Die benutting van batteryhoendermis in oorwinteringsrantsoene van jong vleisbeeste

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Industry-scale application and evaluation of deep learning for drug target prediction

Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.Web of Science121art. no. 2

Deterministic polarization chaos from a laser diode

Fifty years after the invention of the laser diode and fourty years after the report of the butterfly effect - i.e. the unpredictability of deterministic chaos, it is said that a laser diode behaves like a damped nonlinear oscillator. Hence no chaos can be generated unless with additional forcing or parameter modulation. Here we report the first counter-example of a free-running laser diode generating chaos. The underlying physics is a nonlinear coupling between two elliptically polarized modes in a vertical-cavity surface-emitting laser. We identify chaos in experimental time-series and show theoretically the bifurcations leading to single- and double-scroll attractors with characteristics similar to Lorenz chaos. The reported polarization chaos resembles at first sight a noise-driven mode hopping but shows opposite statistical properties. Our findings open up new research areas that combine the high speed performances of microcavity lasers with controllable and integrated sources of optical chaos.Comment: 13 pages, 5 figure

Assessing Neuropsychological Performance in a Migrant Farm Working Colonia in Baja California, Mexico: A Feasibility Study

Neuropsychological impairments (NPI) can lead to difficulties in daily functioning and ultimately contribute to poor health outcomes. However, evidence for the feasibility of NPI assessment in resource-limited settings using tests developed in high literacy/high education cultures is sparse. The main objectives were to: (1) determine the feasibility and appropriateness of conducting neuropsychological assessments among a migrant farm worker population in Baja California, Mexico and (2) preliminary describe neuropsychological test performance in this unique population. A neuropsychological test battery was administered to 21 presumably healthy adults (8 men, 13 women) during a two-day international health services and research collaboration. All but one neuropsychological test (i.e. figure learning) was feasible and appropriate to administer to the study population. Contrary to expectations, participants performed better on verbal rather than nonverbal neuropsychological tests. Results support inclusion of neuropsychological tests into future studies among migrant farm worker populations in Baja California, Mexico

Inmunohistochemical Profile of Solid Cell Nest of Thyroid Gland

It is widely held that solid cell nests (SCN) of the thyroid are ultimobranchial body remnants. SCNs are composed of main cells and C cells. It has been suggested that main cells might be pluripotent cells contributing to the histogenesis of C cells and follicular cells, as well as to the formation of certain thyroid tumors. The present study sought to analyze the immunohistochemical profile of SCN and to investigate the potential stem cell role of SCN main cells. Tissue sections from ten cases of nodular hyperplasia (non-tumor goiter) with SCNs were retrieved from the files of the Hospital Infanta Luisa (Seville, Spain). Parathormone (PTH), calcitonin (CT), thyroglobulin (TG), thyroid transcription factor (TTF-1), galectin 3 (GAL3), cytokeratin 19 (CK 19), p63, bcl-2, OCT4, and SALL4 expression were evaluated by immunohistochemistry. Patient clinical data were collected, and tissue sections were stained with hematoxylin–eosin for histological examination. Most cells stained negative for PTH, CT, TG, and TTF-1. Some cells staining positive for TTF-1 and CT required discussion. However, bcl-2, p63, GAL3, and CK 19 protein expression was detected in main cells. OCT4 protein expression was detected in only two cases, and SALL4 expression in none. Positive staining for bcl-2 and p63, and negative staining for PTH, CT, and TG in SCN main cells are both consistent with the widely accepted minimalist definition of stem cells, thus supporting the hypothesis that they may play a stem cell role in the thyroid gland, although further research will be required into stem cell markers. Furthermore, p63 and GAL-3 staining provides a much more sensitive means of detecting SCNs than staining for carcinoembryonic antigen, calcitonin, or other markers; this may help to distinguish SCNs from their mimics

Architectures for Cognitive Radio Testbeds and Demonstrators – An Overview

Wireless communication standards are developed at an ever-increasing rate of pace, and significant amounts of effort is put into research for new communication methods and concepts. On the physical layer, such topics include MIMO, cooperative communication, and error control coding, whereas research on the medium access layer includes link control, network topology, and cognitive radio. At the same time, implementations are moving from traditional fixed hardware architectures towards software, allowing more efficient development. Today, field-programmable gate arrays (FPGAs) and regular desktop computers are fast enough to handle complete baseband processing chains, and there are several platforms, both open-source and commercial, providing such solutions. The aims of this paper is to give an overview of five of the available platforms and their characteristics, and compare the features and performance measures of the different systems