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Wildfires represent a critical environmental and social challenge, with long-term implications for human health, ecosystems, and infrastructure. This complex issue is exacerbated by various factors, including socioeconomic changes, unsustainable practices in agro-forestry land management, and the intensification of extreme weather events. The complexity of fire management in Italy necessitates effective governance mechanisms and planning tools at both regional and national levels. This study looks at successful prevention strategies, such as prescribed burning and proactive land management, while also addressing existing governance challenges, such as coordination among relevant institutions and the need for stronger regulatory frameworks. In addition to providing insights into the current state of fire governance and proposing practical solutions, we suggest that more resilient and sustainable fire management practices, already successfully implemented in some regions, should be adopted nationwide in Italy.

Concrete is a prominent construction material globally, owing to its reputed attributes such as robustness, endurance, optimal functionality, and adaptability. Formulating concrete mixtures poses a formidable challenge, mainly when introducing novel materials and additives and evaluating diverse design resistances. Recent methodologies for projecting concrete performance in fundamental aspects, including compressive strength, flexural strength, tensile strength, and durability (encompassing homogeneity, porosity, and internal structure), exist. However, actual approaches need more diversity in the materials and properties considered in their analyses.This dataset outlines the outcomes of an extensive 10-year laboratory investigation into concrete materials involving mechanical tests and non-destructive assessments within a comprehensive dataset denoted as ConcreteXAI. This dataset encompasses evaluations of mechanical performances and non-destructive tests. ConcreteXAI integrates a spectrum of analyzed mixtures comprising twelve distinct concrete formulations incorporating diverse additives and aggregate types. The dataset encompasses 18,480 data points, establishing itself as a cutting-edge resource for concrete analysis.ConcreteXAI acknowledges the influence of artificial intelligence techniques in various science fields. Emphatically, deep learning emerges as a precise methodology for analyzing and constructing predictive models. ConcreteXAI is designed to seamlessly integrate with deep learning models, enabling direct application of these models to predict or estimate desired attributes. Consequently, this dataset offers a resourceful avenue for researchers to develop high-quality prediction models for both mechanical and non-destructive tests on concrete elements, employing advanced deep learning techniques.

This study takes a unique approach, using satellite remote sensing to analyze the land surface temperature (LST) in seven coastal cities located at latitudes between 18° and 22° and longitudes between 106° and 91°. The methodology consists of obtaining the LST on two selected days, one in July 2019 and one in July 2020, to determine how the temperature was modified by the atypical mobility caused by Coronavirus Disease 2019 (COVID-19) and social distancing. Using these data, we determine the representative surface temperature that tended to rise (RHST) and the representative surface temperature that tended to decrease (RLST), depending on the affected area. This approach allows us to comprehensively compare how mobility modified the four variables studied: territorial extension, population, types of soil (paving), and vegetation. We concluded that, among the factors analyzed, the types of paving and vegetation were those that generated a more significant decrease in temperature; the variables of territorial extension and the number of inhabitants had a smaller impact. This study paves the way for a discussion of the significant influence of mobility on the behavior of the LST.

Slaked lime is traditionally a suitable material for use in construction activities in historic and traditional buildings whose constitutive characteristics demand compatible and appropriate material solutions. Therefore, knowing the physical and mechanical characterization of lime pastes and mortars for use in restoration is considered an important step in the process of scientific development of a material that, in the Mexican case, has lacked scientific rigor in its production, use and commercialization. With this in mind, the present article aims to investigate the characteristics of lime pastes and mortars that have been used in the traditional way and the new limes that exist in the market, offering suitable options for restoration, for which an integrated methodology was used consisting of physical tests such as surface area, electrical resistivity, pulse velocity, colorimetry, and mechanical tests such as compressive strength, giving as a result that “traditional slaked” lime is more likely to deteriorate than powdered lime, which leads us to conclude that powdered hydrated lime has optimal characteristics for restoration activities.

The State of Michoacan has a wide and rich architectural heritage which is represented by different vernacular typologies which employ different materials and techniques according to the local resources. However, this wide knowledge and cultural heritage are disappearing, with several monuments and buildings being abandoned due to new dynamics and social changes. The traditional techniques have been substituted for modern and industrial construction systems since they are associated with obsolete ways of life. Through international cooperation for development and research projects, many activities were carried out to analyze the durability of local materials and vernacular constructions of the state. The main ones included the architectural survey and inspection of these buildings, photographic and drone surveys, characterization in the laboratory and oral interviews with local users. During the field work, these interviews with the local population, the creation of multimedia content and the use of audiovisual methods had crucial importance in the documentation of this local knowledge and culture, being great methods for scientific communication and dissemination. The main product is the documentary Xirangua, which means ‘roots’ in the Purépecha language, the main indigenous ethnicity in the state. This documentary explores the traditional architecture and construction of Michoacan, showing the reality within the loss of this vernacular heritage and portraying the importance of its conservation through the perspective of the local population, users and artisans. The use of these audiovisual techniques has demonstrated to be a suitable option to promote and preserve cultural heritage and educate, include the local actors in the process, and make the general public aware of the current issues, with this being one of the first works which explores this approach.

Abstract Background Strongyloides stercoralis is widespread; however, there is limited information on its prevalence owing to laboratory underestimation and low clinical manifestations. The Baermann method and agar culture stand out among the parasitological techniques. Strongyloides stercoralis is present in Bolivia, but its prevalence in children remains unknown. The objective of this study was to estimate the applicability of simple parasitological techniques to increase the detection of this parasite in children living in the tropics. Methods This cross-sectional study was conducted in a tropical village in Cochabamba, Bolivia. Participants were 304 children aged 5 – 12 years who provided stool samples for different parasitological analyses (direct examination, Ritchie, Baermann, and Dancescu techniques), and their parents provided informed consent. Results Up to 64.8% of pathogenic parasites were detected using the modified Ritchie method. The Baermann technique identified 17.8% of Strongyloides stercoralis cases, and a high sensitivity with respect to the Baermann technique was only for the Dancescu technique (75.9%) that is also specific for Strongyloides stercoralis, followed by 66.7% for the modified Ritchie technique, which is used in second-line care. Discussion The Baermann technique is the best parasitological option for improving Strongyloides stercoralis diagnosis in the first-line care of the Primary Health Care System. A particular cycle of reinfection, combined with the environment and some other risk factors are related with persistence. Control is difficult without a proper diagnosis, and the Baermann technique is an approach to the solution. We conclude that with a high suspicion of the presence of Strongyloides stercoralis, the use of the Baermann technique is strongly recommended as support for direct examination in primary health care systems especially in tropical areas.

This study examines representation of disabilities by conducting a qualitative content analysis of how 41 journalism/mass communication textbooks frame the ideal standards of verbal communication for media professionals. Textbooks are integral to students' understanding of professional norms and may influence career decisions. Results show that textbooks rarely address the topic of speech disabilities, describing them as "roadblocks to success." Instead, authors often address best practices in broadcast voicing and the value of projecting confidence in interviews and press conferences. What are the explicit and implicit messages for students with speech disabilities such as stuttering? We argue that such framing is a critical media literacy issue because it addresses media diversity and access.

The freight transport industry in Mexico has grown significantly since the establishment of trade agreements in North America, which has brought significant environmental consequences to the main transport corridors. This paper proposes a methodology for the estimation of emissions for freight vehicles on road transportation corridors. The variables included in this analysis allow adequate characterization of the conditions of the vehicle fleet, the geometry and the quality of the road, the environment, and the average annual daily traffic (AADT) of heavy vehicles. The results were structured to show two indicators, the amount of CO2 emissions per kilometer and the amount of emissions per tonne transported. These results will allow establishing a baseline of CO2 emissions through which we can implement actions in the road transport sector to reduce greenhouse gases (GHG) to mitigate climate change and develop parameter values for use in Cost Benefit Analysis. The indicators can also be applied to geospatial modeling of emissions in road transport corridors and forecast its growth.

In this study new compounds consisting of activated carbon cloths (ACC) modified with calcium silicate (CaSiO3) were prepared for hydroxyapatite (HAP) generation. ACC samples were oxidized with 8 M HNO3 at different times (15 min and 2 h), to increase oxygenated functional groups. The CaSiO3 fine powders were prepared by chemical coprecipitation using Ca(NO3)2∙4H2O and Si(OC2H5)4, and 5 M NaOH was used as precipitant. The resulting powders were mixed with ethanol by ultrasound stirring and the previously oxidized activated carbon fibers were placed leaving under stirring for 30 min to allow particle dispersion. Once the formed compounds were dried, the samples were immersed in a simulated body fluid (SBF) solution for 21 days in conical tubes at 36.5 °C to allow the HAP formation on the ACC/CaSiO3 composite surface. The results indicated that the increase in oxidation time improves HAP formation on the surface from ACC/CaSiO3 compounds and this bioactive composite may be a potential material for bone regeneration.

Compacted Au@16-mph-16/DNA-AMOX (NSi) nanosystems were prepared from amoxicillin (AMOX) and precursor Au@16-mph-16 gold nanoparticles (Ni) using a Deoxyribonucleic acid (DNA) biopolymer as a glue. The synthesized nanocarrier was tested on different bacterial strains of Escherichia coli, Staphylococcus aureus, and Streptococcus pneumoniae to evaluate its effectiveness as an antibiotic as well as its internalization. Synthesis of the nanosystems required previous structural and thermodynamic studies using circular dichroism (CD) and UV-visible techniques to guarantee optimal complex formation and maximal DNA compaction, characteristics which facilitate the correct uptake of the nanocarrier. Two nanocomplexes with different compositions and structures, denoted NS1 and NS2, were prepared, the first involving external Au@16-mph-16 binding and the second partial intercalation. The Ni and NSi nanosystems obtained were characterized via transmission electron microscopy (TEM), zeta potential, and dynamic light scattering (DLS) techniques to measure their charge, aggregation state and hydrodynamic size, and to verify their presence inside the bacteria. From these studies, it was concluded that the zeta potential values for gold nanoparticles, NS1, and NS2 nanosystems were 67.8, −36.7, and −45.1 mV. Moreover, the particle size distribution of the Au@16-mph-16 gold nanoparticles and NS2 nanoformulation was found to be 2.6 nm and 69.0 nm, respectively. However, for NS1 nanoformulation, a bimodal size distribution of 44 nm (95.5%) and 205 nm (4.5%) was found. Minimal inhibitory concentration (MIC) values were determined for the bacteria studied using a microdilution plates assay. The effect on Escherichia coli bacteria was notable, with MIC values of 17 µM for both the NS1 and NS2 nanosystems. The Staphylococcus aureus chart shows a greater inhibition effect of NS2 and NP2 in non-diluted wells, and clearly reveals a great effect on Streptococcus pneumoniae, reaching MIC values of 0.53 µM in more diluted wells. These results are in good agreement with TEM internalization studies of bacteria that reveal significant internalization and damage in Streptococcus pneumoniae. In all the treatments carried out, the antibiotic capacity of gold nanosystems as enhancers of amoxicillin was demonstrated, causing both the precursors and the nanosystems to act very quickly, and thus favoring microbial death with a small amount of antibiotic. Therefore, these gold nanosystems may constitute an effective therapy to combat resistance to antibiotics, in addition to avoiding the secondary effects derived from the administration of high doses of antibiotics.

Angela J Okragly,1 Katie Brannon Corwin,2 Marikka Elia,3 Dongmei He,3 Oliver Schroeder,3 Qing Zhang,3 Tatiyana Shiyanova,2 Stuart Bright,1 Sarah B Dicker,4 Lukasz Chlewicki,4 Stephanie ME Truhlar,3 Julian Davies,3 Chetan N Patel,2 Robert J Benschop1 1Immunology Research, Eli Lilly and Company, Indianapolis, IN, USA; 2BioTechnology Discovery Research, Eli Lilly and Company, Indianapolis, IN, USA; 3BioTechnology Discovery Research Eli Lilly and Company, San Diego, CA, USA; 4ADME, Eli Lilly and Company, Indianapolis, IN, USACorrespondence: Angela J OkraglyImmunology Research, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, 46285, USATel +1- 317-276-2839Email okragly_angela@lilly.comBackground: Interleukin-33 (IL-33) is an alarmin that is released following cellular damage, mechanical injury, or necrosis. It is a member of the IL-1 family and binds to a heterodimer receptor consisting of ST2 and IL-1RAP to induce the production of a wide range of cellular mediators, including the type 2 cytokines IL-4, IL-5 and IL-13. This relationship has led to the hypothesis that the IL-33/ST2 pathway is a driver of allergic disease and inhibition of the IL-33 and ST2 association could have therapeutic benefit.Methods: In this paper, we describe the selection of a phage antibody through the ability to bind human IL-33 and block IL-33/ST2 interaction. This hit antibody was then affinity matured by site-directed mutagenesis of the antibody complementarity-determining regions (CDRs). Further characterization of a fully human monoclonal antibody (mAb), torudokimab (LY3375880) included demonstration of human IL-33 neutralization activity in vitro with an NFκB reporter assay and IL-33 induced mast cell cytokine secretion assay, followed by an in vivo IL-33-induced pharmacodynamic inhibition assay in mice that used IL-5 production as the endpoint.Results: Torudokimab is highly specific to IL-33 and does not bind any of the other IL-1 family members. Furthermore, torudokimab binds human and cynomolgus monkey IL-33 with higher affinity than the binding affinity of IL-33 to ST2, but does not bind mouse, rat, or rabbit IL-33. Torudokimab’s half-life in cynomolgous monkey projects monthly dosing in the clinic.Conclusion: Due to torudokimab’s high affinity, its ability to completely neutralize IL-33 activity in vitro and in vivo, and the observed cynomolgus monkey pharmacokinetic properties, this molecule was selected for clinical development.Keywords: IL-33, Th2 immune response, monoclonal antibody

CDKL5 Deficiency Disorder (CDD) is a rare, X-linked dominant condition that causes a developmental and epileptic encephalopathy (DEE). The incidence is between ~ 1:40,000 and 1:60,000 live births. Pathogenic variants in CDKL5 lead to seizures from infancy and severe neurodevelopmental delay. During infancy and childhood, individuals with CDD suffer impairments affecting cognitive, motor, visual, sleep, gastrointestinal and other functions. Here we present the recommendations of international healthcare professionals, experienced in CDD management, to address the multisystem and holistic needs of these individuals. Using a Delphi method, an anonymous survey was administered electronically to an international and multidisciplinary panel of expert clinicians and researchers. To provide summary recommendations, consensus was set, a priori, as >70% agreement for responses. In the absence of large, population-based studies to provide definitive evidence for treatment, we propose recommendations for clinical management, influenced by this proposed threshold for consensus. We believe these recommendations will help standardize, guide and improve the medical care received by individuals with CDD.

Adobe masonry is one of the oldest construction systems still in use today, Mexico has an enormous cultural heritage with traditional adobe houses being very representative of the rural communities and their culture. The 2017 Puebla Earthquake on September 19th struck the country causing the loss, destruction, and damage of historic buildings in several Mexican states, with the traditional earthen dwellings being the most vulnerable structures to these events. The fast abandonment of the local materials and techniques entails further research regarding the characterization of these construction systems, therefore, reconstruction efforts first require the recovery of the construction technique. After the seismic events, adobe samples of the remaining adobe structures of Jojutla de Juarez were collected. This population was one of the most affected in all the country, and, because of the major losses suffered, the study was conducted to determine the material properties of the dwellings’ adobe shards and natural quarry clays of the region. The characterization included destructive and non-destructive tests, mineralogical and granulometry analyses, and composition of the adobe samples of the buildings, as well as the aggregates. As a novelty, the compressive strength of the pieces was tested by two methods: the traditional compression strength test and the point-load test, in order to obtain the indicative values and the correlation equations between both tests. From the formal analysis and the laboratory, it was observed that the adobes from Jojutla presented different compositions which combined with the building malpractices and alterations to the traditional systems caused unpredictable behavior during the earthquake. The conduction of point-load tests in situ, as a part of a complete characterization methodology, could be an alternative to study the mechanical properties of patrimonial or damaged building samples before its disappearance.

A simple synthesis of fluorescent carbon quantum dots from lemon juice is described to introduce advanced high-school students and undergraduate college students to nanoparticle synthesis and quantum dots. The synthesis is based on the carbonization of lemon juice using only a hot plate stirrer. Column chromatography is used to separate different carbon quantum dots according to their size. This laboratory experiment can be carried out within a 2 h laboratory course and introduces the students to (1) nanotechnology and nanoparticle synthesis, using safe and commonly available chemicals. Furthermore, (2) the concept of fluorescence can be visualized in an intriguing manner using a pocket UV lamp. (3) This experiment serves as an introduction into size-exclusion chromatography. (4) An insight into possible sensing applications is given by the specific fluorescence quenching with an iron(III) solution. The experiment has been tested with 80 students in 4 Swiss high schools, and the knowledge of the students was tested before and after the experiment with a questionnaire. The performance increased by 0.42 [plus or minus] 0.39 on a grading scale of 1 to 6. The calculated average effect size was 0.76, which is in the range of a medium- to large-effect size, indicating a favorable effect of the experiment on the nanoparticle knowledge of the students.

This study takes a unique approach, using satellite remote sensing to analyze the land surface temperature (LST) in seven coastal cities located at latitudes between 18° and 22° and longitudes between 106° and 91°. The methodology consists of obtaining the LST on two selected days, one in July 2019 and one in July 2020, to determine how the temperature was modified by the atypical mobility caused by Coronavirus Disease 2019 (COVID-19) and social distancing. Using these data, we determine the representative surface temperature that tended to rise (RHST) and the representative surface temperature that tended to decrease (RLST), depending on the affected area. This approach allows us to comprehensively compare how mobility modified the four variables studied: territorial extension, population, types of soil (paving), and vegetation. We concluded that, among the factors analyzed, the types of paving and vegetation were those that generated a more significant decrease in temperature; the variables of territorial extension and the number of inhabitants had a smaller impact. This study paves the way for a discussion of the significant influence of mobility on the behavior of the LST. [ABSTRACT FROM AUTHOR]

The design of flexible road pavements is a complex process as a result of the multiple variables that influence and interact in the models that allow the design of each layer. In recent years, a particular interest has been raised to ensure that climate is considered in pavement design due to temperature and precipitation that influence the deterioration of pavements, impacting their service life. This paper presents a critical review of flexible pavement design methods, from the first ones based on experience, such as empirical methods, to the most recent ones on mechanical–empirical methodologies, where, based on different principles, they determine the thicknesses of the layers that integrate the structure of a pavement to identify how these methods have included climate variables within their methodology. Through this review, it was identified that temperature is incorporated in the dynamic modulus of the asphalt mix, and precipitation and moisture are incorporated through the resilient modulus in the granular layers (base, subbase, and foundation soil or subgrade courses). As a result, it was identified that the most holistic way of integrating climate is through the Enhanced Integrated Climatic Model (EICM) from the Mechanistic–Empirical Pavement Design Guide (MEPDG). In many cases, climate is incorporated through parameters whose behavior is associated with temperature and precipitation but does not use the data of these climate variables directly from the project site. The practical incorporation of climate into design methods allows an increase in the certainty of results, ensuring additional climate-resilient pavement structures and increasing their durability and sustainability during their service life. [ABSTRACT FROM AUTHOR]

Surface biomass characterization plays a key role in wildfire management. It allows classifying vegetation fuels flammability for fire risk analysis, to define silvicultural prescriptions for fire hazard reduction, to plan prescribed burning, or to model fire behavior and its effects, such as greenhouse gas and pollutant emissions. To facilitate fuel classification and analysis of potential fire behavior and effects in Italy, we harmonized 634 measurements of surface wildland fuels from Alpine, temperate and Mediterranean environments. The dataset provides quantitative data for duff, fine dead fuels and downed woody material, live grasses and shrubs fuel components. Surface fuel data were harmonized by subdividing loads (Mg ha-1) to standard size classes for dead (0-6, 6-25 and 25-75 mm) and live (0-6, 6-25 mm) fuels, collecting percent cover and depth/height (cm) of the various fuel components, and classifying observations into 19 fuelbed categories. To ensure comparability with existing vegetation classification systems, we classified each observation according to the European Fuel Map, the Corine Land Cover classes (level IV), the European Forest Types, and the forest categories of the Italian National Forest Inventory. The dataset and a photo description of each fuelbed category are available as Supplementary material. This dataset is the first step to develop several products at the national scale such as: (i) fuel type classification and mapping; (ii) carbon stock and wildfire emission estimates; (iii) calibration of fuel models for the simulation of fire behavior and effects.

Seasonal influenza continues to be a major cause of illness and death. Vaccination is the most cost-effective prophylaxis to prevent the disease and it is particularly important for people who are at high risk of serious complications derived from influenza, especially for people ≥65 years. In Italy, the influenza vaccination program has been unsuccessful with low rates of uptake in people ≥65 years. We analyzed all the community ≥65 years of the Health Promoting Agency (HPA) of Brescia (northern Italy) to evaluate the propensity attitudes toward influenza vaccination among people ≥65 years in four consecutive seasonal influenza campaigns (from 2014/2015 to 2017/2018). Information about subjects were retrieved from administrative databases. Data from 952,822 records were analyzed. The prevalence of vaccinated subjects in the four campaigns was 38.6%, 33.7%, 37.7%, and 40.1%, respectively. Among vaccinated people, the frequencies of individuals aged 65–69.9 years were lower than the frequencies of those in the other age classes, with highest frequencies of vaccinated people in the 75–79.9 years age-class. Overall, males showed a slightly higher propensity to be vaccinated and the propensity toward vaccination increased with age in both genders. Suffering from a chronic disease increased the propensity to vaccination; hypertension had the highest impact on the propensity whereas suffering from vasculopathy has the opposite effect. The value of this study is the possibility to know the factors that might indicate a propensity to get an influenza vaccination and to consider a different approach to people ≥65 years with the characteristics indicating a lower propensity to vaccination.

There are many different ways to estimate whether a concrete structure will be suffering corrosion degradation as experimental processes and numerical estimations relied on theoretical equations. Nevertheless, these estimations require higher certainty and satisfactory estimation accuracy. Deep Learning is causing profound changes in society. It has inspired unprecedented advances in historically challenging problems. This paper proposes a mathematician approach. A Deep Learning model capable of classifying the risk of corrosion on concrete specimens relied on a standard methodology. It employs the Electrical resistivity measurement for achieving this goal. The deep neural network architecture presented in this study displays a merging of activation functions. Also, a regularized method to avoid overfitting problems was implemented. The model comprises different standard tests as input data and classification of the corrosion risk as output. The outcomes depict an accuracy of about 98%, given the nature of the stochastic learning algorithm. Different concrete samples were analyzed in this research in order to provide data variety to the algorithm and accomplish a robust and stable model.