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Background and Objective
Effective leg extension training at a leg press requires high forces, which need to be controlled to avoid training-induced damage. In order to avoid high external knee adduction moments, which are one reason for unphysiological loadings on knee joint structures, both training movements and the whole reaction force vector need to be observed. In this study, the applicability of lateral and medial changes in foot orientation and position as possible manipulated variables to control external knee adduction moments is investigated. As secondary parameters both the medio-lateral position of the center of pressure and the frontal-plane orientation of the reaction force vector are analyzed.
Methods
Knee adduction moments are estimated using a dynamic model of the musculoskeletal system together with the measured reaction force vector and the motion of the subject by solving the inverse kinematic and dynamic problem. Six different foot conditions with varying positions and orientations of the foot in a static leg press are evaluated and compared to a neutral foot position.
Results
Both lateral and medial wedges under the foot and medial and lateral shifts of the foot can influence external knee adduction moments in the presented study with six healthy subjects. Different effects are observed with the varying conditions: the pose of the leg is changed and the direction and center of pressure of the reaction force vector is influenced. Each effect results in a different direction or center of pressure of the reaction force vector.
Conclusions
The results allow the conclusion that foot position and orientation can be used as manipulated variables in a control loop to actively control knee adduction moments in leg extension training.
Phase change materials offer a way of storing excess heat and releasing it when it is needed. They can be utilized as a method to control thermal behavior without the need for additional energy. This work focuses on exploring the potential of using phase change materials to passively control the thermal behavior of a star tracker by infusing it with a fitting phase change material. Based on the numerical model of the star trackers thermal behavior using ESATAN-TMS without implemented phase change material, a fitting phase change material for selected orbits is chosen and implemented in the thermal model. The altered thermal behavior of the numerical model after the implementation is analyzed for different amounts of the chosen phase change materials using an ESATAN-based subroutine developed by the FH Aachen. The PCM-modelling-subroutine is explained in the paper ICES-2021-110. The results show that an increasing amount of phase change material increasingly damps temperature oscillations. Using an integral part structure some of the mass increase can be compensated.
The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows:
Objective: Identify active learning strategies that were proposed for entity recognition and their evaluation environments (datasets, metrics, hardware, execution time).
Design: We used Scopus and ACM as our search engines. We compared the results with two literature surveys to assess the search quality. We included peer-reviewed English publications introducing or comparing active learning strategies for entity recognition.
Results: We analyzed 62 relevant papers and identified 106 active learning strategies. We grouped them into three categories: exploitation-based (60x), exploration-based (14x), and hybrid strategies (32x). We found that all studies used the F1-score as an evaluation metric. Information about hardware (6x) and execution time (13x) was only occasionally included. The 62 papers used 57 different datasets to evaluate their respective strategies. Most datasets contained newspaper articles or biomedical/medical data. Our analysis revealed that 26 out of 57 datasets are publicly accessible.
Conclusion: Numerous active learning strategies have been identified, along with significant open questions that still need to be addressed. Researchers and practitioners face difficulties when making data-driven decisions about which active learning strategy to adopt. Conducting comprehensive empirical comparisons using the evaluation environment proposed in this study could help establish best practices in the domain.
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
Nanotubular tobacco mosaic virus (TMV) particles and RNA-free lower-order coat protein (CP) aggregates have been employed as enzyme carriers in different diagnostic layouts and compared for their influence on biosensor performance. In the following, we describe a label-free electrochemical biosensor for improved glucose detection by use of TMV adapters and the enzyme glucose oxidase (GOD). A specific and efficient immobilization of streptavidin-conjugated GOD ([SA]-GOD) complexes on biotinylated TMV nanotubes or CP aggregates was achieved via bioaffinity binding. Glucose sensors with adsorptively immobilized [SA]-GOD, and with [SA]-GOD cross-linked with glutardialdehyde, respectively, were tested in parallel on the same sensor chip. Comparison of these sensors revealed that TMV adapters enhanced the amperometric glucose detection remarkably, conveying highest sensitivity, an extended linear detection range and fastest response times. These results underline a great potential of an integration of virus/biomolecule hybrids with electronic transducers for applications in biosensorics and biochips. Here, we describe the fabrication and use of amperometric sensor chips combining an array of circular Pt electrodes, their loading with GOD-modified TMV nanotubes (and other GOD immobilization methods), and the subsequent investigations of the sensor performance.
The presentation of enzymes on viral scaffolds has beneficial effects such as an increased enzyme loading and a prolonged reusability in comparison to conventional immobilization platforms. Here, we used modified tobacco mosaic virus (TMV) nanorods as enzyme carriers in penicillin G detection for the first time. Penicillinase enzymes were conjugated with streptavidin and coupled to TMV rods by use of a bifunctional biotin-linker. Penicillinase-decorated TMV particles were characterized extensively in halochromic dye-based biosensing. Acidometric analyte detection was performed with bromcresol purple as pH indicator and spectrophotometry. The TMV-assisted sensors exhibited increased enzyme loading and strongly improved reusability, and higher analysis rates compared to layouts without viral adapters. They extended the half-life of the sensors from 4 - 6 days to 5 weeks and thus allowed an at least 8-fold longer use of the sensors. Using a commercial budget-priced penicillinase preparation, a detection limit of 100 µM penicillin was obtained. Initial experiments also indicate that the system may be transferred to label-free detection layouts.
Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.
31P MR spectroscopic imaging of the human prostate provides information about phosphorylated metabolites that could be used for prostate cancer characterization. The sensitivity of a magnetic field strength of 7 T might enable 3D 31P MR spectroscopic imaging with relevant spatial resolution in a clinically acceptable measurement time. To this end, a 31P endorectal coil was developed and combined with an eight-channel 1H body-array coil to relate metabolic information to anatomical location. An extensive safety validation was performed to evaluate the specific absorption rate, the radiofrequency field distribution, and the temperature distribution of both coils. This validation consisted of detailed Finite Integration Technique simulations, confirmed by MR thermometry and Burn:x-wiley:07403194:media:MRM24175:tex2gif-stack-1 measurements in a phantom and in vivo temperature measurements. The safety studies demonstrated that the presence of the 31P endorectal coil had no influence on the specific absorption rate levels and temperature distribution of the external eight-channel 1H array coil. To stay within a 10 g averaged local specific absorption rate of 10 W/kg, a maximum time-averaged input power of 33 W for the 1H array coil was allowed. For transmitting with the 31P endorectal coil, our safety limit of less than 1°C temperature increase in vivo during a 15-min MR spectroscopic imaging experiment was reached at a time-averaged input power of 1.9 W. With this power setting, a second in vivo measurement was performed on a healthy volunteer. Using adiabatic excitation, 3D 31P MR spectroscopic imaging produced spectra from the entire prostate in 18 min with a spatial resolution of 4 cm3. The spectral resolution enabled the separate detection of phosphocholine, phosphoethanolamine, inorganic phosphate, and other metabolites that could play an important role in the characterization of prostate cancer.
The simultaneous assessment of glottal dynamics and larynx position can be beneficial for the diagnosis of disordered voice or speech production and swallowing. Up to now, methods either concentrate on assessment of the glottis opening using optical, acoustical or electrical (electroglottography, EGG) methods, or on visualisation of the larynx position using ultrasound, computer tomography or magnetic resonance imaging techniques.
The method presented here makes use of a time-multiplex measurement approach of space-resolved transfer impedances through the larynx. The fast sequence of measurements allows a quasi simultaneous assessment of both larynx position and EGG signal using up to 32 transmit–receive signal paths. The system assesses the dynamic opening status of the glottis as well as the vertical and back/forward motion of the larynx.
Two electrode-arrays are used for the measurement of the electrical transfer impedance through the neck in different directions. From the acquired data the global and individual conductivity is calculated as well as a 2D point spatial representation of the minimum impedance.
The position information is shown together with classical EGG signals allowing a synchronous visual assessment of glottal area and larynx position. A first application to singing voice analysis is presented that indicate a high potential of the method for use as a non-invasive tool in the diagnosis of voice, speech, and swallowing disorders.
Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.