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SEMANTIC ANALYSIS FOR ONLINE TRAVEL ACCOMMODATION REVIEWS
Get PDFABSTRACT Currently, most tourists use the Internet to retrieve information for supporting their decision in selecting the tourist places that conform to their preferences. The most common method is the decision based on reviews of experienced tourists. However, tourists must read enormous reviews in order to select their preferred tourist places. This article presents an analysis module for online travel accommodation reviews. The analysis module combines several techniques, such as ontology, natural language processing, and fuzzy logic. However, this article focuses on applying the natural language processing for semantic analysis to solve the accommodation feature extraction problems. The experimental results of the feature extraction process are achieved in 79.22% of overall accuracy, 100% of overall precision, and 76.05% of overall recall
d% Fermi National Accelerator Laboratory First Observation of Magnetic Moment Precession of Channeled Particles in Bent Crystals
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Get PDFBiodex, and this effect was most marked in the strongest participants. Nevertheless, there was a good correlation between the measures (r = 0.91, p ! 0.0001). Classifi cation of individuals into tertiles of muscle strength showed good agreement between the two methods (Kappa = 0.69, p ! 0.0001). Conclusions: Our fi ndings suggest that the HHD using a supine positioning offers a feasible, inexpensive, and portable test of quadriceps muscle strength for use in healthy older people. It underestimates the absolute quadriceps strength compared to the Biodex particularly in stronger people, but is a useful tool for ranking muscle strength of older people in epidemiological studies. It may also be of value for quick and objective assessment of physical function in the clinical setting
MODERN INSTRUMENTS FOR MEASURING ORGANIZATIONAL PERFORMANCE
Get PDFThe concept of performance Performance can be defined as "a state of competitiveness of the organization, reached through a level of efficiency and productivity which ensures a sustainable market presence" 658 . In our opinion performance needs both effectiveness and productivity simultaneous. Hence we conclude that a performing organization is efficient, competitive and productive. P. Druker considered that to be effective means "to do planned things well"; by efficiency he meant "the extent to which objectives were achieved ˝. T. Katarbinski defined effectiveness as precision in achieving targets. He suggested that efficiency is the action by which an organization achieves its goals in terms of minimal cost. Both management specialists come to reinforce the above statements on the concept of performance. The purpose of the paper is to find indicators and instruments that reflect as closely as possible the subtleties of how an organization is functioning. We started with the following questions. What indicators reflect best organizational performance? Profit level? Different rates of efficiency? Achieve planned results? The answer must take into account the multiplicity and diversity of factors that influence both individual and organizational behaviors. Performance measurement represents results quantification of activities undertaken within an organization over a period of time. For performance measurement we started from a series of questions: Is there a link between objectives, performance measurements and organization results? Are performance metrics relevant? To answer these questions we identified a series of modern management methods for measuring and assessing organizational performance. 658 M. Boulescu, M. GhiĠă, V. Mareú, ˝Auditul performanĠei˝, ed. Tribuna Economică, Bucureúti, pg. 13, 2002
forests, dominating sets and Ramsey-type problems
No full textAbstract A star forest of a graph G is a spanning subgraph of G in which each component is a star. The minimum number of edges required to guarantee that an arbitrary graph, or a bipartite graph, has a star forest of size n is determined. Sharp lower bounds on the size of a largest star forest are also determined. For bipartite graphs, these are used to obtain an upper bound on the domination number in terms of the number of vertices and edges in the graph, which is an improvement on a bound of Vizing. In turn, the results on bipartite graphs are used to determine the minimum number of lattice points required so that there exists a subset of n lattice points, no three of which form a right triangle with legs parallel to the coordinate axes
Household Finance over the Life-Cycle: What does Education Contribute? *
No full textAbstract This paper studies household financial choices: why are these decisions dependent on the education level of the household? A life-cycle model is constructed to understand a rich set of facts about decisions of households with different levels of educational attainment regarding stock market participation, the stock share in wealth, the stock adjustment rate and the wealth-income ratio. Model parameters, including preferences, the cost of stock market participation and portfolio adjustment costs, are estimated to match the financial decisions of different education groups. Based on the estimated model, education affects household finance mainly through increased average income. The estimation also finds evidence that higher educational attainment is associated with a lower stock market entry cost and a larger discount factor. Education specific differences in income risks, medical expenses, mortality risks and the life-cycle pattern of income explain relatively little of the observed differences in household financial choices. Motivation Empirical studies have consistently revealed the importance of education for household financial decisions. Asset market participation decision, stock adjustment rate, savings rate and portfolio choice are frequently linked to educational attainment. But what is the underlying impact of education on financial decisions? Are different household decisions a consequence of education specific observables such as income processes, health risks and mortality rates, and/or * We are grateful to the NSF for financial support. Participants at seminars at Pennsylvania State University, SUFE and SED 2014 provided helpful questions and comments. Thanks to David Lander and Qi Wu for detailed comments and suggestions. The analysis is built upon empirical evidence linking education and household financial choices including: asset market participation, the share of risky assets in household portfolios, the frequency of portfolio adjustment and wealth-income ratios. While a few studies have focused on one or more of these components of household financial decisions, one contribution of the paper is to understand these choices jointly. 2 This is important not just as means of generating a more complete picture of these choices but in allowing us to identify the sources of these differences. For example, a household considering asset market participation will recognize the subsequent costs of portfolio adjustment which is evidenced by the low stock adjustment rate. The factors, such as attitudes towards risk, that determine the share of assets in a household portfolio will also influence wealth accumulation and the stock market participation decision of the household. Another example is that, with fixed portfolio adjustment cost, higher wealth levels may lead to a higher stock share as wealthy households bear a lower cost (per unit) of adjustment. This stock share decision interacts with the participation decision, creating identification problems when participation is not modeled explicitly. Our approach to determining the dependence of financial choices on education starts with the specification and estimation of a life-cycle model of household financial choices. Regression analysis, as in Campbell Most of the existing quantitative studies on household portfolio choice is based on calibrated parameters, including important papers such as Cocco, Gomes, and Maenhout 3 By contrast, estimation is an integral part of our analysis. Based on the estimated model parameters, we are able to quantify the channels of influence between education and household financial decisions. Further, we would not be able to analyze the link between education and the parameters of household preferences and adjustment costs without estimating the parameters. The estimation uses a simulated method of moments approach, where the moments reflect the key household financial decisions by education group. These moments are selected to identify key parameters. More specifically, the analysis puts households into four groups according to the educational attainment of house-heads. 4 From the Survey of Consumer Finance (SCF), the average stock market participation rate and the financial wealth to income ratio increase sharply with education. Stock share also increases with education status, 1 Cole, Paulson, and Shastry (2014) offers some informal discussions about why education leads to different financial decisions. We formally answer the above questions based on an estimated structural model. 2 For example, Hubbard, Skinner, and Zeldes (1995) study why more educated households save more. Achury, Hubar, and Koulovatianos (2012) and Wachter and Yogo (2010) study the relation between education (or wealth) and stock share in wealth. 3 Structural estimation is employed in 4 To be clear, the model does not explain education. Rather it looks at the household financial choices given education. Parameter estimates come from using the structural model to match the life-cycle profiles of stock market participation rates, stock share in wealth, stock adjustment rates and wealth-income ratios of the four education groups. 5 The coefficients from regressing these household financial variables on, inter alia, age and age-squared and education dummies generates moments that are very informative about costs and risk preferences. By matching these moments, we estimate costs associated with stock market participation and adjustment along with preference parameters. In addition, by allowing heterogeneity in preferences and costs across education groups, the estimation results enable us to study the roles played by risk aversion, patience and other unobservables. The recent literature provides insights that costs associated with stock market participation, eg. Vissing- In the absence of costs, predictions based on common representations of risk preferences tend to contradict the data. For example, standard household portfolio models typically predict that every household should participate in the stock market, and that the stock share in total financial wealth should be high, e.g. Heaton and Lucas (1997). As another example, constant absolute risk aversion preferences predict that a household's optimal investment in risky assets is roughly a fixed amount independent of total wealth, which implies that the more educated should have a lower share of stocks in financial wealth. As pointed out by Campbell (2006), a fundamental issue that confronts the household finance literature is how to specify the household utility function. We carry out the estimation using three specifications: constant absolute risk aversion (CARA), constant relative risk aversion (CRRA) and recursive utility (EZW) taken from A critical input into the household optimization problem is the education specific stochastic processes for income, medical expenses and mortality. Education impacts both the permanent and transitory components of labor income. Based on the PSID, more educated households have higher levels of deterministic income, and smaller transitory income shocks before retirement. According to data from the Health and Retirement Study (HRS), after retirement, the more educated have higher out-of-pocket medical expenses relative to their income, and are subject to lower mortality risks. 5 The estimation of parameters from life-cycle profiles is a main feature distinguishing this paper from our earlier study, Cooper and Zhu (2013). 3 DATA FACTS In answer to the central question of our paper, the main observable factor that links household financial decisions to education is the dependence of the mean level of income on education. 6 Other factors, such as income volatility and differences in both medical expenses and mortality risk do not play a large role in explaining the variation of household financial decisions across education groups. We also allow preferences, the stock market entry cost and the portfolio adjustment cost to differ across education groups. Point estimates show that, compared to less educated households, more educated households (i) face lower stock market entry cost, and (ii) discount the future less. Other differences in parameters are not significant and have little power in explaining differences across education groups. Data Facts We present two types of data facts. The first are the processes characterizing exogenous labor income, out-of-pocket medical expenses during retirement and mortality risks faced by households. These processes, taken as exogenous, influence the extent to which households accumulate precautionary savings balances and how they structure their portfolios. 7 The second set of facts concerns household financial choices: asset market participation, stock share in portfolios, the frequency of stock adjustment and wealth-income ratio. These dimensions of household financial choices reflect both the aforementioned processes that households face as well as the costs of participation and adjustment. The life-cycle patterns of these choices become the moments to match in the estimation of household preference parameters and adjustment costs. Consistent with the motivation of the paper, the exogenous processes for income, mortality and medical expenses as well as the moments summarizing household choices are presented by education group. A key point of the paper is to go beyond these education specific observable facts to understand why education matters. Heterogeneity of Exogenous Processes Households are broken into four groups by (highest) educational attainment of the household head. Specifically they have years of schooling less than 12 years, equal to 12 years, over 12 but less than or equal to 16 and over 16 years respectively. Household income is defined as the sum of labor income and transfers. The data are from the Panel Study of Income Dynamics (1989Dynamics ( -2007. The Appendix provides detailed information on sample selection criteria and the decomposition method. 6 Wachter and Yogo (2010) relate the rise of stock share with educational attainment to a luxury goods assumption, underlying which is the higher income of the more educated. Similarly, Achury, Hubar, and Koulovatianos (2012) link income level to stock share through subsistence consumption. 7 Endogenous income as a result of flexible labor supply will lead to more risk taking of working households, which is shown in Bodie, 4 Heterogeneity of Exogenous Processes 2 DATA FACTS The process of log income at the household level is composed of deterministic and stochastic components: y i,t =ȳ i,t +ỹ i,t . (1) Here i indexes the household and t is the time period. As is common to empirical models that use panel data sets, age, time and cohort effects are impossible to generally separate. This is an issue for the income processes characterized in this section as well as the moments summarizing household financial decisions presented later
Niobium Uptake and Release by Bacterial Ferric Ion Binding Protein
No full textFerric ion binding proteins (Fbps) transport Fe III across the periplasm and are vital for the virulence of many Gram negative bacteria. Iron(III) is tightly bound in a hinged binding cleft with octahedral coordination geometry involving binding to protein side chains (including tyrosinate residues) together with a synergistic anion such as phosphate. Niobium compounds are of interest for their potential biological activity, which has been little explored. We have studied the binding of cyclopentadienyl and nitrilotriacetato Nb V complexes to the Fbp from Neisseria gonorrhoeae by UV-vis spectroscopy, chromatography, ICP-OES, mass spectrometry, and Nb K-edge X-ray absorption spectroscopy. These data suggest that Nb V binds strongly to Fbp and that a dinuclear Nb V centre can be readily accommodated in the interdomain binding cleft. The possibility of designing niobium-based antibiotics which block iron uptake by pathogenic bacteria is discussed
Invasive candidiasis in Pakistan: clinical characteristics, species distribution and antifungal susceptibility
No full textThis study reports for the first time, to our knowledge, descriptive epidemiological data for 188 invasive Candida isolates from Pakistan, including species identification and antifungal susceptibility against fluconazole, itraconazole, voriconazole, caspofungin, micafungin, anidulafungin and amphotericin. Risk factors for invasive candidiasis (IC) were determined for 96 patients from Karachi, Pakistan. In adults and neonates, Candida tropicalis (38 and 36 %, respectively) was the most common species, followed in adults by Candida parapsilosis (17.8 %), Candida glabrata (15.9 %) and Candida albicans (12.3 %). C. albicans (21 %) was the second most common in neonates. In children, C. albicans (31.9 %), C. tropicalis (26.4 %) and C. parapsilosis (19.4 %) were the most common. C. albicans IC was significantly associated with paediatric age [crude odds ratio (COR) 3.46, 95 % confidence interval (CI) 1.63-7.32]. Rare species made up 17.5 % of the total isolates studied. Resistance to fluconazole was seen in C. glabrata (15 .0%) and Candida krusei (100 .0%). Only one isolate (C. glabrata) was resistant to all three echinocandins. Low MICs of fluconazole for 98 % (184/188) of isolates tested support its continued use as an empiric therapy for IC. Non-C. albicans IC was associated with the use of blactam inhibitor combinations (COR 3.16, 95 % CI 1.05-9.57). Use of healthcare devices was documented in 85.4 % of IC patients, whilst 75 .0% had been admitted to special care units. Surprisingly, 66.7 % of patients with IC were not obviously immunosuppressed. The high frequency of modifiable risk factors in this population indicates that candidaemia can be reduced with stringent antibiotic and infection control measures. These data will be useful for empiric selection of antifungals in Karachi, and contribute to global assessments of antifungal resistance
Distribution and nutrient limitation of surfgrass, 2 Phyllospadix scouleri and Phyllospadix torreyi, Along the Pacific Coast of 4
No full textAbstract 1 2 Three field surveys and an extensive review of surfgrass (Phyllospadix) 3 specimens from herbarium collections in USA and Mexico were performed to delimit the 4 geographical distribution of Phyllospadix scouleri and Phyllospadix torreyi along the 5 coasts of Baja California (Mexico) which showed that both species had the same 6 distribution in the peninsula with a southern limit at 24º 31' N. Cover estimates along 3 -7 8 transects laid in the lower intertidal and upper subtidal of three locations in Baja 8 California indicated that P. scouleri occurs shallower than P. torreyi when coexisting. A 9 preliminary, short-term experimental increase of nutrient availability in the water column 10 at one of the study sites suggested that the biomass and growth rates of P. torreyi were 11 more limited by the availability of nutrients than those of P. scouleri. 12 1
Late emergence of A594V and L595W mutations related to ganciclovir resistance in a patient with HCMV retinitis and long-term HIV progression
No full textAbstract The emergence of ganciclovir (GCV) resistance during the treatment of human cytomegalovirus (HCMV) infection is a serious clinical challenge, and is associated with high morbidity and mortality. In this case report, we describe the emergence of two consecutive mutations (A594V and L595W) related to GCV resistance in a patient with HCMV retinitis and long-term HIV progression after approximately 240 days of GCV use. Following the diagnosis of retinitis, the introduction of GCV did not result in viral load reduction. The detected mutations appeared late in the treatment, and we propose that other factors (high initial HCMV load, previous GCV exposure, low CD4 + cell count), in addition to the presence of resistance mutations, may have contributed to the treatment failure of HCMV infection in this patient