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Sputtering of silicon in a He magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e., He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect, producing increased Ne and Ar incorporations when using He–Ne and He–Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported using ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, He promotes the formation of larger nanobubbles. In the case of Ne, high-resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported, with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubble’s size and composition. The gas (He, Ne and Ar)-charged thin films are proposed as “solid” targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also, their use as targets for nuclear reaction studies is foreseen.

In clinical practice, dose delivery in proton therapy treatment is affected by uncertainties related to the range of the beam in the patient, which requires medical physicists to introduce safety margins on the penetration depth of the beam. Although this ensures an irradiation of the entire clinical target volume with the prescribed dose, these safety margins also lead to the exposure of nearby healthy tissues and a subsequent risk of side effects. Therefore, non-invasive techniques that allow for margin reduction through online monitoring of prompt gammas emitted along the proton tracks in the patient are currently under development. This study provides the proof-of-concept of metal-based nanoparticles, injected into the tumor, as a prompt gamma enhancer, helping in the beam range verification. It identifies the limitations of this application, suggesting a low feasibility in a realistic clinical scenario but opens some avenues for improvement.

Nanoporous solids that stabilize trapped gas nanobubbles open new possibilities to fabricate solid targets for nuclear reactions. A methodology is described based on the magnetron sputtering (MS) technique operated under quasistatic flux conditions to produce such nanocomposites films with 3He contents of up to 16 at.% in an amorphous-silicon matrix. In addition to the characteristic low pressure (3–6 Pa) needed for the gas discharge, the method ensures almost complete reduction of the process gas flow during film fabrication. The method could produce similar materials to those obtained under classical dynamic flux conditions for MS. The drastic reduction (>99.5%) of the gas consumption is fundamental for the fabrication of targets with scarce and expensive gases. Si:3He and W:3He targets are presented together with their microstructural (scanning and transmission electron microscopy, SEM and TEM respectively) and compositional (Ion Beam Analysis, IBA) characterization. The 3He content achieved was over 1 × 1018 at/cm2 for film thicknesses between 1.5 and 3 μm for both Si and W matrices. First experiments to probe the stability of the targets for nuclear reaction studies in inverse kinematics configurations are presented. Keywords: He-3 solid targets, Quasistatic magnetron sputtering, Low gas consumption, Nuclear reactions, Inverse kinematics, Target stability

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

We review the status of the proton charge radius puzzle. Emphasis is given to the various experiments initiated to resolve the conflict between the muonic hydrogen results and the results from scattering and regular hydrogen spectroscopy.

Sputtering of silicon in a He magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e., He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect, producing increased Ne and Ar incorporations when using He–Ne and He–Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported using ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, He promotes the formation of larger nanobubbles. In the case of Ne, high-resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported, with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubble's size and composition. The gas (He, Ne and Ar)-charged thin films are proposed as "solid" targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also, their use as targets for nuclear reaction studies is foreseen. [ABSTRACT FROM AUTHOR]

Abstract Population expansions and contractions out of and into Africa since the early Pleistocene have influenced the course of human evolution. While local- and regional-scale investigations have provided insights into the drivers of Eurasian hominin dispersals, a continental-scale and integrated study of hominin-environmental interactions across Palearctic Eurasia has been lacking. Here, we report high-resolution (up to ∼5-10 kyr sample interval) carbon isotope time series of loess deposits in Central Asia and northwest China, a region dominated by westerly winds, providing unique paleoecological and paleoclimatic records for over ~3.6 Ma. These data, combined with further syntheses of Pleistocene paleontological and archaeological records and spatio-temporal distributions of Eurasian eolian deposits and river terraces, demonstrate a pronounced transformation of landscapes around the Mid-Pleistocene Climate Transition. Increased climate amplitude and aridity fluctuations over this period led to the widespread formation of more open habitats, river terraces, and desert-loess landscapes, pushing hominins to range more widely and find solutions to increasingly challenging environments. Mid-Pleistocene climatic and ecological transitions, and the formation of modern desert and loess landscapes and river networks, emerge as critical events during the dispersal of early hominins in Palearctic Eurasia.

Abstract Automatic analysis of facial expressions has emerged as a prominent research area in the past decade. Facial expressions serve as crucial indicators for understanding human behavior, enabling the identification and assessment of positive and negative emotions. Moreover, facial expressions provide insights into various aspects of mental activities, social connections, and physiological information. Currently, most facial expression detection systems rely on cameras and wearable devices. However, these methods have drawbacks, including privacy concerns, issues with poor lighting and line of sight blockage, difficulties in training with longer video sequences, computational complexities, and disruptions to daily routines. To address these challenges, this study proposes a novel and privacy-preserving human behavior recognition system that utilizes Frequency Modulated Continuous Wave (FMCW) radar combined with Machine Learning (ML) techniques for classifying facial expressions. Specifically, the study focuses on five common facial expressions: Happy, Sad, Fear, Surprise, and Neutral. The recorded data is obtained in the form of a Micro-Doppler signal, and state-of-the-art ML models such as Super Learner, Linear Discriminant Analysis, Random Forest, K-Nearest Neighbor, Long Short-Term Memory, and Logistic Regression are employed to extract relevant features. These extracted features from the radar data are then fed into ML models for classification. The results show a highly promising classification accuracy of 91%. The future applications of the proposed work will lead to advancements in technology, healthcare, security, and communication, thereby improving overall human well-being and societal functioning.

Abstract Creativity is a key skill for the twenty-first century, where the individual and collective imperative to adapt is omnipresent. Yet, it is still unclear how to put creativity theories into practice, which signals a lacuna in our understanding of the pragmatic means by which we get creative. This paper starts from the identification of a number of gaps in the literature. In particular, individual and group creativity are usually treated separately, and the emphasis on the search for novelty seems to overshadow the importance experts give to the disruption of their habitual patterns of behavior. To overcome these gaps, we propose foundations for a unifying framework that takes the perspective of dynamical systems. Specifically, we suggest that de-synchronization, a hallmark of disruption, is an integral part of the creative processes that operate across individual and collective levels of analysis. We show that by conjuring uncertainty, de-synchronized states provide opportunities for creative reorganization. In order to ground this framework, we survey and discuss existing literature, and focus on group improvisation practices (in particular, music and dance improvisation), where partners use the dynamics of their interaction to bring forth a collective performance in real-time. In these practices, disruption by de-synchronization, termed here as ‘problematization of coordination’, is a pragmatic approach used to push the creative process forward. We suggest that this approach might also be relevant in other types of individual and collective creative processes.

Abstract Background The present analysis aimed to assess the mediating role of psychosocial and behavioural factors in socio-economic inequalities in health-related quality of life (HRQoL) among children and adolescents. Methods Cross-sectional data was drawn from the randomly selected SEROCoV-KIDS cohort study in Geneva, Switzerland. Associations of socio-economic conditions (parents’ highest education, household financial situation) with HRQoL, psychosocial (parent–child relationship, school difficulties, friends, extracurricular activities) and behavioural factors (screen time, physical activity, green spaces time, sleep duration), along with associations of psychosocial and behavioural factors with HRQoL, were evaluated with generalized estimating equations. Counterfactual mediation analyses were conducted to test pathways linking socio-economic conditions to HRQoL. Results Of 965 children and 816 adolescents, those with disadvantaged financial circumstances were more likely to have a poor HRQoL (adjusted Odds Ratio [aOR]: 3.80; 95% confidence interval [CI]: 1.96–7.36 and aOR: 3.66; 95%CI: 2.06–6.52, respectively). Psychosocial characteristics mediated 25% (95%CI: 5–70%) and 40% (95%CI: 18–63%) of financial disparities in HRQoL among children and adolescents, respectively. Health behaviours were weakly patterned by socio-economic conditions and did not contribute to financial differences in HRQoL. Conclusions These findings provide empirical evidence for mechanisms explaining socio-economic disparities in child HRQoL and could inform interventions aimed to tackle health inequalities.

Abstract This editorial outlines the outcome of an interdisciplinary session on collective sense-making through dance improvisation, which took place during the ‘Neural and Social Bases of Creative Movement’ workshop. We argue that joint improvisation practices place the scientist in a privileged position to reveal the nature of cognitive and creative behaviors.

Abstract Background Solving the structure of mRNA transcripts is a major challenge for both research and molecular diagnostic purposes. Current approaches based on short-read RNA sequencing and RT-PCR techniques cannot fully explore the complexity of transcript structure. The emergence of third-generation long-read sequencing addresses this problem by solving this sequence directly. However, genes with low expression levels are difficult to study with the whole transcriptome sequencing approach. To fix this technical limitation, we propose a novel method to capture transcripts of a gene panel using a targeted enrichment approach suitable for Pacific Biosciences and Oxford Nanopore Technologies platforms. Results We designed a set of probes to capture transcripts of a panel of genes involved in hereditary breast and ovarian cancer syndrome. We present SOSTAR (iSofOrmS annoTAtoR), a versatile pipeline to assemble, quantify and annotate isoforms from long read sequencing using a new tool specially designed for this application. The significant enrichment of transcripts by our capture protocol, together with the SOSTAR annotation, allowed the identification of 1,231 unique transcripts within the gene panel from the eight patients sequenced. The structure of these transcripts was annotated with a resolution of one base relative to a reference transcript. All major alternative splicing events of the BRCA1 and BRCA2 genes described in the literature were found. Complex splicing events such as pseudoexons were correctly annotated. SOSTAR enabled the identification of abnormal transcripts in the positive controls. In addition, a case of unexplained inheritance in a family with a history of breast and ovarian cancer was solved by identifying an SVA retrotransposon in intron 13 of the BRCA1 gene. Conclusions We have validated a new protocol for the enrichment of transcripts of interest using probes adapted to the ONT and PacBio platforms. This protocol allows a complete description of the alternative structures of transcripts, the estimation of their expression and the identification of aberrant transcripts in a single experiment. This proof-of-concept opens new possibilities for RNA structure exploration in both research and molecular diagnostics.

Abstract Background To describe French general practioners’ (GPs) adaptation strategies to ensure follow-up care of nursing home patients during the first wave of COVID-19 (May 2020) and to identify factors associated with each strategy. Methods A national cross-sectional study was conducted with online questionnaires in May 2020 among GPs practicing in France (metropolitan and overseas) and usually providing nursing home visits before pandemic. The outcome was defined as the GPs’ adaptation strategies for managing nursing home patients and was categorized into four groups: Maintenance of Nursing Home Visits NHV (reference), Stopping NHV, Numeric adaptation (teleconsultations only), Mixed adaptation (NHV and teleconsultations). The probability of adaptation strategies was analyzed by multilevel logistic models in which the GPs represented level 1 and the counties level 2. We applied three random-intercept multilevel logistic models with the county of GP’s practice as random effect. Results This analysis included 2,146 responses by GPs coming from 98 French counties. Overall, 40.4% of GPs maintained NHV, while other strategies were: Stopping visits (24.1%), Numeric adaptation (15.4%), Mixed adaptation (20.1%). Several individual (age, training GP, perceived status of being at high risk of severe COVID, compliance with temporary delegation of the patient’s management) and territorial factors (excess mortality rate due to COVID-19, GPs’ density, proportion of over-75s, presence of reinforcement measures for nursing home patients) were identified as associated with each strategy. Conclusions This study highlights a rapid adaptation of general practice to keep supporting nursing home patients. Heterogeneity of adaptation strategies could reflect both the lack of national guidelines and the heterogeneity among GPs’ usual practices. Policymakers should take actions at a territorial level (subnational) to strengthen support to nursing home patients considering adaptations to the local context of the pandemic outbreak and perspective of local actors.