The C-5A active lift distribution control system

The ALDCS development and design tasks, ALDCS functional configuration, and resulting challenges encountered while accomplishing the first phase of the program are described. These tasks are establishing system requirements and criteria and synthesizing a system mechanization to meet the desired load alleviation, stability margins, flight safety, and flying qualities performance. Results of the ALDCS development and prototype system flight simulation programs, and control law optimization including system stability, handling qualities and structural load analyses are presented, along with concluding remarks relative to the system design integration

Extension schools in agriculture

"Extension schools in agriculture are courses of instruction offered by the University of Missouri College of Agriculture to farmers in the state who cannot take advantage of the courses given at Columbia. These schools offer five days of consecutive teaching in two or at most, three subjects of special interest in the community. They provide more complete and detailed instruction than can be given in the one-day or two-day farmers' meetings and are designed for the practical farmer. The aim of these schools is to present as briefly and clearly as possible the fundamental scientific principles underlying the common farm practices to the end that farmers may be guided in the application of such practices not by specific recommendations but by an intelligent understanding of the various physical and economic factors involved."--Page 3

Psychosocial Mechanisms Underlying Older Black Men’s Health

Objectives: To evaluate the psychosocial mechanisms underlying older Black men's self-rated health, we examined: (a) the individual, cumulative, and collective effects of stressors on health; (b) the direct effects of psychosocial resources on health; and (c) the stress-moderating effects of psychosocial resources. Method: This study is based on a nationally representative sample of Black men aged 51-81 (N = 593) in the Health and Retirement Study (HRS). Ordinary least squares (OLS) regression models of the psychosocial determinants of self-rated health draw on data from the HRS 2010 and 2012 Core datasets and Psychosocial Modules. Results: Each of the six measures of stressors as well as a cumulative measure of stressors are predictive of worse self-rated health. However, when considered collectively, only two stressors (chronic strains and traumatic events) have statistically significant effects. Furthermore, two of the five psychosocial resources examined (mastery and optimism) have statistically significant protective effects, and prayer moderates the harmful effects of traumatic events on self-rated health. Discussion: Conventional measures of stressors and coping resources-originally developed to account for variance in health outcomes among predominantly white samples-may not capture psychosocial factors most salient for older Black men's health. Future research should incorporate psychosocial measures that reflect their unique experiences

BRIEF COMMUNICATION The projection of species distribution models

and the problem of non-analog climat

Monitoring 2009 Forest Disturbance Across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

This case study shows the promise of computing current season forest disturbance detection products at regional to CONUS scales. Use of the eMODIS expedited product enabled a NRT CONUS forest disturbance detection product, a requirement for an eventual, operational forest threat EWS. The 2009 classification product from this study can be used to quantify the areal extent of forest disturbance across CONUS, although a quantitative accuracy assessment still needs to be completed. However, the results would not include disturbances that occurred after July 27, such as the Station Fire. While not shown here, the project also produced maximum NDVI products for the June 10-July 27 period of each year of the 2000-2009 time frame. These products could be applied to compute forest change products on an annual basis. GIS could then be used to assess disturbance persistence. Such follow-on work could lead to attribution of year in which a disturbance occurred. These products (e.g., Figures 6 and 7) may also be useful for assessing forest change associated with climate change, such as carbon losses from bark beetle-induced forest mortality in the Western United States. Other MODIS phenological products are being assessed for aiding forest monitoring needs of the EWS, including cumulative NDVI products (Figure 10)

Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broad-scale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other data sets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US

Pengaruh Interaksi Sosial dan Efikasi Diri terhadap Kecerdasan Emosi (Survey pada Mahasiswa Pendidikan Akuntansi Upi)

Penelitian ini dilatarbelakangi oleh rendahnya sebagian mahasiswa Pendidikan Akuntansi berkaitan dengan kecerdasan emosi mahasiswa Pendidikan Akuntansi. Pentingnya mengkaji kecerdasan emosi mahasiswa, berkaitan dengan tujuan program studi Pendidikan Akuntansi yaitu mempersiapkan calon guru akuntansi menjelang PPL, dimana bukan hanya aspek kecerdasan intelgensi, namun kecerdasan emosi juga sangat penting dalam mempersiapkan mahasiswa terutama. Teori untuk membahas penelitian ini adalah kecerdasan Emosi dari Goleman, efikasi diri dari Bandura dan Interaksi sosial Tujuan penelitian ini adalah untuk mengkaji pengaruh interaksi sosial dan efikasi diri terhadap kecerdasan emosi. Metode penelitian menggunakan verifikatif dengan desain survey ekspalanatory. Populasi seluruh mahasiswa Pendidikan Akuntansi sebanyak dengan sampel 120 responden. Pengumpulan data dengan angket dan analisis data menggunakan analisis jalur (path analysis). Hasil penelitian menunjukkan bahwa interaksi sosial dan efikasi diri baik secara parsial maupun secara simultan berpengaruh positif terhadap kecerdasan emosi. Dengan Interaksi sosial sebagai faktor yang paling berpengaruh terhadap kecerdasan emosi. Berdasarkan analisis data, maka diperlukan peningkatan indikator yang masih rendah yaitu indikator kerjasama dalam variabel interaksi sosial dan perencanaan pengaturan diri dalam variabel efikasi diri

Evidence for a Time-Invariant Phase Variable in Human Ankle Control

Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-dependent feedback to accommodate perturbations. Two popular theories have been proposed for the underlying embodiment of phase in the human pattern generator: a time-dependent internal representation or a time-invariant feedback representation (i.e., reflex mechanisms). In either case the neuromuscular system must update or represent the phase of locomotor patterns based on the system state, which can include measurements of hundreds of variables. However, a much simpler representation of phase has emerged in recent designs for legged robots, which control joint patterns as functions of a single monotonic mechanical variable, termed a phase variable. We propose that human joint patterns may similarly depend on a physical phase variable, specifically the heel-to-toe movement of the Center of Pressure under the foot. We found that when the ankle is unexpectedly rotated to a position it would have encountered later in the step, the Center of Pressure also shifts forward to the corresponding later position, and the remaining portion of the gait pattern ensues. This phase shift suggests that the progression of the stance ankle is controlled by a biomechanical phase variable, motivating future investigations of phase variables in human locomotor control.United States Army Medical Research Acquisition Activity (USAMRAA grant W81XWH-09-2-0020)National Institute of Neurological Disorders and Stroke (U.S.) (NIH award number F31NS074687)Burroughs Wellcome Fund (Career Award at the Scientific Interface

Using Multiple-hierarchy Stratification and Life Course Approaches to Understand Health Inequalities: The Intersecting Consequences of Race, Gender, SES, and Age

This study examines how the intersecting consequences of race-ethnicity, gender, socioeconomics status (SES), and age influence health inequality. We draw on multiple-hierarchy stratification and life course perspectives to address two main research questions. First, does racial-ethnic stratification of health vary by gender and/or SES? More specifically, are the joint health consequences of racial-ethnic, gender, and socioeconomic stratification additive or multiplicative? Second, does this combined inequality in health decrease, remain stable, or increase between middle and late life? We use panel data from the Health and Retirement Study (N = 12,976) to investigate between- and within-group differences in in self-rated health among whites, blacks, and Mexican Americans. Findings indicate that the effects of racial-ethnic, gender, and SES stratification are interactive, resulting in the greatest racial-ethnic inequalities in health among women and those with higher levels of SES. Furthermore, racial-ethnic/gender/SES inequalities in health tend to decline with age. These results are broadly consistent with intersectionality and aging-as-leveler hypotheses