Mittelstand und EU-Osterweiterung

Viele Umfragen deuten auf eine massive Abwanderung des deutschen Mittelstands in die neuen EU Beitrittsländer hin. Inwieweit kann dieser Exodus empirisch untermauert werden? In welchen Aktivitäten engagieren sich die deutschen mittelständischen Unternehmen in den Beitrittsländern? Welche Chancen und Risiken erwarten sie von der Osterweiterung

Mittelstand und EU-Osterweiterung

Viele Umfragen deuten auf eine massive Abwanderung des deutschen Mittelstands in die neuen EU Beitrittsländer hin. Inwieweit kann dieser Exodus empirisch untermauert werden? In welchen Aktivitäten engagieren sich die deutschen mittelständischen Unternehmen in den Beitrittsländern? Welche Chancen und Risiken erwarten sie von der Osterweiterung? --

Thermal resistivity of layered 4He films on ZYX graphite below 2 K

Thermal resistance and vapor pressure isotherms were taken near superfluid onset for ultra-thin helium films adsorbed on a ZYX graphite wafer between 1-2 K and 3-7 atomic layers. Our data are consistent with previous graphite onsets and are compatible with a current model of film droplet formation. Overlap of thermal resistance curves at 1.19 and 139 K is believed to be associated with discrete layering effects of 2D superfluid film properties.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23266/1/0000201.pd

Thermal resistivity of layered 4He films on ZYX graphite below 2 K

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23286/1/0000223.pd

Structural imaging of a thick-walled carbon microtubule

We analyze the structure of a thick-walled carbon microtubule based on direct electron beam imaging of the graphitic cylinders comprising the fiber. Clearly resolved six-fold symmetry of basal planes overlying the fiber core indicate zero overall fiber helicity and alignment of individual cylinders. Sidewall measurements calibrated from the {100} core fringes show uniform spacings of about 0.375 nm, which are larger than those reported for other microtubules or for crystalline graphite (0.335 nm). Short zones of local 3o helicity are observed along the fiber. Structural transitions which alter the helicity are characterized by extra atomic planes and other defects, including nested sub-tubules. We discuss implications for the fiber's growth and electrical properties.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31407/1/0000324.pd

Corazonin Neurons Function in Sexually Dimorphic Circuitry That Shape Behavioral Responses to Stress in Drosophila

All organisms are confronted with dynamic environmental changes that challenge homeostasis, which is the operational definition of stress. Stress produces adaptive behavioral and physiological responses, which, in the Metazoa, are mediated through the actions of various hormones. Based on its associated phenotypes and its expression profiles, a candidate stress hormone in Drosophila is the corazonin neuropeptide. We evaluated the potential roles of corazonin in mediating stress-related changes in target behaviors and physiologies through genetic alteration of corazonin neuronal excitability. Ablation of corazonin neurons confers resistance to metabolic, osmotic, and oxidative stress, as measured by survival. Silencing and activation of corazonin neurons lead to differential lifespan under stress, and these effects showed a strong dependence on sex. Additionally, altered corazonin neuron physiology leads to fundamental differences in locomotor activity, and these effects were also sex-dependent. The dynamics of altered locomotor behavior accompanying stress was likewise altered in flies with altered corazonin neuronal function. We report that corazonin transcript expression is altered under starvation and osmotic stress, and that triglyceride and dopamine levels are equally impacted in corazonin neuronal alterations and these phenotypes similarly show significant sexual dimorphisms. Notably, these sexual dimorphisms map to corazonin neurons. These results underscore the importance of central peptidergic processing within the context of stress and place corazonin signaling as a critical feature of neuroendocrine events that shape stress responses and may underlie the inherent sexual dimorphic differences in stress responses

Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: application to North American waterfowl

Background: Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods: Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results: Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions: Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing