In just a few short years, the additive manufacturing (AM) technology known as 3D printing has experienced intense growth from a niche technology to a disruptive innovation that has captured the imagination of mainstream manufacturers and hobbyists alike. The purpose of this article is to introduce the use of 3D printing for specific applications, materials, and manufacturing processes that help to optimize heat transfer in heat exchangers, with an emphasis on sustainability. The ability to create complex geometries, customize designs, and use advanced materials provides opportunities for more efficient and stable heat transfer solutions. One of the key benefits of incremental technology is the potential reduction in material waste compared to traditional manufacturing methods. By optimizing the design and structure of heat transfer components, 3D printing enables lighter yet more efficient solutions and systems. The localized manufacturing of components, which reduces the need for intensive transportation and associated carbon emissions, can lead to reduced energy consumption and improved overall efficiency. The customization and flexibility of 3D printing enables the integration of heat transfer components into renewable energy systems. This article presents the key challenges to be addressed and the fundamental research needed to realize the full potential of incremental manufacturing technologies to optimize heat transfer in heat exchangers. It also presents a critical discussion and outlook for solving global energy challenges through innovative incremental manufacturing technologies in the heat exchanger sector. Full article

Mediterranean water-stressed areas face significant challenges from higher temperatures and increasingly severe droughts. We assess the effect of climate change on rainfed barley production in the aridity-prone province of Almería, Spain, using the FAO AquaCrop model. We focus on rainfed barley growth by the mid-century (2041–2070) and end-century (2071–2100) time periods, using three Shared Socio-economic Pathway (SSP)-based scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Using the paired t-test, Spearman and Pearson correlation coefficient, Root Mean Squared Error, and relative Root Mean Squared Error, we verified AquaCrop’s ability to capture local multi-year trends (9 or more years) using standard barley crop parameters, without local recalibration. Starting with a reference Initial Soil Water Content (ISWC), different soil water contents within barley rooting depth were modelled to account for decreases in soil water availability. We then evaluated the efficiency of different climate adaptation strategies: irrigation, mulching, and changing sowing dates. We show average yield changes of +14% to −44.8% (mid-century) and +12% to −55.1% (end-century), with ISWC being the main factor determining yields. Irrigation increases yields by 21.1%, utilizing just 3% of Almería’s superficial water resources. Mulches improve irrigated yield performances by 6.9% while reducing irrigation needs by 40%. Changing sowing dates does not consistently improve yields. We demonstrate that regardless of the scenario used, climate adaptation of field barley production in Almería should prioritize limiting soil water loss by combining irrigation with mulching. This would enable farmers in Almería’s northern communities to maintain their livelihoods, reducing the province’s reliance on horticulture while continuing to contribute to food security goals. Full article

Accelerometers worn by animals produce distinct behavioral signatures, which can be classified accurately using machine learning methods such as random forest decision trees. The objective of this study was to identify accelerometer signal separation among parsimonious behaviors. We achieved this objective by (1) describing functional differences in accelerometer signals among discrete behaviors, (2) identifying the optimal window size for signal pre-processing, and (3) demonstrating the number of observations required to achieve the desired level of model accuracy,. Crossbred steers (Bos taurus indicus; n = 10) were fitted with GPS collars containing a video camera and tri-axial accelerometers (read-rate = 40 Hz). Distinct behaviors from accelerometer signals, particularly for grazing, were apparent because of the head-down posture. Increasing the smoothing window size to 10 s improved classification accuracy (p < 0.05), but reducing the number of observations below 50% resulted in a decrease in accuracy for all behaviors (p < 0.05). In-pasture observation increased accuracy and precision (0.05 and 0.08 percent, respectively) compared with animal-borne collar video observations. Full article

Japanese encephalitis virus (JEV) has a positive-sense single-stranded RNA genome and belongs to the genus Flavivirus of the family Flaviviridae. Persistent JEV infection was previously shown in pig blood cells, which act as a natural reservoir of this virus. We aimed to determine the pathogenicity factors involved in persistent JEV infection by analyzing the pathogenicity and genome sequences of a virus isolated from a persistent infection model. We established persistent JEV infections in cells by inoculating mouse fetus primary cell cultures with the Beijing-1 strain of JEV and then performing repeated infected cell passages, harvesting viruses after each passage while monitoring the plaque size over 100 generations. The virus growth rate was compared among Vero, C6/36, and Neuro-2a cells. The pathogenicity was examined in female ICR mice at several ages. Additionally, we determined the whole-genome sequences. The 134th Beijing-1-derived persistent virus (ME134) grew in Vero cells at a similar rate to the parent strain but did not grow well in C6/36 or Neuro-2a cells. No differences were observed in pathogenicity after intracerebral inoculation in mice of different ages, but the survival time was extended in older mice. Mutations in the persistent virus genomes were found across all regions but were mainly focused in the NS3, NS4b, and 3′NCR regions, with a 34-base-pair deletion found in the variable region. The short deletion in the 3′NCR region appeared to be responsible for the reduced pathogenicity and growth efficiency. Full article

The intelligent warehouse is a modern logistics management system that uses technologies like the Internet of Things, robots, and artificial intelligence to realize automated management and optimize warehousing operations. The multi-robot system (MRS) is an important carrier for implementing an intelligent warehouse, which completes various tasks in the warehouse through cooperation and coordination between robots. As an extension of reinforcement learning and a kind of swarm intelligence, MARL (multi-agent reinforcement learning) can effectively create the multi-robot systems in intelligent warehouses. However, MARL-based multi-robot systems in intelligent warehouses face serious safety issues, such as collisions, conflicts, and congestion. To deal with these issues, this paper proposes a safe MARL method based on runtime verification, i.e., an optimized safety policy-generation framework, for multi-robot systems in intelligent warehouses. The framework consists of three stages. In the first stage, a runtime model SCMG (safety-constrained Markov Game) is defined for the multi-robot system at runtime in the intelligent warehouse. In the second stage, rPATL (probabilistic alternating-time temporal logic with rewards) is used to express safety properties, and SCMG is cyclically verified and refined through runtime verification (RV) to ensure safety. This stage guarantees the safety of robots’ behaviors before training. In the third stage, the verified SCMG guides SCPO (safety-constrained policy optimization) to obtain an optimized safety policy for robots. Finally, a multi-robot warehouse (RWARE) scenario is used for experimental evaluation. The results show that the policy obtained by our framework is safer than existing frameworks and includes a certain degree of optimization. Full article

Heat transfer affects a motor’s sizing, its performance, and, ultimately, the overall vehicle’s range and endurance. However, the thermal literature does not have early-stage models for outrunner brushless DC (BLDC) motors found in small unmanned aerial systems (UASs). To address this gap, we have developed a non-dimensional heat transfer model (Nusselt correlation). Parametric experiments of four different-sized BLDC motors under load in Reynolds-matched wind tunnel tests generated data for model correlation. The motors’ aspect ratios (diameter/length) ranged from 0.9 to 1.5. The freestream Reynolds number of the axial flow over the motors ranged from 20,000 to 40,000. The rotational Reynolds number ranged from 10,000 to 20,000. The results showed that aspect ratio had the largest influence on heat transfer, followed by rotational and freestream Reynolds numbers. A steady-state model used the correlation to predict the motor’s ambient temperature differential within 10 K of experimental data. A case study applied the correlation to predict a hypothetical motor’s continuous torque in different environments. The correlation enables conceptual designers to capture thermally-driven trade-offs in early design stages and reduce costly revisions in later stages. Full article

The urban carbon footprint (UCF) is an important tool for assessing an organization’s ecological impacts and in guiding sustainability efforts. This calculation is usually measured in tons of carbon dioxide equivalent (CO₂-eq). Calculations provide important data to determine strategies to reduce the carbon footprint and establish sustainability targets. Various standards and protocols guide UCF calculation, and many organizations aim to make these data transparent to their stakeholders and the public. This study aims to calculate the UCF of Sarıçam Municipality (SM) in the Adana Province of Türkiye. This study includes the greenhouse gas emission inventories resulting from all activities of the SM main service building, guest house, construction site service building, Cultural Center service building, and additional service buildings between 1 January 2022 and 31 December 2022. The calculations include generator fuel consumption, electricity consumption, the refrigerant gas leaks and refills resulting from these activities, the fuel consumed in vehicles owned by the company or whose fuel consumption is under company control, emissions originating from personal travel, emissions originating from customers and visitors, emissions originating from business travel, purchases, etc. Emissions from products purchased and emissions from waste transportation are included. The findings show that, in 2022, the total UCF of SM was equal to 10,862.46 tons of CO₂-eq. The Paris Agreement aims to reduce the per capita emissions to approximately two tons of CO₂-eq by 2030. The carbon footprint per employee within the municipality was calculated at 12.43 tons of CO₂-eq, as derived from the analyzed data. The results reveal the importance of implementing sustainable practices and strategies within SM, such as energy efficiency measures, waste reduction, and the adoption of renewable energy sources, to mitigate its carbon footprint. This study plans to provide a basis for SM’s reduction efforts by keeping greenhouse gas emissions under control. Full article

The objective of the research is to develop novel materials that are both inexpensive and have a low density, while also being able to endure the transportation of γ-photons with low-to-medium energy levels. The outcome consisted of four epoxy resins that were strengthened with different quantities of heavy metallic waste. The density of the formed composites improved from 1.134 ± 0.022 g/cm³ to 1.560 ± 0.0312 g/cm³ when the waste content was raised from 0 to 40 weight percent. The theoretical investigation was determined using Monte Carlo (MCNP) simulation software, and the results of linear attenuation coefficient were justified experimentally in a low and medium energy range of 15–662 keV. The mass attenuation coefficient results in a low gamma energy range (15–122 keV) varied in between 3.175 and 0.159 cm²/g (for E-MW0 composite) and in between 8.212 and 0.164 cm²/g (for E-MW40 composite). The decrease in mass attenuation coefficient was detected in a medium gamma photon energy range (122–662 keV) with 0.123–0.082 cm²/g (for E-MW0 composite) and 0.121–0.080 cm²/g (for E-MW40 composite). The density of the enhanced composites influenced these parameters. As the metallic waste composition increased, the fabricated composites’ half-value thickness decreased. At 15 keV, the half-value thickness decreased from 0.19 to 0.05 cm. At 59 keV, it fell from 2.70 to 1.41 cm. At 122 keV, it fell from 3.90 to 2.72 cm. At 662 keV, it fell from 7.45 to 5.56 cm. This decrease occurred as the heavy metal waste concentration increased from 0 to 40 wt.%. The study indicates that as metallic waste concentrations rise, there is a rise in the effective atomic number and a decline in the buildup factors. Full article

Maternal type 2 diabetes mellitus (T2DM) has been shown to result in foetal programming of the hypothalamic–pituitary–adrenal (HPA) axis, leading to adverse foetal outcomes. T2DM is preceded by prediabetes and shares similar pathophysiological complications. However, no studies have investigated the effects of maternal prediabetes on foetal HPA axis function and postnatal offspring development. Hence, this study investigated the effects of pregestational prediabetes on maternal HPA axis function and postnatal offspring development. Pre-diabetic (PD) and non-pre-diabetic (NPD) female Sprague Dawley rats were mated with non-prediabetic males. After gestation, male pups born from the PD and NPD groups were collected. Markers of HPA axis function, adrenocorticotropin hormone (ACTH) and corticosterone, were measured in all dams and pups. Glucose tolerance, insulin and gene expressions of mineralocorticoid (MR) and glucocorticoid (GR) receptors were further measured in all pups at birth and their developmental milestones. The results demonstrated increased basal concentrations of ACTH and corticosterone in the dams from the PD group by comparison to NPD. Furthermore, the results show an increase basal ACTH and corticosterone concentrations, disturbed MR and GR gene expression, glucose intolerance and insulin resistance assessed via the Homeostasis Model Assessment (HOMA) indices in the pups born from the PD group compared to NPD group at all developmental milestones. These observations reveal that pregestational prediabetes is associated with maternal dysregulation of the HPA axis, impacting offspring HPA axis development along with impaired glucose handling. Full article

Over the years, tick-borne pathogens (TBPs) have garnered significant interest due to their medical, veterinary and economic importance. Additionally, TBPs have drawn attention to how these microorganisms interact with their own vectors, increasing the risk to human and animal infection of emerging and reemerging zoonoses. In this sense, ticks, which are obligate hematophagous ectoparasites, have a key role in maintaining and transmitting TBPs among humans and animals. The aim of this study was to assess the prevalence of neglected TBPs in mainland Portugal, namely Anaplasma spp., Babesia spp., Ehrlichia spp. and Neoehrlichia mikurensis. DNA fragments were detected in questing ticks collected from five different ecological areas under investigation. To the best of the authors’ knowledge, this study reports new worldwide findings, including B. bigemina infecting Ixodes frontalis, Ixodes ricinus and Rhipicephalus sanguineus sensu lato. Additionally, it presents new findings in Portugal of N. mikurensis infecting I. ricinus and of presumably Wolbachia endosymbionts being detected in I. ricinus. Overall, there were 208 tick samples that were negative for all screened TBPs. The results herein obtained raise concerns about the circulation of neglected TBPs in mainland Portugal, especially in anthropophilic ticks, highlighting the importance of adopting a One Health perspective. Full article

Accurate pavement surface crack detection is crucial for analyzing pavement survey data and the development of maintenance strategies. On the basis of Swin-Unet, this study develops the improved Swin-Unet (iSwin-Unet) model with the developed skip attention module and the residual Swin Transformer block. Based on the channel attention mechanism, the pavement crack region can be better captured while the crack feature channels can be assigned more weights. Taking advantage of the developed residual Swin Transformer block, the encoder architecture can globally model the pavement crack feature. Meanwhile, the crack feature information can be efficiently exchanged. To verify the pavement crack detection performance of the proposed model, we compare the training performance and visualization results with the other three models, which are Swin-Unet, Swin Transformer, and Unet, respectively. Three public benchmarks (CFD, Crack500, and CrackSC) have been adopted for the purpose of training, validation, and testing. Based on the test results, it can be found that the developed iSwin-Unet achieves a significant increase in mF1 score, mPrecision, and mRecall compared to the existing models, thereby establishing its efficacy in pavement crack detection and underlining its significant advancements over current methodologies. Full article

This retrospective multicenter study examines therapy-induced orbital and ocular MRI findings in retinoblastoma patients following selective intra-arterial chemotherapy (SIAC) and quantifies the impact of SIAC on ocular and optic nerve growth. Patients were selected based on medical chart review, with inclusion criteria requiring the availability of posttreatment MR imaging encompassing T2-weighted and T1-weighted images (pre- and post-intravenous gadolinium administration). Qualitative features and quantitative measurements were independently scored by experienced radiologists, with deep learning segmentation aiding total eye volume assessment. Eyes were categorized into three groups: eyes receiving SIAC (Rb-SIAC), eyes treated with other eye-saving methods (Rb-control), and healthy eyes. The most prevalent adverse effects post-SIAC were inflammatory and vascular features, with therapy-induced contrast enhancement observed in the intraorbital optic nerve segment in 6% of patients. Quantitative analysis revealed significant growth arrest in Rb-SIAC eyes, particularly when treatment commenced ≤ 12 months of age. Optic nerve atrophy was a significant complication in Rb-SIAC eyes. In conclusion, this study highlights the vascular and inflammatory adverse effects observed post-SIAC in retinoblastoma patients and demonstrates a negative impact on eye and optic nerve growth, particularly in children treated ≤ 12 months of age, providing crucial insights for clinical management and future research. Full article

Microbes frequently experience nutrient deprivations in the natural environment and may enter dormancy. Aggregatibacter actinomycetemcomitans is known to establish long-term infections in humans. This study examined the dormancy-like phenotype of an A. actinomycetemcomitans strain D7S-1 and its isogenic smooth-colony mutant D7SS. A tissue culture medium RPMI-1640 was nutrient-deficient (ND) and unable to support A. actinomycetemcomitans growth. RPMI-1640 amended with bases was nutrient-limited (NL) and supported limited growth of A. actinomycetemcomitans less than the nutrient-enriched (NE) laboratory medium did. Strain D7S-1, after an initial 2-log reduction in viability, maintained viability from day 4 to day 15 in the NL medium. Strain D7SS, after 1-log reduction in viability, maintained viability from day 3 to day 5. In contrast, bacteria in the NE medium were either non-recoverable (D7S-1; >6-log reduction) or continued to lose viability (D7SS; 3-log reduction) on day 5 and beyond. Scanning and transmission electron microscopy showed that A. actinomycetemcomitans in the NL medium formed robust biofilms similar to those in the NE medium but with evidence of stress. A. actinomycetemcomitans in the ND medium revealed scant biofilms and extensive cellular damage. We concluded that A. actinomycetemcomitans grown in the NL medium exhibited a dormancy-like phenotype characterized by minimum growth, prolonged viability, and distinct cellular morphology. Full article

Background: The assessment information of tumor margins is extremely important for the success of the breast cancer surgery and whether the patient undergoes a second operation. However, conducting surgical margin assessments is a time-consuming task that requires pathology-related skills and equipment, and often cannot be provided in a timely manner. To address this challenge, digital breast tomosynthesis technology was utilized to generate detailed cross-sectional images of the breast tissue and integrate deep learning algorithms for image segmentation, achieving an assessment of tumor margins during surgery. Methods: this study utilized post-operative tissue samples from 46 patients who underwent breast-conserving treatment, and generated image sets using digital breast tomosynthesis for the training and evaluation of deep learning models. Results: Deep learning algorithms effectively identifying the tumor area. They achieved a Mean Intersection over Union (MIoU) of 0.91, global accuracy of 99%, weighted IoU of 44%, precision of 98%, recall of 83%, F1 score of 89%, and dice coefficient of 93% on the training dataset; for the testing dataset, MIoU was at 83%, global accuracy at 97%, weighted IoU at 38%, precision at 87%, recall rate at 69%, F1 score at 76%, dice coefficient at 86%. Conclusions: The initial evaluation suggests that the deep learning-based image segmentation method is highly accurate in measuring breast tumor margins. This helps provide information related to tumor margins during surgery, and by using different datasets, this research method can also be applied to the surgical margin assessment of various types of tumors. Full article

As the LCOE for photovoltaics has decreased several times, it is once again gaining popularity. The intensification of the development of PV installations is contributing to the duck curve phenomenon in an increasing number of countries and, consequently, affecting current electricity prices. Decisions on new investments in large-scale PV sources are driven by potential economic and environmental effects, and these, in turn, are subject to locational considerations, both as to the country and its region. In calculating the economic impact of locating a 1 MWp PV farm, it was assumed that the electricity generated by the farm would be fed into the national grid, and that the life of the PV farm would be 20 years. Poland was considered as an example country for the placement of a photovoltaic farm. The authors of this paper proposed that the main verification parameter is the availability of connection capacities to feed the produced electricity into the country’s electricity grid. The methodology proposed by the authors for the selection of the location of a PV farm consists of four steps: step (i) identification and selection of the administrative division of a given country; step (ii) verification of available connection capacities; step (iii) (two stages) verification of other factors related to the location of the PV farm (e.g., information on land availability and the distance of the land from the substation), and analysis of productivity at each potential location and electricity prices achieved on the power exchange; step (iv) economic analysis of the investment—analyses of PV farm energy productivity in monetary terms on an annual basis, cost analysis (CAPEX, OPEX) and evaluation of economic efficiency (DPP, NPV, IRR). The greatest impact on the economic efficiency of a PV project is shown by the value of land (as part of CAPEX), which is specific to a given location, and revenues from energy sales, which are pretty similar for all locations. Full article

The theoretical basis for the Eddy Damped Markovian Anisotropic Closure (EDMAC) is formulated for two-dimensional anisotropic turbulence interacting with Rossby waves in the presence of advection by a large-scale mean flow. The EDMAC is as computationally efficient as the Eddy Damped Quasi Normal Markovian (EDQNM) closure, but, in contrast, is realizable in the presence of transient waves. The EDMAC is arrived at through systematic simplification of a generalization of the non-Markovian Direct Interaction Approximation (DIA) closure that has its origin in renormalized perturbation theory. Markovian Anisotropic Closures (MACs) are obtained from the DIA by using three variants of the Fluctuation Dissipation Theorem (FDT) with the information in the time history integrals instead carried by Markovian differential equations for two relaxation functions. One of the MACs is simplified to the EDMAC with analytical relaxation functions and high numerical efficiency, like te EDQNM. Sufficient conditions for the EDMAC to be realizable in the presence of Rossby waves are determined. Examples of the numerical integration of the EDMAC compared with the EDQNM are presented for two-dimensional isotropic and anisotropic turbulence, at moderate Reynolds numbers, possibly interacting with Rossby waves and large-scale mean flow. The generalization of the EDMAC for the statistical dynamics of other physical systems to higher dimension and higher order nonlinearity is considered. Full article

Environmental pollution stands as one of the significant global challenges we face today. Polycyclic aromatic hydrocarbons (PAHs), a class of stubborn organic pollutants, have long been a focal point of bioremediation research. This study aims to explore the impact and mechanisms of graphene oxide (GO) on the phytoremediation effectiveness of PAHs. The results underscore the significant efficacy of GO in accelerating the degradation of PAHs. Additionally, the introduction of GO altered the diversity and community structure of endophytic bacteria within the roots, particularly those genera with potential for PAH degradation. Through LEfSe analysis and correlation studies, we identified specific symbiotic bacteria, such as Mycobacterium, Microbacterium, Flavobacterium, Sphingomonas, Devosia, Bacillus, and Streptomyces, which coexist and interact under the influence of GO, synergistically degrading PAHs. These bacteria may serve as key biological markers in the PAH degradation process. These findings provide new theoretical and practical foundations for the application of nanomaterials in plant-based remediation of polluted soils and showcase the immense potential of plant–microbe interactions in environmental restoration. Full article

Background: Alzheimer’s disease (AD) presents a significant global health concern, characterized by neurodegeneration and cognitive decline. Neuroinflammation is a crucial factor in AD development and progression, yet effective pharmacotherapy remains elusive. Sulforaphane (SFN), derived from cruciferous vegetables and mainly from broccoli, has shown a promising effect via in vitro and in vivo studies as a potential treatment for AD. This study aims to investigate the possible prophylactic mechanisms of SFN against prefrontal cortex (PFC)-related recognition memory impairment induced by lipopolysaccharide (LPS) administration. Methodology: Thirty-six Swiss (SWR/J) mice weighing 18–25 g were divided into three groups (n = 12 per group): a control group (vehicle), an LPS group (0.75 mg/kg of LPS), and an LPS + SFN group (25 mg/kg of SFN). The total duration of the study was 3 weeks, during which mice underwent treatments for the initial 2 weeks, with daily monitoring of body weight and temperature. Behavioral assessments via novel object recognition (NOR) and temporal order recognition (TOR) tasks were conducted in the final week of the study. Inflammatory markers (IL-6 and TNF), antioxidant enzymes (SOD, GSH, and CAT), and pro-oxidant (MDA) level, in addition to acetylcholine esterase (AChE) activity and active (caspase-3) and phosphorylated (AMPK) levels, were evaluated. Further, PFC neuronal degeneration, Aβ content, and microglial activation were also examined using H&E, Congo red staining, and Iba1 immunohistochemistry, respectively. Results: SFN pretreatment significantly improved recognition memory performance during the NOR and TOR tests. Moreover, SFN was protected from neuroinflammation and oxidative stress as well as neurodegeneration, Aβ accumulation, and microglial hyperactivity. Conclusion: The obtained results suggested that SFN has a potential protective property to mitigate the behavioral and biochemical impairments induced by chronic LPS administration and suggested to be via an AMPK/caspase-3-dependent manner. Full article

Medulloblastomas (MBs) represent the most prevalent malignant solid tumors in kids. The conventional treatment regimen for MBs includes surgical removal of the tumor, followed by radiation and chemotherapy. However, this approach is associated with significant morbidity and detrimental side effects. Consequently, there is a critical demand for more precise and less harmful treatments to enhance the quality of life for survivors. CEP-18770, a novel proteasome inhibitor that targets the 20S subunit, has emerged as a promising candidate, due to its anticancer activity in metastatic solid tumors and multiple myeloma, coupled with an acceptable safety profile. In this study, we aimed to assess the anticancer efficacy of CEP-18770 by employing a variety of MB patient-derived cells and cell lines. Our preclinical investigations revealed that CEP-18770 effectively inhibits proteasome activity and induces apoptosis in MBs cells. Furthermore, we discovered that CEP-18770 and cisplatin, a current component of MB therapy, exhibit a synergistic apoptotic effect. This paper shows that CEP-18770 holds potential as an adjunctive treatment for MB tumors, thereby paving the way for more targeted and less toxic therapeutic strategies. Full article

The unprecedented reductions in anthropogenic emissions over the COVID-19 lockdowns were utilised to investigate the response of ozone (O₃) concentrations to changes in its precursors across various UK sites. Ozone, volatile organic compounds (VOCs) and NO_x (NO+NO₂) data were obtained for a 3-year period encompassing the pandemic period (January 2019–December 2021), as well as a pre-pandemic year (2017), to better understand the contribution of precursor emissions to O₃ fluctuations. Compared with pre-lockdown levels, NO and NO₂ declined by up to 63% and 42%, respectively, over the lockdown periods, with the most significant changes in pollutant concentrations recorded across the urban traffic sites. O₃ levels correspondingly increased by up to 30%, consistent with decreases in the [NO]/[NO₂] ratio for O₃ concentration response. Analysis of the response of O₃ concentrations to the NO_x reductions suggested that urban traffic, suburban background and suburban industrial sites operate under VOC-limited regimes, while urban background, urban industrial and rural background sites are NO_x-limited. This was in agreement with the [VOC]/[NO_x] ratios determined for the London Marylebone Road (LMR; urban traffic) site and the Chilbolton Observatory (CO; rural background) site, which produced values below and above 8, respectively. Conversely, [VOC]/[NO_x] ratios for the London Eltham (LE; suburban background) site indicated NO_x-sensitivity, which may suggest the [VOC]/[NO_x] ratio for O₃ concentration response may have had a slight NO_x-sensitive bias. Furthermore, O₃ concentration response with [NO]/[NO₂] and [VOC]/[NO_x] were also investigated to determine their relevance and accuracy in identifying O₃-NO_x-VOC relationships across UK sites. While the results obtained via utilisation of these metrics would suggest a shift in photochemical regime, it is likely that variation in O₃ during this period was primarily driven by shifts in oxidant (OX; NO₂ + O₃) equilibrium as a result of decreasing NO₂, with increased O₃ transported from Europe likely having some influence. Full article

Background: In an era of dramatic technological progress, the consequent economic transformations, and an increasing need for an adaptable workforce, the importance of education has risen to the forefront of the social discourse. The concurrent increase in the awareness of issues pertaining to social justice and the debate over what this justice entails and how it ought to be effected, feed into the education policy more than ever before. From the nexus of the aforementioned considerations, concern about the so-called education gap has emerged, with worldwide efforts to close it. Methods: I analyze the premises behind such efforts and demonstrate that they are founded upon fundamentally flawed ideas. Results: I show that in a society in which education is delivered equitably, education gaps emerge naturally as a consequence of differentiation due to talents, the tendency for matched mate selection, and the heritability of intellectual traits. Conclusion: I issue a call for a redirection of efforts away from the ill-founded idea of closing the education gap to the understanding of the magnitude of its unfair contributions, as well as to those social aspects that can modulate it in accordance with what a society deems fair according to its values. Full article

This paper considers the problem of admissibility and admissibilization of 2D singular continuous systems described by the Roesser model. A necessary and sufficient admissibility condition is first proposed for 2D singular continuous systems in terms of a strict Linear Matrix Inequality (LMI). Then, a necessary and sufficient condition is established for the closed-loop system to be admissible (i.e., stable, regular, and impulse-free). Moreover, the stability condition is completed to give a sufficient condition to ensure a specified H_∞ disturbance attenuation level for the state feedback closed loop. To illustrate the effectiveness of the proposed methodology, a numerical example is given to illustrate an admissibilization of a state feedback closed-loop system. Full article