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In this systematic review, we aimed to identify the impact of the COVID-19 pandemic on children/adolescents with a diagnosis of autism spectrum disorder (ASD). The protocol was registered on PROSPERO CRD42021255848. Articles were selected from PubMed, Embase, and LILACS according to these characteristics: patients from zero to 18 years old, exposed to the COVID-19 pandemic, impact on social communication/interaction and restricted/repetitive behavior domains. The Newcastle-Ottawa Scale was used to assess methodological quality and the risk of bias. Of the 351 articles initially identified, 26 were finally included with information on 8,610 patients. Although the studies were heterogeneous, they indicated that the pandemic-related issues experienced by patients with ASD were mostly manifested in their behavior and sleep patterns.

An earlier study of ours investigating the effect of dietary lipid levels on the choline requirement of Atlantic salmon showed increasing severity of intestinal steatosis with increasing lipid levels. As choline is involved in epigenetic regulation by being the key methyl donor, pyloric caeca samples from the study were analysed for epigenetic effects of dietary lipid and choline levels. The diets varied in lipid levels between 16% and 28%, and choline levels between 1.9 and 2.3 g/kg. The diets were fed for 8 weeks to Atlantic salmon of 25 g of initial weight. Using reduced representation bisulfite sequencing (RRBS), this study revealed that increasing dietary lipid levels induced methylation differences in genes involved in membrane transport and signalling pathways, and in microRNAs important for the regulation of lipid homoeostasis. Increasing choline levels also affected genes involved in fatty acid biosynthesis and transport, lipolysis, and lipogenesis, as well as important immune genes. Our observations confirmed that choline is involved in epigenetic regulation in Atlantic salmon, as has been reported for higher vertebrates. This study showed the need for the inclusion of biomarkers of epigenetic processes in studies that must be conducted to define optimal choline levels in diets for Atlantic salmon.

Nowadays, the scientific community and industry are increasingly pressed to provide solutions for developing compact and highly-performing trace-gas sensors for several applications of crucial importance, such as environmental monitoring or medical diagnostics. In this context, this work describes a novel configuration, making use of a mid-IR spectrophone combining the compactness of a photo-acoustic setup, a non-conventional micro-electro-mechanical (MEMS) acousto-to-voltage transducer, and the sensitivity enhancement given by a cost-effective and easy-to-build dual-tube resonator configuration. In the optimal condition of sample pressure, the system developed in this work can achieve a minimum detection limit (MDL) equal to 0.34 ppb when averaging up to 10 s. Compared with previous literature of single-pass photoacoustic-based sensors for N2O, this corresponds to a significant improvement both for the achieved normalized noise equivalent absorption coefficient (NNEA) equal to 1.41 × 10−9 cm−1WHz−1/2, and for a Noise-Equivalent-Concentration (NEC) of 1 ppb obtained at 1 s of averaging time.

Este texto presenta los resultados de un proyecto de investigación que explora la fundamentación epistemológica de la Educación Religiosa Escolar (ERE) en Colombia a partir de la pregunta por el λόγος de los “estudios de la religión”. El problema central radica en cómo armonizar la ERE con la formación integral, evitando el proselitismo religioso en las instituciones educativas del país. Para abordar este desafío, se ha adoptado un enfoque cualitativo, utilizando un método de arqueología transmedia con una perspectiva epistemológica hermenéutica. Este enfoque permite analizar críticamente cómo los principios racionales de los estudios de la religión pueden contribuir a la construcción de una ERE que fomente el cultivo del sentido de la vida, la apertura a la trascendencia, una conciencia profunda de las convicciones y el desarrollo de un horizonte pluralista e intercultural. Como resultado, se espera evidenciar criterios pedagógicos que apoyen una ERE que esté alineada con los principios del respeto a la diversidad, proporcionando así un marco más holístico para su implementación en Colombia. En conclusión, se busca proponer una reflexión crítica y situada sobre la racionalidad de los estudios de la religión como un aporte significativo a los procesos educativos del país.

The urban heat island effect exacerbates the vulnerability of cities to climate change, emphasizing the need for sustainable urban planning driven by data evidence. In the last decade, the Local Climate Zone (LCZ) model emerged as a key tool for categorizing urban landscapes, aiding in the development of urban temperature mitigation strategies. In this work, the contribution of hyperspectral satellite imagery to LCZ mapping, leveraging the Italian Space Agency (ASI)’s PRISMA satellite, is investigated. Mapping performances are compared with traditional multispectral-based LCZ mapping using Sentinel-2 satellite imagery. The Random Forest algorithm is utilized for LCZ classification, with evaluation conducted through spectral separability analysis and accuracy assessment between PRISMA and Sentinel-2 derived LCZ maps as well as with the benchmark LCZ Generator mapping tool. An initial experiment on the effect of PRISMA image pan-sharpening on LCZ spectral separability is also presented. Results obtained for Milan (Northern Italy) demonstrate the potential of hyperspectral imagery in enhancing LCZ identification compared to multispectral data, with promising improvements in LCZ maps overall accuracy. Finally, air temperature patterns within each LCZ class are explored, qualitatively confirming the influence of urban morphology on thermal comfort.

Objetivo: asociar variables sociodemográficas con la autopercepción de los usuarios de la atención primaria de salud. Método: estudio transversal, con 222 usuarios de los servicios odontológicos de 15 unidades de atención primaria de un municipio de tamaño mediano de Rio Grande do Sul, Brasil. Se utilizaron cuestionarios con perfil sociodemográfico, la autopercepción y el Primary Care Assessment Tool Brasil salud bucal. Para comparaciones de las puntuaciones pruebas t-Student para grupos independientes y ANOVA (one way) – Post Hoc Sheffé. Resultados: usuarios con menor ingreso familiar (p=0,016) menor escolaridad (p=0,027) y que necesitaban hacer o cambiar la prótesis dental (p=0,020) obtuvieron asociación significativa en el atributo utilización de los servicios. En cuanto a la accesibilidad, las variables dolor de dientes (p=0,021) y satisfacción con la salud bucal (p

Objective: To associate sociodemographic variables with the self-perception of primary health care users. Method: Cross-sectional study with 222 users of dental services from 15 primary care units in a medium-sized city in Rio Grande do Sul, Brazil. Questionnaires with sociodemographic profile, self-perception, and the Primary Care Assessment Tool Brasil oral health were used. For comparisons of t-Student test scores for independent groups and ANOVA (one way) – Post Hoc Sheffé. Results: Users with lower family income (p=0.016), lower education (p=0.027), and who needed to make or replace dental prostheses (p=0.020) showed a significant association in the attribute of service utilization. Regarding accessibility, the variables toothache (p=0.021) and satisfaction with oral health (p

Objetivo: associar variáveis sociodemográficas com a autopercepção de usuários da atenção primária à saúde. Método: estudo transversal, com 222 usuários dos serviços odontológicos de 15 unidades de atenção primária de município de médio porte do Rio Grande do Sul, Brasil. Foram utilizados questionários com perfil sociodemográfico, a autopercepção e o Primary Care Assessment Tool Brasil saúde bucal. Para comparações dos escores testes t-Student para grupos independentes e ANOVA (one way) – Post Hoc Sheffé. Resultados: usuários com menor renda familiar (p=0,016) menor escolaridade (p=0,027) e que precisavam fazer ou trocar a prótese dentária (p=0,020) obtiveram associação significativa no atributo utilização dos serviços. Quanto à acessibilidade, as variáveis dor de dente (p=0,021) e satisfação com a saúde bucal (p

The achievable sensitivity level of photo-acoustic trace-gas sensors essentially depends on the performances of the acoustic transducer. In this work, the mechanical response of different silicon-based micro-electro-mechanical systems (MEMS) is characterized, aiming at investigating both their mechanical properties, namely the resonance frequency and the quality factor, and the minimum detection limit (MDL) achievable when they are exploited as an acoustic-to-voltage transducer in a trace-gas photoacoustic setup. For this purpose, a 4.56µm Continuous-Wave (CW) quantum cascade laser (QCL) is used to excite a strong N2O roto-vibrational transition with a line strength of 2.14 × 10−19 cm/molecule, and the detection of MEMS oscillations is performed via an interferometric readout. As a general trend, the minimum detection limit decreases when the resonance frequency investigated increases, achieving a value of 15 parts per billion with a 3 dB cut-off lock-in bandwidth equal to 100 mHz, around 10 kHz.

The BLOOM Large Language Model is a cuttingI think that the authors’ way of doing self-training is quite interesting. I suggest writing about self-training in the abstract and generally expose self-training as one of the paper’s contributions.-edge open linguistic model developed to provide computers with natural language understanding skills. Despite its remarkable capabilities in understanding natural language by capturing intricate contextual relationships, the BLOOM model exhibits a notable limitation concerning the number of included languages. In fact, Italian is not included among the languages supported by the model, making its use challenging in this context. Within this study, we explore the language adaptation strategy based on continuing training on language-specific data. Moreover, we fine-tune both the BLOOM and the adapted models on several instruction datasets and different downstream classification tasks over EVALITA datasets. It has been observed that language adaptation followed by instruction-based fine-tuning is shown to be effective in correctly addressing a task never seen by the model in a new language learned on language-specific data.

In the last decade, several methods have been developed for Local Climate Zone (LCZ) mapping, encompassing Remote Sensing and Geographic Information Systems (GIS) −based procedures. Combined approaches have also been proposed to compensate for intrinsic limitations that characterized their separate application. Recent work has disclosed the potential of hyperspectral satellite imagery for improving LCZ identification. However, the use of hyperspectral data for LCZ mapping is yet to be fully unfolded. A combined Remote Sensing and GIS-based method for LCZ mapping is proposed to exploit the integration of hyperspectral PRISMA and multispectral Sentinel-2 images with ancillary urban canopy parameter layers. Random Forest algorithm is applied to the feature sets to obtain the LCZ classification. The method is tested on the Metropolitan City of Milan (Italy), for the period from February to August 2023. A spectral separability analysis is carried out to investigate the improvement in LCZ identification using PRISMA in comparison to Sentinel-2 data, as well as improvements in LCZ spectral separability on PRISMA pan-sharpened images. The resulting maps’ quality is evaluated by extracting accuracy metrics and performing inter-comparisons with maps computed from the LCZ Generator benchmark tool. Inter-comparisons yield promising results with a mean Overall Accuracy increase of 16% using PRISMA for each LCZ class. Furthermore, we find that PRISMA improves the detection of LCZs compared to Sentinel-2, with a mean Overall Accuracy increase of 5%, in line with the higher spectral separability of PRISMA spectral signatures computed on the training samples.

Climate change poses a significant threat to humans and biodiversity, impacting various aspects of livelihoods, infrastructure, and ecosystems. Understanding climate change and its interaction with the environment is crucial for achieving Sustainable Development Goals. Local Climate Zones (LCZ) play a key role in comprehending climate change by categorizing urban areas also based on their thermal characteristics. This study presents prototype open-source software tools developed to integrate ground and satellite data for LCZ analysis in the Metropolitan City of Milan (Northern Italy). These tools consist of a QGIS plugin to access and preprocess ground-based meteorological sensor data and a client-server platform, based on the Open Data Cube and Docker technologies, for the exploitation of multispectral and hyperspectral satellite data in LCZ mapping and analysis. The tools’ architecture, data retrieval methods, and analysis capabilities are described in detail. The QGIS plugin facilitates the access and preprocessing of ground-based sensor data within the user-friendly QGIS environment. The platform enables seamless ground-sensor and satellite data management and analysis, using Jupyter Notebooks as an interface to support programmatic operations on the data. The proposed tools provide a framework for studying climate change and its local impacts on urban environments, with the potential of empowering users to effectively analyze and mitigate its effects.

Rapid urbanization and climate change are intensifying the urban heat island (UHI) phenomenon across cities worldwide. There is a pressing need to implement evidence-based mitigation and adaptation strategies as well as to develop tools for effectively measuring the impact of such actions on UHI patterns. In this context, the Local Climate Zone (LCZ) concept is a well-established classification system commonly used for the assessment of UHI. With this in mind, we present here the LCZ-ODC project aiming to develop a methodology for LCZ mapping in the Metropolitan City of Milan (northern Italy) by leveraging multiple geospatial data and cutting-edge software tools, including the Open Data Cube (ODC). A key aim of the project is to develop user-oriented solutions facilitating the exploitation of the generated LCZ maps for different application tasks. In this paper, we first present a brief overview of the methodologies and data sources used in the literature for LCZ mapping. Then, we introduce the LCZ-ODC project, with a focus on the end-user requirements which were gathered through a questionnaire distributed to a sample of potential stakeholders. The primary objective of the survey was to collect insights and consolidate requirements related to the key features of LCZ maps that will be produced within the project. The outcomes of the survey play a pivotal role in guiding the project’s development phase, ensuring that the project outputs will effectively address the identified end-user needs.

Distalisation of the upper molars can be used to treat a dental Class II deep bite malocclusion with a flat facial profile. It is a useful procedure when extraction treatment has been refused and providing distalisation is an appropriate solution to the patient’s problem.

To determine the most suitable region of the palate for the insertion of miniscrews.

Metal sub-microparticles (SMPs) and nanoparticles (NPs) presence in food is attributable to increasing pollution from the environment in raw materials and finished products. In the present study, a multifaceted analytical strategy based on Environmental Scanning Electron Microscopy and High-Angle Annular Dark-Field—Scanning Transmission Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDX, HAADF-STEM-EDX) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was proposed for the detection and characterization of metal and metal-containing SMPs and NPs in durum wheat samples, covering a size measurement range from 1 nm to multiple µm. ESEM-EDX and ICP-MS techniques were applied for the assessment of SMP and NP contamination on the surface of wheat grains collected from seven geographical areas characterized by different natural and anthropic conditions, namely Italy, the USA, Australia, Slovakia, Mexico, Austria, and Russia. ICP-MS showed significant differences among the mean concentration levels of metals, with the USA and Italy having the highest level. ESEM-EDX analysis confirmed ICP-MS concentration measurements and measured the highest presence of particles < 0.8 µm in size in samples from Italy, followed by the USA. Less marked differences were observed when particles < 0.15 µm were considered. HAADF-STEM-EDX was applied to a selected number of samples for a preliminary assessment of internal contamination by metal SMPs and NPs, and to expand the measurable particle size range. The multifaceted approach provided similar results for Fe-containing SMPs and NPs. ICP-MS and ESEM-EDX also highlighted the presence of a significant abundance of Ti- and Al-containing particles, while for STEM-EDX, sample preparation artifacts complicated the interpretation. Finally, HAADF-STEM-EDX results provided relevant information about particles in the low nm range, since, by applying this technique, no particles smaller than 50 nm were observed in accordance with ESEM-EDX.