ESTIMATION OF FIRM-VARYING, INPUT-SPECIFIC EFFICIENCIES IN DAIRY PRODUCTION

Firm-varying production technologies were estimated using random coefficients regression methods for a sample of Massachusetts dairy farms. Results were compared to OLS Cobb-Douglas production function estimates. The random coefficients regression model was found to virtually eliminate conventionally measured firm technical inefficiencies by estimating individual firm technologies and ascribing remaining inefficiencies to specific inputs. Input-specific measures of firm inefficiencies showed hired labor, land, and machinery inputs to be used in excess of efficient levels. Livestock supplies were underutilized by all farms. Efficiencies of feed, crop materials, fuels, and utilities varied, although estimated means were closer to optimal levels.Production Economics,

Cerebral blood flow changes in Parkinson?s disease associated with dementia

Dementia is one of the main non-motor symptoms of Parkin- son's disease (PD) and it is diagnosed in about 30% of cases. Its aetiology remains unclear and contributing factors are con- troversial. Dementia may be more common in old patients with severe motor symptoms and mild cognitive impairment. Clini- co-pathological studies show the association between demen- tia in PD and the age-related group of dementias, such as AD and VaD. A valuable aid in the assessment of dementia in PD is cerebral blood flow (CBF) brain SPECT scanning. It shows three differ- ent patterns of rCBF reduction, including frontal lobe hypoper- fusion, iuAlzheimer-likel type of hypoperfusion and multiple, vas- cular defects. The heterogeneity of rCBF reduction may reflect the multifactorial pathophysiology of dementia in PD. It may result from concomitant AD pathology, cerebrovascular disease, destruction of nigro-striato-frontal projection or may be a dis- tinct disease of different aetiology

The Newtonian potential of thin disks

The one-dimensional, ordinary differential equation (ODE) by Hur\'e & Hersant (2007) that satisfies the midplane gravitational potential of truncated, flat power-law disks is extended to the whole physical space. It is shown that thickness effects (i.e. non-flatness) can be easily accounted for by implementing an appropriate "softening length" $\lambda$. The solution of this "softened ODE" has the following properties: i) it is regular at the edges (finite radial accelerations), ii) it possesses the correct long-range properties, iii) it matches the Newtonian potential of a geometrically thin disk very well, and iv) it tends continuously to the flat disk solution in the limit $\lambda \rightarrow 0$. As illustrated by many examples, the ODE, subject to exact Dirichlet conditions, can be solved numerically with efficiency for any given colatitude at second-order from center to infinity using radial mapping. This approach is therefore particularly well-suited to generating grids of gravitational forces in order to study particles moving under the field of a gravitating disk as found in various contexts (active nuclei, stellar systems, young stellar objects). Extension to non-power-law surface density profiles is straightforward through superposition. Grids can be produced upon request.Comment: Accepted for publication in A&

Model Reduction for Multiscale Lithium-Ion Battery Simulation

In this contribution we are concerned with efficient model reduction for multiscale problems arising in lithium-ion battery modeling with spatially resolved porous electrodes. We present new results on the application of the reduced basis method to the resulting instationary 3D battery model that involves strong non-linearities due to Buttler-Volmer kinetics. Empirical operator interpolation is used to efficiently deal with this issue. Furthermore, we present the localized reduced basis multiscale method for parabolic problems applied to a thermal model of batteries with resolved porous electrodes. Numerical experiments are given that demonstrate the reduction capabilities of the presented approaches for these real world applications

A key-formula to compute the gravitational potential of inhomogeneous discs in cylindrical coordinates

We have established the exact expression for the gravitational potential of a homogeneous polar cell - an elementary pattern used in hydrodynamical simulations of gravitating discs. This formula, which is a closed-form, works for any opening angle and radial extension of the cell. It is valid at any point in space, i.e. in the plane of the distribution (inside and outside) as well as off-plane, thereby generalizing the results reported by Durand (1953) for the circular disc. The three components of the gravitational acceleration are given. The mathematical demonstration proceeds from the "incomplete version of Durand's formula" for the potential (based on complete elliptic integrals). We determine first the potential due to the circular sector (i.e. a pie-slice sheet), and then deduce that of the polar cell (from convenient radial scaling and subtraction). As a by-product, we generate an integral theorem stating that "the angular average of the potential of any circular sector along its tangent circle is 2/PI times the value at the corner". A few examples are presented. For numerical resolutions and cell shapes commonly used in disc simulations, we quantify the importance of curvature effects by performing a direct comparison between the potential of the polar cell and that of the Cartesian (i.e. rectangular) cell having the same mass. Edge values are found to deviate roughly like 2E-3 x N/256 in relative (N is the number of grid points in the radial direction), while the agreement is typically four orders of magnitude better for values at the cell's center. We also produce a reliable approximation for the potential, valid in the cell's plane, inside and close to the cell. Its remarkable accuracy, about 5E-4 x N/256 in relative, is sufficient to estimate the cell's self-acceleration.Comment: Accepted for publication in Celestial Mechanics and Dynamical Astronom

The Relationship between Dog Ownership, Psychopathological Symptoms and Health-Benefitting Factors in Occupations at Risk for Traumatization

Individuals working in high-risk occupations (e.g., emergency staff) are exposed to high levels of occupational stress including traumatic events. Correspondingly, several studies report high rates of mental health problems among these occupations. Pet ownership has been associated with better mental health. However, to date a study on the association between pet ownership and indicators of mental health in these occupations is missing. The present cross-sectional survey (N = 580) investigated pet ownership, attachment to pets, health-benefitting factors (i.e., sense of coherence, trait-resilience, locus of control) and psychopathological symptoms (i.e., general mental health problems, posttraumatic stress, burnout) in medical staff, police officers, and firefighters. Dog owners and non-dog owners showed comparable levels of psychopathological distress and health-benefitting factors. Compared to cat owners, dog owners demonstrated stronger emotional attachment to their pet. Moreover, a stronger attachment was also linked to higher levels of psychopathological symptoms and lower levels of health-benefitting factors. However, the relationship between attachment to pets and health-benefitting factors could be explained by their overlap with psychopathological symptom levels. Overall, our findings are not in line with the notion that pet ownership generally has a health-benefitting effect. Future studies need to investigate circumstances that modulate positive effects of pet ownership

The relationship between attachment to pets and mental health : the shared link via attachment to humans

Background: Several studies have investigated the relationship between emotional attachment to pets and mental health with the majority of studies fnding a negative relationship between emotional attachment to pets and mental health. Interestingly, attachment to pets difers from attachment to humans with studies showing that humans with an insecure attachment style form a particularly strong emotional attachment to their companion animals. Human attachment style is also related to mental health with secure attachment being associated with superior mental health. Building on those fndings, the current study aimed at exploring the role of attachment to humans in the relationship between emotional attachment to pets and mental health. Methods: In this cross-sectional online survey (N=610) we assessed the strength of emotional attachment to pets and attachment to humans. We further collected pet specifc data as well as mental health burden in a sample of German dog owners (Mage=33.12; 92.79% women). We used a mediation model estimating the indirect link between emotional attachment to pets and mental health burden via human attachment and the direct link between emo‑ tional attachment to pets and mental health burden simultaneously. Results: We found that attachment to humans fully mediated the positive association between emotional attach‑ ment to pets and mental health burden. A stronger emotional attachment to one’s dog was associated with lower comfort with depending on or trusting in others, whereby lower comfort with depending on or trusting in others was related to higher mental health burden. Moreover, a stronger attachment to one’s dog was also related to a greater fear of being rejected and unloved (Anxiety), which was, in turn, associated with a higher mental health burden. Conclusion: Our fndings suggest that the positive link between emotional attachment to pets and mental health burden is fully accounted for by its shared variance with insecure attachment to humans in a sample mostly compris‑ ing self-identifed women. Future studies need to examine whether strong emotional bonds with pets may evolve as a compensatory strategy to bufer difcult childhood bonding experiences

Model Order Reduction for Rotating Electrical Machines

The simulation of electric rotating machines is both computationally expensive and memory intensive. To overcome these costs, model order reduction techniques can be applied. The focus of this contribution is especially on machines that contain non-symmetric components. These are usually introduced during the mass production process and are modeled by small perturbations in the geometry (e.g., eccentricity) or the material parameters. While model order reduction for symmetric machines is clear and does not need special treatment, the non-symmetric setting adds additional challenges. An adaptive strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method