Grandparental effects on reproductive strategizing

This paper analyzes data from the household registers for two villages in the Nôbi region of central Japan in the late Edo period (1717-1869) to assess how grandparents may have affected reproductive strategizing in stem families. The particulars of the family system fostered a culturally favored set of reproductive goals, in particular, a daughter as eldest child, followed by a son (and heir), coupled with gender alternation in subsequent reproduction and overall gender balance. This reproductive strategy was generally followed during the stem phase of the domestic cycle, when one or both grandparents were present, especially when the family head was in the senior generation. By contrast, a son-first strategy was favored when childbearing began in the conjugal phase of the cycle. This suggests grandparental influence on the junior couple’s reproductive decisions in favor of the cultural ideal. I find that the senior couple’s decision to marry the heir early or late strongly affects the reproductive strategies followed by him after marriage. I show that when a grandmother is present at the onset of childbearing, especially if she is relatively young, the junior couple ends up with more offspring on average. A controlled analysis of infanticiding behavior is interpreted in terms of conjugal power and coalition formation. It appears that a grandmother gets her way only when she and her son gang up on the daughter-in-law, but such a coalition is likely only when her son dominates the conjugal relationship (which in turn reflects the grandmother’s success in binding the son tightly to her emotionally and in delaying his marriage). Otherwise, the grandmother may be shut out from reproductive decision-making by the solidary conjugal coalition.family, historical household studies, infanticide, Japan, reproductive strategies

The effect of homogenization at different pressures on the physical properties of an ice cream mixture and the resulting ice cream

The data presented in this bulletin were taken from a thesis submitted by the junior author in partial fulfillment of the requirements for the degree of Master of Arts in the Graduate School of the University of Missouri, 1927--P. [3].Includes bibliographical references (page 24)

Honey Bee Survival and Pathogen Prevalence: From the Perspective of Landscape and Exposure to Pesticides

In order to study the in situ effects of the agricultural landscape and exposure to pesticides on honey bee health, sixteen honey bee colonies were placed in four different agricultural landscapes. Those landscapes were three agricultural areas with varying levels of agricultural intensity (AG areas) and one non-agricultural area (NAG area). Colonies were monitored for different pathogen prevalence and pesticide residues over a period of one year. RT-qPCR was used to study the prevalence of seven different honey bee viruses as well as Nosema sp. in colonies located in different agricultural systems with various intensities of soybean, corn, sorghum, and cotton production. Populations of the parasitic mite Varroa destructor were also extensively monitored. Comprehensive MS-LC pesticide residue analyses were performed on samples of wax, honey, foragers, winter bees, dead bees, and crop flowers for each apiary and location. A significantly higher level of varroa loads were recorded in colonies of the AG areas, but this at least partly correlated with increased colony size and did not necessarily result from exposure to pesticides. Infections of two viruses (deformed wing virus genotype a (DWVa) and acute bee paralysis virus (ABPV)) and Nosema sp. varied among the four studied locations. The urban location significantly elevated colony pathogen loads, while AG locations significantly benefited and increased the colony weight gain. Cotton and sorghum flowers contained high concentrations of insecticide including neonicotinoids, while soybean and corn had less pesticide residues. Several events of pesticide toxicity were recorded in the AG areas, and high concentrations of neonicotinoid insecticides were detected in dead bees

Processing CCD Images to Detect Transits of Earth-Sized Planets: Maximizing Sensitivity While Achieving Reasonable Downlink Requirements

We have performed end-to-end laboratory and numerical simulations to demonstrate the capability of differential photometry under realistic operating conditions to detect transits of Earth-sized planets orbiting solar-like stars. Data acquisition and processing were conducted using the same methods planned for the proposed Kepler Mission. These included performing aperture photometry on large-format CCD images of an artificial star fields obtained without a shutter at a readout rate of 1 megapixel/sec, detecting and removing cosmic rays from individual exposures and making the necessary corrections for nonlinearity and shutterless operation in the absence of darks. We will discuss the image processing tasks performed `on-board' the simulated spacecraft, which yielded raw photometry and ancillary data used to monitor and correct for systematic effects, and the data processing and analysis tasks conducted to obtain lightcurves from the raw data and characterize the detectability of transits. The laboratory results are discussed along with the results of a numerical simulation carried out in parallel with the laboratory simulation. These two simulations demonstrate that a system-level differential photometric precision of 10-5 on five- hour intervals can be achieved under realistic conditions

Precision exercise medicine: understanding exercise response variability

There is evidence from human twin and family studies as well as mouse and rat selection experiments that there are considerable interindividual differences in the response of cardiorespiratory fitness (CRF) and other cardiometabolic traits to a given exercise programme dose. We developed this consensus statement on exercise response variability following a symposium dedicated to this topic. There is strong evidence from both animal and human studies that exercise training doses lead to variable responses. A genetic component contributes to exercise training response variability. In this consensus statement, we (1) briefly review the literature on exercise response variability and the various sources of variations in CRF response to an exercise programme, (2) introduce the key research designs and corresponding statistical models with an emphasis on randomised controlled designs with or without multiple pretests and post-tests, crossover designs and repeated measures designs, (3) discuss advantages and disadvantages of multiple methods of categorising exercise response levels-a topic that is of particular interest for personalised exercise medicine and (4) outline approaches that may identify determinants and modifiers of CRF exercise response. We also summarise gaps in knowledge and recommend future research to better understand exercise response variability531811411153The consensus meeting that led to the writing of this manuscript was held with the financial support of the Pennington Biomedical Research Foundation, the Pennington Biomedical Research Center Division of Education, the LSU Boyd Professorship and the John W. Barton, Sr. Chair in Genetics and Nutrition. No funding and/or honorarium was provided to any member of the writing group for the production of this manuscrip

Association of Accelerometry-Measured Physical Activity and Cardiovascular Events in Mobility-Limited Older Adults: The LIFE (Lifestyle Interventions and Independence for Elders) Study.

BACKGROUND:Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. METHODS AND RESULTS:Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24 months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500 steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30 minutes spent performing activities ≥500 counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24 months), both the number of steps per day (per 500 steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500 counts per minute (per 30 minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. CONCLUSIONS:Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score >10 on the Short Physical Performance Battery) both using baseline and longitudinal data. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT01072500

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data

Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about their biology. Yet, as more experiments are considered, a complex’s signature may become conditional and less identifiable. Previously we successfully distinguished the general proteomic signature of genuine chromosomal proteins from hitchhikers using the Random Forests (RF) machine learning algorithm. Here we test whether small protein complexes can define distinguishable signatures of their own, despite the assumption that machine learning needs large training sets. We show, with simulated and real proteomics data, that RF can detect small protein complexes and relationships between them. We identify several complexes in quantitative proteomics results of wild-type and knockout mitotic chromosomes. Other proteins covary strongly with these complexes, suggesting novel functional links for later study. Integrating the RF analysis for several complexes reveals known interdependences among kinetochore subunits and a novel dependence between the inner kinetochore and condensin. Ribosomal proteins, although identified, remained independent of kinetochore subcomplexes. Together these results show that this complex-oriented RF (NanoRF) approach can integrate proteomics data to uncover subtle protein relationships. Our NanoRF pipeline is available online

The SEC\u27s Misguided Climate Disclosure Rule Proposal

The following article adapts and consolidates two comment letters submitted last spring by a group of twenty-two professors of finance and law on the SEC’s proposed climate change disclosure rules. The professors reiterate their recommendation that the SEC withdraw its proposal as legally misguided, while outlining some of the issues that the proposal will face when challenged in court