HoLLiECares - Development of a multi-functional robot for professional care.

Germany's healthcare sector suffers from a shortage of nursing staff, and robotic solutions are being explored as a means to provide quality care. While many robotic systems have already been established in various medical fields (e.g.

Non-destructive quantification of key quality characteristics in individual grapevine berries using near-infrared spectroscopy.

It is crucial for winegrowers to make informed decisions about the optimum time to harvest the grapes to ensure the production of premium wines. Global warming contributes to decreasing acidity and increasing sugar levels in grapes, resulting in bland wines with high contents of alcohol. Predicting quality in viticulture is thus pivotal.

Impact and visualization of scotomatic glare in central visual field perception.

Strong monochromatic point light sources such as Light Emitting Diodes (LED) or Lasers have been increasingly used in recent decades. This also raises the risk of misuse resulting in glare phenomena and associated visual impairment. The objective of this prospective and partially blinded study was the visualization and characterization of glare-induced scotomas in visual field by dazzling with monochromatic point light sources in terms of disability and discomfort glare.

A Method to Correct the Temporal Drift of Single-Photon Detectors Based on Asynchronous Quantum Ghost Imaging.

Single-photon detection and timing has attracted increasing interest in recent years due to their necessity in the field of quantum sensing and the advantages of single-quanta detection in the field of low-level light imaging. While simple bucket detectors are mature enough for commercial applications, more complex imaging detectors are still a field of research comprising mostly prototype-level detectors. A major problem in these detectors is the implementation of in-pixel timing circuitry, especially for two-dimensional imagers.

Smarter Evolution: Enhancing Evolutionary Black Box Fuzzing with Adaptive Models.

Smart production ecosystems are a valuable target for attackers. In particular, due to the high level of connectivity introduced by Industry 4.0, attackers can potentially attack individual components of production systems from the outside.

Responses of patients with cancer to mRNA vaccines depend on the time interval between vaccination and last treatment.

Background: Personalized mRNA vaccines are promising new therapeutic options for patients with cancer. Because mRNA vaccines are not yet approved for first-line therapy, the vaccines are presently applied to individuals that received prior therapies that can have immunocompromising effects. There is a need to address how prior treatments impact mRNA vaccine outcomes.

Investigations on the Nonlinear Optical Properties of 0D, 1D, and 2D Boron Nitride Nanomaterials in the Visible Spectral Region.

In recent years, boron nitride nanomaterials have attracted increasing attention due to their unique properties such as high temperature stability and high thermal conductivity. They are structurally analogous to carbon nanomaterials and can also be generated as zero-dimensional nanoparticles and fullerenes, one-dimensional nanotubes and nanoribbons, and two-dimensional nanosheets or platelets. In contrast to carbon-based nanomaterials, which have been extensively studied during recent years, the optical limiting properties of boron nitride nanomaterials have hardly been analysed so far.

Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy.

An automatic determination of grape must ingredients during the harvesting process would support cellar logistics and enables an early termination of the harvest if quality parameters are not met. One of the most important quality-determining characteristics of grape must is its sugar and acid content. Among others, the sugars in particular determine the quality of the must and wine.

Open-Source Implementations of the Reactive Asset Administration Shell: A Survey.

The use of open-source software is crucial for the digitalization of manufacturing, including the implementation of Digital Twins as envisioned in Industry 4.0. This research paper provides a comprehensive comparison of free and open-source implementations of the reactive Asset Administration Shell (AAS) for creating Digital Twins.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.

Purpose: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex.

Method: Retrospective analysis of oncological patients without evidence of metastatic disease.

Few-parameter learning for a hierarchical perceptual grouping system.

Perceptual grouping along well-established Gestalt laws provides one set of traditional methods that provide a tiny set of meaningful parameters to be adjusted for each application field. More complex and challenging tasks require a hierarchical setting, where the results aggregated by a first grouping process are later subject to further processing on a larger scale and with more abstract objects. This can be several steps deep.

A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video.

The utilization of stationary underwater cameras is a modern and well-adapted approach to provide a continuous and cost-effective long-term solution to monitor underwater habitats of particular interest. A common goal of such monitoring systems is to gain better insight into the dynamics and condition of populations of various marine organisms, such as migratory or commercially relevant fish taxa. This paper describes a complete processing pipeline to automatically determine the abundance, type and estimate the size of biological taxa from stereoscopic video data captured by the stereo camera of a stationary Underwater Fish Observatory (UFO).

Short-Wave Ultraviolet-Light-Based Disinfection of Surface Environment Using Light-Emitting Diodes: A New Approach to Prevent Health-Care-Associated Infections.

Ultraviolet (UV)-C irradiation is a promising method for microbial eradication on surfaces. Major developments have taken place in UV-C light-emitting diodes (LEDs) technology. In this study, we examined the suitability of UV-C LED-based surface disinfection in hospitals.

Standalone hybrid PV/wind/diesel-electric generator system for a COVID-19 quarantine center.

This work is motivated by the need in overcoming the electricity crisis in Gaza, which is initiated due to political reasons and the spread of COVID-19. Building quarantine centers is one of the most important means used in combating the COVID-19, but connecting these centers to the electricity distribution network at the appropriate time is not always possible and increases the burden on the local utility company. This article proposed a hybrid off-grid energy system (HES) to effectively energize the quarantine COVID-19 center in Gaza economically and environmentally.

Assessment of COVID-19 lung involvement on computed tomography by deep-learning-, threshold-, and human reader-based approaches-an international, multi-center comparative study.

Background: The extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia, quantified on computed tomography (CT), is an established biomarker for prognosis and guides clinical decision-making. The clinical standard is semi-quantitative scoring of lung involvement by an experienced reader. We aim to compare the performance of automated deep-learning- and threshold-based methods to the manual semi-quantitative lung scoring.

Automated Assessment of Breast Positioning Quality in Screening Mammography.

Screening mammography is a widely used approach for early breast cancer detection, effectively increasing the survival rate of affected patients. According to the Food and Drug Administration's Mammography Quality Standards Act and Program statistics, approximately 39 million mammography procedures are performed in the United States each year. Therefore, breast cancer screening is among the most common radiological tasks.

A new promising oncogenic target (p.C382R) for treatment with pemigatinib in patients with cholangiocarcinoma.

Point mutations of the fibroblast growth factor receptor (FGFR)2 receptor in intrahepatic cholangiocarcinoma (iCC) are mainly of unknown functional significance compared to FGFR2 fusions. Pemigatinib, a tyrosine kinase inhibitor, is approved for the treatment of cholangiocarcinoma with FGFR2 fusion/rearrangement. Although it is hypothesized that FGFR2 mutations may cause uncontrolled activation of the signaling pathway, the data for targeted therapies for FGFR2 mutations remain unclear.

Machine-Learning-Inspired Workflow for Camera Calibration.

The performance of modern digital cameras approaches physical limits and enables high-precision measurements in optical metrology and in computer vision. All camera-assisted geometrical measurements are fundamentally limited by the quality of camera calibration. Unfortunately, this procedure is often effectively considered a nuisance: calibration data are collected in a non-systematic way and lack quality specifications; imaging models are selected in an ad hoc fashion without proper justification; and calibration results are evaluated, interpreted, and reported inconsistently.

Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.

Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease.

Handheld Spectral Sensing Devices Should Not Mislead Consumers as Far as Non-Authentic Food Is Concerned: A Case Study with Adulteration of Milk Powder.

With the rising trend of consumers being offered by start-up companies portable devices and applications for checking quality of purchased products, it appears of paramount importance to assess the reliability of miniaturized sensors embedded in such devices. Here, eight sensors were assessed for food fraud applications in skimmed milk powder. The performance was evaluated with dry- and wet-blended powders mimicking adulterated materials by addition of either ammonium sulfate, semicarbazide, or cornstarch in the range 0.

Feasibility of artificial intelligence-supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein - a retrospective observational study.

Objectives: To demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing.

Methods: Individuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively.

Landscape of Biomarkers and Actionable Gene Alterations in Adenocarcinoma of GEJ and Stomach-A Real World Data Analysis.

After several years of negative phase III trials in gastric and esophageal cancer, a significant breakthrough in the treatment of metastatic adenocarcinomas of the gastroesophageal junction (GEJ) and stomach (GC) is now becoming evident with the emerging of precision oncology and implementation of molecular targets in tumor treatment. In addition, new generation studies such as umbrella and basket trials are focused on these molecular targets, which makes an early molecular diagnosis based on IHC/ISH and NGS necessary. The required companion diagnostics of Her2neu overamplification or PD-L1 expression is based on immunohistochemistry (IHC) or additionally in situ hybridization (ISH) in case of an IHC Her2neu score of 2+.

ReStAC-UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices.

With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performance computing, while at the same time preserving a low power consumption, essential for embedded systems. However, the recently increasing availability of embedded GPU-based systems, such as the NVIDIA Jetson series, comprised of an ARM CPU and a NVIDIA Tegra GPU, allows for massively parallel embedded computing on graphics hardware.

Generating Artificial Sensor Data for the Comparison of Unsupervised Machine Learning Methods.

In the field of Cyber-Physical Systems (CPS), there is a large number of machine learning methods, and their intrinsic hyper-parameters are hugely varied. Since no agreed-on datasets for CPS exist, developers of new algorithms are forced to define their own benchmarks. This leads to a large number of algorithms each claiming benefits over other approaches but lacking a fair comparison.