Assisted reproductive technology and women’s choice to pursue professional careers

We examine the impact of assisted reproductive technology on women’s choice to pursue professional careers. We hypothesize that the availability of assisted reproductive technology increases the expected benefits of a professional degree by allowing women to delay childbearing in their 20s and 30s while establishing their careers, thereby reaping greater financial benefit from human capital investment. State-level timing differences in the enactment of laws which mandated infertility treatment coverage in employer-sponsored health plans allow us to exploit state, year, and cohort variation in women’s ages at the time the laws are passed. These insurance mandates dramatically increase access to assisted reproductive technology. Using a triple difference strategy, we find that a mandate to cover assisted reproductive technology does increase the probability that a woman chooses to invest in a professional degree and to work in a professional career.     

Body mass index and functional status in community dwelling older Turkish males

Abstract

Objectives: To assess sex hormones in men with obesity and prostate cancer (PCa) and to study association between androgens and the pathogenesis biology of PCa in vitro.

Subjects and methods: One hundred and eighty-one men older than 45?years selected from of a population attending to Urology departments screening for PCa, (78 participants without PCa and 103 patients with PCa). All participants were assessed for body mass index (BMI), age, Gleason score, and PSA. Endocrine profile was determined for LH, total testosterone (TT), 17β-estradiol (E2), prolactin and leptin. Biochemical profile (HbA1c, triacylglycerols and lipoproteins) was also determined. In vitro experiments were also performed, involving the study of 5α-dihydrotestosterone (DHT) and E2 in the presence of adipocyte-conditioned medium (aCM).

Results: All variables were continuous and described a Gaussian distribution unless mentioned. To determine the relation of aggressiveness, variable were transformed into categories. Thus, PCa aggressiveness is associated with the increase of age and BMI (p?<?.0001) but with is decreased with TT and E2 (p?<?.05). Moreover, adipocyte-secreted molecules increase aggressiveness of PCa cells in vitro. Lastly, DTH but not E2 enables invasiveness in vitro.

Conclusions: It was observed a coexistence of hormone axis profile alteration with sex hormones and BMI in PCa patients, in accordance with the new perspective of PCa pathogenesis.     

Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic

In human reliability analysis (HRA), dependence analysis refers to assessing the influence of the failure of the operators to perform one task on the failure probabilities of subsequent tasks. A commonly used approach is the technique for human error rate prediction (THERP). The assessment of the dependence level in THERP is a highly subjective judgment based on general rules for the influence of five main factors. A frequently used alternative method extends the THERP model with decision trees. Such trees should increase the repeatability of the assessments but they simplify the relationships among the factors and the dependence level. Moreover, the basis for these simplifications and the resulting tree is difficult to trace. The aim of this work is a method for dependence assessment in HRA that captures the rules used by experts to assess dependence levels and incorporates this knowledge into an algorithm and software tool to be used by HRA analysts. A fuzzy expert system (FES) underlies the method. The method and the associated expert elicitation process are demonstrated with a working model. The expert rules are elicited systematically and converted into a traceable, explicit, and computable model. Anchor situations are provided as guidance for the HRA analyst's judgment of the input factors. The expert model and the FES‐based dependence assessment method make the expert rules accessible to the analyst in a usable and repeatable way, with an explicit and traceable basis.     

CUSTOMER OWNERSHIP AND QUALITY PROVISION IN PUBLIC SERVICES UNDER ASYMMETRIC INFORMATION

The implementation of projects producing external effects is often a source of disagreement and conflict between hosting and nonhosting communities. The article focuses on the impact of participatory ownership on conflict resolution and social welfare in the presence of asymmetric information and imperfect quality monitoring. We show that in such situations the participatory solution may help solve deadlocks that money transfers to a for‐profit operator cannot solve. The analysis highlights three main factors behind this fact. First, a customer‐owned cooperative internalizes, at least partially, the external effects generated by the project. Second, the alignment of cooperative members' preferences with those of the social planner reduces (in some cases eliminates) the distortions caused by information asymmetries. Third, cooperatives require less costly monitoring than their for‐profit counterparts. We also show that cooperatives' productive inefficiency with respect to for‐profits may emerge endogenously as a consequence of a lower pressure to compete on costs for the market. (JEL H23, L33, P13)     

Strategic choices and strategic management accounting in large manufacturing firms

Journal of Management and Governance - This study examines the relationship between strategic choices and the use of strategic management accounting (SMA) techniques in large manufacturing...     

Measuring the Behavioural Component of the S&P 500 and its Relationship to Financial Stress and Aggregated Earnings Surprises

Scholars in management and economics have shown increasing interest in isolating the behavioural dimension of market evolution. Indeed, by improving forecast accuracy and precision, this exercise would certainly help firms to anticipate economic fluctuations, thus leading to more profitable business and investment strategies. Yet, how to extract the behavioural component from real market data remains an open question. By using monthly data on the returns of the constituents of the S&P 500 index, we propose a Bayesian methodology to measure the extent to which market data conform to what is predicted by prospect theory (the behavioural perspective), relative to the (standard) subjective expected utility theory baseline. We document a significant behavioural component that reaches its peaks during recession periods and is correlated to measures of financial volatility, market sentiment and financial stress with expected sign. Moreover, the behavioural component decreases around macroeconomic corporate earnings news, while it reacts positively to the number of surprising announcements.     

A neural network clustering model for miscellaneous components production planning

The growing importance of providing service to customers, e.g. post-sale assistance, supplying of spare parts, upgrading and integration of new elements in installed systems, enhances the importance of planning and management of upgrading parts in most manufacturing industries. These parts are generally characterized by high technical heterogeneity and have a highly variable and difficult to forecast demand. In some areas (especially the most dynamic, e.g. high-tech products), these kinds of components are quite common, and represent a very strong relation between the manufacturing firm and the market. These parts are generally too many to be efectively supported on a planning database system with individual records and too heterogeneous ( and sometimes with a too high value) to be supported all together in a single record. In this paper, we want to study the application of adaptive techniques for the clustering of these components in classes based on the similarities in their market behaviour in order to build an optimal database for planning production and supplying of these components.     

“I Know That You Know How I Feel”: Behavioral and Physiological Signals Demonstrate Emotional Attunement While Interacting with a Computer Simulating Emotional Intelligence

Human–human communication studies have suggested that within communicative interactions, individuals acknowledge each other as intentional agents and adjust their emotion nonverbal behavior according to the other. This process has been defined as emotional attunement. In this study, we examine the emotional attunement process in the context of affective human–computer interactions. To this purpose, participants were exposed to one of two conditions. In one case, they played with a computer that simulated understanding of their emotional reactions while guiding them across four different game-like activities; in the other, the computer guided participants across the activities without mentioning any ability to understand emotional responses. Face movements, gaze direction, posture, vocal behavior, electrocardiogram and electrodermal activity were simultaneously recorded during the experimental sessions. Results showed that if participants were aware of interacting with an agent able to recognize their emotions, they reported that the computer was able to “understand” them and showed a higher number of nonverbal behaviors during the most interactive activity. The implications are discussed.