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Intensive poultry operation systems emit a considerable volume of inorganic and organic matter in the surrounding environment. Monitoring cleaning properties of exhaust air cleaning systems and to detect small but significant changes in emission characteristics during a fattening cycle is important for both emission and fattening process control. In the present study, we evaluated the potential of near-infrared spectroscopy (NIRS) combined with chemometric techniques as a monitoring tool of exhaust air from poultry operation systems. To generate a high-quality data set for evaluation, the exhaust air of two poultry houses was sampled by applying state-of-the-art filter sampling protocols. The two stables were identical except for one crucial difference, the presence or absence of an exhaust air cleaning system. In total, twenty-one exhaust air samples were collected at the two sites to monitor spectral differences caused by the cleaning device, and to follow changes in exhaust air characteristics during a fattening period. The total dust load was analyzed by gravimetric determination and included as a response variable in multivariate data analysis. The filter samples were directly measured with NIR spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA), and factor analysis (FA) were effective in classifying the NIR exhaust air spectra according to fattening day and origin. The results indicate that the dust load and the composition of exhaust air (inorganic or organic matter) substantially influence the NIR spectral patterns. In conclusion, NIR spectroscopy as a tool is a promising and very rapid way to detect differences between exhaust air samples based on still not clearly defined circumstances triggered during a fattening period and the availability of an exhaust air cleaning system.
Multi-analyte biosensors may offer the opportunity to perform cost-effective and rapid analysis with reduced sample volume, as compared to electrochemical biosensing of each analyte individually. This work describes the development of an enzyme-based biosensor system for multi-parametric determination of four different organic acids. The biosensor array comprises five working electrodes for simultaneous sensing of ethanol, formate, d-lactate, and l-lactate, and an integrated counter electrode. Storage stability of the biosensor was evaluated under different conditions (stored at +4 °C in buffer solution and dry at −21 °C, +4 °C, and room temperature) over a period of 140 days. After repeated and regular application, the individual sensing electrodes exhibited the best stability when stored at −21 °C. Furthermore, measurements in silage samples (maize and sugarcane silage) were conducted with the portable biosensor system. Comparison with a conventional photometric technique demonstrated successful employment for rapid monitoring of complex media.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric device, which detects concentration changes of an analyte solution on the sensor surface in a spatially resolved way. It uses a light source to generate electron–hole pairs inside the semiconductor, which are separated in the depletion region due to an applied bias voltage across the sensor structure and hence, a surface-potential-dependent photocurrent can be read out. However, depending on the beam angle of the light source, scattering effects can occur, which influence the recorded signal in LAPS-based differential measurements. To solve this problem, a novel illumination unit based on a field programmable gate array (FPGA) consisting of 16 small-sized tunable infrared laser-diode modules (LDMs) is developed. Due to the improved focus of the LDMs with a beam angle of only 2 mrad, undesirable scattering effects are minimized. Escherichia coli (E. coli) K12 bacteria are used as a test microorganism to study the extracellular acidification on the sensor surface. Furthermore, a salt bridge chamber is built up and integrated with the LAPS system enabling multi-chamber differential measurements with a single Ag/AgCl reference electrode.
This paper presents NLP Lean Programming
framework (NLPf), a new framework
for creating custom natural language processing
(NLP) models and pipelines by utilizing
common software development build systems.
This approach allows developers to train and
integrate domain-specific NLP pipelines into
their applications seamlessly. Additionally,
NLPf provides an annotation tool which improves
the annotation process significantly by
providing a well-designed GUI and sophisticated
way of using input devices. Due to
NLPf’s properties developers and domain experts
are able to build domain-specific NLP
applications more efficiently. NLPf is Opensource
software and available at https://
gitlab.com/schrieveslaach/NLPf.
In this study, flexible calorimetric gas sensors are developed for specificdetection of gaseous hydrogen peroxide (H₂O₂) over a wide concentrationrange, which is used in sterilization processes for aseptic packaging industry.The flexibility of these sensors is an advantage for identifying the chemical components of the sterilant on the corners of the food boxes, so-called “coldspots”, as critical locations in aseptic packaging, which are of great importance. These sensors are fabricated on flexible polyimide films by means of thin-film technique. Thin layers of titanium and platinum have been deposited on polyimide to define the conductive structures of the sensors. To detect the high-temperature evaporated H₂O₂, a differential temperature set-up is proposed. The sensors are evaluated in a laboratory-scaled sterilizationsystem to simulate the sterilization process. The concentration range of the evaporated H₂O₂ from 0 to 7.7% v/v was defined and the sensors have successfully detected high as well as low H₂O₂ concentrations with a sensitivity of 5.04 °C/% v/v. The characterizations of the sensors confirm their precise fabrication, high sensitivity and the novelty of low H₂O₂ concentration detections for future inline monitoring of food-package sterilization.
The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.
The pharmacokinetics and metabolism of diclofenac in chimeric humanized and murinized FRG mice
(2018)
The pharmacokinetics of diclofenac were investigated following single oral doses of 10 mg/kg to chimeric liver humanized and murinized FRG and C57BL/6 mice. In addition, the metabolism and excretion were investigated in chimeric liver humanized and murinized FRG mice. Diclofenac reached maximum blood concentrations of 2.43 ± 0.9 µg/mL (n = 3) at 0.25 h post-dose with an AUCinf of 3.67 µg h/mL and an effective half-life of 0.86 h (n = 2). In the murinized animals, maximum blood concentrations were determined as 3.86 ± 2.31 µg/mL at 0.25 h post-dose with an AUCinf of 4.94 ± 2.93 µg h/mL and a half-life of 0.52 ± 0.03 h (n = 3). In C57BL/6J mice, mean peak blood concentrations of 2.31 ± 0.53 µg/mL were seen 0.25 h post-dose with a mean AUCinf of 2.10 ± 0.49 µg h/mL and a half-life of 0.51 ± 0.49 h (n = 3). Analysis of blood indicated only trace quantities of drug-related material in chimeric humanized and murinized FRG mice. Metabolic profiling of urine, bile and faecal extracts revealed a complex pattern of metabolites for both humanized and murinized animals with, in addition to unchanged parent drug, a variety of hydroxylated and conjugated metabolites detected. The profiles in humanized mice were different to those of both murinized and wild-type animals, e.g., a higher proportion of the dose was detected in the form of acyl glucuronide metabolites and much reduced amounts as taurine conjugates. Comparison of the metabolic profiles obtained from the present study with previously published data from C57BL/6J mice and humans revealed a greater, though not complete, match between chimeric humanized mice and humans, such that the liver humanized FRG model may represent a model for assessing the biotransformation of such compounds in humans.