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Background/Objectives: The rise and spread of antimicrobial resistance complicates the treatment of bacterial wound pathogens, further increasing the need for newer, effective therapies. Azoles such as miconazole have shown promise as antibacterial compounds; however, they are currently only used as antifungals. Previous research has shown that combining azoles with quaternary ammonium compounds yields synergistic activity against fungal pathogens, but the effect on bacterial pathogens has not been studied yet. Methods: In this study, the focus was on finding active synergistic combinations of imidazoles and quaternary ammonium compounds against (multidrug-resistant) bacterial pathogens through checkerboard assays. Experimental evolution in liquid culture was used to evaluate the possible emergence of resistance against the most active synergistic combination. Results: Several promising synergistic combinations were identified against an array of Gram-positive pathogens: miconazole/domiphen bromide, ketoconazole/domiphen bromide, clotrimazole/domiphen bromide, fluconazole/domiphen bromide and miconazole/benzalkonium chloride. Especially, miconazole with domiphen bromide exhibits potential, as it has activity at a low concentration against a broad range of pathogens and shows an absence of strong resistance development over 11 cycles of evolution. Conclusions: This study provides valuable insight into the possible combinations of imidazoles and quaternary ammonium compounds that could be repurposed for (topical) wound treatment. Miconazole with domiphen bromide shows the highest application potential as a possible future wound therapy. However, further research is needed into the mode of action of these compounds and their efficacy and toxicity in vivo.

Bio-based and biodegradable polyhydroxyalkanoates (PHAs) have great potential as sustainable packaging materials. The incorporation of zinc oxide nanoparticles (ZnO NPs) could further improve their functional properties by providing enhanced barrier and antimicrobial properties, although current literature lacks details on how the characteristics of ZnO influence the structure–property relationships in PHA/ZnO nanocomposites. Therefore, commercial ZnO NPs with different morphologies (rod-like, spherical) and silane surface modification are incorporated into poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx) via extrusion and compression molding. All ZnO NPs are homogeneously distributed in the PHBHHx matrix at 1, 3 and 5 wt.%, but finer dispersion is achieved with modified ZnO. No chemical interactions between ZnO and PHBHHx are observed due to a lack of hydroxyl groups on ZnO. The fabricated nanocomposite films retain the flexible properties of PHBHHx with minimal impact of ZnO NPs on crystallization kinetics and the degree of crystallinity (53 to 56%). The opacity gradually increases with ZnO loading, while remaining translucent up to 5 wt.% ZnO and providing an effective UV barrier. Improved oxygen barrier and antibacterial effects against S. aureus are dependent on the intrinsic characteristics of ZnO rather than its morphology. We conclude that PHBHHx retains its favorable processing properties while producing nanocomposite films that are suitable as flexible active packaging materials.

Bayesian state and parameter estimation are automated effectively in a variety of probabilistic programming languages. The process of model comparison on the other hand, which still requires error-prone and time-consuming manual derivations, is often overlooked despite its importance. This paper efficiently automates Bayesian model averaging, selection, and combination by message passing on a Forney-style factor graph with a custom mixture node. Parameter and state inference, and model comparison can then be executed simultaneously using message passing with scale factors. This approach shortens the model design cycle and allows for the straightforward extension to hierarchical and temporal model priors to accommodate for modeling complicated time-varying processes.

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Because data are scarce, we examined the relationship between postexercise hypotension (PEH) and heart rate variability (HRV) before and after aerobic exercise training among adults with hypertension. Participants completed a 12 w aerobic training program. Before and after training, they performed a peak graded exercise stress test (GEST) and nonexercise control (CONTROL) and were left attached to an ambulatory BP monitor. Prior to CONTROL, HRV was measured supine for 5 min using a 12-lead electrocardiogram (ECG). The participants (n = 18) were middle-aged (52.1 ± 11.7 y) and 50% men with hypertension (131.7 ± 9.8/85.9 ± 8.5 mmHg) and obesity (30.0 ± 3.7 kg·m−2). Before training, ambulatory systolic BP (ASBP) and diastolic ABP (ADBP) decreased by 3.2 ± 2.1 mmHg and 2.5 ± 1.5 mmHg, respectively, from baseline after the GEST versus CONTROL (p < 0.05). After training, ASBP tended to decrease by 3.5 ± 2.2 mmHg (p = 0.055) and ADBP decreased by 1.7 ± 2.5 mmHg (p = 0.001) from baseline after the GEST versus CONTROL. Before training, HRV high frequency (HFms2) (β = −0.441), age (β = 0.568), and resting SBP (β = 0.504) accounted for 66.8% of the ASBP response (p = 0.001), whereas the low frequency (LF)/HF ratio (β = 0.516) and resting DBP (β = 0.277) accounted for 35.7% of the ADBP response (p = 0.037). After training, the standard deviation of NN intervals (SDNN) (β = −0.556), age (β = 0.506), and resting SBP (β = 0.259) accounted for 60.7% of the ASBP response (p = 0.004), whereas SDNN (β = −0.236) and resting DBP (β = 0.785) accounted for 58.5% of the ADBP response (p = 0.001). Our preliminary findings show that adults with hypertension and parasympathetic suppression (i.e., lower SDNN and HFms2 and higher LF/HF) may elicit PEH to the greatest degree independent of training status versus adults with parasympathetic predominance, suggesting that resting HRV may be an important determinant of PEH.

We analysed all proven cases of SARS-CoV-2 on sea-going vessels entering or present in the Port of Rotterdam to illustrate the burden of the corona pandemic on commercial shipping. We calculated the notification rate (NR) per arrival and attack rate per vessel and correlated outbreak sizes by vessel type over time during the pandemic using routinely gathered data from the port and public health (PH) authorities.

The aim of the study is to describe the routine inspections conducted by competent Public Health Authorities (PHAs) on board passenger ships (cruise ships, inland vessels or ferries) sailing in European countries during the EU HEALTHY GATEWAYS joint action and according to the hygiene standards set out in the European Manual for Hygiene Standards and Communicable Disease Surveillance on Passenger Ships (Edition 2nd, April 2016). From 2018 to the end of April 2022, 138 inspection reports were submitted by PHAs in 38 ports in SIS by 76 inspectors, three SHIPSAN experts, 16 inspectors in training and 31 observers, along with 130 Corrective Action Statements by shipping companies or officers of ships.

We present the first algorithm that combines privacy-preserving technologies and state-of-the-art explainable AI to enable privacy-friendly explanations of black-box AI models. We provide a secure algorithm for contrastive explanations of black-box machine learning models that securely trains and uses local foil trees. Our work shows that the quality of these explanations can be upheld whilst ensuring the privacy of both the training data and the model itself.

C-arm flat-panel detector computed tomographic (CT) imaging in the angiography suite increasingly plays an important part during interventional neuroradiological procedures. In addition to conventional angiographic imaging of blood vessels, flat detector CT (FD CT) imaging allows simultaneous 3D visualization of parenchymal and vascular structures of the brain. Next to imaging of anatomical structures, it is also possible to perform FD CT perfusion imaging of the brain by means of cerebral blood volume (CBV) or pooled blood volume (PBV) mapping during steady state contrast administration. This enables more adequate decision making during interventional neuroradiological procedures, based on real-time insights into brain perfusion on the spot, obviating time consuming and often difficult transportation of the (anesthetized) patient to conventional cross-sectional imaging modalities. In this paper we review the literature about the nature of FD CT PBV mapping in patients and demonstrate its current use for diagnosis and treatment monitoring in interventional neuroradiology.

Pre-operative embolization of hypervascular intracranial tumors can be performed to reduce bleeding complications during resection. Accurate vascular mapping of the tumor is necessary for both the correct indication setting for embolization and for the evaluation of the performed embolization. We prospectively examined the role of whole brain and selective parenchymal blood volume (PBV) flat detector computer tomography perfusion (FD CTP) imaging in pre-operative angiographic mapping and embolization of patients with hypervascular intracranial tumors. Whole brain FD CTP imaging with a contrast injection from the aortic root and selective contrast injection in the dural feeding arteries was performed in five patients referred for tumor resection. Regional relative PBV values were obtained pre- and post-embolization. Total tumor volumes with selective external carotid artery (ECA) supply volumes and post-embolization devascularized tumor volumes were determined as well. In all patients, including four females and one male, with a mean age of 54.2 years (range 44–64 years), the PBV scans were performed without adverse events. The average ECA supply was 54% (range 31.5–91%). The mean embolized tumor volume was 56.5% (range 25–94%). Relative PBV values decreased from 5.75 ± 1.55 before embolization to 2.43 ± 1.70 post-embolization. In one patient, embolization was not performed because of being considered not beneficial for the resection. Angiographic FD CTP imaging of the brain tumor allows 3D identification and quantification of individual tumor feeder arteries. Furthermore, the technique enables monitoring of the efficacy of pre-operative endovascular tumor embolization.

We solve the millionaires problem in the semi-trusted model with homomorphic encryption without using intermediate decryptions. This leads to the computationally least expensive solution with homomorphic encryption so far, with a low bandwidth and very low storage complexity. The number of modular multiplications needed is less than the number of modular multiplications needed for one Pallier encryption. The output of the protocol can be either publicly known, encrypted, or secret-shared. The private input of the first player is computationally secure towards the second player, and the private input of the second player is even unconditionally secure towards the first player. We also introduce an efficient client-server solution for the millionaires problem with similar security properties.

Torsional vibrations play a critical role in the design and operation of a mechanical or mechatronic drivetrain due to their impact on lifetime, performance, and cost. A magnetic spring allows one to reduce these vibrations and improve the actuator performance yet introduces additional challenges on the identification. As a direct torque measurement is generally not favourable because of its intrusive nature, this paper proposes a nonintrusive approach to identify torsional load profiles. The approach combines a physics-based lumped parameter model of the torsional dynamics of the drivetrain with measurements coming from a motor encoder and two MEMS accelerometers in a combined state/input estimation, using an augmented extended Kalman filter (A-EKF). In order to allow a generic magnetic spring torque estimation, a random walk input model is used, where additionally the angle-dependent behaviour is exploited by constructing an angle-dependent estimate and variance map. Experimental validation leads to a significant reduction in bias in the load torque estimation for this approach, compared to conventional estimators. Moreover, this newly proposed approach significantly reduces the variance on the estimated states by exploiting the angle dependency. The proposed approach provides knowledge of the torsional vibrations in a nonintrusive way, without the need for an extensive magnetic spring torque identification. Further, the approach is applicable on any drivetrain with angle-dependent input torques.

The optimization of a 2D optical sensor based on TiO2–SiO2 sol-gel waveguides for damage detection in the aerospace domain was performed in the framework of the ADD-ON European project. The sensor is based on the transportation of visible light along numerous waveguides, and damage is detected and localized through the monitoring of the output light from the waveguide grid. In this work, we have developed an architecture, inspired by a multi-mode interferometer (MMI), allowing us to efficiently multiply the number of waveguides that can be probed by a single optical source. For this, the beam propagation method (BPM) was used to model a rectangular MMI coupler (40 × 5624 µm2) operating in the visible region (600 nm), ensuring the propagation of light into three waveguides. The conceived device was then manufactured by UV photolithography (direct laser writing technique). The simulations and experimental results show that light transport into this architecture allows for the successful simultaneous probing of three waveguides. By complexifying the device structure, successful MMI couplers were easily manufactured, allowing us to probe 9, 15, or 45 TiO2–SiO2 waveguides with a unique light source. Finally, a further investigation regarding 24 consecutive thermal cycles from −40 °C to 60 °C, representative of the temperature changes during aircraft cruising, was performed. This study reveals that TiO2–SiO2 sol-gel waveguides are not mechanically damaged by temperature changes, while the light guidance remains unaffected, confirming that this sensor is very promising for aerospace applications. Since a single source can monitor several guides, the production of more compact, low-cost, and less intrusive sensors can be achieved by fulfilling structural health monitoring requirements.

Vertical farming is on its way to becoming an addition to conventional agricultural practices, improving sustainable food production for the growing world population under increasing climate stress. While the early development of vertical farming systems mainly focused on technological advancement through design innovation, the automation of hydroponic cultivation, and advanced LED lighting systems, more recent studies focus on the resilience and circularity of vertical farming. These sustainability objectives are addressed by investigating water quality and microbial life in a hydroponic cultivation context. Plant growth-promoting rhizobacteria (PGPR) have been shown to improve plant performance and resilience to biotic and abiotic stresses. The application of PGPRs to plant-growing media increases microbial functional diversity, creating opportunities to improve the circularity and resilience of vertical farming systems by reducing our dependency on chemical fertilizers and crop protection products. Here, we give a brief historical overview of vertical farming, review its opportunities and challenges in an economic, environmental, social, and political context, and discuss advances in exploiting the rhizosphere microbiome in hydroponic cultivation systems.

Active galactic nuclei (AGN) at the centres of galaxies can cycle between periods of activity and of quiescence. Characterising the duty-cycle of AGN is crucial for understanding their impact on the evolution of the host galaxy. For radio AGN, their evolutionary stage can be identified from a combination of morphological and spectral properties. We summarise the results we have obtained in the last few years by studying radio galaxies in various crucial phases of their lives, such as remnant and restarted sources. We used morphological information derived from LOw Frequency ARray (LOFAR) images at 150 MHz, combined with resolved spectral indices maps, obtained using recently released images at 1400 MHz from the APERture Tile In Focus (Apertif) phased-array feed system installed on the Westerbork Synthesis Radio Telescope. Our study, limited so far to the Lockman Hole region, has identified radio galaxies in the dying and restarted phases. We found large varieties in their properties, relevant for understanding their evolutionary stage. We started by quantifying their occurrences, the duration of the ‘on’ (active) and ‘off’ (dying) phase, and we compared the results with models of the evolution of radio galaxies. In addition to these extreme phases, the resolved spectral index images can also reveal interesting secrets about the evolution of apparently normal radio galaxies. The spectral information can be connected with, and used to improve, the Fanaroff–Riley classification, and we present one example of this, illustrating what the combination of the LOFAR and Apertif surveys now allow us to do routinely.

Recovery of nutrients from source-separated urine can truncate our dependency on synthetic fertilizers, contributing to more sustainable food production. Urine-derived fertilizers have been successfully applied in soilless cultures. However, little is known about the adaptation of the plant to the nutrient environment. This study investigated the impact of urine-derived fertilizers on plant performance and the root-associated bacterial community of hydroponically grown lettuce (Lactuca sativa L.). Shoot biomass, chlorophyll, phenolic, antioxidant, and mineral content were associated with shifts in the root-associated bacterial community structures. K-struvite, a high-performing urine-derived fertilizer, supported root-associated bacterial communities that overlapped most strongly with control NPK fertilizer. Contrarily, lettuce performed poorly with electrodialysis (ED) concentrate and hydrolyzed urine and hosted distinct root-associated bacterial communities. Comparing the identified operational taxonomic units (OTU) across the fertilizer conditions revealed strong correlations between specific bacterial genera and the plant physiological characteristics, salinity, and NO3−/NH4+ ratio. The root-associated bacterial community networks of K-struvite and NPK control fertilized plants displayed fewer nodes and node edges, suggesting that good plant growth performance does not require highly complex ecological interactions in hydroponic growth conditions.

Accurate evaluation of Bayesian model evidence for a given data set is a fundamental problem in model development. Since evidence evaluations are usually intractable, in practice variational free energy (VFE) minimization provides an attractive alternative, as the VFE is an upper bound on negative model log-evidence (NLE). In order to improve tractability of the VFE, it is common to manipulate the constraints in the search space for the posterior distribution of the latent variables. Unfortunately, constraint manipulation may also lead to a less accurate estimate of the NLE. Thus, constraint manipulation implies an engineering trade-off between tractability and accuracy of model evidence estimation. In this paper, we develop a unifying account of constraint manipulation for variational inference in models that can be represented by a (Forney-style) factor graph, for which we identify the Bethe Free Energy as an approximation to the VFE. We derive well-known message passing algorithms from first principles, as the result of minimizing the constrained Bethe Free Energy (BFE). The proposed method supports evaluation of the BFE in factor graphs for model scoring and development of new message passing-based inference algorithms that potentially improve evidence estimation accuracy.

The potential of sol–gel-based optical sensors is investigated for applications in the aerospace domain. To this aim, a low-cost and non-intrusive sol–gel sensor based on waveguides, arranged as a 2D matrix structure, is fabricated by UV photolithography for delamination and damage detection. Two different organic–inorganic sol–gels were selected to fabricate the photonic device: TiO2–SiO2 and ZrO2–SiO2, acting as the waveguide core and the cladding, respectively. A systematic study was performed to determine the manufacturing parameters controlling their properties. The results show that large surfaces can be functionalized via sol–gel methods using the direct laser-writing approach. The structures are characterized in terms of refractive index, and the guiding properties were investigated through simulations and experiments, indicating an excellent behavior regarding the light guidance in a straight waveguide or in the 2D matrix structure grid. Additionally, preliminary tests show that the presence of impact can be easily detected after damage through the induced optical losses on large surfaces. This proof of concept sensor is a promising tool for structural health monitoring. To achieve the ultimate goal, the integration of this photonic sensor will be later performed on aircraft wings.

The study of cell proliferation is of great importance for medical and biological research, as well as for industrial applications. To render the proliferation process accurately over time, real-time cell proliferation assay methods are required. This work presents a novel real-time and label-free approach for monitoring cell proliferation by continuously measuring changes in thermal properties that occur at the sensor interface during the process. The sensor consists of a single planar resistive structure deposited on a thin foil substrate, integrated at the bottom of a cell culture reservoir. During measurement, the structure is excited with square wave current pulses. Meanwhile, the temperature-induced voltage change measured over the structure is used to derive variations in the number of cells at the interface. This principle is demonstrated first by performing cell sedimentation measurements to quantify the presence of cells at the sensor interface in the absence of cell growth. Later, cell proliferation experiments were performed, whereby parameters such as the available nutrient content and the cell starting concentration were modified. Results from these experiments show that the thermal-based sensor is able to accurately measure variations in the number of cells at the interface. Moreover, the influence of the modified parameters could be observed in the obtained proliferation curves. These findings highlight the potential for the presented thermal method to be incorporated in a standardized well plate format for high-throughput monitoring of cell proliferation.

Recent changes in European legislation have legalized the abandonment of carcasses around livestock farms, but our understanding of how vultures exploit these semi-predictable food sources is still very limited. For filling this gap, we determine the individual and ecological drivers influencing vulture visits to farms. We assessed the effects of individual characteristics of both birds and farms on the frequency of vultures’ visits to livestock facilities using data collected from 45 GPS-tagged Egyptian Vultures (Neophron percnopterus) and 318 farms (>94% of livestock) on Fuerteventura Island, Spain. Farms were more visited during the vultures’ breeding season. Farms located closer to highly predictable feeding places (i.e., vulture restaurants and garbage dumps) or with more available feeding resources were visited by more vultures, whereas those located close to roads and vultures’ breeding territories received fewer visits. Younger territorial birds visited a farm more frequently than older territorial ones, whereas older non-territorial individuals concentrated those visits on farms closer to their activity core areas compared with younger ones. Our findings indicate that visits to farms were determined by their spatial distribution in relation to the age-specific birds’ activity centers, the availability of carcasses, seasonality, and individual characteristics of vultures. These interacting factors should be considered in vulture conservation, avoiding very general solutions that ignore population structure.

There is a need for plant growing media that can support a beneficial microbial root environment to ensure that optimal plant growth properties can be achieved. We investigated the effect of five rhizosphere bacterial community inocula (BCI S1–5) that were collected at three open field organic farms and two soilless farms on the performance of lettuce (Lactuca sativa L.). The lettuce plants were grown in ten different plant growing media (M1–10) composed of 60% v/v peat (black peat or white peat), 20% v/v other organics (coir pith or wood fiber), 10% v/v composted materials (composted bark or green waste compost) and 10% v/v inorganic materials (perlite or sand), and one commercial plant growing medium inside a plant factory with artificial lighting. Fractional factorial design of experiments analysis revealed that the bacterial community inoculum, plant growing medium composition, and their interaction determine plant performance. The impact of bacterial amendments on the plant phenotype relied on the bacterial source. For example, S3 treatment significantly increased lettuce shoot fresh weight (+57%), lettuce head area (+29%), root fresh weight (+53%), and NO3-content (+53%), while S1 treatment significantly increased lettuce shoot dry weight (+15%), total phenolic content (+65%), and decreased NO3-content (−67%). However, the effectiveness of S3 and S1 treatment depended on plant growing medium composition. Principal component analysis revealed that shoot fresh weight, lettuce head area, root fresh weight, and shoot dry weight were the dominant parameters contributing to the variation in the interactions. The dominant treatments were S3-M8, S1-M7, S2-M4, the commercial plant growing medium, S1-M2, and S3-M10. Proper selection of plant growing medium composition is critical for the efficacy of bacterial amendments and achieving optimal plant performance inside a plant factory with artificial lighting.

The recent increase in large converter-based devices like electric vehicles and photovoltaics increases supraharmonic emissions in low-voltage grids, potentially affecting customer equipment and the grid. This paper aims to give an overview of the different factors influencing supraharmonic emissions from electric vehicles and studies the propagation of supraharmonic currents through a small, low-voltage grid. Measurements in an unique lab representing a possible future household gave valuable insight on the possible developments in primary and secondary supraharmonic emissions in a conventional or power-electronic-dominated system. Emission is, for some vehicles, influenced by the type of grid connection, whereas others show no difference in emission. The supraharmonic currents mainly stay within the local installation due to absorption of nearby devices. The level of voltage distortion is dependent on the connection impedance. During the measurements, another type of interaction between devices is observed in the form of “frequency beating” and intermodulation, in some cases resulting in the tripping of residual current devices. This interaction is further analyzed in order to better understand the possible impact it can have on the grid.

Flocculation or cell aggregation is a well-appreciated characteristic of industrial brewer’s strains, since it allows removal of the cells from the beer in a cost-efficient and environmentally-friendly manner. However, many industrial strains are non-flocculent and genetic interference to increase the flocculation characteristics are not appreciated by the consumers. We applied adaptive laboratory evolution (ALE) to three non-flocculent, industrial Saccharomyces cerevisiae brewer’s strains using small continuous bioreactors (ministats) to obtain an aggregative phenotype, i.e., the “snowflake” phenotype. These aggregates could increase yeast sedimentation considerably. We evaluated the performance of these evolved strains and their produced flavor during lab scale beer fermentations. The small aggregates did not result in a premature sedimentation during the fermentation and did not result in major flavor changes of the produced beer. These results show that ALE could be used to increase the sedimentation behavior of non-flocculent brewer’s strains.

Generation of a stable, soluble mimic of the HIV-1 envelope glycoprotein (Env) trimer on the virion surface has been considered an important first step for developing a successful HIV-1 vaccine. Recently, a soluble native-like Env trimer (BG505 SOSIP.664) has been described. This protein has facilitated major advances in the HIV-1 vaccine field, since it was the first Env immunogen that induced consistent neutralizing antibodies against a neutralization-resistant (tier 2) virus. Moreover, BG505 SOSIP.664 enabled elucidation of the atomic resolution structure of the Env trimer and facilitated the isolation and characterization of new broadly neutralizing antibodies against HIV-1. Here, we designed and characterized the BG505 SOSIP.664 trimer fused to fluorescent superfolder GFP (sfGFP), a GFP variant that allows efficient folding (BG505 SOSIP.664-sfGFP). Despite the presence of the sfGFP, the Env protein largely retained its morphology, antigenicity, glycan composition, and thermostability. In addition, we show that BG505 SOSIP.664-sfGFP can be used for fluorescence-based assays, such as flow cytometry.

In this work we present the first steps towards a molecularly imprinted polymer (MIP)-based biomimetic sensor array for the detection of small organic molecules via the heat-transfer method (HTM). HTM relies on the change in thermal resistance upon binding of the target molecule to the MIP-type receptor. A flow-through sensor cell was developed, which is segmented into four quadrants with a volume of 2.5 μL each, allowing four measurements to be done simultaneously on a single substrate. Verification measurements were conducted, in which all quadrants received a uniform treatment and all four channels exhibited a similar response. Subsequently, measurements were performed in quadrants, which were functionalized with different MIP particles. Each of these quadrants was exposed to the same buffer solution, spiked with different molecules, according to the MIP under analysis. With the flow cell design we could discriminate between similar small organic molecules and observed no significant cross-selectivity. Therefore, the MIP array sensor platform with HTM as a readout technique, has the potential to become a low-cost analysis tool for bioanalytical applications.

In this article we describe the integration of impedance spectroscopy (EIS) and surface plasmon resonance (SPR) into one surface analytic device. A polydimethylsiloxane (PDMS) flow cell is created, matching the dimensions of a commercially available sensor chip used for SPR measurements. This flow cell allowed simultaneous measurements between an EIS and a SPR setup. After a successful integration, a proof of principle study was conducted to investigate any signs of interference between the two systems during a measurement. The flow cell was rinsed with 10 mM Tris-HCl and 1× PBS buffer in an alternating manner, while impedance and shifts of the resonance angle were monitored. After achieving a successful proof of principle, a usability test was conducted. It was assessed whether simultaneous detection occurred when: (i) Protein A is adsorbed to the gold surface of the chip; (ii) The non-occupied zone is blocked with BSA molecules and (iii) IgG1 is bound to the Protein A. The results indicate a successful merge between SPR and EIS.

Worldwide cities are facing increasing temperatures due to climate change and increasing urban density. Green roofs are promoted as a climate adaptation measure to lower air temperatures and improve comfort in urban areas, especially during intensive dry and warm spells. However, there is much debate on the effectiveness of this measure, because of a lack of fundamental knowledge about evaporation from different green roof systems. In this study, we investigate the water and energy balance of different roof types on a rooftop in Amsterdam, the Netherlands. Based on lysimeter measurements and modeling, we compared the water and energy balance of a conventional green roof with blue-green roofs equipped with a novel storage and capillary irrigation system. The roofs were covered either with Sedum or by grasses and herbs. Our measurements and modeling showed that conventional green roof systems (i.e., a Sedum cover and a few centimeters of substrate) have a low evaporation rate and due to a rapid decline in available moisture, a minor cooling effect. Roofs equipped with a storage and capillary irrigation system showed a remarkably large evaporation rate for Sedum species behaving as C3 plants during hot, dry periods. Covered with grasses and herbs, the evaporation rate was even larger. Precipitation storage and capillary irrigation strongly reduced the number of days with dry-out events. Implementing these systems therefore could lead to better cooling efficiencies in cities.

To deal with the rising integration of stochastic renewables and energy intensive distributed energy resources (DER) to the electricity network, alternatives to expensive network reinforcements are increasingly needed. An alternative solution often under consideration is integrating flexibility from the consumer side to system management. However, such a solution needs to be contemplated from different angles before it can be implemented in practice. To this end, this article considers a case study of the Amsterdam ArenA stadium and its surrounding network where flexibility is expected to be available to support the network in the future. The article studies the technical aspects of using this flexibility to determine to what extent, despite the different, orthogonal goals, the available flexibility can be used by various stakeholders in scenarios with a large load from electric vehicle charging points. Furthermore, a legal study is performed to determine the feasibility of the technical solutions proposed by analysing current European Union (EU) and Dutch law and focusing on the current agreements existing between the parties involved. The article shows that flexibility in the network provided by Amsterdam ArenA is able to significantly increase the number of charging points the network can accommodate. Nonetheless, while several uses of flexibility are feasible under current law, the use of flexibility provided by electric vehicles specifically faces several legal challenges in current arrangements.

Serotonin is an important neurotransmitter that plays a major role in the pathogenesis of a variety of conditions, including psychiatric disorders. The detection of serotonin typically relies on high-performance liquid chromatography (HPLC), an expensive technique that requires sophisticated equipment and trained personnel, and is not suitable for point-of-care applications. In this contribution, we introduce a novel sensor platform that can measure spiked neurotransmitter concentrations in whole blood samples in a fast and low-cost manner by combining synthetic receptors with a thermal readout technique—the heat-transfer method. In addition, the design of a miniaturized version of the sensing platform is presented that aims to bridge the gap between measurements in a laboratory setting and point-of-care measurements. This fully automated and integrated, user-friendly design features a capillary pumping unit that is compatible with point-of-care sampling techniques such as a blood lancet device (sample volume—between 50 µL and 300 µL). Sample pre-treatment is limited to the addition of an anti-coagulant. With this fully integrated setup, it is possible to successfully discriminate serotonin from a competitor neurotransmitter (histamine) in whole blood samples. This is the first demonstration of a point-of-care ready device based on synthetic receptors for the screening of neurotransmitters in complex matrices, illustrating the sensor’s potential application in clinical research and diagnosis of e.g., early stage depression.

In this work, we investigate scheduling problems for electrical energy storage systems and formulate an algorithm that finds an optimal solution with minimal charging cycles in the case of a single device. For the considered problems, the storage system is used to reduce the peaks of the production and consumption within (part of) the electricity distribution grid, while minimizing device wear. The presented mathematical model of the storage systems captures the general characteristic of electrical energy storage devices while omitting the details of the specific technology used to store the energy. In this way, the model can be applied to a wide range of settings. Within the model, the wear of the storage devices is modeled by either: (1) the total energy throughput; or (2) the number of switches between charging and discharging, the so-called charging cycles. For the first case, where the energy throughput determines the device wear, a linear programming formulation is given. For the case where charging cycles are considered, an NP-hardness proof is given for instances with multiple storage devices. Furthermore, several observations about the structure of the problem are given when considering a single device. Using these observations, we develop a polynomial time algorithm of low complexity that determines an optimal solution. Furthermore, the solutions produced by this algorithm also minimize the throughput, next to the charging cycles, of the device. Due to the low complexity, the algorithm can be applied in various decentralized smart grid applications within future electricity distribution grids.

Implementation of evidence-informed rehabilitation of the upper limb is variable, and outcomes for stroke survivors are often suboptimal. We established a national partnership of clinicians, survivors of stroke, researchers, healthcare organizations, and policy makers to facilitate change. The objectives of this study are to increase access to best-evidence rehabilitation of the upper limb and improve outcomes for stroke survivors. This prospective pragmatic, knowledge translation study involves four new specialist therapy centers to deliver best-evidence upper-limb sensory rehabilitation (known as SENSe therapy) for survivors of stroke in the community. A knowledge-transfer intervention will be used to upskill therapists and guide implementation. Specialist centers will deliver SENSe therapy, an effective and recommended therapy, to stroke survivors in the community. Outcomes include number of successful deliveries of SENSe therapy by credentialled therapists; improved somatosensory function for stroke survivors; improved performance in self-selected activities, arm use, and quality of life; treatment fidelity and confidence to deliver therapy; and for future implementation, expert therapist effect and cost-effectiveness. In summary, we will determine the effect of a national partnership to increase access to evidence-based upper-limb sensory rehabilitation following stroke. If effective, this knowledge-transfer intervention could be used to optimize the delivery of other complex, evidence-based rehabilitation interventions.

Stroke is one of the most common causes of death and disability. Reperfusion therapies are the only treatment available during the acute phase of stroke. Due to recent clinical trials, these therapies may increase their frequency of use by extending the time-window administration, which may lead to an increase in complications such as hemorrhagic transformation, with parenchymal hematoma (PH) being the more severe subtype, associated with higher mortality and disability rates. Our aim was to find genetic risk factors associated with PH, as that could provide molecular targets/pathways for their prevention/treatment and study its genetic correlations to find traits sharing genetic background. We performed a GWAS and meta-analysis, following standard quality controls and association analysis (fastGWAS), adjusting age, NIHSS, and principal components. FUMA was used to annotate, prioritize, visualize, and interpret the meta-analysis results. The total number of patients in the meta-analysis was 2034 (216 cases and 1818 controls). We found rs79770152 having a genome-wide significant association (beta 0.09, p -value 3.90 × 10 -8 ) located in the RP11-362K2.2:RP11-767I20.1 gene and a suggestive variant (rs13297983: beta 0.07, p -value 6.10 × 10 -8 ) located in PCSK5 associated with PH occurrence. The genetic correlation showed a shared genetic background of PH with Alzheimer's disease and white matter hyperintensities. In addition, genes containing the ten most significant associations have been related to aggregated amyloid-β, tau protein, white matter microstructure, inflammation, and matrix metalloproteinases.