Reproductive and Related Disorders on Dairy Farms with Different Levels of Welfare Quality

In this paper reproductive results of six dairy cows farms with total of 766 (farm 1 – 107; farm 2 –175; farm 3 – 49; farm 4 – 400; farm 5 –20 and farm 6 – 11 milking cows) with different system of rearing and welfare level were analyzed. A dairy cow reproductive efficiency is a key factor for milk production - impaired reproductive performance is a major cause of reduced production in dairy industry. Welfare and reproductive disorders data were collected by questionnaire regarding criteria of Animal Need Index (ANI – Bartussek et al., 2000) and compared by multidimensional criteria of total discriminating effect. Possibility of movement, lighting and air quality in the accommodation facility, type and quality of floor, possibility of social contacts with other cows and interaction of stockman with cattle were compared and analysed in respect of farm welfare. In respect to the welfare level of lowest ranked farm (farm 6), farms 1, 2, 3, 4, 5 and 6 were ranked as 4th, 2nd, 1st, 5th, 3rd, and 6th, respectively, but in respect to the reproductive and related disorders occurrence rate lowest ranked farm (farm 4), farms 1, 2, 3, 4, 5 and 6 were ranked as 1st, 4th, 2nd, 6th, 5th and 3rd. Discrepancy derives from the fact that reproduction data were collected for a year, while welfare assessment describes reached level in on particular moment of time, not covering all potential causes of reproductive disorders. Reduced reproductive success would seem promising as information about poor farm welfare, although good results often are not related to good welfare. Nevertheless, assessed welfare protection level provides important information about herd health and potential reproduction problems, pointing out that there are many opportunities for improving the quality of the welfare of dairy cows, mostly through improving the housing conditions of dairy cows

CURVATURE TENSORS AND PSEUDOTENSORS IN A GENERALIZED FINSLER SPACE

We examine relations between the curvature tensor of associated symmetric connection and curvature tensors, curvature pseudotensors and derived curvature tensors of non-symmetric affine connection in Rund's sense

Machine Learning for Detecting Virus Infection Hotspots Via Wastewater-Based Epidemiology: The Case of SARS-CoV-2 RNA

This is the final version. Available on open access from the American Geophysical Union via the DOI in this recordData Availability Statement: The COVID-19 contagious persons per day data used for generating the COVID-19 hotspot prevalence in the study are available from the Dutch National Institute for Public Health and the Environment (RIVM) at https://data.rivm.nl/covid-19/COVID-19_prevalentie.json with license http://creativecommons.org/publicdomain/mark/1.0/deed.nl.Wastewater-based epidemiology (WBE) has been proven to be a useful tool in monitoring public health-related issues such as drug use, and disease. By sampling wastewater and applying WBE methods, wastewater-detectable pathogens such as viruses can be cheaply and effectively monitored, tracking people who might be missed or under-represented in traditional disease surveillance. There is a gap in current knowledge in combining hydraulic modeling with WBE. Recent literature has also identified a gap in combining machine learning with WBE for the detection of viral outbreaks. In this study, we loosely coupled a physically-based hydraulic model of pathogen introduction and transport with a machine learning model to track and trace the source of a pathogen within a sewer network and to evaluate its usefulness under various conditions. The methodology developed was applied to a hypothetical sewer network for the rapid detection of disease hotspots of the disease caused by the SARS-CoV-2 virus. Results showed that the machine learning model's ability to recognize hotspots is promising, but requires a high time-resolution of monitoring data and is highly sensitive to the sewer system's physical layout and properties such as flow velocity, the pathogen sampling procedure, and the model's boundary conditions. The methodology proposed and developed in this paper opens new possibilities for WBE, suggesting a rapid back-tracing of human-excreted biomarkers based on only sampling at the outlet or other key points, but would require high-frequency, contaminant-specific sensor systems that are not available currently

Long-wavelength photonic circuits

Silicon and germanium are transparent in a broad range of the long-wave IR and therefore can be used as photonics platforms in this wavelength region. Furthermore, the free carrier plasma dispersion effect should be stronger, two photon absorption is reduced, and more robust optical bers are now available at longer wavelengths. In addition, the dimensional tolerances are more relaxed than in the near-IR. Moreover, III-V sources and detectors could be bonded on the silicon wafer, similar to approaches already demonstrated in the near-IR. Finally, silicon photonics, or group IV photonics, long wavelength platform is potentially low-cost and offers a possibility of photonicelectronic integration

Low loss silicon waveguides for the mid-infrared

Silicon-on-insulator (SOI) has been used as a platform for near-infrared photonic devices for more than twenty years. Longer wavelengths, however, may be problematic for SOI due to higher absorption loss in silicon dioxide. In this paper we report propagation loss measurements for the longest wavelength used so far on SOI platform. We show that propagation losses of 0.6-0.7 dB/cm can be achieved at a wavelength of 3.39 µm. We also report propagation loss measurements for silicon on porous silicon (SiPSi) waveguides at the same wavelength

Towards the Ultra-Sensitive Optical Link Enabled by Low Noise Phase-Sensitive Amplifiers

Optical phase-sensitive amplifiers (PSAs) are known to be capable, in principle, of realizing noiseless amplification and improving the signal-to-noise-ratio of optical links by 3 dB compared to conventional, phase-insensitively amplified links. However, current state-of-the-art PSAs are still far from being practical, lacking e.g. significant noise performance improvement, broadband gain and modulation-format transparency. Here we demonstrate experimentally, for the first time, an optical-fiber-based non-degenerate PSA link consisting of a phase-insensitive parametric copier followed by a PSA that provides broadband amplification, signal modulation-format independence, and nearly 6-dB link noise-figure (NF) improvement over conventional, erbium-doped fiber amplifier based links. The PSA has a record-low 1.1-dB NF, and can be extended to work with multiple wavelength channels with modest system complexity. This concept can also be realized in other materials with third-order nonlinearities, and is useful in any attenuation-limited optical link