Evaluating metabolites in patients with major depressive disorder who received mindfulness-based cognitive therapy and healthy controls using short echo MRSI at 7 Tesla.

ObjectivesOur aim was to evaluate differences in metabolite levels between unmedicated patients with major depressive disorder (MDD) and healthy controls, to assess changes in metabolites in patients after they completed an 8-week course of mindfulness-based cognitive therapy (MBCT), and to exam the correlation between metabolites and depression severity.Materials and methodsSixteen patients with MDD and ten age- and gender-matched healthy controls were studied using 3D short echo-time (20 ms) magnetic resonance spectroscopic imaging (MRSI) at 7 Tesla. Relative metabolite ratios were estimated in five regions of interest corresponding to insula, anterior cingulate cortex (ACC), caudate, putamen, and thalamus.ResultsIn all cases, MBCT reduced severity of depression. The ratio of total choline-containing compounds/total creatine (tCr) in the right caudate was significantly increased compared to that in healthy controls, while ratios of N-acetyl aspartate (NAA)/tCr in the left ACC, myo-inositol/tCr in the right insula, and glutathione/tCr in the left putamen were significantly decreased. At baseline, the severity of depression was negatively correlated with my-inositol/tCr in the left insula and putamen. The improvement in depression severity was significantly associated with changes in NAA/tCr in the left ACC.ConclusionsThis study has successfully evaluated regional differences in metabolites for patients with MDD who received MBCT treatment and in controls using 7 Tesla MRSI

Regulation of the cardiomyocyte transcriptome vs translatome by endothelin-1 and insulin: translational regulation of 5' terminal oligopyrimidine tract (TOP) mRNAs by insulin

Background: Changes in cellular phenotype result from underlying changes in mRNA transcription and translation. Endothelin-1 stimulates cardiomyocyte hypertrophy with associated changes in mRNA/protein expression and an increase in the rate of protein synthesis. Insulin also increases the rate of translation but does not promote overt cardiomyocyte hypertrophy. One mechanism of translational regulation is through 5' terminal oligopyrimidine tracts (TOPs) that, in response to growth stimuli, promote mRNA recruitment to polysomes for increased translation. TOP mRNAs include those encoding ribosomal proteins, but the full panoply remains to be established. Here, we used microarrays to compare the effects of endothelin-1 and insulin on the global transcriptome of neonatal rat cardiomyocytes, and on mRNA recruitment to polysomes (i.e. the translatome). Results: Globally, endothelin-1 and insulin (1 h) promoted >1.5-fold significant (false discovery rate 1.25-fold significant changes in expression in total and/or polysomal RNA induced by endothelin-1 or insulin, respectively, of which ~35% of endothelin-1-responsive and ~56% of insulin-responsive transcripts were translationally regulated. Of mRNAs for established proteins recruited to polysomes in response to insulin, 49 were known TOP mRNAs with a further 15 probable/possible TOP mRNAs, but 49 had no identifiable TOP sequences or other consistent features in the 5' untranslated region. Conclusions: Endothelin-1, rather than insulin, substantially affects global transcript expression to promote cardiomyocyte hypertrophy. Effects on RNA recruitment to polysomes are subtle, with differential effects of endothelin-1 and insulin on specific transcripts. Furthermore, although insulin promotes recruitment of TOP mRNAs to cardiomyocyte polysomes, not all recruited mRNAs are TOP mRNAs