Search Results (832)

The physical capabilities of a reconfigurable assembly system (RAS) increase the agility and responsiveness of the system in highly volatile market conditions. However, achieving optimal RAS utilization entails solving complex optimization problems effectively and efficiently. These optimizations often define homogenous sets of problem instances. While algorithm configuration in such homogeneous contexts traditionally adopts a “one-size-fits-all” approach, recent studies have shown the potential of per-instance algorithm configuration (PIAC) methods in these settings. In this work, we evaluate and compare the performance of different PIAC methods in this context, namely Hydra—a state-of-the-art PIAC method—and a simpler case-based reasoning (CBR) approach. We evaluate the impact of the tuning time budget and/or the number of unique problem instances used for training on each of the method’s performance and robustness. Our experiments show that whilst Hydra fails to improve upon the default algorithm configuration, the CBR method can lead to 16% performance increase using as few as 100 training instances. Following these findings, we evaluate Hydra’s methodology when applied to homogenous instance spaces. This analysis shows the limitations of Hydra’s inference mechanisms in these settings and showcases the advantages of distance-based approaches used in CBR. Full article

Hardy geranium is a popular ornamental plant with a high market demand. As a result, there is a strong need for continuous innovation to improve its ornamental qualities. Interspecific hybridization is a widely used technique for introducing desirable traits and creating new cultivars with added value. To explore the possibilities of creating novelty within the Geranium genus, we conducted 2438 interspecific crosses over three flowering seasons, resulting in the successful harvest of 445 seeds and the final production of 82 seedlings. Using embryo rescue increased the germination rate of a seedling from 0.17% to 1.01%. To validate the paternal genetic contribution in the new seedlings, we used amplified fragment length polymorphism (AFLP) to assess the proportion of uniquely inherited paternal markers in all seedlings. AFLP analysis confirmed that 54 of the 82 seedlings were indeed true hybrids (65.8% hybridization success rate). A morphological evaluation of the flowers and leaves, including flower diameter (mm), style length (mm), number of flowers, flowering period (weeks), and color of both flowers and leaves, provided further confirmation of the F1 hybrid status of the seedlings. The results of our interspecific breeding demonstrated the efficiency of interspecific hybridization in hardy geraniums and its potential to create distinctive and novel cultivars for the ornamental market. Full article

Putting sensors on the bodies of animals to automate animal activity recognition and gain insight into their behaviors can help improve their living conditions. Although previous hard-coded algorithms failed to classify complex time series obtained from accelerometer data, recent advances in deep learning have improved the task of animal activity recognition for the better. However, a comparative analysis of the generalizing capabilities of various models in combination with different input types has yet to be addressed. This study experimented with two techniques for transforming the segmented accelerometer data to make them more orientation-independent. The methods included calculating the magnitude of the three-axis accelerometer vector and calculating the Discrete Fourier Transform for both sets of three-axis data as the vector magnitude. Three different deep learning models were trained on this data: a Multilayer Perceptron, a Convolutional Neural Network, and an ensemble merging both called a hybrid Convolutional Neural Network. Besides mixed cross-validation, every model and input type combination was assessed on a goat-wise leave-one-out cross-validation set to evaluate its generalizing capability. Using orientation-independent data transformations gave promising results. A hybrid Convolutional Neural Network with $L^2$-norm as the input combined the higher classification accuracy of a Convolutional Neural Network with the lower standard deviation of a Multilayer Perceptron. Most of the misclassifications occurred for behaviors that display similar accelerometer traces and minority classes, which could be improved in future work by assembling larger and more balanced datasets. Full article

Aquatic vegetation in the littoral zone plays a crucial role in attenuating wave energy and protecting coastal communities from hazardous events. This study contributes to the development of numerical models aimed at designing nature-based coastal defense systems. Specifically, a novel numerical application for simulating wave–vegetation interactions at the stem scale is presented. The numerical model employed, DualSPHysics, couples the meshfree Smoothed Particle Hydrodynamics (SPH) fluid solver with a structural solver to accurately capture the two-way interactions between waves and flexible vegetation. The proposed numerical model is validated against experimental data involving a submerged rubber cylinder representing an individual vegetation stem, subjected to regular waves. The results demonstrate excellent agreement in hydrodynamics, force transfer, and the swaying motion of the flexible cylinder. Importantly, the approach explicitly captures energy transfer between the fluid environment and the individual stem. The numerical results indicate persistent turbulent flow along the vegetation stem, even when its swaying speed matches that of the surrounding environment. This reveals the presence of vortex shedding and energy dissipation, which challenges the concept of passive swaying in flexible aquatic vegetation. Full article

A vectorized analytical model for the cutting dynamics in the spiral bevel gear face hobbing process has been developed, which is based on machine tool kinematics and vibration vectorization. The structural modal parameters of the cutter head spindle system are obtained through experimental modal analysis with hammer impact testing. The analytical model is utilized to simulate the generation of simulated vibration acceleration signals during spiral bevel gear hobbing. A wavelet threshold denoising method is applied to process the simulated vibration signals of the spiral bevel gear face hobbing with added white noise. Signal processing methods, including short-time Fourier transform are employed for time-domain analysis, frequency-domain analysis, and time–frequency-domain analysis of measured signals and simulated signals, thereby extracting the corresponding statistical features. In addition to the results of the experimental modal analysis, the causes of chatter in spiral bevel gear hobbing are discussed in detail, revealing that the main factor is cutter head vibration in the Y direction of the Hunan ZDCY CNC EQUIPMENT YKA2260 machine tool used in this research. The error in the time-domain characteristic parameters between simulated signals and measured vibration acceleration signals is within 15%, with a difference of 3.5% in spectral peak values. The predicted tooth surface morphology from simulation matches the actual morphology on the workpiece, comprehensively validating the reliability of the cutting dynamics model for the spiral bevel gear face hobbing process. Another conclusion drawn from numerical simulation experiments is that the amount of tooth surface waviness of the spiral bevel gears is the ratio of tool chatter frequency to cutting fundamental frequency. Full article

Acute kidney damage (AKI) is a serious and common consequence among critically unwell individuals. Traditional biomarkers, such as serum creatinine, frequently fail to detect AKI in its early stages, necessitating the development of new accurate early biomarkers. Tissue inhibitor of metalloproteinases 2 (TIMP-2) has emerged as a promising biomarker for predicting early AKI. The present narrative review investigates the role of TIMP-2 in AKI prediction in a variety of clinical scenarios. In the NephroCheck^® test, TIMP-2 exceeds established biomarkers for the early identification of AKI in terms of sensitivity and specificity when combined with insulin-like growth factor-binding protein 7 (IGFBP-7). Elevated levels of these biomarkers can provide a warning signal for AKI two to three days before clinical symptoms appear. TIMP-2 and IGFBP-7 have high predictive values, with an area under the curve (AUC) typically above 0.8, indicating good predictive capacity. For example, the [TIMP-2] × [IGFBP-7] product produced an AUC of 0.85 in surgical patients at high risk. In critically ill patients, a threshold of 0.3 (ng/mL)²/1000 demonstrated 92% sensitivity and 72% specificity. Elevated TIMP-2 levels have been correlated with higher mortality rates and the need for renal replacement therapy (RRT). In sepsis-associated AKI (SA-AKI), TIMP-2 levels combined with clinical prognostic models improved predictive accuracy (AUC: 0.822). Furthermore, elevated urine TIMP-2 levels were good predictors of AKI in pediatric patients after cardiac surgery, with AUC-ROC values of up to 0.848. Urine output and the presence of concomitant disorders may influence the prognostic accuracy of these biomarkers; therefore, more research is needed to fully understand their utility. The predictive value of TIMP-2 could be strengthened by combining it with other clinical parameters, reinforcing its role in the early detection and treatment of AKI. Full article

Extensive green roofs provide for many ecosystem services in urban environments. The efficacy of these services is influenced by the vegetation structure. Despite their key role in plant performance and productivity, but also their contribution to nitrogen fixation or carbon sequestration, green roof microbial communities have received little attention so far. No study included a spatiotemporal aspect to investigate the core microbiota residing in the substrates of extensive green roofs, although these key taxa are hypothesized to be amongst the most ecologically important taxa. Here, we identified the core microbiota residing in extensive green roof substrates and investigated whether microbial community composition is affected by the vegetation that is planted on extensive green roofs. Eleven green roofs from three different cities in Flanders (Belgium), planted either with a mixture of grasses, wildflowers and succulents (Sedum spp.; Sedum–herbs–grasses roofs) or solely species of Sedum (Sedum–moss roofs), were seasonally sampled to investigate prokaryotic and fungal communities via metabarcoding. Identifying the key microbial taxa revealed that most taxa are dominant phylotypes in soils worldwide. Many bacterial core taxa are capable of nitrogen fixation, and most fungal key taxa are stress-tolerant saprotrophs, endophytes, or both. Considering that soil microbes adapted to the local edaphic conditions have been found to improve plant fitness, further investigation of the core microbiome is warranted to determine the extent to which these stress-tolerant microbes are beneficial for the vegetational layer. Although Sedum–herbs–grasses roofs contained more plant species than Sedum–moss roofs, we observed no discriminant microbial communities between both roof types, likely due to sharing the same substrate textures and the vegetational layers that became more similar throughout time. Future studies are recommended to comprehensively characterize the vegetational layer and composition to examine the primary drivers of microbial community assembly processes. Full article

Vitamin D-binding protein (DBP), also known as Gc-globulin, is a protein that affects several physiological processes, including the transport and regulation of vitamin D metabolites. Genetic polymorphisms in the DBP gene have a significant impact on vitamin D levels and may have implications for disease risk. DBP polymorphisms are linked to differential immune responses, which could influence the onset of juvenile diseases. This narrative review examines the various roles of DBP, with a focus on bone health, immunological regulation, and lipid metabolism in children. Chronic disorders affected by DBP polymorphisms include bone abnormalities, autoimmune diseases, cardiovascular issues, childhood asthma, allergies, cystic fibrosis, acute liver failure, celiac disease, inflammatory bowel disease, and chronic kidney disease. Future research should focus on identifying the processes that underpin the many roles that DBP plays and developing customized therapeutics to improve health outcomes in the juvenile population. Full article

The transport sector accounts for approximately a quarter of the EU’s total greenhouse gas emissions, with freight transport alone accounting for about one-third of the overall transport-related emissions. Mitigating the sector’s environmental impact is crucial for tackling climate change and achieving sustainable development goals. Modal shift is one of the main solutions to address this challenge; however, many companies have yet to realize its full potential. This paper presents a survey conducted in the Flanders region of Belgium, aiming to identify the challenges and barriers faced by industry players in this key geographical area and to explore the reasons behind the limited implementation of synchromodal transport among them. The survey evaluates the current state of synchromodal transport adoption and offers valuable insights for policymakers and industry stakeholders aiming to enhance sustainability in the logistics sector. The findings emphasize that to overcome the identified challenges, both policy support and the companies’ commitment are required. Policy support includes establishing consistent regulations and promoting greener transport modes through providing incentives and technological advancements. This research contributes to the field by examining barriers to the adoption of synchromodality and exploring its application within the context of Flanders. By focusing on this strategic logistics hub, the study provides insights and recommendations tailored to the specific challenges of the region’s logistics sector. The challenges faced by industry players in Flanders offer a deeper understanding of modal shift dynamics, facilitating informed decision-making for policymakers and industry stakeholders. Implementing these strategies paves the way for more environmentally friendly, efficient, and integrated transport, benefiting both the industry and the planet. Full article

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs. Full article

In this work, we present a compact, bifunctional chip-based sensor setup that measures the temperature and electrical conductivity of water samples, including specimens from rivers and channels, aquaculture, and the Atlantic Ocean. For conductivity measurements, we utilize the impedance amplitude recorded via interdigitated electrode structures at a single triggering frequency. The results are well in line with data obtained using a calibrated reference instrument. The new setup holds for conductivity values spanning almost two orders of magnitude (river versus ocean water) without the need for equivalent circuit modelling. Temperature measurements were performed in four-point geometry with an on-chip platinum RTD (resistance temperature detector) in the temperature range between 2 °C and 40 °C, showing no hysteresis effects between warming and cooling cycles. Although the meander was not shielded against the liquid, the temperature calibration provided equivalent results to low conductive Milli-Q and highly conductive ocean water. The sensor is therefore suitable for inline and online monitoring purposes in recirculating aquaculture systems. Full article

The early detection of gynecological cancers, which is critical for improving patient survival rates, is challenging because of the vague early symptoms and the diagnostic limitations of current approaches. This comprehensive review delves into the game-changing potential of infrared (IR) spectroscopy, a noninvasive technology used to transform the landscape of cancer diagnosis in gynecology. By collecting the distinctive vibrational frequencies of chemical bonds inside tissue samples, Fourier-transform infrared (FTIR) spectroscopy provides a ‘molecular fingerprint’ that outperforms existing diagnostic approaches. We highlight significant advances in this field, particularly the identification of discrete biomarker bands in the mid- and near-IR spectra. Proteins, lipids, carbohydrates, and nucleic acids exhibited different absorption patterns. These spectral signatures not only serve to distinguish between malignant and benign diseases, but also provide additional information regarding the cellular changes associated with cancer. To underscore the practical consequences of these findings, we examined studies in which IR spectroscopy demonstrated exceptional diagnostic accuracy. This review supports the use of IR spectroscopy in normal clinical practice, emphasizing its capacity to detect and comprehend the intricate molecular underpinnings of gynecological cancers. Full article

Most highly developed countries invest considerably in language training programmes for refugees, which are assumed to facilitate economic, social, and cultural integration. Although recent research has turned to particular patterns of host country language acquisition amongst refugees, the impact of the COVID-19 pandemic has hitherto remained understudied. Consequently, this article assesses changes in refugees’ uptake and outcomes of language training over the onset of the pandemic using longitudinal population data for Belgium (Flanders). Findings confirm theoretical expectations, as refugee cohorts entering the country after the onset of the pandemic exhibit lower Dutch language credentials, mostly due to lower enrolment and lower proficiency at intake for language courses. Furthermore, this study indicates that such changes are considerably weaker for highly educated and female refugees. These findings are interpreted in terms of increased vulnerability resulting from the pandemic as well as within-group diversity in potential barriers to integration in the host country. Full article

Renal amyloidosis is a set of complex disorders characterized by the deposition of amyloid proteins in the kidneys, which causes gradual organ damage and potential kidney failure. Recent developments in diagnostic methods, particularly mass spectrometry and proteome profiling, have greatly improved the accuracy of amyloid typing, which is critical for disease management. These technologies provide extensive insights into the specific proteins involved, allowing for more targeted treatment approaches and better patient results. Despite these advances, problems remain, owing to the heterogeneous composition of amyloid proteins and the varying efficacy of treatments based on amyloid type. Access to sophisticated diagnostics and therapy varies greatly, highlighting the global difference in renal amyloidosis management. Future research is needed to investigate next-generation sequencing and gene-editing technologies, like clustered regularly interspaced short palindromic repeats (CRISPR), which promise more profound insights into the genetic basis of amyloidosis. Full article

In this paper, we introduce SonoNERFs, a novel approach that adapts Neural Radiance Fields (NeRFs) to model and understand the echolocation process in bats, focusing on the challenges posed by acoustic data interpretation without phase information. Leveraging insights from the field of optical NeRFs, our model, termed SonoNERF, represents the acoustic environment through Neural Reflectivity Fields. This model allows us to reconstruct three-dimensional scenes from echolocation data, obtained by simulating how bats perceive their surroundings through sound. By integrating concepts from biological echolocation and modern computational models, we demonstrate the SonoNERF’s ability to predict echo spectrograms for unseen echolocation poses and effectively reconstruct a mesh-based and energy-based representation of complex scenes. Our work bridges a gap in understanding biological echolocation and proposes a methodological framework that provides a first-order model of how scene understanding might arise in echolocating animals. We demonstrate the efficacy of the SonoNERF model on three scenes of increasing complexity, including some biologically relevant prey–predator interactions. Full article