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Turbidity sensing is very common in the control of drinking water. Furthermore, turbidity measurements are applied in the chemical (e.g., process monitoring), pharmaceutical (e.g., drug discovery), and food industries (e.g., the filtration of wine and beer). The most common measurement technique is nephelometric turbidimetry. A nephelometer is a device for measuring the amount of scattered light of suspended particles in a liquid by using a light source and a light detector orientated in 90°to each other. Commercially available nephelometers cost usually—depending on the measurable range, reliability, and precision —thousands of euros. In contrast, our new developed GRIN-lens-based nephelometer, called GRINephy, combines low costs with excellent reproducibility and precision, even at very low turbidity levels, which is achieved by its ability to rotate the sample. Thereby, many cuvette positions can be measured, which results in a more precise average value for the turbidity calculated by an algorithm, which also eliminates errors caused by scratches and contaminations on the cuvettes. With our compact and cheap Arduino-based sensor, we are able to measure in the range of 0.1–1000 NTU and confirm the ISO 7027-1:2016 for low turbidity values.
Soft lithography, a tool widely applied in biology and life sciences with numerous applications, uses the soft molding of photolithography-generated master structures by polymers. The central part of a photolithography set-up is a mask-aligner mostly based on a high-pressure mercury lamp as an ultraviolet (UV) light source. This type of light source requires a high level of maintenance and shows a decreasing intensity over its lifetime, influencing the lithography outcome. In this paper, we present a low-cost, bench-top photolithography tool based on ninety-eight 375 nm light-emitting diodes (LEDs). With approx. 10 W, our presented lithography set-up requires only a fraction of the energy of a conventional lamp, the LEDs have a guaranteed lifetime of 1000 h, which becomes noticeable by at least 2.5 to 15 times more exposure cycles compared to a standard light source and with costs less than 850 C it is very affordable. Such a set-up is not only attractive to small academic and industrial fabrication facilities who want to enable work with the technology of photolithography and cannot afford a conventional set-up, but also microfluidic teaching laboratories and microfluidic research and development laboratories, in general, could benefit from this cost-effective alternative. With our self-built photolithography system, we were able to produce structures from 6 μm to 50 μm in height and 10 μm to 200 μm in width. As an optional feature, we present a scaled-down laminar flow hood to enable a dust-free working environment for the photolithography process.
Die meisten der aktuell im Allag vorfindlichen Touch-Flächen wurden unter Anwendung komplexer und kostenintensiver Technologien realisiert. Gerade für das Anwendungsszenario eines Touchfloors, bei welchem meist eine überdurchschnittlich große Touch-Fläche erwünscht ist, werden kostengünstigere Umsetzungsmöglichkeiten angestrebt. Dieses Paper dient als Ausgangsbasis für die Umsetzung eines Low-cost Touchfloors, der die kollaborative Arbeit eines Projektteams unterstützen soll. Mithilfe einer Analyse des State of the Arts der Touch-Technologien und einer anschließenden Evaluation, wird die Touch-Technologie abgeleitet, die sich am besten zur Realisierung dieses low-cost Touchfloors eignet. Aus der Evaluation geht hervor, dass vor allem optische Touch-Technologien, insbesondere visionsbasierte, für die Umsetzung von kostengünstigen großen Touch-Flächen geeignet sind.
Die Nachfrage nach kompakten Spannungsversorgungen ist in den letzten Jahren stark gestiegen. Vor allem im Bereich der mobilen Geräte wachsen die Anforderung an die Spannungsversorgung hinsichtlich Bauvolumen und Batterielaufzeit. Für die Vollintegration von DC-DC- Wandlern als „Power Supply on Chip“ ist der SC-Wandler (Switched-Capacitor-Wandler) besonders geeignet. Insbesondere für Low-Power-Anwendungen im Bereich 10 mW kann ein SC-Wandler sehr gut, ohne externe Bauelemente, integriert werden. Während es für niedrige Eingangsspannungen (bis zu 5 V) eine Vielzahl an Topologien und Konzepten gibt, wurden SC-Wandler für höhere Eingangsspannungen (> 8 V) bisher nur wenig untersucht. Dieser Beitrag untersucht die wichtigsten Grundlagen für SC-Wandler mit Schwerpunkt auf hoher und zugleich variabler Eingangsspannung im Bereich 5 - 20 V. Am Beispiel eines Multi-Ratio-Wandlers (Wandler mit mehreren Übersetzungsverhältnissen), dem rekursiven SC-Wandler (RSC- Wandler), werden die Anforderungen eines SC- Wandler für hohe Eingangsspannungen herausgearbeitet und diskutiert.
Human adipose-derived stem cells (hASCs) have become an important cell source for the use in tissue engineering and other medical applications. Not every biomaterial is suitable for human cell culture and requires surface modifications to enable cell adhesion and proliferation. Our hypothesis is that chemical surface modifications introduced by low-discharge plasma enhance the adhesion and proliferation of hASCs. Polystyrene (PS) surfaces were modified either by ammonia (NH3), carbon dioxide (CO2) or acrylic acid (AAc) plasma. The results show that the initial cell adhesion is significantly higher on all modified surfaces than on unmodified material as evaluated by bright field microscopy, live/dead staining, total DNA amount and scanning electron microscopy. The formation of focal adhesions was well pronounced on the Tissue Culture PS, NH3-, and CO2 plasma modified samples. The number of matured fibrillar adhesions was significantly higher on NH3 plasmamodified surfaces than on all other surfaces. Our study validates the suitability of chemical plasma activation and represents a method to enhance hASCs adhesion and improved cell expansion. All chemical modification promoted hASCs adhesion and can therefore be used for the modification of different scaffold materials whereby NH3-plasma modified surfaces resulted in the best outcome concerning hASCs adhesion and proliferation.
Purpose: The purpose of this paper is to analyse the main elements of successful customer loyalty programs in general and emotional components of the buying process in order to determine loyalty programs for fashion retailers.
Findings: The results of this study indicate that loyalty programs in fashion retail require considerable non-monetary benefits such as sense of exclusive membership and enhanced status to distinguish from competitors customer loyalty programs.
Machine failures’ consequences – a classification model considering ultra-efficiency criteria
(2023)
To strive for a sustainable production, maintenance has to evaluate possible machine failure consequences not just economically but also holistically. Approaches such as the ultra-efficiency factory consider energy, material, human/staff, emission, and organization as optimization dimensions. These ultra-efficiency dimensions can be considered for analyzing not only the respective machine failure but also the effects on the entire production system holistically. This paper presents an easy to use method, based on a questionnaire, for assessing the failure consequences of a machine malfunction in a production system considering the ultra-efficiency dimensions. The method was validated in a battery production.
The evaluation of the effectiveness of different machine learning algorithms on a publicly available database of signals derived from wearable devices is presented with the goal of optimizing human activity recognition and classification. Among the wide number of body signals we choose a couple of signals, namely photoplethysmographic (optically detected subcutaneous blood volume) and tri-axis acceleration signals that are easy to be simultaneously acquired using commercial widespread devices (e.g. smartwatches) as well as custom wearable wireless devices designed for sport, healthcare, or clinical purposes. To this end, two widely used algorithms (decision tree and k-nearest neighbor) were tested, and their performance were compared to two new recent algorithms (particle Bernstein and a Monte Carlo-based regression) both in terms of accuracy and processing time. A data preprocessing phase was also considered to improve the performance of the machine learning procedures, in order to reduce the problem size and a detailed analysis of the compression strategy and results is also presented.
This paper presents a machine learning powered, procedural sizing methodology based on pre-computed look-up tables containing operating point characteristics of primitive devices. Several Neural Networks are trained for 90nm and 45nm technologies, mapping different electrical parameters to the corresponding dimensions of a primitive device. This transforms the geometric sizing problem into the domain of circuit design experts, where the desired electrical characteristics are now inputs to the model. Analog building blocks or entire circuits are expressed as a sequence of model evaluations, capturing the sizing strategy and intention of the designer in a procedure, which is reusable across different technology nodes. The methodology is employed for the sizing of two operational amplifiers, and evaluated for two technology nodes, showing the versatility and efficiency of this approach.