Winter wheat is one of the major cereal crops globally and one of the top three cereal crops in China. The precise forecasting of the yield of winter wheat holds significant importance in the realms of agricultural management and ensuring food security. The use of multi-temporal remote sensing data for crop yield prediction has gained increasing attention. Previous research primarily focused on utilizing remote sensing data from individual or a few growth stages as input parameters or integrated data across the entire growth period. However, a detailed analysis of the impact of different temporal combinations on the accuracy of yield prediction has not been extensively reported. In this study, we optimized the temporal sequence of growth stages using interpolation methods, constructed a yield prediction model incorporating the enhanced vegetation index (EVI) at different growth stages as input parameters, and employed a random forest (RF) algorithm. The results indicated that the RF model utilizing the EVI from all the temporal combinations throughout the growth period as input parameters accurately predicted the winter wheat yield with an R² of the calibrated dataset exceeding 0.58 and an RMSE less than 1284 kg/ha. Among the 1023 yield models tested in this study with ten different growth stage combinations, the most accurate temporal combination comprised five stages corresponding to the regreening, erecting, jointing, heading, and filling stages, with an R² of 0.81 and an RMSE of 1250 kg/ha and an NRMSE of 15%. We also observed a significant decrease in estimation accuracy when the number of growth stages was fewer than five and a certain degree of decline when the number exceeded five. Our findings confirmed the optimal number and combination of growth stages for the best yield prediction, providing substantial insights for winter wheat yield forecasting. Full article

The Quintuple Aim seeks to improve healthcare by addressing social determinants of health (SDOHs), which are responsible for 70–80% of medical outcomes. SDOH-related concerns have traditionally been addressed through referrals to social workers and community-based organizations (CBOs), but these pathways have had limited success in connecting patients with resources. Given that health inequity is expected to cost the United States nearly USD 300 billion by 2050, new artificial intelligence (AI) technology may aid providers in addressing SDOH. In this commentary, we present our experience with using ChatGPT to obtain SDOH management recommendations for archetypal patients in Philadelphia, PA. ChatGPT identified relevant SDOH resources and provided contact information for local organizations. Future exploration could improve AI prompts and integrate AI into electronic medical records to provide healthcare providers with real-time SDOH recommendations during appointments. Full article

Batteryless, self-sustaining embedded sensing devices are key enablers for scalable and long-term operations of Internet of Things (IoT) applications. While advancements in both energy harvesting and intermittent computing have helped pave the way for building such batteryless IoT devices, a present challenge is a system design that can utilize intermittent energy to meet data requirements from IoT applications. In this paper, we take the requirement of periodic data sensing and describe the hardware and software of a batteryless IoT device with its model, design, implementation, and evaluation. A key finding is that, by estimating the non-linear hardware charging and discharging time, the device software can make scheduling decisions that both maintain the selected sensing period and improve transmission goodput. A hardware–software prototype was implemented using an MSP430 development board and LoRa radio communication technology. The proposed design was empirically compared with one that does not consider the non-linear hardware characteristics. The result of the experiments illustrated the nuances of the batteryless device design and implementation, and it demonstrated that the proposed design can cover a wider range of feasible sensing rates, which reduces the restriction on this parameter choice. It was further demonstrated that, under an intermittent supply of power, the proposed design could still keep the device functioning as required. Full article

Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a Bayesian optimization algorithm, a deep neural network is structured to evaluate the whole charging curve of the battery using partial charging curve data as input. A 0.74 Ah battery is used for experiments, and the effect of different input data lengths is also investigated to check the high flexibility of the approach. The consequences show that using only 20 points of partial charging data as input, the whole charging profile of a cell can be exactly predicted with a root-mean-square error (RMSE) of less than 19.16 mAh (2.59% of the nominal capacity of 0.74 Ah), and its mean absolute percentage error (MAPE) is less than 1.84%. In addition, critical information including battery state-of-charge (SOC) and state-of-health (SOH) can be extracted in this way to provide a basis for safe and long-lasting battery operation. Full article

Cerebrospinal fluid analysis is an important diagnostic test when assessing a neurological canine patient. For this analysis, the total nucleated cell count and differential cell counts are routinely taken, but both involve time-consuming manual methods. To investigate faster automated methods, in this study, the Sysmex XN-V body fluid mode and the deep-learning-based algorithm generated by the Olympus VS200 slide scanner were compared with the manual methods in 161 canine cerebrospinal fluid samples for the total nucleated cell count and in 65 samples with pleocytosis for the differential counts. Following incorrect gating by the Sysmex body fluid mode, all samples were reanalyzed with manually set gates. The Sysmex body fluid mode then showed a mean bias of 15.19 cells/μL for the total nucleated cell count and mean biases of 4.95% and −4.95% for the two-part differential cell count, while the deep-learning-based algorithm showed mean biases of −7.25%, −0.03% and 7.27% for the lymphocytes, neutrophils and monocytoid cells, respectively. Based on our findings, we propose that the automated Sysmex body fluid mode be used to measure the total nucleated cell count in canine cerebrospinal fluid samples after making adjustments to the predefined settings from the manufacturer. However, the two-part differential count of the Sysmex body fluid mode and the deep-learning-based algorithm require some optimization. Full article

Newcastle disease (ND) is a significant infectious disease in poultry, causing substantial economic losses in developing countries. To control ND, chickens must be vaccinated multiple times a year. In order to develop an improved vaccine that provides long-term protection, the F gene from genotype VII NDV was inserted into the herpesvirus of turkey (HVT) vaccine virus using CRISPR/Cas9-mediated NHEJ repair and Cre/LoxP technology. The immunogenicity and protective efficacy of the resulting recombinant vaccines were evaluated through antibody assays and virus challenge experiments. Two recombinant vaccines, rHVT-005/006-F and rHVT-US2-F, were generated, both exhibiting growth rates comparable with those of HVT in vitro and consistently expressing the F protein. One-day-old specific pathogen-free (SPF) chickens immunized with 2000 PFU/bird of either rHVT-005/006-F or rHVT-US2-F developed robust humoral immunity and were completely protected against challenge with the NDV F48E8 strain at 4 weeks post-vaccination (wpv). Furthermore, a single dose of these vaccines provided sustained protection for at least 52 wpv. Our study identifies rHVT-005/006-F and rHVT-US2-F as promising ND vaccine candidates, offering long-term protection with a single administration. Moreover, HVT-005/006 demonstrates promise for accommodating additional foreign genes, facilitating the construction of multiplex vaccines. Full article

RSV infection causes severe respiratory illness and mortality in the elderly, especially in the presence of comorbidities. Early identification of infection would result in appropriate clinical-therapeutic management, avoiding hospitalizations, the risk of healthcare-associated infections, and inappropriate antibiotic prescriptions, thus reducing healthcare costs and fighting antimicrobial resistance. The aim of this study was to assess RSV hospitalizations in subjects >64 years hospitalized in a large tertiary care hospital in Southern Italy, in order to assess their usefulness as a proxy for targeting a potential vaccination strategy. Fifty-two RSV-positive patients were identified from the 2014–2015 to the 2022–2023 seasons. RSV type B was found in 71.2% of cases. The median age was 78 years (IQR: 72–84) and 40.4% of the subjects had at least one comorbidity; 5.8% needed intensive care. The use of combined rapid tests for SARS-CoV-2/influenza/RSV identification in primary care settings may contribute to an improved definition of the burden of RSV in the elderly. The implementation of an anti-RSV vaccination strategy in the elderly population would reduce direct and indirect infection costs. More robust epidemiological data in Italy are needed for targeted preventive strategies. Full article

Situated within the context of a soft ground foundation at an iron ore mining site, this study investigates the impact of substantial surcharges on the settlement of such foundations and the adjacent infrastructure. By employing the finite-difference numerical software FLAC3D 6.0, a series of three-dimensional simulations were conducted to assess the stress response and deformation of gallery pile foundations, shallow foundations, and mine shed pile foundations to step loading. This study integrates the analysis of soil strength augmentation under considerable stress and its attenuation characteristics under significant deformation. Various reinforcement measures, such as the implementation of stone columns, prefabricated vertical drain, and surcharge preloading techniques, were examined for their capacity to consolidate the foundation, reduce settlement, and mitigate impacts on adjacent structures. The results reveal that horizontal displacements in the pile and shallow foundations escalate progressively with additional surcharge throughout the operational period. The most pronounced horizontal deviation in the pile foundations is observed at the juncture between sand and silt strata. Stone columns act effectively as a barrier to the sliding surface, consequently reducing the influence of surcharge on the movement of the foundation. Full article

To understand the influences of emulsified fuel on ship exhaust emissions more comprehensively, the emissions of particulate matter (PM), nitrated, oxygenated and parent polycyclic aromatic hydrocarbons (PAHs) were studied on a ship main engine burning emulsified heavy fuel oil (EHFO) and heavy fuel oil (HFO) as a reference. The results demonstrate that EHFO (emulsified heavy fuel oil) exhibits notable abilities to significantly reduce emissions of particulate matter (PM) and low molecular weight PAHs (polycyclic aromatic hydrocarbons) in the gas phase, particularly showcasing maximum reductions of 13.99% and 40.5%, respectively. Nevertheless, burning EHFO could increase the emission of high molecular weight PAHs in fine particles and pose a consequent higher carcinogenic risk for individual particles. The total average (gaseous plus particulate) ΣBEQ of EHFO exhausts (41.5 μg/m³) was generally higher than that of HFO exhausts (18.7 μg/m³). Additionally, the combustion of EHFO (extra-heavy fuel oil) can significantly alter the emission quantity, composition, and particle-size distribution of PAH derivatives. These changes may be linked to molecular structures, such as zigzag configurations in C=O bonds. Our findings may favor the comprehensive environmental assessments on the onboard application of EHFO. Full article

Mechanical condition monitoring data in real engineering are often severely unbalanced, which can lead to a decrease in the stability and accuracy of intelligent diagnosis methods. In this paper, a fault diagnosis method based on the SMOTE + Tomek Link and dual-channel feature fusion is proposed to improve the performance of the sample imbalance fault diagnosis method, taking the piston pump of a turnout rutting machine as the research object. Combining the data undersampling method and the oversampling method to redistribute the collected normal data and fault data makes the diagnostic model have better diagnostic performance in the case of insufficient fault samples. And, in order to fully utilize the global features and local features, a global–local feature complementary module (GLFC) is proposed. Firstly, the generated data similar to the original data are constructed using the SMOTE + Tomek Link method; secondly, the generated data are input into a GLFC module and BiGRU at the same time, the GLFC module extracts the spatial global features and local features of the original vibration data, and BiGRU extracts the temporal information features of the original vibration data, and fuses the extracted feature information, and inputs the fused features into the attention layer; finally, a GLFC module is proposed by the SMOTE + Tomek Link method to make full use of the global features and local features. The extracted feature information is fused, and the fused features are input to the attention layer; finally, the fault classification is completed by the softmax classifier. In this paper, the accuracy and robustness of the proposed model are demonstrated through experiments. Full article

In this research, SCAPS-1D simulation software (Version: 3.3.10) was employed to enhance the efficiency of CsSnX₃ (X = Cl, Br, I) all-inorganic perovskite solar cells. By fine-tuning essential parameters like the work function of the conductive glass, the back contact point, defect density, and the thickness of the light absorption layer, we effectively simulated the optimal performance of CsSnX₃ (X = Cl, Br, I) all-inorganic perovskite solar cells under identical conditions. The effects of different X-site elements on the overall performance of the device were also explored. The theoretical photoelectric conversion efficiency of the device gradually increases with the successive substitution of halogen elements (Cl, Br, I), reaching 6.09%, 17.02%, and 26.74%, respectively. This trend is primarily attributed to the increasing size of the halogen atoms, which leads to better light absorption and charge transport properties, with iodine (I) yielding the highest theoretical conversion efficiency. These findings suggest that optimizing the halogen element in CsSnX₃ can significantly enhance device performance, providing valuable theoretical guidance for the development of high-efficiency all-inorganic perovskite solar cells. Full article

We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over Türkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal–Wallis and Mann–Whitney U methods, and long-term trends were analyzed using Modified Mann–Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of Türkiye (χ² values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest ‘greening’ for Türkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of Türkiye. Full article

With more and more loss caused by forest biological disasters (FBDs) in China, forest farmers, as one of the most important stakeholders, are participating in the control. In this study, the ordinary least squares model, simultaneous equation model, and propensity score matching method were used with the data from 818 surveys conducted in the typical FBD outbreak provinces, to reveal the FBD control behaviors of forest farmers and their differences between western and eastern regions of China. The results indicated the following. (1) Household factors: forest farmers could timely take control measures. An increase of 1 ha in the area of occurrence would increase the control measures by 3.26 ha. However, the control measures can only reduce 50% of the economic loss caused by FBDs and cannot effectively control the spread trend of FBDs. There are issues, including an insufficient and old labor force, insufficient technology support, and low consciousness of ecology protection. (2) External factors: forest farmers would increase control when the temperature rises, and reduce control when rainfall increases. After village committees unify organizing the control, their participation enthusiasm would increase, which would have a substitution relationship with the household investment. (3) Regional difference: the eastern region of China has higher figures than the western in terms of outbreak area, economic losses, control measures, and pesticide cost. If the western forest farmers have the control funds as the eastern forest farmers have, and the eastern forest farmers have the control intensity as the western forest farmers have, the overall FBD control effect would be better. Full article

In the face of our rapidly expanding global population, the necessity of meeting the fundamental needs of every individual is more pressing than ever. Human survival depends upon access to water, making it a vital resource that demands novel solutions to ensure universal availability. Although our planet is abundant in water, 97.5% of it is saltwater, compelling nations to investigate ways to make it suitable for consumption. Seawater desalination is becoming increasingly vital for water sustainability. While seawater desalination offers a solution, existing methods often grapple with high energy consumption and maintaining consistent water quality. This paper proposes a novel hybrid water desalination system that addresses these limitations. Our system leverages solar energy, a readily available renewable resource, to power the desalination process, significantly improving its environmental footprint and operational efficiency. Additionally, we integrated a network of sensors and the Internet of Things (IoT) to enable the real-time monitoring of system performance and water quality. This allows for the immediate detection and improvement in any potential issues, ensuring the consistent production of clean drinking water. By combining solar energy with robust quality control via IoT, our hybrid desalination system offers a sustainable and reliable approach to meet the growing demand for freshwater. Full article

Beauveria bassiana and Metarhizium rileyi are extensively utilized to investigate fungal pathogenic mechanisms and to develop biological control agents. Notwithstanding, notable distinctions exist in their pathogenicity against the same host insect. This study aimed to elucidate the pathogenic differences between M. rileyi and B. bassiana by examining the impact of various ratios of B. bassiana strain AJS91881 and M. rileyi strain SXBN200920 on fifth instar larvae of Spodoptera litura, focusing on early infection stages and intestinal microbial community structure. The lethal time 50 (LT₅₀) for B. bassiana was significantly lower than that for M. rileyi, indicating greater efficacy. Survival analyses in mixed groups (ratios of 1:9, 1:1, and 9:1 M. rileyi to B. bassiana) consistently demonstrated higher virulence of B. bassiana. Intestinal microbial diversity analysis revealed a significant increase in Achromobacter and Pseudomonas in larvae infected with M. rileyi, whereas Weissella was notably higher in those infected with B. bassiana. Additionally, significant shifts in microbial genera abundances were observed across all mixed infection groups. KEGG pathway enrichment analysis indicated that M. rileyi and B. bassiana employ distinct pathogenic strategies during early infection stages. In vitro tests confirmed the superior growth and stress resistance of B. bassiana compared to M. rileyi, but the antifungal ability of M. rileyi was better than that of B. bassiana. In conclusion, our findings provide preliminary insights into the differential pathogenic behaviors of M. rileyi and B. bassiana during the early infection stages in S. litura larvae, enhancing our understanding of their mechanisms and informing biological pest control strategies in agriculture and forestry. Full article

The efficiency and method of regeneration in in vitro culture conditions depend primarily on the plant growth regulators (PGRs) used. Even growth regulators belonging to one group may have different effects, stimulating the process of direct or indirect organogenesis, thus possibly disturbing the genetic stability among regenerants. The main aim of this study was to identify the genetic stability of Scutellaria baicalensis regenerates obtained by in vitro culture method using start codon targeted (ScoT) markers. S.baicalensis nodal explants were regenerated on MS medium supplemented with kinetin (KIN) at concentrations of 0.25, 0.5, 1.0, and 2.0 mg × dm⁻³ or benzylaminopurine (BAP)—0.25, 0.5, 1.0, and 2.0 mg × dm⁻³. The effects of the number of propagated shoots, length, number of nodes, and fresh mass of regenerants were assessed. Moreover, the genetic stability of the regenerants was analyzed using start codon targeted (SCoT) markers. Direct shoot organogenesis was observed on an MS medium containing kinetin, while indirect shoot induction occurred on an MS medium supplemented with BAP. The highest average number of shoots (3.6) was achieved for the MS + KIN medium at a concentration of 0.25 and 5.8 for the MS + BAP 1.0 medium. The average length and average number of nodes were the highest on the MS + BAP 0.25 medium (50.0 and 6.0, respectively), while the lowest values of these features were observed on the MS + KIN 2.0 medium (40.3 and 4.9, respectively). A total of 111 amplified bands were exhibited by SCoT primers. Three of the analyzed primers revealed four unique genotype-specific markers. The average percentage of polymorphism obtained was 36.7%. The analysis of genetic similarity revealed a high level of genetic similarity between the donor plant and regenerants obtained on MS “0” (medium without the addition of phytohormones). A slightly lower value of genetic similarity was observed for regenerants obtained by direct organogenesis (MS + KIN medium at all concentrations). Indirect shoot organogenesis observed on the MS + BAP medium (all concentrations) resulted in the highest differentiation, both in relation to the donor plant and MS “0” regenerants. The results of our work indicate that, in the case of S. baicalensis, the maintenance of genetic stability depends primarily on the presence of the cytokinin type in the medium. Full article

The ratoon rice cropping pattern is an alternative to the double-season rice cropping pattern in central China due to its comparable annual yield and relatively lower cost and labor requirements. However, the impact of the ratoon rice cropping pattern on greenhouse gas (GHG) emissions and yields in the double-season rice region requires further investigation. Here, we compared two cropping patterns, fallow-double season rice (DR) and fallow-ratoon rice (RR), by using two early-season rice varieties (ZJZ17, LY287) and two late-season rice varieties (WY103, TY390) for DR, and two ratoon rice varieties (YLY911, LY6326) for RR. The six varieties constituted four treatments, including DR1 (ZJZ17 + WY103), DR2 (LY287 + TY390), RR1 (YLY911), and RR2 (LY6326). The experimental results showed that conversion from DR to RR cropping pattern significantly altered the GHG emissions, global warming potential (GWP), and GWP per unit yield (yield-scaled GWP). Compared with DR, the RR cropping pattern significantly increased cumulative methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂) emissions by 65.73%, 30.56%, and 47.13%, respectively, in the first cropping season. Conversely, in the second cropping season, the RR cropping pattern effectively reduced cumulative CH₄, N₂O, and CO₂ emissions by 79.86%, 27.18%, and 30.31%, respectively. RR led to significantly lower annual cumulative CH₄ emissions, but no significant difference in cumulative annual N₂O and CO₂ emissions compared with DR. In total, the RR cropping pattern reduced the annual GWP by 7.38% and the annual yield-scaled GWP by 2.48% when compared to the DR cropping pattern. Rice variety also showed certain effects on the yields and GHG emissions in different RR cropping patterns. Compared with RR1, RR2 significantly increased annual yield while decreasing annual GWP and annual yield-scaled GWP. In conclusion, the LY6326 RR cropping pattern may be a highly promising strategy to simultaneously reduce GWP and maintain high grain yield in double-season rice regions in central China. Full article

Interest in searches for Charged Lepton Flavor Violation (CLFV) has continued in the past few decades since the observation of CLFV would indicate a new physics Beyond the Standard Model (BSM). As several future lepton colliders with high luminosity have been proposed, the search for CLFV will reach an unprecedented level of precision. Many BSM models allow CLFV processes at the tree level, such as the R-parity-violating (RPV) Minimal Supersymmetric Standard Model (MSSM), which is a good choice for benchmarking. In this paper, we perform a detailed fast Monte Carlo simulation study on RPV-induced CLFV processes at future lepton colliders, including a 240 $\mathrm{GeV}$ circular electron positron collider (CEPC) and a 6 or 14 $\mathrm{TeV}$ Muon Collider. As a result, we found that the upper limits on the $\tau$-related RPV couplings will be significantly improved, while several new limits on RPV couplings can be set, which are inaccessible by low-energy experiments. Full article

Power Electronics Converters (PEC) play a crucial role in the operation of many modern electrical systems and devices. Despite their widespread use, the lack of an efficient and cost-effective disassembly process can limit their repairability, refurbishability, remanufacturability and, ultimately, recyclability, thus hindering the circularity of products. In order to improve their circularity, it is important to assess their ease of disassembly. Therefore, this paper investigates the applicability of the “ease of Disassembly Metric” (eDiM), which is referenced in the material efficiency standards, Benelux repairability assessment method, and Repair Scoring System (RSS), to analyze the ease of disassembly of energy-related products. After identifying the limitations of the eDiM method, we refined and adapted it to make it more suitable for Printed Circuit Board (PCB)-based PEC, and thus propose a PCB-based disassemblability assessment method allowing the implementation of quantifiable requirements supporting their circularity. This standardized approach, at the PCB level, can improve the circularity of such products by facilitating design enhancements. With this approach, policymakers and designers can contribute more effectively to the transition to a circular economy in PCB electronics, particularly in the field of power electronics. Full article

This study evaluates the feasibility of producing high-strength low-alloy (HSLA) steel using advanced wire-fed laser additive manufacturing (LAM-W) and wire arc additive manufacturing (WAAM) technologies. Optimized parameters were independently developed for each heat source, utilizing a self-designed HSLA steel wire as the feedstock. Microstructural features and mechanical properties of the fabricated steels were characterized and compared, taking into account differences in heat input and cooling rates. LAM-W samples exhibited a finer columnar grain microstructure, while both LAM-W- and WAAM-produced steels predominantly showed lower bainite and granular bainite microstructures. LAM-W demonstrated higher strength and hardness, lower ductility, and comparable low-temperature toughness compared to WAAM. Both processes demonstrated an excellent balance between strength and ductility, with absorbed energy exceeding 100 J at −40 °C. The study confirms the feasibility of producing high-strength and tough HSLA steel parts using LAM-W and WAAM technologies, and compares the advantages and disadvantages of each method. These findings assist in selecting the most suitable wire-fed AM process for HSLA steel fabrication at high deposition rates. Full article

Social isolation and loneliness greatly contribute to negative health consequences in older adults. Technological solutions can be an asset in promoting social connections and healthy behaviours. This paper presents an innovative structure for an Internet of Things (IoT) platform specifically tailored for older persons. The framework utilises a supervised learning algorithm to classify users into four identified profiles to facilitate the adoption and engagement of technology. The platform incorporates wearables, such as socks and smart bands, to track physical activity, and a messaging module to encourage social interaction. The platform processes the acquired data to quantify steps and deliver tailored interventions remotely to the older adults through the AGAPE Assistant, the mHealth solution of the platform. Furthermore, the AGAPE Assistant has a user interface design for older adults, with a focus on their specific needs. Additionally, improving digital literacy among older adults is crucial for maximizing the long-term compliance and benefits of such technological solutions. On the other hand, AGAPE Monitor is a web application used by formal caregivers to configure the tailored interventions. The platform’s usability was assessed using different usability scale questionnaires, which revealed a mild level of user satisfaction and acceptance. The proposed framework is currently being deployed on more than 112 older adults across three countries: Italy, Romania, and Portugal. The proposed framework provides a holistic solution to encourage active ageing by adopting technology, implementing hybrid interventions, and promoting social interactions. Full article

Worldwide emission standards are now required to cover engine operation under extreme ambient conditions, which affect the raw emissions and the efficiency of the exhaust aftertreatment systems. These regulations also target new combustion technologies for decarbonization, such as neat hydrogen (${\mathrm{H}}_2$) combustion or dual-fuel strategies, which involve a challenge to the analysis of exhaust aftertreatment system requirements and performance. This work addresses the impact of high altitude and low ambient temperature conditions on the reactivity of an oxidation catalyst in the presence of ${\mathrm{H}}_2$. A reaction mechanism is proposed to cover the main conversion paths of CO, HC, and ${\mathrm{H}}_2$, including the formation and consumption of high-energy surface reaction intermediates. The mechanism has been implemented into a faster-than-real-time reduced-order model for multi-layer washcoat honeycomb catalytic converters. The model was utilized to investigate the effect of ${\mathrm{H}}_2$ concentration on the reactivity of CO and HC within the catalyst under various operating and ambient conditions. By applying the model and examining the selectivity towards different reaction pathways in the presence of ${\mathrm{H}}_2$, insights into surface intermediates and reactivity across different cross-sections of the monolith were obtained. This analysis discusses the underlying causes of reactivity changes promoted by ${\mathrm{H}}_2$ and its relative importance as a function of driving boundary conditions. Full article