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Large-scale river models are generally discretized by relatively large mesh cells resulting in bathymetry discretization errors and numerical effects. These hydraulic models are generally calibrated by altering the bed roughness to compensate for these errors and effects. Consequently, the calibrated roughness values are mesh-dependent while generally local mesh refinements are executed after model calibration to study the effects of river interventions. This study shows both the errors caused by bathymetry discretization and numerical effects for locally refined meshes. First, schematised river meanders with a flat bed in the transverse flow direction are analysed to isolate the induced numerical effects by the mesh. Afterwards, a case study is considered to verify if similar mesh influences are found in natural river meanders. Curvilinear, triangular and hybrid (combination of curvilinear and triangular cells) meshes are used with different resolutions. The analysis shows that in the schematised river meanders lower depth-averaged flow velocities and larger water depths are simulated with coarser meshes. In the case study, substantial differences in hydrodynamics between the meshes are obtained suggesting that the bathymetry discretization is more influential than the numerical effects. Finally, it was found that triangular meshes, and rivers with narrow meander bends, are most sensitive to mesh resolution. Especially in these cases, it is desirable to refine the mesh at the desired locations before model calibration.

In crisis management decision-making, decision-makers have to combine (limited) situational information with their own experience. Whereas traditional, analog training of decision-making situations in crisis management costs considerable time and effort, digital serious games can be used as more accessible training environments to offer additional training moments. Another advantage is that digital games offer new didactic opportunities, such as inducing specific reflection from the trainees. This study examines the effect of self-reflection through social comparison on information usage and information literacy of players of a digital serious game for crisis management decision-making training. In an experiment, data was collected from 73 participants, 47 were eligible for further analysis, split over two conditions. Participants played two gameplay scenarios in fixed order. Participants in the experimental condition, between the two scenarios, saw a dashboard displaying their own as well as previous players’ in-game behavior up to that point. Participants in the control condition received no intervention between playing the two scenarios. Overall, participants in the experimental condition used significantly more information from more different sources, and compared to the control condition they kept taking significantly more time to decide in the second scenario. No significant between-condition differences regarding information literacy were found. Results indicate that in-game behavior can be (positively) influenced by letting players self-reflect on their own in-game behavior through social comparison. Results also suggest that the dashboard should display more specific information of players’ in-game behavior, providing guidance on what to improve, rather than simply offering a broad overview.

The 15 min city (or “X-minute city” in general) concept aims to give people access to all essential services and daily needs (e.g., healthcare, education, etc.) within X minutes of active transportation, to improve transport equity, sustainability, and traffic safety. To date, there is a lack of methods and tools to assess to what degree cities currently, or after implementing policies, comply with the X-minute city concept. This research aims to develop a methodology for quantifying the X-minute city through a metric (CSx) that was developed based on an accessibility framework and tested for cycling mode in the Utrecht region in the Netherlands as a study area. Travel data from the Netherlands mobility panel were analysed to determine input characteristics of the metric, such as the weight of destination types. Standardized gravity-based 2-step floating catchment area (2SFCA) accessibility scores for all destination types were weighted and aggregated into a composite metric that shows relative scores as an X-minute city. The results of the analysis show that 100% of the population in the Utrecht region has access to at least one destination for all 9 destination types within 15 min, whereas this number reduces to 94% within a 10 min cycling threshold; indicating the status of Utrecht as a cycling city with cycling-friendly infrastructure. Furthermore, low-income groups do not have lower cycling accessibility to the services in the 15 min city in the study area, reinforcing the notion that cycling can be an effective solution to reduce transport inequalities. The developed metric can be used to assess cities on their way towards becoming X-minute city, prioritise neighbourhoods to develop, set quantifiable goals, and evaluate planning scenarios.

This paper is aimed at analyzing the consumers’ willingness to use mobile apps that claim to contribute to mitigating the food waste problem. We study the extent to which such willingness is influenced by three factors related to the consumers’ willingness to use mobile apps in general (perceived usefulness, perceived ease of use, and perceived risks) and three factors related to the consumer behavior against food waste (food neophobia, moral attitude, and knowledge about food conservation). A survey was conducted on 283 Italian consumers. Results show that perceived usefulness and perceived ease of use positively affect the willingness to use mobile apps against food waste, while perceived risks by potential users negatively impact such willingness. However, none of the three consumer-related factors has been proved to be significant. The results of this paper offer managerial implications to developers, related to how to advertise the app and how to improve the app functionality, in order to enhance the consumers’ willingness to use.

ACTINOMYCOSIS is a rare chronic granulomatous disease caused by anaerobic filamentous gram-positive bacteria, the most common of which is Actinomyces israelii. Actinomycetes are commensal inhabitants of the oral cavity and gastrointestinal tract, but they may become pathogenic through invasion of breached or necrotic tissue. Pelviabdominal ACTINOMYCOSIS is uncommon and can mimic a variety of disease processes, including abdominal mass mimicking malignancy, acute abdomen, asthenia, and weight loss. We describe a 38-year-old woman who presented with acute abdominal pain and tenderness, as well as constitutional manifestations and elevated inflammatory markers. On initial computerized tomography (CT) and MRI, a large fluid collection underlining the anterior abdominal wall at the false pelvic cavity, as well as parietal peritoneal enhancement and smudging of the mesenteric fat and a bulky fibroid uterus with an implanted IUD, were identified. The ultrasound guided aspiration and anaerobic culture revealed positive growth for Actinomyces bacteria. An exploratory laparoscopy revealed extensive adhesions between the abdominal wall and the small intestine, as well as hyperemic and thickened peritoneum, and peritoneal biopsy confirmed ACTINOMYCOSIS. After the diagnosis was established, the IUD was removed and the patient was given Ceftriaxone 2 gm once daily for 6 weeks before switching to oral doxycycline 100 mg twice daily for another 3 months. A significant regression of the suprapubic fluid collection, and peritoneal-mesenteric changes were confirmed on follow-up. The case is discussed, and the relevant literature reviewed and analyzed.

The role of biofilm in the Microbiologically Influenced Corrosion (MIC) of carbon steel by Sulfate Reducing Bacteria (SRB) in oil and gas exploitation, and geothermal installations is investigated. Simulated biofilm made of calcium alginate, abiotic sulfide (to mimic SRB metabolic end product H2S), CO2 (to mimic CO2 from SRB dissimilatory sulfate reduction) and simulated brine (3.0 wt% NaCl) are used to simulate the SRB environment. For reference experiments, distilled water is used instead of simulated brine. The electrochemical results show that the simulated biofilm in the reference at 120 min exposure time and in brine experiments neither inhibits nor accelerates corrosion. These results are strongly supported by corrosion kinetic adsorption parameters, statistical T-test, ICP-OES, pH, SEM-EDS and XRD. The results contradict with the existing literature on the role of biofilm and this is likely due to the presence of both H2S and CO2 as simulated SRB metabolites. Despite of this discrepancy, the obtained corrosion rates (0.25 to 1.6 mm/year) in the simulated SRB environment are comparable to published corrosion rates obtained in SRB experiments (0.20 to 1.2 mm/year). The results highlight the novelty of this research and have a direct impact on the role of other microbial metabolites on the corrosion of carbon steel.

This article presents a framework for local electricity pricing mechanisms for households designed for social acceptance. The optimization goal of the mechanisms is to flatten the neighborhood electricity profile. The motivation and need for such mechanisms result from the expectation that the energy transition leads to high peaks in the distribution grid, both in electricity consumption and renewable generation, posing a significant challenge to these grids. Following the literature, quadratic cost functions have the potential to achieve the envisioned system optimization. However, their drawback is that consumers find the resulting pricing mechanisms too complicated and are generally not willing to participate in systems offering such prices. In contrast, the simpler pricing mechanisms currently used in practice are socially accepted. However, these mechanisms lack sufficient incentive to reduce electricity peaks in the distribution grids. Our approach is to combine these concepts in a hybrid pricing mechanism for local energy communities, using a piecewise linear cost function, that approximates a quadratic function. The resulting pricing mechanism is evaluated in a field test, and, based on the feedback of participating consumers and other criteria defined in literature, we can conclude that the proposed mechanism is socially accepted. In the implementation of this hybrid pricing mechanism, its performance can be improved such that it obtains results comparable to those of quadratic cost functions. Based on these findings, a detailed numerical evaluation, and the results from the field test, we conclude that the presented pricing mechanism has the potential for being used in practice.

Farms are not homogeneous. Smaller farms generally have different planted crops, yields, agricultural inputs, and irrigation applications compared to larger farms. However, gridded farm-size-specific data that are moreover crop specific, are currently lacking. This obscures our understanding of differences between small-scale and large-scale farms, e.g., with respect to climate change adaptation and mitigation strategies, contribution to (local) food security, and water consumption patterns. This study fills a significant part of the current data gap, by developing high-resolution gridded, simultaneously farm-size-specific and crop-specific datasets of harvested areas for 56 countries (i.e., covering about half the global cropland). Hereto, we downscaled the most complete global direct measurements of farm size and crop type by compiling state of the art datasets, including crop maps, cropland extent maps, and dominant field size distribution, representative for the year 2010. Using two different crop map sources, we were able to produce two new 5 arcmin gridded datasets on simultaneously derived farm-size-specific and crop-specific harvested areas: one for 11 farm sizes, 27 crops, and 2 farming systems, and one for 11 farm sizes, 42 crops, and 4 farming systems. In line with previous findings, our resulting datasets show major differences in planted crops and irrigated area (%) between farm sizes. Consistency between our resulting datasets and (i) observations from satellite images on farm-size-specific oil palm, (ii) household surveys on the farm-size-specific irrigated area (%), and (iii) previous studies that mapped noncrop-specific farm sizes and support the validity of our datasets. Although at grid level some uncertainties remain to be overcome, particularly those stemming from uncertainties in crop maps, results at country level seem robust. Source data, code, and resulting datasets are open access and freely available at https://doi.org/10.5281/zenodo.6976249 (Su et al., 2022).

Studies on polycentric urban development (PUD) have been done by using LandScan and point of interest data. So far, the quality of PUD products has been limited by the spatio-temporal resolution of these datasets. Using Sentinel-1 SAR missions with a 10 m pixel spacing and a weekly repeat cycle, this study, for the first time, explores the potential of using a time series of Sentinel-1 SAR images for measuring urban polycentricity. In particular, we develop a variance-based filtering method to mitigate speckle noise. We propose the Kittler and Illingworth with a Modified Model (KI-MM) method to accurately identify PUD-related changes. We focus on the mean distance of new-born patches and the mean patch area for a PUD-related change analysis. These allow us to associate SAR tailor-made output with PUDs. The proposed methods were implemented on Google Earth Engine platform using 304 Sentinel-1 SAR images on the city of Shanghai, China, acquired between 2015 and 2018. We have tested 80 distribution models and found that the Laplace distribution is the best model for the KI-MM method. Our results show 2526, 2409, 4232 new-born patches for 2015–2016, 2016–2017, 2017-2018, with areas equal to 18, 20, 36 km2, respectively. Using cross-validation with Sentinel-2 (optical) reference, we found that the matching rates and F1-score between detected changes and reference for the years 2015–2016, 2016–2017, 2017-2018 were equal to 89.79% and 91.67%, 100% and 100%, 88.64% and 94.06%, respectively. We conclude that Sentinel-1 SAR images are suited to PUD applications at an intra-city scale with a high spatio-temporal resolution.

We investigate numerically the sound properties of disordered dense granular packings in two dimensions. Employing linear equations of motion and excluding contact changes from our simulations, we demonstrate time evolution of sinusoidal standing waves of granular disks. We varied the strength of normal and tangential viscous forces between the disks in contact to explore the dependence of sound characteristics such as dispersion relations, attenuation coefficients, and sound speeds on the contact damping. For small wave numbers, the dispersion relations and sound speeds of acoustic modes are quite insensitive to the damping. However, a small dip in the phase speed of the transverse mode decreases as the viscous force in normal direction increases. In addition, the dispersion relation of the rotational mode differs qualitatively from the theoretical prediction for granular crystals. Therefore, disordered configurations with energy dissipation play a prominent role in sound properties of granular materials. Furthermore, we report how attenuation coefficients depend on the contact damping and quantify how they differ from the prediction of lattice theory. These improved relations, based on our numerical results, can in future be compared to advanced theories and experiments., Japan Society for the Promotion of Science, Inamori Research Grants, Information Center of Particle Technology, Deutsche Forschungsgemeinschaft (DFG)

The intensity, frequency, and duration of heatwaves are increasing worldwide. Still, heatwaves are systematically underreported and underresearched across the African continent. This study examines heatwaves across Mozambique, a country highly vulnerable to a variety of climate risks yet where heatwaves have received little to no attention. A spatio-temporal analysis was conducted for five heatwave characteristics (heatwave number, frequency, duration, amplitude, and magnitude) and corresponding trends from 1983 to 2016. This was done using the remotely sensed CHIRTS-daily, which presents one of the most accurate and highest resolution (5 × 5 km) daily temperature product currently available, especially for data-scarce regions. Three heatwave definitions were analyzed and compared, which are based on (1) the 90th percentile of daily maximum temperature (TX90), (2) the 90th percentile of daily minimum temperature (TN90), and (3) the Excess Heat Factor (EHF). Results were overlayed with high-resolution population data to obtain heatwave exposure and likely potential implications. Our findings show that Mozambique has experienced many heatwaves over the past decades. On average, 2–18.6 annual heatwave days (HWF) were recorded with the longest heatwaves (HWD) lasting X- 11.5 days. More and longer heatwaves were observed in the North and along the coast of Mozambique. Heatwave magnitude (HWM) ranged from 0.3 to 6.8 °C and amplitude (HWA) from 0.8 to 11.7 °C, with highest values in South and Central Mozambique. Heatwave events, days, and duration were found to be significantly increasing (p

In this editorial linked to the thematic issue on “Gaming, Simulations, and Planning: Physical and Digital Technologies for Public Participation in Urban Planning,” we explore how urban planning has been, arguably, slow on the uptake of modern technologies and the move towards the next media revolution: The Metaverse is now on the horizon. By artfully pushing technological, cultural, and social boundaries in creating virtual environments, games and gaming technologies have presented interesting opportunities and challenges for the planning profession, theory, and education over the years. This thematic issue documents a wide range of innovative practices in planning enabled by games and gaming technologies. It attempts to open discussions about the way we conceptualize and treat new media and technologies in planning. By providing a wide range of examples, from non-digital games to gamified systems, interactive simulations and digital games, the issue shows that the lack of adoption of these practices has less to do with their technical possibilities and more to do with the way we understand tools and their added value in the dominant narratives of planning. As we note at the end, planning should be at the forefront of these technologies, not embracing technologies for technologies sake but because it should, as a profession, be leading the way into these new environments.

In this paper, we investigate the spread of COVID-19 and the impact of government measures at the early stage of the pandemic (before the introduction of the vaccines) in the Netherlands. We build a multiple linear regression model to predict the effective reproduction rate using key factors and measures and integrate it with a system dynamics model to predict the spread and the impact of measures against COVID-19. Data from February to November 2020 is used to train the model and data until December 2020 is used to validate the model. We use data about the key factors, e.g., disease specific such as basic reproduction rate and incubation period, weather related factors such as temperature, and controllable factors such as testing capacity. We consider particularly the following measures taken by the government: wearing facemasks, event allowance, school closure, catering services closure, and self-quarantine. Studying the strategy of the Dutch government, we control these measures by following four main policies: doing nothing, mitigation, curbing, elimination. We develop a systems dynamic model to simulate the effect of policies. Based on our numerical experiments, we develop the following main insights: It is more effective to implement strict, sharp measures earlier but for a shorter duration than to introduce measures gradually for a longer duration. This way, we can prevent a quick rise in the number of infected cases but also to reduce the number of days under measures. Combining the measures with a high testing capacity and with effective self-quarantine can significantly reduce the spread of COVID-19.

BACKGROUND AND OBJECTIVES: A rise in prolonged grief disorder (PGD) levels was expected due to COVID-19 deaths. We tested this assumption, by comparing PGD-severity among people who experienced a death of a loved one during the pandemic caused by a natural (e.g., illness), COVID-19, or unnatural (e.g., accidents, suicides, homicides) loss on average 8 months earlier and in a subgroup of people bereaved ≥12 months earlier.DESIGN AND METHODS: Self-rated DSM-5-TR (acute) PGD levels (using the Traumatic Grief Inventory-Self Report plus) were compared among Dutch adults who experienced a natural ( N = 1036), COVID-19 ( N = 76), or unnatural loss ( N = 271) during the pandemic. Analyses of covariance were used. RESULTS: About two-thirds of the participants scored above the cut-off for (acute) probable PGD. Significantly higher acute PGD-severity was found in people after unnatural loss compared with COVID-19 ( B = -2.44 (SE=0.87), p = .005) or natural loss ( B = -1.78 (SE=0.45), pCONCLUSIONS: We found that acute PGD-severity was significantly higher following unnatural deaths than after COVID-19 deaths or natural causes, but no differences were found for people who experienced a loss ≥12 months earlier.

Given the dynamic nature of engineered vascular networks within biofabricated tissue analogues, it is instrumental to have control over the constantly evolving biochemical cues within synthetic matrices throughout tissue remodeling. Incorporation of pro-angiogenic vascular endothelial growth factor (VEGF165) specific aptamers into cell-instructive polymer networks is shown to be pivotal for spatiotemporally controlling the local bioactivity of VEGF that selectively elicit specific cell responses. To harness this effect and quantitatively unravel its spatial resolution, herein, bicomponent micropatterns consisting of VEGF165 specific aptamer-functionalized gelatin methacryloyl (GelMA) (aptamer regions) overlaid with pristine GelMA regions using visible-light photoinitiators (Ru/SPS) were fabricated via two-step photopatterning approach. For the 3D co-culture study, human umbilical vein-derived endothelial cells and mesenchymal stromal cells were used as model cell types. Bicomponent micropatterns with spatially defined spacings (300/500/800 μm) displayed high aptamer retention, aptamerfluorescent complementary sequence (CSF) molecular recognition and VEGF sequestration localized within patterned aptamer regions. Stiffness gradient at the interface of aptamer and GelMA regions was observed with high modulus in aptamer region followed by low stiffness GelMA regions. Leveraging aptamer-tethered VEGF's dynamic affinity interactions with CS that upon hybridization facilitates triggered VEGF release, co-culture studies revealed unique characteristics of aptamer-tethered VEGF to form spatially defined luminal vascular networks covered with filopodia-like structures in vitro (spatial control) and highlights their ability to control network properties including orientation over time using CS as an external trigger (temporal control). Moreover, the comparison of single and double exposed regions within micropatterns revealed differences in cell behavior among both regions. Specifically, the localized aptamer-tethered VEGF within single exposed aptamer regions exhibited higher cellular alignment within the micropatterns till d5 of culture. Taken together, this study highlights the potential of photopatterned aptamer-tethered VEGF to spatiotemporally regulate vascular morphogenesis as a tool for controlling vascular remodeling in situ.

Background eHealth technology can help patients with cardiovascular disease adopt and maintain a healthy lifestyle by supporting self-management and offering guidance, coaching, and tailored information. However, to support patients over time, eHealth needs to blend in with their needs, treatment, and daily lives. Just as needs can differ between patients, needs can change within patients over time. To better adapt technology features to patients’ needs, it is necessary to account for these changes in needs and contexts of use. Objective This study aimed to identify and monitor patients’ needs for support from a web-based health management platform and how these needs change over time. It aimed to answer the following research questions: “How do novice and more advanced users experience an online health management platform?” “What user expectations support or hinder the adoption of an online health management platform, from a user perspective?” and “How does actual usage relate to user experiences and adoption?” Methods A mixed methods design was adopted. The first method involved 2 rounds of usability testing, followed by interviews, with 10 patients at 0 months (round 1) and 12 patients at 6 months (round 2). In the second method, log data were collected to describe the actual platform use. Results After starting cardiac rehabilitation, the platform was used frequently. The patients mentioned that they need to have an incentive, set goals, self-monitor their health data, and feel empowered by the platform. However, soon after the rehabilitation program stopped, use of the platform declined or patients even quit because of the lack of continued tailored or personalized advice. The reward system motivated them to log data, but most participants indicated that being healthy should be the main focus, not receiving gifts. A web-based platform is flexible, accessible, and does not have any obligations; however, it should be implemented as an addition to regular care. Conclusions Although use of the platform declined in the longer term, patients quitting the technology did not directly indicate that the technology was not functioning well or that patients no longer focused on achieving their values. The key to success should not be user adherence to a platform but adherence to healthy lifestyle habits. Therefore, the implementation of eHealth should include the transition to a stage where patients might no longer need support from a technology platform to be independently and sustainably adherent to their healthy lifestyle habits. This emphasizes the importance of conducting multi-iterative evaluations to continuously monitor whether and how patients’ needs and contexts of use change over time. Future research should focus on how this transition can be identified and monitored and how these insights can inform the design and implementation of the technology.

Climate change is transforming the risks individuals and households face, with potentially profound socioeconomic consequences such as increased poverty, inequality, and social instability. Social protection is a policy tool that governments use to help individuals and households manage risks linked to income and livelihoods, and to achieve societal outcomes such as reducing poverty and inequality. Despite its potential as a policy response to climate change, the integration of social protection within the climate policy agenda is currently limited. While the concept of risk is key to both sectors, different understandings of the nature and scope of climate change impacts and their implications, as well as of the adequacy of social protection instruments to address them, contribute to the lack of policy and practice integration. Our goal is to bridge this cognitive gap by highlighting the potential of social protection as a policy response to climate change. Using a comprehensive climate risk lens, we first explore how climate change drives risks that are within the realm of social protection, and their implications, including likely future trends in demand for social protection. Based on this analysis, we critically review existing arguments for what social protection can do and evidence of what it currently does to manage risks arising from climate change. From the analysis, a set of reconceptualised roles emerge for social protection to strategically contribute to climate-resilient development.

Renewable energy communities (RECs) might be an interesting new stakeholder in stimulating home energy-saving efforts by tenants and homeowners due to their potential of raising awareness locally and gaining public support for low-carbon energy and energy-savings projects, because RECs are often locally sited, in close social proximity of residents, and are already part of local structures and share local institutions. This comes with many benefits since they already have a reputation locally, a social history with the local community, and can be trusted by the latter. This makes them potentially better suited than other—often less-trusted—parties (i.e., government and business companies) to use their agency to encourage sustainable change. The article builds on empirical data from the EU Horizon 2020 project REScoop Plus, using a mixed-methods research approach, including desk research, expert interviews, validation workshops, and multiple surveys among RECs in six EU member states about energy-saving actions implemented, and their effectiveness in terms of raising awareness, influencing the intention to save energy, and actual energy-saving behaviour. This article provides more insight into the assessment of actions and measures for coaching householders to achieve energy savings and low carbon goals. In addition, it shows the potential of using RECs as a new strategy to address home energy savings in the current housing stock, including options to improve the energy performance thereof.

Background The full potential of eHealth technologies to support self-management and disease management for patients with chronic diseases is not being reached. A possible explanation for these lacking results is that during the development process, insufficient attention is paid to the needs, wishes, and context of the prospective end users. To overcome such issues, the user-centered design practice of creating personas is widely accepted to ensure the fit between a technology and the target group or end users throughout all phases of development. Objective In this study, we integrate several approaches to persona development into the Persona Approach Twente to attain a more holistic and structured approach that aligns with the iterative process of eHealth development. Methods In 3 steps, a secondary analysis was carried out on different parts of the data set using the Partitioning Around Medoids clustering method. First, we used health-related electronic patient record data only. Second, we added person-related data that were gathered through interviews and questionnaires. Third, we added log data. Results In the first step, 2 clusters were found, with average silhouette widths of 0.12 and 0.27. In the second step, again 2 clusters were found, with average silhouette widths of 0.08 and 0.12. In the third step, 3 clusters were identified, with average silhouette widths of 0.09, 0.12, and 0.04. Conclusions The Persona Approach Twente is applicable for mixed types of data and allows alignment of this user-centered design method to the iterative approach of eHealth development. A variety of characteristics can be used that stretches beyond (standardized) medical and demographic measurements. Challenges lie in data quality and fitness for (quantitative) clustering.

Public spaces are considered a vital ingredient of prosperous cities as they support their sense of community, identity and culture. Understanding their relevance, the Mexican government has developed new regulatory frameworks. In 2016, the first federal legislation in Mexico was created and combined the concepts of urban development, public space, and social participation. This change affected national and local regulations. Acknowledging that public spaces are anchored to the institutional and governance context, we based our explorative research from a theoretical perspective on the Contextual Interaction Theory (CIT) and its five governance elements. Considering the regulatory and institutional framework for public spaces in Mexico, this research aims to understand how the different actors perceive the current conditions of public spaces in Mexico City. This research adopted a case study approach, and we conducted eight semi-structured interviews with stakeholders that participate in the planning process of public spaces in Mexico City. Through these interviews and revision of secondary sources, we found that all interviewed actors agree that the regulatory framework of public spaces differs with the application in practice, with legal gaps and lack of clarity in responsibilities which brings confusion among practitioners and developers of public space projects. The implementation of the public spaces policy is affected by the lack of continuity of public space projects and the discrepancies between the efforts to promote inclusive and safe public spaces, and a negative perception of society on the current conditions of public spaces.

A graph G is called Hamilton-connected if for every pair of distinct vertices {u, v} of G there exists a Hamilton path in G that connects u and v. A graph G is said to be t-tough if t ω(G - X)≤ |X| for all X ∩ V (G) with ω (G - X) > 1. The toughness of G, denoted τ (G), is the maximum value of t such that G is t-tough (taking τ (Kn) = ∞ for all n ≥ 1). It is known that a Hamilton-connected graph G has toughness τ (G) > 1, but that the reverse statement does not hold in general. In this paper, we investigate all possible forbidden subgraphs H such that every H-free graph G with τ (G) > 1 is Hamilton-connected. We find that the results are completely analogous to the Hamiltonian case: every graph H such that any 1-tough H-free graph is Hamiltonian also ensures that every H-free graph with toughness larger than one is Hamilton-connected. And similarly, there is no other forbidden subgraph having this property, except possibly for the graph K1 ? P4 itself. We leave this as an open case.

Lacustrine non‐skeletal carbonates exhibit a diversity of petrographies due to interactions between physico‐chemical and biologically influenced mechanisms. Despite the suggestion that evaporative concentration was involved in the formation of spherulite and shrubby‐bearing carbonate successions in the Pre‐Salt Cretaceous alkaline lakes of the South Atlantic, no consensus exists about the water chemistries promoting these exotic mineral textures. In this work, an experimental approach was developed to evaluate how changes in salinity (NaCl) and biopolymer concentrations (alginic acid) impact calcite growth dynamics from saline and alkaline synthetic solutions. Hydrochemical and petrographical data from selected modern saline/alkaline environments were compared with experimental datasets to further estimate how the underlying (bio)chemical conditions and lake locations probably converge to allow the formation of calcite spherulite grains in evaporitic settings. Spherulitic calcite from Recent saline lakes and experiments arise from waters with moderate to high [Calcium]/[Alkalinity] ratios ([Ca]/[Alk]) rather than in calcium‐depleted and alkaline‐rich environments which tend to produce single‐crystal calcites during abiotic water mixing or lake evaporation. This observation is consistent with the assembly of polycrystalline textures being a kinetically controlled feature, forced by remarkably high rates of nucleation. Also, the data analysed do not support a causative relationship between evaporite‐driven salinity fluctuations and the preferential formation of spherulites, shrubs or their intermediate textures. Ubiquitous in saline lakes, organic substances can lower the kinetic thresholds for spherulitic calcite aggregation while microbial photosynthesis can also raise pH, altogether enhancing calcite supersaturation and promoting spherulite formation in waters with moderate‐high [Ca]/[Alk] ratios and high salinities. Localised observations of abiotic spherulites in Recent soda lakes can occur in restricted mixing zones where [Ca]/[Alk] ratios are enhanced. This work highlights the roles of concentration regimes associated with biopolymers and microbial metabolism against the background salinity fluctuations in determining the morphological and textural transitions in lacustrine carbonate minerals.

More and more companies have implemented chatbots on their websites to provide support to their visitors on a 24/7 basis. The new customer wants to spend less and less time and therefore expects to reach a company anytime and anywhere, regardless of time, location, and channel. This study provides insight into the influence of chatbots on customer loyalty. System quality, service quality, and information quality are crucial dimensions that a chatbot must meet to give a good customer experience. To make a chatbot more personal, companies can alter the language style. Human-like chatbots lead to greater satisfaction and trust among customers, leading to greater adoption of the chatbot. The results of this study showed that a connection between chatbots and customer loyalty is very likely. Besides, some customers suffer from the privacy paradox because of personalization. Implications of this study are discussed.

Although the Convolutional Neural Network (CNN) has shown great potential for land cover classification, the frequently used single-scale convolution kernel limits the scope of information extraction. Therefore, we propose a Multi-Scale Fully Convolutional Network (MSFCN) with a multi-scale convolutional kernel as well as a Channel Attention Block (CAB) and a Global Pooling Module (GPM) in this paper to exploit discriminative representations from two-dimensional (2D) satellite images. Meanwhile, to explore the ability of the proposed MSFCN for spatio-temporal images, we expand our MSFCN to three-dimension using three-dimensional (3D) CNN, capable of harnessing each land cover category’s time series interaction from the reshaped spatio-temporal remote sensing images. To verify the effectiveness of the proposed MSFCN, we conduct experiments on two spatial datasets and two spatio-temporal datasets. The proposed MSFCN achieves 60.366% on the WHDLD dataset and 75.127% on the GID dataset in terms of mIoU index while the figures for two spatio-temporal datasets are 87.753% and 77.156%. Extensive comparative experiments and ablation studies demonstrate the effectiveness of the proposed MSFCN. Code will be available at https://github.com/lironui/MSFCN.

Smart textiles have extensively progressed in recent years and have expanded the potential scope and market of textiles, especially in areas of sensing, energy storage and heating. A great opportunity still exists to develop heaters based on natural fibre-based fabrics that are soft, light weight, and biodegradable. In this study, a simple, environmentally friendly, and scalable process to prepare highly conductive wool fabrics (CWFs) is reported. This multi-step process consists of stir coating and dip coating techniques using highly conductive ink based on graphene nanoplatelets (GNPs) and carbon black (CB) particles, followed by the cold-pressing process. Time-dependent temperature profiles and heat distribution analysis of the CWFs showed superior electrothermal performance to the heaters reported in the literature, reaching a surface temperature of more than 230 °C with a low applied voltage of 4.5 V (or an equivalent input power of ∼7.2 W). To demonstrate their potential application, the concept of a sandwich-structured and large size heating device was designed and the device was fabricated using a 3 × 3 array of CWFs.

Study region Akaki is a headwater catchment of Awash River Basin that hosts the capital city of Ethiopia, Addis Ababa. The area encompasses several agglomerated towns, water supply, and hydropower reservoirs and is characterized by a chain of mountains and floodplains. Due to basin rainfall, and the expansion of urbanized areas, the catchment is frequently affected by flooding. Study focus This study evaluates dynamic Bayesian Model Averaging (BMA) approach to improve rainfall estimation over the catchment by blending four high-resolution satellite rainfall estimate (SRE) products. Using daily data (2003–2019) observed at thirteen stations as a reference, seven statistical metrics served to assess the point and spatial scale accuracy of the rainfall estimates. New hydrological insights Main findings from this study are: (i) the blended product outperformed the individual SRE products by notably improving correlation with in-situ observed rainfall, and reducing the error of the estimated rainfall, (ii) the blended and individual SRE products performed better in the highlands than the lowlands of the catchment, and (iii) the amount of daily rainfall during the main-rainy season was mostly overestimated by the individual SRE products but was fairly estimated by the blended product. This study showed the nonexistence of surpassing individual SRE products and emphasized the blending of several products for gaining optimal results from each product.

The rheological and mechanical properties of elastomers are defined by their different networks: The crosslink network and the filler network. The crosslink network is influenced by the polymer structure. The filler network – particularly in case of silica as filler – depends on the interaction between the filler particles and the polymer. Liquid polymers can affect these networks by their lower molecular weight and with certain types by their functional groups. The goal of the present work is to gain a better understanding of the network formation: 1. During the sulfur curing of pure liquid polybutadienes with different concentrations of sulfur and curatives, and 2. Through differently added liquid polymer-silica-masterbatches in sulfur cured silica/SSBR mixtures. For the first point, the pre-cured liquid polymer samples were analyzed by gel permeation chromatography. The results indicate an association between weight concentration and the polymer chain length. For the second point, stress-strain analysis according to Mooney-Rivlin provides information about the interaction of liquid polymers with silica and the main polymer when it is added differently throughout the masterbatch approach.

Clinical judgement in primary care is more often decisive than in the hospital. Clinical decision rules (CDRs) can help general practitioners facilitating the work-through of differentials that follows an initial suspicion, resulting in a concrete ‘course of action’: a ‘rule-out’ without further testing, a need for further testing, or a specific treatment. However, in daily primary care, the use of CDRs is limited to only a few isolated rules. In this paper, we aimed to provide insight into the laborious path required to implement a viable CDR. At the same time, we noted that the limited use of CDRs in primary care cannot be explained by implementation barriers alone. Through the case study of the Oudega rule for the exclusion of deep vein thrombosis, we concluded that primary care CDRs come out best if they are tailor-made, taking into consideration the specific context of primary health care. Current CDRs should be evaluated frequently, and future decision rules should anticipate the latest developments such as the use of point-of-care (POC) tests. Hence, such new powerful diagnostic CDRs could improve and expand the possibilities for patient-oriented primary care.

We present a computational framework for two-scale asymptotic homogenization to determine the intrinsic magnetic permeability of composites. To this end, considering linear magnetostatics, both vector and scalar potential formulations are used. Our homogenization algorithm for solving the cell problem is based on the displacement method presented in Lukkassen et al. 1995, Composites Engineering, 5(5), 519-531. We propose the use of the meridional eccentricity of the permeability tensor ellipsoid as an anisotropy index quantifying the degree of directionality in the linear magnetic response. As application problems, 2D regular and random microstructures with overlapping and nonoverlapping monodisperse disks, all of which are periodic, are considered. We show that, for the vanishing corrector function, the derived effective magnetic permeability tensor gives the (lower) Reuss and (upper) Voigt bounds with the vector and scalar potential formulations, respectively. Our results with periodic boundary conditions show an excellent agreement with analytical solutions for regular composites, whereas, for random heterogeneous materials, their convergence with volume element size is fast. Predictions for material systems with monodisperse overlapping disks for a given inclusion volume fraction provide the highest magnetic permeability with the most increased inclusion interaction. In contrast, the disk arrangements in regular square lattices result in the lowest magnetic permeability and inadequate inclusion interaction. Such differences are beyond the reach of the isotropic effective medium theories, which use only the phase volume fraction and shape as mere statistical microstructural descriptors.

Purpose This paper aims to explore the overall research question “How can artificial intelligence (AI) influence consumer information disclosure?”. It considers how anthropomorphism of AI, personalisation and privacy concerns influence consumers’ attitudes and encourage disclosure of their private information. Design/methodology/approach This research draws upon the personalisation-privacy paradox (PPP) and privacy calculus theory (PCT) to address the research question and examine how AI can influence consumer information disclosure. It is proposed that anthropomorphism of AI and personalisation positively influence consumer attitudes and intentions to disclose personal information to a digital assistant, while privacy concerns negatively affect attitude and information disclosure. Findings This paper develops a conceptual model based on and presents seven research propositions (RPs) for future research. Originality/value Building upon PPP and PCT, this paper presents a view on the benefits and drawbacks of AI from a consumer perspective. This paper contributes to literature by critically reflecting upon on the question how consumer information disclosure is influenced by AI. In addition, seven RPs and future research areas are outlined in relation to privacy and consumer information disclosure in relation to AI.

This is a summary article of the SJPS thematic issue on participatory budgeting in the Central and Eastern European region. Its authors provide an overview of the diffusion of participatory budgeting, and they classify relevant countries in terms of the pace of this diffusion into four different groups: frontrunners, early majority, later majority, and lagging adopters. In addition, they uncover various diffusion mechanisms that have been used. Since the research articles included in this thematic issue unpack various factors that influence the diffusion of the innovative practice of participatory budgeting in the specific settings of Central and Eastern Europe, the main goal of this article is to sum up their crucial findings and formulate several conclusions, including a few avenues for further research. A clear majority of countries in the region have already collected a relevant amount of experience with the adoption and further use of participatory budgeting. An analysis of the individual experiences reveals that the position and characteristics of mayors, organizational resources, and available capacities, as well as the quality of public trust, are likely to be important factors that determine the adoption and use of participatory budgeting in the region.

Since thin-film silicon solar cells have limited optical absorption, we explore the effect of a nanostructured back reflector to recycle the unabsorbed light. As a back reflector we investigate a 3D photonic band gap crystal made from silicon that is readily integrated with the thin films. We numerically obtain the optical properties by solving the 3D time-harmonic Maxwell equations using the finite-element method, and model silicon with experimentally determined optical constants. The absorption enhancement relevant for photovoltaics is obtained by weighting the absorption spectra with the AM 1.5 standard solar spectrum. We study thin films either thicker ($L_{Si} = 2400$ nm) or much thinner ($L_{Si} = 80$ nm) than the wavelength of light. At $L_{Si} = 2400$ nm, the 3D photonic band gap crystal enhances the spectrally averaged ($\lambda = 680$ nm to $880$ nm) silicon absorption by $2.22$x (s-pol.) to $2.45$x (p-pol.), which exceeds the enhancement of a perfect metal back reflector ($1.47$ to $1.56$x). The absorption is enhanced by the (i) broadband angle and polarization-independent reflectivity in the 3D photonic band gap, and (ii) the excitation of many guided modes in the film by the crystal's surface diffraction leading to enhanced path lengths. At $L_{Si} = 80$ nm, the photonic crystal back reflector yields a striking average absorption enhancement of $9.15$x, much more than $0.83$x for a perfect metal, which is due to a remarkable guided mode confined within the combined thickness of the thin film and the photonic crystal's Bragg attenuation length. The broad bandwidth of the 3D photonic band gap leads to the back reflector's Bragg attenuation length being much shorter than the silicon absorption length. Consequently, light is confined inside the thin film and the absorption enhancements are not due to the additional thickness of the photonic crystal back reflector., Comment: 23 pages, 15 figures

Study region This research is carried out in the Kabompo Basin, a headwater catchment of the Zambezi Basin which has an area of 67,261 km2. Kabompo River originates in North-Western Province of Zambia between the Zambezi and Congo River Basins. Study focus This study focuses on error propagation of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center-MORPHing (CMORPH) rainfall product on simulated streamflow. Assessments are based on automated multi-objective calibration of the Representative Elementary Watershed (REW) model (2006–2012). Parameters of the model were optimized using the ɛ-NSGAII algorithm. Assessments on error propagation targeted streamflow modelling for hydrograph shape and volume, specific hydrograph characteristics, and water balance composition. New hydrological insights for the region By use of multiple objective functions, this study shows that uncorrected CMORPH results in substantial augmentation of rainfall error to streamflow simulation mismatch whereas bias corrected estimates result in attenuation of error. This study shows that analysis for water balance composition has great potential to improve application of satellite precipitation products in water management and decision making in the Zambezi basin. This study advises optimization of model parameters for each respective rainfall input data source so to identify outcomes and effects of respective rainfall data sources on the simulated water balance. Optimization of parameter sets by ɛ -NSGAII results in optimal parameter sets that attributes to findings on the water balance composition and closure.

We present an acousto-optic imaging system operating in reflection-mode and utilizing a pair of compact, triggerable lasers with 532 and 1064 nm wavelength and nanosecond pulse duration. The system maps the fluence rate distribution of light transmitted through optically scattering samples. The imaging is performed using an acousto-optic probe comprising an ultrasound linear array with attached optical fiber on one side and a camera on the other. The described hardware configuration images samples with access restricted to one side only and ensures mobility of the entire setup. The major challenge of the introduced approach is mitigating the effects of laser parameter instabilities and precise synchronization of ultrasound and laser pulses. We solved this issue by developing an electronic feedback circuit and a microcontroller-based synchronization and control system triggering the ultrasound scanner. Schematics and details regarding control algorithms are introduced. The imaging performance of the system is demonstrated on examples of results obtained for solid, acoustically-homogeneous and optically scattering phantoms with and without light absorbing inclusions present. Adjusting the size and location of the region of interest within the camera sensor matrix and the number of laser pulses illuminating every frame allows for significant improvements in terms of the achievable peak signal to noise ratio. We demonstrate that the developed synchronization algorithm and system play a crucial role in ensuring imaging quality and accuracy.

Visibility is a key factor influencing animal behavior in forest ecosystems. Fine-scale visibility in forested areas has been measured by ground-based approaches at the plot level, using site-specific methods that have limited spatial coverage. Here we examine airborne laser scanning (ALS) as a novel tool to quantify fine-scale visibility in the temperate forests of Germany at a landscape scale. We validate the (vertically-derived) ALS-derived visibility measures using proven (horizontally-derived) terrestrial laser scanning (TLS) estimates of true visibility. Our results indicate that there is a good agreement between the visibility resulting from ALS and TLS with an R2 ranging from 0.53 to 0.84 and a normalized RMSE varying from 15.92% to 11.81% at various plot sizes, with the highest accuracy achieved using a plot size of 35 × 35 m. Our study demonstrates for the first time that ALS can be successfully applied to quantify fine-scale visibility in temperate forests at a landscape level. This approach holds potential for studying the spatial behavior of animals (e.g., habitat selection and predator–prey relationships) in forest ecosystems.

Research interest This paper aims at a better understanding of the governance of the abandonment of socio-technical regimes through the example of the incandescent light bulb phase-out in the European Union and in the Netherlands as one specific case where the EU discontinuation policy has been implemented. In particular, with this paper we focus on the active and intended discontinuation of a socio-technical regime through dedicated governance. Methods We approached the phase-out of the incandescent light bulb from a qualitative perspective and analysed about 230 documents from the EU and Dutch level. The study has an explorative character, for we cannot claim to describe the entire policy process, but bring to surface some key issues in order to outline both governance foci and technicalities of governing the phase-out. We looked into how governance makers were actually structuring the ILB phase-out as a governance task. The specific framings we found were grouped into the (a) spectrum of governance dimensions, (b) the more detailed problem-types raised, and (c) the array of discontinuation issues addressed in policy discourse dedicated to negotiating, drafting and implementing the phase-out measures. Results A set of frames apparent in the discontinuation discourses in the EU and the Netherlands has been reconstructed, which entails the five governance dimensions ‘policy instruments’, ‘implementation’, ‘strictness’, ‘monitoring’, and ‘policy level’. Technical details of both the socio-technical products to be banned and the replacing products have been the subject of meticulous negotiations in order to be able to implement the big picture, the lightbulb ban, appropriately and appropriately for both industry and environmental associations. The design of discontinuation governance at national and EU level are closely intertwined, but not identical in all aspects. The complexity of the governance task is therefore high. Conclusions Discontinuation has to cope with some resistance to dedicated, forced change that takes place in a technically as well as socially highly complex context. Governing the phase-out of a technical device, a production infrastructure, and industry support policy once supposed to support the EU and Dutch ILB industry was a major techno-political challenge, where policymakers needed to grasp key technical and technological problems. These were related to ILBs as objects, to subjects such as engineers and scientists, lobbyists and disinterested experts, to civil society organisations and mass media, along with all sorts of political and administrative issues and discourses. The challenges are threefold: first, translating for each other what cannot be known from one’s own background, second, shutting down governance which so far fostered lighting industry and, third, helping to change parts of this industry from an old, incumbent one to a new, emerging socio-technical regime with a regime providing a political and regulatory framework for it.

Background The Life-Chart Method (LCM) is an effective self-management treatment option in bipolar disorder (BD). There is insufficient knowledge about the consumers’ needs and desires for an e-monitoring solution. The first step towards a new mood monitoring application is an extended inventory among consumers and professionals. Methods The aim of the current study was: to identify opinions about online mood monitoring of patients with BD and professionals and to identify preferences on design, technical features and options facilitating optimal use and implementation of online mood monitoring. This study used a qualitative design with focus-groups. Participants were recruited among patients and care providers. Three focus-groups were held with eight consumers and five professionals. Results The focus-group meetings reveal a shared consciousness of the importance of using the Life-Chart Method for online mood monitoring. There is a need for personalization, adjustability, a strict privacy concept, an adjustable graphic report, and a link to early intervention strategies in the design. Due to the fact that this is a qualitative study with a relative small number of participants, so it remains unclear whether the results are fully generalizable. We can’t rule out a selection bias. Conclusions This study demonstrates the importance of involving stakeholders in identifying a smartphone-based mood charting applications’ requirements. Personalization, adjustability, privacy, an adjustable graphic report, and a direct link to early intervention strategies are necessary requirements for a successful design. The results of this value specification are included in the follow-up of this project.

Functional safety is a key requirement in several application domains in which microprocessors are an essential part. A number of redundancy techniques have been developed with the common purpose of protecting circuits against single event upset (SEU) faults. In microprocessors, functional redundancy may be achieved through multi-core or simultaneous-multi-threading architectures, with techniques that are broadly classifiable as Double Modular Redundancy (DMR) and Triple Modular Redundancy (TMR), involving the duplication or triplication of architecture units, respectively. RISC-V plays an interesting role in this context for its inherent extendability and the availability of open-source microarchitecture designs. In this work, we present a novel way to exploit the advantages of both DMR and TMR techniques in an Interleaved-Multi-Threading (IMT) microprocessor architecture, leveraging its replicated threads for redundancy, and obtaining a system that can dynamically switch from DMR to TMR in the case of faults. We demonstrated the approach for a specific family of RISC-V cores, modifying the microarchitecture and proving its effectiveness with an extensive RTL fault-injection simulation campaign.

Our planet's ecosystems depend on the energy received from the sun to form a bubble of life. Technically, other sources of energy are converted from solar energy. An effective way to directly convert solar energy to electricity is through photovoltaic devices. They could be manufactured on small scales and used in pocket calculations up to large scales power plants. These power stations, known as a solar farm, is composed of grid-connected photovoltaic arrays. The conventional solar cells' efficiency, ceiled by the Shockley-Queisser limit, is in the range of 15%–25%. The rest of the solar energy is converted to heat which would have a detrimental influence on power production and the life span of photovoltaic devices. Hence, employing cooling systems to regulate their operative temperature is crucial. Passive cooling technologies without consuming additional power and with little maintenance cost could be a practical option. In this study, the extensive work of researchers applying passive cooling techniques is gathered and compared. Also, the study will shed light on finding an appropriate cooling technique concerning geographical or environmental conditions. Papers related to each specific passive method are discussed, and the challenges which have remained unsolved are noted. Finally, most of the papers with different environmental conditions are mentioned in an inventory which makes the comparison and evaluation easier. Among the six passive cooling methods, natural air ventilation is economically the most viable option. Hence, designing complex fin structures to help enhance air ventilation is recommended for most of the problems. In the case of water cooling, floatovoltaics are highly recommended because of supplementary advantages such as reducing the algae growth and evaporation rate.

Accessibility, livability, and public health in urban areas can be improved by promoting sustainable and eco-friendly modes of transport such as rail transit. The success and feasibility of a rail transit system, however, rely on maintaining sufficient ridership depending on several factors. This study focuses on two of these factors in examining the SunRail transit system: 1) the ridership dynamics in terms of passenger flows between transit stations, and 2) the socio-demographic characteristics of the population living around and travelling between these stations. The SunRail system is the flagship commuter rail line of Greater Orlando, Florida, encouraging denser and more walkable development and promoting a less car-dependent multimodal transportation system. For this purpose, we utilized an instantaneous-balance Bayesian model estimating the origin–destination passenger flows and conducted a comprehensive assessment of the characteristics of residents living within each SunRail station area. The analyses help provide a more detailed understanding of the travel dynamics of SunRail riders as well as who lives and works in all 12 SunRail station areas. Consequently, the findings and insights obtained from the analyses aim to serve urban and transport planners in devising strategies to influence ridership based on the passenger flows and unique characteristics of the station areas.

Introduction: Alcohol craving is a highly challenging obstacle to achieve long-term abstinence. Making alcohol use disorder patients timely aware of high-risk craving situations may protect them against relapse by prompting them to mobilize their coping resources. Current advances in wearable and smart-phone technology provide novel opportunities for the development of detecting these situations of heightened risk of craving, by enabling continuous tracking of fluctuations in psychological and physiological parameters. The present study therefore aims to determine the association between self-reported craving and relapses, and between heightened physiological activity. Specifically, we measured cardiovascular and electrodermal activity, and self-reported craving during one hundred days in the daily life of people trying to recover from alcoholism. The secondary aim is to study whether the association between physiology and craving can be strengthened by the inclusion of context related psychological parameters. Methods: An intensive repeated and continuous measures in naturalistic settings case-study design was employed. Ten participants were monitored with wearable bio-sensors and answered multiple questions every three hours on a smartphone app about craving, lapsing and multiple evidence based contextual variables. The association between physiology, craving and lapses was explored using Matthews correlation coefficients both with a current and 3 h lagged design. The contextual variables were included in a decision tree together with the physiological parameters to explore the added effect on the correlation of these contextual variables. Results: The association between lapses and craving was highly different across individuals, varying between a weak to a strong association. The association between cardiovascular activity and heightened self-reported craving was negligible to weak, however with a high specificity, meaning that most craving events were accompanied by increase heart rate. However, the association between electrodermal activity and craving was lower than with cardiovascular activity for most participants, both prior (lagged) and during craving. For two of the participants the association between physiology and craving improved by adding contextual variables, however, precision was too low. Conclusions: People differ strongly in their bodily reactions and psychological experiences during the first months of their addiction treatment. No individual in our study had unique one-to-one mappings between on the one hand physiological or psychological precursors, and on the other hand craving and (re)lapses. Therefore, detecting high risk craving situations with both physiological activity measured with wearables and psychological precursors to alert people specifically for an imminent (re)lapse, does not seem viable on the basis of the current results. We do see an added benefit of using physiology during treatment, as physiology can help start the conversation about possible high risk craving situations during that week. This would also help the counselor to gain added insights into the fluctuating states of the clients, and help to ameliorate the recall bias of clients. The present study showed the possibility and paved the way for future intensive longitudinal designs integrating both physiological, psychological and contextual factors during the challenging and lengthy recovery from addiction.

False start of the growing season (Fsos) is a component of the onset variability related to agronomic drought that adversely impact on agricultural production and productivity. In the sub-Saharan Africa (SSA) where agriculture heavily depends on rainfall, the Fsos tends to create confusion among farmers on when to start planting crops thereby affecting seed germination and normal growth after emergence. In this paper, we focus on the Fsos and the occurrence of dry spell especially before the Start of growing Season (SoS). We take advantage of the existing rainfall estimates (CHIRPS) and remotely sensed data for vegetation performance (NDVI) over the period 1999–2017 in combination with local knowledge derived from farmers to map out areas at risk of (i) dry spell at the SoS, and (ii) false timing of SoS or high probability of occurrence of the Fsos. We found that the North Eastern part of Uganda (8.8% of arable area) were at risk of dry spell throughout each year. However, the greater North (58.1% of arable area) was prone to dry spell during the onset of the March–May season. Areas in the South Western (3.7%) region were at risk during the onset of the September–November season. The probability that a location in Uganda experiences an Fsos falls between 0-53%. The findings in this study are vital for planning of predictive adaptation to the impacts of climate variability on agriculture amid struggle aimed at tackling food insecurity challenge in the SSA., False start of growing season; Precipitation variability; Agronomic drought.

Summary Disaster risk management (DRM) seeks to help societies prepare for, mitigate, or recover from the adverse impacts of disasters and climate change. Core to DRM are disaster risk models that rely heavily on geospatial data about the natural and built environments. Developers are increasingly turning to artificial intelligence (AI) to improve the quality of these models. Yet, there is still little understanding of how the extent of hidden geospatial biases affects disaster risk models and how accountability relationships are affected by these emerging actors and methods. In many cases, there is also a disconnect between the algorithm designers and the communities where the research is conducted or algorithms are implemented. This perspective highlights emerging concerns about the use of AI in DRM. We discuss potential concerns and illustrate what must be considered from a data science, ethical, and social perspective to ensure the responsible usage of AI in this field., The bigger picture Artificial Intelligence (AI) is increasingly being used in disaster risk management applications to predict the effect of upcoming disasters, plan for mitigation strategies, and determine who needs how much aid after a disaster strikes. The media is filled with unintended ethical concerns of AI algorithms, such as image recognition algorithms not recognizing persons of color or racist algorithmic predictions of whether offenders will recidivate. We know such unintended ethical consequences must play a role in DRM as well, yet there is surprisingly little research on exactly what the unintended consequences are and what we can do to mitigate them. The aim of this perspective is to call researchers working on fairness, accountability, and transparency to work with DRM and local experts—so we can ensure that disaster mitigation and relief is accountable, considers local values, and is not unintentionally biased., Disaster risk management increasingly relies on artificial intelligence algorithms to help societies mitigate and overcome the adverse impacts of disasters. Yet, there is little research on the ethical implications of using these algorithms. This perspective illustrates concerns voiced by DRM practitioners and highlights the need for research on how to adapt technical solutions for mitigating bias and define new accountability relations. Finally, we emphasize the need to include local experts in prioritizing ethical values.

Purpose We analysed incidence, treatment, survival, occurrence of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC) after lobular carcinoma in situ (LCIS) in the Netherlands. Methods All women diagnosed with classic LCIS between 1989 and 2017 were identified from the Netherlands Cancer Registry. We calculated overall (OS), relative survival (RS) and cumulative incidence functions (CIF, accounting for competing risks) of mortality, DCIS and IBC. For IBC, standardised incidence ratios (SIR) of IBC were calculated. Analyses were stratified for surgical treatment. Results We included 1890 patients. Median age was 51 years. Median follow-up was 8.5 years. In 1989–2017, LCIS incidence increased from 41 to 124, surgical treatment decreased from 100% to 41.1 % – mostly BCS. 10-year OS and 20-year RS exceeded 90 % in all subgroups. Overall, 48 (2.5 %) and 270 (14.3 %) patients were diagnosed with DCIS and IBC. IBCs were mostly early-stage. After mastectomy, 13 of 14 IBCs presented contralaterally. In the other groups, 64.8–70.9 % of IBCs presented ipsilaterally, 34.5–53.9 % of these were lobular. The SIR of ipsilateral IBC was highest after no surgery (6.9, 95%CI:4.9–9.4), lowest after mastectomy (0.2, 95%CI:0.4–0.8). Conclusion LCIS incidence increased, surgical treatment decreased. The low mortality risks support consideration of active surveillance. However, the increased IBC incidence suggests careful monitoring., Highlights • The incidence of LCIS increased, while surgical treatment decreased over time. • 10- and 20-year relative survival rates exceeded 90 %, irrespective of surgery. • The risk of breast cancer was highest after no surgery, lowest after mastectomy. • Subsequent breast cancers were generally of low stage. • Active surveillance for LCIS is advised, with the current follow-up five years.

In high-frequency bus services, maintaining the service regularity is a critical issue. The service regularity is directly related to the excessive waiting times (EWT) of passengers at bus stops. In a regular service, the EWT is minimized resulting in even headways between consecutive buses of the same line. In this study, we propose the combined use of rescheduling and bus holding to improve passengers' excessive waiting times. We model the dynamic rescheduling and bus holding problem as an integer nonlinear program (INLP) and we prove its NP-hardness. Our model considers the constraints of the original timetable – an issue that is usually neglected from most dynamic control methods. Given the NP-hardness of our mathematical program, we introduce a problem-specific heuristic to explore efficiently the solution space. The convergence rate of the proposed heuristic is tested against other solution methods, including simulated annealing with linear cooling, hill climbing and branch and bound with multi-start sequential quadratic programming. In addition, simulations with the use of actual operational data from a major bus operator in Asia Pacific demonstrate an up to 35% potential EWT improvement for a minor increase of 6% to the travel times of onboard passengers.

The current study examines the role of social ties in performing kind acts to enhance university students’ wellbeing. Due to facing multifaceted challenges, university students form a group that is particularly vulnerable in terms of their mental health. Interventions harnessing prosocial behaviour have the potential to increase students’ wellbeing, strengthen personal competencies, and broaden social networks. The first aim of the trial (N = 222) was to explore whether a 4-week acts-of-kindness intervention targeting either (1) strong social ties, (2) weak social ties or (3) unspecified receivers (treatment-as-usual) differ in their impact on students’ mental wellbeing, positive relations, depressive symptoms, anxiety, and perceived stress. The second aim was to examine whether kindness for strong versus weak social ties have different underlying working mechanisms (i.e., positive emotions versus self-esteem) and who benefits most from these instructions (i.e., those with high or low levels of self-esteem and positive relations). Results demonstrated that the most significant improvements in mental wellbeing were found in the kindness for strong social ties condition compared to the other conditions. No mediation effects of positive emotions and self-esteem were found. Moderation analyses revealed that participants who performed kind acts for weak social ties reported significantly less positive effects on mental wellbeing, but only when their levels of self-esteem at baseline were medium or high. Independent of group allocation, participants’ mental wellbeing increased throughout the intervention, but so did the experience of depressive symptoms, anxiety, and perceived stress. More research is needed to examine the timing of kindness interventions and investigate how they can improve mental wellbeing and psychological distress in acute phases of academic stress in university students.

Pancreatic cancer is one of the most malignant tumors with one of the worst survival rates due to its insidious onset and resistance to therapies. Most therapeutics show a desired anticancer effect in vitro; however, very poor efficacy in vivo because of the limited drug delivery and penetration into pancreatic tumors attributed to the abundance of the tumor stroma, ie, the fibrotic tumor microenvironment surrounding the cancer cells. For a better understanding of the challenges posed by the pancreatic tumor stroma, we outline the key features of the tumor microenvironment. Then we highlight major strategies used to tackle the challenges to improve drug penetration into the tumor and achieve enhanced efficacy (pre)clinically. Furthermore, we describe nanomedicine strategies to modulate the tumor stroma, degrade the extracellular matrix, and co-deliver multi-functional drugs, to improve the chemotherapeutics delivery and penetration into pancreatic tumors.

Summary Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution, and data analysis. Therefore, we benchmarked the robustness of MEA-derived neuronal activity patterns from ten healthy individual control lines, and uncover comparable network phenotypes. To achieve standardization, we provide recommendations on experimental design and analysis. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field toward the use of MEAs for disease phenotyping and drug discovery., Highlights • MEAs are a robust tool to model neuronal network functioning • Neuronal networks from different healthy donors show comparable network activity • MEAs are able to distinguish disease-specific neuronal network phenotypes • We provide recommendations to standardize neuronal network recordings on MEA, In this article, Mossink and colleagues demonstrate that micro-electrode arrays (MEAs) are a highly robust tool to uncover genotype/phenotype interactions in hiPSC-derived excitatory neuronal networks, and provide an important resource for the design, execution, and analysis of hiPSC-derived neuronal networks studies on MEA.

Open quantum systems can be systematically controlled by making changes to their environment. A well-known example is the spontaneous radiative decay of an electronically excited emitter, such as an atom or a molecule, which is significantly influenced by the feedback from the emitter’s environment, for example, by the presence of reflecting surfaces. A prerequisite for a deliberate control of an open quantum system is to reveal the physical mechanisms that determine its state. Here, we investigate the Bose-Einstein condensation of a photonic Bose gas in an environment with controlled dissipation and feedback. Our measurements offer a highly systematic picture of Bose-Einstein condensation under non-equilibrium conditions. We show that by adjusting their frequency Bose-Einstein condensates naturally try to avoid particle loss and destructive interference in their environment. In this way our experiments reveal physical mechanisms involved in the formation of a Bose-Einstein condensate, which typically remain hidden when the system is close to thermal equilibrium., Non-equilibrium Bose-Einstein condensates exist in different systems like polaritons, photons. Here the authors demonstrate photonic BECs in an excited or a non-equilibrium state and explore the flow of the photons coupled to the interferometer in order to minimize the loss.

Fluid flow shear stresses are strong regulators for directing the organization of vascular networks. Knowledge of structural and flow dynamics information within complex vasculature is essential for tuning the vascular organization within engineered tissues, by manipulating flows. However, reported investigations of vascular organization and their associated flow dynamics within complex vasculature over time are limited, due to limitations in the available physiological pre-clinical models, and the optical inaccessibility and aseptic nature of these models. Here, we developed laser speckle contrast imaging (LSCI) and side-stream dark field microscopy (SDF) systems to map the vascular organization, spatio-temporal blood flow fluctuations as well as erythrocytes movements within individual blood vessels of developing chick embryo, cultured within an artificial eggshell system. By combining imaging data and computational simulations, we estimated fluid flow shear stresses within multiscale vasculature of varying complexity. Furthermore, we demonstrated the LSCI compatibility with bioengineered perfusable muscle tissue constructs, fabricated via molding techniques. The presented application of LSCI and SDF on perfusable tissues enables us to study the flow perfusion effects in a non-invasive fashion. The gained knowledge can help to use fluid perfusion in order to tune and control multiscale vascular organization within engineered tissues.