Organic egg production in Finland - animal health, welfare and food safety issues

A total of 20 out of 23 commercial organic layer farms took part in the research. Data were collected through observation and by interviewing the producer, using a semi-structured interview guide. Laying hen welfare was estimated using environment-based and animal-based methods. Fresh faecal samples were collected from the floor for analysis of campylobacter and salmonella bacteria and for internal parasite identification

Deep inelastic scattering in the dipole picture at next-to-leading order

We study quantitatively the importance of the recently derived next-to-leading-order corrections to the deep inelastic scattering structure functions at small x in the dipole formalism. We show that these corrections can be significant and depend on the factorization scheme used to resum large logarithms of energy into renormalization group evolution with the Balitsky-Kovchegov equation. This feature is similar to what has recently been observed for single inclusive forward hadron production. Using a factorization scheme consistent with the one recently proposed for the single inclusive cross section, we show that it is possible to obtain meaningful results for the deep inelastic scattering cross sections.Peer reviewe

Organic egg production in Finland: management of animal welfare and food safety

A total of 20 out of 23 commercial organic layer farms (in excess of 80 % of all commercial Finnish organic farms year 2003) took part in the ongoing research, which identifies risk factors and potential solutions for laying hen welfare and food safety. Data was collected during two farm visits by interviewing the producer, using a semi-structured interview guide, making environment and animal-based observations and collecting samples

Image reconstruction in quantitative photoacoustic tomography using adaptive optical Monte Carlo

In quantitative photoacoustic tomography (QPAT), distributions of optical parameters inside the target are reconstructed from photoacoustic images. In this work, we utilize the Monte Carlo (MC) method for light transport in the image reconstruction of QPAT. Modeling light transport accurately with the MC requires simulating a large number of photon packets, which can be computationally expensive. On the other hand, too low number of photon packets results in a high level of stochastic noise, which can lead to significant errors in reconstructed images. In this work, we use an adaptive approach, where the number of simulated photon packets is adjusted during an iterative image reconstruction. It is based on a norm test where the expected relative error of the minimization direction is controlled. The adaptive approach automatically determines the number of simulated photon packets to provide sufficiently accurate light transport modeling without unnecessary computational burden. The presented approach is studied with two-dimensional simulations

Patient-related reasons for late surgery cancellations in a plastic and reconstructive surgery department

Late cancellations of scheduled operations cause direct and indirect costs for a hospital and economic and emotional stress for the patient. Previously, late cancellation rates for scheduled operations in plastic surgery have been shown to be attributable to patient-related causes in the majority of cases. In this retrospective study, we sought to examine specifically the patient-related reasons for the late cancellations in a plastic surgery operating theatre at Helsinki University Hospital in Finland from 2013 to 2014. We calculated latency between the date of decision for surgery and the scheduled operation day. In cases where the surgery was rescheduled and performed before 31 December 2015, the rescheduled waiting time latency was calculated. We aimed to improve our knowledge of the causes of late cancellations to further optimise the operating theatre efficiency and propose a strategic algorithm to avoid late cancellations During the study period, 327 (5.5%) of all the scheduled operations were recorded as late cancellations. Of these, 45.3% were because of patient-related issues. Acute infection, change in medical condition not noticed before and operation no longer necessary were by far the most common causes of cancellation, comprising 63.5%. Sixty-six per cent of patient-related cancelled operations were performed later, especially when the specific reason was patient's acute illness. Root-cause analysis shows that most of the underlying reasons for the cancellations can be attributed to a failure in communication. The majority of these cancellations were considered to be preventable, thus emphasising the importance of communication and skilful multi-professional planning of the operating theatre list. © 2018 The Author(s)Peer reviewe

Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography

SIGNIFICANCE: The image reconstruction problem in quantitative photoacoustic tomography (QPAT) is an ill-posed inverse problem. Monte Carlo method for light transport can be utilized in solving this image reconstruction problem. AIM: The aim was to develop an adaptive image reconstruction method where the number of photon packets in Monte Carlo simulation is varied to achieve a sufficient accuracy with reduced computational burden. APPROACH: The image reconstruction problem was formulated as a minimization problem. An adaptive stochastic Gauss-Newton (A-SGN) method combined with Monte Carlo method for light transport was developed. In the algorithm, the number of photon packets used on Gauss-Newton (GN) iteration was varied utilizing a so-called norm test. RESULTS: The approach was evaluated with numerical simulations. With the proposed approach, the number of photon packets needed for solving the inverse problem was significantly smaller than in a conventional approach where the number of photon packets was fixed for each GN iteration. CONCLUSIONS: The A-SGN method with a norm test can be utilized in QPAT to provide accurate and computationally efficient solutions

Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order

We use a factorization scheme analogous to one proposed for single inclusive forward hadron production to factorize the soft gluon divergence present in the deep inelastic scattering cross sections in the dipole picture at next-to-leading order (NLO). We show numerically that in this carefully constructed scheme it is possible to obtain meaningful results for the DIS cross sections at NLO, and so we are able to quantitatively study the recently derived NLO corrections to the DIS cross sections. We find that the NLO corrections can be significant and sensitive to the details of the factorization scheme used for the resummation of the large logarithms into the BK evolution equation. In the case of an approximative factorization scheme we observe a problematic behavior of the DIS cross sections similar to what has been seen with analogously factorized single inclusive cross sections.Peer reviewe

Asymptotic motion of a single vortex in a rotating cylinder

We study numerically the behavior of a single quantized vortex in a rotating cylinder. We study in particular the spiraling motion of a vortex in a cylinder that is parallel to the rotation axis. We determine the asymptotic form of the vortex and its axial and azimuthal propagation velocities under a wide range of parameters. We also study the stability of the vortex line and the effect of tilting the cylinder from the rotation axis.Comment: 9 pages, 10 figures. Considerable changes, now close to the published versio