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Abstract Background There is a significant demand for intermediate-scale bioreactors in academic and industrial institutions to produce cells for various applications in drug screening and/or cell therapy. However, the application of these bioreactors in cultivating hiPSC-derived immune cells and other blood cells is noticeably lacking. To address this gap, we have developed a xeno-free and chemically defined intermediate-scale bioreactor platform, which allows for the generation of standardized human iPSC-derived hematopoietic organoids and subsequent continuous production of macrophages (iPSC-Mac). Methods We describe a novel method for intermediate-scale immune cell manufacturing, specifically the continuous production of functionally and phenotypically relevant macrophages that are harvested on weekly basis for multiple weeks. Results The continuous production of standardized human iPSC-derived macrophages (iPSC-Mac) from 3D hematopoietic organoids also termed hemanoids, is demonstrated. The hemanoids exhibit successive stage-specific embryonic development, recapitulating embryonic hematopoiesis. iPSC-Mac were efficiently and continuously produced from three different iPSC lines and exhibited a consistent and reproducible phenotype, as well as classical functionality and the ability to adapt towards pro- and anti-inflammatory activation stages. Single-cell transcriptomic analysis revealed high macrophage purity. Additionally, we show the ability to use the produced iPSC-Mac as a model for testing immunomodulatory drugs, exemplified by dexamethasone. Conclusions The novel method demonstrates an easy-to-use intermediate-scale bioreactor platform that produces prime macrophages from human iPSCs. These macrophages are functionally active and require no downstream maturation steps, rendering them highly desirable for both therapeutic and non-therapeutic applications.

Background: There is a significant demand for intermediate-scale bioreactors in academic and industrial institutions to produce cells for various applications in drug screening and/or cell therapy. However, the application of these bioreactors in cultivating hiPSC-derived immune cells and other blood cells is noticeably lacking. To address this gap, we have developed a xeno-free and chemically defined intermediate-scale bioreactor platform, which allows for the generation of standardized human iPSC-derived hematopoietic organoids and subsequent continuous production of macrophages (iPSC-Mac). Methods: We describe a novel method for intermediate-scale immune cell manufacturing, specifically the continuous production of functionally and phenotypically relevant macrophages that are harvested on weekly basis for multiple weeks. Results: The continuous production of standardized human iPSC-derived macrophages (iPSC-Mac) from 3D hematopoietic organoids also termed hemanoids, is demonstrated. The hemanoids exhibit successive stage-specific embryonic development, recapitulating embryonic hematopoiesis. iPSC-Mac were efficiently and continuously produced from three different iPSC lines and exhibited a consistent and reproducible phenotype, as well as classical functionality and the ability to adapt towards pro- and anti-inflammatory activation stages. Single-cell transcriptomic analysis revealed high macrophage purity. Additionally, we show the ability to use the produced iPSC-Mac as a model for testing immunomodulatory drugs, exemplified by dexamethasone. Conclusions: The novel method demonstrates an easy-to-use intermediate-scale bioreactor platform that produces prime macrophages from human iPSCs. These macrophages are functionally active and require no downstream maturation steps, rendering them highly desirable for both therapeutic and non-therapeutic applications. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) are nanometric size, a cell-derived drug delivery carrier composed of membranebound structures, release into the cellular medium and found in body fluids. EVs serve a dual purpose, acting as a means of disposing of redundant material and a method of communication between cells. Their natural origin, biocompatibility, protein, and nucleic acid composition boosts superior targeting capabilities. While strong safety profile, intrinsic pleiotropic therapeutic effects, ability to accommodate both lipophilic and hydrophilic agents, and pass through blood-brain barrier makes them exceptional nanocarrier. Several synthetic drug delivery methods have been fabricated and introduced to the market throughout the previous few decades. However, their inefficiency, cytotoxicity, and/or immunogenicity hinder their applications. Evidence demonstrates that EVs play a critical role in major physiological and pathological processes, such as cellular homeostasis, infection propagation, cancer progression, and cardiovascular diseases. Moreover, EVs offer a range of advantages over traditional synthetic carriers, thus paving the way for innovative drug delivery approaches. Although therapeutic applications as carrier is limited due to lack of scalable isolation techniques and efficient drug loading, EVs serve great potential as nanocarriers. The review summarizes and discuss recent progress and challenges associated with development of EVs as nanocarrier. [ABSTRACT FROM AUTHOR]

Abstract Side streams from the milling industry offer excellent nutritional properties for animal feed; yet their use is constrained by the elevated phosphorus (P) content, mainly in the form of phytate. Biotechnological P recovery fosters sustainable P management, transforming these streams into P-depleted animal feed through enzymatic hydrolysis. The enzymatic P mobilization not only enables P recovery from milling by-products but also supports the valorization of these streams into P-depleted animal feeds. Our study presents the scalability and applicability of the process and characterizes the resulting P-depleted rye bran as animal feed component. Batch mode investigations were conducted to mobilize P from 100 g to 37.1 kg of rye bran using bioreactors up to 400 L. P reductions of 89% to 92% (reducing from 12.7 gP/kg to 1.41–1.28 gP/kg) were achieved. In addition, High Performance Ion Chromatography (HPIC) analysis showed complete depletion of phytate. The successful recovery of the enzymatically mobilized P from the process wastewater by precipitation as struvite and calcium hydrogen phosphate is presented as well, achieving up to 99% removal efficiency. Our study demonstrates a versatile process that is easily adaptable, allowing for a seamless implementation on a larger scale. Graphical Abstract

Side streams from the milling industry offer excellent nutritional properties for animal feed; yet their use is constrained by the elevated phosphorus (P) content, mainly in the form of phytate. Biotechnological P recovery fosters sustainable P management, transforming these streams into P-depleted animal feed through enzymatic hydrolysis. The enzymatic P mobilization not only enables P recovery from milling by-products but also supports the valorization of these streams into P-depleted animal feeds. Our study presents the scalability and applicability of the process and characterizes the resulting P-depleted rye bran as animal feed component. Batch mode investigations were conducted to mobilize P from 100 g to 37.1 kg of rye bran using bioreactors up to 400 L. P reductions of 89% to 92% (reducing from 12.7 gP/kg to 1.41–1.28 gP/kg) were achieved. In addition, High Performance Ion Chromatography (HPIC) analysis showed complete depletion of phytate. The successful recovery of the enzymatically mobilized P from the process wastewater by precipitation as struvite and calcium hydrogen phosphate is presented as well, achieving up to 99% removal efficiency. Our study demonstrates a versatile process that is easily adaptable, allowing for a seamless implementation on a larger scale. [ABSTRACT FROM AUTHOR]

A sol-gel process for the synthesis of a multi-component oxide material from the system SiO2-ZrO2-Al2O3underwent optimization and up-scaling. Initially, on a laboratory scale, components including precursors, catalysts, and additives were methodically evaluated to ensure a safe and efficient transition to larger volumes. Subsequently, the equipment for the whole setup of the sol-gel process was strategically selected. Leveraging insights from these optimizations, the process was successfully scaled-up to pilot-scale operation, conducting hydrolysis, condensation reactions, gelation, aging, and drying within a single, integrated conical dryer system for an 80 L batch. A visual test and FTIR spectroscopy were applied for process control and monitoring.

The FeAl intermetallic compound is of great interest for industry due to its low density, low cost and high mechanical and corrosion resistance, so it can replace stainless steels and nickel-based alloys for some applications. In previous publications, the concept (principle) test for a novel FeAl powder manufacturing process has been shown. It consists mainly of the following stages: (a) metallic strip manufacture through rapid solidification, (b) water vapor exposure of these metallic strips for their disintegration and powder generation and (c) powder drying. Experimental tests were performed for 2 g of the FeAl intermetallic compound. However, this process can be extended to manufacture any other intermetallic compound containing aluminum, such as TiAl, NiAl, CoAl or any other that can be obtained from every element that can combine with aluminum, if the aluminum content is between 55 and 60 at.%. Nowadays, this process is at technology readiness level (TRL) 3. Therefore, in this paper, a process equipment up-scaling configuration for producing up to 15 kg powder is proposed. This manufacturing process is an industrial alternative to those commonly used to produce powders of this type of intermetallic compounds, such as mechanical alloying (MA). Moreover, several alternatives for employing renewable energy sources are given, making it even more environmentally sustainable.

Italy, as other European countries, saw a dramatic increase in international protection claims, heavily impacting the workload of Italian lower courts entitled to re-examine refusal decisions on asylum. The Court of Catania, in Sicily, was the most affected by this situation due to its geographical position, so that in 2016 it registered an increase of 514% in its new proceedings related to international protection. This surge in asylum claims affected the proper functioning of the judiciary and the whole asylum policy, as claims remained unsolved for a long time. In order to face these challenges, from 2015 to 2017 the project Migrantes, funded by the European Social Fund, was developed in the Court of Catania with the aim to better organise and speed up judicial procedures concerning asylum claims, the first and crucial stage of the refugee's integration process. The present article offers an analysis of the project through the lens of the Social Innovation framework, adopting a multi-scalar perspective. In particular, it shows the innovative solutions adopted by the local court, the opportunity structures existing at local, regional, national and EU levels. Moreover, it focuses on the consolidation process that followed up-scaling dynamics and on the factors facilitating it. [ABSTRACT FROM AUTHOR]

The FeAl intermetallic compound is of great interest for industry due to its low density, low cost and high mechanical and corrosion resistance, so it can replace stainless steels and nickel-based alloys for some applications. In previous publications, the concept (principle) test for a novel FeAl powder manufacturing process has been shown. It consists mainly of the following stages: (a) metallic strip manufacture through rapid solidification, (b) water vapor exposure of these metallic strips for their disintegration and powder generation and (c) powder drying. Experimental tests were performed for 2 g of the FeAl intermetallic compound. However, this process can be extended to manufacture any other intermetallic compound containing aluminum, such as TiAl, NiAl, CoAl or any other that can be obtained from every element that can combine with aluminum, if the aluminum content is between 55 and 60 at.%. Nowadays, this process is at technology readiness level (TRL) 3. Therefore, in this paper, a process equipment up-scaling configuration for producing up to 15 kg powder is proposed. This manufacturing process is an industrial alternative to those commonly used to produce powders of this type of intermetallic compounds, such as mechanical alloying (MA). Moreover, several alternatives for employing renewable energy sources are given, making it even more environmentally sustainable. [ABSTRACT FROM AUTHOR]

A 1.03‐inch 2560x2560 low power OLEDoS backplane with a proposed in‐pixel up‐scaling technique is designed and implemented. Due to the proposed technique based on interpolated pixel scheme, the pixel density of the backplane realizes 3514 PPI (Pixels per Inch) with lower power consumption. The backplane has 1280x1280 input video resolution and output video resolution is upscaled to 2560x2560 without additional up‐scaler. A measured power consumption per 1 mega pixel without OLED frontplane is 16.3mW which is less than our previous 0.7‐inch 1920x1080 OLEDoS backplane with the same semiconductor fabrication process. [ABSTRACT FROM AUTHOR]

Smooth perovskite film with high crystallinity and vertical orientation is highly favored for high‐performance quasi‐2D perovskite solar cells (PVSCs), yet limited by the critical balance between nucleation and crystal growth. To address this issue, here a fast solidification and slow growth (FSSG) strategy is developed to effectively optimize the film morphology. The fast solidification enables a smooth, pinhole‐free film, while slow growth allows it to further ripen into high‐crystallinity film. This process is enabled by the low‐boiling point solvent system, that is, acetonitrile, with high‐boiling point additives, that is, NH4SCN and CH3NH3Cl. Compared to the traditional method, uniform film with a larger grain/crystallite size as well as better crystallinity can be easily fabricated through this FSSG strategy. As a result, the quasi‐2D PVSCs based on (GA)2(MA)4Pb5I16 processed with the FSSG strategy show a champion power conversion efficiency of 20.44%, as well as 19.08% for large‐area (1 cm2) devices, which suggest the capability of the FSSG strategy for up‐scaled PVSC fabrication. Therefore, this work opens a new avenue toward morphology control of PVSCs for practical applications. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to introduce flexible dye-sensitized solar cells (FDSSCs). Design/methodology/approach: In the third generation solar cells, glass was used as a substrate, which due to its high weight and fragility, was not possible to produce continuously. However, in flexible solar cells, flexible substrates are used as new technology. The most important thing may choose a suitable substrate to produce a photovoltaic (PV) device with optimal efficiency. Findings: Conductive plastics or metallic foils are the two main candidates for glass replacement, each with its advantages and disadvantages. As some high-temperature methods are used to prepare solar cells, metal substrates can be used to prepare PV devices without any problems. In contrast to the advantage of high thermal resistance in metals, metal substrates are dark and do not transmit enough light. In other words, metal substrates have a high loss of photon energy. Like all technologies, PV devices with polymer substrates have technical disadvantages. Practical implications: In this study, the development of FDSSCs offers improved photovoltaic properties. Social implications: The most important challenge is the poor thermal stability of polymers compared to glass and metal, which requires special methods to prepare polymer solar cells. The second important point is choosing the suitable components and materials for this purpose. Originality/value: Dependence of efficiency and performance of the device on the angle of sunlight, high-cost preparation devices components, limitations of functional materials such as organic-mineral sensitizers, lack of close connection between practical achievements and theoretical results and complicated fabrication process and high weight. [ABSTRACT FROM AUTHOR]

The characterisation of fuel distribution across heterogeneous landscapes is important for wildfire mitigation, validating fuel models, and evaluating fuel treatment outcomes. However, efficient fuel mapping at a landscape scale is challenging. Fuel hazard metrics were obtained using Terrestrial Laser Scanning (TLS) and the current operational approach (visual fuel assessment) for seven sites across south-eastern Australia. These point-based metrics were then up-scaled to a continuous fuel map, an area relevant to fire management using random forest modelling, with predictor variables derived from Airborne Laser Scanning (ALS), Sentinel 2A images, and climate and soil data. The model trained and validated with TLS observations (R 2 = 0.51 for near-surface fuel cover and 0.31 for elevated fuel cover) was found to have higher predictive power than the model trained with visual fuel assessments (R 2 = −0.1 for the cover of both fuel layers). Models for height derived from TLS observations exhibited low-to-moderate performance for the near-surface (R 2 = 0.23) and canopy layers (R 2 = 0.25). The results from this study provide practical guidance for the selection of training data sources and can be utilised by fire managers to accurately generate fuel maps across an area relevant to operational fire management decisions. [ABSTRACT FROM AUTHOR]

Soil moisture is central to local climate on land. In situ soil moisture observations are vital for observing vegetation‐relevant root‐zone soil moisture. However, stations included in the International Soil Moisture Network are sparse in regions with strong land‐atmosphere coupling. We apply a machine‐learning‐based procedure for informing future station placement using virtual soil moisture stations in future CMIP6 projections. Stations are placed where the climate is currently most under‐represented. This strategy outperforms random station placement and station placement according to geographical distance. Doubling the current number of stations using this method alleviates the uneven global distribution of stations, increases the skill in the estimation of inter‐annual variability and trends in dry‐season soil moisture, and reduces its differences across climates in future projections. Stations are predominantly placed in tropical climates, especially when optimizing for drying trends. The results can inform future station placement to support climate change mitigation efforts. Plain Language Summary: Water stored in the ground as soil moisture is the main water supply for ecosystems and can influence local weather. Ground observations of soil moisture can measure water in deeper soil layers that roots can access. Many stations are collected in the International Soil Moisture Network database. However, this database mainly contains observation stations from the US and Europe. If we were to put additional stations, we should focus on regions and climates that the current network does not sufficiently cover. Locations in model projections of future climate that currently contain a station ("virtual stations") are used to build a machine‐learning model that predicts soil moisture at locations without stations. We then place new virtual stations where the prediction error of dry‐season soil moisture variability and dry‐season trends is largest. This strategy outperforms randomly placing new stations or placing stations where they are most distant from existing ones. Stations are placed predominantly in the tropics, but prediction improves in all regions. Furthermore, stations are more evenly distributed across the globe, and differences in skill between regions become smaller. This tool can be used to decide where to place future soil moisture stations, which are important for monitoring climate change. Key Points: In situ soil moisture observations are distributed unequally across the globe and sparse in regions with strong land‐atmosphere couplingWe present a machine‐learning based procedure for informing future station placement using virtual soil moisture stationsDoubling the number of stations with this strategy reduces error in soil moisture trends by 0.2–1.4 kg m−2 and reduces global differences [ABSTRACT FROM AUTHOR]

[Display omitted] • Lab-scale LCA reveals energy use of pyrolysis as hotspot in hard carbon supply chain. • Emission and waste treatment is key to enhance industrial hard carbon sustainability. • Upscaling establishes a predictive benchmark for hard carbon from lab to industry. • Upscaling LCA of the hard carbon outlines its potential as a green anode. This paper aims to address research gaps surrounding the environmental impact of Hard Carbon (HC) production by conducting a Life Cycle Assessment (LCA) based on data from two laboratories with differing backgrounds and scenarios. HC is commonly used as anode material for sodium-ion batteries, a potentially sustainable and cost-efficient alternative for lithium-ion batteries. The study identifies environmentally sustainable routes for HC synthesis by comparing various biomass and synthesis pathways. The study reveals that the energy consumption of the pyrolysis process is the primary contributor to the environmental footprint of lab-scale HC production. A prospective LCA is performed by upscaling the laboratory processes to pilot- and industrial scale based on expert judgement and assumptions on energy and material balance. The results show that the environmental profile of HC can be significantly improved when the production scale is expanded. At large production scales, HC shows great potential to be used as a counterpart to graphite in future battery systems. However, direct emissions, such as methane, and the depletion of materials, such as argon and acid, become more critical to the environmental footprint, highlighting the need for energy recovery, emission treatment strategies, and more efficient use of materials. This work provides a framework for future LCA studies of HC, highlighting the limitations of simplified upscaling. It also provides a foundation for developing sustainable energy storage systems, thereby contributing to more informed decision-making in HC industrial production. [ABSTRACT FROM AUTHOR]

Abstract Soil moisture is central to local climate on land. In situ soil moisture observations are vital for observing vegetation‐relevant root‐zone soil moisture. However, stations included in the International Soil Moisture Network are sparse in regions with strong land‐atmosphere coupling. We apply a machine‐learning‐based procedure for informing future station placement using virtual soil moisture stations in future CMIP6 projections. Stations are placed where the climate is currently most under‐represented. This strategy outperforms random station placement and station placement according to geographical distance. Doubling the current number of stations using this method alleviates the uneven global distribution of stations, increases the skill in the estimation of inter‐annual variability and trends in dry‐season soil moisture, and reduces its differences across climates in future projections. Stations are predominantly placed in tropical climates, especially when optimizing for drying trends. The results can inform future station placement to support climate change mitigation efforts.

One approach to improve the sustainability of food processing is the recovery of valuable compounds from food industry’s side streams. In this study a life cycle assessment (LCA) was used to quantify the potential environmental impacts of cross-processing herring side streams with different antioxidant-rich biomasses, so-called helpers, for the extraction of a protein ingredient that is stable against lipid oxidation. New primary experimental data was combined with literature values to model cross-processing of herring with different helpers, namely, lingonberry pomace, apple pomace, and brown and green seaweed. Different addition ratios and delayed addition of the pomace were also assessed for cross-processing herring with lingonberry pomace. The environmental performance of the resulting protein ingredients were assessed on a mass and delivered protein basis. Potential environmental impacts for climate change, energy consumption, land occupation, and depletion of marine resources were addressed. No ingredient performed better in all environmental impact categories, but delaying the helper addition had the most significant influence in reducing the product’s environmental impacts. This study’s outcomes enable analysts to direct research towards the most relevant parameters for producing a protein ingredient with lower environmental impact.

Vegetation phenology reflects the temporal dynamics of vegetation growth and is an important indicator of climate change. However, differences consistently exist in land surface phenology derived at different spatial scales, which hinders the understanding of phenological events and integration of land surface phenology products from different scales. The Qinling Mountains are a climatic and geographical transitional region in China. To better understand the spatial scale effect issues of land surface phenology in mountainous ecosystems, this study up-scaled vegetation start of season (SOS) and end of season (EOS) in the Qinling Mountains derived from three different Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) products to four scales (i.e., 2 km × 2 km, 4 km × 4 km, 6 km × 6 km, and 8 km × 8 km) using the spatial averaging method. Then, similarities and differences between the up-scaled SOSs/EOSs were examined using the simple linear regression, cumulative distribution function, and absolute difference. Finally, the random forest model was used to reveal the major factors influencing the spatial scale effect of land surface phenology in Qinling Mountains. Results showed that the derived basic SOS/EOS datasets using the same filtering method from the 250 m and 500 m NDVI datasets were consistent in spatial distribution, while the results from the 1000 m NDVI dataset differed. For both the basic and the up-scaled datasets, the land surface phenology derived from the Savitzky-Golay-filtered NDVI showed an advance in SOS, but a delay in EOS, compared to those derived from the asymmetric Gaussian- and double logistic-filtered NDVI. The up-scaled SOS was greatly impacted by both NDVI resolution and the filtering methods. On the other hand, EOS was mostly impacted by the filtering methods. Moreover, up-scaled SOSs usually had larger differences compared to up-scaled EOSs. While different filtering methods sometimes amplified the absolute differences between different SOS/EOS across scales, the upscaling reduced the differences. Influence factor analysis showed that spatial variations observed in SOS in Qinling Mountains were mainly caused by forest cover, uneven distribution of spring precipitation, and annual precipitation, while spatial variations in aspect, winter temperature, and autumn precipitation all strongly influenced the observed EOS across scales in the study area. These findings enhance our understanding of the effects of observational scale on vegetation phenology in mountain ecosystems and provide a reference for phenology modeling in mountainous areas. [ABSTRACT FROM AUTHOR]

For a low-permeability carbonate formation, the acid fracture process is simulated through coupling a commercial acid fracture simulator (GOHFER) to a finite volume reservoir simulator (IMEX). Unlike LGR (Local grid refinement) approach that suffers from severe convergence problems, a dynamic up-scaling procedure is employed to convert the discrete fracture network (DFN) model into a dual continuum model for our simulation. In this paper, multiple simulations are used to optimize the acid fracture schedule parameters, such as fluid volume, flow rate, perforation location, number of injection steps, and acid type, in order to maximize the effective fracture length. For four points perforation as the relevant operation case in this work, acid fracturing consumes 44 Mgal acid volume at a rate of 25 bpm at a 20 ft interval, resulting in a 3.5-fold increase in well productivity index (PI). Based on experimental relative permeability data, two models of fine and medium grid sizes are employed to be compared with the LGR method. The results have shown that these models are 22 and 54 times faster than LGR, however, the latter has a deviation of less than 5% which is quite acceptable. [ABSTRACT FROM AUTHOR]

To reduce the global emissions of CO 2 , the aviation industry largely relies on new light weight materials, which require multifunctional coatings. Graphene and its derivatives are particularly promising for combining light weight applications with functional coatings. Although they have proven to have outstanding properties, graphene and its precursor graphene oxide (GO) remain far from application at the industrial scale since a comprehensive protocol for mass production is still lacking. In this work, we develop and systematically describe a sustainable up-scaling process for the production of GO based on a three-step electrochemical exfoliation method. Surface characterization techniques (XRD, XPS and Raman) allow the understanding of the fast exfoliation rates obtained, and of high conductivities that are up to four orders of magnitude higher compared to GO produced via the commonly used modified Hummers method. Furthermore, we show that a newly developed mild thermal reduction at 250 °C is sufficient to increase conductivity by another order of magnitude, while limiting energy requirements. The proposed GO powder protocol suggests an up-scaling linear relation between the amount of educt surface and volume of electrolyte. This may support the mass production of GO-based coatings for the aviation industry, and address challenges such as low weight, fire, de-icing and lightning strike protection. [ABSTRACT FROM AUTHOR]

Interface engineering is one of the most critical directions in the development of photovoltaics (PVs) based on halide perovskites. A novel triphenylamine-based hole transport material (HTM) with a carboxyl anchoring group (TPATC) was developed for tuning the interface between nanocrystalline NiO and CsCH 3 (NH 2) 2 PbI 3-x Cl x absorber in p-i-n device architectures. Transient spectroscopy measurements revealed that modification of the NiO surface with TPATC in perovskite solar cells (PSCs) reduces the concentration of ionic defects by an order of magnitude and reconfigures the energy levels of traps. Interface engineering allowed to reach power conversion efficiency of 20.58% for small area devices (0.15 cm2) under standard AM 1.5 G conditions. Using TPATC interlayer also provided sustainability of the perovskite absorber to decomposition under operation conditions. After continuous light-soaking (ISOS-L-2 protocol), NiO/TPATC devices showed a slight decrease of 2% in maximum power. We explored the potential of TPATC to modify interfaces in perovskite solar modules (PSM, active area-64.8 cm2). By applying slot-die-coated TPATC, the PCE at AM 1.5 G conditions increased from 13.22% for NiO PSM to 15.64% for NiO/TPATC ones. This study provides new insights into the interface stabilization for perovskite solar cells, behavior of the ionic defects and their contribution to the long-term stability. [Display omitted] • A novel triphenylamine-based self-assembling material (SAM) for p-type interface. • Carboxyl anchoring group provides traps passivation at NiO/perovskite junction. • Quantitative analysis of the defect parameters in the device with SAM. • Improvement was validated for perovskite solar modules with efficiency – 15.64%. • Interface engineering improves phase stability of perovskite thin-films. [ABSTRACT FROM AUTHOR]

Food production and consumption related environmental challenges have come to the forefront of policy discourse in the past decade. This links primarily to concerns in terms of agriculture fueling climate change, but also in terms of long-term food security and availability for growing populations. A proposed solution to these pressures at the urban scale is Vertical Farming (VF), in the understanding of this article, a high-yield form of controlled environment agriculture, staked on multiple layers, which promises to produce leafy greens and vegetables within cities, with potential to reduce the resource intensity of urban food production and consumption. The particular contextual conditions required for VF to be sustainable have not as of yet been holistically assessed. Accordingly, by analyzing these contextual conditions in the Global North, this research assesses how VF can be up-scaled for the sake of sustainability – particularly climate mitigation – by viewing urban food systems through the Multi-Level Perspective. The article presents three findings in relation to the up-scaling potential of VF. Firstly, singular VF interventions in cities should have further functions integrated at the scale of the farm for the sake of viability. Secondly, VF interventions carry the most potential for climate mitigation if they are viewed through urban-level systemic food planning, which sheds light on the contextual conditions needed for VF to contribute to sustainability. Finally, the globalized dynamics of the neoliberal political economy, and in turn the localized effects for food systems, have implications for VF that need to be taken into consideration in framing up-scaling policy. [ABSTRACT FROM AUTHOR]

The commercialization of perovskite photovoltaic technology is dependent on the development of high‐efficiency, stable, and large‐area solar modules. Despite the rapid rise in efficiencies of laboratory‐scale perovskite solar cells (PSCs), there is still a big gap in the transition from small‐area devices to large‐area perovskite solar modules (PSMs). Herein, recent progresses on scaling‐up PSMs are reviewed: first, multifarious scalable preparation methods, solvent engineering, and corresponding morphology control strategies for large‐area homogeneous perovskite films are summarized. Various charge carrier transport materials, electrode materials, and their scaling methods for high‐efficiency and stable PSMs are then outlined and the device structure design of PSMs is discussed. Finally, the current strategies for optimizing the environmental stability of devices are highlighted, and packaging for reducing lead leakage during operation is discussed. [ABSTRACT FROM AUTHOR]

In this work, we present our results on the influence of post-deposition treatments on the morphology and optical properties of photoactive films made of small molecules and their subsequent effect on the performance of photovoltaic (PV) devices. We have chosen DPP(TBFu)2:PC61BM as a benchmark model system and compared a novel joule-heating annealing (JHA) treatment with the widely used temperature annealing (TA) and solvent annealing (SVA) treatments. Detailed characterization of the morphology of the active layer and the performance of the devices suggests that JHA is a valuable post-treatment technique that provides fast information about the development of domains in the photoactive layer. Finally, in this context, solar cells on flexible indium tin oxide (ITO) substrates, made of polyethylene terephthalate (PET), were fabricated and analyzed. [ABSTRACT FROM AUTHOR]

Study region: Two typical flux towers and surrounding 100 km × 100 km areas in Northern China. Study focus: Up-scaling the instantaneous latent heat flux (LE) to daily-scale is an important step for estimate daily evapotranspiration based on satellite observations. This study evaluated the performance three up-scaling methods: constant evaporation fraction (CEF), diurnal LE variation (DLEV) and geosynchronous satellite (GS) by using flux tower and satellite observations at site-scale and regional scales, respectively. The purpose was to improve the accuracy of up-scaling LE. New hydrological insights for the region: The results suggested that: (1) DLEV showed slightly better accuracy (rRMSE = 16.27–26.33%) in estimating daily LE than CEF (rRMSE = 17.21–25.14%) at site-scale; (2) At regional scale, GS showed best accuracy (rRMSE = 34.05%), followed by DLEV (rRMSE = 36.46%), CEF had the worst accuracy (rRMSE = 38.96%); (3) DELV can accurately describe the LE variation during the 8:00–17:00 and show a good agreement with flux tower observations and GS observations, but DLEV cannot guarantee the estimation accuracy outside of this period. In general, this study provided a reference for understanding diurnal LE variation during a single day. Additionally, The DLEV proposed in this study can provide a better up-scaling accuracy of regional LE estimation than the CEF which is currently commonly used.

For the application of composite materials to become more widespread and replace traditional materials their manufacturing processes and final products will need to be competitive and be e.g. lighter, stronger or stiffer and quicker, easier or more cost-efficient to produce than traditional materials. The state of the art for pick-and-place operations for the manufacturing of composite parts focuses on handling single lab-sized layers at undisclosed speeds. The process could however be more competitive by being able to handle more and larger layers in a faster manner than currently presented in research. The aim of the paper is to evaluate the existing pick-and-place strategies on their suitability for the swift automated handling of multiple large-sized layers of reinforcement. The review shows that many of the existing techniques could be suitable for different scenario’s and discusses which factors are to be taken into account when dealing with large layers, more than one layer or rapid handling.

This paper describes how a validated semi-empirical, but physiologically based, remote sensing model – Ensemble_all – was up-scaled using MODIS land surface temperature data (MOD11C2), enhanced vegetation indices (MOD13C1) and land-cover data (MCD12C1) to produce a global terrestrial ecosystem respiration data set (Reco) for January 2001–December 2010. The temporal resolution of this data set is 1 month, the spatial resolution is 0.05°, and the range is from 55°S to 65°N and 180°W to 180°E (crop and natural vegetation mosaic is not included). After cross-validating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model, a LPJ_S1 process model and a machine learning method model, we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world. This data set can be found at http://www.dx.doi.org/10.11922/sciencedb.934.

With the rapid growth of data scale and diversification of demand, people have an urgent desire to extract useful frequent itemset from datasets of different scales. It is no doubt that the traditional method can solve the problem. However, the relationships among datasets of different scales are not fully utilized. A fast approach proposed in this paper is as follows: the frequent itemsets on the large-scale data are directly inferred based on the frequent itemsets that are belonged small-scale datasets, instead of mined from the large-scale dataset again on condition that the frequent itemsets on the small-scale datasets have been mined. We conduct extensive experiments on one synthetic data and four UCI data sets. The experimental results show that our algorithm is significantly faster and consumes less memory than these leading algorithms.

The characterisation of fuel distribution across heterogeneous landscapes is important for wildfire mitigation, validating fuel models, and evaluating fuel treatment outcomes. However, efficient fuel mapping at a landscape scale is challenging. Fuel hazard metrics were obtained using Terrestrial Laser Scanning (TLS) and the current operational approach (visual fuel assessment) for seven sites across south-eastern Australia. These point-based metrics were then up-scaled to a continuous fuel map, an area relevant to fire management using random forest modelling, with predictor variables derived from Airborne Laser Scanning (ALS), Sentinel 2A images, and climate and soil data. The model trained and validated with TLS observations (R2 = 0.51 for near-surface fuel cover and 0.31 for elevated fuel cover) was found to have higher predictive power than the model trained with visual fuel assessments (R2 = −0.1 for the cover of both fuel layers). Models for height derived from TLS observations exhibited low-to-moderate performance for the near-surface (R2 = 0.23) and canopy layers (R2 = 0.25). The results from this study provide practical guidance for the selection of training data sources and can be utilised by fire managers to accurately generate fuel maps across an area relevant to operational fire management decisions.

Vegetation phenology reflects the temporal dynamics of vegetation growth and is an important indicator of climate change. However, differences consistently exist in land surface phenology derived at different spatial scales, which hinders the understanding of phenological events and integration of land surface phenology products from different scales. The Qinling Mountains are a climatic and geographical transitional region in China. To better understand the spatial scale effect issues of land surface phenology in mountainous ecosystems, this study up-scaled vegetation start of season (SOS) and end of season (EOS) in the Qinling Mountains derived from three different Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) products to four scales (i.e., 2 km × 2 km, 4 km × 4 km, 6 km × 6 km, and 8 km × 8 km) using the spatial averaging method. Then, similarities and differences between the up-scaled SOSs/EOSs were examined using the simple linear regression, cumulative distribution function, and absolute difference. Finally, the random forest model was used to reveal the major factors influencing the spatial scale effect of land surface phenology in Qinling Mountains. Results showed that the derived basic SOS/EOS datasets using the same filtering method from the 250 m and 500 m NDVI datasets were consistent in spatial distribution, while the results from the 1000 m NDVI dataset differed. For both the basic and the up-scaled datasets, the land surface phenology derived from the Savitzky-Golay-filtered NDVI showed an advance in SOS, but a delay in EOS, compared to those derived from the asymmetric Gaussian- and double logistic-filtered NDVI. The up-scaled SOS was greatly impacted by both NDVI resolution and the filtering methods. On the other hand, EOS was mostly impacted by the filtering methods. Moreover, up-scaled SOSs usually had larger differences compared to up-scaled EOSs. While different filtering methods sometimes amplified the absolute differences between different SOS/EOS across scales, the upscaling reduced the differences. Influence factor analysis showed that spatial variations observed in SOS in Qinling Mountains were mainly caused by forest cover, uneven distribution of spring precipitation, and annual precipitation, while spatial variations in aspect, winter temperature, and autumn precipitation all strongly influenced the observed EOS across scales in the study area. These findings enhance our understanding of the effects of observational scale on vegetation phenology in mountain ecosystems and provide a reference for phenology modeling in mountainous areas.

The Tibetan Plateau is highly sensitive to elevated temperatures and has experienced significant climate warming in the last decades. While climate warming is known to greatly impact alpine ecosystems, the gas exchange responses at the leaf and community levels to climate warming in alpine meadow ecosystems remain unclear. In this study, the alpine grass, Elymus nutans, and forb, Potentilla anserina, were grown in open-top chambers (OTCs) for 3 consecutive years to evaluate their response to warming. Gas exchange measurements were used to assess the effects of in-situ warming on leaf- and community-level photosynthetic carbon assimilation based on leaf photosynthetic physiological parameters. We introduced a means of up-scaling photosynthetic measurements from the leaf level to the community level based on six easily measurable parameters, including leaf net photosynthetic rate, fresh leaf mass per unit leaf area, fresh weight of all plant leaves in the community, the percentage of healthy leaves, the percentage of received effective light by leaves in the community, and community coverage. The community-level photosynthetic carbon assimilation and productivity all increased with warming, and the net photosynthetic rate at the leaf level was significantly higher than at the community level. Under elevated temperature, the net photosynthetic rate of E. nutans decreased, while that of P. anserina increased. These results indicated that climate warming may significantly influence plant carbon assimilation, which could alter alpine meadow community composition in the future.

There has been limited population-level success in tackling overweight and obesity. The Active Kids program is a universal intervention that aims to increase participation in structured physical activity and sport among children and adolescents in New South Wales (NSW), Australia. This study examined the prevalence of overweight and obesity across subgroups and by social disadvantage in this large broadly representative sample. A cross-sectional study was conducted including all children (n = 671,375) who registered for an Active Kids Program voucher in 2018. The child’s height and weight were obtained from an online registration form. Among children and adolescents who registered in the Active Kids Program, the prevalence of overweight and obesity was 17.2% and 7.6%, respectively. A large number of children and adolescents who lived in the most disadvantaged areas (n = 99,583; 14.8%) registered for the program. There was a clear socio-economic gradient for obesity prevalence across areas of increasing disadvantage, with children and adolescents living in the most disadvantaged area being 1.87 (95% CIs 1.82, 1.93) times more likely to be overweight or obese. The Active Kids program successfully reached a substantial proportion of children who are overweight and obese from socio-economically disadvantaged areas, providing financial support and opportunities for these children to participate in structured sport and physical activity. However, the program did not reach all children, and additional physical activity promotion strategies may be needed in a comprehensive approach. Nonetheless, these findings support government investment in reaching children who are overweight or obese with large-scale programs.

The Tibetan Plateau is highly sensitive to elevated temperatures and has experienced significant climate warming in the last decades. While climate warming is known to greatly impact alpine ecosystems, the gas exchange responses at the leaf and community levels to climate warming in alpine meadow ecosystems remain unclear. In this study, the alpine grass, Elymus nutans , and forb, Potentilla anserina , were grown in open-top chambers (OTCs) for 3 consecutive years to evaluate their response to warming. Gas exchange measurements were used to assess the effects of in-situ warming on leaf- and community-level photosynthetic carbon assimilation based on leaf photosynthetic physiological parameters. We introduced a means of up-scaling photosynthetic measurements from the leaf level to the community level based on six easily measurable parameters, including leaf net photosynthetic rate, fresh leaf mass per unit leaf area, fresh weight of all plant leaves in the community, the percentage of healthy leaves, the percentage of received effective light by leaves in the community, and community coverage. The community-level photosynthetic carbon assimilation and productivity all increased with warming, and the net photosynthetic rate at the leaf level was significantly higher than at the community level. Under elevated temperature, the net photosynthetic rate of E. nutans decreased, while that of P. anserina increased. These results indicated that climate warming may significantly influence plant carbon assimilation, which could alter alpine meadow community composition in the future. [ABSTRACT FROM AUTHOR]

To reduce the global emissions of CO2, the aviation industry largely relies on new light weight materials, which require multifunctional coatings. Graphene and its derivatives are particularly promising for combining light weight applications with functional coatings. Although they have proven to have outstanding properties, graphene and its precursor graphene oxide (GO) remain far from application at the industrial scale since a comprehensive protocol for mass production is still lacking. In this work, we develop and systematically describe a sustainable up-scaling process for the production of GO based on a three-step electrochemical exfoliation method. Surface characterization techniques (XRD, XPS and Raman) allow the understanding of the fast exfoliation rates obtained, and of high conductivities that are up to four orders of magnitude higher compared to GO produced via the commonly used modified Hummers method. Furthermore, we show that a newly developed mild thermal reduction at 250 °C is sufficient to increase conductivity by another order of magnitude, while limiting energy requirements. The proposed GO powder protocol suggests an up-scaling linear relation between the amount of educt surface and volume of electrolyte. This may support the mass production of GO-based coatings for the aviation industry, and address challenges such as low weight, fire, de-icing and lightning strike protection.

The fully printed, hole-transporter-free carbon perovskite solar cell structure incorporating a triple mesoscopic layer has emerged as a possible frontrunner for early industrialisation. It is an attractive structure because it can be fabricated by the simple sequential screen printing and sintering of titania, zirconia, and carbon. The device is finalised by manual dropping of a perovskite precursor solution onto the carbon which subsequently infiltrates. This stage in device fabrication is inhomogeneous, ineffective for large areas, and prone to human error. Here we introduce an automated deposition and infiltration system using a robotic dispenser and mesh which delivers the perovskite precursor uniformly to the carbon surface over a large area. It has been successfully used to prepare perovskite solar cells with over 9% efficiency. Cells, prepared by this robotic mesh deposition, showed comparable performance to reference cells, made by standard drop deposition, confirming this approach to be effective and reliable. X-ray diffraction and Raman spectroscopy were used to confirm the uniformity of the deposition over a large area.

Image up-scaling employs various polynomial interpolation schemes for their reduced computational complexity and suitability for various real-time applications. However, they give blurring artifacts in up-scaled images due to the loss of high frequency (HF) information. Likewise, most of the other edge directed and transform domain interpolation schemes available in the literature though produce lesser blurring as compared to polynomial interpolation schemes but are computationally more complex. To overcome these problems, an iterative spatial domain 2-D signal decomposition technique is proposed. It is meant for extracting the very high frequency (VHF) information from a low resolution (LR) image. The VHF information is obtained by performing the signal decomposition for an estimated number of iterations. Subsequently, the superimposition of this VHF extract with the low resolution image prior to image up-scaling reduces the blurring in its up-scaled counterpart. Since the degradation of higher order sub-band information such as HF and VHF is more than the low and medium frequency information during an up-scaling process, restoration of the most degraded VHF sub-band information would produce much lesser blurring. Simulation results reveal that the proposed scheme gives better performance than many of the existing schemes in terms of objective and subjective measures. [ABSTRACT FROM AUTHOR]

A sol-gel process for the synthesis of a multi-component oxide material from the system SiO2-ZrO2-Al2O3underwent optimization and up-scaling. Initially, on a laboratory scale, components including precursors, catalysts, and additives were methodically evaluated to ensure a safe and efficient transition to larger volumes. Subsequently, the equipment for the whole setup of the sol-gel process was strategically selected. Leveraging insights from these optimizations, the process was successfully scaled-up to pilot-scale operation, conducting hydrolysis, condensation reactions, gelation, aging, and drying within a single, integrated conical dryer system for an 80 L batch. A visual test and FTIR spectroscopy were applied for process control and monitoring., (Copyright 2024 Barbara Pföss, Jonathan Caldi, Sutida Jansod, Christophe Allemann, Pierre Brodard, Roger Marti. License: This work is licensed under a Creative Commons Attribution 4.0 International License.)

The aim of this study has been to investigate the environmental impacts of an innovative food waste management system and compare it with landfilling as a conventional waste management option. The investigated system is still in the laboratory research and development phase. Therefore, inventory data of the laboratory scale food waste management system was collected and then up-scaled for life cycle assessment purposes. The proposed system consists of a hygenization reactor followed by a fermenter and then a centrifuge. The system converts food waste into volatile fatty acid-rich supernatant. Functional unit is management of 1 ton food waste. The results indicate that the proposed system is a better option than landfilling in terms of all impact categories. The produced VFA-rich supernatant is supposed to be used as a replacement for methanol in the denitrification process. In one of the impact categories (ozone depletion potential) the avoided burdens are higher than the burdens and the system provides net gain (−2.82E-07 kg R11 eq.). Majority of the environmental burdens in the proposed system are due to heat consumption for hygenization. Including sludge disposal in the investigated system boundary increases the environmental burdens but the burdens are still lower compared to landfilling option.

In this work, we present our results on the influence of post-deposition treatments on the morphology and optical properties of photoactive films made of small molecules and their subsequent effect on the performance of photovoltaic (PV) devices. We have chosen DPP(TBFu)2:PC61BM as a benchmark model system and compared a novel joule-heating annealing (JHA) treatment with the widely used temperature annealing (TA) and solvent annealing (SVA) treatments. Detailed characterization of the morphology of the active layer and the performance of the devices suggests that JHA is a valuable post-treatment technique that provides fast information about the development of domains in the photoactive layer. Finally, in this context, solar cells on flexible indium tin oxide (ITO) substrates, made of polyethylene terephthalate (PET), were fabricated and analyzed.

Forest canopy height is an essential parameter in estimating forest aboveground biomass (AGB), growing stock volume (GSV), and carbon storage, and it can provide necessary information in forest management activities. Light direction and ranging (LiDAR) is widely used for estimating canopy height. Considering the high cost of acquiring LiDAR data over large areas, we took a two-stage up-scaling approach in estimating forest canopy height and aimed to develop a method for quantifying the uncertainty of the estimation result. Based on the generalized hierarchical model-based (GHMB) estimation framework, a new estimation framework named RK-GHMB that makes use of a geostatistical method (regression kriging, RK) was developed. In this framework, the wall-to-wall forest canopy height and corresponding uncertainty in map unit scale are generated. This study was carried out by integrating plot data, sampled airborne LiDAR data, and wall-to-wall Ziyuan-3 satellite (ZY3) stereo images. The result shows that RK-GHMB can obtain a similar estimation accuracy (r = 0.92, MAE = 1.50 m) to GHMB (r = 0.92, MAE = 1.52 m) with plot-based reference data. For LiDAR-based reference data, the accuracy of RK-GHMB (r = 0.78, MAE = 1.75 m) is higher than that of GHMB (r = 0.75, MAE = 1.85 m). The uncertainties for all map units range from 1.54 to 3.60 m for the RK-GHMB results. The values change between 1.84 and 3.60 m for GHMB. This study demonstrates that this two-stage up-scaling approach can be used to monitor forest canopy height. The proposed RK-GHMB approach considers the spatial autocorrelation of neighboring data in the second modeling stage and can achieve a higher accuracy.

Abstract Background PEACH™QLD translated the PEACH™ Program, designed to manage overweight/obesity in primary school-aged children, from efficacious RCT and small scale community trial to a larger state-wide program. This paper describes the lessons learnt when upscaling to universal health coverage. Methods The 6-month, family-focussed program was delivered in Queensland, Australia from 2013 to 2016. Its implementation was planned by researchers who developed the program and conducted the RCT, and experienced project managers and practitioners across the health continuum. The intervention targeted parents as the agents of change and was delivered via parent-only group sessions. Concurrently, children attended fun, non-competitive activity sessions. Sessions were delivered by facilitators who received standardised training and were employed by a range of service providers. Participants were referred by health professionals or self-referred in response to extensive promotion and marketing. A pilot phase and a quality improvement framework were planned to respond to emerging challenges. Results Implementation challenges included engagement of the health system; participant recruitment; and engagement. A total of 1513 children (1216 families) enrolled, with 1122 children (919 families) in the face-to-face program (105 groups in 50 unique venues) and 391 children (297 families) in PEACH™ Online. Self-referral generated 68% of enrolments. Unexpected, concurrent and, far-reaching public health system changes contributed to poor program uptake by the sector (only 56 [53%] groups delivered by publicly-funded health organisations) requiring substantial modification of the original implementation plan. Process evaluation during the pilot phase and an ongoing quality improvement framework informed program adaptations that included changing from fortnightly to weekly sessions aligned with school terms, revision of parent materials, modification of eligibility criteria to include healthy weight children and provision of services privately. Comparisons between pilot versus state-wide waves showed comparable prevalence of families not attending any sessions (25% vs 28%) but improved number of sessions attended (median = 5 vs 7) and completion rates (43% vs 56%). Conclusions Translating programs developed in the research context to enable implementation at scale is complex and presents substantial challenges. Planning must ensure there is flexibility to accommodate and proactively manage the system changes that are inevitable over time. Trial registration ACTRN12617000315314. This trial was registered retrospectively on 28 February, 2017.

To account for the temperature effect on guided wave signals in complex structures, a significant amount of baseline measurements typically need to be collected over a large temperature range to serve as a library of signals at all possible temperatures, which, if not impossible, is highly impractical. This article presents a data-driven temperature baseline reconstruction approach that is applicable for various structures made from the same material. The influence of temperature on the amplitude and phase of guided wave measurements are experimentally quantified as dimensionless compensation factors. The derived compensation factors are used to reconstruct baselines at various temperatures for guided wave measurements in a simple flat plate and a stiffened panel. With a single baseline measurement at 20°C and the reconstructed baseline using the predetermined temperature compensation factors, impact damage was successfully detected and located when current measurements were up to 25°C and 20°C higher than the baseline temperature, respectively. [ABSTRACT FROM AUTHOR]

For the application of composite materials to become more widespread and replace traditional materials their manufacturing processes and final products will need to be competitive and be e.g. lighter, stronger or stiffer and quicker, easier or more cost-efficient to produce than traditional materials. The state of the art for pick-and-place operations for the manufacturing of composite parts focuses on handling single lab-sized layers at undisclosed speeds. The process could however be more competitive by being able to handle more and larger layers in a faster manner than currently presented in research. The aim of the paper is to evaluate the existing pick-and-place strategies on their suitability for the swift automated handling of multiple large-sized layers of reinforcement. The review shows that many of the existing techniques could be suitable for different scenario's and discusses which factors are to be taken into account when dealing with large layers, more than one layer or rapid handling. [ABSTRACT FROM AUTHOR]