Messung der rektalen Körperinnentemperatur bei Milchkühen zur Detektion von Erkrankungen im Frühpuerperium

Ziel der Studie war es anhand klinischer Untersuchungen und der Messung der rektalen Körperinnentemperatur folgende Fragen zu beantworten: - Eignet sich die Körpertemperaturmessung zur Früherkennung von puerperalen Erkrankungen? - Welche Körperinnentemperatur ist dazu geeignet, Tiere mit puerperalen Erkrankungen frühzeitig zu detektieren? - Besteht ein Zusammenhang zwischen Körpertemperatur und Milchleistung? Dazu wurden Daten von 513 Milchkühen über die ersten 13 Tage post partum erhoben. Folgende relevanten Ergebnisse wurden erzielt: - Die beiden kalibrierten digitalen Thermometer VT 1831 und SC 12 eignen sich zur Messung der rektalen Körperinnentemperatur, wenn sie möglichst tief in das Rektum eingeführt werden. - Die rektale Körperinnentemperatur ist in der zweiten Tageshälfte höher als am Vormittag (p < 0,05). - Der Kotabsatz hat keinen signifikanten Einfluss auf die rektal gemessene Körperinnentemperatur (p > 0,05). - Der arithmetische Mittelwert der rektalen Körperinnentemperatur bei gesunden Milchkühen im Frühpuerperium liegt bei 39,1 °C. - Am häufigsten wurde eine Metritis puerperalis (18,1 %) diagnostiziert. Weiterhin wurden Fälle von klinischer Mastitis (17 %), Retentio secundinarum (13,5 %), Krankheitsursache unbekannt (7,8 %), Erkrankungen des Bewegungsapparates (3,9 %), Gebärparese (3,9 %), Labmagenverlagerung (3,5 %), Ketose (2,7 %), Pneumonie (2,1 %) sowie Scheidenverletzungen (1,8 %) festgestellt. - Das Maximum der Erkrankungsfälle lag am 1. Tag post partum. - Kühe, die eine Metritis puerperalis entwickelten, zeigten ein bis drei Tage vor der klinischen Manifestation zu 87,8 % eine rektale Körperinnentemperatur höher 39,3 °C und zu 63,5 % höher 39,7 °C. - Von den Milchkühen mit einer klinischen Mastitis wiesen 62,7 % einen bis drei Tage vor der klinischen Manifestation eine rektale Körperinnentemperatur höher 39,3 °C und 63,5 % höher 39,7 °C auf. - Die Auswertung aller Erkrankungen ergab, dass in 61,4 % der Fälle ein bis drei Tage vor der klinischen Manifestation eine rektale Körperinnentemperatur höher 39,3 °C und in 39,8 % höher 39,7 °C feststellbar war. - Die Milchleistung bei gesunden Kühen stieg fast konstant vom 2. (26,2 ± 8,1 l) bis zum 10. Tag post partum (35,6 ± 8,8 l). - Bei einer rektalen Körperinnentemperatur höher 39,7 °C sollte wegen der geringen Sensitivität von 0,4 keine grundsätzliche Behandlung sondern eine klinische Untersuchung durchgeführt werden. - Die Thermometrierung sollte vom 1. bis zum 10. Tag post partum durchgeführt werden, da bei einem kürzerem Untersuchungszeitraum zu viele kranke Tiere nicht entdeckt werden. - Eine Korrelation zwischen rektaler Körperinnentemperatur und Milchleistung konnte weder bei gesunden Milchkühen (r = -0,1) noch bei Tieren mit Metritis puerperalis (r = -0,1) nachgewiesen werden.The objective of the study was to answer the following questions based on clinical examinations and on the rectal measurement of the internal body temperature: - Is the body temperature measurement appropriate for the early diagnosis of puerperal diseases? - Which internal body temperature is suitable for an early detection of animals with puerperal diseases? - Exists a connection between body temperature and milk production? For this purpose, data from 513 dairy cows were taken over the first 13 days post partum. The following relevant results were obtained: - Both calibrated digital thermometers, VT 1831 and SC 12, were appropriate for the measurement of the rectal internal body temperature if they are inserted as deep as possible into the rectum. - During the second half of the day the internal rectal body temperature is higher than that in the morning session (p < 0.05). - The defecation has no significant influence on the measured internal rectal body temperature (p > 0.05). - The average value of the internal rectal body temperature for healthy dairy cows in early puerperium is 39.1 °C. - Puerperal metritis (18.1%) was diagnosed in most cases. Furthermore, cases of clinical mastitis (17.0%), retentio secundinarum (13.5%), dysfunctional metabolism (7.8 %), diseases of the locomotory system (3.9%), puerperal paresis (3.9%), displaced abomasum (3.5%), ketosis (2.7%), pneumonia (2.1%) as well as vaginal traumata (1.8%) were detected. - The maximum disease cases were on the 1st day post partum. - 87.8% of cows that developed puerperal metritis had an internal body temperature that was higher than 39.3 °C during the three days before clinical manifestation, while 63.5% had a temperatures higher tan 39.7 °C. - 62.7% of the dairy cows with clinical mastitis exhibited one to three days before clinical manifestation, a rectal internal body temperature higher than 39.3 °C and 63.5% had temperatures higher than 39.7 °C. - The analysis of all the diseases showed that in 61.4% of the cases one to three days before clinical manifestation a rectal internal body temperature higher than 39.3 °C was diagnosable and temperatures higher than 39.7 °C were diagnosable in 39.8% of the cases. - In the case of healthy cows milk production increased almost constantly from the second (26.2 ± 8.1 l) to the tenth day post partum (35.6 ± 8.8 l). - In the case of a rectal internal body temperature higher than 39.7 °C, founded to sensitivity of 0.4, no fundamental treatment but a clinical examination shall be carried out. - Temperature recordings must be carried out from the first to the tenth day post partum, because a shorter examination period will cause a decrease of discovered ill animals. - A correlation between internal rectal body temperature and milk production could not be proven either in the case of healthy dairy cows (r = -0.1) or in the cases of animals with puerperal metritis (r = -0.1)

FRASHER – A framework for automated evaluation of similarity hashing

A challenge for digital forensic investigations is dealing with large amounts of data that need to be processed. Approximate matching (AM), a.k.a. similarity hashing or fuzzy hashing, plays a pivotal role in solving this challenge. Many algorithms have been proposed over the years such as ssdeep, sdhash, MRSH-v2, or TLSH, which can be used for similarity assessment, clustering of different artifacts, or finding fragments and embedded objects. To assess the differences between these implementations (e.g., in terms of runtime efficiency, fragment detection, or resistance against obfuscation attacks), a testing framework is indispensable and the core of this article. The proposed framework is called FRASHER (referring to a predecessor FRASH from 2013) and provides an up-to-date view on the problem of evaluating AM algorithms with respect to both the conceptual and the practical aspects. Consequently, we present and discuss relevant test case scenarios as well as release and demonstrate our framework allowing a comprehensive evaluation of AM algorithms. Compared to its predecessor, we adapt it to a modern environment providing better modularity and usability as well as more thorough testing cases

A simulation framework for the design and evaluation of computational cameras

In the emerging field of computational imaging, rapid prototyping of new camera concepts becomes increasingly difficult since the signal processing is intertwined with the physical design of a camera. As novel computational cameras capture information other than the traditional two-dimensional information, ground truth data, which can be used to thoroughly benchmark a new system design, is also hard to acquire. We propose to bridge this gap by using simulation. In this article, we present a raytracing framework tailored for the design and evaluation of computational imaging systems. We show that, depending on the application, the image formation on a sensor and phenomena like image noise have to be simulated accurately in order to achieve meaningful results while other aspects, such as photorealistic scene modeling, can be omitted. Therefore, we focus on accurately simulating the mandatory components of computational cameras, namely apertures, lenses, spectral filters and sensors. Besides the simulation of the imaging process, the framework is capable of generating various ground truth data, which can be used to evaluate and optimize the performance of a particular imaging system. Due to its modularity, it is easy to further extend the framework to the needs of other fields of application. We make the source code of our simulation framework publicly available and encourage other researchers to use it to design and evaluate their own camera designs

A simulation framework for the design and evaluation of computational cameras

In the emerging field of computational imaging, rapid prototyping of new camera concepts becomes increasingly difficult since the signal processing is intertwined with the physical design of a camera. As novel computational cameras capture information other than the traditional two-dimensional information, ground truth data, which can be used to thoroughly benchmark a new system design, is also hard to acquire. We propose to bridge this gap by using simulation. In this article, we present a raytracing framework tailored for the design and evaluation of computational imaging systems. We show that, depending on the application, the image formation on a sensor and phenomena like image noise have to be simulated accurately in order to achieve meaningful results while other aspects, such as photorealistic scene modeling, can be omitted. Therefore, we focus on accurately simulating the mandatory components of computational cameras, namely apertures, lenses, spectral filters and sensors. Besides the simulation of the imaging process, the framework is capable of generating various ground truth data, which can be used to evaluate and optimize the performance of a particular imaging system. Due to its modularity, it is easy to further extend the framework to the needs of other fields of application. We make the source code of our simulation framework publicly available and encourage other researchers to use it to design and evaluate their own camera designs

Thermoresponsive Microgel Coatings as Versatile Functional Compounds for Novel Cell Manipulation Tools

Uhlig K, Wegener T, Hertle Y, et al. Thermoresponsive Microgel Coatings as Versatile Functional Compounds for Novel Cell Manipulation Tools. POLYMERS. 2018;10(6): 656.For the effective use of live cells in biomedicine as in vitro test systems or in biotechnology, non-invasive cell processing and characterisation are key elements. Thermoresponsive polymer coatings have been demonstrated to be highly beneficial for controlling the interaction of adherent cells through their cultivation support. However, the widespread application of these coatings is hampered by limitations in their adaptability to different cell types and because the full range of applications has not yet been fully explored. In the work presented here, we address these issues by focusing on three different aspects. With regard to the first aspect, by using well-defined laminar flow in a microchannel, a highly controllable and reproducible shear force can be applied to adherent cells. Employing this tool, we demonstrate that cells can be non-invasively detached from a support using a defined shear flow. The second aspect relates to the recent development of simple methods for patterning thermoresponsive coatings. Here, we show how such patterned coatings can be used for improving the handling and reliability of a wound-healing assay. Two pattern geometries are tested using mouse fibroblasts and CHO cells. In terms of the third aspect, the adhesiveness of cells depends on the cell type. Standard thermoresponsive coatings are not functional for all types of cells. By coadsorbing charged nanoparticles and thermoresponsive microgels, it is demonstrated that the adhesion and detachment behaviour of cells on such coatings can be modulated

Combining AI and AM - Improving Approximate Matching through Transformer Networks

Approximate matching (AM) is a concept in digital forensics to determine the similarity between digital artifacts. An important use case of AM is the reliable and efficient detection of case-relevant data structures on a blacklist, if only fragments of the original are available. For instance, if only a cluster of indexed malware is still present during the digital forensic investigation, the AM algorithm shall be able to assign the fragment to the blacklisted malware. However, traditional AM functions like TLSH and ssdeep fail to detect files based on their fragments if the presented piece is relatively small compared to the overall file size. A second well-known issue with traditional AM algorithms is the lack of scaling due to the ever-increasing lookup databases. We propose an improved matching algorithm based on transformer models from the field of natural language processing. We call our approach Deep Learning Approximate Matching (DLAM). As a concept from artificial intelligence (AI), DLAM gets knowledge of characteristic blacklisted patterns during its training phase. Then DLAM is able to detect the patterns in a typically much larger file, that is DLAM focuses on the use case of fragment detection. We reveal that DLAM has three key advantages compared to the prominent conventional approaches TLSH and ssdeep. First, it makes the tedious extraction of known to be bad parts obsolete, which is necessary until now before any search for them with AM algorithms. This allows efficient classification of files on a much larger scale, which is important due to exponentially increasing data to be investigated. Second, depending on the use case, DLAM achieves a similar or even significantly higher accuracy in recovering fragments of blacklisted files. Third, we show that DLAM enables the detection of file correlations in the output of TLSH and ssdeep even for small fragment sizes.Comment: Published at DFRWS USA 2023 as a conference pape

ISS emergency scenarios and a virtual training simulator for Flight Controllers

The current emergency response concept for the International Space Station (ISS) includes the support of the Flight Control Team. Therefore, the team members need to be trained in emergencies and the corresponding crew procedures to ensure a smooth collaboration between crew and ground. In the case where the astronaut and ground personnel training is not collocated it is a challenging endeavor to ensure and maintain proper knowledge and skills for the Flight Control Team. Therefore, a virtual 3D simulator at the Columbus Control Center (Col-CC) is presented, which is used for ground personnel training in the on-board emergency response. The paper briefly introduces the main ISS emergency scenarios and the corresponding response strategy, details the resulting learning objectives for the Flight Controllers and elaborates on the new simulation method, which will be used in the future. The status of the 3D simulator, first experiences and further plans are discussed

LUNA Analog Facility: Moon Simulations in Cologne

With LUNA, a globally unique facility is being created in Cologne that will make a replica of the lunar surface combined with various technical possibilities and extensions accessible to a large circle of users. The project, jointly conducted by the European Space Agency (ESA) and the German Aerospace Center (DLR), benefits from the expertise of both organizations in the field of human and robotic spaceflight missions. The present paper describes the elements of LUNA, the project status, and operational structures