Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women

Identifying the return of fertility with cervical mucus observations is challenging during the postpartum period. Use of urinary measurements of estrogen and progesterone can assist in understanding the return to fertility during this period. The purposes of this study were to describe the postpartum return of fertility by an analysis of total estrogen (TE) and pregnanediol glucuronide (PDG) profiles and to correlate these profiles with cervical mucus observations. Twenty-six participants collected urine samples during the postpartum period and recorded mucus scores. TE and PDG hormones were analyzed and compared with mucus scores. During amenorrhea, mucus reflected TE changes in only 35 percent of women; after amenorrhea, typical mucus patterns were seen in 33 percent of cycles. We concluded that postpartum mucus and hormone profiles are significantly dissociated but that monitoring urinary hormones may assist in identifying the return of fertility. We also identified different hormonal patterns in the return to fertility. The postpartum period is a challenging time for identifying the return of fertility. The purposes of this study were to describe the hormonal patterns during the return of fertility and to correlate these patterns with cervical mucus observations. Twenty-six postpartum women collected urine samples and recorded mucus scores. Urinary estrogen and progesterone hormones were analyzed and compared with mucus scores. Before the return of menses, mucus reflected hormonal changes in only 35 percent women and after first menses in 33 percent of cycles. We found that hormone profiles do not correlate well with mucus observations during the postpartum return of fertility

Bow-Tie Microstrip Antenna Design

In this paper, the bow-tie microstrip antennas have been designed with two different angles of 40° and 80°. An investigaton on the effect of the angle to the return loss and radiation patterns had been carried out. The impedance matching network with the niicrostrip transmission line feeding was used in this study. Simulation and measurement results for the return loss and radiation patterns were presented

Self-Selection Patterns among Return Migrants: Mexico 1990-2010

This paper analyzes the self-selection patterns among Mexican return migrants during the period from 1990 to 2010. Using census data, we can identify return migrants who have lived in the United States within the previous 5 years but who currently live in Mexico. To calculate the selection patterns, we non parametrically estimate the counterfactual wages that the return migrants would have experienced had they never migrated by using the wage structure of non migrants. We find evidence that the selection patterns change over time toward negative selection. For example, in 1990, the wages that the male return migrants would have experienced had they not migrated was 6 percent larger than the wages of male non migrants. However, by 2010, the difference had declined to -14 percent. The increasing negativity of the degree of selection is robust to the analysis of specific subgroups: rural and urban, men and women, and states with high migration rates and low migration rates. Moreover, the negative selection results for the period from 2000 to 2010 are robust to the use of different surveys that define a return migrant by using distinct characteristics. Additionally, we observe that the wages of return migrants are larger than those that the migrants would have obtained had they not migrated. This finding shows that migration has a positive effect on the Mexican economy.Mexican migration, self-selection, return migration, wages

It's the market power, stupid! Stock return patterns in international bank M&A

This paper analyzes capital market reactions to international bank M&A. We investigate combined stock return patterns of targets, bidders, and their peers upon takeover announcement, and closing or withdrawal. We distinguish five common M&A hypotheses and relate characteristic and mutually exclusive abnormal stock return patterns to each hypothesis. We find that investors believe in gains through the exploitation of market power by the post-merger entity. In a multinomial logistic model we show that patterns related to market power significantly concur with large relative target size, intra-industry mergers, and increasing market concentration, suggesting a substantial lessening of competition through M&A. --M&A,Banks,Event Study,Peer Returns,Market Power

Overview of the labour market [June 2011]

Inevitably current interest in the Scottish labour market continues to focus on the trends in both employment and unemployment figures, a theme developed in other sections of this edition. Public interest continues to focus on public sector employment trends and for a further issue we return to these themes. Of interest is the impact of patterns and behaviour of immigrants to and emigrants from Scotland on recent employment patterns, and initially recent findings are considered

Towards the characterization of individual users through Web analytics

We perform an analysis of the way individual users navigate in the Web. We focus primarily in the temporal patterns of they return to a given page. The return probability as a function of time as well as the distribution of time intervals between consecutive visits are measured and found to be independent of the level of activity of single users. The results indicate a rich variety of individual behaviors and seem to preclude the possibility of defining a characteristic frequency for each user in his/her visits to a single site.Comment: 8 pages, 4 figures. To appear in Proceeding of Complex'0

Why are stock market returns correlated with future economic activities?

Stock price, because it is a forward-looking variable, forecasts economic activities. An unexpected increase in stock price reflects that (i) future dividend growth is higher and/or (ii) future discount rates are lower than previously anticipated; therefore, the increase predicts higher output and investment. As well, other studies argue for an important relation between the expected stock market return and investment. In this paper, Hui Guo analyzes the relative importance of these mechanisms by using Campbell and Shiller’s (1988) method to decompose stock market return into three parts: expected return, a shock to the expected future return, and a shock to the expected future dividend growth. Contrary to the conventional wisdom, the author finds that dividend shocks are a rather weak predictor for future economic activities. Moreover, the expected return and shocks to the expected future return display different predictive patterns. The results shown here, collectively, explain why the forecasting power of stock market return is rather limited.Stock market

Insertions Yielding Equivalent Double Occurrence Words

A double occurrence word (DOW) is a word in which every symbol appears exactly twice; two DOWs are equivalent if one is a symbol-to-symbol image of the other. We consider the so called repeat pattern ($\alpha\alpha$) and the return pattern ($\alpha\alpha^R$), with gaps allowed between the $\alpha$'s. These patterns generalize square and palindromic factors of DOWs, respectively. We introduce a notion of inserting repeat/return words into DOWs and study how two distinct insertions into the same word can produce equivalent DOWs. Given a DOW $w$, we characterize the structure of $w$ which allows two distinct insertions to yield equivalent DOWs. This characterization depends on the locations of the insertions and on the length of the inserted repeat/return words and implies that when one inserted word is a repeat word and the other is a return word, then both words must be trivial (i.e., have only one symbol). The characterization also introduces a method to generate families of words recursively

Quantum pattern recognition with liquid-state nuclear magnetic resonance

A novel quantum pattern recognition scheme is presented, which combines the idea of a classic Hopfield neural network with adiabatic quantum computation. Both the input and the memorized patterns are represented by means of the problem Hamiltonian. In contrast to classic neural networks, the algorithm can return a quantum superposition of multiple recognized patterns. A proof of principle for the algorithm for two qubits is provided using a liquid state NMR quantum computer.Comment: updated version, Journal-ref adde

The Return to Capital and the Business Cycle

A widely cited failing of real business cycle models is their inability to account for the cyclical patterns of financial variables. Perhaps less well known is the fact that the return to capital and equity are identical in the neoclassical growth model. This paper constructs a measure of the return to business capital for the U.S. The S&P 500 return is roughly six times more volatile than the return to business capital. Owing to the equivalence between the returns to capital and equity in the neoclassical growth model, papers in the real business cycle literature that successfully account for the time series variation in the S&P 500 return must fail to account for the time series properties of the return to capital. A fairly basic real business cycle model captures most of the observed variability in the return to capital. What is needed is a theory of the stock market that breaks the equivalence between the returns to equity and capital. Forthcoming, Review of Economic Dynamicsreturn to capital, business cycles, asset returns